Merge branch 'main' into v2

.github/workflows/auto-i18n.yml

@@ -77,7 +77,7 @@ jobs:
         with:
           token: ${{ secrets.GITHUB_TOKEN }} # Use the built-in GITHUB_TOKEN for bot actions
           commit-message: "feat(bot): Weekly automated script run"
-          title: "🤖 Weekly Automated Update: ${{ env.CURRENT_DATE }}"
+          title: "🤖 Weekly Auto I18N Sync: ${{ env.CURRENT_DATE }}"
           body: |
             This PR includes changes generated by the weekly auto i18n.
             Review the changes before merging.

.yarn/patches/@ai-sdk-google-npm-2.0.36-6f3cc06026.patch

@@ -1,152 +0,0 @@
-diff --git a/dist/index.js b/dist/index.js
-index c2ef089c42e13a8ee4a833899a415564130e5d79..75efa7baafb0f019fb44dd50dec1641eee8879e7 100644
---- a/dist/index.js
-+++ b/dist/index.js
-@@ -471,7 +471,7 @@ function convertToGoogleGenerativeAIMessages(prompt, options) {
- 
- // src/get-model-path.ts
- function getModelPath(modelId) {
--  return modelId.includes("/") ? modelId : `models/${modelId}`;
-+  return modelId.includes("models/") ? modelId : `models/${modelId}`;
- }
- 
- // src/google-generative-ai-options.ts
-diff --git a/dist/index.mjs b/dist/index.mjs
-index d75c0cc13c41192408c1f3f2d29d76a7bffa6268..ada730b8cb97d9b7d4cb32883a1d1ff416404d9b 100644
---- a/dist/index.mjs
-+++ b/dist/index.mjs
-@@ -477,7 +477,7 @@ function convertToGoogleGenerativeAIMessages(prompt, options) {
- 
- // src/get-model-path.ts
- function getModelPath(modelId) {
--  return modelId.includes("/") ? modelId : `models/${modelId}`;
-+  return modelId.includes("models/") ? modelId : `models/${modelId}`;
- }
- 
- // src/google-generative-ai-options.ts
-diff --git a/dist/internal/index.js b/dist/internal/index.js
-index 277cac8dc734bea2fb4f3e9a225986b402b24f48..bb704cd79e602eb8b0cee1889e42497d59ccdb7a 100644
---- a/dist/internal/index.js
-+++ b/dist/internal/index.js
-@@ -432,7 +432,15 @@ function prepareTools({
-   var _a;
-   tools = (tools == null ? void 0 : tools.length) ? tools : void 0;
-   const toolWarnings = [];
--  const isGemini2 = modelId.includes("gemini-2");
-+  // These changes could be safely removed when @ai-sdk/google v3 released.
-+  const isLatest = (
-+    [
-+      'gemini-flash-latest',
-+      'gemini-flash-lite-latest',
-+      'gemini-pro-latest',
-+    ]
-+  ).some(id => id === modelId);
-+  const isGemini2OrNewer = modelId.includes("gemini-2") || modelId.includes("gemini-3") || isLatest;
-   const supportsDynamicRetrieval = modelId.includes("gemini-1.5-flash") && !modelId.includes("-8b");
-   const supportsFileSearch = modelId.includes("gemini-2.5");
-   if (tools == null) {
-@@ -458,7 +466,7 @@ function prepareTools({
-     providerDefinedTools.forEach((tool) => {
-       switch (tool.id) {
-         case "google.google_search":
--          if (isGemini2) {
-+          if (isGemini2OrNewer) {
-             googleTools2.push({ googleSearch: {} });
-           } else if (supportsDynamicRetrieval) {
-             googleTools2.push({
-@@ -474,7 +482,7 @@ function prepareTools({
-           }
-           break;
-         case "google.url_context":
--          if (isGemini2) {
-+          if (isGemini2OrNewer) {
-             googleTools2.push({ urlContext: {} });
-           } else {
-             toolWarnings.push({
-@@ -485,7 +493,7 @@ function prepareTools({
-           }
-           break;
-         case "google.code_execution":
--          if (isGemini2) {
-+          if (isGemini2OrNewer) {
-             googleTools2.push({ codeExecution: {} });
-           } else {
-             toolWarnings.push({
-@@ -507,7 +515,7 @@ function prepareTools({
-           }
-           break;
-         case "google.vertex_rag_store":
--          if (isGemini2) {
-+          if (isGemini2OrNewer) {
-             googleTools2.push({
-               retrieval: {
-                 vertex_rag_store: {
-diff --git a/dist/internal/index.mjs b/dist/internal/index.mjs
-index 03b7cc591be9b58bcc2e775a96740d9f98862a10..347d2c12e1cee79f0f8bb258f3844fb0522a6485 100644
---- a/dist/internal/index.mjs
-+++ b/dist/internal/index.mjs
-@@ -424,7 +424,15 @@ function prepareTools({
-   var _a;
-   tools = (tools == null ? void 0 : tools.length) ? tools : void 0;
-   const toolWarnings = [];
--  const isGemini2 = modelId.includes("gemini-2");
-+  // These changes could be safely removed when @ai-sdk/google v3 released.
-+  const isLatest = (
-+    [
-+      'gemini-flash-latest',
-+      'gemini-flash-lite-latest',
-+      'gemini-pro-latest',
-+    ]
-+  ).some(id => id === modelId);
-+  const isGemini2OrNewer = modelId.includes("gemini-2") || modelId.includes("gemini-3") || isLatest;
-   const supportsDynamicRetrieval = modelId.includes("gemini-1.5-flash") && !modelId.includes("-8b");
-   const supportsFileSearch = modelId.includes("gemini-2.5");
-   if (tools == null) {
-@@ -450,7 +458,7 @@ function prepareTools({
-     providerDefinedTools.forEach((tool) => {
-       switch (tool.id) {
-         case "google.google_search":
--          if (isGemini2) {
-+          if (isGemini2OrNewer) {
-             googleTools2.push({ googleSearch: {} });
-           } else if (supportsDynamicRetrieval) {
-             googleTools2.push({
-@@ -466,7 +474,7 @@ function prepareTools({
-           }
-           break;
-         case "google.url_context":
--          if (isGemini2) {
-+          if (isGemini2OrNewer) {
-             googleTools2.push({ urlContext: {} });
-           } else {
-             toolWarnings.push({
-@@ -477,7 +485,7 @@ function prepareTools({
-           }
-           break;
-         case "google.code_execution":
--          if (isGemini2) {
-+          if (isGemini2OrNewer) {
-             googleTools2.push({ codeExecution: {} });
-           } else {
-             toolWarnings.push({
-@@ -499,7 +507,7 @@ function prepareTools({
-           }
-           break;
-         case "google.vertex_rag_store":
--          if (isGemini2) {
-+          if (isGemini2OrNewer) {
-             googleTools2.push({
-               retrieval: {
-                 vertex_rag_store: {
-@@ -1434,9 +1442,7 @@ var googleTools = {
-   vertexRagStore
- };
- export {
--  GoogleGenerativeAILanguageModel,
-   getGroundingMetadataSchema,
--  getUrlContextMetadataSchema,
--  googleTools
-+  getUrlContextMetadataSchema, GoogleGenerativeAILanguageModel, googleTools
- };
- //# sourceMappingURL=index.mjs.map
-\ No newline at end of file

.yarn/patches/@ai-sdk-google-npm-2.0.40-47e0eeee83.patch

@@ -0,0 +1,26 @@
+diff --git a/dist/index.js b/dist/index.js
+index dc7b74ba55337c491cdf1ab3e39ca68cc4187884..ace8c90591288e42c2957e93c9bf7984f1b22444 100644
+--- a/dist/index.js
++++ b/dist/index.js
+@@ -472,7 +472,7 @@ function convertToGoogleGenerativeAIMessages(prompt, options) {
+ 
+ // src/get-model-path.ts
+ function getModelPath(modelId) {
+-  return modelId.includes("/") ? modelId : `models/${modelId}`;
++  return modelId.includes("models/") ? modelId : `models/${modelId}`;
+ }
+ 
+ // src/google-generative-ai-options.ts
+diff --git a/dist/index.mjs b/dist/index.mjs
+index 8390439c38cb7eaeb52080862cd6f4c58509e67c..a7647f2e11700dff7e1c8d4ae8f99d3637010733 100644
+--- a/dist/index.mjs
++++ b/dist/index.mjs
+@@ -478,7 +478,7 @@ function convertToGoogleGenerativeAIMessages(prompt, options) {
+ 
+ // src/get-model-path.ts
+ function getModelPath(modelId) {
+-  return modelId.includes("/") ? modelId : `models/${modelId}`;
++  return modelId.includes("models/") ? modelId : `models/${modelId}`;
+ }
+ 
+ // src/google-generative-ai-options.ts

.yarn/patches/@ai-sdk-huggingface-npm-0.0.8-d4d0aaac93.patch

@@ -1,131 +0,0 @@
-diff --git a/dist/index.mjs b/dist/index.mjs
-index b3f018730a93639aad7c203f15fb1aeb766c73f4..ade2a43d66e9184799d072153df61ef7be4ea110 100644
---- a/dist/index.mjs
-+++ b/dist/index.mjs
-@@ -296,7 +296,14 @@ var HuggingFaceResponsesLanguageModel = class {
-       metadata: huggingfaceOptions == null ? void 0 : huggingfaceOptions.metadata,
-       instructions: huggingfaceOptions == null ? void 0 : huggingfaceOptions.instructions,
-       ...preparedTools && { tools: preparedTools },
--      ...preparedToolChoice && { tool_choice: preparedToolChoice }
-+      ...preparedToolChoice && { tool_choice: preparedToolChoice },
-+      ...(huggingfaceOptions?.reasoningEffort != null && {
-+        reasoning: {
-+          ...(huggingfaceOptions?.reasoningEffort != null && {
-+            effort: huggingfaceOptions.reasoningEffort,
-+          }),
-+        },
-+      }),
-     };
-     return { args: baseArgs, warnings };
-   }
-@@ -365,6 +372,20 @@ var HuggingFaceResponsesLanguageModel = class {
-           }
-           break;
-         }
-+        case 'reasoning': {
-+          for (const contentPart of part.content) {
-+            content.push({
-+              type: 'reasoning',
-+              text: contentPart.text,
-+              providerMetadata: {
-+                huggingface: {
-+                  itemId: part.id,
-+                },
-+              },
-+            });
-+          }
-+          break;
-+        }
-         case "mcp_call": {
-           content.push({
-             type: "tool-call",
-@@ -519,6 +540,11 @@ var HuggingFaceResponsesLanguageModel = class {
-                   id: value.item.call_id,
-                   toolName: value.item.name
-                 });
-+              } else if (value.item.type === 'reasoning') {
-+                controller.enqueue({
-+                  type: 'reasoning-start',
-+                  id: value.item.id,
-+                });
-               }
-               return;
-             }
-@@ -570,6 +596,22 @@ var HuggingFaceResponsesLanguageModel = class {
-               });
-               return;
-             }
-+            if (isReasoningDeltaChunk(value)) {
-+              controller.enqueue({
-+                type: 'reasoning-delta',
-+                id: value.item_id,
-+                delta: value.delta,
-+              });
-+              return;
-+            }
-+
-+            if (isReasoningEndChunk(value)) {
-+              controller.enqueue({
-+                type: 'reasoning-end',
-+                id: value.item_id,
-+              });
-+              return;
-+            }
-           },
-           flush(controller) {
-             controller.enqueue({
-@@ -593,7 +635,8 @@ var HuggingFaceResponsesLanguageModel = class {
- var huggingfaceResponsesProviderOptionsSchema = z2.object({
-   metadata: z2.record(z2.string(), z2.string()).optional(),
-   instructions: z2.string().optional(),
--  strictJsonSchema: z2.boolean().optional()
-+  strictJsonSchema: z2.boolean().optional(),
-+  reasoningEffort: z2.string().optional(),
- });
- var huggingfaceResponsesResponseSchema = z2.object({
-   id: z2.string(),
-@@ -727,12 +770,31 @@ var responseCreatedChunkSchema = z2.object({
-     model: z2.string()
-   })
- });
-+var reasoningTextDeltaChunkSchema = z2.object({
-+  type: z2.literal('response.reasoning_text.delta'),
-+  item_id: z2.string(),
-+  output_index: z2.number(),
-+  content_index: z2.number(),
-+  delta: z2.string(),
-+  sequence_number: z2.number(),
-+});
-+
-+var reasoningTextEndChunkSchema = z2.object({
-+  type: z2.literal('response.reasoning_text.done'),
-+  item_id: z2.string(),
-+  output_index: z2.number(),
-+  content_index: z2.number(),
-+  text: z2.string(),
-+  sequence_number: z2.number(),
-+});
- var huggingfaceResponsesChunkSchema = z2.union([
-   responseOutputItemAddedSchema,
-   responseOutputItemDoneSchema,
-   textDeltaChunkSchema,
-   responseCompletedChunkSchema,
-   responseCreatedChunkSchema,
-+  reasoningTextDeltaChunkSchema,
-+  reasoningTextEndChunkSchema,
-   z2.object({ type: z2.string() }).loose()
-   // fallback for unknown chunks
- ]);
-@@ -751,6 +813,12 @@ function isResponseCompletedChunk(chunk) {
- function isResponseCreatedChunk(chunk) {
-   return chunk.type === "response.created";
- }
-+function isReasoningDeltaChunk(chunk) {
-+  return chunk.type === 'response.reasoning_text.delta';
-+}
-+function isReasoningEndChunk(chunk) {
-+  return chunk.type === 'response.reasoning_text.done';
-+}
- 
- // src/huggingface-provider.ts
- function createHuggingFace(options = {}) {

.yarn/patches/@ai-sdk-openai-compatible-npm-1.0.27-06f74278cf.patch

@@ -0,0 +1,140 @@
+diff --git a/dist/index.js b/dist/index.js
+index 73045a7d38faafdc7f7d2cd79d7ff0e2b031056b..8d948c9ac4ea4b474db9ef3c5491961e7fcf9a07 100644
+--- a/dist/index.js
++++ b/dist/index.js
+@@ -421,6 +421,17 @@ var OpenAICompatibleChatLanguageModel = class {
+         text: reasoning
+       });
+     }
++    if (choice.message.images) {
++      for (const image of choice.message.images) {
++        const match1 = image.image_url.url.match(/^data:([^;]+)/)
++        const match2 = image.image_url.url.match(/^data:[^;]*;base64,(.+)$/);
++        content.push({
++          type: 'file',
++          mediaType: match1 ? (match1[1] ?? 'image/jpeg') : 'image/jpeg',
++          data: match2 ? match2[1] : image.image_url.url,
++        });
++      }
++    }
+     if (choice.message.tool_calls != null) {
+       for (const toolCall of choice.message.tool_calls) {
+         content.push({
+@@ -598,6 +609,17 @@ var OpenAICompatibleChatLanguageModel = class {
+                 delta: delta.content
+               });
+             }
++            if (delta.images) {
++              for (const image of delta.images) {
++                const match1 = image.image_url.url.match(/^data:([^;]+)/)
++                const match2 = image.image_url.url.match(/^data:[^;]*;base64,(.+)$/);
++                controller.enqueue({
++                  type: 'file',
++                  mediaType: match1 ? (match1[1] ?? 'image/jpeg') : 'image/jpeg',
++                  data: match2 ? match2[1] : image.image_url.url,
++                });
++              }
++            }
+             if (delta.tool_calls != null) {
+               for (const toolCallDelta of delta.tool_calls) {
+                 const index = toolCallDelta.index;
+@@ -765,6 +787,14 @@ var OpenAICompatibleChatResponseSchema = import_v43.z.object({
+               arguments: import_v43.z.string()
+             })
+           })
++        ).nullish(),
++        images: import_v43.z.array(
++          import_v43.z.object({
++            type: import_v43.z.literal('image_url'),
++            image_url: import_v43.z.object({
++              url: import_v43.z.string(),
++            })
++          })
+         ).nullish()
+       }),
+       finish_reason: import_v43.z.string().nullish()
+@@ -795,6 +825,14 @@ var createOpenAICompatibleChatChunkSchema = (errorSchema) => import_v43.z.union(
+                 arguments: import_v43.z.string().nullish()
+               })
+             })
++          ).nullish(),
++          images: import_v43.z.array(
++            import_v43.z.object({
++              type: import_v43.z.literal('image_url'),
++              image_url: import_v43.z.object({
++                url: import_v43.z.string(),
++              })
++            })
+           ).nullish()
+         }).nullish(),
+         finish_reason: import_v43.z.string().nullish()
+diff --git a/dist/index.mjs b/dist/index.mjs
+index 1c2b9560bbfbfe10cb01af080aeeed4ff59db29c..2c8ddc4fc9bfc5e7e06cfca105d197a08864c427 100644
+--- a/dist/index.mjs
++++ b/dist/index.mjs
+@@ -405,6 +405,17 @@ var OpenAICompatibleChatLanguageModel = class {
+         text: reasoning
+       });
+     }
++    if (choice.message.images) {
++      for (const image of choice.message.images) {
++        const match1 = image.image_url.url.match(/^data:([^;]+)/)
++        const match2 = image.image_url.url.match(/^data:[^;]*;base64,(.+)$/);
++        content.push({
++          type: 'file',
++          mediaType: match1 ? (match1[1] ?? 'image/jpeg') : 'image/jpeg',
++          data: match2 ? match2[1] : image.image_url.url,
++        });
++      }
++    }
+     if (choice.message.tool_calls != null) {
+       for (const toolCall of choice.message.tool_calls) {
+         content.push({
+@@ -582,6 +593,17 @@ var OpenAICompatibleChatLanguageModel = class {
+                 delta: delta.content
+               });
+             }
++            if (delta.images) {
++              for (const image of delta.images) {
++                const match1 = image.image_url.url.match(/^data:([^;]+)/)
++                const match2 = image.image_url.url.match(/^data:[^;]*;base64,(.+)$/);
++                controller.enqueue({
++                  type: 'file',
++                  mediaType: match1 ? (match1[1] ?? 'image/jpeg') : 'image/jpeg',
++                  data: match2 ? match2[1] : image.image_url.url,
++                });
++              }
++            }
+             if (delta.tool_calls != null) {
+               for (const toolCallDelta of delta.tool_calls) {
+                 const index = toolCallDelta.index;
+@@ -749,6 +771,14 @@ var OpenAICompatibleChatResponseSchema = z3.object({
+               arguments: z3.string()
+             })
+           })
++        ).nullish(),
++        images: z3.array(
++          z3.object({
++            type: z3.literal('image_url'),
++            image_url: z3.object({
++              url: z3.string(),
++            })
++          })
+         ).nullish()
+       }),
+       finish_reason: z3.string().nullish()
+@@ -779,6 +809,14 @@ var createOpenAICompatibleChatChunkSchema = (errorSchema) => z3.union([
+                 arguments: z3.string().nullish()
+               })
+             })
++          ).nullish(),
++          images: z3.array(
++            z3.object({
++              type: z3.literal('image_url'),
++              image_url: z3.object({
++                url: z3.string(),
++              })
++            })
+           ).nullish()
+         }).nullish(),
+         finish_reason: z3.string().nullish()

.yarn/patches/@ai-sdk-openai-npm-2.0.71-a88ef00525.patch

@@ -1,5 +1,5 @@
 diff --git a/dist/index.js b/dist/index.js
-index 992c85ac6656e51c3471af741583533c5a7bf79f..83c05952a07aebb95fc6c62f9ddb8aa96b52ac0d 100644
+index 7481f3b3511078068d87d03855b568b20bb86971..8ac5ec28d2f7ad1b3b0d3f8da945c75674e59637 100644
 --- a/dist/index.js
 +++ b/dist/index.js
 @@ -274,6 +274,7 @@ var openaiChatResponseSchema = (0, import_provider_utils3.lazyValidator)(
@@ -18,7 +18,7 @@ index 992c85ac6656e51c3471af741583533c5a7bf79f..83c05952a07aebb95fc6c62f9ddb8aa9
                tool_calls: import_v42.z.array(
                  import_v42.z.object({
                    index: import_v42.z.number(),
-@@ -785,6 +787,13 @@ var OpenAIChatLanguageModel = class {
+@@ -795,6 +797,13 @@ var OpenAIChatLanguageModel = class {
      if (text != null && text.length > 0) {
        content.push({ type: "text", text });
      }
@@ -32,7 +32,7 @@ index 992c85ac6656e51c3471af741583533c5a7bf79f..83c05952a07aebb95fc6c62f9ddb8aa9
      for (const toolCall of (_a = choice.message.tool_calls) != null ? _a : []) {
        content.push({
          type: "tool-call",
-@@ -866,6 +875,7 @@ var OpenAIChatLanguageModel = class {
+@@ -876,6 +885,7 @@ var OpenAIChatLanguageModel = class {
      };
      let metadataExtracted = false;
      let isActiveText = false;
@@ -40,7 +40,7 @@ index 992c85ac6656e51c3471af741583533c5a7bf79f..83c05952a07aebb95fc6c62f9ddb8aa9
      const providerMetadata = { openai: {} };
      return {
        stream: response.pipeThrough(
-@@ -923,6 +933,21 @@ var OpenAIChatLanguageModel = class {
+@@ -933,6 +943,21 @@ var OpenAIChatLanguageModel = class {
                return;
              }
              const delta = choice.delta;
@@ -62,7 +62,7 @@ index 992c85ac6656e51c3471af741583533c5a7bf79f..83c05952a07aebb95fc6c62f9ddb8aa9
              if (delta.content != null) {
                if (!isActiveText) {
                  controller.enqueue({ type: "text-start", id: "0" });
-@@ -1035,6 +1060,9 @@ var OpenAIChatLanguageModel = class {
+@@ -1045,6 +1070,9 @@ var OpenAIChatLanguageModel = class {
              }
            },
            flush(controller) {

biome.jsonc

@@ -14,7 +14,7 @@
       }
     },
     "enabled": true,
-    "includes": ["**/*.json", "!*.json", "!**/package.json"]
+    "includes": ["**/*.json", "!*.json", "!**/package.json", "!coverage/**"]
   },
   "css": {
     "formatter": {
@@ -23,7 +23,7 @@
   },
   "files": {
     "ignoreUnknown": false,
-    "includes": ["**", "!**/.claude/**"],
+    "includes": ["**", "!**/.claude/**", "!**/.vscode/**"],
     "maxSize": 2097152
   },
   "formatter": {

electron-builder.yml

@@ -135,58 +135,66 @@ artifactBuildCompleted: scripts/artifact-build-completed.js
 releaseInfo:
   releaseNotes: |
     <!--LANG:en-->
-    What's New in v1.7.0-rc.1
+    What's New in v1.7.0-rc.2
-
-    🎉 MAJOR NEW FEATURE: AI Agents
-    - Create and manage custom AI agents with specialized tools and permissions
-    - Dedicated agent sessions with persistent SQLite storage, separate from regular chats
-    - Real-time tool approval system - review and approve agent actions dynamically
-    - MCP (Model Context Protocol) integration for connecting external tools
-    - Slash commands support for quick agent interactions
-    - OpenAI-compatible REST API for agent access
 
     ✨ New Features:
-    - AI Providers: Added support for Hugging Face, Mistral, Perplexity, and SophNet
+    - AI Models: Added support for Gemini 3, Gemini 3 Pro with image preview, and GPT-5.1
-    - Knowledge Base: OpenMinerU document preprocessor, full-text search in notes, enhanced tool selection
+    - Import: ChatGPT conversation import feature
-    - Image & OCR: Intel OVMS painting provider and Intel OpenVINO (NPU) OCR support
+    - Agent: Git Bash detection and requirement check for Windows agents
-    - MCP Management: Redesigned interface with dual-column layout for easier management
+    - Search: Native language emoji search with CLDR data format
-    - Languages: Added German language support
+    - Provider: Endpoint type support for cherryin provider
-
+    - Debug: Local crash mini dump file for better diagnostics
-    ⚡ Improvements:
-    - Upgraded to Electron 38.7.0
-    - Enhanced system shutdown handling and automatic update checks
-    - Improved proxy bypass rules
 
     🐛 Important Bug Fixes:
-    - Fixed streaming response issues across multiple AI providers
+    - Error Handling: Improved error display in AiSdkToChunkAdapter
-    - Fixed session list scrolling problems
+    - Database: Optimized DatabaseManager and fixed libsql crash issues
-    - Fixed knowledge base deletion errors
+    - Memory: Fixed EventEmitter memory leak in useApiServer hook
+    - Messages: Fixed adjacent user messages appearing when assistant message contains error only
+    - Tools: Fixed missing execution state for approved tool permissions
+    - File Processing: Fixed "no such file" error for non-English filenames in open-mineru
+    - PDF: Fixed mineru PDF validation and 403 errors
+    - Images: Fixed base64 image save issues
+    - Search: Fixed URL context and web search capability
+    - Models: Added verbosity parameter support for GPT-5 models
+    - UI: Improved todo tool status icon visibility and colors
+    - Providers: Fixed api-host for vercel ai-gateway and gitcode update config
+
+    ⚡ Improvements:
+    - SDK: Updated Google and OpenAI SDKs with new features
+    - UI: Simplified knowledge base creation modal and agent creation form
+    - Tools: Replaced renderToolContent function with ToolContent component
+    - Architecture: Namespace tool call IDs with session ID to prevent conflicts
+    - Config: AI SDK configuration refactoring
 
     <!--LANG:zh-CN-->
-    v1.7.0-rc.1 新特性
+    v1.7.0-rc.2 新特性
-
-    🎉 重大更新：AI Agent 智能体系统
-    - 创建和管理专属 AI Agent，配置专用工具和权限
-    - 独立的 Agent 会话，使用 SQLite 持久化存储，与普通聊天分离
-    - 实时工具审批系统 - 动态审查和批准 Agent 操作
-    - MCP（模型上下文协议）集成，连接外部工具
-    - 支持斜杠命令快速交互
-    - 兼容 OpenAI 的 REST API 访问
 
     ✨ 新功能:
-    - AI 提供商：新增 Hugging Face、Mistral、Perplexity 和 SophNet 支持
+    - AI 模型：新增 Gemini 3、Gemini 3 Pro 图像预览支持，以及 GPT-5.1
-    - 知识库：OpenMinerU 文档预处理器、笔记全文搜索、增强的工具选择
+    - 导入：ChatGPT 对话导入功能
-    - 图像与 OCR：Intel OVMS 绘图提供商和 Intel OpenVINO (NPU) OCR 支持
+    - Agent：Windows Agent 的 Git Bash 检测和要求检查
-    - MCP 管理：重构管理界面，采用双列布局，更加方便管理
+    - 搜索：支持本地语言 emoji 搜索（CLDR 数据格式）
-    - 语言：新增德语支持
+    - 提供商：cherryin provider 的端点类型支持
-
+    - 调试：启用本地崩溃 mini dump 文件，方便诊断
-    ⚡ 改进:
-    - 升级到 Electron 38.7.0
-    - 增强的系统关机处理和自动更新检查
-    - 改进的代理绕过规则
 
     🐛 重要修复:
-    - 修复多个 AI 提供商的流式响应问题
+    - 错误处理：改进 AiSdkToChunkAdapter 的错误显示
-    - 修复会话列表滚动问题
+    - 数据库：优化 DatabaseManager 并修复 libsql 崩溃问题
-    - 修复知识库删除错误
+    - 内存：修复 useApiServer hook 中的 EventEmitter 内存泄漏
+    - 消息：修复当助手消息仅包含错误时相邻用户消息出现的问题
+    - 工具：修复批准工具权限缺少执行状态的问题
+    - 文件处理：修复 open-mineru 处理非英文文件名时的"无此文件"错误
+    - PDF：修复 mineru PDF 验证和 403 错误
+    - 图片：修复 base64 图片保存问题
+    - 搜索：修复 URL 上下文和网络搜索功能
+    - 模型：为 GPT-5 模型添加 verbosity 参数支持
+    - UI：改进 todo 工具状态图标可见性和颜色
+    - 提供商：修复 vercel ai-gateway 和 gitcode 更新配置的 api-host
+
+    ⚡ 改进:
+    - SDK：更新 Google 和 OpenAI SDK，新增功能和修复
+    - UI：简化知识库创建模态框和 agent 创建表单
+    - 工具：用 ToolContent 组件替换 renderToolContent 函数，提升可读性
+    - 架构：用会话 ID 命名工具调用 ID 以防止冲突
+    - 配置：AI SDK 配置重构
     <!--LANG:END-->

package.json

@@ -113,16 +113,17 @@
     "@agentic/exa": "^7.3.3",
     "@agentic/searxng": "^7.3.3",
     "@agentic/tavily": "^7.3.3",
-    "@ai-sdk/amazon-bedrock": "^3.0.53",
+    "@ai-sdk/amazon-bedrock": "^3.0.56",
-    "@ai-sdk/anthropic": "^2.0.44",
+    "@ai-sdk/anthropic": "^2.0.45",
     "@ai-sdk/cerebras": "^1.0.31",
-    "@ai-sdk/gateway": "^2.0.9",
+    "@ai-sdk/gateway": "^2.0.13",
-    "@ai-sdk/google": "patch:@ai-sdk/google@npm%3A2.0.36#~/.yarn/patches/@ai-sdk-google-npm-2.0.36-6f3cc06026.patch",
+    "@ai-sdk/google": "patch:@ai-sdk/google@npm%3A2.0.40#~/.yarn/patches/@ai-sdk-google-npm-2.0.40-47e0eeee83.patch",
-    "@ai-sdk/google-vertex": "^3.0.68",
+    "@ai-sdk/google-vertex": "^3.0.72",
-    "@ai-sdk/huggingface": "patch:@ai-sdk/huggingface@npm%3A0.0.8#~/.yarn/patches/@ai-sdk-huggingface-npm-0.0.8-d4d0aaac93.patch",
+    "@ai-sdk/huggingface": "^0.0.10",
-    "@ai-sdk/mistral": "^2.0.23",
+    "@ai-sdk/mistral": "^2.0.24",
-    "@ai-sdk/openai": "patch:@ai-sdk/openai@npm%3A2.0.64#~/.yarn/patches/@ai-sdk-openai-npm-2.0.64-48f99f5bf3.patch",
+    "@ai-sdk/openai": "patch:@ai-sdk/openai@npm%3A2.0.71#~/.yarn/patches/@ai-sdk-openai-npm-2.0.71-a88ef00525.patch",
-    "@ai-sdk/perplexity": "^2.0.17",
+    "@ai-sdk/perplexity": "^2.0.20",
+    "@ai-sdk/test-server": "^0.0.1",
     "@ant-design/v5-patch-for-react-19": "^1.0.3",
     "@anthropic-ai/sdk": "^0.41.0",
     "@anthropic-ai/vertex-sdk": "patch:@anthropic-ai/vertex-sdk@npm%3A0.11.4#~/.yarn/patches/@anthropic-ai-vertex-sdk-npm-0.11.4-c19cb41edb.patch",
@@ -167,7 +168,7 @@
     "@modelcontextprotocol/sdk": "^1.17.5",
     "@mozilla/readability": "^0.6.0",
     "@notionhq/client": "^2.2.15",
-    "@openrouter/ai-sdk-provider": "^1.2.0",
+    "@openrouter/ai-sdk-provider": "^1.2.5",
     "@opentelemetry/api": "^1.9.0",
     "@opentelemetry/core": "2.0.0",
     "@opentelemetry/exporter-trace-otlp-http": "^0.200.0",
@@ -244,7 +245,7 @@
     "@viz-js/lang-dot": "^1.0.5",
     "@viz-js/viz": "^3.14.0",
     "@xyflow/react": "^12.4.4",
-    "ai": "^5.0.90",
+    "ai": "^5.0.98",
     "antd": "patch:antd@npm%3A5.27.0#~/.yarn/patches/antd-npm-5.27.0-aa91c36546.patch",
     "archiver": "^7.0.1",
     "async-mutex": "^0.5.0",
@@ -417,8 +418,11 @@
     "@langchain/openai@npm:^0.3.16": "patch:@langchain/openai@npm%3A1.0.0#~/.yarn/patches/@langchain-openai-npm-1.0.0-474d0ad9d4.patch",
     "@langchain/openai@npm:>=0.2.0 <0.7.0": "patch:@langchain/openai@npm%3A1.0.0#~/.yarn/patches/@langchain-openai-npm-1.0.0-474d0ad9d4.patch",
     "@ai-sdk/openai@npm:2.0.64": "patch:@ai-sdk/openai@npm%3A2.0.64#~/.yarn/patches/@ai-sdk-openai-npm-2.0.64-48f99f5bf3.patch",
-    "@ai-sdk/openai@npm:^2.0.42": "patch:@ai-sdk/openai@npm%3A2.0.64#~/.yarn/patches/@ai-sdk-openai-npm-2.0.64-48f99f5bf3.patch",
+    "@ai-sdk/openai@npm:^2.0.42": "patch:@ai-sdk/openai@npm%3A2.0.71#~/.yarn/patches/@ai-sdk-openai-npm-2.0.71-a88ef00525.patch",
-    "@ai-sdk/google@npm:2.0.36": "patch:@ai-sdk/google@npm%3A2.0.36#~/.yarn/patches/@ai-sdk-google-npm-2.0.36-6f3cc06026.patch"
+    "@ai-sdk/google@npm:2.0.40": "patch:@ai-sdk/google@npm%3A2.0.40#~/.yarn/patches/@ai-sdk-google-npm-2.0.40-47e0eeee83.patch",
+    "@ai-sdk/openai@npm:2.0.71": "patch:@ai-sdk/openai@npm%3A2.0.71#~/.yarn/patches/@ai-sdk-openai-npm-2.0.71-a88ef00525.patch",
+    "@ai-sdk/openai-compatible@npm:1.0.27": "patch:@ai-sdk/openai-compatible@npm%3A1.0.27#~/.yarn/patches/@ai-sdk-openai-compatible-npm-1.0.27-06f74278cf.patch",
+    "@ai-sdk/openai-compatible@npm:^1.0.19": "patch:@ai-sdk/openai-compatible@npm%3A1.0.27#~/.yarn/patches/@ai-sdk-openai-compatible-npm-1.0.27-06f74278cf.patch"
   },
   "packageManager": "yarn@4.9.1",
   "lint-staged": {

packages/ai-sdk-provider/package.json

@@ -42,7 +42,7 @@
   },
   "dependencies": {
     "@ai-sdk/provider": "^2.0.0",
-    "@ai-sdk/provider-utils": "^3.0.12"
+    "@ai-sdk/provider-utils": "^3.0.17"
   },
   "devDependencies": {
     "tsdown": "^0.13.3",

packages/aiCore/package.json

@@ -39,13 +39,13 @@
     "ai": "^5.0.26"
   },
   "dependencies": {
-    "@ai-sdk/anthropic": "^2.0.43",
+    "@ai-sdk/anthropic": "^2.0.45",
-    "@ai-sdk/azure": "^2.0.66",
+    "@ai-sdk/azure": "^2.0.73",
-    "@ai-sdk/deepseek": "^1.0.27",
+    "@ai-sdk/deepseek": "^1.0.29",
-    "@ai-sdk/openai-compatible": "^1.0.26",
+    "@ai-sdk/openai-compatible": "patch:@ai-sdk/openai-compatible@npm%3A1.0.27#~/.yarn/patches/@ai-sdk-openai-compatible-npm-1.0.27-06f74278cf.patch",
     "@ai-sdk/provider": "^2.0.0",
-    "@ai-sdk/provider-utils": "^3.0.16",
+    "@ai-sdk/provider-utils": "^3.0.17",
-    "@ai-sdk/xai": "^2.0.31",
+    "@ai-sdk/xai": "^2.0.34",
     "zod": "^4.1.5"
   },
   "devDependencies": {

packages/aiCore/src/__tests__/fixtures/mock-providers.ts

@@ -0,0 +1,180 @@
+/**
+ * Mock Provider Instances
+ * Provides mock implementations for all supported AI providers
+ */
+
+import type { ImageModelV2, LanguageModelV2 } from '@ai-sdk/provider'
+import { vi } from 'vitest'
+
+/**
+ * Creates a mock language model with customizable behavior
+ */
+export function createMockLanguageModel(overrides?: Partial<LanguageModelV2>): LanguageModelV2 {
+  return {
+    specificationVersion: 'v1',
+    provider: 'mock-provider',
+    modelId: 'mock-model',
+    defaultObjectGenerationMode: 'tool',
+
+    doGenerate: vi.fn().mockResolvedValue({
+      text: 'Mock response text',
+      finishReason: 'stop',
+      usage: {
+        promptTokens: 10,
+        completionTokens: 20,
+        totalTokens: 30
+      },
+      rawCall: { rawPrompt: null, rawSettings: {} },
+      rawResponse: { headers: {} },
+      warnings: []
+    }),
+
+    doStream: vi.fn().mockReturnValue({
+      stream: (async function* () {
+        yield {
+          type: 'text-delta',
+          textDelta: 'Mock '
+        }
+        yield {
+          type: 'text-delta',
+          textDelta: 'streaming '
+        }
+        yield {
+          type: 'text-delta',
+          textDelta: 'response'
+        }
+        yield {
+          type: 'finish',
+          finishReason: 'stop',
+          usage: {
+            promptTokens: 10,
+            completionTokens: 15,
+            totalTokens: 25
+          }
+        }
+      })(),
+      rawCall: { rawPrompt: null, rawSettings: {} },
+      rawResponse: { headers: {} },
+      warnings: []
+    }),
+
+    ...overrides
+  } as LanguageModelV2
+}
+
+/**
+ * Creates a mock image model with customizable behavior
+ */
+export function createMockImageModel(overrides?: Partial<ImageModelV2>): ImageModelV2 {
+  return {
+    specificationVersion: 'v2',
+    provider: 'mock-provider',
+    modelId: 'mock-image-model',
+
+    doGenerate: vi.fn().mockResolvedValue({
+      images: [
+        {
+          base64: 'mock-base64-image-data',
+          uint8Array: new Uint8Array([1, 2, 3, 4, 5]),
+          mimeType: 'image/png'
+        }
+      ],
+      warnings: []
+    }),
+
+    ...overrides
+  } as ImageModelV2
+}
+
+/**
+ * Mock provider configurations for testing
+ */
+export const mockProviderConfigs = {
+  openai: {
+    apiKey: 'sk-test-openai-key-123456789',
+    baseURL: 'https://api.openai.com/v1',
+    organization: 'test-org'
+  },
+
+  anthropic: {
+    apiKey: 'sk-ant-test-key-123456789',
+    baseURL: 'https://api.anthropic.com'
+  },
+
+  google: {
+    apiKey: 'test-google-api-key-123456789',
+    baseURL: 'https://generativelanguage.googleapis.com/v1'
+  },
+
+  xai: {
+    apiKey: 'xai-test-key-123456789',
+    baseURL: 'https://api.x.ai/v1'
+  },
+
+  azure: {
+    apiKey: 'test-azure-key-123456789',
+    resourceName: 'test-resource',
+    deployment: 'test-deployment'
+  },
+
+  deepseek: {
+    apiKey: 'sk-test-deepseek-key-123456789',
+    baseURL: 'https://api.deepseek.com/v1'
+  },
+
+  openrouter: {
+    apiKey: 'sk-or-test-key-123456789',
+    baseURL: 'https://openrouter.ai/api/v1'
+  },
+
+  huggingface: {
+    apiKey: 'hf_test_key_123456789',
+    baseURL: 'https://api-inference.huggingface.co'
+  },
+
+  'openai-compatible': {
+    apiKey: 'test-compatible-key-123456789',
+    baseURL: 'https://api.example.com/v1',
+    name: 'test-provider'
+  },
+
+  'openai-chat': {
+    apiKey: 'sk-test-chat-key-123456789',
+    baseURL: 'https://api.openai.com/v1'
+  }
+} as const
+
+/**
+ * Mock provider instances for testing
+ */
+export const mockProviderInstances = {
+  openai: {
+    name: 'openai-mock',
+    languageModel: createMockLanguageModel({ provider: 'openai', modelId: 'gpt-4' }),
+    imageModel: createMockImageModel({ provider: 'openai', modelId: 'dall-e-3' })
+  },
+
+  anthropic: {
+    name: 'anthropic-mock',
+    languageModel: createMockLanguageModel({ provider: 'anthropic', modelId: 'claude-3-5-sonnet-20241022' })
+  },
+
+  google: {
+    name: 'google-mock',
+    languageModel: createMockLanguageModel({ provider: 'google', modelId: 'gemini-2.0-flash-exp' }),
+    imageModel: createMockImageModel({ provider: 'google', modelId: 'imagen-3.0-generate-001' })
+  },
+
+  xai: {
+    name: 'xai-mock',
+    languageModel: createMockLanguageModel({ provider: 'xai', modelId: 'grok-2-latest' }),
+    imageModel: createMockImageModel({ provider: 'xai', modelId: 'grok-2-image-latest' })
+  },
+
+  deepseek: {
+    name: 'deepseek-mock',
+    languageModel: createMockLanguageModel({ provider: 'deepseek', modelId: 'deepseek-chat' })
+  }
+}
+
+export type ProviderId = keyof typeof mockProviderConfigs

packages/aiCore/src/__tests__/fixtures/mock-responses.ts

@@ -0,0 +1,331 @@
+/**
+ * Mock Responses
+ * Provides realistic mock responses for all provider types
+ */
+
+import { jsonSchema, type ModelMessage, type Tool } from 'ai'
+
+/**
+ * Standard test messages for all scenarios
+ */
+export const testMessages = {
+  simple: [{ role: 'user' as const, content: 'Hello, how are you?' }],
+
+  conversation: [
+    { role: 'user' as const, content: 'What is the capital of France?' },
+    { role: 'assistant' as const, content: 'The capital of France is Paris.' },
+    { role: 'user' as const, content: 'What is its population?' }
+  ],
+
+  withSystem: [
+    { role: 'system' as const, content: 'You are a helpful assistant that provides concise answers.' },
+    { role: 'user' as const, content: 'Explain quantum computing in one sentence.' }
+  ],
+
+  withImages: [
+    {
+      role: 'user' as const,
+      content: [
+        { type: 'text' as const, text: 'What is in this image?' },
+        {
+          type: 'image' as const,
+          image:
+            'data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAAEAAAABCAYAAAAfFcSJAAAADUlEQVR42mNk+M9QDwADhgGAWjR9awAAAABJRU5ErkJggg=='
+        }
+      ]
+    }
+  ],
+
+  toolUse: [{ role: 'user' as const, content: 'What is the weather in San Francisco?' }],
+
+  multiTurn: [
+    { role: 'user' as const, content: 'Can you help me with a math problem?' },
+    { role: 'assistant' as const, content: 'Of course! What math problem would you like help with?' },
+    { role: 'user' as const, content: 'What is 15 * 23?' },
+    { role: 'assistant' as const, content: '15 * 23 = 345' },
+    { role: 'user' as const, content: 'Now divide that by 5' }
+  ]
+} satisfies Record<string, ModelMessage[]>
+
+/**
+ * Standard test tools for tool calling scenarios
+ */
+export const testTools: Record<string, Tool> = {
+  getWeather: {
+    description: 'Get the current weather in a given location',
+    inputSchema: jsonSchema({
+      type: 'object',
+      properties: {
+        location: {
+          type: 'string',
+          description: 'The city and state, e.g. San Francisco, CA'
+        },
+        unit: {
+          type: 'string',
+          enum: ['celsius', 'fahrenheit'],
+          description: 'The temperature unit to use'
+        }
+      },
+      required: ['location']
+    }),
+    execute: async ({ location, unit = 'fahrenheit' }) => {
+      return {
+        location,
+        temperature: unit === 'celsius' ? 22 : 72,
+        unit,
+        condition: 'sunny'
+      }
+    }
+  },
+
+  calculate: {
+    description: 'Perform a mathematical calculation',
+    inputSchema: jsonSchema({
+      type: 'object',
+      properties: {
+        operation: {
+          type: 'string',
+          enum: ['add', 'subtract', 'multiply', 'divide'],
+          description: 'The operation to perform'
+        },
+        a: {
+          type: 'number',
+          description: 'The first number'
+        },
+        b: {
+          type: 'number',
+          description: 'The second number'
+        }
+      },
+      required: ['operation', 'a', 'b']
+    }),
+    execute: async ({ operation, a, b }) => {
+      const operations = {
+        add: (x: number, y: number) => x + y,
+        subtract: (x: number, y: number) => x - y,
+        multiply: (x: number, y: number) => x * y,
+        divide: (x: number, y: number) => x / y
+      }
+      return { result: operations[operation as keyof typeof operations](a, b) }
+    }
+  },
+
+  searchDatabase: {
+    description: 'Search for information in a database',
+    inputSchema: jsonSchema({
+      type: 'object',
+      properties: {
+        query: {
+          type: 'string',
+          description: 'The search query'
+        },
+        limit: {
+          type: 'number',
+          description: 'Maximum number of results to return',
+          default: 10
+        }
+      },
+      required: ['query']
+    }),
+    execute: async ({ query, limit = 10 }) => {
+      return {
+        results: [
+          { id: 1, title: `Result 1 for ${query}`, relevance: 0.95 },
+          { id: 2, title: `Result 2 for ${query}`, relevance: 0.87 }
+        ].slice(0, limit)
+      }
+    }
+  }
+}
+
+/**
+ * Mock streaming chunks for different providers
+ */
+export const mockStreamingChunks = {
+  text: [
+    { type: 'text-delta' as const, textDelta: 'Hello' },
+    { type: 'text-delta' as const, textDelta: ', ' },
+    { type: 'text-delta' as const, textDelta: 'this ' },
+    { type: 'text-delta' as const, textDelta: 'is ' },
+    { type: 'text-delta' as const, textDelta: 'a ' },
+    { type: 'text-delta' as const, textDelta: 'test.' }
+  ],
+
+  withToolCall: [
+    { type: 'text-delta' as const, textDelta: 'Let me check the weather for you.' },
+    {
+      type: 'tool-call-delta' as const,
+      toolCallType: 'function' as const,
+      toolCallId: 'call_123',
+      toolName: 'getWeather',
+      argsTextDelta: '{"location":'
+    },
+    {
+      type: 'tool-call-delta' as const,
+      toolCallType: 'function' as const,
+      toolCallId: 'call_123',
+      toolName: 'getWeather',
+      argsTextDelta: ' "San Francisco, CA"}'
+    },
+    {
+      type: 'tool-call' as const,
+      toolCallType: 'function' as const,
+      toolCallId: 'call_123',
+      toolName: 'getWeather',
+      args: { location: 'San Francisco, CA' }
+    }
+  ],
+
+  withFinish: [
+    { type: 'text-delta' as const, textDelta: 'Complete response.' },
+    {
+      type: 'finish' as const,
+      finishReason: 'stop' as const,
+      usage: {
+        promptTokens: 10,
+        completionTokens: 5,
+        totalTokens: 15
+      }
+    }
+  ]
+}
+
+/**
+ * Mock complete responses for non-streaming scenarios
+ */
+export const mockCompleteResponses = {
+  simple: {
+    text: 'This is a simple response.',
+    finishReason: 'stop' as const,
+    usage: {
+      promptTokens: 15,
+      completionTokens: 8,
+      totalTokens: 23
+    }
+  },
+
+  withToolCalls: {
+    text: 'I will check the weather for you.',
+    toolCalls: [
+      {
+        toolCallId: 'call_456',
+        toolName: 'getWeather',
+        args: { location: 'New York, NY', unit: 'celsius' }
+      }
+    ],
+    finishReason: 'tool-calls' as const,
+    usage: {
+      promptTokens: 25,
+      completionTokens: 12,
+      totalTokens: 37
+    }
+  },
+
+  withWarnings: {
+    text: 'Response with warnings.',
+    finishReason: 'stop' as const,
+    usage: {
+      promptTokens: 10,
+      completionTokens: 5,
+      totalTokens: 15
+    },
+    warnings: [
+      {
+        type: 'unsupported-setting' as const,
+        message: 'Temperature parameter not supported for this model'
+      }
+    ]
+  }
+}
+
+/**
+ * Mock image generation responses
+ */
+export const mockImageResponses = {
+  single: {
+    image: {
+      base64: 'iVBORw0KGgoAAAANSUhEUgAAAAEAAAABCAYAAAAfFcSJAAAADUlEQVR42mNk+M9QDwADhgGAWjR9awAAAABJRU5ErkJggg==',
+      uint8Array: new Uint8Array([137, 80, 78, 71, 13, 10, 26, 10, 0, 0, 0, 13, 73, 72, 68, 82]),
+      mimeType: 'image/png' as const
+    },
+    warnings: []
+  },
+
+  multiple: {
+    images: [
+      {
+        base64: 'iVBORw0KGgoAAAANSUhEUgAAAAEAAAABCAYAAAAfFcSJAAAADUlEQVR42mNk+M9QDwADhgGAWjR9awAAAABJRU5ErkJggg==',
+        uint8Array: new Uint8Array([137, 80, 78, 71]),
+        mimeType: 'image/png' as const
+      },
+      {
+        base64: 'iVBORw0KGgoAAAANSUhEUgAAAAIAAAACCAYAAABytg0kAAAAEklEQVR42mNk+M9QzwAEjDAGACCKAgdZ9zImAAAAAElFTkSuQmCC',
+        uint8Array: new Uint8Array([137, 80, 78, 71]),
+        mimeType: 'image/png' as const
+      }
+    ],
+    warnings: []
+  },
+
+  withProviderMetadata: {
+    image: {
+      base64: 'iVBORw0KGgoAAAANSUhEUgAAAAEAAAABCAYAAAAfFcSJAAAADUlEQVR42mNk+M9QDwADhgGAWjR9awAAAABJRU5ErkJggg==',
+      uint8Array: new Uint8Array([137, 80, 78, 71]),
+      mimeType: 'image/png' as const
+    },
+    providerMetadata: {
+      openai: {
+        images: [
+          {
+            revisedPrompt: 'A detailed and enhanced version of the original prompt'
+          }
+        ]
+      }
+    },
+    warnings: []
+  }
+}
+
+/**
+ * Mock error responses
+ */
+export const mockErrors = {
+  invalidApiKey: {
+    name: 'APIError',
+    message: 'Invalid API key provided',
+    statusCode: 401
+  },
+
+  rateLimitExceeded: {
+    name: 'RateLimitError',
+    message: 'Rate limit exceeded. Please try again later.',
+    statusCode: 429,
+    headers: {
+      'retry-after': '60'
+    }
+  },
+
+  modelNotFound: {
+    name: 'ModelNotFoundError',
+    message: 'The requested model was not found',
+    statusCode: 404
+  },
+
+  contextLengthExceeded: {
+    name: 'ContextLengthError',
+    message: "This model's maximum context length is 4096 tokens",
+    statusCode: 400
+  },
+
+  timeout: {
+    name: 'TimeoutError',
+    message: 'Request timed out after 30000ms',
+    code: 'ETIMEDOUT'
+  },
+
+  networkError: {
+    name: 'NetworkError',
+    message: 'Network connection failed',
+    code: 'ECONNREFUSED'
+  }
+}

packages/aiCore/src/__tests__/helpers/provider-test-utils.ts

@@ -0,0 +1,329 @@
+/**
+ * Provider-Specific Test Utilities
+ * Helper functions for testing individual providers with all their parameters
+ */
+
+import type { Tool } from 'ai'
+import { expect } from 'vitest'
+
+/**
+ * Provider parameter configurations for comprehensive testing
+ */
+export const providerParameterMatrix = {
+  openai: {
+    models: ['gpt-4', 'gpt-4-turbo', 'gpt-3.5-turbo', 'gpt-4o'],
+    parameters: {
+      temperature: [0, 0.5, 0.7, 1.0, 1.5, 2.0],
+      maxTokens: [100, 500, 1000, 2000, 4000],
+      topP: [0.1, 0.5, 0.9, 1.0],
+      frequencyPenalty: [-2.0, -1.0, 0, 1.0, 2.0],
+      presencePenalty: [-2.0, -1.0, 0, 1.0, 2.0],
+      stop: [undefined, ['stop'], ['STOP', 'END']],
+      seed: [undefined, 12345, 67890],
+      responseFormat: [undefined, { type: 'json_object' as const }],
+      user: [undefined, 'test-user-123']
+    },
+    toolChoice: ['auto', 'required', 'none', { type: 'function' as const, name: 'getWeather' }],
+    parallelToolCalls: [true, false]
+  },
+
+  anthropic: {
+    models: ['claude-3-5-sonnet-20241022', 'claude-3-opus-20240229', 'claude-3-haiku-20240307'],
+    parameters: {
+      temperature: [0, 0.5, 1.0],
+      maxTokens: [100, 1000, 4000, 8000],
+      topP: [0.1, 0.5, 0.9, 1.0],
+      topK: [undefined, 1, 5, 10, 40],
+      stop: [undefined, ['Human:', 'Assistant:']],
+      metadata: [undefined, { userId: 'test-123' }]
+    },
+    toolChoice: ['auto', 'any', { type: 'tool' as const, name: 'getWeather' }]
+  },
+
+  google: {
+    models: ['gemini-2.0-flash-exp', 'gemini-1.5-pro', 'gemini-1.5-flash'],
+    parameters: {
+      temperature: [0, 0.5, 0.9, 1.0],
+      maxTokens: [100, 1000, 2000, 8000],
+      topP: [0.1, 0.5, 0.95, 1.0],
+      topK: [undefined, 1, 16, 40],
+      stopSequences: [undefined, ['END'], ['STOP', 'TERMINATE']]
+    },
+    safetySettings: [
+      undefined,
+      [
+        { category: 'HARM_CATEGORY_HARASSMENT', threshold: 'BLOCK_MEDIUM_AND_ABOVE' },
+        { category: 'HARM_CATEGORY_HATE_SPEECH', threshold: 'BLOCK_ONLY_HIGH' }
+      ]
+    ]
+  },
+
+  xai: {
+    models: ['grok-2-latest', 'grok-2-1212'],
+    parameters: {
+      temperature: [0, 0.5, 1.0, 1.5],
+      maxTokens: [100, 500, 2000, 4000],
+      topP: [0.1, 0.5, 0.9, 1.0],
+      stop: [undefined, ['STOP'], ['END', 'TERMINATE']],
+      seed: [undefined, 12345]
+    }
+  },
+
+  deepseek: {
+    models: ['deepseek-chat', 'deepseek-coder'],
+    parameters: {
+      temperature: [0, 0.5, 1.0],
+      maxTokens: [100, 1000, 4000],
+      topP: [0.1, 0.5, 0.95],
+      frequencyPenalty: [0, 0.5, 1.0],
+      presencePenalty: [0, 0.5, 1.0],
+      stop: [undefined, ['```'], ['END']]
+    }
+  },
+
+  azure: {
+    deployments: ['gpt-4-deployment', 'gpt-35-turbo-deployment'],
+    parameters: {
+      temperature: [0, 0.7, 1.0],
+      maxTokens: [100, 1000, 2000],
+      topP: [0.1, 0.5, 0.95],
+      frequencyPenalty: [0, 1.0],
+      presencePenalty: [0, 1.0],
+      stop: [undefined, ['STOP']]
+    }
+  }
+} as const
+
+/**
+ * Creates test cases for all parameter combinations
+ */
+export function generateParameterTestCases<T extends Record<string, any[]>>(
+  params: T,
+  maxCombinations = 50
+): Array<Partial<{ [K in keyof T]: T[K][number] }>> {
+  const keys = Object.keys(params) as Array<keyof T>
+  const testCases: Array<Partial<{ [K in keyof T]: T[K][number] }>> = []
+
+  // Generate combinations using sampling strategy for large parameter spaces
+  const totalCombinations = keys.reduce((acc, key) => acc * params[key].length, 1)
+
+  if (totalCombinations <= maxCombinations) {
+    // Generate all combinations if total is small
+    generateAllCombinations(params, keys, 0, {}, testCases)
+  } else {
+    // Sample diverse combinations if total is large
+    generateSampledCombinations(params, keys, maxCombinations, testCases)
+  }
+
+  return testCases
+}
+
+function generateAllCombinations<T extends Record<string, any[]>>(
+  params: T,
+  keys: Array<keyof T>,
+  index: number,
+  current: Partial<{ [K in keyof T]: T[K][number] }>,
+  results: Array<Partial<{ [K in keyof T]: T[K][number] }>>
+) {
+  if (index === keys.length) {
+    results.push({ ...current })
+    return
+  }
+
+  const key = keys[index]
+  for (const value of params[key]) {
+    generateAllCombinations(params, keys, index + 1, { ...current, [key]: value }, results)
+  }
+}
+
+function generateSampledCombinations<T extends Record<string, any[]>>(
+  params: T,
+  keys: Array<keyof T>,
+  count: number,
+  results: Array<Partial<{ [K in keyof T]: T[K][number] }>>
+) {
+  // Generate edge cases first (min/max values)
+  const edgeCase1: any = {}
+  const edgeCase2: any = {}
+
+  for (const key of keys) {
+    edgeCase1[key] = params[key][0]
+    edgeCase2[key] = params[key][params[key].length - 1]
+  }
+
+  results.push(edgeCase1, edgeCase2)
+
+  // Generate random combinations for the rest
+  for (let i = results.length; i < count; i++) {
+    const combination: any = {}
+    for (const key of keys) {
+      const values = params[key]
+      combination[key] = values[Math.floor(Math.random() * values.length)]
+    }
+    results.push(combination)
+  }
+}
+
+/**
+ * Validates that all provider-specific parameters are correctly passed through
+ */
+export function validateProviderParams(providerId: string, actualParams: any, expectedParams: any): void {
+  const requiredFields: Record<string, string[]> = {
+    openai: ['model', 'messages'],
+    anthropic: ['model', 'messages'],
+    google: ['model', 'contents'],
+    xai: ['model', 'messages'],
+    deepseek: ['model', 'messages'],
+    azure: ['messages']
+  }
+
+  const fields = requiredFields[providerId] || ['model', 'messages']
+
+  for (const field of fields) {
+    expect(actualParams).toHaveProperty(field)
+  }
+
+  // Validate optional parameters if they were provided
+  const optionalParams = ['temperature', 'max_tokens', 'top_p', 'stop', 'tools']
+
+  for (const param of optionalParams) {
+    if (expectedParams[param] !== undefined) {
+      expect(actualParams[param]).toEqual(expectedParams[param])
+    }
+  }
+}
+
+/**
+ * Creates a comprehensive test suite for a provider
+ */
+// oxlint-disable-next-line no-unused-vars
+export function createProviderTestSuite(_providerId: string) {
+  return {
+    testBasicCompletion: async (executor: any, model: string) => {
+      const result = await executor.generateText({
+        model,
+        messages: [{ role: 'user' as const, content: 'Hello' }]
+      })
+
+      expect(result).toBeDefined()
+      expect(result.text).toBeDefined()
+      expect(typeof result.text).toBe('string')
+    },
+
+    testStreaming: async (executor: any, model: string) => {
+      const chunks: any[] = []
+      const result = await executor.streamText({
+        model,
+        messages: [{ role: 'user' as const, content: 'Hello' }]
+      })
+
+      for await (const chunk of result.textStream) {
+        chunks.push(chunk)
+      }
+
+      expect(chunks.length).toBeGreaterThan(0)
+    },
+
+    testTemperature: async (executor: any, model: string, temperatures: number[]) => {
+      for (const temperature of temperatures) {
+        const result = await executor.generateText({
+          model,
+          messages: [{ role: 'user' as const, content: 'Hello' }],
+          temperature
+        })
+
+        expect(result).toBeDefined()
+      }
+    },
+
+    testMaxTokens: async (executor: any, model: string, maxTokensValues: number[]) => {
+      for (const maxTokens of maxTokensValues) {
+        const result = await executor.generateText({
+          model,
+          messages: [{ role: 'user' as const, content: 'Hello' }],
+          maxTokens
+        })
+
+        expect(result).toBeDefined()
+        if (result.usage?.completionTokens) {
+          expect(result.usage.completionTokens).toBeLessThanOrEqual(maxTokens)
+        }
+      }
+    },
+
+    testToolCalling: async (executor: any, model: string, tools: Record<string, Tool>) => {
+      const result = await executor.generateText({
+        model,
+        messages: [{ role: 'user' as const, content: 'What is the weather in SF?' }],
+        tools
+      })
+
+      expect(result).toBeDefined()
+    },
+
+    testStopSequences: async (executor: any, model: string, stopSequences: string[][]) => {
+      for (const stop of stopSequences) {
+        const result = await executor.generateText({
+          model,
+          messages: [{ role: 'user' as const, content: 'Count to 10' }],
+          stop
+        })
+
+        expect(result).toBeDefined()
+      }
+    }
+  }
+}
+
+/**
+ * Generates test data for vision/multimodal testing
+ */
+export function createVisionTestData() {
+  return {
+    imageUrl: 'https://example.com/test-image.jpg',
+    base64Image:
+      'data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAAEAAAABCAYAAAAfFcSJAAAADUlEQVR42mNk+M9QDwADhgGAWjR9awAAAABJRU5ErkJggg==',
+    messages: [
+      {
+        role: 'user' as const,
+        content: [
+          { type: 'text' as const, text: 'What is in this image?' },
+          {
+            type: 'image' as const,
+            image:
+              'data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAAEAAAABCAYAAAAfFcSJAAAADUlEQVR42mNk+M9QDwADhgGAWjR9awAAAABJRU5ErkJggg=='
+          }
+        ]
+      }
+    ]
+  }
+}
+
+/**
+ * Creates mock responses for different finish reasons
+ */
+export function createFinishReasonMocks() {
+  return {
+    stop: {
+      text: 'Complete response.',
+      finishReason: 'stop' as const,
+      usage: { promptTokens: 10, completionTokens: 5, totalTokens: 15 }
+    },
+    length: {
+      text: 'Incomplete response due to',
+      finishReason: 'length' as const,
+      usage: { promptTokens: 10, completionTokens: 100, totalTokens: 110 }
+    },
+    'tool-calls': {
+      text: 'Calling tools',
+      finishReason: 'tool-calls' as const,
+      toolCalls: [{ toolCallId: 'call_1', toolName: 'getWeather', args: { location: 'SF' } }],
+      usage: { promptTokens: 10, completionTokens: 8, totalTokens: 18 }
+    },
+    'content-filter': {
+      text: '',
+      finishReason: 'content-filter' as const,
+      usage: { promptTokens: 10, completionTokens: 0, totalTokens: 10 }
+    }
+  }
+}

