Update app.py

app.py

@@ -99,8 +99,17 @@ def generate_answer_with_groq(question, context, retries=3, delay=2):
             else:
                 return f"⚠️ Groq API Error: {str(e)}"
 
-
 # --- Twilio Chat Handlers ---
+def fetch_latest_conversation_sid(account_sid, auth_token):
+    try:
+        client = Client(account_sid, auth_token)
+        conversations = client.conversations.v1.conversations.list(limit=1)
+        if conversations:
+            return conversations[0].sid
+    except Exception as e:
+        st.error(f"⚠️ Could not fetch conversation SID: {e}")
+    return None
+
 def fetch_latest_incoming_message(account_sid, auth_token, conversation_sid):
     client = Client(account_sid, auth_token)
     messages = client.conversations.v1.conversations(conversation_sid).messages.list(limit=10)
@@ -120,88 +129,78 @@ def send_twilio_message(account_sid, auth_token, conversation_sid, body):
 # --- Streamlit UI ---
 st.set_page_config(page_title="Quasa – A Smart WhatsApp Chatbot", layout="wide")
 
-# Styling
 st.markdown("""
     <style>
-        .big-font {
-            font-size: 28px !important;
-            font-weight: bold;
-        }
-        .small-font {
-            font-size: 16px !important;
-            color: #555;
-        }
+        .big-font { font-size: 28px !important; font-weight: bold; }
+        .small-font { font-size: 16px; color: #555; }
         .stButton > button {
-            background-color: #0066CC;
-            color: white;
-            padding: 0.5em 1em;
-            border-radius: 8px;
-            font-size: 18px;
-        }
-        .stTextInput > div > input {
-            font-size: 16px;
+            background-color: #0066CC; color: white;
+            padding: 0.5em 1em; border-radius: 8px; font-size: 18px;
         }
+        .stTextInput > div > input { font-size: 16px; }
     </style>
 """, unsafe_allow_html=True)
 
 st.markdown('<div class="big-font">📱 Quasa – A Smart WhatsApp Chatbot</div>', unsafe_allow_html=True)
 st.markdown('<div class="small-font">Talk to your documents using WhatsApp. Powered by Groq, Twilio, and RAG.</div>', unsafe_allow_html=True)
 
-# Load secrets
+# Load secrets or fallback
 account_sid = st.secrets.get("TWILIO_SID")
 auth_token = st.secrets.get("TWILIO_TOKEN")
 GROQ_API_KEY = st.secrets.get("GROQ_API_KEY")
 
-# Allow user input fallback
 if not all([account_sid, auth_token, GROQ_API_KEY]):
     st.warning("⚠️ Some secrets are missing. Please provide them manually:")
     account_sid = st.text_input("Twilio SID", value=account_sid or "")
     auth_token = st.text_input("Twilio Auth Token", type="password", value=auth_token or "")
     GROQ_API_KEY = st.text_input("GROQ API Key", type="password", value=GROQ_API_KEY or "")
 
-conversation_sid = st.text_input("Enter Twilio Conversation SID", value="")
-
-if all([account_sid, auth_token, GROQ_API_KEY, conversation_sid]):
+if all([account_sid, auth_token, GROQ_API_KEY]):
     os.environ["GROQ_API_KEY"] = GROQ_API_KEY
 
-    @st.cache_resource
-    def setup_knowledge_base():
-        folder_path = "docs"
-        all_text = ""
-        for file in os.listdir(folder_path):
-            if file.endswith(".pdf"):
-                all_text += extract_text_from_pdf(os.path.join(folder_path, file)) + "\n"
-            elif file.endswith((".docx", ".doc")):
-                all_text += extract_text_from_docx(os.path.join(folder_path, file)) + "\n"
-        tokenizer = AutoTokenizer.from_pretrained('bert-base-uncased')
-        chunks = chunk_text(all_text, tokenizer)
-        model = SentenceTransformer('all-mpnet-base-v2')
-        embeddings = model.encode(chunks)
-        dim = embeddings[0].shape[0]
-        index = faiss.IndexFlatL2(dim)
-        index.add(np.array(embeddings))
-        return index, model, chunks
-
-    index, embedding_model, text_chunks = setup_knowledge_base()
-
-    st.success("✅ Knowledge base ready. Monitoring WhatsApp messages...")
-
-    if "last_processed_index" not in st.session_state:
-        st.session_state.last_processed_index = -1
-
-    with st.spinner("Checking for new WhatsApp messages..."):
-        question, sender, msg_index = fetch_latest_incoming_message(account_sid, auth_token, conversation_sid)
-
-        if question and msg_index != st.session_state.last_processed_index:
-            st.session_state.last_processed_index = msg_index
-            st.info(f"📥 New question from **{sender}**:\n\n> {question}")
-            relevant_chunks = retrieve_chunks(question, index, embedding_model, text_chunks)
-            context = "\n\n".join(relevant_chunks)
-            answer = generate_answer_with_groq(question, context)
-            send_twilio_message(account_sid, auth_token, conversation_sid, answer)
-            st.success("📤 Answer sent back to user on WhatsApp!")
-            st.markdown(f"### ✨ Answer:\n\n{answer}")
-        else:
-            st.warning("No new messages found.")
+    conversation_sid = fetch_latest_conversation_sid(account_sid, auth_token)
+
+    if conversation_sid:
+        @st.cache_resource
+        def setup_knowledge_base():
+            folder_path = "docs"
+            all_text = ""
+            for file in os.listdir(folder_path):
+                if file.endswith(".pdf"):
+                    all_text += extract_text_from_pdf(os.path.join(folder_path, file)) + "\n"
+                elif file.endswith((".docx", ".doc")):
+                    all_text += extract_text_from_docx(os.path.join(folder_path, file)) + "\n"
+            tokenizer = AutoTokenizer.from_pretrained('bert-base-uncased')
+            chunks = chunk_text(all_text, tokenizer)
+            model = SentenceTransformer('all-mpnet-base-v2')
+            embeddings = model.encode(chunks)
+            dim = embeddings[0].shape[0]
+            index = faiss.IndexFlatL2(dim)
+            index.add(np.array(embeddings))
+            return index, model, chunks
+
+        index, embedding_model, text_chunks = setup_knowledge_base()
+
+        st.success(f"✅ Knowledge base ready. Monitoring WhatsApp messages for conversation: `{conversation_sid}`")
+
+        if "last_processed_index" not in st.session_state:
+            st.session_state.last_processed_index = -1
+
+        with st.spinner("Checking for new WhatsApp messages..."):
+            question, sender, msg_index = fetch_latest_incoming_message(account_sid, auth_token, conversation_sid)
+
+            if question and msg_index != st.session_state.last_processed_index:
+                st.session_state.last_processed_index = msg_index
+                st.info(f"📥 New question from **{sender}**:\n\n> {question}")
+                relevant_chunks = retrieve_chunks(question, index, embedding_model, text_chunks)
+                context = "\n\n".join(relevant_chunks)
+                answer = generate_answer_with_groq(question, context)
+                send_twilio_message(account_sid, auth_token, conversation_sid, answer)
+                st.success("📤 Answer sent back to user on WhatsApp!")
+                st.markdown(f"### ✨ Answer:\n\n{answer}")
+            else:
+                st.warning("No new messages found.")
+    else:
+        st.warning("❗ No active conversation found.")
 else:
-    st.warning("❗ Please provide all required credentials and conversation SID.")
+    st.warning("❗ Please provide all required credentials.")