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fix(openai): 更新openai依赖版本并修复嵌入模型处理逻辑
修复openai客户端中嵌入模型处理逻辑，当模型名称包含"jina"时不使用base64编码 移除平台相关头信息以解决兼容性问题 更新package.json中openai依赖版本至5.12.0
This commit is contained in:
icarus
parent
9f856bd696
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8fa91b35b3
344
.yarn/patches/openai-npm-5.12.0-a06a6369b2.patch
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344
.yarn/patches/openai-npm-5.12.0-a06a6369b2.patch
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@ -0,0 +1,344 @@
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diff --git a/client.js b/client.js
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index 22cc08d77ce849842a28f684c20dd5738152efa4..0c20f96405edbe7724b87517115fa2a61934b343 100644
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--- a/client.js
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+++ b/client.js
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@@ -444,7 +444,7 @@ class OpenAI {
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'User-Agent': this.getUserAgent(),
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'X-Stainless-Retry-Count': String(retryCount),
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...(options.timeout ? { 'X-Stainless-Timeout': String(Math.trunc(options.timeout / 1000)) } : {}),
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- ...(0, detect_platform_1.getPlatformHeaders)(),
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+ // ...(0, detect_platform_1.getPlatformHeaders)(),
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'OpenAI-Organization': this.organization,
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'OpenAI-Project': this.project,
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},
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diff --git a/client.mjs b/client.mjs
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index 7f1af99fb30d2cae03eea6687b53e6c7828faceb..fd66373a5eff31a5846084387a3fd97956c9ad48 100644
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--- a/client.mjs
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+++ b/client.mjs
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@@ -1,43 +1,41 @@
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// File generated from our OpenAPI spec by Stainless. See CONTRIBUTING.md for details.
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var _OpenAI_instances, _a, _OpenAI_encoder, _OpenAI_baseURLOverridden;
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-import { __classPrivateFieldGet, __classPrivateFieldSet } from "./internal/tslib.mjs";
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-import { uuid4 } from "./internal/utils/uuid.mjs";
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-import { validatePositiveInteger, isAbsoluteURL, safeJSON } from "./internal/utils/values.mjs";
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-import { sleep } from "./internal/utils/sleep.mjs";
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-import { castToError, isAbortError } from "./internal/errors.mjs";
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-import { getPlatformHeaders } from "./internal/detect-platform.mjs";
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-import * as Shims from "./internal/shims.mjs";
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-import * as Opts from "./internal/request-options.mjs";
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-import * as qs from "./internal/qs/index.mjs";
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-import { VERSION } from "./version.mjs";
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+import { APIPromise } from "./core/api-promise.mjs";
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import * as Errors from "./core/error.mjs";
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import * as Pagination from "./core/pagination.mjs";
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import * as Uploads from "./core/uploads.mjs";
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-import * as API from "./resources/index.mjs";
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-import { APIPromise } from "./core/api-promise.mjs";
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-import { Batches, } from "./resources/batches.mjs";
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-import { Completions, } from "./resources/completions.mjs";
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-import { Embeddings, } from "./resources/embeddings.mjs";
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-import { Files, } from "./resources/files.mjs";
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-import { Images, } from "./resources/images.mjs";
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-import { Models } from "./resources/models.mjs";
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-import { Moderations, } from "./resources/moderations.mjs";
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-import { Webhooks } from "./resources/webhooks.mjs";
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+import { isRunningInBrowser } from "./internal/detect-platform.mjs";
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+import { castToError, isAbortError } from "./internal/errors.mjs";
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+import { buildHeaders } from "./internal/headers.mjs";
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+import * as qs from "./internal/qs/index.mjs";
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+import * as Opts from "./internal/request-options.mjs";
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+import * as Shims from "./internal/shims.mjs";
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+import { __classPrivateFieldGet, __classPrivateFieldSet } from "./internal/tslib.mjs";
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+import { readEnv } from "./internal/utils/env.mjs";
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+import { formatRequestDetails, loggerFor, parseLogLevel, } from "./internal/utils/log.mjs";
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+import { sleep } from "./internal/utils/sleep.mjs";
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+import { uuid4 } from "./internal/utils/uuid.mjs";
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+import { isAbsoluteURL, isEmptyObj, safeJSON, validatePositiveInteger } from "./internal/utils/values.mjs";
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import { Audio } from "./resources/audio/audio.mjs";
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+import { Batches, } from "./resources/batches.mjs";
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import { Beta } from "./resources/beta/beta.mjs";
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import { Chat } from "./resources/chat/chat.mjs";