packages/aiCore/src/__tests__/helpers/test-utils.ts

@@ -0,0 +1,291 @@
+/**
+ * Test Utilities
+ * Helper functions for testing AI Core functionality
+ */
+
+import { expect, vi } from 'vitest'
+
+import type { ProviderId } from '../fixtures/mock-providers'
+import { createMockImageModel, createMockLanguageModel, mockProviderConfigs } from '../fixtures/mock-providers'
+
+/**
+ * Creates a test provider with streaming support
+ */
+export function createTestStreamingProvider(chunks: any[]) {
+  return createMockLanguageModel({
+    doStream: vi.fn().mockReturnValue({
+      stream: (async function* () {
+        for (const chunk of chunks) {
+          yield chunk
+        }
+      })(),
+      rawCall: { rawPrompt: null, rawSettings: {} },
+      rawResponse: { headers: {} },
+      warnings: []
+    })
+  })
+}
+
+/**
+ * Creates a test provider that throws errors
+ */
+export function createErrorProvider(error: Error) {
+  return createMockLanguageModel({
+    doGenerate: vi.fn().mockRejectedValue(error),
+    doStream: vi.fn().mockImplementation(() => {
+      throw error
+    })
+  })
+}
+
+/**
+ * Collects all chunks from a stream
+ */
+export async function collectStreamChunks<T>(stream: AsyncIterable<T>): Promise<T[]> {
+  const chunks: T[] = []
+  for await (const chunk of stream) {
+    chunks.push(chunk)
+  }
+  return chunks
+}
+
+/**
+ * Waits for a specific number of milliseconds
+ */
+export function wait(ms: number): Promise<void> {
+  return new Promise((resolve) => setTimeout(resolve, ms))
+}
+
+/**
+ * Creates a mock abort controller that aborts after a delay
+ */
+export function createDelayedAbortController(delayMs: number): AbortController {
+  const controller = new AbortController()
+  setTimeout(() => controller.abort(), delayMs)
+  return controller
+}
+
+/**
+ * Asserts that a function throws an error with a specific message
+ */
+export async function expectError(fn: () => Promise<any>, expectedMessage?: string | RegExp): Promise<Error> {
+  try {
+    await fn()
+    throw new Error('Expected function to throw an error, but it did not')
+  } catch (error) {
+    if (expectedMessage) {
+      const message = (error as Error).message
+      if (typeof expectedMessage === 'string') {
+        if (!message.includes(expectedMessage)) {
+          throw new Error(`Expected error message to include "${expectedMessage}", but got "${message}"`)
+        }
+      } else {
+        if (!expectedMessage.test(message)) {
+          throw new Error(`Expected error message to match ${expectedMessage}, but got "${message}"`)
+        }
+      }
+    }
+    return error as Error
+  }
+}
+
+/**
+ * Creates a spy function that tracks calls and arguments
+ */
+export function createSpy<T extends (...args: any[]) => any>() {
+  const calls: Array<{ args: Parameters<T>; result?: ReturnType<T>; error?: Error }> = []
+
+  const spy = vi.fn((...args: Parameters<T>) => {
+    try {
+      const result = undefined as ReturnType<T>
+      calls.push({ args, result })
+      return result
+    } catch (error) {
+      calls.push({ args, error: error as Error })
+      throw error
+    }
+  })
+
+  return {
+    fn: spy,
+    calls,
+    getCalls: () => calls,
+    getCallCount: () => calls.length,
+    getLastCall: () => calls[calls.length - 1],
+    reset: () => {
+      calls.length = 0
+      spy.mockClear()
+    }
+  }
+}
+
+/**
+ * Validates provider configuration
+ */
+export function validateProviderConfig(providerId: ProviderId) {
+  const config = mockProviderConfigs[providerId]
+  if (!config) {
+    throw new Error(`No mock configuration found for provider: ${providerId}`)
+  }
+
+  if (!config.apiKey) {
+    throw new Error(`Provider ${providerId} is missing apiKey in mock config`)
+  }
+
+  return config
+}
+
+/**
+ * Creates a test context with common setup
+ */
+export function createTestContext() {
+  const mocks = {
+    languageModel: createMockLanguageModel(),
+    imageModel: createMockImageModel(),
+    providers: new Map<string, any>()
+  }
+
+  const cleanup = () => {
+    mocks.providers.clear()
+    vi.clearAllMocks()
+  }
+
+  return {
+    mocks,
+    cleanup
+  }
+}
+
+/**
+ * Measures execution time of an async function
+ */
+export async function measureTime<T>(fn: () => Promise<T>): Promise<{ result: T; duration: number }> {
+  const start = Date.now()
+  const result = await fn()
+  const duration = Date.now() - start
+  return { result, duration }
+}
+
+/**
+ * Retries a function until it succeeds or max attempts reached
+ */
+export async function retryUntilSuccess<T>(fn: () => Promise<T>, maxAttempts = 3, delayMs = 100): Promise<T> {
+  let lastError: Error | undefined
+
+  for (let attempt = 1; attempt <= maxAttempts; attempt++) {
+    try {
+      return await fn()
+    } catch (error) {
+      lastError = error as Error
+      if (attempt < maxAttempts) {
+        await wait(delayMs)
+      }
+    }
+  }
+
+  throw lastError || new Error('All retry attempts failed')
+}
+
+/**
+ * Creates a mock streaming response that emits chunks at intervals
+ */
+export function createTimedStream<T>(chunks: T[], intervalMs = 10) {
+  return {
+    async *[Symbol.asyncIterator]() {
+      for (const chunk of chunks) {
+        await wait(intervalMs)
+        yield chunk
+      }
+    }
+  }
+}
+
+/**
+ * Asserts that two objects are deeply equal, ignoring specified keys
+ */
+export function assertDeepEqualIgnoring<T extends Record<string, any>>(
+  actual: T,
+  expected: T,
+  ignoreKeys: string[] = []
+): void {
+  const filterKeys = (obj: T): Partial<T> => {
+    const filtered = { ...obj }
+    for (const key of ignoreKeys) {
+      delete filtered[key]
+    }
+    return filtered
+  }
+
+  const filteredActual = filterKeys(actual)
+  const filteredExpected = filterKeys(expected)
+
+  expect(filteredActual).toEqual(filteredExpected)
+}
+
+/**
+ * Creates a provider mock that simulates rate limiting
+ */
+export function createRateLimitedProvider(limitPerSecond: number) {
+  const calls: number[] = []
+
+  return createMockLanguageModel({
+    doGenerate: vi.fn().mockImplementation(async () => {
+      const now = Date.now()
+      calls.push(now)
+
+      // Remove calls older than 1 second
+      const recentCalls = calls.filter((time) => now - time < 1000)
+
+      if (recentCalls.length > limitPerSecond) {
+        throw new Error('Rate limit exceeded')
+      }
+
+      return {
+        text: 'Rate limited response',
+        finishReason: 'stop' as const,
+        usage: { promptTokens: 10, completionTokens: 5, totalTokens: 15 },
+        rawCall: { rawPrompt: null, rawSettings: {} },
+        rawResponse: { headers: {} },
+        warnings: []
+      }
+    })
+  })
+}
+
+/**
+ * Validates streaming response structure
+ */
+export function validateStreamChunk(chunk: any): void {
+  expect(chunk).toBeDefined()
+  expect(chunk).toHaveProperty('type')
+
+  if (chunk.type === 'text-delta') {
+    expect(chunk).toHaveProperty('textDelta')
+    expect(typeof chunk.textDelta).toBe('string')
+  } else if (chunk.type === 'finish') {
+    expect(chunk).toHaveProperty('finishReason')
+    expect(chunk).toHaveProperty('usage')
+  } else if (chunk.type === 'tool-call') {
+    expect(chunk).toHaveProperty('toolCallId')
+    expect(chunk).toHaveProperty('toolName')
+    expect(chunk).toHaveProperty('args')
+  }
+}
+
+/**
+ * Creates a test logger that captures log messages
+ */
+export function createTestLogger() {
+  const logs: Array<{ level: string; message: string; meta?: any }> = []
+
+  return {
+    info: (message: string, meta?: any) => logs.push({ level: 'info', message, meta }),
+    warn: (message: string, meta?: any) => logs.push({ level: 'warn', message, meta }),
+    error: (message: string, meta?: any) => logs.push({ level: 'error', message, meta }),
+    debug: (message: string, meta?: any) => logs.push({ level: 'debug', message, meta }),
+    getLogs: () => logs,
+    clear: () => {
+      logs.length = 0
+    }
+  }
+}

packages/aiCore/src/__tests__/index.ts

@@ -0,0 +1,12 @@
+/**
+ * Test Infrastructure Exports
+ * Central export point for all test utilities, fixtures, and helpers
+ */
+
+// Fixtures
+export * from './fixtures/mock-providers'
+export * from './fixtures/mock-responses'
+
+// Helpers
+export * from './helpers/provider-test-utils'
+export * from './helpers/test-utils'

packages/aiCore/src/core/runtime/__tests__/generateText.test.ts

@@ -0,0 +1,499 @@
+/**
+ * RuntimeExecutor.generateText Comprehensive Tests
+ * Tests non-streaming text generation across all providers with various parameters
+ */
+
+import { generateText } from 'ai'
+import { beforeEach, describe, expect, it, vi } from 'vitest'
+
+import {
+  createMockLanguageModel,
+  mockCompleteResponses,
+  mockProviderConfigs,
+  testMessages,
+  testTools
+} from '../../../__tests__'
+import type { AiPlugin } from '../../plugins'
+import { globalRegistryManagement } from '../../providers/RegistryManagement'
+import { RuntimeExecutor } from '../executor'
+
+// Mock AI SDK
+vi.mock('ai', () => ({
+  generateText: vi.fn()
+}))
+
+vi.mock('../../providers/RegistryManagement', () => ({
+  globalRegistryManagement: {
+    languageModel: vi.fn()
+  },
+  DEFAULT_SEPARATOR: '|'
+}))
+
+describe('RuntimeExecutor.generateText', () => {
+  let executor: RuntimeExecutor<'openai'>
+  let mockLanguageModel: any
+
+  beforeEach(() => {
+    vi.clearAllMocks()
+
+    executor = RuntimeExecutor.create('openai', mockProviderConfigs.openai)
+
+    mockLanguageModel = createMockLanguageModel({
+      provider: 'openai',
+      modelId: 'gpt-4'
+    })
+
+    vi.mocked(globalRegistryManagement.languageModel).mockReturnValue(mockLanguageModel)
+    vi.mocked(generateText).mockResolvedValue(mockCompleteResponses.simple as any)
+  })
+
+  describe('Basic Functionality', () => {
+    it('should generate text with minimal parameters', async () => {
+      const result = await executor.generateText({
+        model: 'gpt-4',
+        messages: testMessages.simple
+      })
+
+      expect(generateText).toHaveBeenCalledWith({
+        model: mockLanguageModel,
+        messages: testMessages.simple
+      })
+
+      expect(result.text).toBe('This is a simple response.')
+      expect(result.finishReason).toBe('stop')
+      expect(result.usage).toBeDefined()
+    })
+
+    it('should generate with system messages', async () => {
+      await executor.generateText({
+        model: 'gpt-4',
+        messages: testMessages.withSystem
+      })
+
+      expect(generateText).toHaveBeenCalledWith({
+        model: mockLanguageModel,
+        messages: testMessages.withSystem
+      })
+    })
+
+    it('should generate with conversation history', async () => {
+      await executor.generateText({
+        model: 'gpt-4',
+        messages: testMessages.conversation
+      })
+
+      expect(generateText).toHaveBeenCalledWith(
+        expect.objectContaining({
+          messages: testMessages.conversation
+        })
+      )
+    })
+  })
+
+  describe('All Parameter Combinations', () => {
+    it('should support all parameters together', async () => {
+      await executor.generateText({
+        model: 'gpt-4',
+        messages: testMessages.simple,
+        temperature: 0.7,
+        maxOutputTokens: 500,
+        topP: 0.9,
+        frequencyPenalty: 0.5,
+        presencePenalty: 0.3,
+        stopSequences: ['STOP'],
+        seed: 12345
+      })
+
+      expect(generateText).toHaveBeenCalledWith(
+        expect.objectContaining({
+          temperature: 0.7,
+          maxOutputTokens: 500,
+          topP: 0.9,
+          frequencyPenalty: 0.5,
+          presencePenalty: 0.3,
+          stopSequences: ['STOP'],
+          seed: 12345
+        })
+      )
+    })
+
+    it('should support partial parameters', async () => {
+      await executor.generateText({
+        model: 'gpt-4',
+        messages: testMessages.simple,
+        temperature: 0.5,
+        maxOutputTokens: 100
+      })
+
+      expect(generateText).toHaveBeenCalledWith(
+        expect.objectContaining({
+          temperature: 0.5,
+          maxOutputTokens: 100
+        })
+      )
+    })
+  })
+
+  describe('Tool Calling', () => {
+    beforeEach(() => {
+      vi.mocked(generateText).mockResolvedValue(mockCompleteResponses.withToolCalls as any)
+    })
+
+    it('should support tool calling', async () => {
+      const result = await executor.generateText({
+        model: 'gpt-4',
+        messages: testMessages.toolUse,
+        tools: testTools
+      })
+
+      expect(generateText).toHaveBeenCalledWith(
+        expect.objectContaining({
+          tools: testTools
+        })
+      )
+
+      expect(result.toolCalls).toBeDefined()
+      expect(result.toolCalls).toHaveLength(1)
+    })
+
+    it('should support toolChoice auto', async () => {
+      await executor.generateText({
+        model: 'gpt-4',
+        messages: testMessages.toolUse,
+        tools: testTools,
+        toolChoice: 'auto'
+      })
+
+      expect(generateText).toHaveBeenCalledWith(
+        expect.objectContaining({
+          toolChoice: 'auto'
+        })
+      )
+    })
+
+    it('should support toolChoice required', async () => {
+      await executor.generateText({
+        model: 'gpt-4',
+        messages: testMessages.toolUse,
+        tools: testTools,
+        toolChoice: 'required'
+      })
+
+      expect(generateText).toHaveBeenCalledWith(
+        expect.objectContaining({
+          toolChoice: 'required'
+        })
+      )
+    })
+
+    it('should support toolChoice none', async () => {
+      vi.mocked(generateText).mockResolvedValue(mockCompleteResponses.simple as any)
+
+      await executor.generateText({
+        model: 'gpt-4',
+        messages: testMessages.simple,
+        tools: testTools,
+        toolChoice: 'none'
+      })
+
+      expect(generateText).toHaveBeenCalledWith(
+        expect.objectContaining({
+          toolChoice: 'none'
+        })
+      )
+    })
+
+    it('should support specific tool selection', async () => {
+      await executor.generateText({
+        model: 'gpt-4',
+        messages: testMessages.toolUse,
+        tools: testTools,
+        toolChoice: {
+          type: 'tool',
+          toolName: 'getWeather'
+        }
+      })
+
+      expect(generateText).toHaveBeenCalledWith(
+        expect.objectContaining({
+          toolChoice: {
+            type: 'tool',
+            toolName: 'getWeather'
+          }
+        })
+      )
+    })
+  })
+
+  describe('Multiple Providers', () => {
+    it('should work with Anthropic provider', async () => {
+      const anthropicExecutor = RuntimeExecutor.create('anthropic', mockProviderConfigs.anthropic)
+
+      const anthropicModel = createMockLanguageModel({
+        provider: 'anthropic',
+        modelId: 'claude-3-5-sonnet-20241022'
+      })
+
+      vi.mocked(globalRegistryManagement.languageModel).mockReturnValue(anthropicModel)
+
+      await anthropicExecutor.generateText({
+        model: 'claude-3-5-sonnet-20241022',
+        messages: testMessages.simple
+      })
+
+      expect(globalRegistryManagement.languageModel).toHaveBeenCalledWith('anthropic|claude-3-5-sonnet-20241022')
+    })
+
+    it('should work with Google provider', async () => {
+      const googleExecutor = RuntimeExecutor.create('google', mockProviderConfigs.google)
+
+      const googleModel = createMockLanguageModel({
+        provider: 'google',
+        modelId: 'gemini-2.0-flash-exp'
+      })
+
+      vi.mocked(globalRegistryManagement.languageModel).mockReturnValue(googleModel)
+
+      await googleExecutor.generateText({
+        model: 'gemini-2.0-flash-exp',
+        messages: testMessages.simple
+      })
+
+      expect(globalRegistryManagement.languageModel).toHaveBeenCalledWith('google|gemini-2.0-flash-exp')
+    })
+
+    it('should work with xAI provider', async () => {
+      const xaiExecutor = RuntimeExecutor.create('xai', mockProviderConfigs.xai)
+
+      const xaiModel = createMockLanguageModel({
+        provider: 'xai',
+        modelId: 'grok-2-latest'
+      })
+
+      vi.mocked(globalRegistryManagement.languageModel).mockReturnValue(xaiModel)
+
+      await xaiExecutor.generateText({
+        model: 'grok-2-latest',
+        messages: testMessages.simple
+      })
+
+      expect(globalRegistryManagement.languageModel).toHaveBeenCalledWith('xai|grok-2-latest')
+    })
+
+    it('should work with DeepSeek provider', async () => {
+      const deepseekExecutor = RuntimeExecutor.create('deepseek', mockProviderConfigs.deepseek)
+
+      const deepseekModel = createMockLanguageModel({
+        provider: 'deepseek',
+        modelId: 'deepseek-chat'
+      })
+
+      vi.mocked(globalRegistryManagement.languageModel).mockReturnValue(deepseekModel)
+
+      await deepseekExecutor.generateText({
+        model: 'deepseek-chat',
+        messages: testMessages.simple
+      })
+
+      expect(globalRegistryManagement.languageModel).toHaveBeenCalledWith('deepseek|deepseek-chat')
+    })
+  })
+
+  describe('Plugin Integration', () => {
+    it('should execute all plugin hooks', async () => {
+      const pluginCalls: string[] = []
+
+      const testPlugin: AiPlugin = {
+        name: 'test-plugin',
+        onRequestStart: vi.fn(async () => {
+          pluginCalls.push('onRequestStart')
+        }),
+        transformParams: vi.fn(async (params) => {
+          pluginCalls.push('transformParams')
+          return { ...params, temperature: 0.8 }
+        }),
+        transformResult: vi.fn(async (result) => {
+          pluginCalls.push('transformResult')
+          return { ...result, text: result.text + ' [modified]' }
+        }),
+        onRequestEnd: vi.fn(async () => {
+          pluginCalls.push('onRequestEnd')
+        })
+      }
+
+      const executorWithPlugin = RuntimeExecutor.create('openai', mockProviderConfigs.openai, [testPlugin])
+
+      const result = await executorWithPlugin.generateText({
+        model: 'gpt-4',
+        messages: testMessages.simple
+      })
+
+      expect(pluginCalls).toEqual(['onRequestStart', 'transformParams', 'transformResult', 'onRequestEnd'])
+
+      // Verify transformed parameters
+      expect(generateText).toHaveBeenCalledWith(
+        expect.objectContaining({
+          temperature: 0.8
+        })
+      )
+
+      // Verify transformed result
+      expect(result.text).toContain('[modified]')
+    })
+
+    it('should handle multiple plugins in order', async () => {
+      const pluginOrder: string[] = []
+
+      const plugin1: AiPlugin = {
+        name: 'plugin-1',
+        transformParams: vi.fn(async (params) => {
+          pluginOrder.push('plugin-1')
+          return { ...params, temperature: 0.5 }
+        })
+      }
+
+      const plugin2: AiPlugin = {
+        name: 'plugin-2',
+        transformParams: vi.fn(async (params) => {
+          pluginOrder.push('plugin-2')
+          return { ...params, maxTokens: 200 }
+        })
+      }
+
+      const executorWithPlugins = RuntimeExecutor.create('openai', mockProviderConfigs.openai, [plugin1, plugin2])
+
+      await executorWithPlugins.generateText({
+        model: 'gpt-4',
+        messages: testMessages.simple
+      })
+
+      expect(pluginOrder).toEqual(['plugin-1', 'plugin-2'])
+
+      expect(generateText).toHaveBeenCalledWith(
+        expect.objectContaining({
+          temperature: 0.5,
+          maxTokens: 200
+        })
+      )
+    })
+  })
+
+  describe('Error Handling', () => {
+    it('should handle API errors', async () => {
+      const error = new Error('API request failed')
+      vi.mocked(generateText).mockRejectedValue(error)
+
+      await expect(
+        executor.generateText({
+          model: 'gpt-4',
+          messages: testMessages.simple
+        })
+      ).rejects.toThrow('API request failed')
+    })
+
+    it('should execute onError plugin hook', async () => {
+      const error = new Error('Generation failed')
+      vi.mocked(generateText).mockRejectedValue(error)
+
+      const errorPlugin: AiPlugin = {
+        name: 'error-handler',
+        onError: vi.fn()
+      }
+
+      const executorWithPlugin = RuntimeExecutor.create('openai', mockProviderConfigs.openai, [errorPlugin])
+
+      await expect(
+        executorWithPlugin.generateText({
+          model: 'gpt-4',
+          messages: testMessages.simple
+        })
+      ).rejects.toThrow('Generation failed')
+
+      expect(errorPlugin.onError).toHaveBeenCalledWith(
+        error,
+        expect.objectContaining({
+          providerId: 'openai',
+          modelId: 'gpt-4'
+        })
+      )
+    })
+
+    it('should handle model not found error', async () => {
+      const error = new Error('Model not found: invalid-model')
+      vi.mocked(globalRegistryManagement.languageModel).mockImplementation(() => {
+        throw error
+      })
+
+      await expect(
+        executor.generateText({
+          model: 'invalid-model',
+          messages: testMessages.simple
+        })
+      ).rejects.toThrow('Model not found')
+    })
+  })
+
+  describe('Usage and Metadata', () => {
+    it('should return usage information', async () => {
+      const result = await executor.generateText({
+        model: 'gpt-4',
+        messages: testMessages.simple
+      })
+
+      expect(result.usage).toBeDefined()
+      expect(result.usage.inputTokens).toBe(15)
+      expect(result.usage.outputTokens).toBe(8)
+      expect(result.usage.totalTokens).toBe(23)
+    })
+
+    it('should handle warnings', async () => {
+      vi.mocked(generateText).mockResolvedValue(mockCompleteResponses.withWarnings as any)
+
+      const result = await executor.generateText({
+        model: 'gpt-4',
+        messages: testMessages.simple,
+        temperature: 2.5 // Unsupported value
+      })
+
+      expect(result.warnings).toBeDefined()
+      expect(result.warnings).toHaveLength(1)
+      expect(result.warnings![0].type).toBe('unsupported-setting')
+    })
+  })
+
+  describe('Abort Signal', () => {
+    it('should support abort signal', async () => {
+      const abortController = new AbortController()
+
+      await executor.generateText({
+        model: 'gpt-4',
+        messages: testMessages.simple,
+        abortSignal: abortController.signal
+      })
+
+      expect(generateText).toHaveBeenCalledWith(
+        expect.objectContaining({
+          abortSignal: abortController.signal
+        })
+      )
+    })
+
+    it('should handle aborted request', async () => {
+      const abortError = new Error('Request aborted')
+      abortError.name = 'AbortError'
+
+      vi.mocked(generateText).mockRejectedValue(abortError)
+
+      const abortController = new AbortController()
+      abortController.abort()
+
+      await expect(
+        executor.generateText({
+          model: 'gpt-4',
+          messages: testMessages.simple,
+          abortSignal: abortController.signal
+        })
+      ).rejects.toThrow('Request aborted')
+    })
+  })
+})

packages/aiCore/src/core/runtime/__tests__/streamText.test.ts

@@ -0,0 +1,525 @@
+/**
+ * RuntimeExecutor.streamText Comprehensive Tests
+ * Tests streaming text generation across all providers with various parameters
+ */
+
+import { streamText } from 'ai'
+import { beforeEach, describe, expect, it, vi } from 'vitest'
+
+import { collectStreamChunks, createMockLanguageModel, mockProviderConfigs, testMessages } from '../../../__tests__'
+import type { AiPlugin } from '../../plugins'
+import { globalRegistryManagement } from '../../providers/RegistryManagement'
+import { RuntimeExecutor } from '../executor'
+
+// Mock AI SDK
+vi.mock('ai', () => ({
+  streamText: vi.fn()
+}))
+
+vi.mock('../../providers/RegistryManagement', () => ({
+  globalRegistryManagement: {
+    languageModel: vi.fn()
+  },
+  DEFAULT_SEPARATOR: '|'
+}))
+
+describe('RuntimeExecutor.streamText', () => {
+  let executor: RuntimeExecutor<'openai'>
+  let mockLanguageModel: any
+
+  beforeEach(() => {
+    vi.clearAllMocks()
+
+    executor = RuntimeExecutor.create('openai', mockProviderConfigs.openai)
+
+    mockLanguageModel = createMockLanguageModel({
+      provider: 'openai',
+      modelId: 'gpt-4'
+    })
+
+    vi.mocked(globalRegistryManagement.languageModel).mockReturnValue(mockLanguageModel)
+  })
+
+  describe('Basic Functionality', () => {
+    it('should stream text with minimal parameters', async () => {
+      const mockStream = {
+        textStream: (async function* () {
+          yield 'Hello'
+          yield ' '
+          yield 'World'
+        })(),
+        fullStream: (async function* () {
+          yield { type: 'text-delta', textDelta: 'Hello' }
+          yield { type: 'text-delta', textDelta: ' ' }
+          yield { type: 'text-delta', textDelta: 'World' }
+        })(),
+        usage: Promise.resolve({ promptTokens: 5, completionTokens: 3, totalTokens: 8 })
+      }
+
+      vi.mocked(streamText).mockResolvedValue(mockStream as any)
+
+      const result = await executor.streamText({
+        model: 'gpt-4',
+        messages: testMessages.simple
+      })
+
+      expect(streamText).toHaveBeenCalledWith({
+        model: mockLanguageModel,
+        messages: testMessages.simple
+      })
+
+      const chunks = await collectStreamChunks(result.textStream)
+      expect(chunks).toEqual(['Hello', ' ', 'World'])
+    })
+
+    it('should stream with system messages', async () => {
+      const mockStream = {
+        textStream: (async function* () {
+          yield 'Response'
+        })(),
+        fullStream: (async function* () {
+          yield { type: 'text-delta', textDelta: 'Response' }
+        })()
+      }
+
+      vi.mocked(streamText).mockResolvedValue(mockStream as any)
+
+      await executor.streamText({
+        model: 'gpt-4',
+        messages: testMessages.withSystem
+      })
+
+      expect(streamText).toHaveBeenCalledWith({
+        model: mockLanguageModel,
+        messages: testMessages.withSystem
+      })
+    })
+
+    it('should stream multi-turn conversations', async () => {
+      const mockStream = {
+        textStream: (async function* () {
+          yield 'Multi-turn response'
+        })(),
+        fullStream: (async function* () {
+          yield { type: 'text-delta', textDelta: 'Multi-turn response' }
+        })()
+      }
+
+      vi.mocked(streamText).mockResolvedValue(mockStream as any)
+
+      await executor.streamText({
+        model: 'gpt-4',
+        messages: testMessages.multiTurn
+      })
+
+      expect(streamText).toHaveBeenCalled()
+      expect(streamText).toHaveBeenCalledWith(
+        expect.objectContaining({
+          messages: testMessages.multiTurn
+        })
+      )
+    })
+  })
+
+  describe('Temperature Parameter', () => {
+    const temperatures = [0, 0.3, 0.5, 0.7, 0.9, 1.0, 1.5, 2.0]
+
+    it.each(temperatures)('should support temperature=%s', async (temperature) => {
+      const mockStream = {
+        textStream: (async function* () {
+          yield 'Response'
+        })(),
+        fullStream: (async function* () {
+          yield { type: 'text-delta', textDelta: 'Response' }
+        })()
+      }
+
+      vi.mocked(streamText).mockResolvedValue(mockStream as any)
+
+      await executor.streamText({
+        model: 'gpt-4',
+        messages: testMessages.simple,
+        temperature
+      })
+
+      expect(streamText).toHaveBeenCalledWith(
+        expect.objectContaining({
+          temperature
+        })
+      )
+    })
+  })
+
+  describe('Max Tokens Parameter', () => {
+    const maxTokensValues = [10, 50, 100, 500, 1000, 2000, 4000]
+
+    it.each(maxTokensValues)('should support maxTokens=%s', async (maxTokens) => {
+      const mockStream = {
+        textStream: (async function* () {
+          yield 'Response'
+        })(),
+        fullStream: (async function* () {
+          yield { type: 'text-delta', textDelta: 'Response' }
+        })()
+      }
+
+      vi.mocked(streamText).mockResolvedValue(mockStream as any)
+
+      await executor.streamText({
+        model: 'gpt-4',
+        messages: testMessages.simple,
+        maxOutputTokens: maxTokens
+      })
+
+      expect(streamText).toHaveBeenCalledWith(
+        expect.objectContaining({
+          maxTokens
+        })
+      )
+    })
+  })
+
+  describe('Top P Parameter', () => {
+    const topPValues = [0.1, 0.3, 0.5, 0.7, 0.9, 0.95, 1.0]
+
+    it.each(topPValues)('should support topP=%s', async (topP) => {
+      const mockStream = {
+        textStream: (async function* () {
+          yield 'Response'
+        })(),
+        fullStream: (async function* () {
+          yield { type: 'text-delta', textDelta: 'Response' }
+        })()
+      }
+
+      vi.mocked(streamText).mockResolvedValue(mockStream as any)
+
+      await executor.streamText({
+        model: 'gpt-4',
+        messages: testMessages.simple,
+        topP
+      })
+
+      expect(streamText).toHaveBeenCalledWith(
+        expect.objectContaining({
+          topP
+        })
+      )
+    })
+  })
+
+  describe('Frequency and Presence Penalty', () => {
+    it('should support frequency penalty', async () => {
+      const penalties = [-2.0, -1.0, 0, 0.5, 1.0, 1.5, 2.0]
+
+      for (const frequencyPenalty of penalties) {
+        vi.clearAllMocks()
+
+        const mockStream = {
+          textStream: (async function* () {
+            yield 'Response'
+          })(),
+          fullStream: (async function* () {
+            yield { type: 'text-delta', textDelta: 'Response' }
+          })()
+        }
+
+        vi.mocked(streamText).mockResolvedValue(mockStream as any)
+
+        await executor.streamText({
+          model: 'gpt-4',
+          messages: testMessages.simple,
+          frequencyPenalty
+        })
+
+        expect(streamText).toHaveBeenCalledWith(
+          expect.objectContaining({
+            frequencyPenalty
+          })
+        )
+      }
+    })
+
+    it('should support presence penalty', async () => {
+      const penalties = [-2.0, -1.0, 0, 0.5, 1.0, 1.5, 2.0]
+
+      for (const presencePenalty of penalties) {
+        vi.clearAllMocks()
+
+        const mockStream = {
+          textStream: (async function* () {
+            yield 'Response'
+          })(),
+          fullStream: (async function* () {
+            yield { type: 'text-delta', textDelta: 'Response' }
+          })()
+        }
+
+        vi.mocked(streamText).mockResolvedValue(mockStream as any)
+
+        await executor.streamText({
+          model: 'gpt-4',
+          messages: testMessages.simple,
+          presencePenalty
+        })
+
+        expect(streamText).toHaveBeenCalledWith(
+          expect.objectContaining({
+            presencePenalty
+          })
+        )
+      }
+    })
+
+    it('should support both penalties together', async () => {
+      const mockStream = {
+        textStream: (async function* () {
+          yield 'Response'
+        })(),
+        fullStream: (async function* () {
+          yield { type: 'text-delta', textDelta: 'Response' }
+        })()
+      }
+
+      vi.mocked(streamText).mockResolvedValue(mockStream as any)
+
+      await executor.streamText({
+        model: 'gpt-4',
+        messages: testMessages.simple,
+        frequencyPenalty: 0.5,
+        presencePenalty: 0.5
+      })
+
+      expect(streamText).toHaveBeenCalledWith(
+        expect.objectContaining({
+          frequencyPenalty: 0.5,
+          presencePenalty: 0.5
+        })
+      )
+    })
+  })
+
+  describe('Seed Parameter', () => {
+    it('should support seed for deterministic output', async () => {
+      const seeds = [0, 12345, 67890, 999999]
+
+      for (const seed of seeds) {
+        vi.clearAllMocks()
+
+        const mockStream = {
+          textStream: (async function* () {
+            yield 'Response'
+          })(),
+          fullStream: (async function* () {
+            yield { type: 'text-delta', textDelta: 'Response' }
+          })()
+        }
+
+        vi.mocked(streamText).mockResolvedValue(mockStream as any)
+
+        await executor.streamText({
+          model: 'gpt-4',
+          messages: testMessages.simple,
+          seed
+        })
+
+        expect(streamText).toHaveBeenCalledWith(
+          expect.objectContaining({
+            seed
+          })
+        )
+      }
+    })
+  })
+
+  describe('Abort Signal', () => {
+    it('should support abort signal', async () => {
+      const abortController = new AbortController()
+
+      const mockStream = {
+        textStream: (async function* () {
+          yield 'Response'
+        })(),
+        fullStream: (async function* () {
+          yield { type: 'text-delta', textDelta: 'Response' }
+        })()
+      }
+
+      vi.mocked(streamText).mockResolvedValue(mockStream as any)
+
+      await executor.streamText({
+        model: 'gpt-4',
+        messages: testMessages.simple,
+        abortSignal: abortController.signal
+      })
+
+      expect(streamText).toHaveBeenCalledWith(
+        expect.objectContaining({
+          abortSignal: abortController.signal
+        })
+      )
+    })
+
+    it('should handle abort during streaming', async () => {
+      const abortController = new AbortController()
+
+      const mockStream = {
+        textStream: (async function* () {
+          yield 'Start'
+          // Simulate abort
+          abortController.abort()
+          throw new Error('Aborted')
+        })(),
+        fullStream: (async function* () {
+          yield { type: 'text-delta', textDelta: 'Start' }
+          throw new Error('Aborted')
+        })()
+      }
+
+      vi.mocked(streamText).mockResolvedValue(mockStream as any)
+
+      const result = await executor.streamText({
+        model: 'gpt-4',
+        messages: testMessages.simple,
+        abortSignal: abortController.signal
+      })
+
+      await expect(async () => {
+        // oxlint-disable-next-line no-unused-vars
+        for await (const _chunk of result.textStream) {
+          // Stream should be interrupted
+        }
+      }).rejects.toThrow('Aborted')
+    })
+  })
+
+  describe('Plugin Integration', () => {
+    it('should execute plugins during streaming', async () => {
+      const pluginCalls: string[] = []
+
+      const testPlugin: AiPlugin = {
+        name: 'test-plugin',
+        onRequestStart: vi.fn(async () => {
+          pluginCalls.push('onRequestStart')
+        }),
+        transformParams: vi.fn(async (params) => {
+          pluginCalls.push('transformParams')
+          return { ...params, temperature: 0.5 }
+        }),
+        onRequestEnd: vi.fn(async () => {
+          pluginCalls.push('onRequestEnd')
+        })
+      }
+
+      const executorWithPlugin = RuntimeExecutor.create('openai', mockProviderConfigs.openai, [testPlugin])
+
+      const mockStream = {
+        textStream: (async function* () {
+          yield 'Response'
+        })(),
+        fullStream: (async function* () {
+          yield { type: 'text-delta', textDelta: 'Response' }
+        })()
+      }
+
+      vi.mocked(streamText).mockResolvedValue(mockStream as any)
+
+      const result = await executorWithPlugin.streamText({
+        model: 'gpt-4',
+        messages: testMessages.simple
+      })
+
+      // Consume stream
+      // oxlint-disable-next-line no-unused-vars
+      for await (const _chunk of result.textStream) {
+        // Stream chunks
+      }
+
+      expect(pluginCalls).toContain('onRequestStart')
+      expect(pluginCalls).toContain('transformParams')
+
+      // Verify transformed parameters were used
+      expect(streamText).toHaveBeenCalledWith(
+        expect.objectContaining({
+          temperature: 0.5
+        })
+      )
+    })
+  })
+
+  describe('Full Stream with Finish Reason', () => {
+    it('should provide finish reason in full stream', async () => {
+      const mockStream = {
+        textStream: (async function* () {
+          yield 'Response'
+        })(),
+        fullStream: (async function* () {
+          yield { type: 'text-delta', textDelta: 'Response' }
+          yield {
+            type: 'finish',
+            finishReason: 'stop',
+            usage: { promptTokens: 5, completionTokens: 3, totalTokens: 8 }
+          }
+        })()
+      }
+
+      vi.mocked(streamText).mockResolvedValue(mockStream as any)
+
+      const result = await executor.streamText({
+        model: 'gpt-4',
+        messages: testMessages.simple
+      })
+
+      const fullChunks = await collectStreamChunks(result.fullStream)
+
+      expect(fullChunks).toHaveLength(2)
+      expect(fullChunks[0]).toEqual({ type: 'text-delta', textDelta: 'Response' })
+      expect(fullChunks[1]).toEqual({
+        type: 'finish',
+        finishReason: 'stop',
+        usage: { promptTokens: 5, completionTokens: 3, totalTokens: 8 }
+      })
+    })
+  })
+
+  describe('Error Handling', () => {
+    it('should handle streaming errors', async () => {
+      const error = new Error('Streaming failed')
+      vi.mocked(streamText).mockRejectedValue(error)
+
+      await expect(
+        executor.streamText({
+          model: 'gpt-4',
+          messages: testMessages.simple
+        })
+      ).rejects.toThrow('Streaming failed')
+    })
+
+    it('should execute onError plugin hook on failure', async () => {
+      const error = new Error('Stream error')
+      vi.mocked(streamText).mockRejectedValue(error)
+
+      const errorPlugin: AiPlugin = {
+        name: 'error-handler',
+        onError: vi.fn()
+      }
+
+      const executorWithPlugin = RuntimeExecutor.create('openai', mockProviderConfigs.openai, [errorPlugin])
+
+      await expect(
+        executorWithPlugin.streamText({
+          model: 'gpt-4',
+          messages: testMessages.simple
+        })
+      ).rejects.toThrow('Stream error')
+
+      expect(errorPlugin.onError).toHaveBeenCalledWith(
+        error,
+        expect.objectContaining({
+          providerId: 'openai',
+          modelId: 'gpt-4'
+        })
+      )
+    })
+  })
+})

packages/shared/utils.ts

@@ -4,3 +4,34 @@ export const defaultAppHeaders = () => {
     'X-Title': 'Cherry Studio'
   }
 }
+
+// Following two function are not being used for now.
+// I may use them in the future, so just keep them commented. - by eurfelux
+
+/**
+ * Converts an `undefined` value to `null`, otherwise returns the value as-is.
+ * @param value - The value to check
+ * @returns `null` if the input is `undefined`; otherwise the input value
+ */
+
+// export function toNullIfUndefined<T>(value: T | undefined): T | null {
+//   if (value === undefined) {
+//     return null
+//   } else {
+//     return value
+//   }
+// }
+
+/**
+ * Converts a `null` value to `undefined`, otherwise returns the value as-is.
+ * @param value - The value to check
+ * @returns `undefined` if the input is `null`; otherwise the input value
+ */
+
+// export function toUndefinedIfNull<T>(value: T | null): T | undefined {
+//   if (value === null) {
+//     return undefined
+//   } else {
+//     return value
+//   }
+// }

src/main/apiServer/server.ts

@@ -3,7 +3,6 @@ import { createServer } from 'node:http'
 import { loggerService } from '@logger'
 import { IpcChannel } from '@shared/IpcChannel'
 
-import { agentService } from '../services/agents'
 import { windowService } from '../services/WindowService'
 import { app } from './app'
 import { config } from './config'
@@ -32,11 +31,6 @@ export class ApiServer {
     // Load config
     const { port, host } = await config.load()
 
-    // Initialize AgentService
-    logger.info('Initializing AgentService')
-    await agentService.initialize()
-    logger.info('AgentService initialized')
-
     // Create server with Express app
     this.server = createServer(app)
     this.applyServerTimeouts(this.server)

src/main/index.ts

@@ -44,6 +44,7 @@ import {
 import { dataApiService } from '@data/DataApiService'
 import { cacheService } from '@data/CacheService'
 import { initWebviewHotkeys } from './services/WebviewService'
+import { runAsyncFunction } from './utils'
 
 const logger = loggerService.withContext('MainEntry')
 
@@ -256,39 +257,33 @@ if (!app.requestSingleInstanceLock()) {
     //start selection assistant service
     initSelectionService()
 
-    // Initialize Agent Service
+    runAsyncFunction(async () => {
-    try {
+      // Start API server if enabled or if agents exist
-      await agentService.initialize()
+      try {
-      logger.info('Agent service initialized successfully')
+        const config = await apiServerService.getCurrentConfig()
-    } catch (error: any) {
+        logger.info('API server config:', config)
-      logger.error('Failed to initialize Agent service:', error)
-    }
 
-    // Start API server if enabled or if agents exist
+        // Check if there are any agents
-    try {
+        let shouldStart = config.enabled
-      const config = await apiServerService.getCurrentConfig()
+        if (!shouldStart) {
-      logger.info('API server config:', config)
+          try {
-
+            const { total } = await agentService.listAgents({ limit: 1 })
-      // Check if there are any agents
+            if (total > 0) {
-      let shouldStart = config.enabled
+              shouldStart = true
-      if (!shouldStart) {
+              logger.info(`Detected ${total} agent(s), auto-starting API server`)
-        try {
+            }
-          const { total } = await agentService.listAgents({ limit: 1 })
+          } catch (error: any) {
-          if (total > 0) {
+            logger.warn('Failed to check agent count:', error)
-            shouldStart = true
-            logger.info(`Detected ${total} agent(s), auto-starting API server`)
           }
-        } catch (error: any) {
-          logger.warn('Failed to check agent count:', error)
         }
-      }
 
-      if (shouldStart) {
+        if (shouldStart) {
-        await apiServerService.start()
+          await apiServerService.start()
+        }
+      } catch (error: any) {
+        logger.error('Failed to check/start API server:', error)
       }
-    } catch (error: any) {
+    })
-      logger.error('Failed to check/start API server:', error)
-    }
   })
 
   registerProtocolClient(app)

src/main/services/agents/BaseService.ts

@@ -1,16 +1,12 @@
-import { type Client, createClient } from '@libsql/client'
 import { loggerService } from '@logger'
 import { mcpApiService } from '@main/apiServer/services/mcp'
 import { type ModelValidationError, validateModelId } from '@main/apiServer/utils'
 import type { AgentType, MCPTool, SlashCommand, Tool } from '@types'
 import { objectKeys } from '@types'
-import { drizzle, type LibSQLDatabase } from 'drizzle-orm/libsql'
 import fs from 'fs'
 import path from 'path'
 
-import { MigrationService } from './database/MigrationService'
+import { DatabaseManager } from './database/DatabaseManager'
-import * as schema from './database/schema'
-import { dbPath } from './drizzle.config'
 import { type AgentModelField, AgentModelValidationError } from './errors'
 import { builtinSlashCommands } from './services/claudecode/commands'
 import { builtinTools } from './services/claudecode/tools'
@@ -18,22 +14,16 @@ import { builtinTools } from './services/claudecode/tools'
 const logger = loggerService.withContext('BaseService')
 
 /**
- * Base service class providing shared database connection and utilities
+ * Base service class providing shared utilities for all agent-related services.
- * for all agent-related services.
  *
  * Features:
- * - Programmatic schema management (no CLI dependencies)
+ * - Database access through DatabaseManager singleton
- * - Automatic table creation and migration
+ * - JSON field serialization/deserialization
- * - Schema version tracking and compatibility checks
+ * - Path validation and creation
- * - Transaction-based operations for safety
+ * - Model validation
- * - Development vs production mode handling
+ * - MCP tools and slash commands listing
- * - Connection retry logic with exponential backoff
  */
 export abstract class BaseService {
-  protected static client: Client | null = null
-  protected static db: LibSQLDatabase<typeof schema> | null = null
-  protected static isInitialized = false
-  protected static initializationPromise: Promise<void> | null = null
   protected jsonFields: string[] = [
     'tools',
     'mcps',
@@ -43,23 +33,6 @@ export abstract class BaseService {
     'slash_commands'
   ]
 
-  /**
-   * Initialize database with retry logic and proper error handling
-   */
-  protected static async initialize(): Promise<void> {
-    // Return existing initialization if in progress
-    if (BaseService.initializationPromise) {
-      return BaseService.initializationPromise
-    }
-
-    if (BaseService.isInitialized) {
-      return
-    }
-
-    BaseService.initializationPromise = BaseService.performInitialization()
-    return BaseService.initializationPromise
-  }
-
   public async listMcpTools(agentType: AgentType, ids?: string[]): Promise<Tool[]> {
     const tools: Tool[] = []
     if (agentType === 'claude-code') {
@@ -99,78 +72,13 @@ export abstract class BaseService {
     return []
   }
 
-  private static async performInitialization(): Promise<void> {
+  /**
-    const maxRetries = 3
+   * Get database instance
-    let lastError: Error
+   * Automatically waits for initialization to complete
-
+   */
-    for (let attempt = 1; attempt <= maxRetries; attempt++) {
+  protected async getDatabase() {
-      try {
+    const dbManager = await DatabaseManager.getInstance()
-        logger.info(`Initializing Agent database at: ${dbPath} (attempt ${attempt}/${maxRetries})`)
+    return dbManager.getDatabase()
-
-        // Ensure the database directory exists
-        const dbDir = path.dirname(dbPath)
-        if (!fs.existsSync(dbDir)) {
-          logger.info(`Creating database directory: ${dbDir}`)
-          fs.mkdirSync(dbDir, { recursive: true })
-        }
-
-        BaseService.client = createClient({
-          url: `file:${dbPath}`
-        })
-
-        BaseService.db = drizzle(BaseService.client, { schema })
-
-        // Run database migrations
-        const migrationService = new MigrationService(BaseService.db, BaseService.client)
-        await migrationService.runMigrations()
-
-        BaseService.isInitialized = true
-        logger.info('Agent database initialized successfully')
-        return
-      } catch (error) {
-        lastError = error as Error
-        logger.warn(`Database initialization attempt ${attempt} failed:`, lastError)
-
-        // Clean up on failure
-        if (BaseService.client) {
-          try {
-            BaseService.client.close()
-          } catch (closeError) {
-            logger.warn('Failed to close client during cleanup:', closeError as Error)
-          }
-        }
-        BaseService.client = null
-        BaseService.db = null
-
-        // Wait before retrying (exponential backoff)
-        if (attempt < maxRetries) {
-          const delay = Math.pow(2, attempt) * 1000 // 2s, 4s, 8s
-          logger.info(`Retrying in ${delay}ms...`)
-          await new Promise((resolve) => setTimeout(resolve, delay))
-        }
-      }
-    }
-
-    // All retries failed
-    BaseService.initializationPromise = null
-    logger.error('Failed to initialize Agent database after all retries:', lastError!)
-    throw lastError!
-  }
-
-  protected ensureInitialized(): void {
-    if (!BaseService.isInitialized || !BaseService.db || !BaseService.client) {
-      throw new Error('Database not initialized. Call initialize() first.')
-    }
-  }
-
-  protected get database(): LibSQLDatabase<typeof schema> {
-    this.ensureInitialized()
-    return BaseService.db!
-  }
-
-  protected get rawClient(): Client {
-    this.ensureInitialized()
-    return BaseService.client!
   }
 
   protected serializeJsonFields(data: any): any {
@@ -282,7 +190,7 @@ export abstract class BaseService {
   }
 
   /**
-   * Force re-initialization (for development/testing)
+   * Validate agent model configuration
    */
   protected async validateAgentModels(
     agentType: AgentType,
@@ -323,22 +231,4 @@ export abstract class BaseService {
       }
     }
   }
-
-  static async reinitialize(): Promise<void> {
-    BaseService.isInitialized = false
-    BaseService.initializationPromise = null
-
-    if (BaseService.client) {
-      try {
-        BaseService.client.close()
-      } catch (error) {
-        logger.warn('Failed to close client during reinitialize:', error as Error)
-      }
-    }
-
-    BaseService.client = null
-    BaseService.db = null
-
-    await BaseService.initialize()
-  }
 }

src/main/services/agents/database/DatabaseManager.ts

@@ -0,0 +1,156 @@
+import { type Client, createClient } from '@libsql/client'
+import { loggerService } from '@logger'
+import type { LibSQLDatabase } from 'drizzle-orm/libsql'
+import { drizzle } from 'drizzle-orm/libsql'
+import fs from 'fs'
+import path from 'path'
+
+import { dbPath } from '../drizzle.config'
+import { MigrationService } from './MigrationService'
+import * as schema from './schema'
+
+const logger = loggerService.withContext('DatabaseManager')
+
+/**
+ * Database initialization state
+ */
+enum InitState {
+  INITIALIZING = 'initializing',
+  INITIALIZED = 'initialized',
+  FAILED = 'failed'
+}
+
+/**
+ * DatabaseManager - Singleton class for managing libsql database connections
+ *
+ * Responsibilities:
+ * - Single source of truth for database connection
+ * - Thread-safe initialization with state management
+ * - Automatic migration handling
+ * - Safe connection cleanup
+ * - Error recovery and retry logic
+ * - Windows platform compatibility fixes
+ */
+export class DatabaseManager {
+  private static instance: DatabaseManager | null = null
+
+  private client: Client | null = null
+  private db: LibSQLDatabase<typeof schema> | null = null
+  private state: InitState = InitState.INITIALIZING
+
+  /**
+   * Get the singleton instance (database initialization starts automatically)
+   */
+  public static async getInstance(): Promise<DatabaseManager> {
+    if (DatabaseManager.instance) {
+      return DatabaseManager.instance
+    }
+
+    const instance = new DatabaseManager()
+    await instance.initialize()
+    DatabaseManager.instance = instance
+
+    return instance
+  }
+
+  /**
+   * Perform the actual initialization
+   */
+  public async initialize(): Promise<void> {
+    if (this.state === InitState.INITIALIZED) {
+      return
+    }
+
+    try {
+      logger.info(`Initializing database at: ${dbPath}`)
+
+      // Ensure database directory exists
+      const dbDir = path.dirname(dbPath)
+      if (!fs.existsSync(dbDir)) {
+        logger.info(`Creating database directory: ${dbDir}`)
+        fs.mkdirSync(dbDir, { recursive: true })
+      }
+
+      // Check if database file is corrupted (Windows specific check)
+      if (fs.existsSync(dbPath)) {
+        const stats = fs.statSync(dbPath)
+        if (stats.size === 0) {
+          logger.warn('Database file is empty, removing corrupted file')
+          fs.unlinkSync(dbPath)
+        }
+      }
+
+      // Create client with platform-specific options
+      this.client = createClient({
+        url: `file:${dbPath}`,
+        // intMode: 'number' helps avoid some Windows compatibility issues
+        intMode: 'number'
+      })
+
+      // Create drizzle instance
+      this.db = drizzle(this.client, { schema })
+
+      // Run migrations
+      const migrationService = new MigrationService(this.db, this.client)
+      await migrationService.runMigrations()
+
+      this.state = InitState.INITIALIZED
+      logger.info('Database initialized successfully')
+    } catch (error) {
+      const err = error as Error
+      logger.error('Database initialization failed:', {
+        error: err.message,
+        stack: err.stack
+      })
+
+      // Clean up failed initialization
+      this.cleanupFailedInit()
+
+      // Set failed state
+      this.state = InitState.FAILED
+      throw new Error(`Database initialization failed: ${err.message || 'Unknown error'}`)
+    }
+  }
+
+  /**
+   * Clean up after failed initialization
+   */
+  private cleanupFailedInit(): void {
+    if (this.client) {
+      try {
+        // On Windows, closing a partially initialized client can crash
+        // Wrap in try-catch and ignore errors during cleanup
+        this.client.close()
+      } catch (error) {
+        logger.warn('Failed to close client during cleanup:', error as Error)
+      }
+    }
+    this.client = null
+    this.db = null
+  }
+
+  /**
+   * Get the database instance
+   * Automatically waits for initialization to complete
+   * @throws Error if database initialization failed
+   */
+  public getDatabase(): LibSQLDatabase<typeof schema> {
+    return this.db!
+  }
+
+  /**
+   * Get the raw client (for advanced operations)
+   * Automatically waits for initialization to complete
+   * @throws Error if database initialization failed
+   */
+  public async getClient(): Promise<Client> {
+    return this.client!
+  }
+
+  /**
+   * Check if database is initialized
+   */
+  public isInitialized(): boolean {
+    return this.state === InitState.INITIALIZED
+  }
+}

src/main/services/agents/database/index.ts

@@ -7,8 +7,14 @@
  * Schema evolution is handled by Drizzle Kit migrations.
  */
 
+// Database Manager (Singleton)
+export * from './DatabaseManager'
+
 // Drizzle ORM schemas
 export * from './schema'
 
