import streamlit as st
import requests
import tempfile
import uuid
import os
from dotenv import load_dotenv
from groq import Groq
from langsmith import Client as LangSmithClient
import time
import pandas as pd
import plotly.express as px
import plotly.graph_objects as go

load_dotenv()

HF_TOKEN = f"Bearer {os.getenv('HF_TOKEN_SECRET')}"
GROQ_API_KEY = os.getenv("GROQ_API_KEY")
LANGSMITH_API_KEY = os.getenv("LANGSMITH_API_KEY")

groq_client = Groq(api_key=GROQ_API_KEY)
langsmith_client = LangSmithClient(api_key=LANGSMITH_API_KEY)

st.set_page_config(
    page_title="🧠 NLP Magique",
    page_icon="✨",
    layout="wide",
    initial_sidebar_state="collapsed"
)

st.markdown("""
    <style>
    @import url('https://fonts.googleapis.com/css2?family=Inter:wght@300;400;500;600;700&display=swap');
    @import url('https://cdnjs.cloudflare.com/ajax/libs/font-awesome/6.0.0/css/all.min.css');

    .stApp {
        background: linear-gradient(135deg, #f5f7ff, #e4e9ff);
        font-family: 'Inter', sans-serif;
        color: #1f2937;
    }

    .main-title {
        text-align: center;
        font-size: 3.5rem;
        font-weight: 700;
        color: #4f46e5;
        margin: 2rem 0;
        animation: fadeInDown 1s ease-out;
    }

    .navbar {
        background: linear-gradient(90deg, #ffffff, #f9fafb);
        padding: 1rem 2rem;
        border-bottom: 1px solid #e5e7eb;
        display: flex;
        align-items: center;
        gap: 2rem;
        margin-bottom: 2rem;
        overflow-x: auto;
        white-space: nowrap;
        box-shadow: 0 2px 4px rgba(0,0,0,0.05);
        border-radius: 8px;
    }

    .navbar-brand {
        font-size: 1.25rem;
        font-weight: 700;
        color: #4f46e5;
        display: flex;
        align-items: center;
        gap: 0.5rem;
    }

    .navbar-brand i {
        font-size: 1.5rem;
    }

    .navbar button {
        background: none;
        border: none;
        font-size: 1rem;
        font-weight: 500;
        color: #4b5563;
        padding: 0.75rem 1.25rem;
        cursor: pointer;
        transition: all 0.3s ease;
        border-radius: 6px;
        display: flex;
        align-items: center;
        gap: 0.5rem;
    }

    .navbar button:hover {
        color: #4f46e5;
        background: #e0e7ff;
        transform: scale(1.05);
    }

    .navbar button.active {
        color: #4f46e5;
        background: #e0e7ff;
        font-weight: 600;
        border-bottom: 3px solid #4f46e5;
    }

    .navbar button i {
        font-size: 1rem;
    }

    .card {
        background: linear-gradient(145deg, #ffffff, #f9fafb);
        border-radius: 16px;
        padding: 2rem;
        margin: 1.5rem 0;
        box-shadow: 0 4px 20px rgba(0,0,0,0.08);
        transition: all 0.3s ease;
        border: 1px solid #e5e7eb;
    }

    .card:hover {
        transform: translateY(-4px);
        box-shadow: 0 6px 24px rgba(0,0,0,0.12);
    }

    .stButton>button {
        background: linear-gradient(90deg, #4f46e5, #7c3aed);
        color: white;
        font-weight: 600;
        border-radius: 8px;
        padding: 0.75rem 1.5rem;
        border: none;
        transition: all 0.3s ease;
        width: 100%;
    }

    .stButton>button:hover {
        background: linear-gradient(90deg, #4338ca, #6d28d9);
        transform: translateY(-2px);
        box-shadow: 0 4px 12px rgba(79,70,229,0.3);
    }

    .stTextArea textarea, .stSlider>div, .stTextInput input {
        background: #f9fafb;
        border-radius: 8px;
        padding: 1rem;
        border: 1px solid #d1d5db;
        transition: all 0.3s ease;
    }

    .stTextArea textarea:focus, .stTextInput input:focus {
        border-color: #4f46e5;
        box-shadow: 0 0 0 3px rgba(79,70,229,0.1);
    }

    .stFileUploader {
        background: #f9fafb;
        border-radius: 8px;
        padding: 1rem;
        border: 1px solid #d1d5db;
    }

