import streamlit as st
import speech_recognition as sr
from openai import OpenAI

# Initialize session state for chat visibility
if "chat_started" not in st.session_state:
    st.session_state.chat_started = False

if "chat_history" not in st.session_state:
    st.session_state.chat_history = []
if "feedback" not in st.session_state:
    st.session_state.feedback = {}

st.set_page_config(page_title="🍽️ Food Chatbot", page_icon="🍽️", layout="wide")

# 🎯 Welcome Screen (Only Show if Chat Not Started)
if not st.session_state.chat_started:
    st.title("🤖 Welcome to the Foodie Chatbot!")
    st.write("Your go-to chatbot for all things food: recipes, restaurant recommendations, and more!")

    st.subheader("✨ Features")
    st.markdown("""
    - 🍲 **Get Recipes**: Find delicious recipes based on ingredients or dish names.
    - 🛒 **Where to Buy**: Discover where you can buy specific food items.
    - 🍽️ **Restaurant Recommendations**: Find the best restaurants serving your favorite dishes.
    - 🎙️ **Voice Input**: Speak your query instead of typing.
    - 📜 **Chat History**: Track your past questions and answers.
    """)

    if st.button("🚀 Start Chat"):
        st.session_state.chat_started = True
        st.rerun()
    st.stop()

st.title("🍽️ Foodie Chatbot")

# 🎤 Function to capture voice input
def get_voice_input():
    recognizer = sr.Recognizer()
    with sr.Microphone() as source:
        st.info("🎤 Listening... Speak now!")
        try:
            audio = recognizer.listen(source, timeout=5)
            text = recognizer.recognize_google(audio)
            return text
        except sr.UnknownValueError:
            st.error("😕 Could not understand the audio.")
        except sr.RequestError:
            st.error("🔌 Speech Recognition service unavailable.")
    return ""

# 🎤 Voice Input Button
if st.button("🎤 Speak Query"):
    voice_text = get_voice_input()
    if voice_text:
        st.session_state["user_prompt"] = voice_text
    else:
        st.warning("No voice input detected.")

# 📝 User Input Text Area
user_prompt = st.text_area("Enter Any Food:", st.session_state.get("user_prompt", ""))

# ⚙️ Sidebar Settings
st.sidebar.header("⚙️ Settings")
output_format = st.sidebar.selectbox("Select Query Type", ["Recipe", "Where to Buy", "Best Restaurant"])
max_tokens = st.sidebar.slider("Response Length (Max Tokens)", 100, 1024, 500)
creative_mode = st.sidebar.checkbox("Enable Creative Mode", value=True)

# 📜 Chat History in Sidebar
st.sidebar.header("📜 Chat History")
if st.sidebar.button("🗑️ Clear Chat History"):
    st.session_state.chat_history = []
    st.session_state.feedback = {}

with st.sidebar.expander("🔍 View Chat History", expanded=False):
    for i, chat in enumerate(reversed(st.session_state.chat_history)):
        st.markdown(f"**User:** {chat['user']}")
        bot_preview = chat['bot'][:200] + ("..." if len(chat['bot']) > 200 else "")
        st.markdown(f"**Bot:** {bot_preview}")

        if len(chat['bot']) > 200:
            if st.toggle(f"📖 Show Full Response ({i+1})", key=f"toggle_{i}"):
                st.markdown(chat['bot'])

        feedback_value = st.session_state.feedback.get(chat['user'], "No Feedback Given")
        st.markdown(f"**Feedback:** {feedback_value}")
        st.markdown("---")

response_container = st.empty()
feedback_container = st.empty()

# 🚀 Generate Response
if st.button("Generate Response"):
    if user_prompt.strip():
        client = OpenAI(
            base_url="https://integrate.api.nvidia.com/v1",
            api_key="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"
        )

        messages = [{"role": "user", "content": f"Provide information about {user_prompt} as a {output_format.lower()}"}]

        try:
            completion = client.chat.completions.create(
                model="tiiuae/falcon3-7b-instruct",
                messages=messages,
                top_p=0.9 if creative_mode else 0.7,
                max_tokens=max_tokens,
                stream=True
            )

            response_text = ""
            progress_text = st.empty()

            for chunk in completion:
                if chunk.choices[0].delta.content is not None:
                    response_text += chunk.choices[0].delta.content
                    progress_text.markdown(f"### Generating... ⏳\n{response_text}")

            progress_text.empty()
            response_container.markdown(f"### Generated Response\n{response_text}")

            chat_entry = {"user": user_prompt, "bot": response_text}
            st.session_state.chat_history.append(chat_entry)

            feedback = feedback_container.radio(
                "Was this response helpful?",
                ["👍 Yes", "👎 No"],
                index=None,
                key=f"feedback_{len(st.session_state.chat_history)}",
                horizontal=True
            )

            st.session_state.feedback[user_prompt] = feedback

        except Exception as e:
            st.error(f"❌ Error: {e}")