feat(embeddings): support custom OpenAI baseURL for Ollama / OpenAI-compatible providers

Dockerfile

@@ -32,6 +32,12 @@ RUN apt-get update && apt-get install -y \
 
 COPY package*.json ./
 RUN npm install --ignore-scripts
+# --ignore-scripts skips node-gyp rebuild for native modules
+# (security best-practice, blocks malicious postinstall scripts).
+# Explicitly rebuild better-sqlite3 so its arm64/amd64 .node binding
+# is compiled — otherwise the runtime fails with "Could not locate
+# the bindings file" on architectures lacking a prebuild.
+RUN npm rebuild better-sqlite3
 # Install Chrome via Puppeteer as fallback (system Chromium will be used first)
 RUN npx puppeteer browsers install chrome || true
 COPY . .

README.md

@@ -151,6 +151,16 @@ Configuration is managed through two files:
     OPENAI_API_KEY="sk-..."
     OPENAI_MODEL="text-embedding-3-large"  # Optional, defaults to text-embedding-3-large
 
+    # Optional: Override the OpenAI API base URL. Useful for pointing the
+    # OpenAI SDK at an OpenAI-compatible endpoint such as Ollama, LM Studio,
+    # llama.cpp, vLLM, or a proxy gateway. When unset, the SDK uses the
+    # default OpenAI endpoint. Equivalent to the `embedding.openai.base_url`
+    # field in config.yaml; the env var wins if both are set.
+    # Example values:
+    #   OPENAI_BASE_URL="http://localhost:11434/v1"        # Ollama
+    #   OPENAI_BASE_URL="https://gateway.example.com/v1"   # proxy / gateway
+    OPENAI_BASE_URL="http://localhost:11434/v1"
+
     # Optional: Embedding dimension size (defaults to 3072)
     EMBEDDING_DIMENSION="3072"
 
@@ -277,6 +287,7 @@ Configuration is managed through two files:
       openai:
         api_key: '${OPENAI_API_KEY}'  # Optional, uses env var by default
         model: 'text-embedding-3-large'  # Optional, defaults to text-embedding-3-large
+        # base_url: 'http://localhost:11434/v1'  # Optional, override OpenAI API base URL for Ollama / other OpenAI-compatible endpoints. Falls back to OPENAI_BASE_URL env var.
       # For Azure OpenAI, use this instead:
       # azure:
       #   api_key: '${AZURE_OPENAI_KEY}'

doc2vec.ts

@@ -89,15 +89,19 @@ export class Doc2Vec {
         } else {
             const openaiApiKey = embeddingConfig.openai?.api_key || process.env.OPENAI_API_KEY;
             const openaiModel = embeddingConfig.openai?.model || process.env.OPENAI_MODEL || 'text-embedding-3-large';
-
+            const openaiBaseURL = embeddingConfig.openai?.base_url || process.env.OPENAI_BASE_URL;
+
             if (!openaiApiKey) {
                 this.logger.error('OpenAI requires api_key to be configured');
                 process.exit(1);
             }
-
-            this.openai = new OpenAI({ apiKey: openaiApiKey });
+
+            this.openai = new OpenAI({
+                apiKey: openaiApiKey,
+                ...(openaiBaseURL && { baseURL: openaiBaseURL }),
+            });
             this.embeddingModel = openaiModel;
-            this.logger.info(`Using OpenAI with model: ${openaiModel} (${this.embeddingDimension} dimensions)`);
+            this.logger.info(`Using OpenAI with model: ${openaiModel} (${this.embeddingDimension} dimensions)${openaiBaseURL ? ` via ${openaiBaseURL}` : ''}`);
         }
 
         this.contentProcessor = new ContentProcessor(this.logger);

mcp/package.json

@@ -1,6 +1,6 @@
 {
   "name": "sqlite-vec-mcp-server",
-  "version": "2.1.0",
+  "version": "2.1.1",
   "description": "MCP Server for querying documentation with sqlite-vec",
   "main": "build/index.js",
   "type": "module",

mcp/src/index.ts

@@ -34,6 +34,7 @@ const embeddingProvider = process.env.EMBEDDING_PROVIDER || 'openai';
 // OpenAI configuration
 const openAIApiKey = process.env.OPENAI_API_KEY;
 const openAIModel = process.env.OPENAI_MODEL || 'text-embedding-3-large';
+const openAIBaseURL = process.env.OPENAI_BASE_URL;  // Optional: override API base URL for Ollama / other OpenAI-compatible endpoints
 
 // Azure OpenAI configuration
 const azureApiKey = process.env.AZURE_OPENAI_KEY;
@@ -110,6 +111,7 @@ async function createEmbeddings(text: string): Promise<number[]> {
             case 'openai': {
                 const openai = new OpenAI({
                     apiKey: openAIApiKey,
+                    ...(openAIBaseURL && { baseURL: openAIBaseURL }),
                 });
                 const response = await openai.embeddings.create({
                     model: openAIModel,

package.json

@@ -1,6 +1,6 @@
 {
     "name": "doc2vec",
-    "version": "2.10.2",
+    "version": "2.10.3",
     "type": "commonjs",
     "description": "",
     "main": "dist/doc2vec.js",

types.ts

@@ -99,8 +99,9 @@ export interface EmbeddingConfig {
     provider: 'openai' | 'azure';
     dimension?: number;
     openai?: {
-        api_key?: string;  // Can also use OPENAI_API_KEY env var
-        model?: string;    // Default: text-embedding-3-large
+        api_key?: string;   // Can also use OPENAI_API_KEY env var
+        model?: string;     // Default: text-embedding-3-large
+        base_url?: string;  // Override OpenAI API base URL — useful for Ollama or other OpenAI-compatible endpoints. Can also use OPENAI_BASE_URL env var.
     };
     azure?: {
         api_key?: string;        // Can also use AZURE_OPENAI_KEY env var