    .output-card {
        background: #f9fafb;
        border-radius: 8px;
        padding: 1.5rem;
        margin-top: 1rem;
        border: 1px solid #e5e7eb;
        position: relative;
        font-size: 1rem;
        line-height: 1.6;
    }

    .copy-button {
        position: absolute;
        top: 0.5rem;
        right: 0.5rem;
        background: #4f46e5;
        color: white;
        border: none;
        border-radius: 6px;
        padding: 0.5rem 1rem;
        font-size: 0.875rem;
        cursor: pointer;
        transition: all 0.3s ease;
    }

    .copy-button:hover {
        background: #4338ca;
    }

    .chat-window {
        width: 100%;
        max-width: 600px;
        height: 500px;
        background: #ffffff;
        border-radius: 12px;
        box-shadow: 0 6px 20px rgba(0,0,0,0.15);
        display: flex;
        flex-direction: column;
        overflow: hidden;
        margin: 0 auto;
        border: 1px solid #e5e7eb;
    }

    .chat-header {
        background: #f9fafb;
        color: #1f2937;
        padding: 0.75rem 1rem;
        display: flex;
        justify-content: space-between;
        align-items: center;
        font-weight: 500;
        font-size: 0.875rem;
        border-bottom: 1px solid #e5e7eb;
    }

    .chat-body {
        flex: 1;
        overflow-y: auto;
        padding: 0.75rem;
        background: #f9fafb;
    }

    .chat-message {
        margin: 0.5rem 0;
        padding: 0.5rem 0.75rem;
        border-radius: 8px;
        max-width: 85%;
        font-size: 0.875rem;
        line-height: 1.4;
    }

    .user-message {
        background: #e0e7ff;
        margin-left: auto;
        border: 1px solid #c7d2fe;
    }

    .bot-message {
        background: #f3e8ff;
        margin-right: auto;
        border: 1px solid #e9d5ff;
    }

    .chat-input {
        display: flex;
        align-items: center;
        padding: 0.5rem;
        background: #ffffff;
        border-top: 1px solid #e5e7eb;
        gap: 0.5rem;
    }

    .chat-input button {
        background: #4f46e5;
        color: white;
        border: none;
        border-radius: 6px;
        padding: 0.5rem 1rem;
        font-size: 0.875rem;
        cursor: pointer;
        transition: background 0.2s ease;
    }

    .chat-input button:hover {
        background: #4338ca;
    }

    .langsmith-table {
        width: 100%;
        border-collapse: collapse;
        margin-top: 1rem;
    }

    .langsmith-table th, .langsmith-table td {
        border: 1px solid #e5e7eb;
        padding: 0.75rem;
        text-align: left;
        font-size: 0.875rem;
    }

    .langsmith-table th {
        background: #f9fafb;
        font-weight: 600;
    }

    .langsmith-table tr:nth-child(even) {
        background: #f9fafb;
    }

    .footer {
        text-align: center;
        padding: 2rem;
        margin-top: 3rem;
        background: #ffffff;
        border-radius: 12px;
        box-shadow: 0 4px 12px rgba(0,0,0,0.08);
        font-size: 1rem;
        color: #4b5563;
    }

    .footer a {
        color: #4f46e5;
        font-weight: 600;
        text-decoration: none;
    }

    .footer a:hover {
        color: #4338ca;
        text-decoration: underline;
    }

    .social-icons img {
        width: 24px;
        margin: 0 0.5rem;
        transition: transform 0.3s ease;
    }

    .social-icons img:hover {
        transform: scale(1.2);
    }

    @keyframes fadeInDown {
        from { opacity: 0; transform: translateY(-20px); }
        to { opacity: 1; transform: translateY(0); }
    }

    @media (max-width: 768px) {
        .main-title { font-size: 2.5rem; }
        .card { padding: 1.5rem; }
        .chat-window { width: 90vw; }
        .navbar { gap: 1rem; padding: 0.75rem 1rem; }
        .navbar-brand { font-size: 1rem; }
        .navbar button { padding: 0.5rem 0.75rem; font-size: 0.875rem; }
    }
    </style>
""", unsafe_allow_html=True)

st.markdown("""
    <script>
    function copyToClipboard(text) {
        navigator.clipboard.writeText(text).then(() => {
            alert('Texte copié !');
        });
    }
    </script>
""", unsafe_allow_html=True)


def generate_text(prompt):
    url = "https://api-inference.huggingface.co/models/gpt2"
    headers = {"Authorization": HF_TOKEN}
    payload = {"inputs": f"{prompt}"}
    response = requests.post(url, headers=headers, json=payload)
    if response.ok:
        return response.json()[0]["generated_text"]
    else:
        st.error(f"Erreur: {response.status_code} - {response.text}")
        return "Erreur lors de la génération."


