added csv-code executor

controller.py

@@ -14,7 +14,7 @@ import pandas as pd
 from pandasai import SmartDataframe
 from langchain_groq.chat_models import ChatGroq
 from dotenv import load_dotenv
-from pydantic import BaseModel, Field
+from pydantic import BaseModel, Field, ValidationError
 from csv_service import clean_data, extract_chart_filenames, generate_csv_data, get_csv_basic_info
 from urllib.parse import unquote
 from langchain_groq import ChatGroq
@@ -212,24 +212,37 @@ class ExecutionRequest(BaseModel):
     response_type: Literal["casual", "data_analysis", "visualization", "mixed"]
     codeExecutionPayload: CsvChatResult
 
+
 @app.post("/api/code_execution_csv")
 async def code_execution_csv(
-    request: ExecutionRequest,
+    request_data: dict,  # Change from ExecutionRequest to dict to see raw input
     authorization: Optional[str] = Header(None)
 ):
+    # Auth check remains the same
     expected_token = os.environ.get("AUTH_TOKEN")
     if not authorization or not expected_token or authorization.replace("Bearer ", "") != expected_token:
         raise HTTPException(status_code=401, detail="Unauthorized")
 
     try:
+        # First log the incoming request data
+        print("Incoming request data:", request_data)
+        
+        # Then validate
+        try:
+            request = ExecutionRequest(**request_data)
+        except ValidationError as e:
+            print("Validation error:", e.json())
+            raise HTTPException(status_code=422, detail=e.errors())
+            
+        # Rest of your processing logic...
         decoded_url = unquote(request.csv_url)
         df = clean_data(decoded_url)
         executor = PythonExecutor(df)
-
         formatted_output = await executor.process_response(request.codeExecutionPayload, request.chat_id)
         return {"answer": formatted_output}
 
     except Exception as e:
+        print("Processing error:", str(e))
         return {"error": "Failed to execute request", "message": str(e)}