Update frontend.py

frontend.py

@@ -1,7 +1,6 @@
 import streamlit as st
 import requests
 import pandas as pd
-import azure.cognitiveservices.speech as speechsdk
 import tempfile
 import os
 import plotly.express as px
@@ -57,48 +56,6 @@ with st.sidebar:
     use_aspects = st.checkbox("🔍 Detect Pain Points")
     use_explain_bulk = st.checkbox("🧠 Generate PM Insight (Bulk)")
     verbosity = st.radio("🗣️ Response Style", ["Brief", "Detailed"])
-    voice_lang = st.selectbox("🔈 Voice Language", ["en", "fr", "es", "de", "hi", "zh"])
-
-# Text-to-Speech
-# Setup usage tracking
-if "tts_usage_count" not in st.session_state:
-    st.session_state.tts_usage_count = 0
-if "enable_audio" not in st.session_state:
-    st.session_state.enable_audio = False
-
-# Azure TTS function
-def azure_speak(text, lang='en-US'):
-    import os
-    if "HF_SPACE_ID" in os.environ:
-        st.warning("Azure TTS is not supported on Hugging Face Spaces. Using fallback TTS.")
-        return None
-
-    if st.session_state.tts_usage_count > 20:
-        st.warning("🔇 TTS usage limit reached.")
-        return None
-
-    try:
-        import azure.cognitiveservices.speech as speechsdk
-        speech_config = speechsdk.SpeechConfig(
-            subscription=st.secrets["AZURE_SPEECH_KEY"],
-            region=st.secrets["AZURE_REGION"]
-        )
-        speech_config.speech_synthesis_language = lang
-        with tempfile.NamedTemporaryFile(delete=False, suffix=".mp3") as tmpfile:
-            audio_config = speechsdk.audio.AudioOutputConfig(filename=tmpfile.name)
-            synthesizer = speechsdk.SpeechSynthesizer(speech_config, audio_config)
-            result = synthesizer.speak_text_async(text).get()
-        if result.reason == speechsdk.ResultReason.SynthesizingAudioCompleted:
-            st.session_state.tts_usage_count += 1
-            return tmpfile.name
-        else:
-            st.error("❌ Azure TTS failed.")
-            return None
-    except Exception as e:
-        st.error(f"Azure TTS error: {e}")
-        return None
-
-
 
 tab1, tab2 = st.tabs(["🧠 Analyze Review", "📚 Bulk Reviews"])
 
@@ -146,7 +103,11 @@ with tab1:
                 if res.ok:
                     st.session_state.last_response = res.json()
                 else:
-                    st.error(f"Error: {res.status_code} - {res.json().get('detail')}")
+                    try:
+                        err_detail = res.json().get("detail", "No detail provided.")
+                    except Exception:
+                        err_detail = res.text
+                    st.error(f"❌ Backend Error ({res.status_code}): {err_detail}")
             except Exception as e:
                 st.error(f"🚫 Exception: {e}")
 
@@ -165,7 +126,6 @@ with tab1:
         if data.get("pain_points"):
             st.error("🔍 Pain Points: " + ", ".join(data["pain_points"]))
 
-        # Add to churn log
         try:
             st.session_state.churn_log.append({
                 "timestamp": datetime.now(),
@@ -178,21 +138,6 @@ with tab1:
         except Exception as e:
             st.warning(f"🧪 Logging failed: {e}")
 
-        # Only show toggle and button for audio
-        st.subheader("🔊 Audio Summary")
-        st.session_state.enable_audio = st.toggle("🎧 Generate Audio Summary")
-
-        if st.session_state.enable_audio:
-            if st.session_state.tts_usage_count > 20:
-                st.warning("🔇 Azure TTS usage limit reached for this session.")
-            else:
-                if st.button("▶️ Generate & Play Audio"):
-                    audio_path = azure_speak(data["summary"], lang=f"{voice_lang}-US")
-                    if audio_path:
-                        audio_bytes = open(audio_path, "rb").read()
-                        st.audio(audio_bytes, format="audio/mp3")
-                        st.download_button("⬇️ Download Audio", audio_bytes, "summary.mp3")
-
         st.markdown("### 🔁 Ask a Follow-Up")
         sentiment = data["sentiment"]["label"].lower()
         churn = data.get("churn_risk", "")
@@ -215,12 +160,15 @@ with tab1:
                     "verbosity": verbosity
                 }
                 headers = {"x-api-key": api_token}
-
                 res = requests.post(f"{backend_url}/followup/", json=follow_payload, headers=headers)
                 if res.ok:
                     st.success(res.json().get("answer"))
                 else:
-                    st.error("Failed to get follow-up answer.")
+                    try:
+                        err_detail = res.json().get("detail", "No detail provided.")
+                    except Exception:
+                        err_detail = res.text
+                    st.error(f"❌ Follow-up API Error ({res.status_code}): {err_detail}")
             except Exception as e:
                 st.error(f"⚠️ Follow-up error: {e}")
 
@@ -237,7 +185,6 @@ with tab1:
             except Exception as e:
                 st.error(f"Trend error: {e}")
 
-
 # === BULK REVIEW ANALYSIS ===
 with tab2:
     st.title("📚 Bulk Feedback Analysis")
@@ -261,6 +208,10 @@ with tab2:
                 st.dataframe(df)
                 st.download_button("⬇️ Export Results CSV", df.to_csv(index=False), "bulk_results.csv")
             else:
-                st.error(f"API Error: {res.status_code}")
+                try:
+                    err_detail = res.json().get("detail", "No detail provided.")
+                except Exception:
+                    err_detail = res.text
+                st.error(f"❌ Bulk API Error ({res.status_code}): {err_detail}")
         except Exception as e:
-            st.error(f"Bulk analysis failed: {e}")
+            st.error(f"Bulk analysis failed: {e}")