 // Repository helpers
 export * from './sessionMessageRepository'
+
+// Migration Service
+export * from './MigrationService'

src/main/services/agents/database/sessionMessageRepository.ts

@@ -15,26 +15,16 @@ import { sessionMessagesTable } from './schema'
 
 const logger = loggerService.withContext('AgentMessageRepository')
 
-type TxClient = any
-
 export type PersistUserMessageParams = AgentMessageUserPersistPayload & {
   sessionId: string
   agentSessionId?: string
-  tx?: TxClient
 }
 
 export type PersistAssistantMessageParams = AgentMessageAssistantPersistPayload & {
   sessionId: string
   agentSessionId: string
-  tx?: TxClient
 }
 
-type PersistExchangeParams = AgentMessagePersistExchangePayload & {
-  tx?: TxClient
-}
-
-type PersistExchangeResult = AgentMessagePersistExchangeResult
-
 class AgentMessageRepository extends BaseService {
   private static instance: AgentMessageRepository | null = null
 
@@ -87,17 +77,13 @@ class AgentMessageRepository extends BaseService {
     return deserialized
   }
 
-  private getWriter(tx?: TxClient): TxClient {
-    return tx ?? this.database
-  }
-
   private async findExistingMessageRow(
-    writer: TxClient,
     sessionId: string,
     role: string,
     messageId: string
   ): Promise<SessionMessageRow | null> {
-    const candidateRows: SessionMessageRow[] = await writer
+    const database = await this.getDatabase()
+    const candidateRows: SessionMessageRow[] = await database
       .select()
       .from(sessionMessagesTable)
       .where(and(eq(sessionMessagesTable.session_id, sessionId), eq(sessionMessagesTable.role, role)))
@@ -122,10 +108,7 @@ class AgentMessageRepository extends BaseService {
   private async upsertMessage(
     params: PersistUserMessageParams | PersistAssistantMessageParams
   ): Promise<AgentSessionMessageEntity> {
-    await AgentMessageRepository.initialize()
+    const { sessionId, agentSessionId = '', payload, metadata, createdAt } = params
-    this.ensureInitialized()
-
-    const { sessionId, agentSessionId = '', payload, metadata, createdAt, tx } = params
 
     if (!payload?.message?.role) {
       throw new Error('Message payload missing role')
@@ -135,18 +118,18 @@ class AgentMessageRepository extends BaseService {
       throw new Error('Message payload missing id')
     }
 
-    const writer = this.getWriter(tx)
+    const database = await this.getDatabase()
     const now = createdAt ?? payload.message.createdAt ?? new Date().toISOString()
     const serializedPayload = this.serializeMessage(payload)
     const serializedMetadata = this.serializeMetadata(metadata)
 
-    const existingRow = await this.findExistingMessageRow(writer, sessionId, payload.message.role, payload.message.id)
+    const existingRow = await this.findExistingMessageRow(sessionId, payload.message.role, payload.message.id)
 
     if (existingRow) {
       const metadataToPersist = serializedMetadata ?? existingRow.metadata ?? undefined
       const agentSessionToPersist = agentSessionId || existingRow.agent_session_id || ''
 
-      await writer
+      await database
         .update(sessionMessagesTable)
         .set({
           content: serializedPayload,
@@ -175,7 +158,7 @@ class AgentMessageRepository extends BaseService {
       updated_at: now
     }
 
-    const [saved] = await writer.insert(sessionMessagesTable).values(insertData).returning()
+    const [saved] = await database.insert(sessionMessagesTable).values(insertData).returning()
 
     return this.deserialize(saved)
   }
@@ -188,49 +171,38 @@ class AgentMessageRepository extends BaseService {
     return this.upsertMessage(params)
   }
 
-  async persistExchange(params: PersistExchangeParams): Promise<PersistExchangeResult> {
+  async persistExchange(params: AgentMessagePersistExchangePayload): Promise<AgentMessagePersistExchangeResult> {
-    await AgentMessageRepository.initialize()
-    this.ensureInitialized()
-
     const { sessionId, agentSessionId, user, assistant } = params
 
-    const result = await this.database.transaction(async (tx) => {
+    const exchangeResult: AgentMessagePersistExchangeResult = {}
-      const exchangeResult: PersistExchangeResult = {}
 
-      if (user?.payload) {
+    if (user?.payload) {
-        exchangeResult.userMessage = await this.persistUserMessage({
+      exchangeResult.userMessage = await this.persistUserMessage({
-          sessionId,
+        sessionId,
-          agentSessionId,
+        agentSessionId,
-          payload: user.payload,
+        payload: user.payload,
-          metadata: user.metadata,
+        metadata: user.metadata,
-          createdAt: user.createdAt,
+        createdAt: user.createdAt
-          tx
+      })
-        })
+    }
-      }
 
-      if (assistant?.payload) {
+    if (assistant?.payload) {
-        exchangeResult.assistantMessage = await this.persistAssistantMessage({
+      exchangeResult.assistantMessage = await this.persistAssistantMessage({
-          sessionId,
+        sessionId,
-          agentSessionId,
+        agentSessionId,
-          payload: assistant.payload,
+        payload: assistant.payload,
-          metadata: assistant.metadata,
+        metadata: assistant.metadata,
-          createdAt: assistant.createdAt,
+        createdAt: assistant.createdAt
-          tx
+      })
-        })
+    }
-      }
 
-      return exchangeResult
+    return exchangeResult
-    })
-
-    return result
   }
 
   async getSessionHistory(sessionId: string): Promise<AgentPersistedMessage[]> {
-    await AgentMessageRepository.initialize()
-    this.ensureInitialized()
-
     try {
-      const rows = await this.database
+      const database = await this.getDatabase()
+      const rows = await database
         .select()
         .from(sessionMessagesTable)
         .where(eq(sessionMessagesTable.session_id, sessionId))

src/main/services/agents/services/AgentService.ts

@@ -32,14 +32,8 @@ export class AgentService extends BaseService {
     return AgentService.instance
   }
 
-  async initialize(): Promise<void> {
-    await BaseService.initialize()
-  }
-
   // Agent Methods
   async createAgent(req: CreateAgentRequest): Promise<CreateAgentResponse> {
-    this.ensureInitialized()
-
     const id = `agent_${Date.now()}_${Math.random().toString(36).substring(2, 11)}`
     const now = new Date().toISOString()
 
@@ -75,8 +69,9 @@ export class AgentService extends BaseService {
       updated_at: now
     }
 
-    await this.database.insert(agentsTable).values(insertData)
+    const database = await this.getDatabase()
-    const result = await this.database.select().from(agentsTable).where(eq(agentsTable.id, id)).limit(1)
+    await database.insert(agentsTable).values(insertData)
+    const result = await database.select().from(agentsTable).where(eq(agentsTable.id, id)).limit(1)
     if (!result[0]) {
       throw new Error('Failed to create agent')
     }
@@ -86,9 +81,8 @@ export class AgentService extends BaseService {
   }
 
   async getAgent(id: string): Promise<GetAgentResponse | null> {
-    this.ensureInitialized()
+    const database = await this.getDatabase()
-
+    const result = await database.select().from(agentsTable).where(eq(agentsTable.id, id)).limit(1)
-    const result = await this.database.select().from(agentsTable).where(eq(agentsTable.id, id)).limit(1)
 
     if (!result[0]) {
       return null
@@ -118,9 +112,9 @@ export class AgentService extends BaseService {
   }
 
   async listAgents(options: ListOptions = {}): Promise<{ agents: AgentEntity[]; total: number }> {
-    this.ensureInitialized() // Build query with pagination
+    // Build query with pagination
-
+    const database = await this.getDatabase()
-    const totalResult = await this.database.select({ count: count() }).from(agentsTable)
+    const totalResult = await database.select({ count: count() }).from(agentsTable)
 
     const sortBy = options.sortBy || 'created_at'
     const orderBy = options.orderBy || 'desc'
@@ -128,7 +122,7 @@ export class AgentService extends BaseService {
     const sortField = agentsTable[sortBy]
     const orderFn = orderBy === 'asc' ? asc : desc
 
-    const baseQuery = this.database.select().from(agentsTable).orderBy(orderFn(sortField))
+    const baseQuery = database.select().from(agentsTable).orderBy(orderFn(sortField))
 
     const result =
       options.limit !== undefined
@@ -151,8 +145,6 @@ export class AgentService extends BaseService {
     updates: UpdateAgentRequest,
     options: { replace?: boolean } = {}
   ): Promise<UpdateAgentResponse | null> {
-    this.ensureInitialized()
-
     // Check if agent exists
     const existing = await this.getAgent(id)
     if (!existing) {
@@ -195,22 +187,21 @@ export class AgentService extends BaseService {
       }
     }
 
-    await this.database.update(agentsTable).set(updateData).where(eq(agentsTable.id, id))
+    const database = await this.getDatabase()
+    await database.update(agentsTable).set(updateData).where(eq(agentsTable.id, id))
     return await this.getAgent(id)
   }
 
   async deleteAgent(id: string): Promise<boolean> {
-    this.ensureInitialized()
+    const database = await this.getDatabase()
-
+    const result = await database.delete(agentsTable).where(eq(agentsTable.id, id))
-    const result = await this.database.delete(agentsTable).where(eq(agentsTable.id, id))
 
     return result.rowsAffected > 0
   }
 
   async agentExists(id: string): Promise<boolean> {
-    this.ensureInitialized()
+    const database = await this.getDatabase()
-
+    const result = await database
-    const result = await this.database
       .select({ id: agentsTable.id })
       .from(agentsTable)
       .where(eq(agentsTable.id, id))

src/main/services/agents/services/SessionMessageService.ts

@@ -104,14 +104,9 @@ export class SessionMessageService extends BaseService {
     return SessionMessageService.instance
   }
 
-  async initialize(): Promise<void> {
-    await BaseService.initialize()
-  }
-
   async sessionMessageExists(id: number): Promise<boolean> {
-    this.ensureInitialized()
+    const database = await this.getDatabase()
-
+    const result = await database
-    const result = await this.database
       .select({ id: sessionMessagesTable.id })
       .from(sessionMessagesTable)
       .where(eq(sessionMessagesTable.id, id))
@@ -124,10 +119,9 @@ export class SessionMessageService extends BaseService {
     sessionId: string,
     options: ListOptions = {}
   ): Promise<{ messages: AgentSessionMessageEntity[] }> {
-    this.ensureInitialized()
-
     // Get messages with pagination
-    const baseQuery = this.database
+    const database = await this.getDatabase()
+    const baseQuery = database
       .select()
       .from(sessionMessagesTable)
       .where(eq(sessionMessagesTable.session_id, sessionId))
@@ -146,9 +140,8 @@ export class SessionMessageService extends BaseService {
   }
 
   async deleteSessionMessage(sessionId: string, messageId: number): Promise<boolean> {
-    this.ensureInitialized()
+    const database = await this.getDatabase()
-
+    const result = await database
-    const result = await this.database
       .delete(sessionMessagesTable)
       .where(and(eq(sessionMessagesTable.id, messageId), eq(sessionMessagesTable.session_id, sessionId)))
 
@@ -160,8 +153,6 @@ export class SessionMessageService extends BaseService {
     messageData: CreateSessionMessageRequest,
     abortController: AbortController
   ): Promise<SessionStreamResult> {
-    this.ensureInitialized()
-
     return await this.startSessionMessageStream(session, messageData, abortController)
   }
 
@@ -270,10 +261,9 @@ export class SessionMessageService extends BaseService {
   }
 
   private async getLastAgentSessionId(sessionId: string): Promise<string> {
-    this.ensureInitialized()
-
     try {
-      const result = await this.database
+      const database = await this.getDatabase()
+      const result = await database
         .select({ agent_session_id: sessionMessagesTable.agent_session_id })
         .from(sessionMessagesTable)
         .where(and(eq(sessionMessagesTable.session_id, sessionId), not(eq(sessionMessagesTable.agent_session_id, ''))))

src/main/services/agents/services/SessionService.ts

@@ -31,10 +31,6 @@ export class SessionService extends BaseService {
     return SessionService.instance
   }
 
-  async initialize(): Promise<void> {
-    await BaseService.initialize()
-  }
-
   /**
    * Override BaseService.listSlashCommands to merge builtin and plugin commands
    */
@@ -85,13 +81,12 @@ export class SessionService extends BaseService {
     agentId: string,
     req: Partial<CreateSessionRequest> = {}
   ): Promise<GetAgentSessionResponse | null> {
-    this.ensureInitialized()
-
     // Validate agent exists - we'll need to import AgentService for this check
     // For now, we'll skip this validation to avoid circular dependencies
     // The database foreign key constraint will handle this
 
-    const agents = await this.database.select().from(agentsTable).where(eq(agentsTable.id, agentId)).limit(1)
+    const database = await this.getDatabase()
+    const agents = await database.select().from(agentsTable).where(eq(agentsTable.id, agentId)).limit(1)
     if (!agents[0]) {
       throw new Error('Agent not found')
     }
@@ -136,9 +131,10 @@ export class SessionService extends BaseService {
       updated_at: now
     }
 
-    await this.database.insert(sessionsTable).values(insertData)
+    const db = await this.getDatabase()
+    await db.insert(sessionsTable).values(insertData)
 
-    const result = await this.database.select().from(sessionsTable).where(eq(sessionsTable.id, id)).limit(1)
+    const result = await db.select().from(sessionsTable).where(eq(sessionsTable.id, id)).limit(1)
 
     if (!result[0]) {
       throw new Error('Failed to create session')
@@ -149,9 +145,8 @@ export class SessionService extends BaseService {
   }
 
   async getSession(agentId: string, id: string): Promise<GetAgentSessionResponse | null> {
-    this.ensureInitialized()
+    const database = await this.getDatabase()
-
+    const result = await database
-    const result = await this.database
       .select()
       .from(sessionsTable)
       .where(and(eq(sessionsTable.id, id), eq(sessionsTable.agent_id, agentId)))
@@ -177,8 +172,6 @@ export class SessionService extends BaseService {
     agentId?: string,
     options: ListOptions = {}
   ): Promise<{ sessions: AgentSessionEntity[]; total: number }> {
-    this.ensureInitialized()
-
     // Build where conditions
     const whereConditions: SQL[] = []
     if (agentId) {
@@ -193,16 +186,13 @@ export class SessionService extends BaseService {
           : undefined
 
     // Get total count
-    const totalResult = await this.database.select({ count: count() }).from(sessionsTable).where(whereClause)
+    const database = await this.getDatabase()
+    const totalResult = await database.select({ count: count() }).from(sessionsTable).where(whereClause)
 
     const total = totalResult[0].count
 
     // Build list query with pagination - sort by updated_at descending (latest first)
-    const baseQuery = this.database
+    const baseQuery = database.select().from(sessionsTable).where(whereClause).orderBy(desc(sessionsTable.updated_at))
-      .select()
-      .from(sessionsTable)
-      .where(whereClause)
-      .orderBy(desc(sessionsTable.updated_at))
 
     const result =
       options.limit !== undefined
@@ -221,8 +211,6 @@ export class SessionService extends BaseService {
     id: string,
     updates: UpdateSessionRequest
   ): Promise<UpdateSessionResponse | null> {
-    this.ensureInitialized()
-
     // Check if session exists
     const existing = await this.getSession(agentId, id)
     if (!existing) {
@@ -263,15 +251,15 @@ export class SessionService extends BaseService {
       }
     }
 
-    await this.database.update(sessionsTable).set(updateData).where(eq(sessionsTable.id, id))
+    const database = await this.getDatabase()
+    await database.update(sessionsTable).set(updateData).where(eq(sessionsTable.id, id))
 
     return await this.getSession(agentId, id)
   }
 
   async deleteSession(agentId: string, id: string): Promise<boolean> {
-    this.ensureInitialized()
+    const database = await this.getDatabase()
-
+    const result = await database
-    const result = await this.database
       .delete(sessionsTable)
       .where(and(eq(sessionsTable.id, id), eq(sessionsTable.agent_id, agentId)))
 
@@ -279,9 +267,8 @@ export class SessionService extends BaseService {
   }
 
   async sessionExists(agentId: string, id: string): Promise<boolean> {
-    this.ensureInitialized()
+    const database = await this.getDatabase()
-
+    const result = await database
-    const result = await this.database
       .select({ id: sessionsTable.id })
       .from(sessionsTable)
       .where(and(eq(sessionsTable.id, id), eq(sessionsTable.agent_id, agentId)))

src/main/services/agents/services/claudecode/index.ts

@@ -2,7 +2,14 @@
 import { EventEmitter } from 'node:events'
 import { createRequire } from 'node:module'
 
-import type { CanUseTool, McpHttpServerConfig, Options, SDKMessage } from '@anthropic-ai/claude-agent-sdk'
+import type {
+  CanUseTool,
+  HookCallback,
+  McpHttpServerConfig,
+  Options,
+  PreToolUseHookInput,
+  SDKMessage
+} from '@anthropic-ai/claude-agent-sdk'
 import { query } from '@anthropic-ai/claude-agent-sdk'
 import { loggerService } from '@logger'
 import { config as apiConfigService } from '@main/apiServer/config'
@@ -157,6 +164,63 @@ class ClaudeCodeService implements AgentServiceInterface {
       })
     }
 
+    const preToolUseHook: HookCallback = async (input, toolUseID, options) => {
+      // Type guard to ensure we're handling PreToolUse event
+      if (input.hook_event_name !== 'PreToolUse') {
+        return {}
+      }
+
+      const hookInput = input as PreToolUseHookInput
+      const toolName = hookInput.tool_name
+
+      logger.debug('PreToolUse hook triggered', {
+        session_id: hookInput.session_id,
+        tool_name: hookInput.tool_name,
+        tool_use_id: toolUseID,
+        tool_input: hookInput.tool_input,
+        cwd: hookInput.cwd,
+        permission_mode: hookInput.permission_mode,
+        autoAllowTools: autoAllowTools
+      })
+
+      if (options?.signal?.aborted) {
+        logger.debug('PreToolUse hook signal already aborted; skipping tool use', {
+          tool_name: hookInput.tool_name
+        })
+        return {}
+      }
+
+      // handle auto approved tools since it never triggers canUseTool
+      const normalizedToolName = normalizeToolName(toolName)
+      if (toolUseID) {
+        const bypassAll = input.permission_mode === 'bypassPermissions'
+        const autoAllowed = autoAllowTools.has(toolName) || autoAllowTools.has(normalizedToolName)
+        if (bypassAll || autoAllowed) {
+          const namespacedToolCallId = buildNamespacedToolCallId(session.id, toolUseID)
+          logger.debug('handling auto approved tools', {
+            toolName,
+            normalizedToolName,
+            namespacedToolCallId,
+            permission_mode: input.permission_mode,
+            autoAllowTools
+          })
+          const isRecord = (v: unknown): v is Record<string, unknown> => {
+            return !!v && typeof v === 'object' && !Array.isArray(v)
+          }
+          const toolInput = isRecord(input.tool_input) ? input.tool_input : {}
+
+          await promptForToolApproval(toolName, toolInput, {
+            ...options,
+            toolCallId: namespacedToolCallId,
+            autoApprove: true
+          })
+        }
+      }
+
+      // Return to proceed without modification
+      return {}
+    }
+
     // Build SDK options from parameters
     const options: Options = {
       abortController,
@@ -180,7 +244,14 @@ class ClaudeCodeService implements AgentServiceInterface {
       permissionMode: session.configuration?.permission_mode,
       maxTurns: session.configuration?.max_turns,
       allowedTools: session.allowed_tools,
-      canUseTool
+      canUseTool,
+      hooks: {
+        PreToolUse: [
+          {
+            hooks: [preToolUseHook]
+          }
+        ]
+      }
     }
 
     if (session.accessible_paths.length > 1) {

src/main/services/agents/services/claudecode/tool-permissions.ts

@@ -31,6 +31,7 @@ type PendingPermissionRequest = {
   abortListener?: () => void
   originalInput: Record<string, unknown>
   toolName: string
+  toolCallId?: string
 }
 
 type RendererPermissionRequestPayload = {
@@ -45,6 +46,7 @@ type RendererPermissionRequestPayload = {
   createdAt: number
   expiresAt: number
   suggestions: PermissionUpdate[]
+  autoApprove?: boolean
 }
 
 type RendererPermissionResultPayload = {
@@ -52,6 +54,7 @@ type RendererPermissionResultPayload = {
   behavior: ToolPermissionBehavior
   message?: string
   reason: 'response' | 'timeout' | 'aborted' | 'no-window'
+  toolCallId?: string
 }
 
 const pendingRequests = new Map<string, PendingPermissionRequest>()
@@ -145,7 +148,8 @@ const finalizeRequest = (
     requestId,
     behavior: update.behavior,
     message: update.behavior === 'deny' ? update.message : undefined,
-    reason
+    reason,
+    toolCallId: pending.toolCallId
   }
 
   const dispatched = broadcastToRenderer(IpcChannel.AgentToolPermission_Result, resultPayload)
@@ -210,6 +214,7 @@ const ensureIpcHandlersRegistered = () => {
 type PromptForToolApprovalOptions = {
   signal: AbortSignal
   suggestions?: PermissionUpdate[]
+  autoApprove?: boolean
 
   // NOTICE: This ID is namespaced with session ID, not the raw SDK tool call ID.
   // Format: `${sessionId}:${rawToolCallId}`, e.g., `session_123:WebFetch_0`
@@ -270,7 +275,8 @@ export async function promptForToolApproval(
     inputPreview,
     createdAt,
     expiresAt,
-    suggestions: sanitizedSuggestions
+    suggestions: sanitizedSuggestions,
+    autoApprove: options.autoApprove
   }
 
   const defaultDenyUpdate: PermissionResult = { behavior: 'deny', message: 'Tool request aborted before user decision' }
@@ -299,7 +305,8 @@ export async function promptForToolApproval(
       timeout,
       originalInput: sanitizedInput,
       toolName,
-      signal: options?.signal
+      signal: options?.signal,
+      toolCallId: options.toolCallId
     }
 
     if (options?.signal) {

src/renderer/src/aiCore/chunk/AiSdkToChunkAdapter.ts

@@ -385,14 +385,13 @@ export class AiSdkToChunkAdapter {
       case 'error':
         this.onChunk({
           type: ChunkType.ERROR,
-          error:
+          error: AISDKError.isInstance(chunk.error)
-            chunk.error instanceof AISDKError
+            ? chunk.error
-              ? chunk.error
+            : new ProviderSpecificError({
-              : new ProviderSpecificError({
+                message: formatErrorMessage(chunk.error),
-                  message: formatErrorMessage(chunk.error),
+                provider: 'unknown',
-                  provider: 'unknown',
+                cause: chunk.error
-                  cause: chunk.error
+              })
-                })
         })
         break
 

src/renderer/src/aiCore/index_new.ts

@@ -32,6 +32,7 @@ import {
   prepareSpecialProviderConfig,
   providerToAiSdkConfig
 } from './provider/providerConfig'
+import type { AiSdkConfig } from './types'
 
 const logger = loggerService.withContext('ModernAiProvider')
 
@@ -44,7 +45,7 @@ export type ModernAiProviderConfig = AiSdkMiddlewareConfig & {
 
 export default class ModernAiProvider {
   private legacyProvider: LegacyAiProvider
-  private config?: ReturnType<typeof providerToAiSdkConfig>
+  private config?: AiSdkConfig
   private actualProvider: Provider
   private model?: Model
   private localProvider: Awaited<AiSdkProvider> | null = null
@@ -89,6 +90,11 @@ export default class ModernAiProvider {
     // 每次请求时重新生成配置以确保API key轮换生效
     this.config = providerToAiSdkConfig(this.actualProvider, this.model)
     logger.debug('Generated provider config for completions', this.config)
+
+    // 检查 config 是否存在
+    if (!this.config) {
+      throw new Error('Provider config is undefined; cannot proceed with completions')
+    }
     if (SUPPORTED_IMAGE_ENDPOINT_LIST.includes(this.config.options.endpoint)) {
       providerConfig.isImageGenerationEndpoint = true
     }
@@ -149,7 +155,8 @@ export default class ModernAiProvider {
     params: StreamTextParams,
     config: ModernAiProviderConfig
   ): Promise<CompletionsResult> {
-    if (config.isImageGenerationEndpoint) {
+    // ai-gateway不是image/generation 端点，所以就先不走legacy了
+    if (config.isImageGenerationEndpoint && config.provider!.id !== SystemProviderIds['ai-gateway']) {
       // 使用 legacy 实现处理图像生成（支持图片编辑等高级功能）
       if (!config.uiMessages) {
         throw new Error('uiMessages is required for image generation endpoint')
@@ -463,8 +470,13 @@ export default class ModernAiProvider {
     // 如果支持新的 AI SDK，使用现代化实现
     if (isModernSdkSupported(this.actualProvider)) {
       try {
+        // 确保 config 已定义
+        if (!this.config) {
+          throw new Error('Provider config is undefined; cannot proceed with generateImage')
+        }
+
         // 确保本地provider已创建
-        if (!this.localProvider) {
+        if (!this.localProvider && this.config) {
           this.localProvider = await createAiSdkProvider(this.config)
           if (!this.localProvider) {
             throw new Error('Local provider not created')

src/renderer/src/aiCore/legacy/clients/ApiClientFactory.ts

@@ -1,6 +1,6 @@
 import { loggerService } from '@logger'
-import { isNewApiProvider } from '@renderer/config/providers'
 import type { Provider } from '@renderer/types'
+import { isNewApiProvider } from '@renderer/utils/provider'
 
 import { AihubmixAPIClient } from './aihubmix/AihubmixAPIClient'
 import { AnthropicAPIClient } from './anthropic/AnthropicAPIClient'

src/renderer/src/aiCore/legacy/clients/BaseApiClient.ts

@@ -7,7 +7,6 @@ import {
   isOpenAIModel,
   isSupportFlexServiceTierModel
 } from '@renderer/config/models'
-import { isSupportServiceTierProvider } from '@renderer/config/providers'
 import { getLMStudioKeepAliveTime } from '@renderer/hooks/useLMStudio'
 import { getAssistantSettings } from '@renderer/services/AssistantService'
 import type {
@@ -19,7 +18,6 @@ import type {
   MCPToolResponse,
   MemoryItem,
   Model,
-  OpenAIVerbosity,
   Provider,
   ToolCallResponse,
   WebSearchProviderResponse,
@@ -33,6 +31,7 @@ import {
   OpenAIServiceTiers,
   SystemProviderIds
 } from '@renderer/types'
+import type { OpenAIVerbosity } from '@renderer/types/aiCoreTypes'
 import type { Message } from '@renderer/types/newMessage'
 import type {
   RequestOptions,
@@ -48,6 +47,7 @@ import type {
 import { isJSON, parseJSON } from '@renderer/utils'
 import { addAbortController, removeAbortController } from '@renderer/utils/abortController'
 import { findFileBlocks, getMainTextContent } from '@renderer/utils/messageUtils/find'
+import { isSupportServiceTierProvider } from '@renderer/utils/provider'
 import { defaultTimeout } from '@shared/config/constant'
 import { REFERENCE_PROMPT } from '@shared/config/prompts'
 import { defaultAppHeaders } from '@shared/utils'

src/renderer/src/aiCore/legacy/clients/__tests__/ApiClientFactory.test.ts

@@ -58,10 +58,27 @@ vi.mock('../aws/AwsBedrockAPIClient', () => ({
   AwsBedrockAPIClient: vi.fn().mockImplementation(() => ({}))
 }))
 
+vi.mock('@renderer/services/AssistantService.ts', () => ({
+  getDefaultAssistant: () => {
+    return {
+      id: 'default',
+      name: 'default',
+      emoji: '😀',
+      prompt: '',
+      topics: [],
+      messages: [],
+      type: 'assistant',
+      regularPhrases: [],
+      settings: {}
+    }
+  }
+}))
+
 // Mock the models config to prevent circular dependency issues
 vi.mock('@renderer/config/models', () => ({
   findTokenLimit: vi.fn(),
   isReasoningModel: vi.fn(),
+  isOpenAILLMModel: vi.fn(),
   SYSTEM_MODELS: {
     silicon: [],
     defaultModel: []

src/renderer/src/aiCore/legacy/clients/gemini/VertexAPIClient.ts

@@ -1,7 +1,8 @@
 import { GoogleGenAI } from '@google/genai'
 import { loggerService } from '@logger'
-import { createVertexProvider, isVertexAIConfigured, isVertexProvider } from '@renderer/hooks/useVertexAI'
+import { createVertexProvider, isVertexAIConfigured } from '@renderer/hooks/useVertexAI'
 import type { Model, Provider, VertexProvider } from '@renderer/types'
+import { isVertexProvider } from '@renderer/utils/provider'
 import { isEmpty } from 'lodash'
 
 import { AnthropicVertexClient } from '../anthropic/AnthropicVertexClient'

src/renderer/src/aiCore/legacy/clients/openai/OpenAIApiClient.ts

@@ -10,7 +10,6 @@ import { DEFAULT_MAX_TOKENS } from '@renderer/config/constant'
 import {
   findTokenLimit,
   GEMINI_FLASH_MODEL_REGEX,
-  getOpenAIWebSearchParams,
   getThinkModelType,
   isClaudeReasoningModel,
   isDeepSeekHybridInferenceModel,
@@ -40,12 +39,6 @@ import {
   MODEL_SUPPORTED_REASONING_EFFORT,
   ZHIPU_RESULT_TOKENS
 } from '@renderer/config/models'
-import {
-  isSupportArrayContentProvider,
-  isSupportDeveloperRoleProvider,
-  isSupportEnableThinkingProvider,
-  isSupportStreamOptionsProvider
-} from '@renderer/config/providers'
 import { mapLanguageToQwenMTModel } from '@renderer/config/translate'
 import { processPostsuffixQwen3Model, processReqMessages } from '@renderer/services/ModelMessageService'
 import { estimateTextTokens } from '@renderer/services/TokenService'
@@ -89,6 +82,12 @@ import {
   openAIToolsToMcpTool
 } from '@renderer/utils/mcp-tools'
 import { findFileBlocks, findImageBlocks } from '@renderer/utils/messageUtils/find'
+import {
+  isSupportArrayContentProvider,
+  isSupportDeveloperRoleProvider,
+  isSupportEnableThinkingProvider,
+  isSupportStreamOptionsProvider
+} from '@renderer/utils/provider'
 import { t } from 'i18next'
 
 import type { GenericChunk } from '../../middleware/schemas'
@@ -743,7 +742,7 @@ export class OpenAIAPIClient extends OpenAIBaseClient<
             : {}),
           ...this.getProviderSpecificParameters(assistant, model),
           ...reasoningEffort,
-          ...getOpenAIWebSearchParams(model, enableWebSearch),
+          // ...getOpenAIWebSearchParams(model, enableWebSearch),
           // OpenRouter usage tracking
           ...(this.provider.id === 'openrouter' ? { usage: { include: true } } : {}),
           ...extra_body,

src/renderer/src/aiCore/legacy/clients/openai/OpenAIResponseAPIClient.ts

@@ -12,7 +12,6 @@ import {
   isSupportVerbosityModel,
   isVisionModel
 } from '@renderer/config/models'
-import { isSupportDeveloperRoleProvider } from '@renderer/config/providers'
 import { estimateTextTokens } from '@renderer/services/TokenService'
 import type {
   FileMetadata,
@@ -43,6 +42,7 @@ import {
   openAIToolsToMcpTool
 } from '@renderer/utils/mcp-tools'
 import { findFileBlocks, findImageBlocks } from '@renderer/utils/messageUtils/find'
+import { isSupportDeveloperRoleProvider } from '@renderer/utils/provider'
 import { MB } from '@shared/config/constant'
 import { t } from 'i18next'
 import { isEmpty } from 'lodash'

src/renderer/src/aiCore/legacy/middleware/common/ErrorHandlerMiddleware.ts

@@ -1,6 +1,7 @@
 import { loggerService } from '@logger'
 import { isZhipuModel } from '@renderer/config/models'
 import { getStoreProviders } from '@renderer/hooks/useStore'
+import { getDefaultModel } from '@renderer/services/AssistantService'
 import type { Chunk } from '@renderer/types/chunk'
 
 import type { CompletionsParams, CompletionsResult } from '../schemas'
@@ -66,7 +67,7 @@ export const ErrorHandlerMiddleware =
   }
 
 function handleError(error: any, params: CompletionsParams): any {
-  if (isZhipuModel(params.assistant.model) && error.status && !params.enableGenerateImage) {
+  if (isZhipuModel(params.assistant.model || getDefaultModel()) && error.status && !params.enableGenerateImage) {
     return handleZhipuError(error)
   }
 

src/renderer/src/aiCore/middleware/AiSdkMiddlewareBuilder.ts

@@ -1,10 +1,10 @@
 import type { WebSearchPluginConfig } from '@cherrystudio/ai-core/built-in/plugins'
 import { loggerService } from '@logger'
 import { isSupportedThinkingTokenQwenModel } from '@renderer/config/models'
-import { isSupportEnableThinkingProvider } from '@renderer/config/providers'
 import type { MCPTool } from '@renderer/types'
-import { type Assistant, type Message, type Model, type Provider } from '@renderer/types'
+import { type Assistant, type Message, type Model, type Provider, SystemProviderIds } from '@renderer/types'
 import type { Chunk } from '@renderer/types/chunk'
+import { isSupportEnableThinkingProvider } from '@renderer/utils/provider'
 import type { LanguageModelMiddleware } from 'ai'
 import { extractReasoningMiddleware, simulateStreamingMiddleware } from 'ai'
 import { isEmpty } from 'lodash'
@@ -12,6 +12,7 @@ import { isEmpty } from 'lodash'
 import { isOpenRouterGeminiGenerateImageModel } from '../utils/image'
 import { noThinkMiddleware } from './noThinkMiddleware'
 import { openrouterGenerateImageMiddleware } from './openrouterGenerateImageMiddleware'
+import { openrouterReasoningMiddleware } from './openrouterReasoningMiddleware'
 import { qwenThinkingMiddleware } from './qwenThinkingMiddleware'
 import { toolChoiceMiddleware } from './toolChoiceMiddleware'
 
@@ -217,6 +218,14 @@ function addProviderSpecificMiddlewares(builder: AiSdkMiddlewareBuilder, config:
       middleware: noThinkMiddleware()
     })
   }
+
+  if (config.provider.id === SystemProviderIds.openrouter && config.enableReasoning) {
+    builder.add({
+      name: 'openrouter-reasoning-redaction',
+      middleware: openrouterReasoningMiddleware()
+    })
+    logger.debug('Added OpenRouter reasoning redaction middleware')
+  }
 }
 
 /**

src/renderer/src/aiCore/middleware/openrouterReasoningMiddleware.ts

@@ -0,0 +1,50 @@
+import type { LanguageModelV2StreamPart } from '@ai-sdk/provider'
+import type { LanguageModelMiddleware } from 'ai'
+
+/**
+ * https://openrouter.ai/docs/docs/best-practices/reasoning-tokens#example-preserving-reasoning-blocks-with-openrouter-and-claude
+ *
+ * @returns LanguageModelMiddleware - a middleware filter redacted block
+ */
+export function openrouterReasoningMiddleware(): LanguageModelMiddleware {
+  const REDACTED_BLOCK = '[REDACTED]'
+  return {
+    middlewareVersion: 'v2',
+    wrapGenerate: async ({ doGenerate }) => {
+      const { content, ...rest } = await doGenerate()
+      const modifiedContent = content.map((part) => {
+        if (part.type === 'reasoning' && part.text.includes(REDACTED_BLOCK)) {
+          return {
+            ...part,
+            text: part.text.replace(REDACTED_BLOCK, '')
+          }
+        }
+        return part
+      })
+      return { content: modifiedContent, ...rest }
+    },
+    wrapStream: async ({ doStream }) => {
+      const { stream, ...rest } = await doStream()
+      return {
+        stream: stream.pipeThrough(
+          new TransformStream<LanguageModelV2StreamPart, LanguageModelV2StreamPart>({
+            transform(
+              chunk: LanguageModelV2StreamPart,
+              controller: TransformStreamDefaultController<LanguageModelV2StreamPart>
+            ) {
+              if (chunk.type === 'reasoning-delta' && chunk.delta.includes(REDACTED_BLOCK)) {
+                controller.enqueue({
+                  ...chunk,
+                  delta: chunk.delta.replace(REDACTED_BLOCK, '')
+                })
+              } else {
+                controller.enqueue(chunk)
+              }
+            }
+          })
+        ),
+        ...rest
+      }
+    }
+  }
+}

src/renderer/src/aiCore/prepareParams/__tests__/message-converter.test.ts

@@ -0,0 +1,234 @@
+import type { Message, Model } from '@renderer/types'
+import type { FileMetadata } from '@renderer/types/file'
+import { FileTypes } from '@renderer/types/file'
+import {
+  AssistantMessageStatus,
+  type FileMessageBlock,
+  type ImageMessageBlock,
+  MessageBlockStatus,
+  MessageBlockType,
+  type ThinkingMessageBlock,
+  UserMessageStatus
+} from '@renderer/types/newMessage'
+import { beforeEach, describe, expect, it, vi } from 'vitest'
+
+const { convertFileBlockToFilePartMock, convertFileBlockToTextPartMock } = vi.hoisted(() => ({
+  convertFileBlockToFilePartMock: vi.fn(),
+  convertFileBlockToTextPartMock: vi.fn()
+}))
+
+vi.mock('../fileProcessor', () => ({
+  convertFileBlockToFilePart: convertFileBlockToFilePartMock,
+  convertFileBlockToTextPart: convertFileBlockToTextPartMock
+}))
+
+const visionModelIds = new Set(['gpt-4o-mini', 'qwen-image-edit'])
+const imageEnhancementModelIds = new Set(['qwen-image-edit'])
+
+vi.mock('@renderer/config/models', () => ({
+  isVisionModel: (model: Model) => visionModelIds.has(model.id),
+  isImageEnhancementModel: (model: Model) => imageEnhancementModelIds.has(model.id)
+}))
+
+type MockableMessage = Message & {
+  __mockContent?: string
+  __mockFileBlocks?: FileMessageBlock[]
+  __mockImageBlocks?: ImageMessageBlock[]
+  __mockThinkingBlocks?: ThinkingMessageBlock[]
+}
+
+vi.mock('@renderer/utils/messageUtils/find', () => ({
+  getMainTextContent: (message: Message) => (message as MockableMessage).__mockContent ?? '',
+  findFileBlocks: (message: Message) => (message as MockableMessage).__mockFileBlocks ?? [],
+  findImageBlocks: (message: Message) => (message as MockableMessage).__mockImageBlocks ?? [],
+  findThinkingBlocks: (message: Message) => (message as MockableMessage).__mockThinkingBlocks ?? []
+}))
+
+import { convertMessagesToSdkMessages, convertMessageToSdkParam } from '../messageConverter'
+
+let messageCounter = 0
+let blockCounter = 0
+
+const createModel = (overrides: Partial<Model> = {}): Model => ({
+  id: 'gpt-4o-mini',
+  name: 'GPT-4o mini',
+  provider: 'openai',
+  group: 'openai',
+  ...overrides
+})
+
+const createMessage = (role: Message['role']): MockableMessage =>
+  ({
+    id: `message-${++messageCounter}`,
+    role,
+    assistantId: 'assistant-1',
+    topicId: 'topic-1',
+    createdAt: new Date(2024, 0, 1, 0, 0, messageCounter).toISOString(),
+    status: role === 'assistant' ? AssistantMessageStatus.SUCCESS : UserMessageStatus.SUCCESS,
+    blocks: []
+  }) as MockableMessage
+
+const createFileBlock = (
+  messageId: string,
+  overrides: Partial<Omit<FileMessageBlock, 'file' | 'messageId' | 'type'>> & { file?: Partial<FileMetadata> } = {}
+): FileMessageBlock => {
+  const { file, ...blockOverrides } = overrides
+  const timestamp = new Date(2024, 0, 1, 0, 0, ++blockCounter).toISOString()
+  return {
+    id: blockOverrides.id ?? `file-block-${blockCounter}`,
+    messageId,
+    type: MessageBlockType.FILE,
+    createdAt: blockOverrides.createdAt ?? timestamp,
+    status: blockOverrides.status ?? MessageBlockStatus.SUCCESS,
+    file: {
+      id: file?.id ?? `file-${blockCounter}`,
+      name: file?.name ?? 'document.txt',
+      origin_name: file?.origin_name ?? 'document.txt',
+      path: file?.path ?? '/tmp/document.txt',
+      size: file?.size ?? 1024,
+      ext: file?.ext ?? '.txt',
+      type: file?.type ?? FileTypes.TEXT,
+      created_at: file?.created_at ?? timestamp,
+      count: file?.count ?? 1,
+      ...file
+    },
+    ...blockOverrides
+  }
+}
+
+const createImageBlock = (
+  messageId: string,
+  overrides: Partial<Omit<ImageMessageBlock, 'type' | 'messageId'>> = {}
+): ImageMessageBlock => ({
+  id: overrides.id ?? `image-block-${++blockCounter}`,
+  messageId,
+  type: MessageBlockType.IMAGE,
+  createdAt: overrides.createdAt ?? new Date(2024, 0, 1, 0, 0, blockCounter).toISOString(),
+  status: overrides.status ?? MessageBlockStatus.SUCCESS,
+  url: overrides.url ?? 'https://example.com/image.png',
+  ...overrides
+})
+
+describe('messageConverter', () => {
+  beforeEach(() => {
+    convertFileBlockToFilePartMock.mockReset()
+    convertFileBlockToTextPartMock.mockReset()
+    convertFileBlockToFilePartMock.mockResolvedValue(null)
+    convertFileBlockToTextPartMock.mockResolvedValue(null)
+    messageCounter = 0
+    blockCounter = 0
+  })
+
+  describe('convertMessageToSdkParam', () => {
+    it('includes text and image parts for user messages on vision models', async () => {
+      const model = createModel()
+      const message = createMessage('user')
+      message.__mockContent = 'Describe this picture'
+      message.__mockImageBlocks = [createImageBlock(message.id, { url: 'https://example.com/cat.png' })]
+
+      const result = await convertMessageToSdkParam(message, true, model)
+
+      expect(result).toEqual({
+        role: 'user',
+        content: [
+          { type: 'text', text: 'Describe this picture' },
+          { type: 'image', image: 'https://example.com/cat.png' }
+        ]
+      })
+    })
+
+    it('returns file instructions as a system message when native uploads succeed', async () => {
+      const model = createModel()
+      const message = createMessage('user')
+      message.__mockContent = 'Summarize the PDF'
+      message.__mockFileBlocks = [createFileBlock(message.id)]
+      convertFileBlockToFilePartMock.mockResolvedValueOnce({
+        type: 'file',
+        filename: 'document.pdf',
+        mediaType: 'application/pdf',
+        data: 'fileid://remote-file'
+      })
+
+      const result = await convertMessageToSdkParam(message, false, model)
+
+      expect(result).toEqual([
+        {
+          role: 'system',
+          content: 'fileid://remote-file'
+        },
+        {
+          role: 'user',
+          content: [{ type: 'text', text: 'Summarize the PDF' }]
+        }
+      ])
+    })
+  })
+
+  describe('convertMessagesToSdkMessages', () => {
+    it('appends assistant images to the final user message for image enhancement models', async () => {
+      const model = createModel({ id: 'qwen-image-edit', name: 'Qwen Image Edit', provider: 'qwen', group: 'qwen' })
+      const initialUser = createMessage('user')
+      initialUser.__mockContent = 'Start editing'
+
+      const assistant = createMessage('assistant')
+      assistant.__mockContent = 'Here is the current preview'
+      assistant.__mockImageBlocks = [createImageBlock(assistant.id, { url: 'https://example.com/preview.png' })]
+
+      const finalUser = createMessage('user')
+      finalUser.__mockContent = 'Increase the brightness'
+
+      const result = await convertMessagesToSdkMessages([initialUser, assistant, finalUser], model)
+
+      expect(result).toEqual([
+        {
+          role: 'assistant',
+          content: [{ type: 'text', text: 'Here is the current preview' }]
+        },
+        {
+          role: 'user',
+          content: [
+            { type: 'text', text: 'Increase the brightness' },
+            { type: 'image', image: 'https://example.com/preview.png' }
+          ]
+        }
+      ])
+    })
+
+    it('preserves preceding system instructions when building enhancement payloads', async () => {
+      const model = createModel({ id: 'qwen-image-edit', name: 'Qwen Image Edit', provider: 'qwen', group: 'qwen' })
+      const fileUser = createMessage('user')
+      fileUser.__mockContent = 'Use this document as inspiration'
+      fileUser.__mockFileBlocks = [createFileBlock(fileUser.id, { file: { ext: '.pdf', type: FileTypes.DOCUMENT } })]
+      convertFileBlockToFilePartMock.mockResolvedValueOnce({
+        type: 'file',
+        filename: 'reference.pdf',
+        mediaType: 'application/pdf',
+        data: 'fileid://reference'
+      })
+
+      const assistant = createMessage('assistant')
+      assistant.__mockContent = 'Generated previews ready'
+      assistant.__mockImageBlocks = [createImageBlock(assistant.id, { url: 'https://example.com/reference.png' })]
+
+      const finalUser = createMessage('user')
+      finalUser.__mockContent = 'Apply the edits'
+
+      const result = await convertMessagesToSdkMessages([fileUser, assistant, finalUser], model)
+
+      expect(result).toEqual([
+        { role: 'system', content: 'fileid://reference' },
+        {
+          role: 'assistant',
+          content: [{ type: 'text', text: 'Generated previews ready' }]
+        },
+        {
+          role: 'user',
+          content: [
+            { type: 'text', text: 'Apply the edits' },
+            { type: 'image', image: 'https://example.com/reference.png' }
+          ]
+        }
+      ])
+    })
+  })
+})

src/renderer/src/aiCore/prepareParams/__tests__/model-parameters.test.ts

@@ -0,0 +1,218 @@
+import type { Assistant, AssistantSettings, Model, Topic } from '@renderer/types'
+import { TopicType } from '@renderer/types'
+import { defaultTimeout } from '@shared/config/constant'
+import { describe, expect, it, vi } from 'vitest'
+
+import { getTemperature, getTimeout, getTopP } from '../modelParameters'
+
+vi.mock('@renderer/services/AssistantService', () => ({
+  getAssistantSettings: (assistant: Assistant): AssistantSettings => ({
+    contextCount: assistant.settings?.contextCount ?? 4096,
+    temperature: assistant.settings?.temperature ?? 0.7,
+    enableTemperature: assistant.settings?.enableTemperature ?? true,
+    topP: assistant.settings?.topP ?? 1,
+    enableTopP: assistant.settings?.enableTopP ?? false,
+    enableMaxTokens: assistant.settings?.enableMaxTokens ?? false,
+    maxTokens: assistant.settings?.maxTokens,
+    streamOutput: assistant.settings?.streamOutput ?? true,
+    toolUseMode: assistant.settings?.toolUseMode ?? 'prompt',
+    defaultModel: assistant.defaultModel,
+    customParameters: assistant.settings?.customParameters ?? [],
+    reasoning_effort: assistant.settings?.reasoning_effort,
+    reasoning_effort_cache: assistant.settings?.reasoning_effort_cache,
+    qwenThinkMode: assistant.settings?.qwenThinkMode
+  })
+}))
+
+vi.mock('@renderer/hooks/useSettings', () => ({
+  getStoreSetting: vi.fn(),
+  useSettings: vi.fn(() => ({})),
+  useNavbarPosition: vi.fn(() => ({ navbarPosition: 'left', isLeftNavbar: true, isTopNavbar: false }))
+}))
+
+vi.mock('@renderer/hooks/useStore', () => ({
+  getStoreProviders: vi.fn(() => [])
+}))
+
+vi.mock('@renderer/store/settings', () => ({
+  default: (state = { settings: {} }) => state
+}))
+
+vi.mock('@renderer/store/assistants', () => ({
+  default: (state = { assistants: [] }) => state
+}))
+
+const createTopic = (assistantId: string): Topic => ({
+  id: `topic-${assistantId}`,
+  assistantId,
+  name: 'topic',
+  createdAt: new Date().toISOString(),
+  updatedAt: new Date().toISOString(),
+  messages: [],
+  type: TopicType.Chat
+})
+
+const createAssistant = (settings: Assistant['settings'] = {}): Assistant => {
+  const assistantId = 'assistant-1'
+  return {
+    id: assistantId,
+    name: 'Test Assistant',
+    prompt: 'prompt',
+    topics: [createTopic(assistantId)],
+    type: 'assistant',
+    settings
+  }
+}
+
+const createModel = (overrides: Partial<Model> = {}): Model => ({
+  id: 'gpt-4o',
+  provider: 'openai',
+  name: 'GPT-4o',
+  group: 'openai',
+  ...overrides
+})
+
+describe('modelParameters', () => {
+  describe('getTemperature', () => {
+    it('returns undefined when reasoning effort is enabled for Claude models', () => {
+      const assistant = createAssistant({ reasoning_effort: 'medium' })
+      const model = createModel({ id: 'claude-opus-4', name: 'Claude Opus 4', provider: 'anthropic', group: 'claude' })
+
+      expect(getTemperature(assistant, model)).toBeUndefined()
+    })
+
+    it('returns undefined for models without temperature/topP support', () => {
+      const assistant = createAssistant({ enableTemperature: true })
+      const model = createModel({ id: 'qwen-mt-large', name: 'Qwen MT', provider: 'qwen', group: 'qwen' })
+
+      expect(getTemperature(assistant, model)).toBeUndefined()
+    })
+
+    it('returns undefined for Claude 4.5 reasoning models when only TopP is enabled', () => {
+      const assistant = createAssistant({ enableTopP: true, enableTemperature: false })
+      const model = createModel({
+        id: 'claude-sonnet-4.5',
+        name: 'Claude Sonnet 4.5',
+        provider: 'anthropic',
+        group: 'claude'
+      })
+
+      expect(getTemperature(assistant, model)).toBeUndefined()
+    })
+
+    it('returns configured temperature when enabled', () => {
+      const assistant = createAssistant({ enableTemperature: true, temperature: 0.42 })
+      const model = createModel({ id: 'gpt-4o', provider: 'openai', group: 'openai' })
+
+      expect(getTemperature(assistant, model)).toBe(0.42)
+    })
+
+    it('returns undefined when temperature is disabled', () => {
+      const assistant = createAssistant({ enableTemperature: false, temperature: 0.9 })
+      const model = createModel({ id: 'gpt-4o', provider: 'openai', group: 'openai' })
+
+      expect(getTemperature(assistant, model)).toBeUndefined()
+    })
+
+    it('clamps temperature to max 1.0 for Zhipu models', () => {
+      const assistant = createAssistant({ enableTemperature: true, temperature: 2.0 })
+      const model = createModel({ id: 'glm-4-plus', name: 'GLM-4 Plus', provider: 'zhipu', group: 'zhipu' })
+
+      expect(getTemperature(assistant, model)).toBe(1.0)
+    })
+
+    it('clamps temperature to max 1.0 for Anthropic models', () => {
+      const assistant = createAssistant({ enableTemperature: true, temperature: 1.5 })
+      const model = createModel({
+        id: 'claude-sonnet-3.5',
+        name: 'Claude 3.5 Sonnet',
+        provider: 'anthropic',
+        group: 'claude'
+      })
+
+      expect(getTemperature(assistant, model)).toBe(1.0)
+    })
+
+    it('clamps temperature to max 1.0 for Moonshot models', () => {
+      const assistant = createAssistant({ enableTemperature: true, temperature: 2.0 })
+      const model = createModel({
+        id: 'moonshot-v1-8k',
+        name: 'Moonshot v1 8k',
+        provider: 'moonshot',
+        group: 'moonshot'
+      })
+
+      expect(getTemperature(assistant, model)).toBe(1.0)
+    })
+
+    it('does not clamp temperature for OpenAI models', () => {
+      const assistant = createAssistant({ enableTemperature: true, temperature: 2.0 })
+      const model = createModel({ id: 'gpt-4o', provider: 'openai', group: 'openai' })
+
+      expect(getTemperature(assistant, model)).toBe(2.0)
+    })
+
+    it('does not clamp temperature when it is already within limits', () => {
+      const assistant = createAssistant({ enableTemperature: true, temperature: 0.8 })
+      const model = createModel({ id: 'glm-4-plus', name: 'GLM-4 Plus', provider: 'zhipu', group: 'zhipu' })
+
+      expect(getTemperature(assistant, model)).toBe(0.8)
+    })
+  })
+
+  describe('getTopP', () => {
+    it('returns undefined when reasoning effort is enabled for Claude models', () => {
+      const assistant = createAssistant({ reasoning_effort: 'high' })
+      const model = createModel({ id: 'claude-opus-4', provider: 'anthropic', group: 'claude' })
+
+      expect(getTopP(assistant, model)).toBeUndefined()
+    })
+
+    it('returns undefined for models without TopP support', () => {
+      const assistant = createAssistant({ enableTopP: true })
+      const model = createModel({ id: 'qwen-mt-small', name: 'Qwen MT', provider: 'qwen', group: 'qwen' })
+
+      expect(getTopP(assistant, model)).toBeUndefined()
+    })
+
+    it('returns undefined for Claude 4.5 reasoning models when temperature is enabled', () => {
+      const assistant = createAssistant({ enableTemperature: true })
+      const model = createModel({
+        id: 'claude-opus-4.5',
+        name: 'Claude Opus 4.5',
+        provider: 'anthropic',
+        group: 'claude'
+      })
+
+      expect(getTopP(assistant, model)).toBeUndefined()
+    })
+
+    it('returns configured TopP when enabled', () => {
+      const assistant = createAssistant({ enableTopP: true, topP: 0.73 })
+      const model = createModel({ id: 'gpt-4o', provider: 'openai', group: 'openai' })
+
+      expect(getTopP(assistant, model)).toBe(0.73)
+    })
+
+    it('returns undefined when TopP is disabled', () => {
+      const assistant = createAssistant({ enableTopP: false, topP: 0.5 })
+      const model = createModel({ id: 'gpt-4o', provider: 'openai', group: 'openai' })
+
+      expect(getTopP(assistant, model)).toBeUndefined()
+    })
+  })
+
+  describe('getTimeout', () => {
+    it('uses an extended timeout for flex service tier models', () => {
+      const model = createModel({ id: 'o3-pro', provider: 'openai', group: 'openai' })
+
+      expect(getTimeout(model)).toBe(15 * 1000 * 60)
+    })
+
+    it('falls back to the default timeout otherwise', () => {
+      const model = createModel({ id: 'gpt-4o', provider: 'openai', group: 'openai' })
+
+      expect(getTimeout(model)).toBe(defaultTimeout)
+    })
+  })
+})

src/renderer/src/aiCore/prepareParams/header.ts

@@ -1,13 +1,31 @@
-import { isClaude45ReasoningModel } from '@renderer/config/models'
+import { isClaude4SeriesModel, isClaude45ReasoningModel } from '@renderer/config/models'
+import { getProviderByModel } from '@renderer/services/AssistantService'
 import type { Assistant, Model } from '@renderer/types'
 import { isToolUseModeFunction } from '@renderer/utils/assistant'
+import { isAwsBedrockProvider, isVertexProvider } from '@renderer/utils/provider'
 
+// https://docs.claude.com/en/docs/build-with-claude/extended-thinking#interleaved-thinking
 const INTERLEAVED_THINKING_HEADER = 'interleaved-thinking-2025-05-14'
+// https://docs.claude.com/en/docs/build-with-claude/context-windows#1m-token-context-window
+const CONTEXT_100M_HEADER = 'context-1m-2025-08-07'
+// https://docs.cloud.google.com/vertex-ai/generative-ai/docs/partner-models/claude/web-search
+const WEBSEARCH_HEADER = 'web-search-2025-03-05'
 
 export function addAnthropicHeaders(assistant: Assistant, model: Model): string[] {
   const anthropicHeaders: string[] = []
-  if (isClaude45ReasoningModel(model) && isToolUseModeFunction(assistant)) {
+  const provider = getProviderByModel(model)
+  if (
+    isClaude45ReasoningModel(model) &&
+    isToolUseModeFunction(assistant) &&
+    !(isVertexProvider(provider) && isAwsBedrockProvider(provider))
+  ) {
     anthropicHeaders.push(INTERLEAVED_THINKING_HEADER)
   }
+  if (isClaude4SeriesModel(model)) {
+    if (isVertexProvider(provider) && assistant.enableWebSearch) {
+      anthropicHeaders.push(WEBSEARCH_HEADER)
+    }
+    anthropicHeaders.push(CONTEXT_100M_HEADER)
+  }
   return anthropicHeaders
 }

src/renderer/src/aiCore/prepareParams/modelCapabilities.ts

@@ -85,19 +85,6 @@ export function supportsLargeFileUpload(model: Model): boolean {
   })
 }
 
-/**
- * 检查模型是否支持TopP
- */
-export function supportsTopP(model: Model): boolean {
-  const provider = getProviderByModel(model)
-
-  if (provider?.type === 'anthropic' || model?.endpoint_type === 'anthropic') {
-    return false
-  }
-
-  return true
-}
-
 /**
  * 获取提供商特定的文件大小限制
  */

src/renderer/src/aiCore/prepareParams/modelParameters.ts

@@ -3,17 +3,27 @@
  * 处理温度、TopP、超时等基础参数的获取逻辑
  */
 
+import { DEFAULT_MAX_TOKENS } from '@renderer/config/constant'
 import {
   isClaude45ReasoningModel,
   isClaudeReasoningModel,
+  isMaxTemperatureOneModel,
   isNotSupportTemperatureAndTopP,
-  isSupportedFlexServiceTier
+  isSupportedFlexServiceTier,
+  isSupportedThinkingTokenClaudeModel
 } from '@renderer/config/models'
-import { getAssistantSettings } from '@renderer/services/AssistantService'
+import { getAssistantSettings, getProviderByModel } from '@renderer/services/AssistantService'
 import type { Assistant, Model } from '@renderer/types'
 import { defaultTimeout } from '@shared/config/constant'
 
+import { getAnthropicThinkingBudget } from '../utils/reasoning'
+
 /**
+ * Claude 4.5 推理模型:
+ * - 只启用 temperature → 使用 temperature
+ * - 只启用 top_p → 使用 top_p
+ * - 同时启用 → temperature 生效,top_p 被忽略
+ * - 都不启用 → 都不使用
  * 获取温度参数
  */
 export function getTemperature(assistant: Assistant, model: Model): number | undefined {
@@ -27,7 +37,11 @@ export function getTemperature(assistant: Assistant, model: Model): number | und
     return undefined
   }
   const assistantSettings = getAssistantSettings(assistant)
-  return assistantSettings?.enableTemperature ? assistantSettings?.temperature : undefined
+  let temperature = assistantSettings?.temperature
+  if (temperature && isMaxTemperatureOneModel(model)) {
+    temperature = Math.min(1, temperature)
+  }
+  return assistantSettings?.enableTemperature ? temperature : undefined
 }
 
 /**
@@ -56,3 +70,18 @@ export function getTimeout(model: Model): number {
   }
   return defaultTimeout
 }
+
+export function getMaxTokens(assistant: Assistant, model: Model): number | undefined {
+  // NOTE: ai-sdk会把maxToken和budgetToken加起来
+  let { maxTokens = DEFAULT_MAX_TOKENS } = getAssistantSettings(assistant)
+
+  const provider = getProviderByModel(model)
+  if (isSupportedThinkingTokenClaudeModel(model) && ['anthropic', 'aws-bedrock'].includes(provider.type)) {
+    const { reasoning_effort: reasoningEffort } = getAssistantSettings(assistant)
+    const budget = getAnthropicThinkingBudget(maxTokens, reasoningEffort, model.id)
+    if (budget) {
+      maxTokens -= budget
+    }
+  }
+  return maxTokens
+}

src/renderer/src/aiCore/prepareParams/parameterBuilder.ts

@@ -4,11 +4,12 @@
  */
 
 import { anthropic } from '@ai-sdk/anthropic'
+import { azure } from '@ai-sdk/azure'
 import { google } from '@ai-sdk/google'
 import { vertexAnthropic } from '@ai-sdk/google-vertex/anthropic/edge'
 import { vertex } from '@ai-sdk/google-vertex/edge'
 import { combineHeaders } from '@ai-sdk/provider-utils'
-import type { WebSearchPluginConfig } from '@cherrystudio/ai-core/built-in/plugins'
+import type { AnthropicSearchConfig, WebSearchPluginConfig } from '@cherrystudio/ai-core/built-in/plugins'
 import { isBaseProvider } from '@cherrystudio/ai-core/core/providers/schemas'
 import { loggerService } from '@logger'
 import {
@@ -17,13 +18,10 @@ import {
   isOpenRouterBuiltInWebSearchModel,
   isReasoningModel,
   isSupportedReasoningEffortModel,
-  isSupportedThinkingTokenClaudeModel,
   isSupportedThinkingTokenModel,
   isWebSearchModel
 } from '@renderer/config/models'
-import { isAwsBedrockProvider } from '@renderer/config/providers'
+import { getDefaultModel } from '@renderer/services/AssistantService'
-import { isVertexProvider } from '@renderer/hooks/useVertexAI'
-import { getAssistantSettings, getDefaultModel } from '@renderer/services/AssistantService'
 import store from '@renderer/store'
 import type { CherryWebSearchConfig } from '@renderer/store/websearch'
 import { type Assistant, type MCPTool, type Provider } from '@renderer/types'
@@ -36,11 +34,9 @@ import { stepCountIs } from 'ai'
 import { getAiSdkProviderId } from '../provider/factory'
 import { setupToolsConfig } from '../utils/mcp'
 import { buildProviderOptions } from '../utils/options'
-import { getAnthropicThinkingBudget } from '../utils/reasoning'
 import { buildProviderBuiltinWebSearchConfig } from '../utils/websearch'
 import { addAnthropicHeaders } from './header'
-import { supportsTopP } from './modelCapabilities'
+import { getMaxTokens, getTemperature, getTopP } from './modelParameters'
-import { getTemperature, getTopP } from './modelParameters'
 
 const logger = loggerService.withContext('parameterBuilder')
 
@@ -63,7 +59,7 @@ export async function buildStreamTextParams(
       timeout?: number
       headers?: Record<string, string>
     }
-  } = {}
+  }
 ): Promise<{
   params: StreamTextParams
   modelId: string
@@ -80,8 +76,6 @@ export async function buildStreamTextParams(
   const model = assistant.model || getDefaultModel()
   const aiSdkProviderId = getAiSdkProviderId(provider)
 
-  let { maxTokens } = getAssistantSettings(assistant)
-
   // 这三个变量透传出来，交给下面启用插件/中间件
   // 也可以在外部构建好再传入buildStreamTextParams
   // FIXME: qwen3即使关闭思考仍然会导致enableReasoning的结果为true
@@ -118,16 +112,6 @@ export async function buildStreamTextParams(
     enableGenerateImage
   })
 
-  // NOTE: ai-sdk会把maxToken和budgetToken加起来
-  if (
-    enableReasoning &&
-    maxTokens !== undefined &&
-    isSupportedThinkingTokenClaudeModel(model) &&
-    (provider.type === 'anthropic' || provider.type === 'aws-bedrock')
-  ) {
-    maxTokens -= getAnthropicThinkingBudget(assistant, model)
-  }
-
   let webSearchPluginConfig: WebSearchPluginConfig | undefined = undefined
   if (enableWebSearch) {
     if (isBaseProvider(aiSdkProviderId)) {
@@ -144,6 +128,17 @@ export async function buildStreamTextParams(
         maxUses: webSearchConfig.maxResults,
         blockedDomains: blockedDomains.length > 0 ? blockedDomains : undefined
       }) as ProviderDefinedTool
+    } else if (aiSdkProviderId === 'azure-responses') {
+      tools.web_search_preview = azure.tools.webSearchPreview({
+        searchContextSize: webSearchPluginConfig?.openai!.searchContextSize
+      }) as ProviderDefinedTool
+    } else if (aiSdkProviderId === 'azure-anthropic') {
+      const blockedDomains = mapRegexToPatterns(webSearchConfig.excludeDomains)
+      const anthropicSearchOptions: AnthropicSearchConfig = {
+        maxUses: webSearchConfig.maxResults,
+        blockedDomains: blockedDomains.length > 0 ? blockedDomains : undefined
+      }
+      tools.web_search = anthropic.tools.webSearch_20250305(anthropicSearchOptions) as ProviderDefinedTool
     }
   }
 
@@ -161,9 +156,10 @@ export async function buildStreamTextParams(
         tools.url_context = google.tools.urlContext({}) as ProviderDefinedTool
         break
       case 'anthropic':
+      case 'azure-anthropic':
       case 'google-vertex-anthropic':
         tools.web_fetch = (
-          aiSdkProviderId === 'anthropic'
+          ['anthropic', 'azure-anthropic'].includes(aiSdkProviderId)
             ? anthropic.tools.webFetch_20250910({
                 maxUses: webSearchConfig.maxResults,
                 blockedDomains: blockedDomains.length > 0 ? blockedDomains : undefined
@@ -179,8 +175,7 @@ export async function buildStreamTextParams(
 
   let headers: Record<string, string | undefined> = options.requestOptions?.headers ?? {}
 
-  // https://docs.claude.com/en/docs/build-with-claude/extended-thinking#interleaved-thinking
+  if (isAnthropicModel(model)) {
-  if (!isVertexProvider(provider) && !isAwsBedrockProvider(provider) && isAnthropicModel(model)) {
     const newBetaHeaders = { 'anthropic-beta': addAnthropicHeaders(assistant, model).join(',') }
     headers = combineHeaders(headers, newBetaHeaders)
   }
@@ -188,8 +183,9 @@ export async function buildStreamTextParams(
   // 构建基础参数
   const params: StreamTextParams = {
     messages: sdkMessages,
-    maxOutputTokens: maxTokens,
+    maxOutputTokens: getMaxTokens(assistant, model),
     temperature: getTemperature(assistant, model),
+    topP: getTopP(assistant, model),
     abortSignal: options.requestOptions?.signal,
     headers,
     providerOptions,
@@ -197,10 +193,6 @@ export async function buildStreamTextParams(
     maxRetries: 0
   }
 
-  if (supportsTopP(model)) {
-    params.topP = getTopP(assistant, model)
-  }
-
   if (tools) {
     params.tools = tools
   }

src/renderer/src/aiCore/provider/__tests__/integratedRegistry.test.ts

@@ -23,6 +23,26 @@ vi.mock('@cherrystudio/ai-core', () => ({
   }
 }))
 
+vi.mock('@renderer/services/AssistantService', () => ({
+  getProviderByModel: vi.fn(),
+  getAssistantSettings: vi.fn(),
+  getDefaultAssistant: vi.fn().mockReturnValue({
+    id: 'default',
+    name: 'Default Assistant',
+    prompt: '',
+    settings: {}
+  })
+}))
+
+vi.mock('@renderer/store/settings', () => ({
+  default: {},
+  settingsSlice: {
+    name: 'settings',
+    reducer: vi.fn(),
+    actions: {}
+  }
+}))
+
 // Mock the provider configs
 vi.mock('../providerConfigs', () => ({
   initializeNewProviders: vi.fn()

src/renderer/src/aiCore/provider/__tests__/providerConfig.test.ts

@@ -12,7 +12,14 @@ vi.mock('@renderer/services/LoggerService', () => ({
 }))
 
 vi.mock('@renderer/services/AssistantService', () => ({
-  getProviderByModel: vi.fn()
+  getProviderByModel: vi.fn(),
+  getAssistantSettings: vi.fn(),
+  getDefaultAssistant: vi.fn().mockReturnValue({
+    id: 'default',
+    name: 'Default Assistant',
+    prompt: '',
+    settings: {}
+  })
 }))
 
 vi.mock('@renderer/store', () => ({
@@ -34,7 +41,7 @@ vi.mock('@renderer/utils/api', () => ({
   }))
 }))
 
-vi.mock('@renderer/config/providers', async (importOriginal) => {
+vi.mock('@renderer/utils/provider', async (importOriginal) => {
   const actual = (await importOriginal()) as any
   return {
     ...actual,
@@ -53,10 +60,21 @@ vi.mock('@renderer/hooks/useVertexAI', () => ({
   createVertexProvider: vi.fn()
 }))
 
-import { isCherryAIProvider, isPerplexityProvider } from '@renderer/config/providers'
+vi.mock('@renderer/services/AssistantService', () => ({
+  getProviderByModel: vi.fn(),
+  getAssistantSettings: vi.fn(),
+  getDefaultAssistant: vi.fn().mockReturnValue({
+    id: 'default',
+    name: 'Default Assistant',
+    prompt: '',
+    settings: {}
+  })
+}))
+
 import { getProviderByModel } from '@renderer/services/AssistantService'
 import type { Model, Provider } from '@renderer/types'
 import { formatApiHost } from '@renderer/utils/api'
+import { isCherryAIProvider, isPerplexityProvider } from '@renderer/utils/provider'
 
 import { COPILOT_DEFAULT_HEADERS, COPILOT_EDITOR_VERSION, isCopilotResponsesModel } from '../constants'
 import { getActualProvider, providerToAiSdkConfig } from '../providerConfig'

src/renderer/src/aiCore/provider/config/azure-anthropic.ts

@@ -0,0 +1,22 @@
+import type { Provider } from '@renderer/types'
+
+import { provider2Provider, startsWith } from './helper'
+import type { RuleSet } from './types'
+
+// https://platform.claude.com/docs/en/build-with-claude/claude-in-microsoft-foundry
+const AZURE_ANTHROPIC_RULES: RuleSet = {
+  rules: [
+    {
+      match: startsWith('claude'),
+      provider: (provider: Provider) => ({
+        ...provider,
+        type: 'anthropic',
+        apiHost: provider.apiHost + 'anthropic/v1',
+        id: 'azure-anthropic'
+      })
+    }
+  ],
+  fallbackRule: (provider: Provider) => provider
+}
+
+export const azureAnthropicProviderCreator = provider2Provider.bind(null, AZURE_ANTHROPIC_RULES)

src/renderer/src/aiCore/provider/factory.ts

@@ -2,8 +2,10 @@ import { hasProviderConfigByAlias, type ProviderId, resolveProviderConfigId } fr
 import { createProvider as createProviderCore } from '@cherrystudio/ai-core/provider'
 import { loggerService } from '@logger'
 import type { Provider } from '@renderer/types'
+import { isAzureOpenAIProvider, isAzureResponsesEndpoint } from '@renderer/utils/provider'
 import type { Provider as AiSdkProvider } from 'ai'
 
+import type { AiSdkConfig } from '../types'
 import { initializeNewProviders } from './providerInitialization'
 
 const logger = loggerService.withContext('ProviderFactory')
@@ -55,9 +57,12 @@ function tryResolveProviderId(identifier: string): ProviderId | null {
  * 获取AI SDK Provider ID
  * 简化版：减少重复逻辑，利用通用解析函数
  */
-export function getAiSdkProviderId(provider: Provider): ProviderId | 'openai-compatible' {
+export function getAiSdkProviderId(provider: Provider): string {
   // 1. 尝试解析provider.id
   const resolvedFromId = tryResolveProviderId(provider.id)
+  if (isAzureOpenAIProvider(provider) && isAzureResponsesEndpoint(provider)) {
+    return 'azure-responses'
+  }
   if (resolvedFromId) {
     return resolvedFromId
   }
@@ -73,11 +78,11 @@ export function getAiSdkProviderId(provider: Provider): ProviderId | 'openai-com
   if (provider.apiHost.includes('api.openai.com')) {
     return 'openai-chat'
   }
-  // 3. 最后的fallback（通常会成为openai-compatible）
+  // 3. 最后的fallback（使用provider本身的id）
-  return provider.id as ProviderId
+  return provider.id
 }
 
-export async function createAiSdkProvider(config) {
+export async function createAiSdkProvider(config: AiSdkConfig): Promise<AiSdkProvider | null> {
   let localProvider: Awaited<AiSdkProvider> | null = null
   try {
     if (config.providerId === 'openai' && config.options?.mode === 'chat') {

src/renderer/src/aiCore/provider/providerConfig.ts

@@ -1,20 +1,6 @@
-import {
+import { formatPrivateKey, hasProviderConfig, ProviderConfigFactory } from '@cherrystudio/ai-core/provider'
-  formatPrivateKey,
-  hasProviderConfig,
-  ProviderConfigFactory,
-  type ProviderId,
-  type ProviderSettingsMap
-} from '@cherrystudio/ai-core/provider'
 import { cacheService } from '@data/CacheService'
 import { isOpenAIChatCompletionOnlyModel } from '@renderer/config/models'
-import {
-  isAnthropicProvider,
-  isAzureOpenAIProvider,
-  isCherryAIProvider,
-  isGeminiProvider,
-  isNewApiProvider,
-  isPerplexityProvider
-} from '@renderer/config/providers'
 import {
   getAwsBedrockAccessKeyId,
   getAwsBedrockApiKey,
@@ -22,14 +8,25 @@ import {
   getAwsBedrockRegion,
   getAwsBedrockSecretAccessKey
 } from '@renderer/hooks/useAwsBedrock'
-import { createVertexProvider, isVertexAIConfigured, isVertexProvider } from '@renderer/hooks/useVertexAI'
+import { createVertexProvider, isVertexAIConfigured } from '@renderer/hooks/useVertexAI'
 import { getProviderByModel } from '@renderer/services/AssistantService'
 import store from '@renderer/store'
 import { isSystemProvider, type Model, type Provider, SystemProviderIds } from '@renderer/types'
 import { formatApiHost, formatAzureOpenAIApiHost, formatVertexApiHost, routeToEndpoint } from '@renderer/utils/api'
+import {
+  isAnthropicProvider,
+  isAzureOpenAIProvider,
+  isCherryAIProvider,
+  isGeminiProvider,
+  isNewApiProvider,
+  isPerplexityProvider,
+  isVertexProvider
+} from '@renderer/utils/provider'
 import { cloneDeep } from 'lodash'
 
+import type { AiSdkConfig } from '../types'
 import { aihubmixProviderCreator, newApiResolverCreator, vertexAnthropicProviderCreator } from './config'
+import { azureAnthropicProviderCreator } from './config/azure-anthropic'
 import { COPILOT_DEFAULT_HEADERS } from './constants'
 import { getAiSdkProviderId } from './factory'
 
@@ -75,6 +72,9 @@ function handleSpecialProviders(model: Model, provider: Provider): Provider {
       return vertexAnthropicProviderCreator(model, provider)
     }
   }
+  if (isAzureOpenAIProvider(provider)) {
+    return azureAnthropicProviderCreator(model, provider)
+  }
   return provider
 }
 
@@ -132,13 +132,7 @@ export function getActualProvider(model: Model): Provider {
  * 将 Provider 配置转换为新 AI SDK 格式
  * 简化版：利用新的别名映射系统
  */
-export function providerToAiSdkConfig(
+export function providerToAiSdkConfig(actualProvider: Provider, model: Model): AiSdkConfig {
-  actualProvider: Provider,
-  model: Model
-): {
-  providerId: ProviderId | 'openai-compatible'
-  options: ProviderSettingsMap[keyof ProviderSettingsMap]
-} {
   const aiSdkProviderId = getAiSdkProviderId(actualProvider)
 
   // 构建基础配置
@@ -192,13 +186,10 @@ export function providerToAiSdkConfig(
   // azure
   // https://learn.microsoft.com/en-us/azure/ai-foundry/openai/latest
   // https://learn.microsoft.com/en-us/azure/ai-foundry/openai/how-to/responses?tabs=python-key#responses-api
-  if (aiSdkProviderId === 'azure' || actualProvider.type === 'azure-openai') {
+  if (aiSdkProviderId === 'azure-responses') {
-    // extraOptions.apiVersion = actualProvider.apiVersion === 'preview' ? 'v1' : actualProvider.apiVersion 默认使用v1，不使用azure endpoint
+    extraOptions.mode = 'responses'
-    if (actualProvider.apiVersion === 'preview' || actualProvider.apiVersion === 'v1') {
+  } else if (aiSdkProviderId === 'azure') {
-      extraOptions.mode = 'responses'
+    extraOptions.mode = 'chat'
-    } else {
-      extraOptions.mode = 'chat'
-    }
   }
 
   // bedrock
@@ -238,7 +229,7 @@ export function providerToAiSdkConfig(
   if (hasProviderConfig(aiSdkProviderId) && aiSdkProviderId !== 'openai-compatible') {
     const options = ProviderConfigFactory.fromProvider(aiSdkProviderId, baseConfig, extraOptions)
     return {
-      providerId: aiSdkProviderId as ProviderId,
+      providerId: aiSdkProviderId,
       options
     }
   }

src/renderer/src/aiCore/provider/providerInitialization.ts

@@ -32,6 +32,14 @@ export const NEW_PROVIDER_CONFIGS: ProviderConfig[] = [
     supportsImageGeneration: true,
     aliases: ['vertexai-anthropic']
   },
+  {
+    id: 'azure-anthropic',
+    name: 'Azure AI Anthropic',
+    import: () => import('@ai-sdk/anthropic'),
+    creatorFunctionName: 'createAnthropic',
+    supportsImageGeneration: false,
+    aliases: ['azure-anthropic']
+  },
   {
     id: 'github-copilot-openai-compatible',
     name: 'GitHub Copilot OpenAI Compatible',

src/renderer/src/aiCore/trace/AiSdkSpanAdapter.ts

@@ -133,7 +133,7 @@ export class AiSdkSpanAdapter {
 
     // 详细记录转换过程
     const operationId = attributes['ai.operationId']
-    logger.info('Converting AI SDK span to SpanEntity', {
+    logger.debug('Converting AI SDK span to SpanEntity', {
       spanName: spanName,
       operationId,
       spanTag,
@@ -149,7 +149,7 @@ export class AiSdkSpanAdapter {
     })
 
     if (tokenUsage) {
-      logger.info('Token usage data found', {
+      logger.debug('Token usage data found', {
         spanName: spanName,
         operationId,
         usage: tokenUsage,
@@ -158,7 +158,7 @@ export class AiSdkSpanAdapter {
     }
 
     if (inputs || outputs) {
-      logger.info('Input/Output data extracted', {
+      logger.debug('Input/Output data extracted', {
         spanName: spanName,
         operationId,
         hasInputs: !!inputs,
@@ -170,7 +170,7 @@ export class AiSdkSpanAdapter {
     }
 
     if (Object.keys(typeSpecificData).length > 0) {
-      logger.info('Type-specific data extracted', {
+      logger.debug('Type-specific data extracted', {
         spanName: spanName,
         operationId,
         typeSpecificKeys: Object.keys(typeSpecificData),
@@ -204,7 +204,7 @@ export class AiSdkSpanAdapter {
       modelName: modelName || this.extractModelFromAttributes(attributes)
     }
 
-    logger.info('AI SDK span successfully converted to SpanEntity', {
+    logger.debug('AI SDK span successfully converted to SpanEntity', {
       spanName: spanName,
       operationId,
       spanId: spanContext.spanId,

src/renderer/src/aiCore/types/index.ts

@@ -0,0 +1,15 @@
+/**
+ * This type definition file is only for renderer.
+ * It cannot be migrated to @renderer/types since files within it are actually being used by both main and renderer.
+ * If we do that, main would throw an error because it cannot import a module which imports a type from a browser-enviroment-only package.
+ * (ai-core package is set as browser-enviroment-only)
+ *
+ * TODO: We should separate them clearly. Keep renderer only types in renderer, and main only types in main, and shared types in shared.
+ */
+
+import type { ProviderSettingsMap } from '@cherrystudio/ai-core/provider'
+
+export type AiSdkConfig = {
+  providerId: string
+  options: ProviderSettingsMap[keyof ProviderSettingsMap]
+}

src/renderer/src/aiCore/utils/__tests__/image.test.ts

@@ -0,0 +1,121 @@
+/**
+ * image.ts Unit Tests
+ * Tests for Gemini image generation utilities
+ */
+
+import type { Model, Provider } from '@renderer/types'
+import { SystemProviderIds } from '@renderer/types'
+import { describe, expect, it } from 'vitest'
+
+import { buildGeminiGenerateImageParams, isOpenRouterGeminiGenerateImageModel } from '../image'
+
+describe('image utils', () => {
+  describe('buildGeminiGenerateImageParams', () => {
+    it('should return correct response modalities', () => {
+      const result = buildGeminiGenerateImageParams()
+
+      expect(result).toEqual({
+        responseModalities: ['TEXT', 'IMAGE']
+      })
+    })
+
+    it('should return an object with responseModalities property', () => {
+      const result = buildGeminiGenerateImageParams()
+
+      expect(result).toHaveProperty('responseModalities')
+      expect(Array.isArray(result.responseModalities)).toBe(true)
+      expect(result.responseModalities).toHaveLength(2)
+    })
+  })
+
+  describe('isOpenRouterGeminiGenerateImageModel', () => {
+    const mockOpenRouterProvider: Provider = {
+      id: SystemProviderIds.openrouter,
+      name: 'OpenRouter',
+      apiKey: 'test-key',
+      apiHost: 'https://openrouter.ai/api/v1',
+      isSystem: true
+    } as Provider
+
+    const mockOtherProvider: Provider = {
+      id: SystemProviderIds.openai,
+      name: 'OpenAI',
+      apiKey: 'test-key',
+      apiHost: 'https://api.openai.com/v1',
+      isSystem: true
+    } as Provider
+
+    it('should return true for OpenRouter Gemini 2.5 Flash Image model', () => {
+      const model: Model = {
+        id: 'google/gemini-2.5-flash-image-preview',
+        name: 'Gemini 2.5 Flash Image',
+        provider: SystemProviderIds.openrouter
+      } as Model
+
+      const result = isOpenRouterGeminiGenerateImageModel(model, mockOpenRouterProvider)
+      expect(result).toBe(true)
+    })
+
+    it('should return false for non-Gemini model on OpenRouter', () => {
+      const model: Model = {
+        id: 'openai/gpt-4',
+        name: 'GPT-4',
+        provider: SystemProviderIds.openrouter
+      } as Model
+
+      const result = isOpenRouterGeminiGenerateImageModel(model, mockOpenRouterProvider)
+      expect(result).toBe(false)
+    })
+
+    it('should return false for Gemini model on non-OpenRouter provider', () => {
+      const model: Model = {
+        id: 'gemini-2.5-flash-image-preview',
+        name: 'Gemini 2.5 Flash Image',
+        provider: SystemProviderIds.gemini
+      } as Model
+
+      const result = isOpenRouterGeminiGenerateImageModel(model, mockOtherProvider)
+      expect(result).toBe(false)
+    })
+
+    it('should return false for Gemini model without image suffix', () => {
+      const model: Model = {
+        id: 'google/gemini-2.5-flash',
+        name: 'Gemini 2.5 Flash',
+        provider: SystemProviderIds.openrouter
+      } as Model
+
+      const result = isOpenRouterGeminiGenerateImageModel(model, mockOpenRouterProvider)
+      expect(result).toBe(false)
+    })
+
+    it('should handle model ID with partial match', () => {
+      const model: Model = {
+        id: 'google/gemini-2.5-flash-image-generation',
+        name: 'Gemini Image Gen',
+        provider: SystemProviderIds.openrouter
+      } as Model
+
+      const result = isOpenRouterGeminiGenerateImageModel(model, mockOpenRouterProvider)
+      expect(result).toBe(true)
+    })
+
+    it('should return false for custom provider', () => {
+      const customProvider: Provider = {
+        id: 'custom-provider-123',
+        name: 'Custom Provider',
+        apiKey: 'test-key',
+        apiHost: 'https://custom.com'
+      } as Provider
+
+      const model: Model = {
+        id: 'gemini-2.5-flash-image-preview',
+        name: 'Gemini 2.5 Flash Image',
+        provider: 'custom-provider-123'
+      } as Model
+
+      const result = isOpenRouterGeminiGenerateImageModel(model, customProvider)
+      expect(result).toBe(false)
+    })
+  })
+})

src/renderer/src/aiCore/utils/__tests__/mcp.test.ts

@@ -0,0 +1,435 @@
+/**
+ * mcp.ts Unit Tests
+ * Tests for MCP tools configuration and conversion utilities
+ */
+
+import type { MCPTool } from '@renderer/types'
+import type { Tool } from 'ai'
+import { beforeEach, describe, expect, it, vi } from 'vitest'
+
+import { convertMcpToolsToAiSdkTools, setupToolsConfig } from '../mcp'
+
+// Mock dependencies
+vi.mock('@logger', () => ({
+  loggerService: {
+    withContext: () => ({
+      debug: vi.fn(),
+      error: vi.fn(),
+      warn: vi.fn(),
+      info: vi.fn()
+    })
+  }
+}))
+
+vi.mock('@renderer/utils/mcp-tools', () => ({
+  getMcpServerByTool: vi.fn(() => ({ id: 'test-server', autoApprove: false })),
+  isToolAutoApproved: vi.fn(() => false),
+  callMCPTool: vi.fn(async () => ({
+    content: [{ type: 'text', text: 'Tool executed successfully' }],
+    isError: false
+  }))
+}))
+
+vi.mock('@renderer/utils/userConfirmation', () => ({
+  requestToolConfirmation: vi.fn(async () => true)
+}))
+
+describe('mcp utils', () => {
+  beforeEach(() => {
+    vi.clearAllMocks()
+  })
+
+  describe('setupToolsConfig', () => {
+    it('should return undefined when no MCP tools provided', () => {
+      const result = setupToolsConfig()
+      expect(result).toBeUndefined()
+    })
+
+    it('should return undefined when empty MCP tools array provided', () => {
+      const result = setupToolsConfig([])
+      expect(result).toBeUndefined()
+    })
+
+    it('should convert MCP tools to AI SDK tools format', () => {
+      const mcpTools: MCPTool[] = [
+        {
+          id: 'test-tool-1',
+          serverId: 'test-server',
+          serverName: 'test-server',
+          name: 'test-tool',
+          description: 'A test tool',
+          type: 'mcp',
+          inputSchema: {
+            type: 'object',
+            properties: {
+              query: { type: 'string' }
+            }
+          }
+        }
+      ]
+
+      const result = setupToolsConfig(mcpTools)
+
+      expect(result).not.toBeUndefined()
+      expect(Object.keys(result!)).toEqual(['test-tool'])
+      expect(result!['test-tool']).toHaveProperty('description')
+      expect(result!['test-tool']).toHaveProperty('inputSchema')
+      expect(result!['test-tool']).toHaveProperty('execute')
+    })
+
+    it('should handle multiple MCP tools', () => {
+      const mcpTools: MCPTool[] = [
+        {
+          id: 'tool1-id',
+          serverId: 'server1',
+          serverName: 'server1',
+          name: 'tool1',
+          description: 'First tool',
+          type: 'mcp',
+          inputSchema: {
+            type: 'object',
+            properties: {}
+          }
+        },
+        {
+          id: 'tool2-id',
+          serverId: 'server2',
+          serverName: 'server2',
+          name: 'tool2',
+          description: 'Second tool',
+          type: 'mcp',
+          inputSchema: {
+            type: 'object',
+            properties: {}
+          }
+        }
+      ]
+
+      const result = setupToolsConfig(mcpTools)
+
+      expect(result).not.toBeUndefined()
+      expect(Object.keys(result!)).toHaveLength(2)
+      expect(Object.keys(result!)).toEqual(['tool1', 'tool2'])
+    })
+  })
+
+  describe('convertMcpToolsToAiSdkTools', () => {
+    it('should convert single MCP tool to AI SDK tool', () => {
+      const mcpTools: MCPTool[] = [
+        {
+          id: 'get-weather-id',
+          serverId: 'weather-server',
+          serverName: 'weather-server',
+          name: 'get-weather',
+          description: 'Get weather information',
+          type: 'mcp',
+          inputSchema: {
+            type: 'object',
+            properties: {
+              location: { type: 'string' }
+            },
+            required: ['location']
+          }
+        }
+      ]
+
+      const result = convertMcpToolsToAiSdkTools(mcpTools)
+
+      expect(Object.keys(result)).toEqual(['get-weather'])
+
+      const tool = result['get-weather'] as Tool
+      expect(tool.description).toBe('Get weather information')
+      expect(tool.inputSchema).toBeDefined()
+      expect(typeof tool.execute).toBe('function')
+    })
+
+    it('should handle tool without description', () => {
+      const mcpTools: MCPTool[] = [
+        {
+          id: 'no-desc-tool-id',
+          serverId: 'test-server',
+          serverName: 'test-server',
+          name: 'no-desc-tool',
+          type: 'mcp',
+          inputSchema: {
+            type: 'object',
+            properties: {}
+          }
+        }
+      ]
+
+      const result = convertMcpToolsToAiSdkTools(mcpTools)
+
+      expect(Object.keys(result)).toEqual(['no-desc-tool'])
+      const tool = result['no-desc-tool'] as Tool
+      expect(tool.description).toBe('Tool from test-server')
+    })
+
+    it('should convert empty tools array', () => {
+      const result = convertMcpToolsToAiSdkTools([])
+      expect(result).toEqual({})
+    })
+
+    it('should handle complex input schemas', () => {
+      const mcpTools: MCPTool[] = [
+        {
+          id: 'complex-tool-id',
+          serverId: 'server',
+          serverName: 'server',
+          name: 'complex-tool',
+          description: 'Tool with complex schema',
+          type: 'mcp',
+          inputSchema: {
+            type: 'object',
+            properties: {
+              name: { type: 'string' },
+              age: { type: 'number' },
+              tags: {
+                type: 'array',
+                items: { type: 'string' }
+              },
+              metadata: {
+                type: 'object',
+                properties: {
+                  key: { type: 'string' }
+                }
+              }
+            },
+            required: ['name']
+          }
+        }
+      ]
+
+      const result = convertMcpToolsToAiSdkTools(mcpTools)
+
+      expect(Object.keys(result)).toEqual(['complex-tool'])
+      const tool = result['complex-tool'] as Tool
+      expect(tool.inputSchema).toBeDefined()
+      expect(typeof tool.execute).toBe('function')
+    })
+
+    it('should preserve tool names with special characters', () => {
+      const mcpTools: MCPTool[] = [
+        {
+          id: 'special-tool-id',
+          serverId: 'server',
+          serverName: 'server',
+          name: 'tool_with-special.chars',
+          description: 'Special chars tool',
+          type: 'mcp',
+          inputSchema: {
+            type: 'object',
+            properties: {}
+          }
+        }
+      ]
+
+      const result = convertMcpToolsToAiSdkTools(mcpTools)
+      expect(Object.keys(result)).toEqual(['tool_with-special.chars'])
+    })
+
+    it('should handle multiple tools with different schemas', () => {
+      const mcpTools: MCPTool[] = [
+        {
+          id: 'string-tool-id',
+          serverId: 'server1',
+          serverName: 'server1',
+          name: 'string-tool',
+          description: 'String tool',
+          type: 'mcp',
+          inputSchema: {
+            type: 'object',
+            properties: {
+              input: { type: 'string' }
+            }
+          }
+        },
+        {
+          id: 'number-tool-id',
+          serverId: 'server2',
+          serverName: 'server2',
+          name: 'number-tool',
+          description: 'Number tool',
+          type: 'mcp',
+          inputSchema: {
+            type: 'object',
+            properties: {
+              count: { type: 'number' }
+            }
+          }
+        },
+        {
+          id: 'boolean-tool-id',
+          serverId: 'server3',
+          serverName: 'server3',
+          name: 'boolean-tool',
+          description: 'Boolean tool',
+          type: 'mcp',
+          inputSchema: {
+            type: 'object',
+            properties: {
+              enabled: { type: 'boolean' }
+            }
+          }
+        }
+      ]
+
+      const result = convertMcpToolsToAiSdkTools(mcpTools)
+
+      expect(Object.keys(result).sort()).toEqual(['boolean-tool', 'number-tool', 'string-tool'])
+      expect(result['string-tool']).toBeDefined()
+      expect(result['number-tool']).toBeDefined()
+      expect(result['boolean-tool']).toBeDefined()
+    })
+  })
+
+  describe('tool execution', () => {
+    it('should execute tool with user confirmation', async () => {
+      const { callMCPTool } = await import('@renderer/utils/mcp-tools')
+      const { requestToolConfirmation } = await import('@renderer/utils/userConfirmation')
+
+      vi.mocked(requestToolConfirmation).mockResolvedValue(true)
+      vi.mocked(callMCPTool).mockResolvedValue({
+        content: [{ type: 'text', text: 'Success' }],
+        isError: false
+      })
+
+      const mcpTools: MCPTool[] = [
+        {
+          id: 'test-exec-tool-id',
+          serverId: 'test-server',
+          serverName: 'test-server',
+          name: 'test-exec-tool',
+          description: 'Test execution tool',
+          type: 'mcp',
+          inputSchema: {
+            type: 'object',
+            properties: {}
+          }
+        }
+      ]
+
+      const tools = convertMcpToolsToAiSdkTools(mcpTools)
+      const tool = tools['test-exec-tool'] as Tool
+      const result = await tool.execute!({}, { messages: [], abortSignal: undefined, toolCallId: 'test-call-123' })
+
+      expect(requestToolConfirmation).toHaveBeenCalled()
+      expect(callMCPTool).toHaveBeenCalled()
+      expect(result).toEqual({
+        content: [{ type: 'text', text: 'Success' }],
+        isError: false
+      })
+    })
+
+    it('should handle user cancellation', async () => {
+      const { requestToolConfirmation } = await import('@renderer/utils/userConfirmation')
+      const { callMCPTool } = await import('@renderer/utils/mcp-tools')
+
+      vi.mocked(requestToolConfirmation).mockResolvedValue(false)
+
+      const mcpTools: MCPTool[] = [
+        {
+          id: 'cancelled-tool-id',
+          serverId: 'test-server',
+          serverName: 'test-server',
+          name: 'cancelled-tool',
+          description: 'Tool to cancel',
+          type: 'mcp',
+          inputSchema: {
+            type: 'object',
+            properties: {}
+          }
+        }
+      ]
+
+      const tools = convertMcpToolsToAiSdkTools(mcpTools)
+      const tool = tools['cancelled-tool'] as Tool
+      const result = await tool.execute!({}, { messages: [], abortSignal: undefined, toolCallId: 'cancel-call-123' })
+
+      expect(requestToolConfirmation).toHaveBeenCalled()
+      expect(callMCPTool).not.toHaveBeenCalled()
+      expect(result).toEqual({
+        content: [
+          {
+            type: 'text',
+            text: 'User declined to execute tool "cancelled-tool".'
+          }
+        ],
+        isError: false
+      })
+    })
+
+    it('should handle tool execution error', async () => {
+      const { callMCPTool } = await import('@renderer/utils/mcp-tools')
+      const { requestToolConfirmation } = await import('@renderer/utils/userConfirmation')
+
+      vi.mocked(requestToolConfirmation).mockResolvedValue(true)
+      vi.mocked(callMCPTool).mockResolvedValue({
+        content: [{ type: 'text', text: 'Error occurred' }],
+        isError: true
+      })
+
+      const mcpTools: MCPTool[] = [
+        {
+          id: 'error-tool-id',
+          serverId: 'test-server',
+          serverName: 'test-server',
+          name: 'error-tool',
+          description: 'Tool that errors',
+          type: 'mcp',
+          inputSchema: {
+            type: 'object',
+            properties: {}
+          }
+        }
+      ]
+
+      const tools = convertMcpToolsToAiSdkTools(mcpTools)
+      const tool = tools['error-tool'] as Tool
+
+      await expect(
+        tool.execute!({}, { messages: [], abortSignal: undefined, toolCallId: 'error-call-123' })
+      ).rejects.toEqual({
+        content: [{ type: 'text', text: 'Error occurred' }],
+        isError: true
+      })
+    })
+
+    it('should auto-approve when enabled', async () => {
+      const { callMCPTool, isToolAutoApproved } = await import('@renderer/utils/mcp-tools')
+      const { requestToolConfirmation } = await import('@renderer/utils/userConfirmation')
+
+      vi.mocked(isToolAutoApproved).mockReturnValue(true)
+      vi.mocked(callMCPTool).mockResolvedValue({
+        content: [{ type: 'text', text: 'Auto-approved success' }],
+        isError: false
+      })
+
+      const mcpTools: MCPTool[] = [
+        {
+          id: 'auto-approve-tool-id',
+          serverId: 'test-server',
+          serverName: 'test-server',
+          name: 'auto-approve-tool',
+          description: 'Auto-approved tool',
+          type: 'mcp',
+          inputSchema: {
+            type: 'object',
+            properties: {}
+          }
+        }
+      ]
+
+      const tools = convertMcpToolsToAiSdkTools(mcpTools)
+      const tool = tools['auto-approve-tool'] as Tool
+      const result = await tool.execute!({}, { messages: [], abortSignal: undefined, toolCallId: 'auto-call-123' })
+
+      expect(requestToolConfirmation).not.toHaveBeenCalled()
+      expect(callMCPTool).toHaveBeenCalled()
+      expect(result).toEqual({
+        content: [{ type: 'text', text: 'Auto-approved success' }],
+        isError: false
+      })
+    })
+  })
+})

src/renderer/src/aiCore/utils/__tests__/options.test.ts

@@ -0,0 +1,545 @@
+/**
+ * options.ts Unit Tests
+ * Tests for building provider-specific options
+ */
+
+import type { Assistant, Model, Provider } from '@renderer/types'
+import { OpenAIServiceTiers, SystemProviderIds } from '@renderer/types'
+import { beforeEach, describe, expect, it, vi } from 'vitest'
+
+import { buildProviderOptions } from '../options'
+
+// Mock dependencies
+vi.mock('@cherrystudio/ai-core/provider', async (importOriginal) => {
+  const actual = (await importOriginal()) as object
+  return {
+    ...actual,
+    baseProviderIdSchema: {
+      safeParse: vi.fn((id) => {
+        const baseProviders = [
+          'openai',
+          'openai-chat',
+          'azure',
+          'azure-responses',
+          'huggingface',
+          'anthropic',
+          'google',
+          'xai',
+          'deepseek',
+          'openrouter',
+          'openai-compatible'
+        ]
+        if (baseProviders.includes(id)) {
+          return { success: true, data: id }
+        }
+        return { success: false }
+      })
+    },
+    customProviderIdSchema: {
+      safeParse: vi.fn((id) => {
+        const customProviders = ['google-vertex', 'google-vertex-anthropic', 'bedrock']
+        if (customProviders.includes(id)) {
+          return { success: true, data: id }
+        }
+        return { success: false, error: new Error('Invalid provider') }
+      })
+    }
+  }
+})
+
+vi.mock('../provider/factory', () => ({
+  getAiSdkProviderId: vi.fn((provider) => {
+    // Simulate the provider ID mapping
+    const mapping: Record<string, string> = {
+      [SystemProviderIds.gemini]: 'google',
+      [SystemProviderIds.openai]: 'openai',
+      [SystemProviderIds.anthropic]: 'anthropic',
+      [SystemProviderIds.grok]: 'xai',
+      [SystemProviderIds.deepseek]: 'deepseek',
+      [SystemProviderIds.openrouter]: 'openrouter'
+    }
+    return mapping[provider.id] || provider.id
+  })
+}))
+
+vi.mock('@renderer/config/models', async (importOriginal) => ({
+  ...(await importOriginal()),
+  isOpenAIModel: vi.fn((model) => model.id.includes('gpt') || model.id.includes('o1')),
+  isQwenMTModel: vi.fn(() => false),
+  isSupportFlexServiceTierModel: vi.fn(() => true),
+  isOpenAILLMModel: vi.fn(() => true),
+  SYSTEM_MODELS: {
+    defaultModel: [
+      { id: 'default-1', name: 'Default 1' },
+      { id: 'default-2', name: 'Default 2' },
+      { id: 'default-3', name: 'Default 3' }
+    ]
+  }
+}))
+
+vi.mock(import('@renderer/utils/provider'), async (importOriginal) => {
+  return {
+    ...(await importOriginal()),
+    isSupportServiceTierProvider: vi.fn((provider) => {
+      return [SystemProviderIds.openai, SystemProviderIds.groq].includes(provider.id)
+    })
+  }
+})
+
+vi.mock('@renderer/store/settings', () => ({
+  default: (state = { settings: {} }) => state
+}))
+
+vi.mock('@renderer/hooks/useSettings', () => ({
+  getStoreSetting: vi.fn((key) => {
+    if (key === 'openAI') {
+      return { summaryText: 'off', verbosity: 'medium' } as any
+    }
+    return {}
+  })
+}))
+
+vi.mock('@renderer/services/AssistantService', () => ({
+  getDefaultAssistant: vi.fn(() => ({
+    id: 'default',
+    name: 'Default Assistant',
+    settings: {}
+  })),
+  getAssistantSettings: vi.fn(() => ({
+    reasoning_effort: 'medium',
+    maxTokens: 4096
+  })),
+  getProviderByModel: vi.fn((model: Model) => ({
+    id: model.provider,
+    name: 'Mock Provider'
+  }))
+}))
+
+vi.mock('../reasoning', () => ({
+  getOpenAIReasoningParams: vi.fn(() => ({ reasoningEffort: 'medium' })),
+  getAnthropicReasoningParams: vi.fn(() => ({
+    thinking: { type: 'enabled', budgetTokens: 5000 }
+  })),
+  getGeminiReasoningParams: vi.fn(() => ({
+    thinkingConfig: { include_thoughts: true }
+  })),
+  getXAIReasoningParams: vi.fn(() => ({ reasoningEffort: 'high' })),
+  getBedrockReasoningParams: vi.fn(() => ({
+    reasoningConfig: { type: 'enabled', budgetTokens: 5000 }
+  })),
+  getReasoningEffort: vi.fn(() => ({ reasoningEffort: 'medium' })),
+  getCustomParameters: vi.fn(() => ({}))
+}))
+
+vi.mock('../image', () => ({
+  buildGeminiGenerateImageParams: vi.fn(() => ({
+    responseModalities: ['TEXT', 'IMAGE']
+  }))
+}))
+
+vi.mock('../websearch', () => ({
+  getWebSearchParams: vi.fn(() => ({ enable_search: true }))
+}))
+
+const ensureWindowApi = () => {
+  const globalWindow = window as any
+  globalWindow.api = globalWindow.api || {}
+  globalWindow.api.getAppInfo = globalWindow.api.getAppInfo || vi.fn(async () => ({ notesPath: '' }))
+}
+
+ensureWindowApi()
+
+describe('options utils', () => {
+  const mockAssistant: Assistant = {
+    id: 'test-assistant',
+    name: 'Test Assistant',
+    settings: {}
+  } as Assistant
+
+  const mockModel: Model = {
+    id: 'gpt-4',
+    name: 'GPT-4',
+    provider: SystemProviderIds.openai
+  } as Model
+
+  beforeEach(() => {
+    vi.clearAllMocks()
+  })
+
+  describe('buildProviderOptions', () => {
+    describe('OpenAI provider', () => {
+      const openaiProvider: Provider = {
+        id: SystemProviderIds.openai,
+        name: 'OpenAI',
+        type: 'openai-response',
+        apiKey: 'test-key',
+        apiHost: 'https://api.openai.com/v1',
+        isSystem: true
+      } as Provider
+
+      it('should build basic OpenAI options', () => {
+        const result = buildProviderOptions(mockAssistant, mockModel, openaiProvider, {
+          enableReasoning: false,
+          enableWebSearch: false,
+          enableGenerateImage: false
+        })
+
+        expect(result).toHaveProperty('openai')
+        expect(result.openai).toBeDefined()
+      })
+
+      it('should include reasoning parameters when enabled', () => {
+        const result = buildProviderOptions(mockAssistant, mockModel, openaiProvider, {
+          enableReasoning: true,
+          enableWebSearch: false,
+          enableGenerateImage: false
+        })
+
+        expect(result.openai).toHaveProperty('reasoningEffort')
+        expect(result.openai.reasoningEffort).toBe('medium')
+      })
+
+      it('should include service tier when supported', () => {
+        const providerWithServiceTier: Provider = {
+          ...openaiProvider,
+          serviceTier: OpenAIServiceTiers.auto
+        }
+
+        const result = buildProviderOptions(mockAssistant, mockModel, providerWithServiceTier, {
+          enableReasoning: false,
+          enableWebSearch: false,
+          enableGenerateImage: false
+        })
+
+        expect(result.openai).toHaveProperty('serviceTier')
+        expect(result.openai.serviceTier).toBe(OpenAIServiceTiers.auto)
+      })
+    })
+
+    describe('Anthropic provider', () => {
+      const anthropicProvider: Provider = {
+        id: SystemProviderIds.anthropic,
+        name: 'Anthropic',
+        type: 'anthropic',
+        apiKey: 'test-key',
+        apiHost: 'https://api.anthropic.com',
+        isSystem: true
+      } as Provider
+
+      const anthropicModel: Model = {
+        id: 'claude-3-5-sonnet-20241022',
+        name: 'Claude 3.5 Sonnet',
+        provider: SystemProviderIds.anthropic
+      } as Model
+
+      it('should build basic Anthropic options', () => {
+        const result = buildProviderOptions(mockAssistant, anthropicModel, anthropicProvider, {
+          enableReasoning: false,
+          enableWebSearch: false,
+          enableGenerateImage: false
+        })
+
+        expect(result).toHaveProperty('anthropic')
+        expect(result.anthropic).toBeDefined()
+      })
+
+      it('should include reasoning parameters when enabled', () => {
+        const result = buildProviderOptions(mockAssistant, anthropicModel, anthropicProvider, {
+          enableReasoning: true,
+          enableWebSearch: false,
+          enableGenerateImage: false
+        })
+
+        expect(result.anthropic).toHaveProperty('thinking')
+        expect(result.anthropic.thinking).toEqual({
+          type: 'enabled',
+          budgetTokens: 5000
+        })
+      })
+    })
+
+    describe('Google provider', () => {
+      const googleProvider: Provider = {
+        id: SystemProviderIds.gemini,
+        name: 'Google',
+        type: 'gemini',
+        apiKey: 'test-key',
+        apiHost: 'https://generativelanguage.googleapis.com',
+        isSystem: true,
+        models: [{ id: 'gemini-2.0-flash-exp' }] as Model[]
+      } as Provider
+
+      const googleModel: Model = {
+        id: 'gemini-2.0-flash-exp',
+        name: 'Gemini 2.0 Flash',
+        provider: SystemProviderIds.gemini
+      } as Model
+
+      it('should build basic Google options', () => {
+        const result = buildProviderOptions(mockAssistant, googleModel, googleProvider, {
+          enableReasoning: false,
+          enableWebSearch: false,
+          enableGenerateImage: false
+        })
+
+        expect(result).toHaveProperty('google')
+        expect(result.google).toBeDefined()
+      })
+
+      it('should include reasoning parameters when enabled', () => {
+        const result = buildProviderOptions(mockAssistant, googleModel, googleProvider, {
+          enableReasoning: true,
+          enableWebSearch: false,
+          enableGenerateImage: false
+        })
+
+        expect(result.google).toHaveProperty('thinkingConfig')
+        expect(result.google.thinkingConfig).toEqual({
+          include_thoughts: true
+        })
+      })
+
+      it('should include image generation parameters when enabled', () => {
+        const result = buildProviderOptions(mockAssistant, googleModel, googleProvider, {
+          enableReasoning: false,
+          enableWebSearch: false,
+          enableGenerateImage: true
+        })
+
+        expect(result.google).toHaveProperty('responseModalities')
+        expect(result.google.responseModalities).toEqual(['TEXT', 'IMAGE'])
+      })
+    })
+
+    describe('xAI provider', () => {
+      const xaiProvider = {
+        id: SystemProviderIds.grok,
+        name: 'xAI',
+        type: 'new-api',
+        apiKey: 'test-key',
+        apiHost: 'https://api.x.ai/v1',
+        isSystem: true,
+        models: [] as Model[]
+      } as Provider
+
+      const xaiModel: Model = {
+        id: 'grok-2-latest',
+        name: 'Grok 2',
+        provider: SystemProviderIds.grok
+      } as Model
+
+      it('should build basic xAI options', () => {
+        const result = buildProviderOptions(mockAssistant, xaiModel, xaiProvider, {
+          enableReasoning: false,
+          enableWebSearch: false,
+          enableGenerateImage: false
+        })
+
+        expect(result).toHaveProperty('xai')
+        expect(result.xai).toBeDefined()
+      })
+
+      it('should include reasoning parameters when enabled', () => {
+        const result = buildProviderOptions(mockAssistant, xaiModel, xaiProvider, {
+          enableReasoning: true,
+          enableWebSearch: false,
+          enableGenerateImage: false
+        })
+
+        expect(result.xai).toHaveProperty('reasoningEffort')
+        expect(result.xai.reasoningEffort).toBe('high')
+      })
+    })
+
+    describe('DeepSeek provider', () => {
+      const deepseekProvider: Provider = {
+        id: SystemProviderIds.deepseek,
+        name: 'DeepSeek',
+        type: 'openai',
+        apiKey: 'test-key',
+        apiHost: 'https://api.deepseek.com',
+        isSystem: true
+      } as Provider
+
+      const deepseekModel: Model = {
+        id: 'deepseek-chat',
+        name: 'DeepSeek Chat',
+        provider: SystemProviderIds.deepseek
+      } as Model
+
+      it('should build basic DeepSeek options', () => {
+        const result = buildProviderOptions(mockAssistant, deepseekModel, deepseekProvider, {
+          enableReasoning: false,
+          enableWebSearch: false,
+          enableGenerateImage: false
+        })
+
+        expect(result).toHaveProperty('deepseek')
+        expect(result.deepseek).toBeDefined()
+      })
+    })
+
+    describe('OpenRouter provider', () => {
+      const openrouterProvider: Provider = {
+        id: SystemProviderIds.openrouter,
+        name: 'OpenRouter',
+        type: 'openai',
+        apiKey: 'test-key',
+        apiHost: 'https://openrouter.ai/api/v1',
+        isSystem: true
+      } as Provider
+
+      const openrouterModel: Model = {
+        id: 'openai/gpt-4',
+        name: 'GPT-4',
+        provider: SystemProviderIds.openrouter
+      } as Model
+
+      it('should build basic OpenRouter options', () => {
+        const result = buildProviderOptions(mockAssistant, openrouterModel, openrouterProvider, {
+          enableReasoning: false,
+          enableWebSearch: false,
+          enableGenerateImage: false
+        })
+
+        expect(result).toHaveProperty('openrouter')
+        expect(result.openrouter).toBeDefined()
+      })
+
+      it('should include web search parameters when enabled', () => {
+        const result = buildProviderOptions(mockAssistant, openrouterModel, openrouterProvider, {
+          enableReasoning: false,
+          enableWebSearch: true,
+          enableGenerateImage: false
+        })
+
+        expect(result.openrouter).toHaveProperty('enable_search')
+      })
+    })
+
+    describe('Custom parameters', () => {
+      it('should merge custom parameters', async () => {
+        const { getCustomParameters } = await import('../reasoning')
+
+        vi.mocked(getCustomParameters).mockReturnValue({
+          custom_param: 'custom_value',
+          another_param: 123
+        })
+
+        const result = buildProviderOptions(
+          mockAssistant,
+          mockModel,
+          {
+            id: SystemProviderIds.openai,
+            name: 'OpenAI',
+            type: 'openai',
+            apiKey: 'test-key',
+            apiHost: 'https://api.openai.com/v1'
+          } as Provider,
+          {
+            enableReasoning: false,
+            enableWebSearch: false,
+            enableGenerateImage: false
+          }
+        )
+
+        expect(result.openai).toHaveProperty('custom_param')
+        expect(result.openai.custom_param).toBe('custom_value')
+        expect(result.openai).toHaveProperty('another_param')
+        expect(result.openai.another_param).toBe(123)
+      })
+    })
+
+    describe('Multiple capabilities', () => {
+      const googleProvider = {
+        id: SystemProviderIds.gemini,
+        name: 'Google',
+        type: 'gemini',
+        apiKey: 'test-key',
+        apiHost: 'https://generativelanguage.googleapis.com',
+        isSystem: true,
+        models: [] as Model[]
+      } as Provider
+
+      const googleModel: Model = {
+        id: 'gemini-2.0-flash-exp',
+        name: 'Gemini 2.0 Flash',
+        provider: SystemProviderIds.gemini
+      } as Model
+
+      it('should combine reasoning and image generation', () => {
+        const result = buildProviderOptions(mockAssistant, googleModel, googleProvider, {
+          enableReasoning: true,
+          enableWebSearch: false,
+          enableGenerateImage: true
+        })
+
+        expect(result.google).toHaveProperty('thinkingConfig')
+        expect(result.google).toHaveProperty('responseModalities')
+      })
+
+      it('should handle all capabilities enabled', () => {
+        const result = buildProviderOptions(mockAssistant, googleModel, googleProvider, {
+          enableReasoning: true,
+          enableWebSearch: true,
+          enableGenerateImage: true
+        })
+
+        expect(result.google).toBeDefined()
+        expect(Object.keys(result.google).length).toBeGreaterThan(0)
+      })
+    })
+
+    describe('Vertex AI providers', () => {
+      it('should map google-vertex to google', () => {
+        const vertexProvider = {
+          id: 'google-vertex',
+          name: 'Vertex AI',
+          type: 'vertexai',
+          apiKey: 'test-key',
+          apiHost: 'https://vertex-ai.googleapis.com',
+          models: [] as Model[]
+        } as Provider
+
+        const vertexModel: Model = {
+          id: 'gemini-2.0-flash-exp',
+          name: 'Gemini 2.0 Flash',
+          provider: 'google-vertex'
+        } as Model
+
+        const result = buildProviderOptions(mockAssistant, vertexModel, vertexProvider, {
+          enableReasoning: false,
+          enableWebSearch: false,
+          enableGenerateImage: false
+        })
+
+        expect(result).toHaveProperty('google')
+      })
+
+      it('should map google-vertex-anthropic to anthropic', () => {
+        const vertexAnthropicProvider = {
+          id: 'google-vertex-anthropic',
+          name: 'Vertex AI Anthropic',
+          type: 'vertex-anthropic',
+          apiKey: 'test-key',
+          apiHost: 'https://vertex-ai.googleapis.com',
+          models: [] as Model[]
+        } as Provider
+
+        const vertexModel: Model = {
+          id: 'claude-3-5-sonnet-20241022',
+          name: 'Claude 3.5 Sonnet',
+          provider: 'google-vertex-anthropic'
+        } as Model
+
+        const result = buildProviderOptions(mockAssistant, vertexModel, vertexAnthropicProvider, {
+          enableReasoning: false,
+          enableWebSearch: false,
+          enableGenerateImage: false
+        })
+
+        expect(result).toHaveProperty('anthropic')
+      })
+    })
+  })
+})