def summarize_text(text):
    url = "https://api-inference.huggingface.co/models/facebook/bart-large-cnn"
    headers = {"Authorization": HF_TOKEN}
    payload = {"inputs": text}
    response = requests.post(url, headers=headers, json=payload)
    if response.ok:
        return response.json()[0]["summary_text"]
    else:
        st.error(f"Erreur: {response.status_code} - {response.text}")
        return "Erreur lors du résumé."


def transcribe_audio(path):
    url = "https://api-inference.huggingface.co/models/openai/whisper-large-v2"
    headers = {
        "Authorization": HF_TOKEN,
        "Content-Type": "application/octet-stream"
    }
    with open(path, "rb") as f:
        response = requests.post(url, headers=headers, data=f)
    if response.ok:
        return response.json()["text"]
    else:
        st.error(f"Erreur: {response.status_code} - {response.text}")
        return "Erreur lors de la transcription."


def chat_with_grok(user_input, conversation_id):
    try:
        run = langsmith_client.create_run(
            name="Grok_Chat",
            run_type="chain",
            inputs={"user_input": user_input, "conversation_id": conversation_id}
        )
        response = groq_client.chat.completions.create(
            messages=[
                {"role": "system",
                 "content": "Vous êtes Grok, un assistant IA créé par xAI. Répondez en français avec précision et clarté."},
                {"role": "user", "content": user_input}
            ],
            model="llama-3.3-70b-versatile",
            temperature=0.7,
            max_tokens=1000
        )
        response_text = response.choices[0].message.content
        if run:
            run.update({"outputs": response_text, "end_time": time.time()})
        return response_text
    except Exception as e:
        if 'run' in locals() and run:
            run.update({"outputs": {"error": str(e)}, "end_time": time.time(), "status": "error"})
        st.error(f"Erreur: {str(e)}")
        return "Une erreur s'est produite. Réessayez."


# Navbar
st.markdown('<div class="navbar">', unsafe_allow_html=True)
st.markdown('<span class="navbar-brand"><i class="fas fa-brain"></i> NLP Magique</span>', unsafe_allow_html=True)
tabs = [
    {"name": "Résumé", "icon": "fas fa-compress"},
    {"name": "Génération", "icon": "fas fa-pen-fancy"},
    {"name": "Transcription", "icon": "fas fa-microphone"},
    {"name": "Chatbot", "icon": "fas fa-comment-dots"},
    {"name": "LangSmith Monitoring", "icon": "fas fa-chart-line"}
]
selected_tab = st.session_state.get('selected_tab', tabs[0]["name"])
for tab in tabs:
    active = 'active' if selected_tab == tab["name"] else ''
    if st.button(f'<i class="{tab["icon"]}"></i> {tab["name"]}', key=f"nav_{tab["name"]}", help=tab["name"],
                 unsafe_allow_html=True):
        st.session_state.selected_tab = tab["name"]
        st.rerun()
st.markdown('</div>', unsafe_allow_html=True)

# Initialize session state
if 'chat_history' not in st.session_state:
    st.session_state.chat_history = []
if 'conversation_id' not in st.session_state:
    st.session_state.conversation_id = str(uuid.uuid4())
if 'langsmith_runs' not in st.session_state:
    st.session_state.langsmith_runs = []

st.markdown('<h1 class="main-title">✨ NLP Magique</h1>', unsafe_allow_html=True)

if selected_tab == "Génération":
    with st.container():
        st.markdown("<div class='card'>", unsafe_allow_html=True)
        st.subheader("Génération de texte")
        prompt = st.text_area("Entrez votre idée :", "La médecine moderne", height=150)
        temp = st.slider("Créativité", 0.1, 1.0, 0.7, step=0.1)
        if st.button("Générer"):
            with st.spinner("Génération..."):
                output = generate_text(prompt)
            st.markdown(
                f'<div class="output-card">{output}<button class="copy-button" onclick="copyToClipboard(\'{output}\')">Copier</button></div>',
                unsafe_allow_html=True)
        st.markdown("</div>", unsafe_allow_html=True)