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+import { Completions, } from "./resources/completions.mjs";
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import { Containers, } from "./resources/containers/containers.mjs";
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+import { Embeddings, } from "./resources/embeddings.mjs";
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import { Evals, } from "./resources/evals/evals.mjs";
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+import { Files, } from "./resources/files.mjs";
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import { FineTuning } from "./resources/fine-tuning/fine-tuning.mjs";
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import { Graders } from "./resources/graders/graders.mjs";
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+import { Images, } from "./resources/images.mjs";
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+import * as API from "./resources/index.mjs";
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+import { Models } from "./resources/models.mjs";
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+import { Moderations, } from "./resources/moderations.mjs";
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import { Responses } from "./resources/responses/responses.mjs";
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import { Uploads as UploadsAPIUploads, } from "./resources/uploads/uploads.mjs";
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import { VectorStores, } from "./resources/vector-stores/vector-stores.mjs";
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-import { isRunningInBrowser } from "./internal/detect-platform.mjs";
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-import { buildHeaders } from "./internal/headers.mjs";
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-import { readEnv } from "./internal/utils/env.mjs";
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-import { formatRequestDetails, loggerFor, parseLogLevel, } from "./internal/utils/log.mjs";
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-import { isEmptyObj } from "./internal/utils/values.mjs";
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+import { Webhooks } from "./resources/webhooks.mjs";
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+import { VERSION } from "./version.mjs";
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/**
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* API Client for interfacing with the OpenAI API.
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*/
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@@ -441,7 +439,7 @@ export class OpenAI {
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'User-Agent': this.getUserAgent(),
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'X-Stainless-Retry-Count': String(retryCount),
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...(options.timeout ? { 'X-Stainless-Timeout': String(Math.trunc(options.timeout / 1000)) } : {}),
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- ...getPlatformHeaders(),
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+ // ...getPlatformHeaders(),
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'OpenAI-Organization': this.organization,
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'OpenAI-Project': this.project,
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},
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diff --git a/core/error.js b/core/error.js
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index c302cc356f0f24b50c3f5a0aa3ea0b79ae1e9a8d..164ee2ee31cd7eea8f70139e25d140b763e91d36 100644
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--- a/core/error.js
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+++ b/core/error.js
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@@ -40,7 +40,7 @@ class APIError extends OpenAIError {
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if (!status || !headers) {
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return new APIConnectionError({ message, cause: (0, errors_1.castToError)(errorResponse) });
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}
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- const error = errorResponse?.['error'];
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+ const error = errorResponse?.['error'] || errorResponse;
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if (status === 400) {
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return new BadRequestError(status, error, message, headers);
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}
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diff --git a/core/error.mjs b/core/error.mjs
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index 75f5b0c328cc4894478f3490a00dbf6abd96fc12..269f46f96e9fad1f7a1649a3810562abc7fae37f 100644
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--- a/core/error.mjs
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+++ b/core/error.mjs
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@@ -36,7 +36,7 @@ export class APIError extends OpenAIError {
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if (!status || !headers) {
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return new APIConnectionError({ message, cause: castToError(errorResponse) });
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}
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- const error = errorResponse?.['error'];
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+ const error = errorResponse?.['error'] || errorResponse;
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if (status === 400) {
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return new BadRequestError(status, error, message, headers);
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}
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diff --git a/resources/embeddings.js b/resources/embeddings.js
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index 2404264d4ba0204322548945ebb7eab3bea82173..93b9e286f62101b5aa7532e96ddba61f682ece3f 100644
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--- a/resources/embeddings.js
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+++ b/resources/embeddings.js
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@@ -5,52 +5,64 @@ exports.Embeddings = void 0;
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const resource_1 = require("../core/resource.js");
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const utils_1 = require("../internal/utils.js");
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class Embeddings extends resource_1.APIResource {
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- /**
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- * Creates an embedding vector representing the input text.
