Update app.py

app.py

@@ -8,20 +8,19 @@ from transformers import AutoTokenizer
 import faiss
 import numpy as np
 import docx
-from groq import Groq
 import PyPDF2
 import requests
-from streamlit_autorefresh import st_autorefresh
 
-# Extract text from PDF with fallback
-# --- Document Loaders ---
+# --- Streamlit Config ---
+st.set_page_config(page_title="Quasa – A Smart WhatsApp Chatbot", layout="wide")
+
+# --- Utility: Extract Text ---
 def extract_text_from_pdf(pdf_path):
     try:
         text = ""
         with open(pdf_path, 'rb') as file:
             pdf_reader = PyPDF2.PdfReader(file)
-            for page_num in range(len(pdf_reader.pages)):
-                page = pdf_reader.pages[page_num]
+            for page in pdf_reader.pages:
                 page_text = page.extract_text()
                 if page_text:
                     text += page_text
@@ -36,6 +35,7 @@ def extract_text_from_docx(docx_path):
     except:
         return ""
 
+# --- Chunking ---
 def chunk_text(text, tokenizer, chunk_size=150, chunk_overlap=30):
     tokens = tokenizer.tokenize(text)
     chunks, start = [], 0
@@ -46,18 +46,16 @@ def chunk_text(text, tokenizer, chunk_size=150, chunk_overlap=30):
         start += chunk_size - chunk_overlap
     return chunks
 
+# --- Retrieve Relevant Chunks ---
 def retrieve_chunks(question, index, embed_model, text_chunks, k=3):
     question_embedding = embed_model.encode([question])[0]
     D, I = index.search(np.array([question_embedding]), k)
     return [text_chunks[i] for i in I[0]]
 
-# Generate answer using Groq API with retries and timeout
+# --- GROQ API Call ---
 def generate_answer_with_groq(question, context, retries=3, delay=2):
     url = "https://api.groq.com/openai/v1/chat/completions"
     api_key = os.environ.get("GROQ_API_KEY")
-    if not api_key:
-        return "⚠️ GROQ_API_KEY not set."
-
     headers = {
         "Authorization": f"Bearer {api_key}",
         "Content-Type": "application/json",
@@ -75,8 +73,7 @@ def generate_answer_with_groq(question, context, retries=3, delay=2):
                 "content": (
                     "You are ToyBot, a friendly and helpful WhatsApp assistant for an online toy shop. "
                     "Your goal is to politely answer customer questions, help them choose the right toys, "
-                    "provide order or delivery information, explain return policies, and guide them through purchases. "
-                    "Always sound warm, helpful, and trustworthy like a professional customer support agent."
+                    "provide order or delivery information, explain return policies, and guide them through purchases."
                 )
             },
             {"role": "user", "content": prompt},
@@ -87,20 +84,16 @@ def generate_answer_with_groq(question, context, retries=3, delay=2):
 
     for attempt in range(retries):
         try:
-            response = requests.post(url, headers=headers, json=payload, timeout=10)
-            response.raise_for_status()
+            response = requests.post(url, headers=headers, json=payload)
             result = response.json()
             return result['choices'][0]['message']['content'].strip()
-        except requests.exceptions.HTTPError as e:
-            if response.status_code == 503 and attempt < retries - 1:
+        except Exception as e:
+            if "503" in str(e) and attempt < retries - 1:
                 time.sleep(delay)
                 continue
-            else:
-                return f"⚠️ Groq API HTTPError: {e}"
-        except Exception as e:
-            return f"⚠️ Groq API Error: {e}"
+            return f"⚠️ Groq API Error: {str(e)}"
 
-# Twilio message fetch and send
+# --- Twilio Helpers ---
 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)
@@ -112,79 +105,84 @@ def fetch_latest_incoming_message(account_sid, auth_token, conversation_sid):
 def send_twilio_message(account_sid, auth_token, conversation_sid, body):
     try:
         client = Client(account_sid, auth_token)
-        message = client.conversations.v1.conversations(conversation_sid).messages.create(author="system", body=body)
+        message = client.conversations.v1.conversations(conversation_sid).messages.create(
+            author="system",
+            body=body
+        )
         return message.sid
     except Exception as e:
         return str(e)
 
-# Streamlit UI
-st.set_page_config(page_title="Quasa – A Smart WhatsApp Chatbot", layout="wide")
-st.title("📱 Quasa – A Smart WhatsApp Chatbot")
-
-if "last_index" not in st.session_state:
-    st.session_state.last_index = -1
-
-account_sid = st.secrets.get("TWILIO_SID")
-auth_token = st.secrets.get("TWILIO_TOKEN")
-GROQ_API_KEY = st.secrets.get("GROQ_API_KEY")
-
-if not all([account_sid, auth_token, GROQ_API_KEY]):
-    st.warning("⚠️ Some secrets not found. Please enter missing credentials below:")
-    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 Conversation SID", value="")
-
-enable_autorefresh = st.checkbox("🔄 Enable Auto-Refresh", value=True)
-interval_seconds = st.selectbox("Refresh Interval (seconds)", options=[5, 10, 15, 30, 60], index=1)
-
-if enable_autorefresh:
-    st_autorefresh(interval=interval_seconds * 1000, key="auto-refresh")
-
-if all([account_sid, auth_token, GROQ_API_KEY, conversation_sid]):
-    os.environ["GROQ_API_KEY"] = GROQ_API_KEY
-
-    @st.cache_data(show_spinner=False)
-    def setup_knowledge_base():
-        folder_path = "docs"
-        all_text = ""
-        try:
-            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).astype('float32'))
-            return index, model, chunks
-        except Exception as e:
-            st.error(f"Error setting up knowledge base: {e}")
-            return None, None, None
-
-    index, embedding_model, text_chunks = setup_knowledge_base()
-    if index is None:
-        st.stop()
-
-    st.success("✅ Knowledge base ready. Monitoring WhatsApp...")
-
-    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_index:
-            st.session_state.last_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 via WhatsApp!")
-            st.markdown(f"### ✨ Answer:\n\n{answer}")
+# --- UI Styling ---
+st.markdown("""
+    <style>
+        .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; }
+    </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)
+
+# --- Credentials ---
+account_sid = st.secrets.get("TWILIO_SID") or st.text_input("🔐 Twilio SID", "")
+auth_token = st.secrets.get("TWILIO_TOKEN") or st.text_input("🔐 Twilio Auth Token", type="password")
+groq_key = st.secrets.get("GROQ_API_KEY") or st.text_input("🔐 GROQ API Key", type="password")
+
+if all([account_sid, auth_token, groq_key]):
+    os.environ["GROQ_API_KEY"] = groq_key
+
+    # Conversation SID Input
+    conversation_sid = st.text_input("💬 Enter Twilio Conversation SID", key="conv_sid")
+
+    if st.button("🔄 Load Conversation"):
+        if not conversation_sid:
+            st.warning("Please enter a valid Conversation SID.")
         else:
-            st.caption("✅ No new message yet. Waiting for refresh...")
+            st.success(f"Conversation SID `{conversation_sid}` loaded!")
+
+            @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 loaded!")
+
+            if "last_processed_index" not in st.session_state:
+                st.session_state.last_processed_index = -1
+
+            if st.button("📲 Check WhatsApp for New Message"):
+                with st.spinner("Checking 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 message 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 to user!")
+                        st.markdown(f"### 🧠 Answer:\n\n{answer}")
+                    else:
+                        st.warning("No new messages found.")
 else:
-    st.warning("❗ Please provide all required credentials and conversation SID.")
+    st.warning("Please enter all required credentials.")