Update frontend.py

frontend.py

@@ -4,92 +4,60 @@ import pandas as pd
 from gtts import gTTS
 import base64
 from io import BytesIO
-from PIL import Image
 import os
 import plotly.express as px
 
 st.set_page_config(page_title="NeuroPulse AI", page_icon="🧠", layout="wide")
 
-# Logo
-logo_path = "logo.png"
-if os.path.exists(logo_path):
-    st.image(logo_path, width=180)
-
-# Session State
-if "review" not in st.session_state:
-    st.session_state.review = ""
-if "dark_mode" not in st.session_state:
-    st.session_state.dark_mode = False
-if "intelligence_mode" not in st.session_state:
-    st.session_state.intelligence_mode = True
-if "trigger_example_analysis" not in st.session_state:
-    st.session_state.trigger_example_analysis = False
-
-# Dark Mode Style
+if os.path.exists("logo.png"):
+    st.image("logo.png", width=180)
+
+# Session variables
+for key, default in {
+    "review": "",
+    "dark_mode": False,
+    "intelligence_mode": True,
+    "trigger_example_analysis": False,
+    "last_response": None,
+    "followup_answer": None,
+}.items():
+    if key not in st.session_state:
+        st.session_state[key] = default
+
+# Dark mode CSS
 if st.session_state.dark_mode:
     st.markdown("""
-        <style>
-        html, body, [class*="st-"] {
-            background-color: #121212;
-            color: #f5f5f5;
-        }
-        .stTextInput > div > div > input,
-        .stTextArea > div > textarea,
-        .stSelectbox div div,
-        .stDownloadButton > button,
-        .stButton > button {
-            background-color: #1e1e1e;
-            color: white;
-        }
-        </style>
+    <style>
+    html, body, [class*="st-"] {
+        background-color: #121212;
+        color: #f5f5f5;
+    }
+    .stTextInput > div > div > input,
+    .stTextArea > div > textarea,
+    .stSelectbox div div,
+    .stDownloadButton > button,
+    .stButton > button {
+        background-color: #1e1e1e;
+        color: white;
+    }
+    </style>
     """, unsafe_allow_html=True)
 
-# Sidebar Controls
+# Sidebar controls
 with st.sidebar:
     st.header("⚙️ Global Settings")
+    st.session_state.dark_mode = st.toggle("🌙 Dark Mode", value=st.session_state.dark_mode)
+    st.session_state.intelligence_mode = st.toggle("🧠 Intelligence Mode", value=st.session_state.intelligence_mode)
 
-    # Dark Mode Toggle with refresh
-    if st.toggle("🌙 Dark Mode", value=st.session_state.dark_mode):
-        if not st.session_state.dark_mode:
-            st.session_state.dark_mode = True
-            st.rerun()
-    else:
-        if st.session_state.dark_mode:
-            st.session_state.dark_mode = False
-            st.rerun()
-
-    if st.toggle("🧠 Intelligence Mode", value=st.session_state.intelligence_mode):
-        st.session_state.intelligence_mode = True
-    else:
-        st.session_state.intelligence_mode = False
-
-    DEFAULT_DEMO_TOKEN = "my-secret-key"
-    api_token = st.text_input("🔐 API Token", value=DEFAULT_DEMO_TOKEN, type="password")
-    if not api_token or api_token.strip() == "my-secret-key":
-        st.warning("🧪 Running in demo mode — for full access, enter a valid API key.")
-
+    api_token = st.text_input("🔐 API Token", value="my-secret-key", type="password")
     backend_url = st.text_input("🌐 Backend URL", value="http://localhost:8000")
 
     sentiment_model = st.selectbox("📊 Sentiment Model", [
         "distilbert-base-uncased-finetuned-sst-2-english",
         "nlptown/bert-base-multilingual-uncased-sentiment"
     ])
-
-    industry = st.selectbox("🏭 Industry", [
-        "Auto-detect", "Generic", "E-commerce", "Healthcare", "Education", "Travel", "Banking", "Insurance",
-        "Gaming", "Food Delivery", "Real Estate", "Fitness", "Entertainment"
-    ])
-
-    product_category = st.selectbox("🧩 Product Category", [
-        "Auto-detect", "General", "Mobile Devices", "Laptops", "Healthcare Devices", "Banking App",
-        "Travel Service", "Educational Tool", "Insurance Portal", "Streaming App", "Wearables",
-        "Home Appliances", "Food Apps"
-    ])
-
-    use_aspects = st.checkbox("🔬 Enable Aspect Analysis")
-    use_smart_summary = st.checkbox("🧠 Smart Summary (Single)")
-    use_smart_summary_bulk = st.checkbox("🧠 Smart Summary for Bulk")
-    use_explain_bulk = st.checkbox("🧠 Generate Explanations (Bulk)")
+    industry = st.selectbox("🏭 Industry", ["Auto-detect", "Generic", "E-commerce", "Healthcare", "Education"])
+    product_category = st.selectbox("🧩 Product Category", ["Auto-detect", "General", "Mobile Devices", "Laptops"])
     verbosity = st.radio("🗣️ Response Style", ["Brief", "Detailed"])
     voice_lang = st.selectbox("🔈 Voice Language", ["en", "fr", "es", "de", "hi", "zh"])
 
