Update app/api/v1/chat.py

app/api/v1/chat.py

@@ -109,13 +109,38 @@ async def chat_with_repository(
                 success=False
             )
         
-        logger.info(f"✅ Found {len(similar_chunks)} relevant code chunks")
+        logger.info(f"✅ Found {len(similar_chunks)} relevant chunk identifiers from Pinecone")
         
-        # Generate AI response
-        logger.info(f"🤖 Generating AI response with Gemini...")
+        # Fetch full content from PostgreSQL
+        logger.info(f"📖 Fetching full code content from PostgreSQL...")
+        from app.models.code_file import CodeFile
+        
+        full_chunks = []
+        for chunk_meta in similar_chunks:
+            # Query database for full content
+            code_file = db.query(CodeFile).filter(
+                CodeFile.repository_id == request.repository_id,
+                CodeFile.file_path == chunk_meta['file_path'],
+                CodeFile.chunk_index == chunk_meta['chunk_index']
+            ).first()
+            
+            if code_file:
+                full_chunks.append({
+                    'file_path': code_file.file_path,
+                    'content': code_file.full_content,  # FULL CONTENT from PostgreSQL!
+                    'start_line': code_file.start_line,
+                    'end_line': code_file.end_line,
+                    'chunk_type': code_file.chunk_type,
+                    'similarity': chunk_meta['similarity']
+                })
+        
+        logger.info(f"✅ Retrieved {len(full_chunks)} complete code chunks from database")
+        
+        # Generate AI response with FULL content
+        logger.info(f"🤖 Generating AI response with Gemini using complete code...")
         ai_response = await chat_service.generate_response(
             query=request.query,
-            code_chunks=similar_chunks,
+            code_chunks=full_chunks,  # Use full_chunks instead of similar_chunks
             repository_name=repository.name
         )
         
@@ -166,7 +191,7 @@ async def chat_with_repository(
             response=ai_response['response'],
             sources=ai_response['sources'],
             repository_name=repository.name,
-            context_chunks_used=len(similar_chunks),
+            context_chunks_used=len(full_chunks),  # Use full_chunks count
             model_used=ai_response['model_used'],
             success=ai_response['success']
         )