only groq

controller.py

@@ -342,25 +342,25 @@ async def csv_chat(request: Dict, authorization: str = Header(None)):
         generate_report = request.get("generate_report")
         chat_id = request.get("chat_id")
         
-        if generate_report is True:
-            report_files = await generate_csv_report(csv_url, query, chat_id)
-            if report_files is not None:
-                return {"answer": jsonable_encoder(report_files)}
-
-        if if_initial_chat_question(query):
-            answer = await asyncio.to_thread(
-                langchain_csv_chat, decoded_url, query, False
-            )
-            logger.info("langchain_answer:", answer)
-            return {"answer": jsonable_encoder(answer)}
+        # if generate_report is True:
+        #     report_files = await generate_csv_report(csv_url, query, chat_id)
+        #     if report_files is not None:
+        #         return {"answer": jsonable_encoder(report_files)}
+
+        # if if_initial_chat_question(query):
+        #     answer = await asyncio.to_thread(
+        #         langchain_csv_chat, decoded_url, query, False
+        #     )
+        #     logger.info("langchain_answer:", answer)
+        #     return {"answer": jsonable_encoder(answer)}
         
-        # Orchestrate the execution
-        if detailed_answer is True:
-           orchestrator_answer = await asyncio.to_thread(
-            csv_orchestrator_chat, decoded_url, query, conversation_history, chat_id
-           )
-           if orchestrator_answer is not None:
-              return {"answer": jsonable_encoder(orchestrator_answer)}
+        # # Orchestrate the execution
+        # if detailed_answer is True:
+        #    orchestrator_answer = await asyncio.to_thread(
+        #     csv_orchestrator_chat, decoded_url, query, conversation_history, chat_id
+        #    )
+        #    if orchestrator_answer is not None:
+        #       return {"answer": jsonable_encoder(orchestrator_answer)}
 
         # Process with groq_chat first
         groq_answer = await asyncio.to_thread(groq_chat, decoded_url, query)
@@ -369,13 +369,13 @@ async def csv_chat(request: Dict, authorization: str = Header(None)):
         if process_answer(groq_answer) == "Empty response received.":
             return {"answer": "Sorry, I couldn't find relevant data..."}
 
-        if process_answer(groq_answer):
-            lang_answer = await asyncio.to_thread(
-                langchain_csv_chat, decoded_url, query, False
-            )
-            if process_answer(lang_answer):
-                return {"answer": "error"}
-            return {"answer": jsonable_encoder(lang_answer)}
+        # if process_answer(groq_answer):
+        #     lang_answer = await asyncio.to_thread(
+        #         langchain_csv_chat, decoded_url, query, False
+        #     )
+        #     if process_answer(lang_answer):
+        #         return {"answer": "error"}
+        #     return {"answer": jsonable_encoder(lang_answer)}
 
         return {"answer": jsonable_encoder(groq_answer)}
 
@@ -584,35 +584,35 @@ async def csv_chart(request: dict, authorization: str = Header(None)):
         generate_report = request.get("generate_report", False)
         chat_id = request.get("chat_id", "")
         
-        if generate_report is True:
-            report_files = await generate_csv_report(csv_url, query, chat_id)
-            if report_files is not None:
-                return {"orchestrator_response": jsonable_encoder(report_files)}
+        # if generate_report is True:
+        #     report_files = await generate_csv_report(csv_url, query, chat_id)
+        #     if report_files is not None:
+        #         return {"orchestrator_response": jsonable_encoder(report_files)}
 