@@ -103,20 +71,22 @@ def speak(text, lang='en'):
     mp3.seek(0)
     return mp3
 
+# Tabs
 tab1, tab2 = st.tabs(["🧠 Single Review", "📚 Bulk CSV"])
 
-# --- SINGLE REVIEW TAB ---
+# ---- SINGLE REVIEW ----
 with tab1:
     st.title("🧠 NeuroPulse AI – Multimodal Review Analyzer")
     st.markdown("<div style='font-size:16px;color:#888;'>Minimum 20–50 words recommended.</div>", unsafe_allow_html=True)
 
     review = st.text_area("📝 Enter Review", value=st.session_state.review, height=180)
+    st.session_state.review = review
 
     col1, col2, col3 = st.columns(3)
     with col1:
-        analyze = st.button("🔍 Analyze", use_container_width=True, disabled=not api_token)
+        analyze = st.button("🔍 Analyze")
     with col2:
-        if st.button("🎲 Example", use_container_width=True):
+        if st.button("🎲 Example"):
             st.session_state.review = (
                 "I love this phone! Super fast performance, great battery, and smooth UI. "
                 "Camera is awesome too, though the price is a bit high. Overall, very happy."
@@ -124,90 +94,69 @@ with tab1:
             st.session_state.trigger_example_analysis = True
             st.rerun()
     with col3:
-        if st.button("🧹 Clear", use_container_width=True):
-            st.session_state.review = ""
+        if st.button("🧹 Clear"):
+            for key in ["review", "last_response", "followup_answer"]:
+                st.session_state[key] = ""
             st.rerun()
 