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- *
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- * @example
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- * ```ts
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- * const createEmbeddingResponse =
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- * await client.embeddings.create({
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- * input: 'The quick brown fox jumped over the lazy dog',
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- * model: 'text-embedding-3-small',
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- * });
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- * ```
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- */
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- create(body, options) {
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- const hasUserProvidedEncodingFormat = !!body.encoding_format;
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- // No encoding_format specified, defaulting to base64 for performance reasons
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- // See https://github.com/openai/openai-node/pull/1312
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- let encoding_format = hasUserProvidedEncodingFormat ? body.encoding_format : 'base64';
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- if (hasUserProvidedEncodingFormat) {
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- (0, utils_1.loggerFor)(this._client).debug('embeddings/user defined encoding_format:', body.encoding_format);
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- }
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- const response = this._client.post('/embeddings', {
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- body: {
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- ...body,
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- encoding_format: encoding_format,
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- },
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- ...options,
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- });
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- // if the user specified an encoding_format, return the response as-is
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- if (hasUserProvidedEncodingFormat) {
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- return response;
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- }
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- // in this stage, we are sure the user did not specify an encoding_format
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- // and we defaulted to base64 for performance reasons
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- // we are sure then that the response is base64 encoded, let's decode it
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- // the returned result will be a float32 array since this is OpenAI API's default encoding
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- (0, utils_1.loggerFor)(this._client).debug('embeddings/decoding base64 embeddings from base64');
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- return response._thenUnwrap((response) => {
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- if (response && response.data) {
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- response.data.forEach((embeddingBase64Obj) => {
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- const embeddingBase64Str = embeddingBase64Obj.embedding;
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- embeddingBase64Obj.embedding = (0, utils_1.toFloat32Array)(embeddingBase64Str);
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- });
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- }
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- return response;
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- });
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+ /**
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+ * Creates an embedding vector representing the input text.
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+ *
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+ * @example
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+ * ```ts
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+ * const createEmbeddingResponse =
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+ * await client.embeddings.create({
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+ * input: 'The quick brown fox jumped over the lazy dog',
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+ * model: 'text-embedding-3-small',
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+ * });
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+ * ```
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+ */
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+ create(body, options) {
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+ const hasUserProvidedEncodingFormat = !!body.encoding_format;
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+ // No encoding_format specified, defaulting to base64 for performance reasons
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+ // See https://github.com/openai/openai-node/pull/1312
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+ let encoding_format = hasUserProvidedEncodingFormat
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+ ? body.encoding_format
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+ : "base64";
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+ if (body.model.includes("jina")) {
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+ encoding_format = undefined;
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+ }
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+ if (hasUserProvidedEncodingFormat) {
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+ (0, utils_1.loggerFor)(this._client).debug(
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+ "embeddings/user defined encoding_format:",
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+ body.encoding_format
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+ );
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}
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+ const response = this._client.post("/embeddings", {
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+ body: {
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+ ...body,
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+ encoding_format: encoding_format,
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+ },
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+ ...options,
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+ });
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+ // if the user specified an encoding_format, return the response as-is