src/renderer/src/aiCore/utils/__tests__/reasoning.test.ts

@@ -0,0 +1,967 @@
+/**
+ * reasoning.ts Unit Tests
+ * Tests for reasoning parameter generation utilities
+ */
+
+import { getStoreSetting } from '@renderer/hooks/useSettings'
+import type { SettingsState } from '@renderer/store/settings'
+import type { Assistant, Model, Provider } from '@renderer/types'
+import { SystemProviderIds } from '@renderer/types'
+import { beforeEach, describe, expect, it, vi } from 'vitest'
+
+import {
+  getAnthropicReasoningParams,
+  getBedrockReasoningParams,
+  getCustomParameters,
+  getGeminiReasoningParams,
+  getOpenAIReasoningParams,
+  getReasoningEffort,
+  getXAIReasoningParams
+} from '../reasoning'
+
+function defaultGetStoreSetting<K extends keyof SettingsState>(key: K): SettingsState[K] {
+  if (key === 'openAI') {
+    return {
+      summaryText: 'auto',
+      verbosity: 'medium'
+    } as SettingsState[K]
+  }
+  return undefined as SettingsState[K]
+}
+
+// Mock dependencies
+vi.mock('@logger', () => ({
+  loggerService: {
+    withContext: () => ({
+      debug: vi.fn(),
+      error: vi.fn(),
+      warn: vi.fn(),
+      info: vi.fn()
+    })
+  }
+}))
+
+vi.mock('@renderer/store/settings', () => ({
+  default: (state = { settings: {} }) => state
+}))
+
+vi.mock('@renderer/store/llm', () => ({
+  initialState: {},
+  default: (state = { llm: {} }) => state
+}))
+
+vi.mock('@renderer/config/constant', () => ({
+  DEFAULT_MAX_TOKENS: 4096,
+  isMac: false,
+  isWin: false,
+  TOKENFLUX_HOST: 'mock-host'
+}))
+
+vi.mock('@renderer/utils/provider', () => ({
+  isSupportEnableThinkingProvider: vi.fn((provider) => {
+    return [SystemProviderIds.dashscope, SystemProviderIds.silicon].includes(provider.id)
+  })
+}))
+
+vi.mock('@renderer/config/models', async (importOriginal) => {
+  const actual: any = await importOriginal()
+  return {
+    ...actual,
+    isReasoningModel: vi.fn(() => false),
+    isOpenAIDeepResearchModel: vi.fn(() => false),
+    isOpenAIModel: vi.fn(() => false),
+    isSupportedReasoningEffortOpenAIModel: vi.fn(() => false),
+    isSupportedThinkingTokenQwenModel: vi.fn(() => false),
+    isQwenReasoningModel: vi.fn(() => false),
+    isSupportedThinkingTokenClaudeModel: vi.fn(() => false),
+    isSupportedThinkingTokenGeminiModel: vi.fn(() => false),
+    isSupportedThinkingTokenDoubaoModel: vi.fn(() => false),
+    isSupportedThinkingTokenZhipuModel: vi.fn(() => false),
+    isSupportedReasoningEffortModel: vi.fn(() => false),
+    isDeepSeekHybridInferenceModel: vi.fn(() => false),
+    isSupportedReasoningEffortGrokModel: vi.fn(() => false),
+    getThinkModelType: vi.fn(() => 'default'),
+    isDoubaoSeedAfter251015: vi.fn(() => false),
+    isDoubaoThinkingAutoModel: vi.fn(() => false),
+    isGrok4FastReasoningModel: vi.fn(() => false),
+    isGrokReasoningModel: vi.fn(() => false),
+    isOpenAIReasoningModel: vi.fn(() => false),
+    isQwenAlwaysThinkModel: vi.fn(() => false),
+    isSupportedThinkingTokenHunyuanModel: vi.fn(() => false),
+    isSupportedThinkingTokenModel: vi.fn(() => false),
+    isGPT51SeriesModel: vi.fn(() => false)
+  }
+})
+
+vi.mock('@renderer/hooks/useSettings', () => ({
+  getStoreSetting: vi.fn(defaultGetStoreSetting)
+}))
+
+vi.mock('@renderer/services/AssistantService', () => ({
+  getAssistantSettings: vi.fn((assistant) => ({
+    maxTokens: assistant?.settings?.maxTokens || 4096,
+    reasoning_effort: assistant?.settings?.reasoning_effort
+  })),
+  getProviderByModel: vi.fn((model) => ({
+    id: model.provider,
+    name: 'Test Provider'
+  })),
+  getDefaultAssistant: vi.fn(() => ({
+    id: 'default',
+    name: 'Default Assistant',
+    settings: {}
+  }))
+}))
+
+const ensureWindowApi = () => {
+  const globalWindow = window as any
+  globalWindow.api = globalWindow.api || {}
+  globalWindow.api.getAppInfo = globalWindow.api.getAppInfo || vi.fn(async () => ({ notesPath: '' }))
+}
+
+ensureWindowApi()
+
+describe('reasoning utils', () => {
+  beforeEach(() => {
+    vi.resetAllMocks()
+  })
+
+  describe('getReasoningEffort', () => {
+    it('should return empty object for non-reasoning model', async () => {
+      const model: Model = {
+        id: 'gpt-4',
+        name: 'GPT-4',
+        provider: SystemProviderIds.openai
+      } as Model
+
+      const assistant: Assistant = {
+        id: 'test',
+        name: 'Test',
+        settings: {}
+      } as Assistant
+
+      const result = getReasoningEffort(assistant, model)
+      expect(result).toEqual({})
+    })
+
+    it('should disable reasoning for OpenRouter when no reasoning effort set', async () => {
+      const { isReasoningModel } = await import('@renderer/config/models')
+
+      vi.mocked(isReasoningModel).mockReturnValue(true)
+
+      const model: Model = {
+        id: 'anthropic/claude-sonnet-4',
+        name: 'Claude Sonnet 4',
+        provider: SystemProviderIds.openrouter
+      } as Model
+
+      const assistant: Assistant = {
+        id: 'test',
+        name: 'Test',
+        settings: {}
+      } as Assistant
+
+      const result = getReasoningEffort(assistant, model)
+      expect(result).toEqual({ reasoning: { enabled: false, exclude: true } })
+    })
+
+    it('should handle Qwen models with enable_thinking', async () => {
+      const { isReasoningModel, isSupportedThinkingTokenQwenModel, isQwenReasoningModel } = await import(
+        '@renderer/config/models'
+      )
+
+      vi.mocked(isReasoningModel).mockReturnValue(true)
+      vi.mocked(isSupportedThinkingTokenQwenModel).mockReturnValue(true)
+      vi.mocked(isQwenReasoningModel).mockReturnValue(true)
+
+      const model: Model = {
+        id: 'qwen-plus',
+        name: 'Qwen Plus',
+        provider: SystemProviderIds.dashscope
+      } as Model
+
+      const assistant: Assistant = {
+        id: 'test',
+        name: 'Test',
+        settings: {
+          reasoning_effort: 'medium'
+        }
+      } as Assistant
+
+      const result = getReasoningEffort(assistant, model)
+      expect(result).toHaveProperty('enable_thinking')
+    })
+
+    it('should handle Claude models with thinking config', async () => {
+      const {
+        isSupportedThinkingTokenClaudeModel,
+        isReasoningModel,
+        isQwenReasoningModel,
+        isSupportedThinkingTokenGeminiModel,
+        isSupportedThinkingTokenDoubaoModel,
+        isSupportedThinkingTokenZhipuModel,
+        isSupportedReasoningEffortModel
+      } = await import('@renderer/config/models')
+
+      vi.mocked(isReasoningModel).mockReturnValue(true)
+      vi.mocked(isSupportedThinkingTokenClaudeModel).mockReturnValue(true)
+      vi.mocked(isQwenReasoningModel).mockReturnValue(false)
+      vi.mocked(isSupportedThinkingTokenGeminiModel).mockReturnValue(false)
+      vi.mocked(isSupportedThinkingTokenDoubaoModel).mockReturnValue(false)
+      vi.mocked(isSupportedThinkingTokenZhipuModel).mockReturnValue(false)
+      vi.mocked(isSupportedReasoningEffortModel).mockReturnValue(false)
+
+      const model: Model = {
+        id: 'claude-3-7-sonnet',
+        name: 'Claude 3.7 Sonnet',
+        provider: SystemProviderIds.anthropic
+      } as Model
+
+      const assistant: Assistant = {
+        id: 'test',
+        name: 'Test',
+        settings: {
+          reasoning_effort: 'high',
+          maxTokens: 4096
+        }
+      } as Assistant
+
+      const result = getReasoningEffort(assistant, model)
+      expect(result).toEqual({
+        thinking: {
+          type: 'enabled',
+          budget_tokens: expect.any(Number)
+        }
+      })
+    })
+
+    it('should handle Gemini Flash models with thinking budget 0', async () => {
+      const {
+        isSupportedThinkingTokenGeminiModel,
+        isReasoningModel,
+        isQwenReasoningModel,
+        isSupportedThinkingTokenClaudeModel,
+        isSupportedThinkingTokenDoubaoModel,
+        isSupportedThinkingTokenZhipuModel,
+        isOpenAIDeepResearchModel,
+        isSupportedThinkingTokenQwenModel,
+        isSupportedThinkingTokenHunyuanModel,
+        isDeepSeekHybridInferenceModel
+      } = await import('@renderer/config/models')
+
+      vi.mocked(isReasoningModel).mockReturnValue(true)
+      vi.mocked(isOpenAIDeepResearchModel).mockReturnValue(false)
+      vi.mocked(isSupportedThinkingTokenGeminiModel).mockReturnValue(true)
+      vi.mocked(isQwenReasoningModel).mockReturnValue(false)
+      vi.mocked(isSupportedThinkingTokenClaudeModel).mockReturnValue(false)
+      vi.mocked(isSupportedThinkingTokenDoubaoModel).mockReturnValue(false)
+      vi.mocked(isSupportedThinkingTokenZhipuModel).mockReturnValue(false)
+      vi.mocked(isSupportedThinkingTokenQwenModel).mockReturnValue(false)
+      vi.mocked(isSupportedThinkingTokenHunyuanModel).mockReturnValue(false)
+      vi.mocked(isDeepSeekHybridInferenceModel).mockReturnValue(false)
+
+      const model: Model = {
+        id: 'gemini-2.5-flash',
+        name: 'Gemini 2.5 Flash',
+        provider: SystemProviderIds.openai
+      } as Model
+
+      const assistant: Assistant = {
+        id: 'test',
+        name: 'Test',
+        settings: {}
+      } as Assistant
+
+      const result = getReasoningEffort(assistant, model)
+      expect(result).toEqual({
+        extra_body: {
+          google: {
+            thinking_config: {
+              thinking_budget: 0
+            }
+          }
+        }
+      })
+    })
+
+    it('should handle GPT-5.1 reasoning model with effort levels', async () => {
+      const {
+        isReasoningModel,
+        isOpenAIDeepResearchModel,
+        isSupportedReasoningEffortModel,
+        isGPT51SeriesModel,
+        getThinkModelType
+      } = await import('@renderer/config/models')
+
+      vi.mocked(isReasoningModel).mockReturnValue(true)
+      vi.mocked(isOpenAIDeepResearchModel).mockReturnValue(false)
+      vi.mocked(isSupportedReasoningEffortModel).mockReturnValue(true)
+      vi.mocked(getThinkModelType).mockReturnValue('gpt5_1')
+      vi.mocked(isGPT51SeriesModel).mockReturnValue(true)
+
+      const model: Model = {
+        id: 'gpt-5.1',
+        name: 'GPT-5.1',
+        provider: SystemProviderIds.openai
+      } as Model
+
+      const assistant: Assistant = {
+        id: 'test',
+        name: 'Test',
+        settings: {
+          reasoning_effort: 'none'
+        }
+      } as Assistant
+
+      const result = getReasoningEffort(assistant, model)
+      expect(result).toEqual({
+        reasoningEffort: 'none'
+      })
+    })
+
+    it('should handle DeepSeek hybrid inference models', async () => {
+      const { isReasoningModel, isDeepSeekHybridInferenceModel } = await import('@renderer/config/models')
+
+      vi.mocked(isReasoningModel).mockReturnValue(true)
+      vi.mocked(isDeepSeekHybridInferenceModel).mockReturnValue(true)
+
+      const model: Model = {
+        id: 'deepseek-v3.1',
+        name: 'DeepSeek V3.1',
+        provider: SystemProviderIds.silicon
+      } as Model
+
+      const assistant: Assistant = {
+        id: 'test',
+        name: 'Test',
+        settings: {
+          reasoning_effort: 'high'
+        }
+      } as Assistant
+
+      const result = getReasoningEffort(assistant, model)
+      expect(result).toEqual({
+        enable_thinking: true
+      })
+    })
+
+    it('should return medium effort for deep research models', async () => {
+      const { isReasoningModel, isOpenAIDeepResearchModel } = await import('@renderer/config/models')
+
+      vi.mocked(isReasoningModel).mockReturnValue(true)
+      vi.mocked(isOpenAIDeepResearchModel).mockReturnValue(true)
+
+      const model: Model = {
+        id: 'o3-deep-research',
+        provider: SystemProviderIds.openai
+      } as Model
+
+      const assistant: Assistant = {
+        id: 'test',
+        name: 'Test',
+        settings: {}
+      } as Assistant
+
+      const result = getReasoningEffort(assistant, model)
+      expect(result).toEqual({ reasoning_effort: 'medium' })
+    })
+
+    it('should return empty for groq provider', async () => {
+      const { getProviderByModel } = await import('@renderer/services/AssistantService')
+
+      vi.mocked(getProviderByModel).mockReturnValue({
+        id: 'groq',
+        name: 'Groq'
+      } as Provider)
+
+      const model: Model = {
+        id: 'groq-model',
+        name: 'Groq Model',
+        provider: 'groq'
+      } as Model
+
+      const assistant: Assistant = {
+        id: 'test',
+        name: 'Test',
+        settings: {}
+      } as Assistant
+
+      const result = getReasoningEffort(assistant, model)
+      expect(result).toEqual({})
+    })
+  })
+
+  describe('getOpenAIReasoningParams', () => {
+    it('should return empty object for non-reasoning model', async () => {
+      const model: Model = {
+        id: 'gpt-4',
+        name: 'GPT-4',
+        provider: SystemProviderIds.openai
+      } as Model
+
+      const assistant: Assistant = {
+        id: 'test',
+        name: 'Test',
+        settings: {}
+      } as Assistant
+
+      const result = getOpenAIReasoningParams(assistant, model)
+      expect(result).toEqual({})
+    })
+
+    it('should return empty when no reasoning effort set', async () => {
+      const model: Model = {
+        id: 'o1-preview',
+        name: 'O1 Preview',
+        provider: SystemProviderIds.openai
+      } as Model
+
+      const assistant: Assistant = {
+        id: 'test',
+        name: 'Test',
+        settings: {}
+      } as Assistant
+
+      const result = getOpenAIReasoningParams(assistant, model)
+      expect(result).toEqual({})
+    })
+
+    it('should return reasoning effort for OpenAI models', async () => {
+      const { isReasoningModel, isOpenAIModel, isSupportedReasoningEffortOpenAIModel } = await import(
+        '@renderer/config/models'
+      )
+
+      vi.mocked(isReasoningModel).mockReturnValue(true)
+      vi.mocked(isOpenAIModel).mockReturnValue(true)
+      vi.mocked(isSupportedReasoningEffortOpenAIModel).mockReturnValue(true)
+
+      const model: Model = {
+        id: 'gpt-5.1',
+        name: 'GPT 5.1',
+        provider: SystemProviderIds.openai
+      } as Model
+
+      const assistant: Assistant = {
+        id: 'test',
+        name: 'Test',
+        settings: {
+          reasoning_effort: 'high'
+        }
+      } as Assistant
+
+      const result = getOpenAIReasoningParams(assistant, model)
+      expect(result).toEqual({
+        reasoningEffort: 'high',
+        reasoningSummary: 'auto'
+      })
+    })
+
+    it('should include reasoning summary when not o1-pro', async () => {
+      const { isReasoningModel, isOpenAIModel, isSupportedReasoningEffortOpenAIModel } = await import(
+        '@renderer/config/models'
+      )
+
+      vi.mocked(isReasoningModel).mockReturnValue(true)
+      vi.mocked(isOpenAIModel).mockReturnValue(true)
+      vi.mocked(isSupportedReasoningEffortOpenAIModel).mockReturnValue(true)
+
+      const model: Model = {
+        id: 'gpt-5',
+        provider: SystemProviderIds.openai
+      } as Model
+
+      const assistant: Assistant = {
+        id: 'test',
+        name: 'Test',
+        settings: {
+          reasoning_effort: 'medium'
+        }
+      } as Assistant
+
+      const result = getOpenAIReasoningParams(assistant, model)
+      expect(result).toEqual({
+        reasoningEffort: 'medium',
+        reasoningSummary: 'auto'
+      })
+    })
+
+    it('should not include reasoning summary for o1-pro', async () => {
+      const { isReasoningModel, isOpenAIDeepResearchModel, isSupportedReasoningEffortOpenAIModel } = await import(
+        '@renderer/config/models'
+      )
+
+      vi.mocked(isReasoningModel).mockReturnValue(true)
+      vi.mocked(isOpenAIDeepResearchModel).mockReturnValue(false)
+      vi.mocked(isSupportedReasoningEffortOpenAIModel).mockReturnValue(true)
+      vi.mocked(getStoreSetting).mockReturnValue({ summaryText: 'off' } as any)
+
+      const model: Model = {
+        id: 'o1-pro',
+        name: 'O1 Pro',
+        provider: SystemProviderIds.openai
+      } as Model
+
+      const assistant: Assistant = {
+        id: 'test',
+        name: 'Test',
+        settings: {
+          reasoning_effort: 'high'
+        }
+      } as Assistant
+
+      const result = getOpenAIReasoningParams(assistant, model)
+      expect(result).toEqual({
+        reasoningEffort: 'high',
+        reasoningSummary: undefined
+      })
+    })
+
+    it('should force medium effort for deep research models', async () => {
+      const { isReasoningModel, isOpenAIModel, isOpenAIDeepResearchModel, isSupportedReasoningEffortOpenAIModel } =
+        await import('@renderer/config/models')
+      const { getStoreSetting } = await import('@renderer/hooks/useSettings')
+
+      vi.mocked(isReasoningModel).mockReturnValue(true)
+      vi.mocked(isOpenAIModel).mockReturnValue(true)
+      vi.mocked(isOpenAIDeepResearchModel).mockReturnValue(true)
+      vi.mocked(isSupportedReasoningEffortOpenAIModel).mockReturnValue(true)
+      vi.mocked(getStoreSetting).mockReturnValue({ summaryText: 'off' } as any)
+
+      const model: Model = {
+        id: 'o3-deep-research',
+        name: 'O3 Mini',
+        provider: SystemProviderIds.openai
+      } as Model
+
+      const assistant: Assistant = {
+        id: 'test',
+        name: 'Test',
+        settings: {
+          reasoning_effort: 'high'
+        }
+      } as Assistant
+
+      const result = getOpenAIReasoningParams(assistant, model)
+      expect(result).toEqual({
+        reasoningEffort: 'medium',
+        reasoningSummary: 'off'
+      })
+    })
+  })
+
+  describe('getAnthropicReasoningParams', () => {
+    it('should return empty for non-reasoning model', async () => {
+      const { isReasoningModel } = await import('@renderer/config/models')
+
+      vi.mocked(isReasoningModel).mockReturnValue(false)
+
+      const model: Model = {
+        id: 'claude-3-5-sonnet',
+        name: 'Claude 3.5 Sonnet',
+        provider: SystemProviderIds.anthropic
+      } as Model
+
+      const assistant: Assistant = {
+        id: 'test',
+        name: 'Test',
+        settings: {}
+      } as Assistant
+
+      const result = getAnthropicReasoningParams(assistant, model)
+      expect(result).toEqual({})
+    })
+
+    it('should return disabled thinking when no reasoning effort', async () => {
+      const { isReasoningModel, isSupportedThinkingTokenClaudeModel } = await import('@renderer/config/models')
+
+      vi.mocked(isReasoningModel).mockReturnValue(true)
+      vi.mocked(isSupportedThinkingTokenClaudeModel).mockReturnValue(false)
+
+      const model: Model = {
+        id: 'claude-3-7-sonnet',
+        name: 'Claude 3.7 Sonnet',
+        provider: SystemProviderIds.anthropic
+      } as Model
+
+      const assistant: Assistant = {
+        id: 'test',
+        name: 'Test',
+        settings: {}
+      } as Assistant
+
+      const result = getAnthropicReasoningParams(assistant, model)
+      expect(result).toEqual({
+        thinking: {
+          type: 'disabled'
+        }
+      })
+    })
+
+    it('should return enabled thinking with budget for Claude models', async () => {
+      const { isReasoningModel, isSupportedThinkingTokenClaudeModel } = await import('@renderer/config/models')
+
+      vi.mocked(isReasoningModel).mockReturnValue(true)
+      vi.mocked(isSupportedThinkingTokenClaudeModel).mockReturnValue(true)
+
+      const model: Model = {
+        id: 'claude-3-7-sonnet',
+        name: 'Claude 3.7 Sonnet',
+        provider: SystemProviderIds.anthropic
+      } as Model
+
+      const assistant: Assistant = {
+        id: 'test',
+        name: 'Test',
+        settings: {
+          reasoning_effort: 'medium',
+          maxTokens: 4096
+        }
+      } as Assistant
+
+      const result = getAnthropicReasoningParams(assistant, model)
+      expect(result).toEqual({
+        thinking: {
+          type: 'enabled',
+          budgetTokens: 2048
+        }
+      })
+    })
+  })
+
+  describe('getGeminiReasoningParams', () => {
+    it('should return empty for non-reasoning model', async () => {
+      const { isReasoningModel } = await import('@renderer/config/models')
+
+      vi.mocked(isReasoningModel).mockReturnValue(false)
+
+      const model: Model = {
+        id: 'gemini-2.0-flash',
+        name: 'Gemini 2.0 Flash',
+        provider: SystemProviderIds.gemini
+      } as Model
+
+      const assistant: Assistant = {
+        id: 'test',
+        name: 'Test',
+        settings: {}
+      } as Assistant
+
+      const result = getGeminiReasoningParams(assistant, model)
+      expect(result).toEqual({})
+    })
+
+    it('should disable thinking for Flash models without reasoning effort', async () => {
+      const { isReasoningModel, isSupportedThinkingTokenGeminiModel } = await import('@renderer/config/models')
+
+      vi.mocked(isReasoningModel).mockReturnValue(true)
+      vi.mocked(isSupportedThinkingTokenGeminiModel).mockReturnValue(true)
+
+      const model: Model = {
+        id: 'gemini-2.5-flash',
+        name: 'Gemini 2.5 Flash',
+        provider: SystemProviderIds.gemini
+      } as Model
+
+      const assistant: Assistant = {
+        id: 'test',
+        name: 'Test',
+        settings: {}
+      } as Assistant
+
+      const result = getGeminiReasoningParams(assistant, model)
+      expect(result).toEqual({
+        thinkingConfig: {
+          includeThoughts: false,
+          thinkingBudget: 0
+        }
+      })
+    })
+
+    it('should enable thinking with budget for reasoning effort', async () => {
+      const { isReasoningModel, isSupportedThinkingTokenGeminiModel } = await import('@renderer/config/models')
+
+      vi.mocked(isReasoningModel).mockReturnValue(true)
+      vi.mocked(isSupportedThinkingTokenGeminiModel).mockReturnValue(true)
+
+      const model: Model = {
+        id: 'gemini-2.5-pro',
+        name: 'Gemini 2.5 Pro',
+        provider: SystemProviderIds.gemini
+      } as Model
+
+      const assistant: Assistant = {
+        id: 'test',
+        name: 'Test',
+        settings: {
+          reasoning_effort: 'medium'
+        }
+      } as Assistant
+
+      const result = getGeminiReasoningParams(assistant, model)
+      expect(result).toEqual({
+        thinkingConfig: {
+          thinkingBudget: 16448,
+          includeThoughts: true
+        }
+      })
+    })
+
+    it('should enable thinking without budget for auto effort ratio > 1', async () => {
+      const { isReasoningModel, isSupportedThinkingTokenGeminiModel } = await import('@renderer/config/models')
+
+      vi.mocked(isReasoningModel).mockReturnValue(true)
+      vi.mocked(isSupportedThinkingTokenGeminiModel).mockReturnValue(true)
+
+      const model: Model = {
+        id: 'gemini-2.5-pro',
+        name: 'Gemini 2.5 Pro',
+        provider: SystemProviderIds.gemini
+      } as Model
+
+      const assistant: Assistant = {
+        id: 'test',
+        name: 'Test',
+        settings: {
+          reasoning_effort: 'auto'
+        }
+      } as Assistant
+
+      const result = getGeminiReasoningParams(assistant, model)
+      expect(result).toEqual({
+        thinkingConfig: {
+          includeThoughts: true
+        }
+      })
+    })
+  })
+
+  describe('getXAIReasoningParams', () => {
+    it('should return empty for non-Grok model', async () => {
+      const { isSupportedReasoningEffortGrokModel } = await import('@renderer/config/models')
+
+      vi.mocked(isSupportedReasoningEffortGrokModel).mockReturnValue(false)
+
+      const model: Model = {
+        id: 'other-model',
+        name: 'Other Model',
+        provider: SystemProviderIds.grok
+      } as Model
+
+      const assistant: Assistant = {
+        id: 'test',
+        name: 'Test',
+        settings: {}
+      } as Assistant
+
+      const result = getXAIReasoningParams(assistant, model)
+      expect(result).toEqual({})
+    })
+
+    it('should return empty when no reasoning effort', async () => {
+      const { isSupportedReasoningEffortGrokModel } = await import('@renderer/config/models')
+
+      vi.mocked(isSupportedReasoningEffortGrokModel).mockReturnValue(true)
+
+      const model: Model = {
+        id: 'grok-2',
+        name: 'Grok 2',
+        provider: SystemProviderIds.grok
+      } as Model
+
+      const assistant: Assistant = {
+        id: 'test',
+        name: 'Test',
+        settings: {}
+      } as Assistant
+
+      const result = getXAIReasoningParams(assistant, model)
+      expect(result).toEqual({})
+    })
+
+    it('should return reasoning effort for Grok models', async () => {
+      const { isSupportedReasoningEffortGrokModel } = await import('@renderer/config/models')
+
+      vi.mocked(isSupportedReasoningEffortGrokModel).mockReturnValue(true)
+
+      const model: Model = {
+        id: 'grok-3',
+        name: 'Grok 3',
+        provider: SystemProviderIds.grok
+      } as Model
+
+      const assistant: Assistant = {
+        id: 'test',
+        name: 'Test',
+        settings: {
+          reasoning_effort: 'high'
+        }
+      } as Assistant
+
+      const result = getXAIReasoningParams(assistant, model)
+      expect(result).toHaveProperty('reasoningEffort')
+      expect(result.reasoningEffort).toBe('high')
+    })
+  })
+
+  describe('getBedrockReasoningParams', () => {
+    it('should return empty for non-reasoning model', async () => {
+      const model: Model = {
+        id: 'other-model',
+        name: 'Other Model',
+        provider: 'bedrock'
+      } as Model
+
+      const assistant: Assistant = {
+        id: 'test',
+        name: 'Test',
+        settings: {}
+      } as Assistant
+
+      const result = getBedrockReasoningParams(assistant, model)
+      expect(result).toEqual({})
+    })
+
+    it('should return empty when no reasoning effort', async () => {
+      const model: Model = {
+        id: 'claude-3-7-sonnet',
+        name: 'Claude 3.7 Sonnet',
+        provider: 'bedrock'
+      } as Model
+
+      const assistant: Assistant = {
+        id: 'test',
+        name: 'Test',
+        settings: {}
+      } as Assistant
+
+      const result = getBedrockReasoningParams(assistant, model)
+      expect(result).toEqual({})
+    })
+
+    it('should return reasoning config for Claude models on Bedrock', async () => {
+      const { isReasoningModel, isSupportedThinkingTokenClaudeModel } = await import('@renderer/config/models')
+
+      vi.mocked(isReasoningModel).mockReturnValue(true)
+      vi.mocked(isSupportedThinkingTokenClaudeModel).mockReturnValue(true)
+
+      const model: Model = {
+        id: 'claude-3-7-sonnet',
+        name: 'Claude 3.7 Sonnet',
+        provider: 'bedrock'
+      } as Model
+
+      const assistant: Assistant = {
+        id: 'test',
+        name: 'Test',
+        settings: {
+          reasoning_effort: 'medium',
+          maxTokens: 4096
+        }
+      } as Assistant
+
+      const result = getBedrockReasoningParams(assistant, model)
+      expect(result).toEqual({
+        reasoningConfig: {
+          type: 'enabled',
+          budgetTokens: 2048
+        }
+      })
+    })
+  })
+
+  describe('getCustomParameters', () => {
+    it('should return empty object when no custom parameters', async () => {
+      const assistant: Assistant = {
+        id: 'test',
+        name: 'Test',
+        settings: {}
+      } as Assistant
+
+      const result = getCustomParameters(assistant)
+      expect(result).toEqual({})
+    })
+
+    it('should return custom parameters as key-value pairs', async () => {
+      const assistant: Assistant = {
+        id: 'test',
+        name: 'Test',
+        settings: {
+          customParameters: [
+            { name: 'param1', value: 'value1', type: 'string' },
+            { name: 'param2', value: 123, type: 'number' }
+          ]
+        }
+      } as Assistant
+
+      const result = getCustomParameters(assistant)
+      expect(result).toEqual({
+        param1: 'value1',
+        param2: 123
+      })
+    })
+
+    it('should parse JSON type parameters', async () => {
+      const assistant: Assistant = {
+        id: 'test',
+        name: 'Test',
+        settings: {
+          customParameters: [{ name: 'config', value: '{"key": "value"}', type: 'json' }]
+        }
+      } as Assistant
+
+      const result = getCustomParameters(assistant)
+      expect(result).toEqual({
+        config: { key: 'value' }
+      })
+    })
+
+    it('should handle invalid JSON gracefully', async () => {
+      const assistant: Assistant = {
+        id: 'test',
+        name: 'Test',
+        settings: {
+          customParameters: [{ name: 'invalid', value: '{invalid json', type: 'json' }]
+        }
+      } as Assistant
+
+      const result = getCustomParameters(assistant)
+      expect(result).toEqual({
+        invalid: '{invalid json'
+      })
+    })
+
+    it('should handle undefined JSON value', async () => {
+      const assistant: Assistant = {
+        id: 'test',
+        name: 'Test',
+        settings: {
+          customParameters: [{ name: 'undef', value: 'undefined', type: 'json' }]
+        }
+      } as Assistant
+
+      const result = getCustomParameters(assistant)
+      expect(result).toEqual({
+        undef: undefined
+      })
+    })
+
+    it('should skip parameters with empty names', async () => {
+      const assistant: Assistant = {
+        id: 'test',
+        name: 'Test',
+        settings: {
+          customParameters: [
+            { name: '', value: 'value1', type: 'string' },
+            { name: '  ', value: 'value2', type: 'string' },
+            { name: 'valid', value: 'value3', type: 'string' }
+          ]
+        }
+      } as Assistant
+
+      const result = getCustomParameters(assistant)
+      expect(result).toEqual({
+        valid: 'value3'
+      })
+    })
+  })
+})

src/renderer/src/aiCore/utils/__tests__/websearch.test.ts

@@ -0,0 +1,384 @@
+/**
+ * websearch.ts Unit Tests
+ * Tests for web search parameters generation utilities
+ */
+
+import type { CherryWebSearchConfig } from '@renderer/store/websearch'
+import type { Model } from '@renderer/types'
+import { describe, expect, it, vi } from 'vitest'
+
+import { buildProviderBuiltinWebSearchConfig, getWebSearchParams } from '../websearch'
+
+// Mock dependencies
+vi.mock('@renderer/config/models', () => ({
+  isOpenAIWebSearchChatCompletionOnlyModel: vi.fn((model) => model?.id?.includes('o1-pro') ?? false),
+  isOpenAIDeepResearchModel: vi.fn((model) => model?.id?.includes('o3-mini') ?? false)
+}))
+
+vi.mock('@renderer/utils/blacklistMatchPattern', () => ({
+  mapRegexToPatterns: vi.fn((patterns) => patterns || [])
+}))
+
+describe('websearch utils', () => {
+  describe('getWebSearchParams', () => {
+    it('should return enhancement params for hunyuan provider', () => {
+      const model: Model = {
+        id: 'hunyuan-model',
+        name: 'Hunyuan Model',
+        provider: 'hunyuan'
+      } as Model
+
+      const result = getWebSearchParams(model)
+
+      expect(result).toEqual({
+        enable_enhancement: true,
+        citation: true,
+        search_info: true
+      })
+    })
+
+    it('should return search params for dashscope provider', () => {
+      const model: Model = {
+        id: 'qwen-model',
+        name: 'Qwen Model',
+        provider: 'dashscope'
+      } as Model
+
+      const result = getWebSearchParams(model)
+
+      expect(result).toEqual({
+        enable_search: true,
+        search_options: {
+          forced_search: true
+        }
+      })
+    })
+
+    it('should return web_search_options for OpenAI web search models', () => {
+      const model: Model = {
+        id: 'o1-pro',
+        name: 'O1 Pro',
+        provider: 'openai'
+      } as Model
+
+      const result = getWebSearchParams(model)
+
+      expect(result).toEqual({
+        web_search_options: {}
+      })
+    })
+
+    it('should return empty object for other providers', () => {
+      const model: Model = {
+        id: 'gpt-4',
+        name: 'GPT-4',
+        provider: 'openai'
+      } as Model
+
+      const result = getWebSearchParams(model)
+
+      expect(result).toEqual({})
+    })
+
+    it('should return empty object for custom provider', () => {
+      const model: Model = {
+        id: 'custom-model',
+        name: 'Custom Model',
+        provider: 'custom-provider'
+      } as Model
+
+      const result = getWebSearchParams(model)
+
+      expect(result).toEqual({})
+    })
+  })
+
+  describe('buildProviderBuiltinWebSearchConfig', () => {
+    const defaultWebSearchConfig: CherryWebSearchConfig = {
+      searchWithTime: true,
+      maxResults: 50,
+      excludeDomains: []
+    }
+
+    describe('openai provider', () => {
+      it('should return low search context size for low maxResults', () => {
+        const config: CherryWebSearchConfig = {
+          searchWithTime: true,
+          maxResults: 20,
+          excludeDomains: []
+        }
+
+        const result = buildProviderBuiltinWebSearchConfig('openai', config)
+
+        expect(result).toEqual({
+          openai: {
+            searchContextSize: 'low'
+          }
+        })
+      })
+
+      it('should return medium search context size for medium maxResults', () => {
+        const config: CherryWebSearchConfig = {
+          searchWithTime: true,
+          maxResults: 50,
+          excludeDomains: []
+        }
+
+        const result = buildProviderBuiltinWebSearchConfig('openai', config)
+
+        expect(result).toEqual({
+          openai: {
+            searchContextSize: 'medium'
+          }
+        })
+      })
+
+      it('should return high search context size for high maxResults', () => {
+        const config: CherryWebSearchConfig = {
+          searchWithTime: true,
+          maxResults: 80,
+          excludeDomains: []
+        }
+
+        const result = buildProviderBuiltinWebSearchConfig('openai', config)
+
+        expect(result).toEqual({
+          openai: {
+            searchContextSize: 'high'
+          }
+        })
+      })
+
+      it('should use medium for deep research models regardless of maxResults', () => {
+        const config: CherryWebSearchConfig = {
+          searchWithTime: true,
+          maxResults: 100,
+          excludeDomains: []
+        }
+
+        const model: Model = {
+          id: 'o3-mini',
+          name: 'O3 Mini',
+          provider: 'openai'
+        } as Model
+
+        const result = buildProviderBuiltinWebSearchConfig('openai', config, model)
+
+        expect(result).toEqual({
+          openai: {
+            searchContextSize: 'medium'
+          }
+        })
+      })
+    })
+
+    describe('openai-chat provider', () => {
+      it('should return correct search context size', () => {
+        const config: CherryWebSearchConfig = {
+          searchWithTime: true,
+          maxResults: 50,
+          excludeDomains: []
+        }
+
+        const result = buildProviderBuiltinWebSearchConfig('openai-chat', config)
+
+        expect(result).toEqual({
+          'openai-chat': {
+            searchContextSize: 'medium'
+          }
+        })
+      })
+
+      it('should handle deep research models', () => {
+        const config: CherryWebSearchConfig = {
+          searchWithTime: true,
+          maxResults: 100,
+          excludeDomains: []
+        }
+
+        const model: Model = {
+          id: 'o3-mini',
+          name: 'O3 Mini',
+          provider: 'openai'
+        } as Model
+
+        const result = buildProviderBuiltinWebSearchConfig('openai-chat', config, model)
+
+        expect(result).toEqual({
+          'openai-chat': {
+            searchContextSize: 'medium'
+          }
+        })
+      })
+    })
+
+    describe('anthropic provider', () => {
+      it('should return anthropic search options with maxUses', () => {
+        const result = buildProviderBuiltinWebSearchConfig('anthropic', defaultWebSearchConfig)
+
+        expect(result).toEqual({
+          anthropic: {
+            maxUses: 50,
+            blockedDomains: undefined
+          }
+        })
+      })
+
+      it('should include blockedDomains when excludeDomains provided', () => {
+        const config: CherryWebSearchConfig = {
+          searchWithTime: true,
+          maxResults: 30,
+          excludeDomains: ['example.com', 'test.com']
+        }
+
+        const result = buildProviderBuiltinWebSearchConfig('anthropic', config)
+
+        expect(result).toEqual({
+          anthropic: {
+            maxUses: 30,
+            blockedDomains: ['example.com', 'test.com']
+          }
+        })
+      })
+
+      it('should not include blockedDomains when empty', () => {
+        const result = buildProviderBuiltinWebSearchConfig('anthropic', defaultWebSearchConfig)
+
+        expect(result).toEqual({
+          anthropic: {
+            maxUses: 50,
+            blockedDomains: undefined
+          }
+        })
+      })
+    })
+
+    describe('xai provider', () => {
+      it('should return xai search options', () => {
+        const result = buildProviderBuiltinWebSearchConfig('xai', defaultWebSearchConfig)
+
+        expect(result).toEqual({
+          xai: {
+            maxSearchResults: 50,
+            returnCitations: true,
+            sources: [{ type: 'web', excludedWebsites: [] }, { type: 'news' }, { type: 'x' }],
+            mode: 'on'
+          }
+        })
+      })
+
+      it('should limit excluded websites to 5', () => {
+        const config: CherryWebSearchConfig = {
+          searchWithTime: true,
+          maxResults: 40,
+          excludeDomains: ['site1.com', 'site2.com', 'site3.com', 'site4.com', 'site5.com', 'site6.com', 'site7.com']
+        }
+
+        const result = buildProviderBuiltinWebSearchConfig('xai', config)
+
+        expect(result?.xai?.sources).toBeDefined()
+        const webSource = result?.xai?.sources?.[0]
+        if (webSource && webSource.type === 'web') {
+          expect(webSource.excludedWebsites).toHaveLength(5)
+        }
+      })
+
+      it('should include all sources types', () => {
+        const result = buildProviderBuiltinWebSearchConfig('xai', defaultWebSearchConfig)
+
+        expect(result?.xai?.sources).toHaveLength(3)
+        expect(result?.xai?.sources?.[0].type).toBe('web')
+        expect(result?.xai?.sources?.[1].type).toBe('news')
+        expect(result?.xai?.sources?.[2].type).toBe('x')
+      })
+    })
+
+    describe('openrouter provider', () => {
+      it('should return openrouter plugins config', () => {
+        const result = buildProviderBuiltinWebSearchConfig('openrouter', defaultWebSearchConfig)
+
+        expect(result).toEqual({
+          openrouter: {
+            plugins: [
+              {
+                id: 'web',
+                max_results: 50
+              }
+            ]
+          }
+        })
+      })
+
+      it('should respect custom maxResults', () => {
+        const config: CherryWebSearchConfig = {
+          searchWithTime: true,
+          maxResults: 75,
+          excludeDomains: []
+        }
+
+        const result = buildProviderBuiltinWebSearchConfig('openrouter', config)
+
+        expect(result).toEqual({
+          openrouter: {
+            plugins: [
+              {
+                id: 'web',
+                max_results: 75
+              }
+            ]
+          }
+        })
+      })
+    })
+
+    describe('unsupported provider', () => {
+      it('should return empty object for unsupported provider', () => {
+        const result = buildProviderBuiltinWebSearchConfig('unsupported' as any, defaultWebSearchConfig)
+
+        expect(result).toEqual({})
+      })
+
+      it('should return empty object for google provider', () => {
+        const result = buildProviderBuiltinWebSearchConfig('google', defaultWebSearchConfig)
+
+        expect(result).toEqual({})
+      })
+    })
+
+    describe('edge cases', () => {
+      it('should handle maxResults at boundary values', () => {
+        // Test boundary at 33 (low/medium)
+        const config33: CherryWebSearchConfig = { searchWithTime: true, maxResults: 33, excludeDomains: [] }
+        const result33 = buildProviderBuiltinWebSearchConfig('openai', config33)
+        expect(result33?.openai?.searchContextSize).toBe('low')
+
+        // Test boundary at 34 (medium)
+        const config34: CherryWebSearchConfig = { searchWithTime: true, maxResults: 34, excludeDomains: [] }
+        const result34 = buildProviderBuiltinWebSearchConfig('openai', config34)
+        expect(result34?.openai?.searchContextSize).toBe('medium')
+
+        // Test boundary at 66 (medium)
+        const config66: CherryWebSearchConfig = { searchWithTime: true, maxResults: 66, excludeDomains: [] }
+        const result66 = buildProviderBuiltinWebSearchConfig('openai', config66)
+        expect(result66?.openai?.searchContextSize).toBe('medium')
+
+        // Test boundary at 67 (high)
+        const config67: CherryWebSearchConfig = { searchWithTime: true, maxResults: 67, excludeDomains: [] }
+        const result67 = buildProviderBuiltinWebSearchConfig('openai', config67)
+        expect(result67?.openai?.searchContextSize).toBe('high')
+      })
+
+      it('should handle zero maxResults', () => {
+        const config: CherryWebSearchConfig = { searchWithTime: true, maxResults: 0, excludeDomains: [] }
+        const result = buildProviderBuiltinWebSearchConfig('openai', config)
+        expect(result?.openai?.searchContextSize).toBe('low')
+      })
+
+      it('should handle very large maxResults', () => {
+        const config: CherryWebSearchConfig = { searchWithTime: true, maxResults: 1000, excludeDomains: [] }
+        const result = buildProviderBuiltinWebSearchConfig('openai', config)
+        expect(result?.openai?.searchContextSize).toBe('high')
+      })
+    })
+  })
+})

src/renderer/src/aiCore/utils/options.ts

@@ -1,3 +1,8 @@
+import type { BedrockProviderOptions } from '@ai-sdk/amazon-bedrock'
+import type { AnthropicProviderOptions } from '@ai-sdk/anthropic'
+import type { GoogleGenerativeAIProviderOptions } from '@ai-sdk/google'
+import type { OpenAIResponsesProviderOptions } from '@ai-sdk/openai'
+import type { XaiProviderOptions } from '@ai-sdk/xai'
 import { baseProviderIdSchema, customProviderIdSchema } from '@cherrystudio/ai-core/provider'
 import { loggerService } from '@logger'
 import {
@@ -7,17 +12,27 @@ import {
   isSupportFlexServiceTierModel,
   isSupportVerbosityModel
 } from '@renderer/config/models'
-import { isSupportServiceTierProvider } from '@renderer/config/providers'
 import { mapLanguageToQwenMTModel } from '@renderer/config/translate'
-import type { Assistant, Model, Provider } from '@renderer/types'
+import { getStoreSetting } from '@renderer/hooks/useSettings'
 import {
+  type Assistant,
+  type GroqServiceTier,
   GroqServiceTiers,
+  type GroqSystemProvider,
   isGroqServiceTier,
+  isGroqSystemProvider,
   isOpenAIServiceTier,
   isTranslateAssistant,
+  type Model,
+  type NotGroqProvider,
+  type OpenAIServiceTier,
   OpenAIServiceTiers,
-  SystemProviderIds
+  type Provider,
+  type ServiceTier
 } from '@renderer/types'
+import type { OpenAIVerbosity } from '@renderer/types/aiCoreTypes'
+import { isSupportServiceTierProvider } from '@renderer/utils/provider'
+import type { JSONValue } from 'ai'
 import { t } from 'i18next'
 
 import { getAiSdkProviderId } from '../provider/factory'
@@ -35,8 +50,31 @@ import { getWebSearchParams } from './websearch'
 
 const logger = loggerService.withContext('aiCore.utils.options')
 
-// copy from BaseApiClient.ts
+function toOpenAIServiceTier(model: Model, serviceTier: ServiceTier): OpenAIServiceTier {
-const getServiceTier = (model: Model, provider: Provider) => {
+  if (
+    !isOpenAIServiceTier(serviceTier) ||
+    (serviceTier === OpenAIServiceTiers.flex && !isSupportFlexServiceTierModel(model))
+  ) {
+    return undefined
+  } else {
+    return serviceTier
+  }
+}
+
+function toGroqServiceTier(model: Model, serviceTier: ServiceTier): GroqServiceTier {
+  if (
+    !isGroqServiceTier(serviceTier) ||
+    (serviceTier === GroqServiceTiers.flex && !isSupportFlexServiceTierModel(model))
+  ) {
+    return undefined
+  } else {
+    return serviceTier
+  }
+}
+
+function getServiceTier<T extends GroqSystemProvider>(model: Model, provider: T): GroqServiceTier
+function getServiceTier<T extends NotGroqProvider>(model: Model, provider: T): OpenAIServiceTier
+function getServiceTier<T extends Provider>(model: Model, provider: T): OpenAIServiceTier | GroqServiceTier {
   const serviceTierSetting = provider.serviceTier
 
   if (!isSupportServiceTierProvider(provider) || !isOpenAIModel(model) || !serviceTierSetting) {
@@ -44,24 +82,17 @@ const getServiceTier = (model: Model, provider: Provider) => {
   }
 
   // 处理不同供应商需要 fallback 到默认值的情况
-  if (provider.id === SystemProviderIds.groq) {
+  if (isGroqSystemProvider(provider)) {
-    if (
+    return toGroqServiceTier(model, serviceTierSetting)
-      !isGroqServiceTier(serviceTierSetting) ||
-      (serviceTierSetting === GroqServiceTiers.flex && !isSupportFlexServiceTierModel(model))
-    ) {
-      return undefined
-    }
   } else {
     // 其他 OpenAI 供应商，假设他们的服务层级设置和 OpenAI 完全相同
-    if (
+    return toOpenAIServiceTier(model, serviceTierSetting)
-      !isOpenAIServiceTier(serviceTierSetting) ||
-      (serviceTierSetting === OpenAIServiceTiers.flex && !isSupportFlexServiceTierModel(model))
-    ) {
-      return undefined
-    }
   }
+}
 
-  return serviceTierSetting
+function getVerbosity(): OpenAIVerbosity {
+  const openAI = getStoreSetting('openAI')
+  return openAI.verbosity
 }
 
 /**
@@ -78,13 +109,13 @@ export function buildProviderOptions(
     enableWebSearch: boolean
     enableGenerateImage: boolean
   }
-): Record<string, any> {
+): Record<string, Record<string, JSONValue>> {
   logger.debug('buildProviderOptions', { assistant, model, actualProvider, capabilities })
   const rawProviderId = getAiSdkProviderId(actualProvider)
   // 构建 provider 特定的选项
   let providerSpecificOptions: Record<string, any> = {}
-  const serviceTierSetting = getServiceTier(model, actualProvider)
+  const serviceTier = getServiceTier(model, actualProvider)
-  providerSpecificOptions.serviceTier = serviceTierSetting
+  const textVerbosity = getVerbosity()
   // 根据 provider 类型分离构建逻辑
   const { data: baseProviderId, success } = baseProviderIdSchema.safeParse(rawProviderId)
   if (success) {
@@ -94,9 +125,14 @@ export function buildProviderOptions(
       case 'openai-chat':
       case 'azure':
       case 'azure-responses':
-        providerSpecificOptions = {
+        {
-          ...buildOpenAIProviderOptions(assistant, model, capabilities),
+          const options: OpenAIResponsesProviderOptions = buildOpenAIProviderOptions(
-          serviceTier: serviceTierSetting
+            assistant,
+            model,
+            capabilities,
+            serviceTier
+          )
+          providerSpecificOptions = options
         }
         break
       case 'anthropic':
@@ -116,12 +152,19 @@ export function buildProviderOptions(
         // 对于其他 provider，使用通用的构建逻辑
         providerSpecificOptions = {
           ...buildGenericProviderOptions(assistant, model, capabilities),
-          serviceTier: serviceTierSetting
+          serviceTier,
+          textVerbosity
         }
         break
       }
       case 'cherryin':
-        providerSpecificOptions = buildCherryInProviderOptions(assistant, model, capabilities, actualProvider)
+        providerSpecificOptions = buildCherryInProviderOptions(
+          assistant,
+          model,
+          capabilities,
+          actualProvider,
+          serviceTier
+        )
         break
       default:
         throw new Error(`Unsupported base provider ${baseProviderId}`)
@@ -135,6 +178,7 @@ export function buildProviderOptions(
         case 'google-vertex':
           providerSpecificOptions = buildGeminiProviderOptions(assistant, model, capabilities)
           break
+        case 'azure-anthropic':
         case 'google-vertex-anthropic':
           providerSpecificOptions = buildAnthropicProviderOptions(assistant, model, capabilities)
           break
@@ -142,13 +186,14 @@ export function buildProviderOptions(
           providerSpecificOptions = buildBedrockProviderOptions(assistant, model, capabilities)
           break
         case 'huggingface':
-          providerSpecificOptions = buildOpenAIProviderOptions(assistant, model, capabilities)
+          providerSpecificOptions = buildOpenAIProviderOptions(assistant, model, capabilities, serviceTier)
           break
         default:
           // 对于其他 provider，使用通用的构建逻辑
           providerSpecificOptions = {
             ...buildGenericProviderOptions(assistant, model, capabilities),
-            serviceTier: serviceTierSetting
+            serviceTier,
+            textVerbosity
           }
       }
     } else {
@@ -166,6 +211,7 @@ export function buildProviderOptions(
     {
       'google-vertex': 'google',
       'google-vertex-anthropic': 'anthropic',
+      'azure-anthropic': 'anthropic',
       'ai-gateway': 'gateway'
     }[rawProviderId] || rawProviderId
 
@@ -189,10 +235,11 @@ function buildOpenAIProviderOptions(
     enableReasoning: boolean
     enableWebSearch: boolean
     enableGenerateImage: boolean
-  }
+  },
-): Record<string, any> {
+  serviceTier: OpenAIServiceTier
+): OpenAIResponsesProviderOptions {
   const { enableReasoning } = capabilities
-  let providerOptions: Record<string, any> = {}
+  let providerOptions: OpenAIResponsesProviderOptions = {}
   // OpenAI 推理参数
   if (enableReasoning) {
     const reasoningParams = getOpenAIReasoningParams(assistant, model)
@@ -203,8 +250,8 @@ function buildOpenAIProviderOptions(
   }
 
   if (isSupportVerbosityModel(model)) {
-    const state = window.store?.getState()
+    const openAI = getStoreSetting<'openAI'>('openAI')
-    const userVerbosity = state?.settings?.openAI?.verbosity
+    const userVerbosity = openAI?.verbosity
 
     if (userVerbosity && ['low', 'medium', 'high'].includes(userVerbosity)) {
       const supportedVerbosity = getModelSupportedVerbosity(model)
@@ -218,6 +265,11 @@ function buildOpenAIProviderOptions(
     }
   }
 
+  providerOptions = {
+    ...providerOptions,
+    serviceTier
+  }
+
   return providerOptions
 }
 
@@ -232,9 +284,9 @@ function buildAnthropicProviderOptions(
     enableWebSearch: boolean
     enableGenerateImage: boolean
   }
-): Record<string, any> {
+): AnthropicProviderOptions {
   const { enableReasoning } = capabilities
-  let providerOptions: Record<string, any> = {}
+  let providerOptions: AnthropicProviderOptions = {}
 
   // Anthropic 推理参数
   if (enableReasoning) {
@@ -259,9 +311,9 @@ function buildGeminiProviderOptions(
     enableWebSearch: boolean
     enableGenerateImage: boolean
   }
-): Record<string, any> {
+): GoogleGenerativeAIProviderOptions {
   const { enableReasoning, enableGenerateImage } = capabilities
-  let providerOptions: Record<string, any> = {}
+  let providerOptions: GoogleGenerativeAIProviderOptions = {}
 
   // Gemini 推理参数
   if (enableReasoning) {
@@ -290,7 +342,7 @@ function buildXAIProviderOptions(
     enableWebSearch: boolean
     enableGenerateImage: boolean
   }
-): Record<string, any> {
+): XaiProviderOptions {
   const { enableReasoning } = capabilities
   let providerOptions: Record<string, any> = {}
 