-    if st.session_state.trigger_example_analysis and st.session_state.review:
-        analyze = True
+    if (analyze or st.session_state.trigger_example_analysis) and st.session_state.review:
         st.session_state.trigger_example_analysis = False
-
-    if analyze and review:
-        if len(review.split()) < 20:
-            st.warning("⚠️ Please enter at least 20 words.")
-        else:
-            with st.spinner("Analyzing..."):
+        st.session_state.followup_answer = None
+        with st.spinner("Analyzing..."):
+            try:
+                payload = {
+                    "text": st.session_state.review,
+                    "model": sentiment_model,
+                    "industry": industry,
+                    "product_category": product_category,
+                    "verbosity": verbosity,
+                    "intelligence": st.session_state.intelligence_mode
+                }
+                headers = {"x-api-key": api_token}
+                res = requests.post(f"{backend_url}/analyze/", json=payload, headers=headers)
+                if res.status_code == 200:
+                    st.session_state.last_response = res.json()
+                else:
+                    st.error(f"API error: {res.status_code} - {res.json().get('detail')}")
+            except Exception as e:
+                st.error(f"🚫 Exception: {e}")
+
+    data = st.session_state.last_response
+    if data:
+        st.subheader("📌 Summary")
+        st.info(data["summary"])
+        st.metric("📊 Sentiment", data["sentiment"]["label"], delta=f"{data['sentiment']['score']:.2%}")
+        st.info(f"💢 Emotion: {data['emotion']}")
+        st.subheader("🔊 Audio")
+        audio = speak(data["summary"], lang=voice_lang)
+        st.download_button("⬇️ Download Summary Audio", audio.read(), "summary.mp3")
+
+        st.markdown("### 🔁 Got questions?")
+        sample_questions = ["What did the user like most?", "Any complaints mentioned?", "Is it positive overall?"]
+        selected_q = st.selectbox("💡 Sample Questions", ["Type your own..."] + sample_questions)
+        custom_q = selected_q if selected_q != "Type your own..." else st.text_input("🔍 Ask a follow-up")
+
+        if custom_q:
+            with st.spinner("Thinking..."):
                 try:
-                    payload = {
-                        "text": review,
-                        "model": sentiment_model,
-                        "industry": industry,
-                        "aspects": use_aspects,
-                        "follow_up": None,
-                        "product_category": product_category,
-                        "verbosity": verbosity,
-                        "intelligence": st.session_state.intelligence_mode
+                    follow_payload = {
+                        "text": st.session_state.review,
+                        "question": custom_q,
+                        "verbosity": verbosity
                     }
-                    headers = {"x-api-key": st.session_state.get("api_token", api_token)}
-                    params = {"smart": "1"} if use_smart_summary else {}
-                    res = requests.post(f"{backend_url}/analyze/", json=payload, headers=headers, params=params)
-
+                    res = requests.post(f"{backend_url}/followup/", json=follow_payload, headers=headers)
                     if res.status_code == 200:
-                        data = res.json()
-                        st.success("✅ Analysis Complete")
-                        st.subheader("📌 Summary")
-                        st.info(data["summary"])
-                        st.caption(f"🧠 Summary Type: {'Smart' if use_smart_summary else 'Standard'} | {verbosity} Response")
-                        st.markdown(f"**Context:** `{data['industry']}` | `{data['product_category']}` | `Web`")
-
-                        st.subheader("🔊 Audio")
-                        audio = speak(data["summary"], lang=voice_lang)
-                        st.download_button("⬇️ Download Summary Audio", audio.read(), "summary.mp3", mime="audio/mp3")
-
-                        st.metric("📊 Sentiment", data["sentiment"]["label"], delta=f"{data['sentiment']['score']:.2%}")
-                        st.info(f"💢 Emotion: {data['emotion']}")
-
-                        # Follow-up Section
-                        st.markdown("### 🔁 Got questions?")
-                        st.info("💬 Ask a follow-up question about this review.")
-                        sample_questions = [
-                            "What did the user like most?",
-                            "Any complaints mentioned?",
-                            "Is it positive overall?",
-                            "What are the improvement areas?"
-                        ]
-                        selected_q = st.selectbox("💡 Sample Questions", ["Type your own..."] + sample_questions)
-
-                        if selected_q != "Type your own...":
-                            custom_q = selected_q
-                        else:
-                            custom_q = st.text_input("🔍 Ask a follow-up")
-
-                        if custom_q:
-                            with st.spinner("Thinking..."):
-                                try:
-                                    follow_payload = {
-                                        "text": review,
-                                        "question": custom_q,
-                                        "verbosity": verbosity
-                                    }
-                                    res = requests.post(f"{backend_url}/followup/", json=follow_payload, headers=headers)
-                                    if res.status_code == 200:
-                                        follow = res.json().get("answer")
-                                        st.subheader("🔁 Follow-Up Answer")
-                                        st.warning(follow)
-                                    else:
-                                        st.error(f"❌ Follow-up failed: {res.json().get('detail', 'Unknown error')}")
-                                except Exception as e:
-                                    st.error(f"⚠️ Follow-up error: {e}")
+                        st.session_state.followup_answer = res.json().get("answer")
                     else:
-                        st.error(f"❌ API Error {res.status_code}: {res.json().get('detail', 'Unknown error')}")
+                        st.error(f"❌ Follow-up failed: {res.json().get('detail')}")
                 except Exception as e:
-                    st.error(f"🚫 Exception occurred: {e}")
+                    st.error(f"⚠️ Follow-up error: {e}")
+
+    if st.session_state.followup_answer:
+        st.subheader("🔁 Follow-Up Answer")
+        st.success(st.session_state.followup_answer)
 
-# -------------------
-# BULK CSV TAB
-# -------------------
+# ---- BULK CSV ----
 with tab2:
     st.title("📚 Bulk CSV Upload")
     st.markdown("""
@@ -246,16 +195,14 @@ with tab2:
                                 payload = {
                                     "reviews": df["review"].tolist(),
                                     "model": sentiment_model,
-                                    "aspects": use_aspects,
                                     "industry": df["industry"].tolist(),
                                     "product_category": df["product_category"].tolist(),
                                     "device": df["device"].tolist(),
                                     "follow_up": df["follow_up"].tolist(),
-                                    "explain": use_explain_bulk,
                                     "intelligence": st.session_state.intelligence_mode,
                                 }
                                 res = requests.post(
-                                    f"{backend_url}/bulk/?token={st.session_state.get('api_token', api_token)}",
+                                    f"{backend_url}/bulk/?token={api_token}",
                                     json=payload
                                 )
                                 if res.status_code == 200: