import streamlit as st
import requests
import pandas as pd
from gtts import gTTS
import base64
from io import BytesIO
from PIL import Image
import os

st.set_page_config(page_title="NeuroPulse AI", page_icon="🧠", layout="wide")

# Optional logo
logo_path = os.path.join("app", "static", "logo.png")
if os.path.exists(logo_path):
    st.image(logo_path, width=160)

# Session state
if "page" not in st.session_state:
    st.session_state.page = "Home"
if "review" not in st.session_state:
    st.session_state.review = ""

# Navigation
with st.sidebar:
    st.title("🧭 Navigation")
    st.session_state.page = st.radio("Go to", ["Home", "Single Review", "Bulk CSV"])

# Text-to-speech
def speak(text, lang='en'):
    tts = gTTS(text, lang=lang)
    mp3 = BytesIO()
    tts.write_to_fp(mp3)
    b64 = base64.b64encode(mp3.getvalue()).decode()
    st.markdown(f'<audio controls><source src="data:audio/mp3;base64,{b64}" type="audio/mp3"></audio>', unsafe_allow_html=True)
    mp3.seek(0)
    return mp3

# Page: Home
if st.session_state.page == "Home":
    st.markdown("""
        <div style='text-align: center;'>
            <h1 style='font-size: 48px;'>🧠 NeuroPulse AI</h1>
            <p style='font-size: 20px;'>Smarter feedback analyzer using GenAI for Summarization, Sentiment, Emotion, Aspects, and GPT Q&A</p>
            <a href='https://huggingface.co/spaces/your-space-name' target='_blank' style='text-decoration: none;'>
                <button style='padding: 12px 30px; font-size: 18px; border-radius: 8px; background: linear-gradient(90deg, #6366f1, #4f46e5); color: white; border: none;'>🚀 Try App</button>
            </a>
        </div>
    """, unsafe_allow_html=True)

# Page: Single Review
elif st.session_state.page == "Single Review":
    st.title("🧠 Analyze Single Review")

    with st.expander("⚙️ Settings"):
        sentiment_model = st.selectbox("Sentiment Model", [
            "distilbert-base-uncased-finetuned-sst-2-english",
            "nlptown/bert-base-multilingual-uncased-sentiment"])
        industry = st.selectbox("Industry", ["Generic", "E-commerce", "Healthcare"])
        product_category = st.text_input("Product Category", "General")
        device = st.text_input("Device", "Web")
        use_aspects = st.checkbox("Enable Aspect Analysis")
        use_smart = st.checkbox("Use Smart Summary")
        follow_up = st.text_input("Follow-up Question")
        voice_lang = st.selectbox("Voice Language", ["en", "fr", "es"])
        backend_url = st.text_input("Backend URL", "http://0.0.0.0:8000")
        api_token = st.text_input("API Token", type="password")

    st.session_state.review = st.text_area("📝 Enter your review", value=st.session_state.review, height=160)

    if st.button("🔍 Analyze") and st.session_state.review:
        with st.spinner("Analyzing..."):
            payload = {
                "text": st.session_state.review,
                "model": sentiment_model,
                "industry": industry,
                "aspects": use_aspects,
                "follow_up": follow_up,
                "product_category": product_category,
                "device": device
            }
            headers = {"X-API-Key": api_token}
            params = {"smart": "1"} if use_smart else {}
            res = requests.post(f"{backend_url}/analyze/", json=payload, headers=headers, params=params)
            if res.status_code == 200:
                out = res.json()
                st.success("✅ Done")
                st.markdown(f"### 📌 Summary\n{out['summary']}")
                st.caption(f"Smart Summary: {use_smart}")
                audio = speak(out["summary"], lang=voice_lang)
                st.download_button("⬇️ Download Audio", audio.read(), "summary.mp3")
                st.metric("📊 Sentiment", out['sentiment']['label'], f"{out['sentiment']['score']:.2%}")
                st.info(f"💢 Emotion: {out['emotion']}")
                if out.get("aspects"):
                    st.markdown("### 🔍 Aspects")
                    for asp in out["aspects"]:
                        st.write(f"- {asp['aspect']}: {asp['sentiment']} ({asp['score']:.2%})")
                if out.get("follow_up"):
                    st.warning(f"🧠 GPT: {out['follow_up']}")
            else:
                st.error(f"❌ Error: {res.status_code}")

# Page: Bulk CSV
elif st.session_state.page == "Bulk CSV":
    st.title("📚 Analyze CSV in Bulk")
    uploaded_file = st.file_uploader("Upload CSV with `review` column", type="csv")
    if uploaded_file:
        df = pd.read_csv(uploaded_file)
        if "review" not in df.columns:
            st.error("CSV must have a 'review' column")
        else:
            st.success(f"✅ {len(df)} reviews loaded")
            df.fillna("", inplace=True)
            if st.button("📊 Run Bulk Analysis"):
                with st.spinner("Running..."):
                    payload = {
                        "reviews": df["review"].tolist(),
                        "model": sentiment_model,
                        "industry": df["industry"].tolist() if "industry" in df else ["Generic"]*len(df),
                        "product_category": df["product_category"].tolist() if "product_category" in df else [""]*len(df),
                        "device": df["device"].tolist() if "device" in df else [""]*len(df),
                        "aspects": use_aspects
                    }
                    headers = {"X-API-Key": api_token}
                    params = {"smart": "1"} if use_smart else {}
                    res = requests.post(f"{backend_url}/bulk/", json=payload, headers=headers, params=params)
                    if res.status_code == 200:
                        results = pd.DataFrame(res.json()["results"])
                        st.dataframe(results)
                        st.download_button("⬇️ Download CSV", results.to_csv(index=False), "results.csv")
                    else:
                        st.error(f"❌ Failed: {res.status_code}")
    with st.expander("📄 Sample CSV"):
        st.markdown("""
            Download sample CSV [here](https://huggingface.co/datasets/hasi-labs/sample-neuropulse-csv/raw/main/sample.csv)
            
            Required column: `review` (Optional: `industry`, `product_category`, `device`)
        """)