@@ -313,16 +365,12 @@ function buildCherryInProviderOptions(
     enableWebSearch: boolean
     enableGenerateImage: boolean
   },
-  actualProvider: Provider
+  actualProvider: Provider,
-): Record<string, any> {
+  serviceTier: OpenAIServiceTier
-  const serviceTierSetting = getServiceTier(model, actualProvider)
+): OpenAIResponsesProviderOptions | AnthropicProviderOptions | GoogleGenerativeAIProviderOptions {
-
   switch (actualProvider.type) {
     case 'openai':
-      return {
+      return buildOpenAIProviderOptions(assistant, model, capabilities, serviceTier)
-        ...buildOpenAIProviderOptions(assistant, model, capabilities),
-        serviceTier: serviceTierSetting
-      }
 
     case 'anthropic':
       return buildAnthropicProviderOptions(assistant, model, capabilities)
@@ -344,9 +392,9 @@ function buildBedrockProviderOptions(
     enableWebSearch: boolean
     enableGenerateImage: boolean
   }
-): Record<string, any> {
+): BedrockProviderOptions {
   const { enableReasoning } = capabilities
-  let providerOptions: Record<string, any> = {}
+  let providerOptions: BedrockProviderOptions = {}
 
   if (enableReasoning) {
     const reasoningParams = getBedrockReasoningParams(assistant, model)

src/renderer/src/aiCore/utils/reasoning.ts

@@ -1,6 +1,7 @@
 import type { BedrockProviderOptions } from '@ai-sdk/amazon-bedrock'
 import type { AnthropicProviderOptions } from '@ai-sdk/anthropic'
 import type { GoogleGenerativeAIProviderOptions } from '@ai-sdk/google'
+import type { OpenAIResponsesProviderOptions } from '@ai-sdk/openai'
 import type { XaiProviderOptions } from '@ai-sdk/xai'
 import { loggerService } from '@logger'
 import { DEFAULT_MAX_TOKENS } from '@renderer/config/constant'
@@ -11,6 +12,7 @@ import {
   isDeepSeekHybridInferenceModel,
   isDoubaoSeedAfter251015,
   isDoubaoThinkingAutoModel,
+  isGemini3Model,
   isGPT51SeriesModel,
   isGrok4FastReasoningModel,
   isGrokReasoningModel,
@@ -32,13 +34,13 @@ import {
   isSupportedThinkingTokenZhipuModel,
   MODEL_SUPPORTED_REASONING_EFFORT
 } from '@renderer/config/models'
-import { isSupportEnableThinkingProvider } from '@renderer/config/providers'
 import { getStoreSetting } from '@renderer/hooks/useSettings'
 import { getAssistantSettings, getProviderByModel } from '@renderer/services/AssistantService'
-import type { SettingsState } from '@renderer/store/settings'
+import type { Assistant, Model, ReasoningEffortOption } from '@renderer/types'
-import type { Assistant, Model } from '@renderer/types'
 import { EFFORT_RATIO, isSystemProvider, SystemProviderIds } from '@renderer/types'
+import type { OpenAISummaryText } from '@renderer/types/aiCoreTypes'
 import type { ReasoningEffortOptionalParams } from '@renderer/types/sdk'
+import { isSupportEnableThinkingProvider } from '@renderer/utils/provider'
 import { toInteger } from 'lodash'
 
 const logger = loggerService.withContext('reasoning')
@@ -130,7 +132,7 @@ export function getReasoningEffort(assistant: Assistant, model: Model): Reasonin
     }
 
     // Specially for GPT-5.1. Suppose this is a OpenAI Compatible provider
-    if (isGPT51SeriesModel(model) && reasoningEffort === 'none') {
+    if (isGPT51SeriesModel(model)) {
       return {
         reasoningEffort: 'none'
       }
@@ -278,6 +280,12 @@ export function getReasoningEffort(assistant: Assistant, model: Model): Reasonin
 
   // gemini series, openai compatible api
   if (isSupportedThinkingTokenGeminiModel(model)) {
+    // https://ai.google.dev/gemini-api/docs/gemini-3?thinking=high#openai_compatibility
+    if (isGemini3Model(model)) {
+      return {
+        reasoning_effort: reasoningEffort
+      }
+    }
     if (reasoningEffort === 'auto') {
       return {
         extra_body: {
@@ -341,10 +349,14 @@ export function getReasoningEffort(assistant: Assistant, model: Model): Reasonin
 }
 
 /**
- * 获取 OpenAI 推理参数
+ * Get OpenAI reasoning parameters
- * 从 OpenAIResponseAPIClient 和 OpenAIAPIClient 中提取的逻辑
+ * Extracted from OpenAIResponseAPIClient and OpenAIAPIClient logic
+ * For official OpenAI provider only
  */
-export function getOpenAIReasoningParams(assistant: Assistant, model: Model): Record<string, any> {
+export function getOpenAIReasoningParams(
+  assistant: Assistant,
+  model: Model
+): Pick<OpenAIResponsesProviderOptions, 'reasoningEffort' | 'reasoningSummary'> {
   if (!isReasoningModel(model)) {
     return {}
   }
@@ -355,6 +367,10 @@ export function getOpenAIReasoningParams(assistant: Assistant, model: Model): Re
     return {}
   }
 
+  if (isOpenAIDeepResearchModel(model) || reasoningEffort === 'auto') {
+    reasoningEffort = 'medium'
+  }
+
   // 非OpenAI模型，但是Provider类型是responses/azure openai的情况
   if (!isOpenAIModel(model)) {
     return {
@@ -362,21 +378,17 @@ export function getOpenAIReasoningParams(assistant: Assistant, model: Model): Re
     }
   }
 
-  const openAI = getStoreSetting('openAI') as SettingsState['openAI']
+  const openAI = getStoreSetting('openAI')
-  const summaryText = openAI?.summaryText || 'off'
+  const summaryText = openAI.summaryText
 
-  let reasoningSummary: string | undefined = undefined
+  let reasoningSummary: OpenAISummaryText = undefined
 
-  if (summaryText === 'off' || model.id.includes('o1-pro')) {
+  if (model.id.includes('o1-pro')) {
     reasoningSummary = undefined
   } else {
     reasoningSummary = summaryText
   }
 
-  if (isOpenAIDeepResearchModel(model)) {
-    reasoningEffort = 'medium'
-  }
-
   // OpenAI 推理参数
   if (isSupportedReasoningEffortOpenAIModel(model)) {
     return {
@@ -388,19 +400,26 @@ export function getOpenAIReasoningParams(assistant: Assistant, model: Model): Re
   return {}
 }
 
-export function getAnthropicThinkingBudget(assistant: Assistant, model: Model): number {
+export function getAnthropicThinkingBudget(
-  const { maxTokens, reasoning_effort: reasoningEffort } = getAssistantSettings(assistant)
+  maxTokens: number | undefined,
+  reasoningEffort: string | undefined,
+  modelId: string
+): number | undefined {
   if (reasoningEffort === undefined || reasoningEffort === 'none') {
-    return 0
+    return undefined
   }
   const effortRatio = EFFORT_RATIO[reasoningEffort]
 
+  const tokenLimit = findTokenLimit(modelId)
+  if (!tokenLimit) {
+    return undefined
+  }
+
   const budgetTokens = Math.max(
     1024,
     Math.floor(
       Math.min(
-        (findTokenLimit(model.id)?.max! - findTokenLimit(model.id)?.min!) * effortRatio +
+        (tokenLimit.max - tokenLimit.min) * effortRatio + tokenLimit.min,
-          findTokenLimit(model.id)?.min!,
         (maxTokens || DEFAULT_MAX_TOKENS) * effortRatio
       )
     )
@@ -432,7 +451,8 @@ export function getAnthropicReasoningParams(
 
   // Claude 推理参数
   if (isSupportedThinkingTokenClaudeModel(model)) {
-    const budgetTokens = getAnthropicThinkingBudget(assistant, model)
+    const { maxTokens } = getAssistantSettings(assistant)
+    const budgetTokens = getAnthropicThinkingBudget(maxTokens, reasoningEffort, model.id)
 
     return {
       thinking: {
@@ -445,6 +465,21 @@ export function getAnthropicReasoningParams(
   return {}
 }
 
+type GoogelThinkingLevel = NonNullable<GoogleGenerativeAIProviderOptions['thinkingConfig']>['thinkingLevel']
+
+function mapToGeminiThinkingLevel(reasoningEffort: ReasoningEffortOption): GoogelThinkingLevel {
+  switch (reasoningEffort) {
+    case 'low':
+      return 'low'
+    case 'medium':
+      return 'medium'
+    case 'high':
+      return 'high'
+    default:
+      return 'medium'
+  }
+}
+
 /**
  * 获取 Gemini 推理参数
  * 从 GeminiAPIClient 中提取的逻辑
@@ -472,6 +507,15 @@ export function getGeminiReasoningParams(
       }
     }
 
+    // https://ai.google.dev/gemini-api/docs/gemini-3?thinking=high#new_api_features_in_gemini_3
+    if (isGemini3Model(model)) {
+      return {
+        thinkingConfig: {
+          thinkingLevel: mapToGeminiThinkingLevel(reasoningEffort)
+        }
+      }
+    }
+
     const effortRatio = EFFORT_RATIO[reasoningEffort]
 
     if (effortRatio > 1) {
@@ -555,7 +599,8 @@ export function getBedrockReasoningParams(
     return {}
   }
 
-  const budgetTokens = getAnthropicThinkingBudget(assistant, model)
+  const { maxTokens } = getAssistantSettings(assistant)
+  const budgetTokens = getAnthropicThinkingBudget(maxTokens, reasoningEffort, model.id)
   return {
     reasoningConfig: {
       type: 'enabled',

src/renderer/src/aiCore/utils/websearch.ts

@@ -47,6 +47,7 @@ export function buildProviderBuiltinWebSearchConfig(
   model?: Model
 ): WebSearchPluginConfig | undefined {
   switch (providerId) {
+    case 'azure-responses':
     case 'openai': {
       const searchContextSize = isOpenAIDeepResearchModel(model)
         ? 'medium'

src/renderer/src/components/Selector.tsx

@@ -6,7 +6,7 @@ import { useEffect, useMemo, useRef, useState } from 'react'
 import { useTranslation } from 'react-i18next'
 import styled, { css } from 'styled-components'
 
-interface SelectorOption<V = string | number> {
+interface SelectorOption<V = string | number | undefined | null> {
   label: string | ReactNode
   value: V
   type?: 'group'
@@ -14,7 +14,7 @@ interface SelectorOption<V = string | number> {
   disabled?: boolean
 }
 
-interface BaseSelectorProps<V = string | number> {
+interface BaseSelectorProps<V = string | number | undefined | null> {
   options: SelectorOption<V>[]
   placeholder?: string
   placement?: 'topLeft' | 'topCenter' | 'topRight' | 'bottomLeft' | 'bottomCenter' | 'bottomRight' | 'top' | 'bottom'
@@ -39,7 +39,7 @@ interface MultipleSelectorProps<V> extends BaseSelectorProps<V> {
 
 export type SelectorProps<V> = SingleSelectorProps<V> | MultipleSelectorProps<V>
 
-const Selector = <V extends string | number>({
+const Selector = <V extends string | number | undefined | null>({
   options,
   value,
   onChange = () => {},

src/renderer/src/config/__test__/reasoning.test.ts

@@ -1,520 +0,0 @@
-import { describe, expect, it, vi } from 'vitest'
-
-import {
-  isDoubaoSeedAfter251015,
-  isDoubaoThinkingAutoModel,
-  isGeminiReasoningModel,
-  isLingReasoningModel,
-  isSupportedThinkingTokenGeminiModel
-} from '../models/reasoning'
-
-vi.mock('@renderer/store', () => ({
-  default: {
-    getState: () => ({
-      llm: {
-        settings: {}
-      }
-    })
-  }
-}))
-
-// FIXME: Idk why it's imported. Maybe circular dependency somewhere
-vi.mock('@renderer/services/AssistantService.ts', () => ({
-  getDefaultAssistant: () => {
-    return {
-      id: 'default',
-      name: 'default',
-      emoji: '😀',
-      prompt: '',
-      topics: [],
-      messages: [],
-      type: 'assistant',
-      regularPhrases: [],
-      settings: {}
-    }
-  }
-}))
-
-describe('Doubao Models', () => {
-  describe('isDoubaoThinkingAutoModel', () => {
-    it('should return false for invalid models', () => {
-      expect(
-        isDoubaoThinkingAutoModel({
-          id: 'doubao-seed-1-6-251015',
-          name: 'doubao-seed-1-6-251015',
-          provider: '',
-          group: ''
-        })
-      ).toBe(false)
-      expect(
-        isDoubaoThinkingAutoModel({
-          id: 'doubao-seed-1-6-lite-251015',
-          name: 'doubao-seed-1-6-lite-251015',
-          provider: '',
-          group: ''
-        })
-      ).toBe(false)
-      expect(
-        isDoubaoThinkingAutoModel({
-          id: 'doubao-seed-1-6-thinking-250715',
-          name: 'doubao-seed-1-6-thinking-250715',
-          provider: '',
-          group: ''
-        })
-      ).toBe(false)
-      expect(
-        isDoubaoThinkingAutoModel({
-          id: 'doubao-seed-1-6-flash',
-          name: 'doubao-seed-1-6-flash',
-          provider: '',
-          group: ''
-        })
-      ).toBe(false)
-      expect(
-        isDoubaoThinkingAutoModel({
-          id: 'doubao-seed-1-6-thinking',
-          name: 'doubao-seed-1-6-thinking',
-          provider: '',
-          group: ''
-        })
-      ).toBe(false)
-    })
-
-    it('should return true for valid models', () => {
-      expect(
-        isDoubaoThinkingAutoModel({
-          id: 'doubao-seed-1-6-250615',
-          name: 'doubao-seed-1-6-250615',
-          provider: '',
-          group: ''
-        })
-      ).toBe(true)
-      expect(
-        isDoubaoThinkingAutoModel({
-          id: 'Doubao-Seed-1.6',
-          name: 'Doubao-Seed-1.6',
-          provider: '',
-          group: ''
-        })
-      ).toBe(true)
-      expect(
-        isDoubaoThinkingAutoModel({
-          id: 'doubao-1-5-thinking-pro-m',
-          name: 'doubao-1-5-thinking-pro-m',
-          provider: '',
-          group: ''
-        })
-      ).toBe(true)
-      expect(
-        isDoubaoThinkingAutoModel({
-          id: 'doubao-seed-1.6-lite',
-          name: 'doubao-seed-1.6-lite',
-          provider: '',
-          group: ''
-        })
-      ).toBe(true)
-      expect(
-        isDoubaoThinkingAutoModel({
-          id: 'doubao-1-5-thinking-pro-m-12345',
-          name: 'doubao-1-5-thinking-pro-m-12345',
-          provider: '',
-          group: ''
-        })
-      ).toBe(true)
-    })
-  })
-
-  describe('isDoubaoSeedAfter251015', () => {
-    it('should return true for models matching the pattern', () => {
-      expect(
-        isDoubaoSeedAfter251015({
-          id: 'doubao-seed-1-6-251015',
-          name: '',
-          provider: '',
-          group: ''
-        })
-      ).toBe(true)
-      expect(
-        isDoubaoSeedAfter251015({
-          id: 'doubao-seed-1-6-lite-251015',
-          name: '',
-          provider: '',
-          group: ''
-        })
-      ).toBe(true)
-    })
-
-    it('should return false for models not matching the pattern', () => {
-      expect(
-        isDoubaoSeedAfter251015({
-          id: 'doubao-seed-1-6-250615',
-          name: '',
-          provider: '',
-          group: ''
-        })
-      ).toBe(false)
-      expect(
-        isDoubaoSeedAfter251015({
-          id: 'Doubao-Seed-1.6',
-          name: '',
-          provider: '',
-          group: ''
-        })
-      ).toBe(false)
-      expect(
-        isDoubaoSeedAfter251015({
-          id: 'doubao-1-5-thinking-pro-m',
-          name: '',
-          provider: '',
-          group: ''
-        })
-      ).toBe(false)
-      expect(
-        isDoubaoSeedAfter251015({
-          id: 'doubao-seed-1-6-lite-251016',
-          name: '',
-          provider: '',
-          group: ''
-        })
-      ).toBe(false)
-    })
-  })
-})
-describe('Ling Models', () => {
-  describe('isLingReasoningModel', () => {
-    it('should return false for ling variants', () => {
-      expect(
-        isLingReasoningModel({
-          id: 'ling-1t',
-          name: '',
-          provider: '',
-          group: ''
-        })
-      ).toBe(false)
-      expect(
-        isLingReasoningModel({
-          id: 'ling-flash-2.0',
-          name: '',
-          provider: '',
-          group: ''
-        })
-      ).toBe(false)
-      expect(
-        isLingReasoningModel({
-          id: 'ling-mini-2.0',
-          name: '',
-          provider: '',
-          group: ''
-        })
-      ).toBe(false)
-    })
-
-    it('should return true for ring variants', () => {
-      expect(
-        isLingReasoningModel({
-          id: 'ring-1t',
-          name: '',
-          provider: '',
-          group: ''
-        })
-      ).toBe(true)
-      expect(
-        isLingReasoningModel({
-          id: 'ring-flash-2.0',
-          name: '',
-          provider: '',
-          group: ''
-        })
-      ).toBe(true)
-      expect(
-        isLingReasoningModel({
-          id: 'ring-mini-2.0',
-          name: '',
-          provider: '',
-          group: ''
-        })
-      ).toBe(true)
-    })
-  })
-})
-
-describe('Gemini Models', () => {
-  describe('isSupportedThinkingTokenGeminiModel', () => {
-    it('should return true for gemini 2.5 models', () => {
-      expect(
-        isSupportedThinkingTokenGeminiModel({
-          id: 'gemini-2.5-flash',
-          name: '',
-          provider: '',
-          group: ''
-        })
-      ).toBe(true)
-      expect(
-        isSupportedThinkingTokenGeminiModel({
-          id: 'gemini-2.5-pro',
-          name: '',
-          provider: '',
-          group: ''
-        })
-      ).toBe(true)
-      expect(
-        isSupportedThinkingTokenGeminiModel({
-          id: 'gemini-2.5-flash-latest',
-          name: '',
-          provider: '',
-          group: ''
-        })
-      ).toBe(true)
-      expect(
-        isSupportedThinkingTokenGeminiModel({
-          id: 'gemini-2.5-pro-latest',
-          name: '',
-          provider: '',
-          group: ''
-        })
-      ).toBe(true)
-    })
-
-    it('should return true for gemini latest models', () => {
-      expect(
-        isSupportedThinkingTokenGeminiModel({
-          id: 'gemini-flash-latest',
-          name: '',
-          provider: '',
-          group: ''
-        })
-      ).toBe(true)
-      expect(
-        isSupportedThinkingTokenGeminiModel({
-          id: 'gemini-pro-latest',
-          name: '',
-          provider: '',
-          group: ''
-        })
-      ).toBe(true)
-      expect(
-        isSupportedThinkingTokenGeminiModel({
-          id: 'gemini-flash-lite-latest',
-          name: '',
-          provider: '',
-          group: ''
-        })
-      ).toBe(true)
-    })
-
-    it('should return true for gemini 3 models', () => {
-      // Preview versions
-      expect(
-        isSupportedThinkingTokenGeminiModel({
-          id: 'gemini-3-pro-preview',
-          name: '',
-          provider: '',
-          group: ''
-        })
-      ).toBe(true)
-      expect(
-        isSupportedThinkingTokenGeminiModel({
-          id: 'google/gemini-3-pro-preview',
-          name: '',
-          provider: '',
-          group: ''
-        })
-      ).toBe(true)
-      // Future stable versions
-      expect(
-        isSupportedThinkingTokenGeminiModel({
-          id: 'gemini-3-flash',
-          name: '',
-          provider: '',
-          group: ''
-        })
-      ).toBe(true)
-      expect(
-        isSupportedThinkingTokenGeminiModel({
-          id: 'gemini-3-pro',
-          name: '',
-          provider: '',
-          group: ''
-        })
-      ).toBe(true)
-      expect(
-        isSupportedThinkingTokenGeminiModel({
-          id: 'google/gemini-3-flash',
-          name: '',
-          provider: '',
-          group: ''
-        })
-      ).toBe(true)
-      expect(
-        isSupportedThinkingTokenGeminiModel({
-          id: 'google/gemini-3-pro',
-          name: '',
-          provider: '',
-          group: ''
-        })
-      ).toBe(true)
-    })
-
-    it('should return false for image and tts models', () => {
-      expect(
-        isSupportedThinkingTokenGeminiModel({
-          id: 'gemini-2.5-flash-image',
-          name: '',
-          provider: '',
-          group: ''
-        })
-      ).toBe(false)
-      expect(
-        isSupportedThinkingTokenGeminiModel({
-          id: 'gemini-2.5-flash-preview-tts',
-          name: '',
-          provider: '',
-          group: ''
-        })
-      ).toBe(false)
-    })
-
-    it('should return false for older gemini models', () => {
-      expect(
-        isSupportedThinkingTokenGeminiModel({
-          id: 'gemini-1.5-flash',
-          name: '',
-          provider: '',
-          group: ''
-        })
-      ).toBe(false)
-      expect(
-        isSupportedThinkingTokenGeminiModel({
-          id: 'gemini-1.5-pro',
-          name: '',
-          provider: '',
-          group: ''
-        })
-      ).toBe(false)
-      expect(
-        isSupportedThinkingTokenGeminiModel({
-          id: 'gemini-1.0-pro',
-          name: '',
-          provider: '',
-          group: ''
-        })
-      ).toBe(false)
-    })
-  })
-
-  describe('isGeminiReasoningModel', () => {
-    it('should return true for gemini thinking models', () => {
-      expect(
-        isGeminiReasoningModel({
-          id: 'gemini-2.0-flash-thinking',
-          name: '',
-          provider: '',
-          group: ''
-        })
-      ).toBe(true)
-      expect(
-        isGeminiReasoningModel({
-          id: 'gemini-thinking-exp',
-          name: '',
-          provider: '',
-          group: ''
-        })
-      ).toBe(true)
-    })
-
-    it('should return true for supported thinking token gemini models', () => {
-      expect(
-        isGeminiReasoningModel({
-          id: 'gemini-2.5-flash',
-          name: '',
-          provider: '',
-          group: ''
-        })
-      ).toBe(true)
-      expect(
-        isGeminiReasoningModel({
-          id: 'gemini-2.5-pro',
-          name: '',
-          provider: '',
-          group: ''
-        })
-      ).toBe(true)
-    })
-
-    it('should return true for gemini-3 models', () => {
-      // Preview versions
-      expect(
-        isGeminiReasoningModel({
-          id: 'gemini-3-pro-preview',
-          name: '',
-          provider: '',
-          group: ''
-        })
-      ).toBe(true)
-      expect(
-        isGeminiReasoningModel({
-          id: 'google/gemini-3-pro-preview',
-          name: '',
-          provider: '',
-          group: ''
-        })
-      ).toBe(true)
-      // Future stable versions
-      expect(
-        isGeminiReasoningModel({
-          id: 'gemini-3-flash',
-          name: '',
-          provider: '',
-          group: ''
-        })
-      ).toBe(true)
-      expect(
-        isGeminiReasoningModel({
-          id: 'gemini-3-pro',
-          name: '',
-          provider: '',
-          group: ''
-        })
-      ).toBe(true)
-      expect(
-        isGeminiReasoningModel({
-          id: 'google/gemini-3-flash',
-          name: '',
-          provider: '',
-          group: ''
-        })
-      ).toBe(true)
-      expect(
-        isGeminiReasoningModel({
-          id: 'google/gemini-3-pro',
-          name: '',
-          provider: '',
-          group: ''
-        })
-      ).toBe(true)
-    })
-
-    it('should return false for older gemini models without thinking', () => {
-      expect(
-        isGeminiReasoningModel({
-          id: 'gemini-1.5-flash',
-          name: '',
-          provider: '',
-          group: ''
-        })
-      ).toBe(false)
-      expect(
-        isGeminiReasoningModel({
-          id: 'gemini-1.5-pro',
-          name: '',
-          provider: '',
-          group: ''
-        })
-      ).toBe(false)
-    })
-
-    it('should return false for undefined model', () => {
-      expect(isGeminiReasoningModel(undefined)).toBe(false)
-    })
-  })
-})

src/renderer/src/config/__test__/vision.test.ts

@@ -1,167 +0,0 @@
-import { describe, expect, it, vi } from 'vitest'
-
-import { isVisionModel } from '../models/vision'
-
-vi.mock('@renderer/store', () => ({
-  default: {
-    getState: () => ({
-      llm: {
-        settings: {}
-      }
-    })
-  }
-}))
-
-// FIXME: Idk why it's imported. Maybe circular dependency somewhere
-vi.mock('@renderer/services/AssistantService.ts', () => ({
-  getDefaultAssistant: () => {
-    return {
-      id: 'default',
-      name: 'default',
-      emoji: '😀',
-      prompt: '',
-      topics: [],
-      messages: [],
-      type: 'assistant',
-      regularPhrases: [],
-      settings: {}
-    }
-  },
-  getProviderByModel: () => null
-}))
-
-describe('isVisionModel', () => {
-  describe('Gemini Models', () => {
-    it('should return true for gemini 1.5 models', () => {
-      expect(
-        isVisionModel({
-          id: 'gemini-1.5-flash',
-          name: '',
-          provider: '',
-          group: ''
-        })
-      ).toBe(true)
-      expect(
-        isVisionModel({
-          id: 'gemini-1.5-pro',
-          name: '',
-          provider: '',
-          group: ''
-        })
-      ).toBe(true)
-    })
-
-    it('should return true for gemini 2.x models', () => {
-      expect(
-        isVisionModel({
-          id: 'gemini-2.0-flash',
-          name: '',
-          provider: '',
-          group: ''
-        })
-      ).toBe(true)
-      expect(
-        isVisionModel({
-          id: 'gemini-2.0-pro',
-          name: '',
-          provider: '',
-          group: ''
-        })
-      ).toBe(true)
-      expect(
-        isVisionModel({
-          id: 'gemini-2.5-flash',
-          name: '',
-          provider: '',
-          group: ''
-        })
-      ).toBe(true)
-      expect(
-        isVisionModel({
-          id: 'gemini-2.5-pro',
-          name: '',
-          provider: '',
-          group: ''
-        })
-      ).toBe(true)
-    })
-
-    it('should return true for gemini latest models', () => {
-      expect(
-        isVisionModel({
-          id: 'gemini-flash-latest',
-          name: '',
-          provider: '',
-          group: ''
-        })
-      ).toBe(true)
-      expect(
-        isVisionModel({
-          id: 'gemini-pro-latest',
-          name: '',
-          provider: '',
-          group: ''
-        })
-      ).toBe(true)
-      expect(
-        isVisionModel({
-          id: 'gemini-flash-lite-latest',
-          name: '',
-          provider: '',
-          group: ''
-        })
-      ).toBe(true)
-    })
-
-    it('should return true for gemini 3 models', () => {
-      // Preview versions
-      expect(
-        isVisionModel({
-          id: 'gemini-3-pro-preview',
-          name: '',
-          provider: '',
-          group: ''
-        })
-      ).toBe(true)
-      // Future stable versions
-      expect(
-        isVisionModel({
-          id: 'gemini-3-flash',
-          name: '',
-          provider: '',
-          group: ''
-        })
-      ).toBe(true)
-      expect(
-        isVisionModel({
-          id: 'gemini-3-pro',
-          name: '',
-          provider: '',
-          group: ''
-        })
-      ).toBe(true)
-    })
-
-    it('should return true for gemini exp models', () => {
-      expect(
-        isVisionModel({
-          id: 'gemini-exp-1206',
-          name: '',
-          provider: '',
-          group: ''
-        })
-      ).toBe(true)
-    })
-
-    it('should return false for gemini 1.0 models', () => {
-      expect(
-        isVisionModel({
-          id: 'gemini-1.0-pro',
-          name: '',
-          provider: '',
-          group: ''
-        })
-      ).toBe(false)
-    })
-  })
-})

src/renderer/src/config/__test__/websearch.test.ts

@@ -1,64 +0,0 @@
-import { describe, expect, it, vi } from 'vitest'
-
-import { GEMINI_SEARCH_REGEX } from '../models/websearch'
-
-vi.mock('@renderer/store', () => ({
-  default: {
-    getState: () => ({
-      llm: {
-        settings: {}
-      }
-    })
-  }
-}))
-
-// FIXME: Idk why it's imported. Maybe circular dependency somewhere
-vi.mock('@renderer/services/AssistantService.ts', () => ({
-  getDefaultAssistant: () => {
-    return {
-      id: 'default',
-      name: 'default',
-      emoji: '😀',
-      prompt: '',
-      topics: [],
-      messages: [],
-      type: 'assistant',
-      regularPhrases: [],
-      settings: {}
-    }
-  },
-  getProviderByModel: () => null
-}))
-
-describe('Gemini Search Models', () => {
-  describe('GEMINI_SEARCH_REGEX', () => {
-    it('should match gemini 2.x models', () => {
-      expect(GEMINI_SEARCH_REGEX.test('gemini-2.0-flash')).toBe(true)
-      expect(GEMINI_SEARCH_REGEX.test('gemini-2.0-pro')).toBe(true)
-      expect(GEMINI_SEARCH_REGEX.test('gemini-2.5-flash')).toBe(true)
-      expect(GEMINI_SEARCH_REGEX.test('gemini-2.5-pro')).toBe(true)
-      expect(GEMINI_SEARCH_REGEX.test('gemini-2.5-flash-latest')).toBe(true)
-      expect(GEMINI_SEARCH_REGEX.test('gemini-2.5-pro-latest')).toBe(true)
-    })
-
-    it('should match gemini latest models', () => {
-      expect(GEMINI_SEARCH_REGEX.test('gemini-flash-latest')).toBe(true)
-      expect(GEMINI_SEARCH_REGEX.test('gemini-pro-latest')).toBe(true)
-      expect(GEMINI_SEARCH_REGEX.test('gemini-flash-lite-latest')).toBe(true)
-    })
-
-    it('should match gemini 3 models', () => {
-      // Preview versions
-      expect(GEMINI_SEARCH_REGEX.test('gemini-3-pro-preview')).toBe(true)
-      // Future stable versions
-      expect(GEMINI_SEARCH_REGEX.test('gemini-3-flash')).toBe(true)
-      expect(GEMINI_SEARCH_REGEX.test('gemini-3-pro')).toBe(true)
-    })
-
-    it('should not match older gemini models', () => {
-      expect(GEMINI_SEARCH_REGEX.test('gemini-1.5-flash')).toBe(false)
-      expect(GEMINI_SEARCH_REGEX.test('gemini-1.5-pro')).toBe(false)
-      expect(GEMINI_SEARCH_REGEX.test('gemini-1.0-pro')).toBe(false)
-    })
-  })
-})

src/renderer/src/config/models/__tests__/embedding.test.ts

@@ -0,0 +1,101 @@
+import type { Model } from '@renderer/types'
+import { describe, expect, it, vi } from 'vitest'
+
+vi.mock('@renderer/hooks/useStore', () => ({
+  getStoreProviders: vi.fn(() => [])
+}))
+
+vi.mock('@renderer/store', () => ({
+  __esModule: true,
+  default: {
+    getState: () => ({
+      llm: { providers: [] },
+      settings: {}
+    })
+  },
+  useAppDispatch: vi.fn(),
+  useAppSelector: vi.fn()
+}))
+
+vi.mock('@renderer/store/settings', () => {
+  const noop = vi.fn()
+  return new Proxy(
+    {},
+    {
+      get: (_target, prop) => {
+        if (prop === 'initialState') {
+          return {}
+        }
+        return noop
+      }
+    }
+  )
+})
+
+vi.mock('@renderer/hooks/useSettings', () => ({
+  useSettings: vi.fn(() => ({})),
+  useNavbarPosition: vi.fn(() => ({ navbarPosition: 'left' })),
+  useMessageStyle: vi.fn(() => ({ isBubbleStyle: false })),
+  getStoreSetting: vi.fn()
+}))
+
+import { isEmbeddingModel, isRerankModel } from '../embedding'
+
+const createModel = (overrides: Partial<Model> = {}): Model => ({
+  id: 'test-model',
+  name: 'Test Model',
+  provider: 'openai',
+  group: 'Test',
+  ...overrides
+})
+
+describe('isEmbeddingModel', () => {
+  it('returns true for ids that match the embedding regex', () => {
+    expect(isEmbeddingModel(createModel({ id: 'Text-Embedding-3-Small' }))).toBe(true)
+  })
+
+  it('returns false for rerank models even if they match embedding patterns', () => {
+    const model = createModel({ id: 'rerank-qa', name: 'rerank-qa' })
+    expect(isRerankModel(model)).toBe(true)
+    expect(isEmbeddingModel(model)).toBe(false)
+  })
+
+  it('honors user overrides for embedding capability', () => {
+    const model = createModel({
+      id: 'text-embedding-3-small',
+      capabilities: [{ type: 'embedding', isUserSelected: false }]
+    })
+    expect(isEmbeddingModel(model)).toBe(false)
+  })
+
+  it('uses the model name when provider is doubao', () => {
+    const model = createModel({
+      id: 'custom-id',
+      name: 'BGE-Large-zh-v1.5',
+      provider: 'doubao'
+    })
+    expect(isEmbeddingModel(model)).toBe(true)
+  })
+
+  it('returns false for anthropic provider models', () => {
+    const model = createModel({
+      id: 'text-embedding-ada-002',
+      provider: 'anthropic'
+    })
+    expect(isEmbeddingModel(model)).toBe(false)
+  })
+})
+
+describe('isRerankModel', () => {
+  it('identifies ids that match rerank regex', () => {
+    expect(isRerankModel(createModel({ id: 'jina-rerank-v2-base' }))).toBe(true)
+  })
+
+  it('honors user overrides for rerank capability', () => {
+    const model = createModel({
+      id: 'jina-rerank-v2-base',
+      capabilities: [{ type: 'rerank', isUserSelected: false }]
+    })
+    expect(isRerankModel(model)).toBe(false)
+  })
+})

src/renderer/src/config/models/__tests__/models.test.ts

@@ -1,33 +1,55 @@
 import {
   isImageEnhancementModel,
-  isPureGenerateImageModel,
   isQwenReasoningModel,
   isSupportedThinkingTokenQwenModel,
-  isVisionModel,
+  isVisionModel
-  isWebSearchModel
 } from '@renderer/config/models'
 import type { Model } from '@renderer/types'
 import { beforeEach, describe, expect, test, vi } from 'vitest'
 
+vi.mock('@renderer/store/llm', () => ({
+  initialState: {}
+}))
+
+vi.mock('@renderer/store', () => ({
+  default: {
+    getState: () => ({
+      llm: {
+        settings: {}
+      }
+    })
+  }
+}))
+
+const getProviderByModelMock = vi.fn()
+const isEmbeddingModelMock = vi.fn()
+const isRerankModelMock = vi.fn()
+
+vi.mock('@renderer/services/AssistantService', () => ({
+  getProviderByModel: (...args: any[]) => getProviderByModelMock(...args),
+  getAssistantSettings: vi.fn(),
+  getDefaultAssistant: vi.fn().mockReturnValue({
+    id: 'default',
+    name: 'Default Assistant',
+    prompt: '',
+    settings: {}
+  })
+}))
+
+vi.mock('@renderer/config/models/embedding', () => ({
+  isEmbeddingModel: (...args: any[]) => isEmbeddingModelMock(...args),
+  isRerankModel: (...args: any[]) => isRerankModelMock(...args)
+}))
+
+beforeEach(() => {
+  vi.clearAllMocks()
+  getProviderByModelMock.mockReturnValue({ type: 'openai-response' } as any)
+  isEmbeddingModelMock.mockReturnValue(false)
+  isRerankModelMock.mockReturnValue(false)
+})
+
 // Suggested test cases
 describe('Qwen Model Detection', () => {
-  beforeEach(() => {
-    vi.mock('@renderer/store/llm', () => ({
-      initialState: {}
-    }))
-    vi.mock('@renderer/services/AssistantService', () => ({
-      getProviderByModel: vi.fn().mockReturnValue({ id: 'cherryai' })
-    }))
-    vi.mock('@renderer/store', () => ({
-      default: {
-        getState: () => ({
-          llm: {
-            settings: {}
-          }
-        })
-      }
-    }))
-  })
   test('isQwenReasoningModel', () => {
     expect(isQwenReasoningModel({ id: 'qwen3-thinking' } as Model)).toBe(true)
     expect(isQwenReasoningModel({ id: 'qwen3-instruct' } as Model)).toBe(false)
@@ -56,14 +78,6 @@ describe('Qwen Model Detection', () => {
 })
 
 describe('Vision Model Detection', () => {
-  beforeEach(() => {
-    vi.mock('@renderer/store/llm', () => ({
-      initialState: {}
-    }))
-    vi.mock('@renderer/services/AssistantService', () => ({
-      getProviderByModel: vi.fn().mockReturnValue({ id: 'cherryai' })
-    }))
-  })
   test('isVisionModel', () => {
     expect(isVisionModel({ id: 'qwen-vl-max' } as Model)).toBe(true)
     expect(isVisionModel({ id: 'qwen-omni-turbo' } as Model)).toBe(true)
@@ -75,25 +89,4 @@ describe('Vision Model Detection', () => {
     expect(isImageEnhancementModel({ id: 'qwen-image-edit' } as Model)).toBe(true)
     expect(isImageEnhancementModel({ id: 'grok-2-image-latest' } as Model)).toBe(true)
   })
-  test('isPureGenerateImageModel', () => {
-    expect(isPureGenerateImageModel({ id: 'gpt-image-1' } as Model)).toBe(true)
-    expect(isPureGenerateImageModel({ id: 'gemini-2.5-flash-image-preview' } as Model)).toBe(true)
-    expect(isPureGenerateImageModel({ id: 'gemini-2.0-flash-preview-image-generation' } as Model)).toBe(true)
-    expect(isPureGenerateImageModel({ id: 'grok-2-image-latest' } as Model)).toBe(true)
-    expect(isPureGenerateImageModel({ id: 'gpt-4o' } as Model)).toBe(false)
-  })
-})
-
-describe('Web Search Model Detection', () => {
-  beforeEach(() => {
-    vi.mock('@renderer/store/llm', () => ({
-      initialState: {}
-    }))
-    vi.mock('@renderer/services/AssistantService', () => ({
-      getProviderByModel: vi.fn().mockReturnValue({ id: 'cherryai' })
-    }))
-  })
-  test('isWebSearchModel', () => {
-    expect(isWebSearchModel({ id: 'grok-2-image-latest' } as Model)).toBe(false)
-  })
 })

src/renderer/src/config/models/__tests__/tooluse.test.ts

@@ -0,0 +1,137 @@
+import type { Model } from '@renderer/types'
+import { beforeEach, describe, expect, it, vi } from 'vitest'
+
+import { isEmbeddingModel, isRerankModel } from '../embedding'
+import { isDeepSeekHybridInferenceModel } from '../reasoning'
+import { isFunctionCallingModel } from '../tooluse'
+import { isPureGenerateImageModel, isTextToImageModel } from '../vision'
+
+vi.mock('@renderer/hooks/useStore', () => ({
+  getStoreProviders: vi.fn(() => [])
+}))
+
+vi.mock('@renderer/store', () => ({
+  __esModule: true,
+  default: {
+    getState: () => ({
+      llm: { providers: [] },
+      settings: {}
+    })
+  },
+  useAppDispatch: vi.fn(),
+  useAppSelector: vi.fn()
+}))
+
+vi.mock('@renderer/store/settings', () => {
+  const noop = vi.fn()
+  return new Proxy(
+    {},
+    {
+      get: (_target, prop) => {
+        if (prop === 'initialState') {
+          return {}
+        }
+        return noop
+      }
+    }
+  )
+})
+
+vi.mock('@renderer/hooks/useSettings', () => ({
+  useSettings: vi.fn(() => ({})),
+  useNavbarPosition: vi.fn(() => ({ navbarPosition: 'left' })),
+  useMessageStyle: vi.fn(() => ({ isBubbleStyle: false })),
+  getStoreSetting: vi.fn()
+}))
+
+vi.mock('../embedding', () => ({
+  isEmbeddingModel: vi.fn(),
+  isRerankModel: vi.fn()
+}))
+
+vi.mock('../vision', () => ({
+  isPureGenerateImageModel: vi.fn(),
+  isTextToImageModel: vi.fn()
+}))
+
+vi.mock('../reasoning', () => ({
+  isDeepSeekHybridInferenceModel: vi.fn()
+}))
+
+const createModel = (overrides: Partial<Model> = {}): Model => ({
+  id: 'gpt-4o',
+  name: 'gpt-4o',
+  provider: 'openai',
+  group: 'OpenAI',
+  ...overrides
+})
+
+const embeddingMock = vi.mocked(isEmbeddingModel)
+const rerankMock = vi.mocked(isRerankModel)
+const pureImageMock = vi.mocked(isPureGenerateImageModel)
+const textToImageMock = vi.mocked(isTextToImageModel)
+const deepSeekHybridMock = vi.mocked(isDeepSeekHybridInferenceModel)
+
+describe('isFunctionCallingModel', () => {
+  beforeEach(() => {
+    vi.clearAllMocks()
+    embeddingMock.mockReturnValue(false)
+    rerankMock.mockReturnValue(false)
+    pureImageMock.mockReturnValue(false)
+    textToImageMock.mockReturnValue(false)
+    deepSeekHybridMock.mockReturnValue(false)
+  })
+
+  it('returns false when the model is undefined', () => {
+    expect(isFunctionCallingModel(undefined as unknown as Model)).toBe(false)
+  })
+
+  it('returns false when model is classified as embedding/rerank/image', () => {
+    embeddingMock.mockReturnValueOnce(true)
+    expect(isFunctionCallingModel(createModel())).toBe(false)
+  })
+
+  it('respect manual user overrides', () => {
+    const model = createModel({
+      capabilities: [{ type: 'function_calling', isUserSelected: false }]
+    })
+    expect(isFunctionCallingModel(model)).toBe(false)
+    const enabled = createModel({
+      capabilities: [{ type: 'function_calling', isUserSelected: true }]
+    })
+    expect(isFunctionCallingModel(enabled)).toBe(true)
+  })
+
+  it('matches doubao models by name when regex applies', () => {
+    const doubao = createModel({
+      id: 'custom-model',
+      name: 'Doubao-Seed-1.6-251015',
+      provider: 'doubao'
+    })
+    expect(isFunctionCallingModel(doubao)).toBe(true)
+  })
+
+  it('returns true for regex matches on standard providers', () => {
+    expect(isFunctionCallingModel(createModel({ id: 'gpt-5' }))).toBe(true)
+  })
+
+  it('excludes explicitly blocked ids', () => {
+    expect(isFunctionCallingModel(createModel({ id: 'gemini-1.5-flash' }))).toBe(false)
+  })
+
+  it('forces support for trusted providers', () => {
+    for (const provider of ['deepseek', 'anthropic', 'kimi', 'moonshot']) {
+      expect(isFunctionCallingModel(createModel({ provider }))).toBe(true)
+    }
+  })
+
+  it('returns true when identified as deepseek hybrid inference model', () => {
+    deepSeekHybridMock.mockReturnValueOnce(true)
+    expect(isFunctionCallingModel(createModel({ id: 'deepseek-v3-1', provider: 'custom' }))).toBe(true)
+  })
+
+  it('returns false for deepseek hybrid models behind restricted system providers', () => {
+    deepSeekHybridMock.mockReturnValueOnce(true)
+    expect(isFunctionCallingModel(createModel({ id: 'deepseek-v3-1', provider: 'dashscope' }))).toBe(false)
+  })
+})

src/renderer/src/config/models/__tests__/utils.test.ts

@@ -0,0 +1,280 @@
+import { isEmbeddingModel, isRerankModel } from '@renderer/config/models/embedding'
+import type { Model } from '@renderer/types'
+import { beforeEach, describe, expect, it, vi } from 'vitest'
+
+import {
+  isGPT5ProModel,
+  isGPT5SeriesModel,
+  isGPT5SeriesReasoningModel,
+  isGPT51SeriesModel,
+  isOpenAIChatCompletionOnlyModel,
+  isOpenAILLMModel,
+  isOpenAIModel,
+  isOpenAIOpenWeightModel,
+  isOpenAIReasoningModel,
+  isSupportVerbosityModel
+} from '../openai'
+import { isQwenMTModel } from '../qwen'
+import {
+  agentModelFilter,
+  getModelSupportedVerbosity,
+  groupQwenModels,
+  isAnthropicModel,
+  isGeminiModel,
+  isGemmaModel,
+  isGenerateImageModels,
+  isMaxTemperatureOneModel,
+  isNotSupportedTextDelta,
+  isNotSupportSystemMessageModel,
+  isNotSupportTemperatureAndTopP,
+  isSupportedFlexServiceTier,
+  isSupportedModel,
+  isSupportFlexServiceTierModel,
+  isVisionModels,
+  isZhipuModel
+} from '../utils'
+import { isGenerateImageModel, isTextToImageModel, isVisionModel } from '../vision'
+import { isOpenAIWebSearchChatCompletionOnlyModel } from '../websearch'
+
+vi.mock('@renderer/hooks/useStore', () => ({
+  getStoreProviders: vi.fn(() => [])
+}))
+
+vi.mock('@renderer/store', () => ({
+  __esModule: true,
+  default: {
+    getState: () => ({
+      llm: { providers: [] },
+      settings: {}
+    })
+  },
+  useAppDispatch: vi.fn(),
+  useAppSelector: vi.fn()
+}))
+
+vi.mock('@renderer/store/settings', () => {
+  const noop = vi.fn()
+  return new Proxy(
+    {},
+    {
+      get: (_target, prop) => {
+        if (prop === 'initialState') {
+          return {}
+        }
+        return noop
+      }
+    }
+  )
+})
+
+vi.mock('@renderer/hooks/useSettings', () => ({
+  useSettings: vi.fn(() => ({})),
+  useNavbarPosition: vi.fn(() => ({ navbarPosition: 'left' })),
+  useMessageStyle: vi.fn(() => ({ isBubbleStyle: false })),
+  getStoreSetting: vi.fn()
+}))
+
+vi.mock('@renderer/config/models/embedding', () => ({
+  isEmbeddingModel: vi.fn(),
+  isRerankModel: vi.fn()
+}))
+
+vi.mock('../vision', () => ({
+  isGenerateImageModel: vi.fn(),
+  isTextToImageModel: vi.fn(),
+  isVisionModel: vi.fn()
+}))
+
+vi.mock(import('../openai'), async (importOriginal) => {
+  const actual = await importOriginal()
+  return {
+    ...actual,
+    isOpenAIReasoningModel: vi.fn()
+  }
+})
+
+vi.mock('../websearch', () => ({
+  isOpenAIWebSearchChatCompletionOnlyModel: vi.fn()
+}))
+
+const createModel = (overrides: Partial<Model> = {}): Model => ({
+  id: 'gpt-4o',
+  name: 'gpt-4o',
+  provider: 'openai',
+  group: 'OpenAI',
+  ...overrides
+})
+
+const embeddingMock = vi.mocked(isEmbeddingModel)
+const rerankMock = vi.mocked(isRerankModel)
+const visionMock = vi.mocked(isVisionModel)
+const textToImageMock = vi.mocked(isTextToImageModel)
+const generateImageMock = vi.mocked(isGenerateImageModel)
+const reasoningMock = vi.mocked(isOpenAIReasoningModel)
+const openAIWebSearchOnlyMock = vi.mocked(isOpenAIWebSearchChatCompletionOnlyModel)
+
+describe('model utils', () => {
+  beforeEach(() => {
+    vi.clearAllMocks()
+    embeddingMock.mockReturnValue(false)
+    rerankMock.mockReturnValue(false)
+    visionMock.mockReturnValue(true)
+    textToImageMock.mockReturnValue(false)
+    generateImageMock.mockReturnValue(true)
+    reasoningMock.mockReturnValue(false)
+    openAIWebSearchOnlyMock.mockReturnValue(false)
+  })
+
+  it('detects OpenAI LLM models through reasoning and GPT prefix', () => {
+    expect(isOpenAILLMModel(undefined as unknown as Model)).toBe(false)
+    expect(isOpenAILLMModel(createModel({ id: 'gpt-4o-image' }))).toBe(false)
+
+    reasoningMock.mockReturnValueOnce(true)
+    expect(isOpenAILLMModel(createModel({ id: 'o1-preview' }))).toBe(true)
+
+    expect(isOpenAILLMModel(createModel({ id: 'GPT-5-turbo' }))).toBe(true)
+  })
+
+  it('detects OpenAI models via GPT prefix or reasoning support', () => {
+    expect(isOpenAIModel(createModel({ id: 'gpt-4.1' }))).toBe(true)
+    reasoningMock.mockReturnValueOnce(true)
+    expect(isOpenAIModel(createModel({ id: 'o3' }))).toBe(true)
+  })
+
+  it('evaluates support for flex service tier and alias helper', () => {
+    expect(isSupportFlexServiceTierModel(createModel({ id: 'o3' }))).toBe(true)
+    expect(isSupportFlexServiceTierModel(createModel({ id: 'o3-mini' }))).toBe(false)
+    expect(isSupportFlexServiceTierModel(createModel({ id: 'o4-mini' }))).toBe(true)
+    expect(isSupportFlexServiceTierModel(createModel({ id: 'gpt-5-preview' }))).toBe(true)
+    expect(isSupportedFlexServiceTier(createModel({ id: 'gpt-4o' }))).toBe(false)
+  })
+
+  it('detects verbosity support for GPT-5+ families', () => {
+    expect(isSupportVerbosityModel(createModel({ id: 'gpt-5' }))).toBe(true)
+    expect(isSupportVerbosityModel(createModel({ id: 'gpt-5-chat' }))).toBe(false)
+    expect(isSupportVerbosityModel(createModel({ id: 'gpt-5.1-preview' }))).toBe(true)
+  })
+
+  it('limits verbosity controls for GPT-5 Pro models', () => {
+    const proModel = createModel({ id: 'gpt-5-pro' })
+    const previewModel = createModel({ id: 'gpt-5-preview' })
+    expect(getModelSupportedVerbosity(proModel)).toEqual([undefined, 'high'])
+    expect(getModelSupportedVerbosity(previewModel)).toEqual([undefined, 'low', 'medium', 'high'])
+    expect(isGPT5ProModel(proModel)).toBe(true)
+    expect(isGPT5ProModel(previewModel)).toBe(false)
+  })
+
+  it('identifies OpenAI chat-completion-only models', () => {
+    expect(isOpenAIChatCompletionOnlyModel(createModel({ id: 'gpt-4o-search-preview' }))).toBe(true)
+    expect(isOpenAIChatCompletionOnlyModel(createModel({ id: 'o1-mini' }))).toBe(true)
+    expect(isOpenAIChatCompletionOnlyModel(createModel({ id: 'gpt-4o' }))).toBe(false)
+  })
+
+  it('filters unsupported OpenAI catalog entries', () => {
+    expect(isSupportedModel({ id: 'gpt-4', object: 'model' } as any)).toBe(true)
+    expect(isSupportedModel({ id: 'tts-1', object: 'model' } as any)).toBe(false)
+  })
+
+  it('calculates temperature/top-p support correctly', () => {
+    const model = createModel({ id: 'o1' })
+    reasoningMock.mockReturnValue(true)
+    expect(isNotSupportTemperatureAndTopP(model)).toBe(true)
+
+    const openWeight = createModel({ id: 'gpt-oss-debug' })
+    expect(isNotSupportTemperatureAndTopP(openWeight)).toBe(false)
+
+    const chatOnly = createModel({ id: 'o1-preview' })
+    reasoningMock.mockReturnValue(false)
+    expect(isNotSupportTemperatureAndTopP(chatOnly)).toBe(true)
+
+    const qwenMt = createModel({ id: 'qwen-mt-large', provider: 'aliyun' })
+    expect(isNotSupportTemperatureAndTopP(qwenMt)).toBe(true)
+  })
+
+  it('handles gemma and gemini detections plus zhipu tagging', () => {
+    expect(isGemmaModel(createModel({ id: 'Gemma-3-27B' }))).toBe(true)
+    expect(isGemmaModel(createModel({ group: 'Gemma' }))).toBe(true)
+    expect(isGemmaModel(createModel({ id: 'gpt-4o' }))).toBe(false)
+
+    expect(isGeminiModel(createModel({ id: 'Gemini-2.0' }))).toBe(true)
+
+    expect(isZhipuModel(createModel({ provider: 'zhipu' }))).toBe(true)
+    expect(isZhipuModel(createModel({ provider: 'openai' }))).toBe(false)
+  })
+
+  it('groups qwen models by prefix', () => {
+    const qwen = createModel({ id: 'Qwen-7B', provider: 'qwen', name: 'Qwen-7B' })
+    const qwenOmni = createModel({ id: 'qwen2.5-omni', name: 'qwen2.5-omni' })
+    const other = createModel({ id: 'deepseek-v3', group: 'DeepSeek' })
+
+    const grouped = groupQwenModels([qwen, qwenOmni, other])
+    expect(Object.keys(grouped)).toContain('qwen-7b')
+    expect(Object.keys(grouped)).toContain('qwen2.5')
+    expect(grouped.DeepSeek).toContain(other)
+  })
+
+  it('aggregates boolean helpers based on regex rules', () => {
+    expect(isAnthropicModel(createModel({ id: 'claude-3.5' }))).toBe(true)
+    expect(isQwenMTModel(createModel({ id: 'qwen-mt-large' }))).toBe(true)
+    expect(isNotSupportedTextDelta(createModel({ id: 'qwen-mt-large' }))).toBe(true)
+    expect(isNotSupportSystemMessageModel(createModel({ id: 'gemma-moe' }))).toBe(true)
+    expect(isOpenAIOpenWeightModel(createModel({ id: 'gpt-oss-free' }))).toBe(true)
+  })
+
+  it('evaluates GPT-5 family helpers', () => {
+    expect(isGPT5SeriesModel(createModel({ id: 'gpt-5-preview' }))).toBe(true)
+    expect(isGPT5SeriesModel(createModel({ id: 'gpt-5.1-preview' }))).toBe(false)
+    expect(isGPT51SeriesModel(createModel({ id: 'gpt-5.1-mini' }))).toBe(true)
+    expect(isGPT5SeriesReasoningModel(createModel({ id: 'gpt-5-prompt' }))).toBe(true)
+    expect(isSupportVerbosityModel(createModel({ id: 'gpt-5-chat' }))).toBe(false)
+  })
+
+  it('wraps generate/vision helpers that operate on arrays', () => {
+    const models = [createModel({ id: 'gpt-4o' }), createModel({ id: 'gpt-4o-mini' })]
+    expect(isVisionModels(models)).toBe(true)
+    visionMock.mockReturnValueOnce(true).mockReturnValueOnce(false)
+    expect(isVisionModels(models)).toBe(false)
+
+    expect(isGenerateImageModels(models)).toBe(true)
+    generateImageMock.mockReturnValueOnce(true).mockReturnValueOnce(false)
+    expect(isGenerateImageModels(models)).toBe(false)
+  })
+
+  it('filters models for agent usage', () => {
+    expect(agentModelFilter(createModel())).toBe(true)
+
+    embeddingMock.mockReturnValueOnce(true)
+    expect(agentModelFilter(createModel({ id: 'text-embedding' }))).toBe(false)
+
+    embeddingMock.mockReturnValue(false)
+    rerankMock.mockReturnValueOnce(true)
+    expect(agentModelFilter(createModel({ id: 'rerank' }))).toBe(false)
+
+    rerankMock.mockReturnValue(false)
+    textToImageMock.mockReturnValueOnce(true)
+    expect(agentModelFilter(createModel({ id: 'gpt-image-1' }))).toBe(false)
+  })
+
+  it('identifies models with maximum temperature of 1.0', () => {
+    // Zhipu models should have max temperature of 1.0
+    expect(isMaxTemperatureOneModel(createModel({ id: 'glm-4' }))).toBe(true)
+    expect(isMaxTemperatureOneModel(createModel({ id: 'GLM-4-Plus' }))).toBe(true)
+    expect(isMaxTemperatureOneModel(createModel({ id: 'glm-3-turbo' }))).toBe(true)
+
+    // Anthropic models should have max temperature of 1.0
+    expect(isMaxTemperatureOneModel(createModel({ id: 'claude-3.5-sonnet' }))).toBe(true)
+    expect(isMaxTemperatureOneModel(createModel({ id: 'Claude-3-opus' }))).toBe(true)
+    expect(isMaxTemperatureOneModel(createModel({ id: 'claude-2.1' }))).toBe(true)
+
+    // Moonshot models should have max temperature of 1.0
+    expect(isMaxTemperatureOneModel(createModel({ id: 'moonshot-1.0' }))).toBe(true)
+    expect(isMaxTemperatureOneModel(createModel({ id: 'kimi-k2-thinking' }))).toBe(true)
+    expect(isMaxTemperatureOneModel(createModel({ id: 'Moonshot-Pro' }))).toBe(true)
+
+    // Other models should return false
+    expect(isMaxTemperatureOneModel(createModel({ id: 'gpt-4o' }))).toBe(false)
+    expect(isMaxTemperatureOneModel(createModel({ id: 'gpt-4-turbo' }))).toBe(false)
+    expect(isMaxTemperatureOneModel(createModel({ id: 'qwen-max' }))).toBe(false)
+    expect(isMaxTemperatureOneModel(createModel({ id: 'gemini-pro' }))).toBe(false)
+  })
+})

