Hola

controller.py

@@ -396,33 +396,33 @@ async def csv_chat(request: Dict, authorization: str = Header(None)):
         
         # Handle report generation with Cerebras first, then Gemini fallback
         if generate_report is True:
-            # logger.info("Starting report generation process...")
+            logger.info("Starting report generation process...")
             
-            # # Try Cerebras first for report generation
-            # logger.info("Attempting report generation with Cerebras...")
-            # try:
-            #     report_files = await generate_csv_report_cerebras(csv_url, query, chat_id, conversation_history)
-            #     if report_files is not None and (report_files.files.csv_files or report_files.files.image_files):
-            #         logger.info(f"Cerebras report generation successful: {len(report_files.files.csv_files)} CSV files, {len(report_files.files.image_files)} image files")
-            #         return {"answer": jsonable_encoder(report_files)}
-            #     else:
-            #         logger.warning("Cerebras report generation returned empty or None result")
-            # except Exception as cerebras_error:
-            #     logger.error(f"Cerebras report generation failed: {str(cerebras_error)}")
+            # Try Cerebras first for report generation
+            logger.info("Attempting report generation with Cerebras...")
+            try:
+                report_files = await generate_csv_report_cerebras(csv_url, query, chat_id, conversation_history)
+                if report_files is not None and (report_files.files.csv_files or report_files.files.image_files):
+                    logger.info(f"Cerebras report generation successful: {len(report_files.files.csv_files)} CSV files, {len(report_files.files.image_files)} image files")
+                    return {"answer": jsonable_encoder(report_files)}
+                else:
+                    logger.warning("Cerebras report generation returned empty or None result")
+            except Exception as cerebras_error:
+                logger.error(f"Cerebras report generation failed: {str(cerebras_error)}")
             
-            # # Fallback to Gemini for report generation
-            # logger.info("Falling back to Gemini for report generation...")
-            # try:
-            #     report_files = await generate_csv_report_gemini(csv_url, query, chat_id, conversation_history)
-            #     if report_files is not None and (report_files.files.csv_files or report_files.files.image_files):
-            #         logger.info(f"Gemini report generation successful: {len(report_files.files.csv_files)} CSV files, {len(report_files.files.image_files)} image files")
-            #         return {"answer": jsonable_encoder(report_files)}
-            #     else:
-            #         logger.warning("Gemini report generation returned empty or None result")
-            # except Exception as gemini_error:
-            #     logger.error(f"Gemini report generation failed: {str(gemini_error)}")
+            # Fallback to Gemini for report generation
+            logger.info("Falling back to Gemini for report generation...")
+            try:
+                report_files = await generate_csv_report_gemini(csv_url, query, chat_id, conversation_history)
+                if report_files is not None and (report_files.files.csv_files or report_files.files.image_files):
+                    logger.info(f"Gemini report generation successful: {len(report_files.files.csv_files)} CSV files, {len(report_files.files.image_files)} image files")
+                    return {"answer": jsonable_encoder(report_files)}
+                else:
+                    logger.warning("Gemini report generation returned empty or None result")
+            except Exception as gemini_error:
+                logger.error(f"Gemini report generation failed: {str(gemini_error)}")
             
-            # logger.error("Both Cerebras and Gemini report generation failed")
+            logger.error("Both Cerebras and Gemini report generation failed")
            
            # Gemini failed, last resort Groq Report Generation
             logger.info("Attempting report generation with Groq as last resort...")

groq_instance_provider.py

@@ -18,7 +18,7 @@ class InstanceProvider:
     def _initialize_instances(self):
         """Load all API keys and create instances"""
         api_keys = os.getenv("GROQ_API_KEYS", "").split(",")
-        base_url = os.getenv("GROQ_BASE_URL")
+        base_url = os.getenv("GROQ_OPENAI_URL")
         model_name = os.getenv("GROQ_LLM_MODEL")
         
         for key in api_keys:

groq_report_generator.py

@@ -25,7 +25,7 @@ load_dotenv()
 
 API_KEYS = os.getenv("GROQ_API_KEYS", "").split(",")[::-1]
 MODEL_NAME = os.getenv("GROQ_LLM_MODEL")  # Kimi model
-GROQ_BASE_URL = os.getenv("GROQ_BASE_URL")
+GROQ_OPENAI_URL = os.getenv("GROQ_OPENAI_URL")
 
 class FileProps(BaseModel):
     fileName: str
@@ -300,7 +300,7 @@ def groq_llm_chat(csv_url: str, query: str, conversation_history: List[Dict[str,
         df = pd.read_csv(csv_url)
         agent = RethinkAgent(df=df, conversation=conversation_history, model_name=MODEL_NAME)
         
-        if not agent.initialize_model(API_KEYS, GROQ_BASE_URL):
+        if not agent.initialize_model(API_KEYS, GROQ_OPENAI_URL):
             return {"error": "API configuration failed"}
         
         result = agent.execute_query(query)