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+ if (hasUserProvidedEncodingFormat || body.model.includes("jina")) {
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+ return response;
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+ }
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+ // in this stage, we are sure the user did not specify an encoding_format
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+ // and we defaulted to base64 for performance reasons
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+ // we are sure then that the response is base64 encoded, let's decode it
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+ // the returned result will be a float32 array since this is OpenAI API's default encoding
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+ (0, utils_1.loggerFor)(this._client).debug(
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+ "embeddings/decoding base64 embeddings from base64"
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+ );
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+ return response._thenUnwrap((response) => {
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+ if (response && response.data && typeof response.data[0]?.embedding === 'string') {
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+ response.data.forEach((embeddingBase64Obj) => {
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+ const embeddingBase64Str = embeddingBase64Obj.embedding;
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+ embeddingBase64Obj.embedding = (0, utils_1.toFloat32Array)(
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+ embeddingBase64Str
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+ );
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+ });
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+ }
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+ return response;
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+ });
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+ }
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}
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exports.Embeddings = Embeddings;
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//# sourceMappingURL=embeddings.js.map
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diff --git a/resources/embeddings.mjs b/resources/embeddings.mjs
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index 19dcaef578c194a89759c4360073cfd4f7dd2cbf..42c903fadb03c707356a983603ff09e4152ecf11 100644
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--- a/resources/embeddings.mjs
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+++ b/resources/embeddings.mjs
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@@ -2,51 +2,61 @@
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import { APIResource } from "../core/resource.mjs";
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import { loggerFor, toFloat32Array } from "../internal/utils.mjs";
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export class Embeddings extends APIResource {
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- /**
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|
- * Creates an embedding vector representing the input text.
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|
- *
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|
- * @example
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|
- * ```ts
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|
- * const createEmbeddingResponse =
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|
- * await client.embeddings.create({
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|
- * input: 'The quick brown fox jumped over the lazy dog',
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|
- * model: 'text-embedding-3-small',
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|
- * });
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|
- * ```
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|
- */
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|
- create(body, options) {
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|
- const hasUserProvidedEncodingFormat = !!body.encoding_format;
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|
- // No encoding_format specified, defaulting to base64 for performance reasons
|
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|
- // See https://github.com/openai/openai-node/pull/1312
|
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|
- let encoding_format = hasUserProvidedEncodingFormat ? body.encoding_format : 'base64';
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|
- if (hasUserProvidedEncodingFormat) {
|
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|
- loggerFor(this._client).debug('embeddings/user defined encoding_format:', body.encoding_format);
|
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|
- }
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|
- const response = this._client.post('/embeddings', {
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|
- body: {
|
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|
- ...body,
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|
- encoding_format: encoding_format,
|
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|
- },
|
||||||
|
- ...options,
|
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|
- });
|
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|
- // if the user specified an encoding_format, return the response as-is
|
||||||
|
- if (hasUserProvidedEncodingFormat) {
|
||||||
|
- return response;
|
||||||
|
- }
|
||||||
|
- // in this stage, we are sure the user did not specify an encoding_format
|
||||||
|
- // and we defaulted to base64 for performance reasons
|
||||||
|
- // we are sure then that the response is base64 encoded, let's decode it
|
||||||
|
- // the returned result will be a float32 array since this is OpenAI API's default encoding
|
||||||
|
- loggerFor(this._client).debug('embeddings/decoding base64 embeddings from base64');
|
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|
- return response._thenUnwrap((response) => {
|
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|
- if (response && response.data) {
|
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|
- response.data.forEach((embeddingBase64Obj) => {
|
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|
- const embeddingBase64Str = embeddingBase64Obj.embedding;
|
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|
- embeddingBase64Obj.embedding = toFloat32Array(embeddingBase64Str);
|
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|
- });
|
||||||
|
- }
|
||||||
|
- return response;
|
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|
- });
|
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|
+ /**
|
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|
+ * Creates an embedding vector representing the input text.