src/renderer/src/config/models/__tests__/vision.test.ts

@@ -0,0 +1,311 @@
+import { getProviderByModel } from '@renderer/services/AssistantService'
+import type { Model } from '@renderer/types'
+import { beforeEach, describe, expect, it, vi } from 'vitest'
+
+import { isEmbeddingModel, isRerankModel } from '../embedding'
+import {
+  isAutoEnableImageGenerationModel,
+  isDedicatedImageGenerationModel,
+  isGenerateImageModel,
+  isImageEnhancementModel,
+  isPureGenerateImageModel,
+  isTextToImageModel,
+  isVisionModel
+} from '../vision'
+
+vi.mock('@renderer/hooks/useStore', () => ({
+  getStoreProviders: vi.fn(() => [])
+}))
+
+vi.mock('@renderer/store', () => ({
+  __esModule: true,
+  default: {
+    getState: () => ({
+      llm: { providers: [] },
+      settings: {}
+    })
+  },
+  useAppDispatch: vi.fn(),
+  useAppSelector: vi.fn()
+}))
+
+vi.mock('@renderer/store/settings', () => {
+  const noop = vi.fn()
+  return new Proxy(
+    {},
+    {
+      get: (_target, prop) => {
+        if (prop === 'initialState') {
+          return {}
+        }
+        return noop
+      }
+    }
+  )
+})
+
+vi.mock('@renderer/hooks/useSettings', () => ({
+  useSettings: vi.fn(() => ({})),
+  useNavbarPosition: vi.fn(() => ({ navbarPosition: 'left' })),
+  useMessageStyle: vi.fn(() => ({ isBubbleStyle: false })),
+  getStoreSetting: vi.fn()
+}))
+
+vi.mock('@renderer/services/AssistantService', () => ({
+  getProviderByModel: vi.fn()
+}))
+
+vi.mock('../embedding', () => ({
+  isEmbeddingModel: vi.fn(),
+  isRerankModel: vi.fn()
+}))
+
+const createModel = (overrides: Partial<Model> = {}): Model => ({
+  id: 'gpt-4o',
+  name: 'gpt-4o',
+  provider: 'openai',
+  group: 'OpenAI',
+  ...overrides
+})
+
+const providerMock = vi.mocked(getProviderByModel)
+const embeddingMock = vi.mocked(isEmbeddingModel)
+const rerankMock = vi.mocked(isRerankModel)
+
+describe('vision helpers', () => {
+  beforeEach(() => {
+    vi.clearAllMocks()
+    providerMock.mockReturnValue({ type: 'openai-response' } as any)
+    embeddingMock.mockReturnValue(false)
+    rerankMock.mockReturnValue(false)
+  })
+
+  describe('isGenerateImageModel', () => {
+    it('returns false for embedding/rerank models or missing providers', () => {
+      embeddingMock.mockReturnValueOnce(true)
+      expect(isGenerateImageModel(createModel({ id: 'gpt-image-1' }))).toBe(false)
+
+      embeddingMock.mockReturnValue(false)
+      rerankMock.mockReturnValueOnce(true)
+      expect(isGenerateImageModel(createModel({ id: 'gpt-image-1' }))).toBe(false)
+
+      rerankMock.mockReturnValue(false)
+      providerMock.mockReturnValueOnce(undefined as any)
+      expect(isGenerateImageModel(createModel({ id: 'gpt-image-1' }))).toBe(false)
+    })
+
+    it('detects OpenAI and third-party generative image models', () => {
+      expect(isGenerateImageModel(createModel({ id: 'gpt-4o-mini' }))).toBe(true)
+
+      providerMock.mockReturnValue({ type: 'custom' } as any)
+      expect(isGenerateImageModel(createModel({ id: 'gemini-2.5-flash-image' }))).toBe(true)
+    })
+
+    it('returns false when openai-response model is not on allow list', () => {
+      expect(isGenerateImageModel(createModel({ id: 'gpt-4.2-experimental' }))).toBe(false)
+    })
+  })
+
+  describe('isPureGenerateImageModel', () => {
+    it('requires both generate and text-to-image support', () => {
+      expect(isPureGenerateImageModel(createModel({ id: 'gpt-image-1' }))).toBe(true)
+      expect(isPureGenerateImageModel(createModel({ id: 'gpt-4o' }))).toBe(false)
+      expect(isPureGenerateImageModel(createModel({ id: 'gemini-2.5-flash-image-preview' }))).toBe(true)
+    })
+  })
+
+  describe('text-to-image helpers', () => {
+    it('matches predefined keywords', () => {
+      expect(isTextToImageModel(createModel({ id: 'midjourney-v6' }))).toBe(true)
+      expect(isTextToImageModel(createModel({ id: 'gpt-4o' }))).toBe(false)
+    })
+
+    it('detects models with restricted image size support and enhancement', () => {
+      expect(isImageEnhancementModel(createModel({ id: 'qwen-image-edit' }))).toBe(true)
+      expect(isImageEnhancementModel(createModel({ id: 'gpt-4o' }))).toBe(false)
+    })
+
+    it('identifies dedicated and auto-enabled image generation models', () => {
+      expect(isDedicatedImageGenerationModel(createModel({ id: 'grok-2-image-1212' }))).toBe(true)
+      expect(isAutoEnableImageGenerationModel(createModel({ id: 'gemini-2.5-flash-image-ultra' }))).toBe(true)
+    })
+
+    it('returns false when models are not in dedicated or auto-enable sets', () => {
+      expect(isDedicatedImageGenerationModel(createModel({ id: 'gpt-4o' }))).toBe(false)
+      expect(isAutoEnableImageGenerationModel(createModel({ id: 'gpt-4o' }))).toBe(false)
+    })
+  })
+})
+
+describe('isVisionModel', () => {
+  it('returns false for embedding/rerank models and honors overrides', () => {
+    embeddingMock.mockReturnValueOnce(true)
+    expect(isVisionModel(createModel({ id: 'gpt-4o' }))).toBe(false)
+
+    embeddingMock.mockReturnValue(false)
+    const disabled = createModel({
+      id: 'gpt-4o',
+      capabilities: [{ type: 'vision', isUserSelected: false }]
+    })
+    expect(isVisionModel(disabled)).toBe(false)
+
+    const forced = createModel({
+      id: 'gpt-4o',
+      capabilities: [{ type: 'vision', isUserSelected: true }]
+    })
+    expect(isVisionModel(forced)).toBe(true)
+  })
+
+  it('matches doubao models by name and general regexes by id', () => {
+    const doubao = createModel({
+      id: 'custom-id',
+      provider: 'doubao',
+      name: 'Doubao-Seed-1-6-Lite-251015'
+    })
+    expect(isVisionModel(doubao)).toBe(true)
+
+    expect(isVisionModel(createModel({ id: 'gpt-4o-mini' }))).toBe(true)
+  })
+
+  it('leverages image enhancement regex when standard vision regex does not match', () => {
+    expect(isVisionModel(createModel({ id: 'qwen-image-edit' }))).toBe(true)
+  })
+
+  it('returns false for doubao models that fail regex checks', () => {
+    const doubao = createModel({ id: 'doubao-standard', provider: 'doubao', name: 'basic' })
+    expect(isVisionModel(doubao)).toBe(false)
+  })
+  describe('Gemini Models', () => {
+    it('should return true for gemini 1.5 models', () => {
+      expect(
+        isVisionModel({
+          id: 'gemini-1.5-flash',
+          name: '',
+          provider: '',
+          group: ''
+        })
+      ).toBe(true)
+      expect(
+        isVisionModel({
+          id: 'gemini-1.5-pro',
+          name: '',
+          provider: '',
+          group: ''
+        })
+      ).toBe(true)
+    })
+
+    it('should return true for gemini 2.x models', () => {
+      expect(
+        isVisionModel({
+          id: 'gemini-2.0-flash',
+          name: '',
+          provider: '',
+          group: ''
+        })
+      ).toBe(true)
+      expect(
+        isVisionModel({
+          id: 'gemini-2.0-pro',
+          name: '',
+          provider: '',
+          group: ''
+        })
+      ).toBe(true)
+      expect(
+        isVisionModel({
+          id: 'gemini-2.5-flash',
+          name: '',
+          provider: '',
+          group: ''
+        })
+      ).toBe(true)
+      expect(
+        isVisionModel({
+          id: 'gemini-2.5-pro',
+          name: '',
+          provider: '',
+          group: ''
+        })
+      ).toBe(true)
+    })
+
+    it('should return true for gemini latest models', () => {
+      expect(
+        isVisionModel({
+          id: 'gemini-flash-latest',
+          name: '',
+          provider: '',
+          group: ''
+        })
+      ).toBe(true)
+      expect(
+        isVisionModel({
+          id: 'gemini-pro-latest',
+          name: '',
+          provider: '',
+          group: ''
+        })
+      ).toBe(true)
+      expect(
+        isVisionModel({
+          id: 'gemini-flash-lite-latest',
+          name: '',
+          provider: '',
+          group: ''
+        })
+      ).toBe(true)
+    })
+
+    it('should return true for gemini 3 models', () => {
+      // Preview versions
+      expect(
+        isVisionModel({
+          id: 'gemini-3-pro-preview',
+          name: '',
+          provider: '',
+          group: ''
+        })
+      ).toBe(true)
+      // Future stable versions
+      expect(
+        isVisionModel({
+          id: 'gemini-3-flash',
+          name: '',
+          provider: '',
+          group: ''
+        })
+      ).toBe(true)
+      expect(
+        isVisionModel({
+          id: 'gemini-3-pro',
+          name: '',
+          provider: '',
+          group: ''
+        })
+      ).toBe(true)
+    })
+
+    it('should return true for gemini exp models', () => {
+      expect(
+        isVisionModel({
+          id: 'gemini-exp-1206',
+          name: '',
+          provider: '',
+          group: ''
+        })
+      ).toBe(true)
+    })
+
+    it('should return false for gemini 1.0 models', () => {
+      expect(
+        isVisionModel({
+          id: 'gemini-1.0-pro',
+          name: '',
+          provider: '',
+          group: ''
+        })
+      ).toBe(false)
+    })
+  })
+})

src/renderer/src/config/models/__tests__/websearch.test.ts

@@ -0,0 +1,397 @@
+import { beforeEach, describe, expect, it, vi } from 'vitest'
+
+const providerMock = vi.mocked(getProviderByModel)
+
+vi.mock('@renderer/services/AssistantService', () => ({
+  getProviderByModel: vi.fn(),
+  getAssistantSettings: vi.fn(),
+  getDefaultAssistant: vi.fn().mockReturnValue({
+    id: 'default',
+    name: 'Default Assistant',
+    prompt: '',
+    settings: {}
+  })
+}))
+
+const isEmbeddingModel = vi.hoisted(() => vi.fn())
+const isRerankModel = vi.hoisted(() => vi.fn())
+vi.mock('../embedding', () => ({
+  isEmbeddingModel: (...args: any[]) => isEmbeddingModel(...args),
+  isRerankModel: (...args: any[]) => isRerankModel(...args)
+}))
+
+const isPureGenerateImageModel = vi.hoisted(() => vi.fn())
+const isTextToImageModel = vi.hoisted(() => vi.fn())
+const isGenerateImageModel = vi.hoisted(() => vi.fn())
+vi.mock('../vision', () => ({
+  isPureGenerateImageModel: (...args: any[]) => isPureGenerateImageModel(...args),
+  isTextToImageModel: (...args: any[]) => isTextToImageModel(...args),
+  isGenerateImageModel: (...args: any[]) => isGenerateImageModel(...args),
+  isModernGenerateImageModel: vi.fn()
+}))
+
+const providerMocks = vi.hoisted(() => ({
+  isGeminiProvider: vi.fn(),
+  isNewApiProvider: vi.fn(),
+  isOpenAICompatibleProvider: vi.fn(),
+  isOpenAIProvider: vi.fn(),
+  isVertexProvider: vi.fn(),
+  isAwsBedrockProvider: vi.fn(),
+  isAzureOpenAIProvider: vi.fn()
+}))
+
+vi.mock('@renderer/utils/provider', () => providerMocks)
+
+vi.mock('@renderer/hooks/useStore', () => ({
+  getStoreProviders: vi.fn(() => [])
+}))
+
+vi.mock('@renderer/store', () => ({
+  __esModule: true,
+  default: {
+    getState: () => ({
+      llm: { providers: [] },
+      settings: {}
+    })
+  },
+  useAppDispatch: vi.fn(),
+  useAppSelector: vi.fn()
+}))
+
+vi.mock('@renderer/store/settings', () => {
+  const noop = vi.fn()
+  return new Proxy(
+    {},
+    {
+      get: (_target, prop) => {
+        if (prop === 'initialState') {
+          return {}
+        }
+        return noop
+      }
+    }
+  )
+})
+
+vi.mock('@renderer/hooks/useSettings', () => ({
+  useSettings: vi.fn(() => ({})),
+  useNavbarPosition: vi.fn(() => ({ navbarPosition: 'left' })),
+  useMessageStyle: vi.fn(() => ({ isBubbleStyle: false })),
+  getStoreSetting: vi.fn()
+}))
+
+import { getProviderByModel } from '@renderer/services/AssistantService'
+import type { Model, Provider } from '@renderer/types'
+import { SystemProviderIds } from '@renderer/types'
+
+import { isOpenAIDeepResearchModel } from '../openai'
+import {
+  GEMINI_SEARCH_REGEX,
+  isHunyuanSearchModel,
+  isMandatoryWebSearchModel,
+  isOpenAIWebSearchChatCompletionOnlyModel,
+  isOpenAIWebSearchModel,
+  isOpenRouterBuiltInWebSearchModel,
+  isWebSearchModel
+} from '../websearch'
+
+const createModel = (overrides: Partial<Model> = {}): Model => ({
+  id: 'gpt-4o',
+  name: 'gpt-4o',
+  provider: 'openai',
+  group: 'OpenAI',
+  ...overrides
+})
+
+const createProvider = (overrides: Partial<Provider> = {}): Provider => ({
+  id: 'openai',
+  type: 'openai',
+  name: 'OpenAI',
+  apiKey: '',
+  apiHost: '',
+  models: [],
+  ...overrides
+})
+
+const resetMocks = () => {
+  providerMock.mockReturnValue(createProvider())
+  isEmbeddingModel.mockReturnValue(false)
+  isRerankModel.mockReturnValue(false)
+  isPureGenerateImageModel.mockReturnValue(false)
+  isTextToImageModel.mockReturnValue(false)
+  providerMocks.isGeminiProvider.mockReturnValue(false)
+  providerMocks.isNewApiProvider.mockReturnValue(false)
+  providerMocks.isOpenAICompatibleProvider.mockReturnValue(false)
+  providerMocks.isOpenAIProvider.mockReturnValue(false)
+}
+
+describe('websearch helpers', () => {
+  beforeEach(() => {
+    vi.clearAllMocks()
+    resetMocks()
+  })
+
+  describe('isOpenAIDeepResearchModel', () => {
+    it('detects deep research ids for OpenAI only', () => {
+      expect(isOpenAIDeepResearchModel(createModel({ id: 'openai/deep-research-preview' }))).toBe(true)
+      expect(isOpenAIDeepResearchModel(createModel({ provider: 'openai', id: 'gpt-4o' }))).toBe(false)
+      expect(isOpenAIDeepResearchModel(createModel({ provider: 'openrouter', id: 'deep-research' }))).toBe(false)
+    })
+  })
+
+  describe('isWebSearchModel', () => {
+    it('returns false for embedding/rerank/image models', () => {
+      isEmbeddingModel.mockReturnValueOnce(true)
+      expect(isWebSearchModel(createModel())).toBe(false)
+
+      resetMocks()
+      isRerankModel.mockReturnValueOnce(true)
+      expect(isWebSearchModel(createModel())).toBe(false)
+
+      resetMocks()
+      isTextToImageModel.mockReturnValueOnce(true)
+      expect(isWebSearchModel(createModel())).toBe(false)
+    })
+
+    it('honors user overrides', () => {
+      const enabled = createModel({ capabilities: [{ type: 'web_search', isUserSelected: true }] })
+      expect(isWebSearchModel(enabled)).toBe(true)
+
+      const disabled = createModel({ capabilities: [{ type: 'web_search', isUserSelected: false }] })
+      expect(isWebSearchModel(disabled)).toBe(false)
+    })
+
+    it('returns false when provider lookup fails', () => {
+      providerMock.mockReturnValueOnce(undefined as any)
+      expect(isWebSearchModel(createModel())).toBe(false)
+    })
+
+    it('handles Anthropic providers on unsupported platforms', () => {
+      providerMock.mockReturnValueOnce(createProvider({ id: SystemProviderIds['aws-bedrock'] }))
+      const model = createModel({ id: 'claude-2-sonnet' })
+      expect(isWebSearchModel(model)).toBe(false)
+    })
+
+    it('returns true for first-party Anthropic provider', () => {
+      providerMock.mockReturnValueOnce(createProvider({ id: 'anthropic' }))
+      const model = createModel({ id: 'claude-3.5-sonnet-latest', provider: 'anthropic' })
+      expect(isWebSearchModel(model)).toBe(true)
+    })
+
+    it('detects OpenAI preview search models only when supported', () => {
+      providerMocks.isOpenAIProvider.mockReturnValue(true)
+      const model = createModel({ id: 'gpt-4o-search-preview' })
+      expect(isWebSearchModel(model)).toBe(true)
+
+      const nonSearch = createModel({ id: 'gpt-4o-image' })
+      expect(isWebSearchModel(nonSearch)).toBe(false)
+    })
+
+    it('supports Perplexity sonar families including mandatory variants', () => {
+      providerMock.mockReturnValueOnce(createProvider({ id: SystemProviderIds.perplexity }))
+      expect(isWebSearchModel(createModel({ id: 'sonar-deep-research' }))).toBe(true)
+    })
+
+    it('handles AIHubMix Gemini and OpenAI search models', () => {
+      providerMock.mockReturnValueOnce(createProvider({ id: SystemProviderIds.aihubmix }))
+      expect(isWebSearchModel(createModel({ id: 'gemini-2.5-pro-preview' }))).toBe(true)
+
+      providerMock.mockReturnValueOnce(createProvider({ id: SystemProviderIds.aihubmix }))
+      const openaiSearch = createModel({ id: 'gpt-4o-search-preview' })
+      expect(isWebSearchModel(openaiSearch)).toBe(true)
+    })
+
+    it('supports OpenAI-compatible or new API providers for Gemini/OpenAI models', () => {
+      const model = createModel({ id: 'gemini-2.5-flash-lite-latest' })
+      providerMock.mockReturnValueOnce(createProvider({ id: 'custom' }))
+      providerMocks.isOpenAICompatibleProvider.mockReturnValueOnce(true)
+      expect(isWebSearchModel(model)).toBe(true)
+
+      resetMocks()
+      providerMock.mockReturnValueOnce(createProvider({ id: 'custom' }))
+      providerMocks.isNewApiProvider.mockReturnValueOnce(true)
+      expect(isWebSearchModel(createModel({ id: 'gpt-4o-search-preview' }))).toBe(true)
+    })
+
+    it('falls back to Gemini/Vertex provider regex matching', () => {
+      providerMock.mockReturnValueOnce(createProvider({ id: SystemProviderIds.vertexai }))
+      providerMocks.isGeminiProvider.mockReturnValueOnce(true)
+      expect(isWebSearchModel(createModel({ id: 'gemini-2.0-flash-latest' }))).toBe(true)
+    })
+
+    it('evaluates hunyuan/zhipu/dashscope/openrouter/grok providers', () => {
+      providerMock.mockReturnValueOnce(createProvider({ id: 'hunyuan' }))
+      expect(isWebSearchModel(createModel({ id: 'hunyuan-pro' }))).toBe(true)
+      expect(isWebSearchModel(createModel({ id: 'hunyuan-lite', provider: 'hunyuan' }))).toBe(false)
+
+      providerMock.mockReturnValueOnce(createProvider({ id: 'zhipu' }))
+      expect(isWebSearchModel(createModel({ id: 'glm-4-air' }))).toBe(true)
+
+      providerMock.mockReturnValueOnce(createProvider({ id: 'dashscope' }))
+      expect(isWebSearchModel(createModel({ id: 'qwen-max-latest' }))).toBe(true)
+
+      providerMock.mockReturnValueOnce(createProvider({ id: 'openrouter' }))
+      expect(isWebSearchModel(createModel())).toBe(true)
+
+      providerMock.mockReturnValueOnce(createProvider({ id: 'grok' }))
+      expect(isWebSearchModel(createModel({ id: 'grok-2' }))).toBe(true)
+    })
+  })
+
+  describe('isMandatoryWebSearchModel', () => {
+    it('requires sonar ids for perplexity/openrouter providers', () => {
+      providerMock.mockReturnValueOnce(createProvider({ id: SystemProviderIds.perplexity }))
+      expect(isMandatoryWebSearchModel(createModel({ id: 'sonar-pro' }))).toBe(true)
+
+      providerMock.mockReturnValueOnce(createProvider({ id: SystemProviderIds.openrouter }))
+      expect(isMandatoryWebSearchModel(createModel({ id: 'sonar-reasoning' }))).toBe(true)
+
+      providerMock.mockReturnValueOnce(createProvider({ id: 'openai' }))
+      expect(isMandatoryWebSearchModel(createModel({ id: 'sonar-pro' }))).toBe(false)
+    })
+
+    it.each([
+      ['perplexity', 'non-sonar'],
+      ['openrouter', 'gpt-4o-search-preview']
+    ])('returns false for %s provider when id is %s', (providerId, modelId) => {
+      providerMock.mockReturnValueOnce(createProvider({ id: providerId }))
+      expect(isMandatoryWebSearchModel(createModel({ id: modelId }))).toBe(false)
+    })
+  })
+
+  describe('isOpenRouterBuiltInWebSearchModel', () => {
+    it('checks for sonar ids or OpenAI chat-completion-only variants', () => {
+      providerMock.mockReturnValueOnce(createProvider({ id: 'openrouter' }))
+      expect(isOpenRouterBuiltInWebSearchModel(createModel({ id: 'sonar-reasoning' }))).toBe(true)
+
+      providerMock.mockReturnValueOnce(createProvider({ id: 'openrouter' }))
+      expect(isOpenRouterBuiltInWebSearchModel(createModel({ id: 'gpt-4o-search-preview' }))).toBe(true)
+
+      providerMock.mockReturnValueOnce(createProvider({ id: 'custom' }))
+      expect(isOpenRouterBuiltInWebSearchModel(createModel({ id: 'sonar-reasoning' }))).toBe(false)
+    })
+  })
+
+  describe('OpenAI web search helpers', () => {
+    it('detects chat completion only variants and openai search ids', () => {
+      expect(isOpenAIWebSearchChatCompletionOnlyModel(createModel({ id: 'gpt-4o-search-preview' }))).toBe(true)
+      expect(isOpenAIWebSearchChatCompletionOnlyModel(createModel({ id: 'gpt-4o-mini-search-preview' }))).toBe(true)
+      expect(isOpenAIWebSearchChatCompletionOnlyModel(createModel({ id: 'gpt-4o' }))).toBe(false)
+
+      expect(isOpenAIWebSearchModel(createModel({ id: 'gpt-4.1-turbo' }))).toBe(true)
+      expect(isOpenAIWebSearchModel(createModel({ id: 'gpt-4o-image' }))).toBe(false)
+      expect(isOpenAIWebSearchModel(createModel({ id: 'gpt-5.1-chat' }))).toBe(false)
+      expect(isOpenAIWebSearchModel(createModel({ id: 'o3-mini' }))).toBe(true)
+    })
+
+    it.each(['gpt-4.1-preview', 'gpt-4o-2024-05-13', 'o4-mini', 'gpt-5-explorer'])(
+      'treats %s as an OpenAI web search model',
+      (id) => {
+        expect(isOpenAIWebSearchModel(createModel({ id }))).toBe(true)
+      }
+    )
+
+    it.each(['gpt-4o-image-preview', 'gpt-4.1-nano', 'gpt-5.1-chat', 'gpt-image-1'])(
+      'excludes %s from OpenAI web search',
+      (id) => {
+        expect(isOpenAIWebSearchModel(createModel({ id }))).toBe(false)
+      }
+    )
+
+    it.each(['gpt-4o-search-preview', 'gpt-4o-mini-search-preview'])('flags %s as chat-completion-only', (id) => {
+      expect(isOpenAIWebSearchChatCompletionOnlyModel(createModel({ id }))).toBe(true)
+    })
+  })
+
+  describe('isHunyuanSearchModel', () => {
+    it('identifies hunyuan models except lite', () => {
+      expect(isHunyuanSearchModel(createModel({ id: 'hunyuan-pro', provider: 'hunyuan' }))).toBe(true)
+      expect(isHunyuanSearchModel(createModel({ id: 'hunyuan-lite', provider: 'hunyuan' }))).toBe(false)
+      expect(isHunyuanSearchModel(createModel())).toBe(false)
+    })
+
+    it.each(['hunyuan-standard', 'hunyuan-advanced'])('accepts %s', (suffix) => {
+      expect(isHunyuanSearchModel(createModel({ id: suffix, provider: 'hunyuan' }))).toBe(true)
+    })
+  })
+
+  describe('provider-specific regex coverage', () => {
+    it.each(['qwen-turbo', 'qwen-max-0919', 'qwen3-max', 'qwen-plus-2024', 'qwq-32b'])(
+      'dashscope treats %s as searchable',
+      (id) => {
+        providerMock.mockReturnValue(createProvider({ id: 'dashscope' }))
+        expect(isWebSearchModel(createModel({ id }))).toBe(true)
+      }
+    )
+
+    it.each(['qwen-1.5-chat', 'custom-model'])('dashscope ignores %s', (id) => {
+      providerMock.mockReturnValue(createProvider({ id: 'dashscope' }))
+      expect(isWebSearchModel(createModel({ id }))).toBe(false)
+    })
+
+    it.each(['sonar', 'sonar-pro', 'sonar-reasoning-pro', 'sonar-deep-research'])(
+      'perplexity provider supports %s',
+      (id) => {
+        providerMock.mockReturnValue(createProvider({ id: SystemProviderIds.perplexity }))
+        expect(isWebSearchModel(createModel({ id }))).toBe(true)
+      }
+    )
+
+    it.each([
+      'gemini-2.0-flash-latest',
+      'gemini-2.5-flash-lite-latest',
+      'gemini-flash-lite-latest',
+      'gemini-pro-latest'
+    ])('Gemini provider supports %s', (id) => {
+      providerMock.mockReturnValue(createProvider({ id: SystemProviderIds.vertexai }))
+      providerMocks.isGeminiProvider.mockReturnValue(true)
+      expect(isWebSearchModel(createModel({ id }))).toBe(true)
+    })
+  })
+
+  describe('Gemini Search Models', () => {
+    describe('GEMINI_SEARCH_REGEX', () => {
+      it('should match gemini 2.x models', () => {
+        expect(GEMINI_SEARCH_REGEX.test('gemini-2.0-flash')).toBe(true)
+        expect(GEMINI_SEARCH_REGEX.test('gemini-2.0-pro')).toBe(true)
+        expect(GEMINI_SEARCH_REGEX.test('gemini-2.5-flash')).toBe(true)
+        expect(GEMINI_SEARCH_REGEX.test('gemini-2.5-pro')).toBe(true)
+        expect(GEMINI_SEARCH_REGEX.test('gemini-2.5-flash-latest')).toBe(true)
+        expect(GEMINI_SEARCH_REGEX.test('gemini-2.5-pro-latest')).toBe(true)
+      })
+
+      it('should match gemini latest models', () => {
+        expect(GEMINI_SEARCH_REGEX.test('gemini-flash-latest')).toBe(true)
+        expect(GEMINI_SEARCH_REGEX.test('gemini-pro-latest')).toBe(true)
+        expect(GEMINI_SEARCH_REGEX.test('gemini-flash-lite-latest')).toBe(true)
+      })
+
+      it('should match gemini 3 models', () => {
+        // Preview versions
+        expect(GEMINI_SEARCH_REGEX.test('gemini-3-pro-preview')).toBe(true)
+        expect(GEMINI_SEARCH_REGEX.test('gemini-3-flash-preview')).toBe(true)
+        expect(GEMINI_SEARCH_REGEX.test('gemini-3-pro-image-preview')).toBe(true)
+        expect(GEMINI_SEARCH_REGEX.test('gemini-3-flash-image-preview')).toBe(true)
+        // Future stable versions
+        expect(GEMINI_SEARCH_REGEX.test('gemini-3-flash')).toBe(true)
+        expect(GEMINI_SEARCH_REGEX.test('gemini-3-pro')).toBe(true)
+        // Version with decimals
+        expect(GEMINI_SEARCH_REGEX.test('gemini-3.0-flash')).toBe(true)
+        expect(GEMINI_SEARCH_REGEX.test('gemini-3.0-pro')).toBe(true)
+        expect(GEMINI_SEARCH_REGEX.test('gemini-3.5-flash-preview')).toBe(true)
+        expect(GEMINI_SEARCH_REGEX.test('gemini-3.5-pro-image-preview')).toBe(true)
+      })
+
+      it('should not match gemini 2.x image-preview models', () => {
+        expect(GEMINI_SEARCH_REGEX.test('gemini-2.5-flash-image-preview')).toBe(false)
+        expect(GEMINI_SEARCH_REGEX.test('gemini-2.0-pro-image-preview')).toBe(false)
+      })
+
+      it('should not match older gemini models', () => {
+        expect(GEMINI_SEARCH_REGEX.test('gemini-1.5-flash')).toBe(false)
+        expect(GEMINI_SEARCH_REGEX.test('gemini-1.5-pro')).toBe(false)
+        expect(GEMINI_SEARCH_REGEX.test('gemini-1.0-pro')).toBe(false)
+      })
+    })
+  })
+})

src/renderer/src/config/models/index.ts

@@ -1,6 +1,8 @@
 export * from './default'
 export * from './embedding'
 export * from './logo'
+export * from './openai'
+export * from './qwen'
 export * from './reasoning'
 export * from './tooluse'
 export * from './utils'

src/renderer/src/config/models/openai.ts

@@ -0,0 +1,107 @@
+import type { Model } from '@renderer/types'
+import { getLowerBaseModelName } from '@renderer/utils'
+
+export const OPENAI_NO_SUPPORT_DEV_ROLE_MODELS = ['o1-preview', 'o1-mini']
+
+export function isOpenAILLMModel(model: Model): boolean {
+  if (!model) {
+    return false
+  }
+  const modelId = getLowerBaseModelName(model.id)
+
+  if (modelId.includes('gpt-4o-image')) {
+    return false
+  }
+  if (isOpenAIReasoningModel(model)) {
+    return true
+  }
+  if (modelId.includes('gpt')) {
+    return true
+  }
+  return false
+}
+
+export function isOpenAIModel(model: Model): boolean {
+  if (!model) {
+    return false
+  }
+  const modelId = getLowerBaseModelName(model.id)
+
+  return modelId.includes('gpt') || isOpenAIReasoningModel(model)
+}
+
+export const isGPT5ProModel = (model: Model) => {
+  const modelId = getLowerBaseModelName(model.id)
+  return modelId.includes('gpt-5-pro')
+}
+
+export const isOpenAIOpenWeightModel = (model: Model) => {
+  const modelId = getLowerBaseModelName(model.id)
+  return modelId.includes('gpt-oss')
+}
+
+export const isGPT5SeriesModel = (model: Model) => {
+  const modelId = getLowerBaseModelName(model.id)
+  return modelId.includes('gpt-5') && !modelId.includes('gpt-5.1')
+}
+
+export const isGPT5SeriesReasoningModel = (model: Model) => {
+  const modelId = getLowerBaseModelName(model.id)
+  return isGPT5SeriesModel(model) && !modelId.includes('chat')
+}
+
+export const isGPT51SeriesModel = (model: Model) => {
+  const modelId = getLowerBaseModelName(model.id)
+  return modelId.includes('gpt-5.1')
+}
+
+export function isSupportVerbosityModel(model: Model): boolean {
+  const modelId = getLowerBaseModelName(model.id)
+  return (isGPT5SeriesModel(model) || isGPT51SeriesModel(model)) && !modelId.includes('chat')
+}
+
+export function isOpenAIChatCompletionOnlyModel(model: Model): boolean {
+  if (!model) {
+    return false
+  }
+
+  const modelId = getLowerBaseModelName(model.id)
+  return (
+    modelId.includes('gpt-4o-search-preview') ||
+    modelId.includes('gpt-4o-mini-search-preview') ||
+    modelId.includes('o1-mini') ||
+    modelId.includes('o1-preview')
+  )
+}
+
+export function isOpenAIReasoningModel(model: Model): boolean {
+  const modelId = getLowerBaseModelName(model.id, '/')
+  return isSupportedReasoningEffortOpenAIModel(model) || modelId.includes('o1')
+}
+
+export function isSupportedReasoningEffortOpenAIModel(model: Model): boolean {
+  const modelId = getLowerBaseModelName(model.id)
+  return (
+    (modelId.includes('o1') && !(modelId.includes('o1-preview') || modelId.includes('o1-mini'))) ||
+    modelId.includes('o3') ||
+    modelId.includes('o4') ||
+    modelId.includes('gpt-oss') ||
+    ((isGPT5SeriesModel(model) || isGPT51SeriesModel(model)) && !modelId.includes('chat'))
+  )
+}
+
+const OPENAI_DEEP_RESEARCH_MODEL_REGEX = /deep[-_]?research/
+
+export function isOpenAIDeepResearchModel(model?: Model): boolean {
+  if (!model) {
+    return false
+  }
+
+  const providerId = model.provider
+  if (providerId !== 'openai' && providerId !== 'openai-chat') {
+    return false
+  }
+
+  const modelId = getLowerBaseModelName(model.id, '/')
+  return OPENAI_DEEP_RESEARCH_MODEL_REGEX.test(modelId)
+}

src/renderer/src/config/models/qwen.ts

@@ -0,0 +1,7 @@
+import type { Model } from '@renderer/types'
+import { getLowerBaseModelName } from '@renderer/utils'
+
+export const isQwenMTModel = (model: Model): boolean => {
+  const modelId = getLowerBaseModelName(model.id)
+  return modelId.includes('qwen-mt')
+}

src/renderer/src/config/models/reasoning.ts

@@ -8,9 +8,16 @@ import type {
 import { getLowerBaseModelName, isUserSelectedModelType } from '@renderer/utils'
 
 import { isEmbeddingModel, isRerankModel } from './embedding'
-import { isGPT5ProModel, isGPT5SeriesModel, isGPT51SeriesModel } from './utils'
+import {
+  isGPT5ProModel,
+  isGPT5SeriesModel,
+  isGPT51SeriesModel,
+  isOpenAIDeepResearchModel,
+  isOpenAIReasoningModel,
+  isSupportedReasoningEffortOpenAIModel
+} from './openai'
+import { GEMINI_FLASH_MODEL_REGEX, isGemini3Model } from './utils'
 import { isTextToImageModel } from './vision'
-import { GEMINI_FLASH_MODEL_REGEX, isOpenAIDeepResearchModel } from './websearch'
 
 // Reasoning models
 export const REASONING_REGEX =
@@ -30,6 +37,7 @@ export const MODEL_SUPPORTED_REASONING_EFFORT: ReasoningEffortConfig = {
   grok: ['low', 'high'] as const,
   grok4_fast: ['auto'] as const,
   gemini: ['low', 'medium', 'high', 'auto'] as const,
+  gemini3: ['low', 'medium', 'high'] as const,
   gemini_pro: ['low', 'medium', 'high', 'auto'] as const,
   qwen: ['low', 'medium', 'high'] as const,
   qwen_thinking: ['low', 'medium', 'high'] as const,
@@ -56,6 +64,7 @@ export const MODEL_SUPPORTED_OPTIONS: ThinkingOptionConfig = {
   grok4_fast: ['none', ...MODEL_SUPPORTED_REASONING_EFFORT.grok4_fast] as const,
   gemini: ['none', ...MODEL_SUPPORTED_REASONING_EFFORT.gemini] as const,
   gemini_pro: MODEL_SUPPORTED_REASONING_EFFORT.gemini_pro,
+  gemini3: MODEL_SUPPORTED_REASONING_EFFORT.gemini3,
   qwen: ['none', ...MODEL_SUPPORTED_REASONING_EFFORT.qwen] as const,
   qwen_thinking: MODEL_SUPPORTED_REASONING_EFFORT.qwen_thinking,
   doubao: ['none', ...MODEL_SUPPORTED_REASONING_EFFORT.doubao] as const,
@@ -106,6 +115,9 @@ const _getThinkModelType = (model: Model): ThinkingModelType => {
     } else {
       thinkingModelType = 'gemini_pro'
     }
+    if (isGemini3Model(model)) {
+      thinkingModelType = 'gemini3'
+    }
   } else if (isSupportedReasoningEffortGrokModel(model)) thinkingModelType = 'grok'
   else if (isSupportedThinkingTokenQwenModel(model)) {
     if (isQwenAlwaysThinkModel(model)) {
@@ -254,11 +266,19 @@ export function isGeminiReasoningModel(model?: Model): boolean {
 
 // Gemini 支持思考模式的模型正则
 export const GEMINI_THINKING_MODEL_REGEX =
-  /gemini-(?:2\.5.*(?:-latest)?|3-(?:flash|pro)(?:-preview)?|flash-latest|pro-latest|flash-lite-latest)(?:-[\w-]+)*$/i
+  /gemini-(?:2\.5.*(?:-latest)?|3(?:\.\d+)?-(?:flash|pro)(?:-preview)?|flash-latest|pro-latest|flash-lite-latest)(?:-[\w-]+)*$/i
 
 export const isSupportedThinkingTokenGeminiModel = (model: Model): boolean => {
   const modelId = getLowerBaseModelName(model.id, '/')
   if (GEMINI_THINKING_MODEL_REGEX.test(modelId)) {
+    // gemini-3.x 的 image 模型支持思考模式
+    if (isGemini3Model(model)) {
+      if (modelId.includes('tts')) {
+        return false
+      }
+      return true
+    }
+    // gemini-2.x 的 image/tts 模型不支持
     if (modelId.includes('image') || modelId.includes('tts')) {
       return false
     }
@@ -382,6 +402,12 @@ export function isClaude45ReasoningModel(model: Model): boolean {
   return regex.test(modelId)
 }
 
+export function isClaude4SeriesModel(model: Model): boolean {
+  const modelId = getLowerBaseModelName(model.id, '/')
+  const regex = /claude-(sonnet|opus|haiku)-4(?:[.-]\d+)?(?:-[\w-]+)?$/i
+  return regex.test(modelId)
+}
+
 export function isClaudeReasoningModel(model?: Model): boolean {
   if (!model) {
     return false
@@ -529,22 +555,6 @@ export function isReasoningModel(model?: Model): boolean {
   return REASONING_REGEX.test(modelId) || false
 }
 
-export function isOpenAIReasoningModel(model: Model): boolean {
-  const modelId = getLowerBaseModelName(model.id, '/')
-  return isSupportedReasoningEffortOpenAIModel(model) || modelId.includes('o1')
-}
-
-export function isSupportedReasoningEffortOpenAIModel(model: Model): boolean {
-  const modelId = getLowerBaseModelName(model.id)
-  return (
-    (modelId.includes('o1') && !(modelId.includes('o1-preview') || modelId.includes('o1-mini'))) ||
-    modelId.includes('o3') ||
-    modelId.includes('o4') ||
-    modelId.includes('gpt-oss') ||
-    ((isGPT5SeriesModel(model) || isGPT51SeriesModel(model)) && !modelId.includes('chat'))
-  )
-}
-
 export const THINKING_TOKEN_MAP: Record<string, { min: number; max: number }> = {
   // Gemini models
   'gemini-2\\.5-flash-lite.*$': { min: 512, max: 24576 },

src/renderer/src/config/models/tooluse.ts

@@ -4,7 +4,7 @@ import { getLowerBaseModelName, isUserSelectedModelType } from '@renderer/utils'
 
 import { isEmbeddingModel, isRerankModel } from './embedding'
 import { isDeepSeekHybridInferenceModel } from './reasoning'
-import { isPureGenerateImageModel, isTextToImageModel } from './vision'
+import { isTextToImageModel } from './vision'
 
 // Tool calling models
 export const FUNCTION_CALLING_MODELS = [
@@ -41,7 +41,9 @@ const FUNCTION_CALLING_EXCLUDED_MODELS = [
   'gemini-1(?:\\.[\\w-]+)?',
   'qwen-mt(?:-[\\w-]+)?',
   'gpt-5-chat(?:-[\\w-]+)?',
-  'glm-4\\.5v'
+  'glm-4\\.5v',
+  'gemini-2.5-flash-image(?:-[\\w-]+)?',
+  'gemini-2.0-flash-preview-image-generation'
 ]
 
 export const FUNCTION_CALLING_REGEX = new RegExp(
@@ -50,13 +52,7 @@ export const FUNCTION_CALLING_REGEX = new RegExp(
 )
 
 export function isFunctionCallingModel(model?: Model): boolean {
-  if (
+  if (!model || isEmbeddingModel(model) || isRerankModel(model) || isTextToImageModel(model)) {
-    !model ||
-    isEmbeddingModel(model) ||
-    isRerankModel(model) ||
-    isTextToImageModel(model) ||
-    isPureGenerateImageModel(model)
-  ) {
     return false
   }
 
@@ -66,10 +62,6 @@ export function isFunctionCallingModel(model?: Model): boolean {
     return isUserSelectedModelType(model, 'function_calling')!
   }
 
-  if (model.provider === 'qiniu') {
-    return ['deepseek-v3-tool', 'deepseek-v3-0324', 'qwq-32b', 'qwen2.5-72b-instruct'].includes(modelId)
-  }
-
   if (model.provider === 'doubao' || modelId.includes('doubao')) {
     return FUNCTION_CALLING_REGEX.test(modelId) || FUNCTION_CALLING_REGEX.test(model.name)
   }

src/renderer/src/config/models/utils.ts

@@ -1,43 +1,14 @@
 import type OpenAI from '@cherrystudio/openai'
 import { isEmbeddingModel, isRerankModel } from '@renderer/config/models/embedding'
-import type { Model } from '@renderer/types'
+import { type Model, SystemProviderIds } from '@renderer/types'
+import type { OpenAIVerbosity, ValidOpenAIVerbosity } from '@renderer/types/aiCoreTypes'
 import { getLowerBaseModelName } from '@renderer/utils'
-import { WEB_SEARCH_PROMPT_FOR_OPENROUTER } from '@shared/config/prompts'
 
-import { getWebSearchTools } from '../tools'
+import { isOpenAIChatCompletionOnlyModel, isOpenAIOpenWeightModel, isOpenAIReasoningModel } from './openai'
-import { isOpenAIReasoningModel } from './reasoning'
+import { isQwenMTModel } from './qwen'
 import { isGenerateImageModel, isTextToImageModel, isVisionModel } from './vision'
-import { isOpenAIWebSearchChatCompletionOnlyModel } from './websearch'
 export const NOT_SUPPORTED_REGEX = /(?:^tts|whisper|speech)/i
-
+export const GEMINI_FLASH_MODEL_REGEX = new RegExp('gemini.*-flash.*$', 'i')
-export const OPENAI_NO_SUPPORT_DEV_ROLE_MODELS = ['o1-preview', 'o1-mini']
-
-export function isOpenAILLMModel(model: Model): boolean {
-  if (!model) {
-    return false
-  }
-  const modelId = getLowerBaseModelName(model.id)
-
-  if (modelId.includes('gpt-4o-image')) {
-    return false
-  }
-  if (isOpenAIReasoningModel(model)) {
-    return true
-  }
-  if (modelId.includes('gpt')) {
-    return true
-  }
-  return false
-}
-
-export function isOpenAIModel(model: Model): boolean {
-  if (!model) {
-    return false
-  }
-  const modelId = getLowerBaseModelName(model.id)
-
-  return modelId.includes('gpt') || isOpenAIReasoningModel(model)
-}
 
 export function isSupportFlexServiceTierModel(model: Model): boolean {
   if (!model) {
@@ -52,33 +23,6 @@ export function isSupportedFlexServiceTier(model: Model): boolean {
   return isSupportFlexServiceTierModel(model)
 }
 
-export function isSupportVerbosityModel(model: Model): boolean {
-  const modelId = getLowerBaseModelName(model.id)
-  return (isGPT5SeriesModel(model) || isGPT51SeriesModel(model)) && !modelId.includes('chat')
-}
-
-export function isOpenAIChatCompletionOnlyModel(model: Model): boolean {
-  if (!model) {
-    return false
-  }
-
-  const modelId = getLowerBaseModelName(model.id)
-  return (
-    modelId.includes('gpt-4o-search-preview') ||
-    modelId.includes('gpt-4o-mini-search-preview') ||
-    modelId.includes('o1-mini') ||
-    modelId.includes('o1-preview')
-  )
-}
-
-export function isGrokModel(model?: Model): boolean {
-  if (!model) {
-    return false
-  }
-  const modelId = getLowerBaseModelName(model.id)
-  return modelId.includes('grok')
-}
-
 export function isSupportedModel(model: OpenAI.Models.Model): boolean {
   if (!model) {
     return false
@@ -105,53 +49,6 @@ export function isNotSupportTemperatureAndTopP(model: Model): boolean {
   return false
 }
 
-export function getOpenAIWebSearchParams(model: Model, isEnableWebSearch?: boolean): Record<string, any> {
-  if (!isEnableWebSearch) {
-    return {}
-  }
-
-  const webSearchTools = getWebSearchTools(model)
-
-  if (model.provider === 'grok') {
-    return {
-      search_parameters: {
-        mode: 'auto',
-        return_citations: true,
-        sources: [{ type: 'web' }, { type: 'x' }, { type: 'news' }]
-      }
-    }
-  }
-
-  if (model.provider === 'hunyuan') {
-    return { enable_enhancement: true, citation: true, search_info: true }
-  }
-
-  if (model.provider === 'dashscope') {
-    return {
-      enable_search: true,
-      search_options: {
-        forced_search: true
-      }
-    }
-  }
-
-  if (isOpenAIWebSearchChatCompletionOnlyModel(model)) {
-    return {
-      web_search_options: {}
-    }
-  }
-
-  if (model.provider === 'openrouter') {
-    return {
-      plugins: [{ id: 'web', search_prompts: WEB_SEARCH_PROMPT_FOR_OPENROUTER }]
-    }
-  }
-
-  return {
-    tools: webSearchTools
-  }
-}
-
 export function isGemmaModel(model?: Model): boolean {
   if (!model) {
     return false
@@ -161,12 +58,14 @@ export function isGemmaModel(model?: Model): boolean {
   return modelId.includes('gemma-') || model.group === 'Gemma'
 }
 
-export function isZhipuModel(model?: Model): boolean {
+export function isZhipuModel(model: Model): boolean {
-  if (!model) {
+  const modelId = getLowerBaseModelName(model.id)
-    return false
+  return modelId.includes('glm') || model.provider === SystemProviderIds.zhipu
-  }
+}
 
-  return model.provider === 'zhipu'
+export function isMoonshotModel(model: Model): boolean {
+  const modelId = getLowerBaseModelName(model.id)
+  return ['moonshot', 'kimi'].some((m) => modelId.includes(m))
 }
 
 /**
@@ -212,11 +111,6 @@ export const isAnthropicModel = (model?: Model): boolean => {
   return modelId.startsWith('claude')
 }
 
-export const isQwenMTModel = (model: Model): boolean => {
-  const modelId = getLowerBaseModelName(model.id)
-  return modelId.includes('qwen-mt')
-}
-
 export const isNotSupportedTextDelta = (model: Model): boolean => {
   return isQwenMTModel(model)
 }
@@ -225,34 +119,22 @@ export const isNotSupportSystemMessageModel = (model: Model): boolean => {
   return isQwenMTModel(model) || isGemmaModel(model)
 }
 
-export const isGPT5SeriesModel = (model: Model) => {
-  const modelId = getLowerBaseModelName(model.id)
-  return modelId.includes('gpt-5') && !modelId.includes('gpt-5.1')
-}
-
-export const isGPT5SeriesReasoningModel = (model: Model) => {
-  const modelId = getLowerBaseModelName(model.id)
-  return isGPT5SeriesModel(model) && !modelId.includes('chat')
-}
-
-export const isGPT51SeriesModel = (model: Model) => {
-  const modelId = getLowerBaseModelName(model.id)
-  return modelId.includes('gpt-5.1')
-}
-
 // GPT-5 verbosity configuration
 // gpt-5-pro only supports 'high', other GPT-5 models support all levels
-export const MODEL_SUPPORTED_VERBOSITY: Record<string, ('low' | 'medium' | 'high')[]> = {
+export const MODEL_SUPPORTED_VERBOSITY: Record<string, ValidOpenAIVerbosity[]> = {
   'gpt-5-pro': ['high'],
   default: ['low', 'medium', 'high']
-}
+} as const
 
-export const getModelSupportedVerbosity = (model: Model): ('low' | 'medium' | 'high')[] => {
+export const getModelSupportedVerbosity = (model: Model): OpenAIVerbosity[] => {
   const modelId = getLowerBaseModelName(model.id)
+  let supportedValues: ValidOpenAIVerbosity[]
   if (modelId.includes('gpt-5-pro')) {
-    return MODEL_SUPPORTED_VERBOSITY['gpt-5-pro']
+    supportedValues = MODEL_SUPPORTED_VERBOSITY['gpt-5-pro']
+  } else {
+    supportedValues = MODEL_SUPPORTED_VERBOSITY.default
   }
-  return MODEL_SUPPORTED_VERBOSITY.default
+  return [undefined, ...supportedValues]
 }
 
 export const isGeminiModel = (model: Model) => {
@@ -260,11 +142,6 @@ export const isGeminiModel = (model: Model) => {
   return modelId.includes('gemini')
 }
 
-export const isOpenAIOpenWeightModel = (model: Model) => {
-  const modelId = getLowerBaseModelName(model.id)
-  return modelId.includes('gpt-oss')
-}
-
 // zhipu 视觉推理模型用这组 special token 标记推理结果
 export const ZHIPU_RESULT_TOKENS = ['<|begin_of_box|>', '<|end_of_box|>'] as const
 
@@ -272,7 +149,14 @@ export const agentModelFilter = (model: Model): boolean => {
   return !isEmbeddingModel(model) && !isRerankModel(model) && !isTextToImageModel(model)
 }
 
-export const isGPT5ProModel = (model: Model) => {
+export const isMaxTemperatureOneModel = (model: Model): boolean => {
-  const modelId = getLowerBaseModelName(model.id)
+  if (isZhipuModel(model) || isAnthropicModel(model) || isMoonshotModel(model)) {
-  return modelId.includes('gpt-5-pro')
+    return true
+  }
+  return false
+}
+
+export const isGemini3Model = (model: Model) => {
+  const modelId = getLowerBaseModelName(model.id)
+  return modelId.includes('gemini-3')
 }

src/renderer/src/config/models/vision.ts

@@ -3,6 +3,7 @@ import type { Model } from '@renderer/types'
 import { getLowerBaseModelName, isUserSelectedModelType } from '@renderer/utils'
 
 import { isEmbeddingModel, isRerankModel } from './embedding'
+import { isFunctionCallingModel } from './tooluse'
 
 // Vision models
 const visionAllowedModels = [
@@ -72,12 +73,10 @@ const VISION_REGEX = new RegExp(
 
 // For middleware to identify models that must use the dedicated Image API
 const DEDICATED_IMAGE_MODELS = [
-  'grok-2-image',
+  'grok-2-image(?:-[\\w-]+)?',
-  'grok-2-image-1212',
+  'dall-e(?:-[\\w-]+)?',
-  'grok-2-image-latest',
+  'gpt-image-1(?:-[\\w-]+)?',
-  'dall-e-3',
+  'imagen(?:-[\\w-]+)?'
-  'dall-e-2',
-  'gpt-image-1'
 ]
 
 const IMAGE_ENHANCEMENT_MODELS = [
@@ -85,13 +84,22 @@ const IMAGE_ENHANCEMENT_MODELS = [
   'qwen-image-edit',
   'gpt-image-1',
   'gemini-2.5-flash-image(?:-[\\w-]+)?',
-  'gemini-2.0-flash-preview-image-generation'
+  'gemini-2.0-flash-preview-image-generation',
+  'gemini-3(?:\\.\\d+)?-pro-image(?:-[\\w-]+)?'
 ]
 
 const IMAGE_ENHANCEMENT_MODELS_REGEX = new RegExp(IMAGE_ENHANCEMENT_MODELS.join('|'), 'i')
 
+const DEDICATED_IMAGE_MODELS_REGEX = new RegExp(DEDICATED_IMAGE_MODELS.join('|'), 'i')
+
 // Models that should auto-enable image generation button when selected
-const AUTO_ENABLE_IMAGE_MODELS = ['gemini-2.5-flash-image', ...DEDICATED_IMAGE_MODELS]
+const AUTO_ENABLE_IMAGE_MODELS = [
+  'gemini-2.5-flash-image(?:-[\\w-]+)?',
+  'gemini-3(?:\\.\\d+)?-pro-image(?:-[\\w-]+)?',
+  ...DEDICATED_IMAGE_MODELS
+]
+
+const AUTO_ENABLE_IMAGE_MODELS_REGEX = new RegExp(AUTO_ENABLE_IMAGE_MODELS.join('|'), 'i')
 
 const OPENAI_TOOL_USE_IMAGE_GENERATION_MODELS = [
   'o3',
@@ -105,26 +113,34 @@ const OPENAI_TOOL_USE_IMAGE_GENERATION_MODELS = [
 
 const OPENAI_IMAGE_GENERATION_MODELS = [...OPENAI_TOOL_USE_IMAGE_GENERATION_MODELS, 'gpt-image-1']
 
+const MODERN_IMAGE_MODELS = ['gemini-3(?:\\.\\d+)?-pro-image(?:-[\\w-]+)?']
+
 const GENERATE_IMAGE_MODELS = [
-  'gemini-2.0-flash-exp',
+  'gemini-2.0-flash-exp(?:-[\\w-]+)?',
-  'gemini-2.0-flash-exp-image-generation',
+  'gemini-2.5-flash-image(?:-[\\w-]+)?',
   'gemini-2.0-flash-preview-image-generation',
-  'gemini-2.5-flash-image',
+  ...MODERN_IMAGE_MODELS,
   ...DEDICATED_IMAGE_MODELS
 ]
 
+const OPENAI_IMAGE_GENERATION_MODELS_REGEX = new RegExp(OPENAI_IMAGE_GENERATION_MODELS.join('|'), 'i')
+
+const GENERATE_IMAGE_MODELS_REGEX = new RegExp(GENERATE_IMAGE_MODELS.join('|'), 'i')
+
+const MODERN_GENERATE_IMAGE_MODELS_REGEX = new RegExp(MODERN_IMAGE_MODELS.join('|'), 'i')
+
 export const isDedicatedImageGenerationModel = (model: Model): boolean => {
   if (!model) return false
 
   const modelId = getLowerBaseModelName(model.id)
-  return DEDICATED_IMAGE_MODELS.some((m) => modelId.includes(m))
+  return DEDICATED_IMAGE_MODELS_REGEX.test(modelId)
 }
 
 export const isAutoEnableImageGenerationModel = (model: Model): boolean => {
   if (!model) return false
 
   const modelId = getLowerBaseModelName(model.id)
-  return AUTO_ENABLE_IMAGE_MODELS.some((m) => modelId.includes(m))
+  return AUTO_ENABLE_IMAGE_MODELS_REGEX.test(modelId)
 }
 
 /**
@@ -146,48 +162,44 @@ export function isGenerateImageModel(model: Model): boolean {
   const modelId = getLowerBaseModelName(model.id, '/')
 
   if (provider.type === 'openai-response') {
-    return (
+    return OPENAI_IMAGE_GENERATION_MODELS_REGEX.test(modelId) || GENERATE_IMAGE_MODELS_REGEX.test(modelId)
-      OPENAI_IMAGE_GENERATION_MODELS.some((imageModel) => modelId.includes(imageModel)) ||
-      GENERATE_IMAGE_MODELS.some((imageModel) => modelId.includes(imageModel))
-    )
   }
 
-  return GENERATE_IMAGE_MODELS.some((imageModel) => modelId.includes(imageModel))
+  return GENERATE_IMAGE_MODELS_REGEX.test(modelId)
 }
 
+// TODO: refine the regex
 /**
  * 判断模型是否支持纯图片生成（不支持通过工具调用）
  * @param model
  * @returns
  */
 export function isPureGenerateImageModel(model: Model): boolean {
-  if (!isGenerateImageModel(model) || !isTextToImageModel(model)) {
+  if (!isGenerateImageModel(model) && !isTextToImageModel(model)) {
+    return false
+  }
+
+  if (isFunctionCallingModel(model)) {
     return false
   }
 
   const modelId = getLowerBaseModelName(model.id)
-  return !OPENAI_TOOL_USE_IMAGE_GENERATION_MODELS.some((imageModel) => modelId.includes(imageModel))
+  if (GENERATE_IMAGE_MODELS_REGEX.test(modelId) && !MODERN_GENERATE_IMAGE_MODELS_REGEX.test(modelId)) {
+    return true
+  }
+
+  return !OPENAI_TOOL_USE_IMAGE_GENERATION_MODELS.some((m) => modelId.includes(m))
 }
 
