Merge pull request 'dev' (#5) from dev into main

Reviewed-on: #5

app.py

@@ -1,6 +1,6 @@
 import os
 from typing import Optional
-from fastapi import FastAPI, HTTPException, Security, Depends
+from fastapi import FastAPI, HTTPException, Security, Depends, Request
 from fastapi.security import APIKeyHeader
 from fastapi.middleware.cors import CORSMiddleware
 from fastapi.responses import JSONResponse
@@ -27,9 +27,23 @@ import os
 from PyPDF2 import PdfReader
 from config import QUIZ_TYPES
 from config import Config
+import logging
+import time
 # Load environment variables
 load_dotenv()
-API_KEY = os.getenv("API_KEY_ACCESS")
+from config import Config
+API_KEY = Config.API_KEY_ACCESS
+
+# Configure logging
+logging.basicConfig(
+    level=logging.INFO,
+    format='%(asctime)s - %(name)s - %(levelname)s - %(message)s'
+)
+logger = logging.getLogger(__name__)
+
+# Also configure uvicorn logger
+uvicorn_logger = logging.getLogger("uvicorn.access")
+uvicorn_logger.setLevel(logging.INFO)
 
 base_path = os.path.join("data", "config_files")
 QUESTIONS_PATH = os.path.join(base_path, "questions.json")
@@ -46,6 +60,40 @@ app = FastAPI(
     version="1.0.0"
 )
 
+# Add request logging middleware
+@app.middleware("http")
+async def log_requests(request: Request, call_next):
+    start_time = time.time()
+
+    # Log incoming request (using both logger and print for visibility)
+    log_msg = f"🔥 INCOMING REQUEST: {request.method} {request.url}"
+    logger.info(log_msg)
+    print(log_msg)
+
+  
+
+    # Get request body for POST requests
+    if request.method == "POST":
+        body = await request.body()
+        body_msg = f"🔥 Request Body: {body.decode('utf-8') if body else 'Empty'}"
+        logger.info(body_msg)
+        print(body_msg)
+
+        # Re-create request with body for downstream processing
+        async def receive():
+            return {"type": "http.request", "body": body}
+        request._receive = receive
+
+    response = await call_next(request)
+
+    # Log response
+    process_time = time.time() - start_time
+    response_msg = f"🔥 RESPONSE: {response.status_code} - Time: {process_time:.4f}s"
+    logger.info(response_msg)
+    print(response_msg)
+
+    return response
+
 # Add CORS middleware
 app.add_middleware(
     CORSMiddleware,
@@ -288,7 +336,7 @@ async def generate_pdf_endpoint(
         if request.form_id:
             print(f"Fetching form response for form_id: {request.form_id}")  # Debugging print
             try:
-                x_api_key = os.getenv("BACKEND_XAPI_KEY")
+                x_api_key = Config.BACKEND_XAPI_KEY
                 url = f"{backend_base_url}/v3/api/custom/theme-document/answer/{request.form_id}?x-project={x_api_key}"
                 result = requests.get(url)
                 result.raise_for_status()  # Ensure we raise an error for bad responses

src/llm.py

@@ -62,6 +62,8 @@ def setup_prompt_template(theme: int, resume: str,full_history=None,form_respons
         ("system", chat_prompt(theme, resume,full_history,form_response,generate_theme)),
         MessagesPlaceholder(variable_name="messages")
     ])
+
+
 def fetch_conversation_history(conversation_id: str) -> List[Message]:
     """
     Fetch conversation history from the API using the conversation ID.
@@ -74,18 +76,54 @@ def fetch_conversation_history(conversation_id: str) -> List[Message]:
         response = requests.get(url)
         response.raise_for_status()  # Raise an error for bad responses
         data = response.json()["data"]  # First JSON parse
-        data = json.loads(json.loads(data))
+
+        if isinstance(data, str):
+            print("Data is a string, parsing as JSON...")
+            data = json.loads(data)
+           
+
         # Parse the API response into Message objects
         messages = []
+        
+        # Check if data exists and is a list
+        if data and isinstance(data, list):
             for item in data:
+               
+                
+                # Check if item is a dictionary
+                if isinstance(item, dict):
                     role = item.get("role", "unknown")
                     content = item.get("content", "")
                     timestamp = datetime.now().isoformat()  # Use current timestamp if not provided
                     messages.append(Message(role=role, content=content))
+                elif isinstance(item, str):
+                    # If item is a string, it might be JSON that needs parsing
+                    try:
+                        parsed_item = json.loads(item)
+                        if isinstance(parsed_item, dict):
+                            role = parsed_item.get("role", "unknown")
+                            content = parsed_item.get("content", "")
+                            messages.append(Message(role=role, content=content))
+                        else:
+                            print(f"Parsed item is not a dict: {parsed_item}")
+                    except json.JSONDecodeError as json_err:
+                        print(f"Failed to parse JSON string: {item}, error: {json_err}")
+                else:
+                    print(f"Unexpected item type: {type(item)} for item: {item}")
+        else:
+            print(f"No data or data is not a list. Data: {data}")
+            
         return messages
+        
     except requests.RequestException as e:
         print(f"Error fetching conversation history: {e}")
         return []
+    except KeyError as e:
+        print(f"Expected key not found in response: {e}")
+        return []
+    except Exception as e:
+        print(f"Unexpected error: {e}")
+        return []
 
 
 def convert_to_langchain_messages(messages: List[Message]) -> List[HumanMessage | AIMessage]:
@@ -131,6 +169,8 @@ def ai_chat(query: str, conversation_id: str, theme_id: int, resume: str, full_h
     # Fetch conversation history from the API
     history = fetch_conversation_history(conversation_id)
 
+    print(history)
+    
     config = {"configurable": {"thread_id": conversation_id}}
     language = "English"