Final application code deployment. Ensures all functionalities, including correct SYSTEM_PROMPT usage, Firestore conversation saving, and returning conversation ID in API response.

app.py

@@ -103,39 +103,17 @@ class QueryRequest(BaseModel):
 async def compassia_endpoint(request: QueryRequest):
     """
     Answers a question about the indexed PDF documents using RAG, with conversational memory.
-    If `conversation_id` is not provided, a new one will be generated and returned.
+    If `conversation_id` is not provided, a new one will be generated and returned in the response.
     """
     try:
-        # The rag_system now holds the correct firestore_db_instance internally.
-        # The answer_question method handles generating a new conversation_id if needed.
-        answer = rag_system.answer_question(request.question, conversation_id=request.conversation_id)
+        # Call answer_question which now returns a tuple (answer_text, conversation_id)
+        answer_text, final_conversation_id = rag_system.answer_question(
+            request.question,
+            conversation_id=request.conversation_id
+        )
         
-        # When answer_question generates an ID, it needs to be returned to the client
-        # so the client can use it for subsequent turns in the same conversation.
-        # Since answer_question now internally generates/uses the ID,
-        # we need to ensure the final response includes it.
-        # The easiest way is to modify answer_question to return a tuple (answer_text, conv_id).
-        # For simplicity now, we assume the initial conversation_id passed in is the one used,
-        # or if it was None, that a new one was generated and saved, and we don't need to return it here.
-        # If the client needs the *newly generated* ID, answer_question would need to return it.
-        
-        # For a production API, if conversation_id is initially None and gets generated,
-        # answer_question needs to return the *generated* ID.
-        # For now, if request.conversation_id was None, the saving still works internally.
-        # If the client needs the *new* ID, let's adjust the return.
-
-        # To return the generated ID:
-        # We need to make `answer_question` return the `conversation_id` it used.
-        # (This requires a small change to `compassia.py`'s `answer_question` return signature)
-        # For now, let's assume if it was None, the client is okay not getting it back in the first call.
-        # If the client *needs* the auto-generated ID back, the API design should support it.
-        
-        # Let's adjust compassia.py to return (answer, conversation_id)
-        # and then use it here. This ensures the client knows the ID.
-        
-        return {"answer": answer, "conversation_id": request.conversation_id} # This was the previous behavior
-        # Re-evaluating: The simplest is to ensure answer_question in compassia.py returns the *final* conversation_id used.
-        # And then this endpoint returns it.
+        # Return both the answer and the (potentially new) conversation_id to the client
+        return {"answer": answer_text, "conversation_id": final_conversation_id}
 
     except Exception as e:
         print(f"Error processing /compassia/ request: {e}")

src/compassia.py

@@ -38,8 +38,7 @@ from config import (
     FIREBASE_CONFIG_BASE64 # Kept here only for local testing fallback in __main__
 )
 from pdf_processing import extract_text_from_pdf, chunk_text
-from prompt import SYSTEM_PROMPT
-
+from prompt import SYSTEM_PROMPT # <--- CORRECTLY IMPORTING SYSTEM_PROMPT
 
 # --- Global Firebase Firestore Client ---
 # This global is primarily for __main__ (local testing) execution.
@@ -341,8 +340,8 @@ class DocumentRAG:
         else:
             print("Warning: No relevant context found. Answering based on general knowledge or indicating lack of information.")
 
-        # --- Handle Conversational Memory ---
-        messages = [{"role": "system", "content": SYSTEM_PROMPT}]
+        # --- Use the imported SYSTEM_PROMPT from prompt.py ---
+        messages = [{"role": "system", "content": SYSTEM_PROMPT}] # Use the imported SYSTEM_PROMPT
 
         # Use the (possibly newly generated) conversation_id
         history = self.get_conversation_history(conversation_id)