Updated app to use fire base

app.py

@@ -1,32 +1,11 @@
-import os
-import json
 import streamlit as st
-import firebase_admin
-from firebase_admin import credentials, firestore
 import faiss
 import numpy as np
 import pickle
+import json
+import torch
 from sentence_transformers import SentenceTransformer
-from transformers import pipeline
-
-# -----------------------------
-# Firebase Initialization
-# -----------------------------
-@st.cache_resource
-def init_firestore():
-    # Load the service account JSON from the environment variable
-    firebase_creds_json = os.environ.get("FIREBASE_SERVICE_ACCOUNT")
-    if not firebase_creds_json:
-        st.error("Firebase service account credentials not found in environment variables!")
-        return None
-    service_account_info = json.loads(firebase_creds_json)
-    cred = credentials.Certificate(service_account_info)
-    # Initialize the Firebase app only once
-    if not firebase_admin._apps:
-        firebase_admin.initialize_app(cred)
-    return firestore.client()
-
-db = init_firestore()
+from transformers import pipeline, RagTokenizer, RagRetriever, RagSequenceForGeneration
 
 # ========================
 # File Names & Model Names
@@ -65,21 +44,22 @@ def load_curated_qa_pairs():
     try:
         with open(CURATED_QA_FILE, "r", encoding="utf-8") as f:
             return json.load(f)
-    except Exception as e:
-        st.error(f"Error loading curated Q/A pairs: {e}")
+    except:
         return []
 
 # ========================================
 # Chatbot Interface & Conversation Handling
 # ========================================
+
 def display_conversation():
     """Displays conversation history in a structured chat format."""
-    for role, message in st.session_state.conversation_history:
+    for entry in st.session_state.conversation_history:
+        role, message = entry
         with st.chat_message(role):
             st.write(message)
 
 def add_to_conversation(role, message):
-    """Adds a message to the conversation history."""
+    """Adds a message to conversation history."""
     st.session_state.conversation_history.append((role, message))
 
 # Initialize conversation history
@@ -104,25 +84,15 @@ user_query = st.chat_input("Ask a question about the document...")
 if user_query:
     add_to_conversation("user", user_query)
     
-    # Check for a curated Q/A pair match
+    # Check for curated Q/A pair
     answer = None
     for pair in curated_qa_pairs:
         if user_query.lower() in pair["question"].lower():
             answer = pair["answer"]
             break
-
-    # If no curated answer is found, save the question to Firebase and process it.
+    
     if not answer:
-        try:
-            if db is not None:
-                db.collection("llmquestions").add({
-                    "question": user_query,
-                    "timestamp": firestore.SERVER_TIMESTAMP
-                })
-        except Exception as e:
-            st.error(f"Error saving question to Firebase: {e}")
-
-        # Retrieve relevant context from FAISS index
+        # Retrieve relevant context
         query_embedding = embed_model.encode([user_query]).astype("float32")
         distances, indices = index.search(query_embedding, 3)
         pdf_context = "\n".join(chunks[idx] for idx in indices[0])
@@ -132,4 +102,4 @@ if user_query:
         answer = response.get("answer", "I couldn't find an answer to that.")
     
     add_to_conversation("assistant", answer)
-    st.rerun()
+    st.rerun()