|
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|
+ *
|
||||||
|
+ * @example
|
||||||
|
+ * ```ts
|
||||||
|
+ * const createEmbeddingResponse =
|
||||||
|
+ * await client.embeddings.create({
|
||||||
|
+ * input: 'The quick brown fox jumped over the lazy dog',
|
||||||
|
+ * model: 'text-embedding-3-small',
|
||||||
|
+ * });
|
||||||
|
+ * ```
|
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|
+ */
|
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|
+ create(body, options) {
|
||||||
|
+ const hasUserProvidedEncodingFormat = !!body.encoding_format;
|
||||||
|
+ // No encoding_format specified, defaulting to base64 for performance reasons
|
||||||
|
+ // See https://github.com/openai/openai-node/pull/1312
|
||||||
|
+ let encoding_format = hasUserProvidedEncodingFormat
|
||||||
|
+ ? body.encoding_format
|
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|
+ : "base64";
|
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|
+ if (body.model.includes("jina")) {
|
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|
+ encoding_format = undefined;
|
||||||
|
+ }
|
||||||
|
+ if (hasUserProvidedEncodingFormat) {
|
||||||
|
+ loggerFor(this._client).debug(
|
||||||
|
+ "embeddings/user defined encoding_format:",
|
||||||
|
+ body.encoding_format
|
||||||
|
+ );
|
||||||
|
}
|
||||||
|
+ const response = this._client.post("/embeddings", {
|
||||||
|
+ body: {
|
||||||
|
+ ...body,
|
||||||
|
+ encoding_format: encoding_format,
|
||||||
|
+ },
|
||||||
|
+ ...options,
|
||||||
|
+ });
|
||||||
|
+ // if the user specified an encoding_format, return the response as-is
|
||||||
|
+ if (hasUserProvidedEncodingFormat || body.model.includes("jina")) {
|
||||||
|
+ return response;
|
||||||
|
+ }
|
||||||
|
+ // in this stage, we are sure the user did not specify an encoding_format
|
||||||
|
+ // and we defaulted to base64 for performance reasons
|
||||||
|
+ // we are sure then that the response is base64 encoded, let's decode it
|
||||||
|
+ // the returned result will be a float32 array since this is OpenAI API's default encoding
|
||||||
|
+ loggerFor(this._client).debug(
|
||||||
|
+ "embeddings/decoding base64 embeddings from base64"
|
||||||
|
+ );
|
||||||
|
+ return response._thenUnwrap((response) => {
|
||||||
|
+ if (response && response.data && typeof response.data[0]?.embedding === 'string') {
|
||||||
|
+ response.data.forEach((embeddingBase64Obj) => {
|
||||||
|
+ const embeddingBase64Str = embeddingBase64Obj.embedding;
|
||||||
|
+ embeddingBase64Obj.embedding = toFloat32Array(embeddingBase64Str);
|
||||||
|
+ });
|
||||||
|
+ }
|
||||||
|
+ return response;
|
||||||
|
+ });
|
||||||
|
+ }
|
||||||
|
}
|
||||||
|
//# sourceMappingURL=embeddings.mjs.map
|
||||||
@ -216,7 +216,7 @@
|
|||||||
"motion": "^12.10.5",
|
"motion": "^12.10.5",
|
||||||
