Upload app.py with huggingface_hub

app.py

@@ -1,9 +1,4 @@
-"""
-UHC Medical Policy Chatbot — Streamlit Web UI.
-
-Deployed on HuggingFace Spaces. Uses MedEmbed for retrieval from Qdrant Cloud
-and Groq (Llama 3.1 8B) for answer generation.
-"""
+"""Streamlit web interface for the UHC medical policy chatbot."""
 
 import time
 import streamlit as st
@@ -13,18 +8,12 @@ from chatbot.retriever import PolicyRetriever
 from chatbot.llm_groq import GroqClient, GroqError
 from chatbot.prompts import format_context, build_messages, deduplicate_chunks
 
-# ---------------------------------------------------------------------------
-# Page config
-# ---------------------------------------------------------------------------
 st.set_page_config(
     page_title="UHC Policy Chatbot",
     page_icon="🏥",
     layout="centered",
 )
 
-# ---------------------------------------------------------------------------
-# Cached singletons — loaded once, shared across reruns
-# ---------------------------------------------------------------------------
 
 @st.cache_resource(show_spinner=False)
 def load_retriever() -> PolicyRetriever:
@@ -62,18 +51,17 @@ with st.sidebar:
     )
     st.divider()
 
+    tts_enabled = st.toggle("🔊 Read answers aloud", value=False)
+
     if st.button("🗑️ Clear conversation"):
         st.session_state.messages = []
         st.session_state.chunks_history = []
         st.rerun()
 
-    st.caption(
-        "Built for the CombineHealth Technical Assignment. "
-        "Answers are generated from policy documents only."
-    )
+    st.caption("Answers are based on official UHC policy documents only.")
 
 # ---------------------------------------------------------------------------
-# Init session state
+# Session state
 # ---------------------------------------------------------------------------
 if "messages" not in st.session_state:
     st.session_state.messages = []
@@ -92,9 +80,6 @@ except GroqError as e:
     st.error(f"LLM initialization failed: {e}")
     st.stop()
 
-# ---------------------------------------------------------------------------
-# Header
-# ---------------------------------------------------------------------------
 st.title("🏥 UHC Medical Policy Chatbot")
 st.caption(
     "Ask questions about UnitedHealthcare insurance policies. "
@@ -132,7 +117,6 @@ if query := st.chat_input("Ask about UHC medical policies..."):
     with st.chat_message("user"):
         st.markdown(query)
 
-    # -- Retrieve -------------------------------------------------------------
     with st.chat_message("assistant"):
         with st.spinner("Searching policies..."):
             t0 = time.perf_counter()
@@ -166,7 +150,6 @@ if query := st.chat_input("Ask about UHC medical policies..."):
 
         messages = build_messages(query, context, history=history_for_llm)
 
-        # -- Generate -----------------------------------------------------------
         try:
             t1 = time.perf_counter()
             response_text = st.write_stream(llm.chat_stream(messages))
@@ -175,7 +158,6 @@ if query := st.chat_input("Ask about UHC medical policies..."):
             st.error(str(e))
             st.stop()
 
-        # -- Sources -----------------------------------------------------------
         deduped = deduplicate_chunks(chunks)
         with st.expander("📚 Sources", expanded=False):
             for c in deduped:
@@ -188,6 +170,15 @@ if query := st.chat_input("Ask about UHC medical policies..."):
             f"Retrieval: {t_retrieval:.1f}s · Generation: {t_gen:.1f}s"
         )
 
+        if tts_enabled and response_text:
+            with st.spinner("Generating audio..."):
+                try:
+                    from chatbot.tts import synthesize
+                    audio_bytes = synthesize(response_text)
+                    st.audio(audio_bytes, format="audio/wav", autoplay=True)
+                except Exception as e:
+                    st.caption(f"⚠️ TTS unavailable: {e}")
+
     st.session_state.messages.append(
         {"role": "assistant", "content": response_text}
     )