🦙 fix: Ollama Custom Headers (#10314)

* 🦙 fix: Ollama Custom Headers

* chore: Correct import order for resolveHeaders in OllamaClient.js

* fix: Improve error logging for Ollama API model fetch failure

* ci: update Ollama model fetch tests

* ci: Add unit test for passing headers and user object to Ollama fetchModels

api/app/clients/OllamaClient.js

@@ -2,7 +2,7 @@ const { z } = require('zod');
 const axios = require('axios');
 const { Ollama } = require('ollama');
 const { sleep } = require('@librechat/agents');
-const { logAxiosError } = require('@librechat/api');
+const { resolveHeaders } = require('@librechat/api');
 const { logger } = require('@librechat/data-schemas');
 const { Constants } = require('librechat-data-provider');
 const { deriveBaseURL } = require('~/utils');
@@ -44,6 +44,7 @@ class OllamaClient {
   constructor(options = {}) {
     const host = deriveBaseURL(options.baseURL ?? 'http://localhost:11434');
     this.streamRate = options.streamRate ?? Constants.DEFAULT_STREAM_RATE;
+    this.headers = options.headers ?? {};
     /** @type {Ollama} */
     this.client = new Ollama({ host });
   }
@@ -51,27 +52,32 @@ class OllamaClient {
   /**
    * Fetches Ollama models from the specified base API path.
    * @param {string} baseURL
+   * @param {Object} [options] - Optional configuration
+   * @param {Partial<IUser>} [options.user] - User object for header resolution
+   * @param {Record<string, string>} [options.headers] - Headers to include in the request
    * @returns {Promise<string[]>} The Ollama models.
+   * @throws {Error} Throws if the Ollama API request fails
    */
-  static async fetchModels(baseURL) {
+  static async fetchModels(baseURL, options = {}) {
-    let models = [];
     if (!baseURL) {
-      return models;
-    }
-    try {
-      const ollamaEndpoint = deriveBaseURL(baseURL);
-      /** @type {Promise<AxiosResponse<OllamaListResponse>>} */
-      const response = await axios.get(`${ollamaEndpoint}/api/tags`, {
-        timeout: 5000,
-      });
-      models = response.data.models.map((tag) => tag.name);
-      return models;
-    } catch (error) {
-      const logMessage =
-        "Failed to fetch models from Ollama API. If you are not using Ollama directly, and instead, through some aggregator or reverse proxy that handles fetching via OpenAI spec, ensure the name of the endpoint doesn't start with `ollama` (case-insensitive).";
-      logAxiosError({ message: logMessage, error });
       return [];
     }
+
+    const ollamaEndpoint = deriveBaseURL(baseURL);
+
+    const resolvedHeaders = resolveHeaders({
+      headers: options.headers,
+      user: options.user,
+    });
+
+    /** @type {Promise<AxiosResponse<OllamaListResponse>>} */
+    const response = await axios.get(`${ollamaEndpoint}/api/tags`, {
+      headers: resolvedHeaders,
+      timeout: 5000,
+    });
+
+    const models = response.data.models.map((tag) => tag.name);
+    return models;
   }
 
   /**

api/server/services/Config/loadConfigModels.js

@@ -57,7 +57,7 @@ async function loadConfigModels(req) {
 
   for (let i = 0; i < customEndpoints.length; i++) {
     const endpoint = customEndpoints[i];
-    const { models, name: configName, baseURL, apiKey } = endpoint;
+    const { models, name: configName, baseURL, apiKey, headers: endpointHeaders } = endpoint;
     const name = normalizeEndpointName(configName);
     endpointsMap[name] = endpoint;
 
@@ -76,6 +76,8 @@ async function loadConfigModels(req) {
           apiKey: API_KEY,
           baseURL: BASE_URL,
           user: req.user.id,
+          userObject: req.user,
+          headers: endpointHeaders,
           direct: endpoint.directEndpoint,
           userIdQuery: models.userIdQuery,
         });

api/server/services/Endpoints/custom/initialize.js

@@ -1,4 +1,3 @@
-const { Providers } = require('@librechat/agents');
 const {
   resolveHeaders,
   isUserProvided,
@@ -143,39 +142,27 @@ const initializeClient = async ({ req, res, endpointOption, optionsOnly, overrid
 
   if (optionsOnly) {
     const modelOptions = endpointOption?.model_parameters ?? {};
-    if (endpoint !== Providers.OLLAMA) {
+    clientOptions = Object.assign(
-      clientOptions = Object.assign(
+      {
-        {
+        modelOptions,
-          modelOptions,
+      },
-        },
+      clientOptions,
-        clientOptions,
+    );
-      );
+    clientOptions.modelOptions.user = req.user.id;
-      clientOptions.modelOptions.user = req.user.id;
+    const options = getOpenAIConfig(apiKey, clientOptions, endpoint);
-      const options = getOpenAIConfig(apiKey, clientOptions, endpoint);
+    if (options != null) {
-      if (options != null) {
+      options.useLegacyContent = true;
-        options.useLegacyContent = true;
+      options.endpointTokenConfig = endpointTokenConfig;
-        options.endpointTokenConfig = endpointTokenConfig;
+    }
-      }
+    if (!clientOptions.streamRate) {
-      if (!clientOptions.streamRate) {
-        return options;
-      }
-      options.llmConfig.callbacks = [
-        {
-          handleLLMNewToken: createHandleLLMNewToken(clientOptions.streamRate),
-        },
-      ];
       return options;
     }
-
+    options.llmConfig.callbacks = [
-    if (clientOptions.reverseProxyUrl) {
+      {
-      modelOptions.baseUrl = clientOptions.reverseProxyUrl.split('/v1')[0];
+        handleLLMNewToken: createHandleLLMNewToken(clientOptions.streamRate),
-      delete clientOptions.reverseProxyUrl;
+      },
-    }
+    ];
-
+    return options;
-    return {
-      useLegacyContent: true,
-      llmConfig: modelOptions,
-    };
   }
 