         loop = asyncio.get_running_loop()
-        # First, try the langchain-based method if the question qualifies
-        if if_initial_chart_question(query):
-            langchain_result = await loop.run_in_executor(
-                process_executor, langchain_csv_chart, csv_url, query, True
-            )
-            logger.info("Langchain chart result:", langchain_result)
-            if isinstance(langchain_result, list) and len(langchain_result) > 0:
-                unique_file_name =f'{str(uuid.uuid4())}.png'
-                logger.info("Uploading the chart to supabase...")
-                image_public_url = await upload_file_to_supabase(f"{langchain_result[0]}", unique_file_name, chat_id=chat_id)
-                logger.info("Image uploaded to Supabase and Image URL is... ", {image_public_url})
-                os.remove(langchain_result[0])
-                return {"image_url": image_public_url}
-               # return FileResponse(langchain_result[0], media_type="image/png")
+        # # First, try the langchain-based method if the question qualifies
+        # if if_initial_chart_question(query):
+        #     langchain_result = await loop.run_in_executor(
+        #         process_executor, langchain_csv_chart, csv_url, query, True
+        #     )
+        #     logger.info("Langchain chart result:", langchain_result)
+        #     if isinstance(langchain_result, list) and len(langchain_result) > 0:
+        #         unique_file_name =f'{str(uuid.uuid4())}.png'
+        #         logger.info("Uploading the chart to supabase...")
+        #         image_public_url = await upload_file_to_supabase(f"{langchain_result[0]}", unique_file_name, chat_id=chat_id)
+        #         logger.info("Image uploaded to Supabase and Image URL is... ", {image_public_url})
+        #         os.remove(langchain_result[0])
+        #         return {"image_url": image_public_url}
+        #        # return FileResponse(langchain_result[0], media_type="image/png")
                
-        # Use orchestrator to handle the user's chart query first
-        if detailed_answer is True:
-           orchestrator_answer = await asyncio.to_thread(
-             csv_orchestrator_chat, csv_url, query, conversation_history, chat_id
-           )
+        # # Use orchestrator to handle the user's chart query first
+        # if detailed_answer is True:
+        #    orchestrator_answer = await asyncio.to_thread(
+        #      csv_orchestrator_chat, csv_url, query, conversation_history, chat_id
+        #    )
         
-           if orchestrator_answer is not None:
-             return {"orchestrator_response": jsonable_encoder(orchestrator_answer)}
+        #    if orchestrator_answer is not None:
+        #      return {"orchestrator_response": jsonable_encoder(orchestrator_answer)}
         
         # Next, try the groq-based method
         groq_result = await loop.run_in_executor(
@@ -629,18 +629,18 @@ async def csv_chart(request: dict, authorization: str = Header(None)):
             # return FileResponse(groq_result, media_type="image/png")
           
         # Fallback: try langchain-based again
-        logger.error("Groq chart generation failed, trying langchain....")
-        langchain_paths = await loop.run_in_executor(
-            process_executor, langchain_csv_chart, csv_url, query, True
-        )
-        logger.info("Fallback langchain chart result:", langchain_paths)
-        if isinstance(langchain_paths, list) and len(langchain_paths) > 0:
-           unique_file_name =f'{str(uuid.uuid4())}.png'
-           logger.info("Uploading the chart to supabase...")
-           image_public_url = await upload_file_to_supabase(f"{langchain_paths[0]}", unique_file_name, chat_id=chat_id)
-           logger.info("Image uploaded to Supabase and Image URL is... ", {image_public_url})
-           os.remove(langchain_paths[0])
-           return {"image_url": image_public_url}
+        # logger.error("Groq chart generation failed, trying langchain....")
+        # langchain_paths = await loop.run_in_executor(
+        #     process_executor, langchain_csv_chart, csv_url, query, True
+        # )
+        # logger.info("Fallback langchain chart result:", langchain_paths)
+        # if isinstance(langchain_paths, list) and len(langchain_paths) > 0:
+        #    unique_file_name =f'{str(uuid.uuid4())}.png'
+        #    logger.info("Uploading the chart to supabase...")
+        #    image_public_url = await upload_file_to_supabase(f"{langchain_paths[0]}", unique_file_name, chat_id=chat_id)
+        #    logger.info("Image uploaded to Supabase and Image URL is... ", {image_public_url})
+        #    os.remove(langchain_paths[0])
+        #    return {"image_url": image_public_url}
            # return FileResponse(langchain_paths[0], media_type="image/png")
         else:
            logger.error("All chart generation methods failed")