initial commit

app/api/routers/chat.py

@@ -3,7 +3,6 @@ Router for the chat-to-tasks functionality.
 """
 
 import logging
-
 from fastapi import APIRouter, Depends, HTTPException
 from sqlalchemy.orm import Session
 
@@ -30,12 +29,7 @@ async def create_tasks_from_chat(
     """
     Convert natural language chat input into one or more structured task objects.
 
-    Steps:
+    This endpoint now returns internal debug logs in the response for easier debugging.
-    1. Validate the input message length.
-    2. Send the message to the LLM service for task extraction.
-    3. Parse the response into TaskCreate schemas.
-    4. Persist tasks in the database linked to the authenticated user.
-    5. Return the list of created tasks or an error response.
     """
     message = chat_input.message.strip()
     if len(message) < 3:
@@ -45,49 +39,53 @@ async def create_tasks_from_chat(
         )
 
     response = ChatResponse(original_message=message)
+    debug_logs = []  # Collect debug logs here
+
+    def log_debug(msg):
+        debug_logs.append(msg)
+        logger.debug(msg)
 
     try:
-        logger.info(f"Received chat input for task extraction: {message[:50]}...")
+        log_debug(f"Received chat input for task extraction: {message[:50]}...")
 
         # Extract tasks from the LLM service
         llm_tasks = await llm_service.chat_to_tasks(message)
+        log_debug(f"LLM service raw output: {llm_tasks}")
 
         if not llm_tasks:
-            logger.warning("LLM service returned no tasks.")
+            log_debug("LLM service returned no tasks.")
             response.processing_successful = False
             response.error = ChatProcessingError(
                 error_type="parsing_error",
                 error_detail="No tasks could be extracted from your message.",
             )
+            response.debug_logs = debug_logs  # Attach logs to response
             return response
 
         created_tasks = []
 
-        for task_data in llm_tasks:
+        for idx, task_data in enumerate(llm_tasks, 1):
             try:
-                # Map LLM response fields to TaskCreate schema fields
                 task_create_data = {
                     "title": task_data.get("title", "Untitled Task"),
                     "description": task_data.get("description", ""),
                     "priority": task_data.get("priority", "medium").lower(),
                 }
 
-                # Validate and include due_date if present and valid
                 due_date = task_data.get("due_date")
                 if due_date and due_date != "null":
                     task_create_data["due_date"] = due_date
 
-                # Map status field and normalize to internal status naming
                 status = task_data.get("status", "").lower()
                 if status == "pending":
                     task_create_data["status"] = "todo"
                 elif status:
                     task_create_data["status"] = status
 
-                # Validate input data against TaskCreate schema
+                log_debug(f"Task #{idx} data prepared for creation: {task_create_data}")
+
                 task_in = TaskCreate(**task_create_data)
 
-                # Create task with ownership linked to current user
                 db_task = task_crud.task.create_with_owner(
                     db=db,
                     obj_in=task_in,
@@ -95,9 +93,11 @@ async def create_tasks_from_chat(
                 )
 
                 created_tasks.append(TaskRead.model_validate(db_task))
+                log_debug(f"Task #{idx} created successfully with ID {db_task.id}")
 
             except Exception as task_exc:
-                logger.error(f"Failed to create task from LLM data: {task_exc}")
+                err_msg = f"Failed to create task #{idx} from LLM data: {task_exc}. Data: {task_data}"
+                log_debug(err_msg)
                 # Continue processing remaining tasks even if one fails
 
         if not created_tasks:
@@ -108,14 +108,18 @@ async def create_tasks_from_chat(
             )
         else:
             response.tasks = created_tasks
+            response.processing_successful = True
 
+        response.debug_logs = debug_logs
         return response
 
     except Exception as exc:
-        logger.exception(f"Unexpected error in chat-to-tasks endpoint: {exc}")
+        err_msg = f"Unexpected error in chat-to-tasks endpoint: {exc}"
+        log_debug(err_msg)
         response.processing_successful = False
         response.error = ChatProcessingError(
             error_type="processing_error",
             error_detail=f"An error occurred while processing your request: {str(exc)}",
         )
+        response.debug_logs = debug_logs
         return response

app/schemas/chat.py

@@ -41,4 +41,5 @@ class ChatResponse(BaseModel):
     error: Optional[ChatProcessingError] = Field(
         default=None,
         description="Error details if processing was not successful",
-    )
+    )
+    debug_logs: Optional[List[str]] = None  # <-- Add this field