   const client = new OpenAIClient(apiKey, clientOptions);

api/server/services/ModelService.js

@@ -39,6 +39,8 @@ const { openAIApiKey, userProvidedOpenAI } = require('./Config/EndpointService')
  * @param {boolean} [params.userIdQuery=false] - Whether to send the user ID as a query parameter.
  * @param {boolean} [params.createTokenConfig=true] - Whether to create a token configuration from the API response.
  * @param {string} [params.tokenKey] - The cache key to save the token configuration. Uses `name` if omitted.
+ * @param {Record<string, string>} [params.headers] - Optional headers for the request.
+ * @param {Partial<IUser>} [params.userObject] - Optional user object for header resolution.
  * @returns {Promise<string[]>} A promise that resolves to an array of model identifiers.
  * @async
  */
@@ -52,6 +54,8 @@ const fetchModels = async ({
   userIdQuery = false,
   createTokenConfig = true,
   tokenKey,
+  headers,
+  userObject,
 }) => {
   let models = [];
   const baseURL = direct ? extractBaseURL(_baseURL) : _baseURL;
@@ -65,7 +69,13 @@ const fetchModels = async ({
   }
 
   if (name && name.toLowerCase().startsWith(Providers.OLLAMA)) {
-    return await OllamaClient.fetchModels(baseURL);
+    try {
+      return await OllamaClient.fetchModels(baseURL, { headers, user: userObject });
+    } catch (ollamaError) {
+      const logMessage =
+        'Failed to fetch models from Ollama API. Attempting to fetch via OpenAI-compatible endpoint.';
+      logAxiosError({ message: logMessage, error: ollamaError });
+    }
   }
 
   try {

api/server/services/ModelService.spec.js

@@ -1,5 +1,5 @@
 const axios = require('axios');
-const { logger } = require('@librechat/data-schemas');
+const { logAxiosError, resolveHeaders } = require('@librechat/api');
 const { EModelEndpoint, defaultModels } = require('librechat-data-provider');
 
 const {
@@ -18,6 +18,8 @@ jest.mock('@librechat/api', () => {
     processModelData: jest.fn((...args) => {
       return originalUtils.processModelData(...args);
     }),
+    logAxiosError: jest.fn(),
+    resolveHeaders: jest.fn((options) => options?.headers || {}),
   };
 });
 
@@ -277,12 +279,51 @@ describe('fetchModels with Ollama specific logic', () => {
 
     expect(models).toEqual(['Ollama-Base', 'Ollama-Advanced']);
     expect(axios.get).toHaveBeenCalledWith('https://api.ollama.test.com/api/tags', {
+      headers: {},
       timeout: 5000,
     });
   });
 
-  it('should handle errors gracefully when fetching Ollama models fails', async () => {
+  it('should pass headers and user object to Ollama fetchModels', async () => {
-    axios.get.mockRejectedValue(new Error('Network error'));
+    const customHeaders = {
+      'Content-Type': 'application/json',
+      Authorization: 'Bearer custom-token',
+    };
+    const userObject = {
+      id: 'user789',
+      email: 'test@example.com',
+    };
+
+    resolveHeaders.mockReturnValueOnce(customHeaders);
+
+    const models = await fetchModels({
+      user: 'user789',
+      apiKey: 'testApiKey',
+      baseURL: 'https://api.ollama.test.com',
+      name: 'ollama',
+      headers: customHeaders,
+      userObject,
+    });
+
+    expect(models).toEqual(['Ollama-Base', 'Ollama-Advanced']);
+    expect(resolveHeaders).toHaveBeenCalledWith({
+      headers: customHeaders,
+      user: userObject,
+    });
+    expect(axios.get).toHaveBeenCalledWith('https://api.ollama.test.com/api/tags', {
+      headers: customHeaders,
+      timeout: 5000,
+    });
+  });
+
+  it('should handle errors gracefully when fetching Ollama models fails and fallback to OpenAI-compatible fetch', async () => {
+    axios.get.mockRejectedValueOnce(new Error('Ollama API error'));
+    axios.get.mockResolvedValueOnce({
+      data: {
+        data: [{ id: 'fallback-model-1' }, { id: 'fallback-model-2' }],
+      },
+    });
+
     const models = await fetchModels({
       user: 'user789',
       apiKey: 'testApiKey',
@@ -290,8 +331,13 @@ describe('fetchModels with Ollama specific logic', () => {
       name: 'OllamaAPI',
     });
 
-    expect(models).toEqual([]);
+    expect(models).toEqual(['fallback-model-1', 'fallback-model-2']);
-    expect(logger.error).toHaveBeenCalled();
+    expect(logAxiosError).toHaveBeenCalledWith({
+      message:
+        'Failed to fetch models from Ollama API. Attempting to fetch via OpenAI-compatible endpoint.',
+      error: expect.any(Error),
+    });
+    expect(axios.get).toHaveBeenCalledTimes(2);
   });
 
   it('should return an empty array if no baseURL is provided', async () => {