+// TODO: refine the regex
 // Text to image models
-const TEXT_TO_IMAGE_REGEX = /flux|diffusion|stabilityai|sd-|dall|cogview|janus|midjourney|mj-|image|gpt-image/i
+const TEXT_TO_IMAGE_REGEX = /flux|diffusion|stabilityai|sd-|dall|cogview|janus|midjourney|mj-|imagen|gpt-image/i
 
 export function isTextToImageModel(model: Model): boolean {
   const modelId = getLowerBaseModelName(model.id)
   return TEXT_TO_IMAGE_REGEX.test(modelId)
 }
 
-// It's not used now
-// export function isNotSupportedImageSizeModel(model?: Model): boolean {
-//   if (!model) {
-//     return false
-//   }
-
-//   const baseName = getLowerBaseModelName(model.id, '/')
-
-//   return baseName.includes('grok-2-image')
-// }
-
 /**
  * 判断模型是否支持图片增强（包括编辑、增强、修复等）
  * @param model

src/renderer/src/config/models/websearch.ts

@@ -2,27 +2,29 @@ import { getProviderByModel } from '@renderer/services/AssistantService'
 import type { Model } from '@renderer/types'
 import { SystemProviderIds } from '@renderer/types'
 import { getLowerBaseModelName, isUserSelectedModelType } from '@renderer/utils'
-
 import {
+  isAzureOpenAIProvider,
   isGeminiProvider,
   isNewApiProvider,
   isOpenAICompatibleProvider,
   isOpenAIProvider,
-  isVertexAiProvider
+  isVertexProvider
-} from '../providers'
+} from '@renderer/utils/provider'
-import { isEmbeddingModel, isRerankModel } from './embedding'
-import { isAnthropicModel } from './utils'
-import { isPureGenerateImageModel, isTextToImageModel } from './vision'
 
-export const CLAUDE_SUPPORTED_WEBSEARCH_REGEX = new RegExp(
+export { GEMINI_FLASH_MODEL_REGEX } from './utils'
+
+import { isEmbeddingModel, isRerankModel } from './embedding'
+import { isClaude4SeriesModel } from './reasoning'
+import { isAnthropicModel } from './utils'
+import { isTextToImageModel } from './vision'
+
+const CLAUDE_SUPPORTED_WEBSEARCH_REGEX = new RegExp(
   `\\b(?:claude-3(-|\\.)(7|5)-sonnet(?:-[\\w-]+)|claude-3(-|\\.)5-haiku(?:-[\\w-]+)|claude-(haiku|sonnet|opus)-4(?:-[\\w-]+)?)\\b`,
   'i'
 )
 
-export const GEMINI_FLASH_MODEL_REGEX = new RegExp('gemini.*-flash.*$')
-
 export const GEMINI_SEARCH_REGEX = new RegExp(
-  'gemini-(?:2.*(?:-latest)?|3-(?:flash|pro)(?:-preview)?|flash-latest|pro-latest|flash-lite-latest)(?:-[\\w-]+)*$',
+  'gemini-(?:2(?!.*-image-preview).*(?:-latest)?|3(?:\\.\\d+)?-(?:flash|pro)(?:-(?:image-)?preview)?|flash-latest|pro-latest|flash-lite-latest)(?:-[\\w-]+)*$',
   'i'
 )
 
@@ -34,30 +36,8 @@ export const PERPLEXITY_SEARCH_MODELS = [
   'sonar-deep-research'
 ]
 
-const OPENAI_DEEP_RESEARCH_MODEL_REGEX = /deep[-_]?research/
-
-export function isOpenAIDeepResearchModel(model?: Model): boolean {
-  if (!model) {
-    return false
-  }
-
-  const providerId = model.provider
-  if (providerId !== 'openai' && providerId !== 'openai-chat') {
-    return false
-  }
-
-  const modelId = getLowerBaseModelName(model.id, '/')
-  return OPENAI_DEEP_RESEARCH_MODEL_REGEX.test(modelId)
-}
-
 export function isWebSearchModel(model: Model): boolean {
-  if (
+  if (!model || isEmbeddingModel(model) || isRerankModel(model) || isTextToImageModel(model)) {
-    !model ||
-    isEmbeddingModel(model) ||
-    isRerankModel(model) ||
-    isTextToImageModel(model) ||
-    isPureGenerateImageModel(model)
-  ) {
     return false
   }
 
@@ -73,16 +53,17 @@ export function isWebSearchModel(model: Model): boolean {
 
   const modelId = getLowerBaseModelName(model.id, '/')
 
-  // bedrock和vertex不支持
+  // bedrock不支持, azure支持
-  if (
+  if (isAnthropicModel(model) && !(provider.id === SystemProviderIds['aws-bedrock'])) {
-    isAnthropicModel(model) &&
+    if (isVertexProvider(provider)) {
-    !(provider.id === SystemProviderIds['aws-bedrock'] || provider.id === SystemProviderIds.vertexai)
+      return isClaude4SeriesModel(model)
-  ) {
+    }
     return CLAUDE_SUPPORTED_WEBSEARCH_REGEX.test(modelId)
   }
 
   // TODO: 当其他供应商采用Response端点时，这个地方逻辑需要改进
-  if (isOpenAIProvider(provider)) {
+  // azure现在也支持了websearch
+  if (isOpenAIProvider(provider) || isAzureOpenAIProvider(provider)) {
     if (isOpenAIWebSearchModel(model)) {
       return true
     }
@@ -113,7 +94,7 @@ export function isWebSearchModel(model: Model): boolean {
     }
   }
 
-  if (isGeminiProvider(provider) || isVertexAiProvider(provider)) {
+  if (isGeminiProvider(provider) || isVertexProvider(provider)) {
     return GEMINI_SEARCH_REGEX.test(modelId)
   }
 

src/renderer/src/config/providers.ts

@@ -59,15 +59,8 @@ import VoyageAIProviderLogo from '@renderer/assets/images/providers/voyageai.png
 import XirangProviderLogo from '@renderer/assets/images/providers/xirang.png'
 import ZeroOneProviderLogo from '@renderer/assets/images/providers/zero-one.png'
 import ZhipuProviderLogo from '@renderer/assets/images/providers/zhipu.png'
-import type {
+import type { AtLeast, SystemProvider, SystemProviderId } from '@renderer/types'
-  AtLeast,
+import { OpenAIServiceTiers } from '@renderer/types'
-  AzureOpenAIProvider,
-  Provider,
-  ProviderType,
-  SystemProvider,
-  SystemProviderId
-} from '@renderer/types'
-import { isSystemProvider, OpenAIServiceTiers, SystemProviderIds } from '@renderer/types'
 
 import { TOKENFLUX_HOST } from './constant'
 import { glm45FlashModel, qwen38bModel, SYSTEM_MODELS } from './models'
@@ -1441,153 +1434,3 @@ export const PROVIDER_URLS: Record<SystemProviderId, ProviderUrls> = {
     }
   }
 }
-
-const NOT_SUPPORT_ARRAY_CONTENT_PROVIDERS = [
-  'deepseek',
-  'baichuan',
-  'minimax',
-  'xirang',
-  'poe',
-  'cephalon'
-] as const satisfies SystemProviderId[]
-
-/**
- * 判断提供商是否支持 message 的 content 为数组类型。 Only for OpenAI Chat Completions API.
- */
-export const isSupportArrayContentProvider = (provider: Provider) => {
-  return (
-    provider.apiOptions?.isNotSupportArrayContent !== true &&
-    !NOT_SUPPORT_ARRAY_CONTENT_PROVIDERS.some((pid) => pid === provider.id)
-  )
-}
-
-const NOT_SUPPORT_DEVELOPER_ROLE_PROVIDERS = ['poe', 'qiniu'] as const satisfies SystemProviderId[]
-
-/**
- * 判断提供商是否支持 developer 作为 message role。 Only for OpenAI API.
- */
-export const isSupportDeveloperRoleProvider = (provider: Provider) => {
-  return (
-    provider.apiOptions?.isSupportDeveloperRole === true ||
-    (isSystemProvider(provider) && !NOT_SUPPORT_DEVELOPER_ROLE_PROVIDERS.some((pid) => pid === provider.id))
-  )
-}
-
-const NOT_SUPPORT_STREAM_OPTIONS_PROVIDERS = ['mistral'] as const satisfies SystemProviderId[]
-
-/**
- * 判断提供商是否支持 stream_options 参数。Only for OpenAI API.
- */
-export const isSupportStreamOptionsProvider = (provider: Provider) => {
-  return (
-    provider.apiOptions?.isNotSupportStreamOptions !== true &&
-    !NOT_SUPPORT_STREAM_OPTIONS_PROVIDERS.some((pid) => pid === provider.id)
-  )
-}
-
-const NOT_SUPPORT_QWEN3_ENABLE_THINKING_PROVIDER = [
-  'ollama',
-  'lmstudio',
-  'nvidia'
-] as const satisfies SystemProviderId[]
-
-/**
- * 判断提供商是否支持使用 enable_thinking 参数来控制 Qwen3 等模型的思考。 Only for OpenAI Chat Completions API.
- */
-export const isSupportEnableThinkingProvider = (provider: Provider) => {
-  return (
-    provider.apiOptions?.isNotSupportEnableThinking !== true &&
-    !NOT_SUPPORT_QWEN3_ENABLE_THINKING_PROVIDER.some((pid) => pid === provider.id)
-  )
-}
-
-const NOT_SUPPORT_SERVICE_TIER_PROVIDERS = ['github', 'copilot', 'cerebras'] as const satisfies SystemProviderId[]
-
-/**
- * 判断提供商是否支持 service_tier 设置。 Only for OpenAI API.
- */
-export const isSupportServiceTierProvider = (provider: Provider) => {
-  return (
-    provider.apiOptions?.isSupportServiceTier === true ||
-    (isSystemProvider(provider) && !NOT_SUPPORT_SERVICE_TIER_PROVIDERS.some((pid) => pid === provider.id))
-  )
-}
-
-const SUPPORT_URL_CONTEXT_PROVIDER_TYPES = [
-  'gemini',
-  'vertexai',
-  'anthropic',
-  'new-api'
-] as const satisfies ProviderType[]
-
-export const isSupportUrlContextProvider = (provider: Provider) => {
-  return (
-    SUPPORT_URL_CONTEXT_PROVIDER_TYPES.some((type) => type === provider.type) ||
-    provider.id === SystemProviderIds.cherryin
-  )
-}
-
-const SUPPORT_GEMINI_NATIVE_WEB_SEARCH_PROVIDERS = ['gemini', 'vertexai'] as const satisfies SystemProviderId[]
-
-/** 判断是否是使用 Gemini 原生搜索工具的 provider. 目前假设只有官方 API 使用原生工具 */
-export const isGeminiWebSearchProvider = (provider: Provider) => {
-  return SUPPORT_GEMINI_NATIVE_WEB_SEARCH_PROVIDERS.some((id) => id === provider.id)
-}
-
-export const isNewApiProvider = (provider: Provider) => {
-  return ['new-api', 'cherryin'].includes(provider.id) || provider.type === 'new-api'
-}
-
-export function isCherryAIProvider(provider: Provider): boolean {
-  return provider.id === 'cherryai'
-}
-
-export function isPerplexityProvider(provider: Provider): boolean {
-  return provider.id === 'perplexity'
-}
-
-/**
- * 判断是否为 OpenAI 兼容的提供商
- * @param {Provider} provider 提供商对象
- * @returns {boolean} 是否为 OpenAI 兼容提供商
- */
-export function isOpenAICompatibleProvider(provider: Provider): boolean {
-  return ['openai', 'new-api', 'mistral'].includes(provider.type)
-}
-
-export function isAzureOpenAIProvider(provider: Provider): provider is AzureOpenAIProvider {
-  return provider.type === 'azure-openai'
-}
-
-export function isOpenAIProvider(provider: Provider): boolean {
-  return provider.type === 'openai-response'
-}
-
-export function isAnthropicProvider(provider: Provider): boolean {
-  return provider.type === 'anthropic'
-}
-
-export function isGeminiProvider(provider: Provider): boolean {
-  return provider.type === 'gemini'
-}
-
-export function isVertexAiProvider(provider: Provider): boolean {
-  return provider.type === 'vertexai'
-}
-
-export function isAIGatewayProvider(provider: Provider): boolean {
-  return provider.type === 'ai-gateway'
-}
-
-export function isAwsBedrockProvider(provider: Provider): boolean {
-  return provider.type === 'aws-bedrock'
-}
-
-const NOT_SUPPORT_API_VERSION_PROVIDERS = ['github', 'copilot', 'perplexity'] as const satisfies SystemProviderId[]
-
-export const isSupportAPIVersionProvider = (provider: Provider) => {
-  if (isSystemProvider(provider)) {
-    return !NOT_SUPPORT_API_VERSION_PROVIDERS.some((pid) => pid === provider.id)
-  }
-  return provider.apiOptions?.isNotSupportAPIVersion !== false
-}

src/renderer/src/config/tools.ts

@@ -1,55 +0,0 @@
-import type { ChatCompletionTool } from '@cherrystudio/openai/resources'
-import type { Model } from '@renderer/types'
-import { WEB_SEARCH_PROMPT_FOR_ZHIPU } from '@shared/config/prompts'
-
-export function getWebSearchTools(model: Model): ChatCompletionTool[] {
-  if (model?.provider === 'zhipu') {
-    if (model.id === 'glm-4-alltools') {
-      return [
-        {
-          type: 'web_browser',
-          web_browser: {
-            browser: 'auto'
-          }
-        } as unknown as ChatCompletionTool
-      ]
-    }
-    return [
-      {
-        type: 'web_search',
-        web_search: {
-          enable: true,
-          search_result: true,
-          search_prompt: WEB_SEARCH_PROMPT_FOR_ZHIPU
-        }
-      } as unknown as ChatCompletionTool
-    ]
-  }
-
-  if (model?.id.includes('gemini')) {
-    return [
-      {
-        type: 'function',
-        function: {
-          name: 'googleSearch'
-        }
-      }
-    ]
-  }
-  return []
-}
-
-export function getUrlContextTools(model: Model): ChatCompletionTool[] {
-  if (model.id.includes('gemini')) {
-    return [
-      {
-        type: 'function',
-        function: {
-          name: 'urlContext'
-        }
-      }
-    ]
-  }
-
-  return []
-}

src/renderer/src/hooks/useAppInit.ts

@@ -175,14 +175,46 @@ export function useAppInit() {
   useEffect(() => {
     if (!window.electron?.ipcRenderer) return
 
-    const requestListener = (_event: Electron.IpcRendererEvent, payload: ToolPermissionRequestPayload) => {
+    const requestListener = async (_event: Electron.IpcRendererEvent, payload: ToolPermissionRequestPayload) => {
       logger.debug('Renderer received tool permission request', {
         requestId: payload.requestId,
         toolName: payload.toolName,
         expiresAt: payload.expiresAt,
-        suggestionCount: payload.suggestions.length
+        suggestionCount: payload.suggestions.length,
+        autoApprove: payload.autoApprove
       })
       dispatch(toolPermissionsActions.requestReceived(payload))
+
+      // Auto-approve if requested
+      if (payload.autoApprove) {
+        logger.debug('Auto-approving tool permission request', {
+          requestId: payload.requestId,
+          toolName: payload.toolName
+        })
+
+        dispatch(toolPermissionsActions.submissionSent({ requestId: payload.requestId, behavior: 'allow' }))
+
+        try {
+          const response = await window.api.agentTools.respondToPermission({
+            requestId: payload.requestId,
+            behavior: 'allow',
+            updatedInput: payload.input,
+            updatedPermissions: payload.suggestions
+          })
+
+          if (!response?.success) {
+            throw new Error('Auto-approval response rejected by main process')
+          }
+
+          logger.debug('Auto-approval acknowledged by main process', {
+            requestId: payload.requestId,
+            toolName: payload.toolName
+          })
+        } catch (error) {
+          logger.error('Failed to send auto-approval response', error as Error)
+          dispatch(toolPermissionsActions.submissionFailed({ requestId: payload.requestId }))
+        }
+      }
     }
 
     const resultListener = (_event: Electron.IpcRendererEvent, payload: ToolPermissionResultPayload) => {

src/renderer/src/hooks/useVertexAI.ts

@@ -38,13 +38,6 @@ export function getVertexAIServiceAccount() {
   return store.getState().llm.settings.vertexai.serviceAccount
 }
 
-/**
- * 类型守卫：检查 Provider 是否为 VertexProvider
- */
-export function isVertexProvider(provider: Provider): provider is VertexProvider {
-  return provider.type === 'vertexai'
-}
-
 /**
  * 创建 VertexProvider 对象，整合单独的配置
  * @param baseProvider 基础的 provider 配置

src/renderer/src/i18n/locales/en-us.json

@@ -266,6 +266,7 @@
       "error": {
         "sendFailed": "Failed to send your decision. Please try again."
       },
+      "executing": "Executing...",
       "expired": "Expired",
       "inputPreview": "Tool input preview",
       "pending": "Pending ({{seconds}}s)",
@@ -1158,6 +1159,7 @@
     "name": "Name",
     "no_results": "No results",
     "none": "None",
+    "off": "Off",
     "open": "Open",
     "paste": "Paste",
     "placeholders": {
@@ -4259,7 +4261,6 @@
         "default": "default",
         "flex": "flex",
         "on_demand": "on demand",
-        "performance": "performance",
         "priority": "priority",
         "tip": "Specifies the latency tier to use for processing the request",
         "title": "Service Tier"
@@ -4278,7 +4279,7 @@
         "low": "Low",
         "medium": "Medium",
         "tip": "Control the level of detail in the model's output",
-        "title": "Level of detail"
+        "title": "Verbosity"
       }
     },
     "privacy": {

src/renderer/src/i18n/locales/zh-cn.json

@@ -266,6 +266,7 @@
       "error": {
         "sendFailed": "发送您的决定失败，请重试。"
       },
+      "executing": "正在执行...",
       "expired": "已过期",
       "inputPreview": "工具输入预览",
       "pending": "等待中 ({{seconds}}秒)",
@@ -1158,6 +1159,7 @@
     "name": "名称",
     "no_results": "无结果",
     "none": "无",
+    "off": "关闭",
     "open": "打开",
     "paste": "粘贴",
     "placeholders": {
@@ -4259,7 +4261,6 @@
         "default": "默认",
         "flex": "灵活",
         "on_demand": "按需",
-        "performance": "性能",
         "priority": "优先",
         "tip": "指定用于处理请求的延迟层级",
         "title": "服务层级"

src/renderer/src/i18n/locales/zh-tw.json

@@ -37,7 +37,7 @@
       "success": "成功偵測到 Git Bash！"
     },
     "input": {
-      "placeholder": "[to be translated]:Enter your message here, send with {{key}} - @ select path, / select command"
+      "placeholder": "在這裡輸入您的訊息，使用 {{key}} 傳送 - @ 選擇路徑，/ 選擇命令"
     },
     "list": {
       "error": {
@@ -266,6 +266,7 @@
       "error": {
         "sendFailed": "傳送您的決定失敗，請重試。"
       },
+      "executing": "執行中...",
       "expired": "已過期",
       "inputPreview": "工具輸入預覽",
       "pending": "等待中 ({{seconds}}秒)",
@@ -1158,6 +1159,7 @@
     "name": "名稱",
     "no_results": "沒有結果",
     "none": "無",
+    "off": "關閉",
     "open": "開啟",
     "paste": "貼上",
     "placeholders": {
@@ -4259,7 +4261,6 @@
         "default": "預設",
         "flex": "彈性",
         "on_demand": "按需",
-        "performance": "效能",
         "priority": "優先",
         "tip": "指定用於處理請求的延遲層級",
         "title": "服務層級"

src/renderer/src/i18n/translate/de-de.json

@@ -29,15 +29,15 @@
     },
     "gitBash": {
       "error": {
-        "description": "[to be translated]:Git Bash is required to run agents on Windows. The agent cannot function without it. Please install Git for Windows from",
+        "description": "Git Bash ist erforderlich, um Agents unter Windows auszuführen. Der Agent kann ohne es nicht funktionieren. Bitte installieren Sie Git für Windows von",
-        "recheck": "[to be translated]:Recheck Git Bash Installation",
+        "recheck": "Überprüfe die Git Bash-Installation erneut",
-        "title": "[to be translated]:Git Bash Required"
+        "title": "Git Bash erforderlich"
       },
-      "notFound": "[to be translated]:Git Bash not found. Please install it first.",
+      "notFound": "Git Bash nicht gefunden. Bitte installieren Sie es zuerst.",
-      "success": "[to be translated]:Git Bash detected successfully!"
+      "success": "Git Bash erfolgreich erkannt!"
     },
     "input": {
-      "placeholder": "[to be translated]:Enter your message here, send with {{key}} - @ select path, / select command"
+      "placeholder": "Gib hier deine Nachricht ein, senden mit {{key}} – @ Pfad auswählen, / Befehl auswählen"
     },
     "list": {
       "error": {
@@ -266,6 +266,7 @@
       "error": {
         "sendFailed": "Ihre Entscheidung konnte nicht gesendet werden. Bitte versuchen Sie es erneut."
       },
+      "executing": "Ausführen...",
       "expired": "Abgelaufen",
       "inputPreview": "Vorschau der Werkzeugeingabe",
       "pending": "Ausstehend ({{seconds}}s)",
@@ -1158,6 +1159,7 @@
     "name": "Name",
     "no_results": "Keine Ergebnisse",
     "none": "Keine",
+    "off": "Aus",
     "open": "Öffnen",
     "paste": "Einfügen",
     "placeholders": {
@@ -1385,6 +1387,36 @@
     "preview": "Vorschau",
     "split": "Geteilte Ansicht"
   },
+  "import": {
+    "chatgpt": {
+      "assistant_name": "ChatGPT-Import",
+      "button": "Datei auswählen",
+      "description": "Importiert nur Gesprächstexte, keine Bilder und Anhänge",
+      "error": {
+        "invalid_json": "Ungültiges JSON-Dateiformat",
+        "no_conversations": "Keine Gespräche in der Datei gefunden",
+        "no_valid_conversations": "Keine gültigen Konversationen zum Importieren",
+        "unknown": "Import fehlgeschlagen, bitte überprüfen Sie das Dateiformat"
+      },
+      "help": {
+        "step1": "1. Melden Sie sich bei ChatGPT an, gehen Sie zu Einstellungen > Dateneinstellungen > Daten exportieren",
+        "step2": "2. Warten Sie auf die Exportdatei per E-Mail",
+        "step3": "3. Extrahiere die heruntergeladene Datei und finde conversations.json",
+        "title": "Wie exportiere ich ChatGPT-Gespräche?"
+      },
+      "importing": "Konversationen werden importiert...",
+      "selecting": "Datei wird ausgewählt...",
+      "success": "Erfolgreich {{topics}} Konversationen mit {{messages}} Nachrichten importiert",
+      "title": "ChatGPT-Unterhaltungen importieren",
+      "untitled_conversation": "Unbenannte Unterhaltung"
+    },
+    "confirm": {
+      "button": "Importdatei auswählen",
+      "label": "Sind Sie sicher, dass Sie externe Daten importieren möchten?"
+    },
+    "content": "Wählen Sie die zu importierende Gesprächsdatei einer externen Anwendung aus; derzeit werden nur ChatGPT-JSON-Formatdateien unterstützt.",
+    "title": "Externe Gespräche importieren"
+  },
   "knowledge": {
     "add": {
       "title": "Wissensdatenbank hinzufügen"
@@ -3094,6 +3126,7 @@
         "basic": "Grundlegende Dateneinstellungen",
         "cloud_storage": "Cloud-Backup-Einstellungen",
         "export_settings": "Export-Einstellungen",
+        "import_settings": "Importeinstellungen",
         "third_party": "Drittanbieter-Verbindungen"
       },
       "export_menu": {
@@ -3152,6 +3185,11 @@
       },
       "hour_interval_one": "{{count}} Stunde",
       "hour_interval_other": "{{count}} Stunden",
+      "import_settings": {
+        "button": "JSON-Datei importieren",
+        "chatgpt": "Import aus ChatGPT",
+        "title": "Importiere Daten von externen Anwendungen"
+      },
       "joplin": {
         "check": {
           "button": "Erkennen",
@@ -4223,7 +4261,6 @@
         "default": "Standard",
         "flex": "Flexibel",
         "on_demand": "Auf Anfrage",
-        "performance": "Leistung",
         "priority": "Priorität",
         "tip": "Latenz-Ebene für Anfrageverarbeitung festlegen",
         "title": "Service-Tier"

src/renderer/src/i18n/translate/el-gr.json

@@ -29,15 +29,15 @@
     },
     "gitBash": {
       "error": {
-        "description": "[to be translated]:Git Bash is required to run agents on Windows. The agent cannot function without it. Please install Git for Windows from",
+        "description": "Το Git Bash απαιτείται για την εκτέλεση πρακτόρων στα Windows. Ο πράκτορας δεν μπορεί να λειτουργήσει χωρίς αυτό. Παρακαλούμε εγκαταστήστε το Git για Windows από",
-        "recheck": "[to be translated]:Recheck Git Bash Installation",
+        "recheck": "Επανέλεγχος Εγκατάστασης του Git Bash",
-        "title": "[to be translated]:Git Bash Required"
+        "title": "Απαιτείται Git Bash"
       },
-      "notFound": "[to be translated]:Git Bash not found. Please install it first.",
+      "notFound": "Το Git Bash δεν βρέθηκε. Παρακαλώ εγκαταστήστε το πρώτα.",
-      "success": "[to be translated]:Git Bash detected successfully!"
+      "success": "Το Git Bash εντοπίστηκε με επιτυχία!"
     },
     "input": {
-      "placeholder": "[to be translated]:Enter your message here, send with {{key}} - @ select path, / select command"
+      "placeholder": "Εισάγετε το μήνυμά σας εδώ, στείλτε με {{key}} - @ επιλέξτε διαδρομή, / επιλέξτε εντολή"
     },
     "list": {
       "error": {
@@ -266,6 +266,7 @@
       "error": {
         "sendFailed": "Αποτυχία αποστολής της απόφασής σας. Προσπαθήστε ξανά."
       },
+      "executing": "Εκτέλεση...",
       "expired": "Ληγμένο",
       "inputPreview": "Προεπισκόπηση εισόδου εργαλείου",
       "pending": "Εκκρεμεί ({{seconds}}δ)",
@@ -1158,6 +1159,7 @@
     "name": "Όνομα",
     "no_results": "Δεν βρέθηκαν αποτελέσματα",
     "none": "Χωρίς",
+    "off": "Κλειστό",
     "open": "Άνοιγμα",
     "paste": "Επικόλληση",
     "placeholders": {
@@ -1385,6 +1387,36 @@
     "preview": "Προεπισκόπηση",
     "split": "Διαχωρισμός"
   },
+  "import": {
+    "chatgpt": {
+      "assistant_name": "Εισαγωγή ChatGPT",
+      "button": "Επιλέξτε Αρχείο",
+      "description": "Εισάγει μόνο κείμενο συνομιλίας, δεν περιλαμβάνει εικόνες και συνημμένα",
+      "error": {
+        "invalid_json": "Μη έγκυρη μορφή αρχείου JSON",
+        "no_conversations": "Δεν βρέθηκαν συνομιλίες στο αρχείο",
+        "no_valid_conversations": "Δεν υπάρχουν έγκυρες συνομιλίες προς εισαγωγή",
+        "unknown": "Η εισαγωγή απέτυχε, παρακαλώ ελέγξτε τη μορφή του αρχείου"
+      },
+      "help": {
+        "step1": "1. Συνδεθείτε στο ChatGPT, πηγαίνετε στις Ρυθμίσεις > Έλεγχοι δεδομένων > Εξαγωγή δεδομένων",
+        "step2": "2. Περιμένετε το αρχείο εξαγωγής μέσω email",
+        "step3": "3. Εξαγάγετε το ληφθέν αρχείο και βρείτε το conversations.json",
+        "title": "Πώς να εξάγετε συνομιλίες του ChatGPT;"
+      },
+      "importing": "Εισαγωγή συνομιλιών...",
+      "selecting": "Επιλογή αρχείου...",
+      "success": "Επιτυχής εισαγωγή {{topics}} συνομιλιών με {{messages}} μηνύματα",
+      "title": "Εισαγωγή Συνομιλιών του ChatGPT",
+      "untitled_conversation": "Συνομιλία χωρίς τίτλο"
+    },
+    "confirm": {
+      "button": "Επιλέξτε Εισαγωγή Αρχείου",
+      "label": "Είστε σίγουροι ότι θέλετε να εισάγετε εξωτερικά δεδομένα;"
+    },
+    "content": "Επιλέξτε εξωτερικό αρχείο συνομιλίας εφαρμογής για εισαγωγή, προς το παρόν υποστηρίζονται μόνο αρχεία μορφής JSON του ChatGPT",
+    "title": "Εισαγωγή Εξωτερικών Συνομιλιών"
+  },
   "knowledge": {
     "add": {
       "title": "Προσθήκη βιβλιοθήκης γνώσεων"
@@ -3094,6 +3126,7 @@
         "basic": "Ρυθμίσεις βασικών δεδομένων",
         "cloud_storage": "Ρυθμίσεις αποθήκευσης στο νέφος",
         "export_settings": "Ρυθμίσεις εξαγωγής",
+        "import_settings": "Εισαγωγή Ρυθμίσεων",
         "third_party": "Σύνδεση τρίτων"
       },
       "export_menu": {
@@ -3152,6 +3185,11 @@
       },
       "hour_interval_one": "{{count}} ώρα",
       "hour_interval_other": "{{count}} ώρες",
+      "import_settings": {
+        "button": "Εισαγωγή αρχείου Json",
+        "chatgpt": "Εισαγωγή από το ChatGPT",
+        "title": "Εισαγωγή Δεδομένων Εξωτερικής Εφαρμογής"
+      },
       "joplin": {
         "check": {
           "button": "Έλεγχος",
@@ -4223,7 +4261,6 @@
         "default": "Προεπιλογή",
         "flex": "Εύκαμπτο",
         "on_demand": "κατά παραγγελία",
-        "performance": "Απόδοση",
         "priority": "προτεραιότητα",
         "tip": "Καθορίστε το επίπεδο καθυστέρησης που χρησιμοποιείται για την επεξεργασία των αιτημάτων",
         "title": "Επίπεδο υπηρεσίας"

src/renderer/src/i18n/translate/es-es.json

@@ -29,15 +29,15 @@
     },
     "gitBash": {
       "error": {
-        "description": "[to be translated]:Git Bash is required to run agents on Windows. The agent cannot function without it. Please install Git for Windows from",
+        "description": "Se requiere Git Bash para ejecutar agentes en Windows. El agente no puede funcionar sin él. Instale Git para Windows desde",
-        "recheck": "[to be translated]:Recheck Git Bash Installation",
+        "recheck": "Volver a verificar la instalación de Git Bash",
-        "title": "[to be translated]:Git Bash Required"
+        "title": "Git Bash Requerido"
       },
-      "notFound": "[to be translated]:Git Bash not found. Please install it first.",
+      "notFound": "Git Bash no encontrado. Por favor, instálalo primero.",
-      "success": "[to be translated]:Git Bash detected successfully!"
+      "success": "¡Git Bash detectado con éxito!"
     },
     "input": {
-      "placeholder": "[to be translated]:Enter your message here, send with {{key}} - @ select path, / select command"
+      "placeholder": "Introduce tu mensaje aquí, envía con {{key}} - @ seleccionar ruta, / seleccionar comando"
     },
     "list": {
       "error": {
@@ -266,6 +266,7 @@
       "error": {
         "sendFailed": "No se pudo enviar tu decisión. Por favor, inténtalo de nuevo."
       },
+      "executing": "Ejecutando...",
       "expired": "Caducado",
       "inputPreview": "Vista previa de entrada de herramienta",
       "pending": "Pendiente ({{seconds}}s)",
@@ -1158,6 +1159,7 @@
     "name": "Nombre",
     "no_results": "Sin resultados",
     "none": "无",
+    "off": "Apagado",
     "open": "Abrir",
     "paste": "Pegar",
     "placeholders": {
@@ -1385,6 +1387,36 @@
     "preview": "Vista previa",
     "split": "Dividir"
   },
+  "import": {
+    "chatgpt": {
+      "assistant_name": "Importación de ChatGPT",
+      "button": "Seleccionar archivo",
+      "description": "Solo importa el texto de la conversación, no incluye imágenes ni archivos adjuntos",
+      "error": {
+        "invalid_json": "Formato de archivo JSON inválido",
+        "no_conversations": "No se encontraron conversaciones en el archivo",
+        "no_valid_conversations": "No hay conversaciones válidas para importar",
+        "unknown": "Error de importación, por favor verifica el formato del archivo"
+      },
+      "help": {
+        "step1": "1. Inicia sesión en ChatGPT, ve a Configuración > Controles de datos > Exportar datos",
+        "step2": "2. Espera el archivo de exportación por correo electrónico",
+        "step3": "3. Extrae el archivo descargado y busca conversations.json",
+        "title": "Cómo exportar conversaciones de ChatGPT"
+      },
+      "importing": "Importando conversaciones...",
+      "selecting": "Seleccionando archivo...",
+      "success": "Importadas con éxito {{topics}} conversaciones con {{messages}} mensajes",
+      "title": "Importar conversaciones de ChatGPT",
+      "untitled_conversation": "Conversación Sin Título"
+    },
+    "confirm": {
+      "button": "Seleccionar Archivo de Importación",
+      "label": "¿Estás seguro de que quieres importar datos externos?"
+    },
+    "content": "Selecciona el archivo de conversación de la aplicación externa para importar; actualmente solo admite archivos en formato JSON de ChatGPT",
+    "title": "Importar Conversaciones Externas"
+  },
   "knowledge": {
     "add": {
       "title": "Agregar base de conocimientos"
@@ -3094,6 +3126,7 @@
         "basic": "Configuración básica",
         "cloud_storage": "Configuración de almacenamiento en la nube",
         "export_settings": "Configuración de exportación",
+        "import_settings": "Importar configuración",
         "third_party": "Conexiones de terceros"
       },
       "export_menu": {
@@ -3152,6 +3185,11 @@
       },
       "hour_interval_one": "{{count}} hora",
       "hour_interval_other": "{{count}} horas",
+      "import_settings": {
+        "button": "Importar archivo Json",
+        "chatgpt": "Importar desde ChatGPT",
+        "title": "Importar datos de aplicaciones externas"
+      },
       "joplin": {
         "check": {
           "button": "Revisar",
@@ -4223,7 +4261,6 @@
         "default": "Predeterminado",
         "flex": "Flexible",
         "on_demand": "según demanda",
-        "performance": "rendimiento",
         "priority": "prioridad",
         "tip": "Especifica el nivel de latencia utilizado para procesar la solicitud",
         "title": "Nivel de servicio"

src/renderer/src/i18n/translate/fr-fr.json

@@ -29,15 +29,15 @@
     },
     "gitBash": {
       "error": {
-        "description": "[to be translated]:Git Bash is required to run agents on Windows. The agent cannot function without it. Please install Git for Windows from",
+        "description": "Git Bash est requis pour exécuter des agents sur Windows. L'agent ne peut pas fonctionner sans. Veuillez installer Git pour Windows depuis",
-        "recheck": "[to be translated]:Recheck Git Bash Installation",
+        "recheck": "Revérifier l'installation de Git Bash",
-        "title": "[to be translated]:Git Bash Required"
+        "title": "Git Bash requis"
       },
-      "notFound": "[to be translated]:Git Bash not found. Please install it first.",
+      "notFound": "Git Bash introuvable. Veuillez l’installer d’abord.",
-      "success": "[to be translated]:Git Bash detected successfully!"
+      "success": "Git Bash détecté avec succès !"
     },
     "input": {
-      "placeholder": "[to be translated]:Enter your message here, send with {{key}} - @ select path, / select command"
+      "placeholder": "Entrez votre message ici, envoyez avec {{key}} - @ sélectionner le chemin, / sélectionner la commande"
     },
     "list": {
       "error": {
@@ -266,6 +266,7 @@
       "error": {
         "sendFailed": "Échec de l'envoi de votre décision. Veuillez réessayer."
       },
+      "executing": "Exécution en cours...",
       "expired": "Expiré",
       "inputPreview": "Aperçu de l'entrée de l'outil",
       "pending": "En attente ({{seconds}}s)",
@@ -1158,6 +1159,7 @@
     "name": "Nom",
     "no_results": "Aucun résultat",
     "none": "Aucun",
+    "off": "Désactivé",
     "open": "Ouvrir",
     "paste": "Coller",
     "placeholders": {
@@ -1385,6 +1387,36 @@
     "preview": "Aperçu",
     "split": "Diviser"
   },
+  "import": {
+    "chatgpt": {
+      "assistant_name": "Importation de ChatGPT",
+      "button": "Sélectionner le fichier",
+      "description": "Importe uniquement le texte de la conversation, n'inclut pas les images et les pièces jointes",
+      "error": {
+        "invalid_json": "Format de fichier JSON invalide",
+        "no_conversations": "Aucune conversation trouvée dans le fichier",
+        "no_valid_conversations": "Aucune conversation valide à importer",
+        "unknown": "L'importation a échoué, veuillez vérifier le format du fichier"
+      },
+      "help": {
+        "step1": "1. Connectez-vous à ChatGPT, allez dans Paramètres > Contrôles des données > Exporter les données",
+        "step2": "2. Attendez le fichier d’exportation par e-mail",
+        "step3": "3. Extrayez le fichier téléchargé et recherchez conversations.json",
+        "title": "Comment exporter les conversations de ChatGPT ?"
+      },
+      "importing": "Importation des conversations...",
+      "selecting": "Sélection du fichier...",
+      "success": "Importation réussie de {{topics}} conversations avec {{messages}} messages",
+      "title": "Importer les conversations de ChatGPT",
+      "untitled_conversation": "Conversation sans titre"
+    },
+    "confirm": {
+      "button": "Sélectionner le fichier à importer",
+      "label": "Êtes-vous sûr de vouloir importer des données externes ?"
+    },
+    "content": "Sélectionnez le fichier de conversation de l'application externe à importer, actuellement uniquement les fichiers au format JSON de ChatGPT sont pris en charge",
+    "title": "Importer des conversations externes"
+  },
   "knowledge": {
     "add": {
       "title": "Ajouter une base de connaissances"
@@ -3094,6 +3126,7 @@
         "basic": "Paramètres de base",
         "cloud_storage": "Paramètres de sauvegarde cloud",
         "export_settings": "Paramètres d'exportation",
+        "import_settings": "Importer les paramètres",
         "third_party": "Connexion tierce"
       },
       "export_menu": {
@@ -3152,6 +3185,11 @@
       },
       "hour_interval_one": "{{count}} heure",
       "hour_interval_other": "{{count}} heures",
+      "import_settings": {
+        "button": "Importer le fichier JSON",
+        "chatgpt": "Importer depuis ChatGPT",
+        "title": "Importer des données d'applications externes"
+      },
       "joplin": {
         "check": {
           "button": "Vérifier",
@@ -4223,7 +4261,6 @@
         "default": "Par défaut",
         "flex": "Flexible",
         "on_demand": "à la demande",
-        "performance": "performance",
         "priority": "priorité",
         "tip": "Spécifie le niveau de latence utilisé pour traiter la demande",
         "title": "Niveau de service"

src/renderer/src/i18n/translate/ja-jp.json

@@ -29,15 +29,15 @@
     },
     "gitBash": {
       "error": {
-        "description": "[to be translated]:Git Bash is required to run agents on Windows. The agent cannot function without it. Please install Git for Windows from",
+        "description": "Windowsでエージェントを実行するにはGit Bashが必要です。これがないとエージェントは動作しません。以下からGit for Windowsをインストールしてください。",
-        "recheck": "[to be translated]:Recheck Git Bash Installation",
+        "recheck": "Git Bashのインストールを再確認してください",
-        "title": "[to be translated]:Git Bash Required"
+        "title": "Git Bashが必要です"
       },
-      "notFound": "[to be translated]:Git Bash not found. Please install it first.",
+      "notFound": "Git Bash が見つかりません。先にインストールしてください。",
-      "success": "[to be translated]:Git Bash detected successfully!"
+      "success": "Git Bashが正常に検出されました！"
     },
     "input": {
-      "placeholder": "[to be translated]:Enter your message here, send with {{key}} - @ select path, / select command"
+      "placeholder": "メッセージをここに入力し、{{key}}で送信 - @でパスを選択、/でコマンドを選択"
     },
     "list": {
       "error": {
@@ -266,6 +266,7 @@
       "error": {
         "sendFailed": "決定の送信に失敗しました。もう一度お試しください。"
       },
+      "executing": "実行中...",
       "expired": "期限切れ",
       "inputPreview": "ツール入力プレビュー",
       "pending": "保留中（{{seconds}}秒）",
@@ -1158,6 +1159,7 @@
     "name": "名前",
     "no_results": "検索結果なし",
     "none": "無",
+    "off": "オフ",
     "open": "開く",
     "paste": "貼り付け",
     "placeholders": {
@@ -1385,6 +1387,36 @@
     "preview": "プレビュー",
     "split": "分割"
   },
+  "import": {
+    "chatgpt": {
+      "assistant_name": "ChatGPTインポート",
+      "button": "ファイルを選択",
+      "description": "会話のテキストのみをインポートし、画像や添付ファイルは含まれません",
+      "error": {
+        "invalid_json": "無効なJSONファイル形式",
+        "no_conversations": "ファイルに会話が見つかりません",
+        "no_valid_conversations": "インポートする有効な会話がありません",
+        "unknown": "インポートに失敗しました。ファイル形式を確認してください。"
+      },
+      "help": {
+        "step1": "1. ChatGPTにログインし、設定 > データ管理 > データをエクスポートへ進みます",
+        "step2": "2. エクスポートファイルが届くまでメールでお待ちください",
+        "step3": "3. ダウンロードしたファイルを展開し、conversations.jsonを探してください",
+        "title": "ChatGPTの会話をエクスポートする方法は？"
+      },
+      "importing": "会話をインポートしています...",
+      "selecting": "ファイルを選択中...",
+      "success": "{{topics}}件の会話と{{messages}}件のメッセージを正常にインポートしました",
+      "title": "ChatGPTの会話をインポート",
+      "untitled_conversation": "無題の会話"
+    },
+    "confirm": {
+      "button": "ファイルのインポートを選択",
+      "label": "外部データをインポートしてもよろしいですか？"
+    },
+    "content": "外部アプリケーションの会話ファイルを選択してインポートします。現在、ChatGPT JSON形式ファイルのみサポートしています。",
+    "title": "外部会話をインポート"
+  },
   "knowledge": {
     "add": {
       "title": "ナレッジベースを追加"
@@ -3094,6 +3126,7 @@
         "basic": "基本データ設定",
         "cloud_storage": "クラウドバックアップ設定",
         "export_settings": "エクスポート設定",
+        "import_settings": "設定のインポート",
         "third_party": "サードパーティー連携"
       },
       "export_menu": {
@@ -3152,6 +3185,11 @@
       },
       "hour_interval_one": "{{count}} 時間",
       "hour_interval_other": "{{count}} 時間",
+      "import_settings": {
+        "button": "JSONファイルをインポート",
+        "chatgpt": "ChatGPTからインポート",
+        "title": "外部アプリケーションデータをインポート"
+      },
       "joplin": {
         "check": {
           "button": "確認",
@@ -4223,7 +4261,6 @@
         "default": "デフォルト",
         "flex": "フレックス",
         "on_demand": "オンデマンド",
-        "performance": "性能",
         "priority": "優先",
         "tip": "リクエスト処理に使用するレイテンシティアを指定します",
         "title": "サービスティア"

src/renderer/src/i18n/translate/pt-pt.json

@@ -29,15 +29,15 @@
     },
     "gitBash": {
       "error": {
-        "description": "[to be translated]:Git Bash is required to run agents on Windows. The agent cannot function without it. Please install Git for Windows from",
+        "description": "O Git Bash é necessário para executar agentes no Windows. O agente não pode funcionar sem ele. Por favor, instale o Git para Windows a partir de",
-        "recheck": "[to be translated]:Recheck Git Bash Installation",
+        "recheck": "Reverificar a Instalação do Git Bash",
-        "title": "[to be translated]:Git Bash Required"
+        "title": "Git Bash Necessário"
       },
-      "notFound": "[to be translated]:Git Bash not found. Please install it first.",
+      "notFound": "Git Bash não encontrado. Por favor, instale-o primeiro.",
-      "success": "[to be translated]:Git Bash detected successfully!"
+      "success": "Git Bash detectado com sucesso!"
     },
     "input": {
-      "placeholder": "[to be translated]:Enter your message here, send with {{key}} - @ select path, / select command"
+      "placeholder": "Digite sua mensagem aqui, envie com {{key}} - @ selecionar caminho, / selecionar comando"
     },
     "list": {
       "error": {
@@ -266,6 +266,7 @@
       "error": {
         "sendFailed": "Falha ao enviar sua decisão. Por favor, tente novamente."
       },
+      "executing": "Executando...",
       "expired": "Expirado",
       "inputPreview": "Pré-visualização da entrada da ferramenta",
       "pending": "Pendente ({{seconds}}s)",
@@ -1158,6 +1159,7 @@
     "name": "Nome",
     "no_results": "Nenhum resultado",
     "none": "Nenhum",
+    "off": "Desligado",
     "open": "Abrir",
     "paste": "Colar",
     "placeholders": {
@@ -1385,6 +1387,36 @@
     "preview": "Visualizar",
     "split": "Dividir"
   },
+  "import": {
+    "chatgpt": {
+      "assistant_name": "Importação do ChatGPT",
+      "button": "Selecionar Arquivo",
+      "description": "Importa apenas o texto da conversa, não inclui imagens e anexos",
+      "error": {
+        "invalid_json": "Formato de arquivo JSON inválido",
+        "no_conversations": "Nenhuma conversa encontrada no arquivo",
+        "no_valid_conversations": "Nenhuma conversa válida para importar",
+        "unknown": "Falha na importação, verifique o formato do arquivo"
+      },
+      "help": {
+        "step1": "1. Faça login no ChatGPT, vá para Configurações > Controles de dados > Exportar dados",
+        "step2": "2. Aguarde o arquivo de exportação por e-mail",
+        "step3": "3. Extraia o arquivo baixado e localize conversations.json",
+        "title": "Como exportar conversas do ChatGPT?"
+      },
+      "importing": "Importando conversas...",
+      "selecting": "Selecionando arquivo...",
+      "success": "Importadas com sucesso {{topics}} conversas com {{messages}} mensagens",
+      "title": "Importar Conversas do ChatGPT",
+      "untitled_conversation": "Conversa Sem Título"
+    },
+    "confirm": {
+      "button": "Selecionar Arquivo de Importação",
+      "label": "Tem certeza de que deseja importar dados externos?"
+    },
+    "content": "Selecione o arquivo de conversa do aplicativo externo para importar; atualmente, apenas arquivos no formato JSON do ChatGPT são suportados.",
+    "title": "Importar Conversas Externas"
+  },
   "knowledge": {
     "add": {
       "title": "Adicionar Base de Conhecimento"
@@ -3094,6 +3126,7 @@
         "basic": "Configurações Básicas",
         "cloud_storage": "Configurações de Armazenamento em Nuvem",
         "export_settings": "Configurações de Exportação",
+        "import_settings": "Importar Configurações",
         "third_party": "Conexões de Terceiros"
       },
       "export_menu": {
@@ -3152,6 +3185,11 @@
       },
       "hour_interval_one": "{{count}} hora",
       "hour_interval_other": "{{count}} horas",
+      "import_settings": {
+        "button": "Importar Arquivo Json",
+        "chatgpt": "Importar do ChatGPT",
+        "title": "Importar Dados de Aplicações Externas"
+      },
       "joplin": {
         "check": {
           "button": "Verificar",
@@ -4223,7 +4261,6 @@
         "default": "Padrão",
         "flex": "Flexível",
         "on_demand": "sob demanda",
-        "performance": "desempenho",
         "priority": "prioridade",
         "tip": "Especifique o nível de latência usado para processar a solicitação",
         "title": "Nível de Serviço"

src/renderer/src/i18n/translate/ru-ru.json

@@ -29,15 +29,15 @@
     },
     "gitBash": {
       "error": {
-        "description": "[to be translated]:Git Bash is required to run agents on Windows. The agent cannot function without it. Please install Git for Windows from",
+        "description": "Для запуска агентов в Windows требуется Git Bash. Без него агент не может работать. Пожалуйста, установите Git для Windows с",
-        "recheck": "[to be translated]:Recheck Git Bash Installation",
+        "recheck": "Повторная проверка установки Git Bash",
-        "title": "[to be translated]:Git Bash Required"
+        "title": "Требуется Git Bash"
       },
-      "notFound": "[to be translated]:Git Bash not found. Please install it first.",
+      "notFound": "Git Bash не найден. Пожалуйста, сначала установите его.",
-      "success": "[to be translated]:Git Bash detected successfully!"
+      "success": "Git Bash успешно обнаружен!"
     },
     "input": {
-      "placeholder": "[to be translated]:Enter your message here, send with {{key}} - @ select path, / select command"
+      "placeholder": "Введите ваше сообщение здесь, отправьте с помощью {{key}} — @ выбрать путь, / выбрать команду"
     },
     "list": {
       "error": {
@@ -266,6 +266,7 @@
       "error": {
         "sendFailed": "Не удалось отправить ваше решение. Попробуйте ещё раз."
       },
+      "executing": "Выполнение...",
       "expired": "Истёк",
       "inputPreview": "Предварительный просмотр ввода инструмента",
       "pending": "Ожидание ({{seconds}}с)",
@@ -1158,6 +1159,7 @@
     "name": "Имя",
     "no_results": "Результатов не найдено",
     "none": "без",
+    "off": "Выкл",
     "open": "Открыть",
     "paste": "Вставить",
     "placeholders": {
@@ -1385,6 +1387,36 @@
     "preview": "Предпросмотр",
     "split": "Разделить"
   },
+  "import": {
+    "chatgpt": {
+      "assistant_name": "Импорт ChatGPT",
+      "button": "Выбрать файл",
+      "description": "Импортирует только текст переписки, не включает изображения и вложения",
+      "error": {
+        "invalid_json": "Неверный формат файла JSON",
+        "no_conversations": "В файле не найдено ни одной беседы",
+        "no_valid_conversations": "Нет допустимых бесед для импорта",
+        "unknown": "Импорт не удался, проверьте формат файла"
+      },
+      "help": {
+        "step1": "1. Войдите в ChatGPT, перейдите в Настройки > Управление данными > Экспортировать данные",
+        "step2": "2. Дождитесь письма с файлом экспорта",
+        "step3": "3. Распакуйте загруженный файл и найдите conversations.json",
+        "title": "Как экспортировать диалоги с ChatGPT?"
+      },
+      "importing": "Импортирование разговоров...",
+      "selecting": "Выбор файла...",
+      "success": "Успешно импортировано {{topics}} бесед с {{messages}} сообщениями",
+      "title": "Импортировать диалоги ChatGPT",
+      "untitled_conversation": "Безымянный разговор"
+    },
+    "confirm": {
+      "button": "Выберите файл для импорта",
+      "label": "Вы уверены, что хотите импортировать внешние данные?"
+    },
+    "content": "Выберите внешний файл с перепиской для импорта; в настоящее время поддерживаются только файлы в формате JSON ChatGPT",
+    "title": "Импорт внешних бесед"
+  },
   "knowledge": {
     "add": {
       "title": "Добавить базу знаний"
@@ -3094,6 +3126,7 @@
         "basic": "Основные настройки данных",
         "cloud_storage": "Настройки облачного резервирования",
         "export_settings": "Настройки экспорта",
+        "import_settings": "Импорт настроек",
         "third_party": "Сторонние подключения"
       },
       "export_menu": {
@@ -3152,6 +3185,11 @@
       },
       "hour_interval_one": "{{count}} час",
       "hour_interval_other": "{{count}} часов",
+      "import_settings": {
+        "button": "Импортировать файл JSON",
+        "chatgpt": "Импорт из ChatGPT",
+        "title": "Импорт внешних данных приложения"
+      },
       "joplin": {
         "check": {
           "button": "Проверить",
@@ -4223,7 +4261,6 @@
         "default": "По умолчанию",
         "flex": "Гибкий",
         "on_demand": "по требованию",
-        "performance": "производительность",
         "priority": "приоритет",
         "tip": "Указывает уровень задержки, который следует использовать для обработки запроса",
         "title": "Уровень сервиса"

src/renderer/src/pages/home/Inputbar/tools/components/MCPToolsButton.tsx

@@ -3,7 +3,6 @@ import { ActionIconButton } from '@renderer/components/Buttons'
 import type { QuickPanelListItem } from '@renderer/components/QuickPanel'
 import { QuickPanelReservedSymbol, useQuickPanel } from '@renderer/components/QuickPanel'
 import { isGeminiModel } from '@renderer/config/models'
-import { isGeminiWebSearchProvider, isSupportUrlContextProvider } from '@renderer/config/providers'
 import { useAssistant } from '@renderer/hooks/useAssistant'
 import { useMCPServers } from '@renderer/hooks/useMCPServers'
 import { useTimer } from '@renderer/hooks/useTimer'
@@ -12,6 +11,7 @@ import { getProviderByModel } from '@renderer/services/AssistantService'
 import { EventEmitter } from '@renderer/services/EventService'
 import type { MCPPrompt, MCPResource, MCPServer } from '@renderer/types'
 import { isToolUseModeFunction } from '@renderer/utils/assistant'
+import { isGeminiWebSearchProvider, isSupportUrlContextProvider } from '@renderer/utils/provider'
 import { Form, Input } from 'antd'
 import { CircleX, Hammer, Plus } from 'lucide-react'
 import type { FC } from 'react'

src/renderer/src/pages/home/Inputbar/tools/components/WebSearchQuickPanelManager.tsx

@@ -9,7 +9,6 @@ import {
   isOpenAIWebSearchModel,
   isWebSearchModel
 } from '@renderer/config/models'
-import { isGeminiWebSearchProvider } from '@renderer/config/providers'
 import { useAssistant } from '@renderer/hooks/useAssistant'
 import { useTimer } from '@renderer/hooks/useTimer'
 import { useWebSearchProviders } from '@renderer/hooks/useWebSearchProviders'
@@ -19,6 +18,7 @@ import WebSearchService from '@renderer/services/WebSearchService'
 import type { WebSearchProvider, WebSearchProviderId } from '@renderer/types'
 import { hasObjectKey } from '@renderer/utils'
 import { isToolUseModeFunction } from '@renderer/utils/assistant'
+import { isGeminiWebSearchProvider } from '@renderer/utils/provider'
 import { Globe } from 'lucide-react'
 import { useCallback, useEffect, useMemo } from 'react'
 import { useTranslation } from 'react-i18next'

src/renderer/src/pages/home/Inputbar/tools/urlContextTool.tsx

@@ -1,7 +1,7 @@
-import { isAnthropicModel, isGeminiModel } from '@renderer/config/models'
+import { isAnthropicModel, isGeminiModel, isPureGenerateImageModel } from '@renderer/config/models'
-import { isSupportUrlContextProvider } from '@renderer/config/providers'
 import { defineTool, registerTool, TopicType } from '@renderer/pages/home/Inputbar/types'
 import { getProviderByModel } from '@renderer/services/AssistantService'
+import { isSupportUrlContextProvider } from '@renderer/utils/provider'
 
 import UrlContextButton from './components/UrlContextbutton'
 
@@ -11,7 +11,12 @@ const urlContextTool = defineTool({
   visibleInScopes: [TopicType.Chat],
   condition: ({ model }) => {
     const provider = getProviderByModel(model)
-    return !!provider && isSupportUrlContextProvider(provider) && (isGeminiModel(model) || isAnthropicModel(model))
+    return (
+      !!provider &&
+      isSupportUrlContextProvider(provider) &&
+      !isPureGenerateImageModel(model) &&
+      (isGeminiModel(model) || isAnthropicModel(model))
+    )
   },
   render: ({ assistant }) => <UrlContextButton assistantId={assistant.id} />
 })

src/renderer/src/pages/home/Inputbar/tools/webSearchTool.tsx

@@ -1,4 +1,4 @@
-import { isMandatoryWebSearchModel } from '@renderer/config/models'
+import { isMandatoryWebSearchModel, isWebSearchModel } from '@renderer/config/models'
 import { defineTool, registerTool, TopicType } from '@renderer/pages/home/Inputbar/types'
 
 import WebSearchButton from './components/WebSearchButton'
@@ -15,7 +15,7 @@ const webSearchTool = defineTool({
   label: (t) => t('chat.input.web_search.label'),
 
   visibleInScopes: [TopicType.Chat],
-  condition: ({ model }) => !isMandatoryWebSearchModel(model),
+  condition: ({ model }) => isWebSearchModel(model) && !isMandatoryWebSearchModel(model),
 
   render: function WebSearchToolRender(context) {
     const { assistant, quickPanelController } = context