elif selected_tab == "Résumé":
    with st.container():
        st.markdown("<div class='card'>", unsafe_allow_html=True)
        st.subheader("Résumé de texte")
        texte = st.text_area("Collez votre texte :", height=200)
        if st.button("Résumer"):
            with st.spinner("Résumé..."):
                summary = summarize_text(texte)
            st.markdown(
                f'<div class="output-card">{summary}<button class="copy-button" onclick="copyToClipboard(\'{summary}\')">Copier</button></div>',
                unsafe_allow_html=True)
        st.markdown("</div>", unsafe_allow_html=True)

elif selected_tab == "Transcription":
    with st.container():
        st.markdown("<div class='card'>", unsafe_allow_html=True)
        st.subheader("Transcription audio")
        audio_file = st.file_uploader("Chargez un audio (max 30s)", type=["wav", "mp3", "m4a"])
        if audio_file:
            with tempfile.NamedTemporaryFile(delete=False, suffix='.wav') as tmp_file:
                tmp_file.write(audio_file.read())
                audio_path = tmp_file.name
            st.audio(audio_path)
            if st.button("Transcrire"):
                with st.spinner("Transcription..."):
                    transcript = transcribe_audio(audio_path)
                st.markdown(
                    f'<div class="output-card">{transcript}<button class="copy-button" onclick="copyToClipboard(\'{transcript}\')">Copier</button></div>',
                    unsafe_allow_html=True)
        st.markdown("</div>", unsafe_allow_html=True)

elif selected_tab == "Chatbot":
    with st.container():
        st.markdown('<div class="chat-window">', unsafe_allow_html=True)
        st.markdown('<div class="chat-header">Grok AI</div>', unsafe_allow_html=True)
        st.markdown('<div class="chat-body">', unsafe_allow_html=True)
        for message in st.session_state.chat_history:
            if message['role'] == 'user':
                st.markdown(f'<div class="chat-message user-message">{message["content"]}</div>',
                            unsafe_allow_html=True)
            else:
                st.markdown(f'<div class="chat-message bot-message">{message["content"]}</div>', unsafe_allow_html=True)
        st.markdown('</div>', unsafe_allow_html=True)
        st.markdown('<div class="chat-input">', unsafe_allow_html=True)
        user_input = st.text_input("Votre message :", key="chat_input", placeholder="Tapez ici...")
        col1, col2 = st.columns([3, 1])
        with col1:
            if st.button("Envoyer", key="chat_send"):
                if user_input:
                    with st.spinner("Grok répond..."):
                        st.session_state.chat_history.append({"role": "user", "content": user_input})
                        response = chat_with_grok(user_input, st.session_state.conversation_id)
                        st.session_state.chat_history.append({"role": "assistant", "content": response})
                        st.session_state.langsmith_runs.append({
                            "input": user_input,
                            "output": response,
                            "timestamp": time.strftime("%Y-%m-%d %H:%M:%S"),
                            "input_length": len(user_input)
                        })
                        st.rerun()
        with col2:
            if st.button("Effacer", key="chat_clear"):
                st.session_state.chat_history = []
                st.session_state.conversation_id = str(uuid.uuid4())
                st.session_state.langsmith_runs = []
                st.rerun()
        st.markdown('</div>', unsafe_allow_html=True)
        st.markdown('</div>', unsafe_allow_html=True)

elif selected_tab == "LangSmith Monitoring":
    with st.container():
        st.markdown("<div class='card'>", unsafe_allow_html=True)
        st.subheader("LangSmith Monitoring")

        if st.session_state.langsmith_runs:
            df = pd.DataFrame(st.session_state.langsmith_runs)
            df['timestamp'] = pd.to_datetime(df['timestamp'])
            df['hour'] = df['timestamp'].dt.strftime('%Y-%m-%d %H:00')

            # Chart 1: Interactions per Hour
            st.markdown("<h3>Interactions par heure</h3>", unsafe_allow_html=True)
            chart_type = st.selectbox("Type de graphique", ["Bar", "Line", "Area"], key="chart_type_interactions")
            interaction_counts = df.groupby('hour').size().reset_index(name='count')

