src/utils/embeddings.ts

@@ -119,16 +119,22 @@ class EmbeddingsService {
     const apiKey = process.env.AI_EMBEDDINGS_API_KEY;
     const model = process.env.AI_EMBEDDINGS_MODEL;
 
-    if (!endpoint || !apiKey || !model) {
+    if (!endpoint || !model) {
       throw new Error('Missing embeddings API configuration');
     }
 
+    const headers: Record<string, string> = {
+      'Content-Type': 'application/json'
+    };
+
+    // API key is optional for Ollama but required for Mistral/OpenAI
+    if (apiKey) {
+      headers['Authorization'] = `Bearer ${apiKey}`;
+    }
+
     const response = await fetch(endpoint, {
       method: 'POST',
-      headers: {
-        'Content-Type': 'application/json',
-        'Authorization': `Bearer ${apiKey}`
-      },
+      headers,
       body: JSON.stringify({
         model,
         input: contents
@@ -141,9 +147,20 @@ class EmbeddingsService {
     }
 
     const data = await response.json();
+
+    // Detect Ollama format
+    if (Array.isArray(data.embeddings)) {
+      return data.embeddings;
+    }
+
+    // Detect OpenAI/Mistral format
+    if (Array.isArray(data.data)) {
       return data.data.map((item: any) => item.embedding);
     }
 
+    throw new Error('Unknown embeddings API response format');
+  }
+
   private async generateEmbeddings(toolsData: any, version: string): Promise<void> {
     const allItems = [
       ...toolsData.tools.map((tool: any) => ({ ...tool, type: 'tool' })),