"notion-helper": "^1.3.22",
|
"notion-helper": "^1.3.22",
|
||||||
"npx-scope-finder": "^1.2.0",
|
"npx-scope-finder": "^1.2.0",
|
||||||
"openai": "^5.12.0",
|
"openai": "patch:openai@npm%3A5.12.0#~/.yarn/patches/openai-npm-5.12.0-a06a6369b2.patch",
|
||||||
"p-queue": "^8.1.0",
|
"p-queue": "^8.1.0",
|
||||||
"pdf-lib": "^1.17.1",
|
"pdf-lib": "^1.17.1",
|
||||||
"playwright": "^1.52.0",
|
"playwright": "^1.52.0",
|
||||||
@ -273,10 +273,10 @@
|
|||||||
"@langchain/openai@npm:^0.3.16": "patch:@langchain/openai@npm%3A0.3.16#~/.yarn/patches/@langchain-openai-npm-0.3.16-e525b59526.patch",
|
"@langchain/openai@npm:^0.3.16": "patch:@langchain/openai@npm%3A0.3.16#~/.yarn/patches/@langchain-openai-npm-0.3.16-e525b59526.patch",
|
||||||
"@langchain/openai@npm:>=0.1.0 <0.4.0": "patch:@langchain/openai@npm%3A0.3.16#~/.yarn/patches/@langchain-openai-npm-0.3.16-e525b59526.patch",
|
"@langchain/openai@npm:>=0.1.0 <0.4.0": "patch:@langchain/openai@npm%3A0.3.16#~/.yarn/patches/@langchain-openai-npm-0.3.16-e525b59526.patch",
|
||||||
"libsql@npm:^0.4.4": "patch:libsql@npm%3A0.4.7#~/.yarn/patches/libsql-npm-0.4.7-444e260fb1.patch",
|
"libsql@npm:^0.4.4": "patch:libsql@npm%3A0.4.7#~/.yarn/patches/libsql-npm-0.4.7-444e260fb1.patch",
|
||||||
"openai@npm:^4.77.0": "patch:openai@npm%3A5.1.0#~/.yarn/patches/openai-npm-5.1.0-0e7b3ccb07.patch",
|
"openai@npm:^4.77.0": "patch:openai@npm%3A5.12.0#~/.yarn/patches/openai-npm-5.12.0-a06a6369b2.patch",
|
||||||
"pkce-challenge@npm:^4.1.0": "patch:pkce-challenge@npm%3A4.1.0#~/.yarn/patches/pkce-challenge-npm-4.1.0-fbc51695a3.patch",
|
"pkce-challenge@npm:^4.1.0": "patch:pkce-challenge@npm%3A4.1.0#~/.yarn/patches/pkce-challenge-npm-4.1.0-fbc51695a3.patch",
|
||||||
"app-builder-lib@npm:26.0.13": "patch:app-builder-lib@npm%3A26.0.13#~/.yarn/patches/app-builder-lib-npm-26.0.13-a064c9e1d0.patch",
|
"app-builder-lib@npm:26.0.13": "patch:app-builder-lib@npm%3A26.0.13#~/.yarn/patches/app-builder-lib-npm-26.0.13-a064c9e1d0.patch",
|
||||||
"openai@npm:^4.87.3": "patch:openai@npm%3A5.1.0#~/.yarn/patches/openai-npm-5.1.0-0e7b3ccb07.patch",
|
"openai@npm:^4.87.3": "patch:openai@npm%3A5.12.0#~/.yarn/patches/openai-npm-5.12.0-a06a6369b2.patch",
|
||||||
"app-builder-lib@npm:26.0.15": "patch:app-builder-lib@npm%3A26.0.15#~/.yarn/patches/app-builder-lib-npm-26.0.15-360e5b0476.patch",
|
"app-builder-lib@npm:26.0.15": "patch:app-builder-lib@npm%3A26.0.15#~/.yarn/patches/app-builder-lib-npm-26.0.15-360e5b0476.patch",
|
||||||
"@langchain/core@npm:^0.3.26": "patch:@langchain/core@npm%3A0.3.44#~/.yarn/patches/@langchain-core-npm-0.3.44-41d5c3cb0a.patch",
|
"@langchain/core@npm:^0.3.26": "patch:@langchain/core@npm%3A0.3.44#~/.yarn/patches/@langchain-core-npm-0.3.44-41d5c3cb0a.patch",
|
||||||
"node-abi": "4.12.0",
|
"node-abi": "4.12.0",
|
||||||
|
|||||||
Loading…
Reference in New Issue
Block a user