            if chart_type == "Bar":
                fig = px.bar(
                    interaction_counts,
                    x='hour',
                    y='count',
                    color_discrete_sequence=['#4f46e5'],
                    title="Nombre d'interactions par heure",
                    labels={'hour': 'Heure', 'count': 'Nombre d\'interactions'}
                )
            elif chart_type == "Line":
                fig = px.line(
                    interaction_counts,
                    x='hour',
                    y='count',
                    color_discrete_sequence=['#4f46e5'],
                    title="Nombre d'interactions par heure",
                    labels={'hour': 'Heure', 'count': 'Nombre d\'interactions'},
                    markers=True
                )
            else:  # Area
                fig = px.area(
                    interaction_counts,
                    x='hour',
                    y='count',
                    color_discrete_sequence=['#4f46e5'],
                    title="Nombre d'interactions par heure",
                    labels={'hour': 'Heure', 'count': 'Nombre d\'interactions'}
                )

            fig.update_layout(
                plot_bgcolor='rgba(0,0,0,0)',
                paper_bgcolor='rgba(0,0,0,0)',
                font=dict(family="Inter, sans-serif", size=12, color="#1f2937"),
                xaxis_tickangle=45,
                showlegend=False,
                margin=dict(l=40, r=40, t=80, b=40)
            )
            st.plotly_chart(fig, use_container_width=True)

            # Chart 2: Input Length per Interaction
            st.markdown("<h3>Longueur des entrées par interaction</h3>", unsafe_allow_html=True)
            input_length_chart_type = st.selectbox("Type de graphique", ["Bar", "Line", "Area"],
                                                   key="chart_type_input_length")
            input_lengths = df.groupby('hour')['input_length'].mean().reset_index(name='avg_length')

            if input_length_chart_type == "Bar":
                fig2 = px.bar(
                    input_lengths,
                    x='hour',
                    y='avg_length',
                    color_discrete_sequence=['#7c3aed'],
                    title="Longueur moyenne des entrées par heure",
                    labels={'hour': 'Heure', 'avg_length': 'Longueur moyenne (caractères)'}
                )
            elif input_length_chart_type == "Line":
                fig2 = px.line(
                    input_lengths,
                    x='hour',
                    y='avg_length',
                    color_discrete_sequence=['#7c3aed'],
                    title="Longueur moyenne des entrées par heure",
                    labels={'hour': 'Heure', 'avg_length': 'Longueur moyenne (caractères)'},
                    markers=True
                )
            else:  # Area
                fig2 = px.area(
                    input_lengths,
                    x='hour',
                    y='avg_length',
                    color_discrete_sequence=['#7c3aed'],
                    title="Longueur moyenne des entrées par heure",
                    labels={'hour': 'Heure', 'avg_length': 'Longueur moyenne (caractères)'}
                )

            fig2.update_layout(
                plot_bgcolor='rgba(0,0,0,0)',
                paper_bgcolor='rgba(0,0,0,0)',
                font=dict(family="Inter, sans-serif", size=12, color="#1f2937"),
                xaxis_tickangle=45,
                showlegend=False,
                margin=dict(l=40, r=40, t=80, b=40)
            )
            st.plotly_chart(fig2, use_container_width=True)

            # Table: Run Details
            st.markdown("<h3>Détails des interactions</h3>", unsafe_allow_html=True)
            st.markdown('<table class="langsmith-table">', unsafe_allow_html=True)
            st.markdown('<tr><th>Timestamp</th><th>Input</th><th>Output</th><th>Longueur entrée</th></tr>',
                        unsafe_allow_html=True)
            for run in st.session_state.langsmith_runs:
                st.markdown(
                    f'<tr><td>{run["timestamp"]}</td><td>{run["input"]}</td><td>{run["output"]}</td><td>{run["input_length"]}</td></tr>',
                    unsafe_allow_html=True
                )
            st.markdown('</table>', unsafe_allow_html=True)
        else:
            st.write("Aucune donnée de monitoring disponible.")
        st.markdown("</div>", unsafe_allow_html=True)

st.markdown("""
    <div class="footer">
        <p>© 2025 NTONGA<br>
        Propulsé par <a href='https://www.huggingface.co/' target='_blank'>Hugging Face</a>, <a href='https://streamlit.io/' target='_blank'>Streamlit</a>, et <a href='https://x.ai/' target='_blank'>xAI</a></p>
        <div class='social-icons'>
            <a href="https://twitter.com" target="_blank"><img src='https://img.icons8.com/color/48/twitter--v1.png'></a>
            <a href="https://www.linkedin.com" target="_blank"><img src='https://img.icons8.com/color/48/linkedin.png'></a>
            <a href="https://github.com" target="_blank"><img src='https://img.icons8.com/color/48/github--v1.png'></a>
        </div>
    </div>
""", unsafe_allow_html=True)