import sys
import toml
from omegaconf import OmegaConf
import os
from transformers import pipeline
import numpy as np
import tempfile
import openai
from pinecone.grpc import PineconeGRPC as Pinecone  # Corrected Pinecone import
from pinecone import ServerlessSpec
import streamlit as st
from PIL import Image
from gtts import gTTS 
from io import BytesIO
import time  # For delay during index readiness check

# Pinecone and OpenAI setup
pinecone_api_key = os.getenv("PINECONE_API_KEY")
openai.api_key = os.getenv("OPENAI_API_KEY")

# Initialize Pinecone client
pc = Pinecone(api_key=pinecone_api_key)

# Create or retrieve Pinecone index
index_name = "farming-assistant"
dimension = 1536  # Adjust dimension to match OpenAI embeddings

if not pc.has_index(index_name):
    pc.create_index(
        name=index_name,
        dimension=dimension,
        metric="cosine",
        spec=ServerlessSpec(
            cloud='aws',
            region='us-east-1'
        )
    )

# Wait for the index to be ready
while not pc.describe_index(index_name).status['ready']:
    time.sleep(1)

index = pc.Index(index_name)  # Corrected method to connect to the index

master_prompt = """
As a Natural Farming Fertilizers Assistant, you will assist the user with any farming-related question, always willing to answer any question and provide useful organic farming advice in the following format.
...
[Words of encouragement]
"""

denial_response = "Database scraping is not permitted. Please abide by the terms of membership, and reach out with any collaboration requests via email"

# Temporary file system created: used for text-to-speech
fp = tempfile.TemporaryFile()

def generate_response(question):
    # Generate embeddings for the query using OpenAI
    query_embedding = openai.Embedding.create(
        input=question,
        model="text-embedding-ada-002"
    )["data"][0]["embedding"]

    # Query Pinecone for relevant documents
    query_result = index.query(
        vector=query_embedding,
        top_k=5,
        include_metadata=True,
        namespace="farming-assistant"
    )
    
    # Extract relevant information
    contexts = [match["metadata"]["text"] for match in query_result["matches"]]
    context_text = "\n".join(contexts)

    # Generate a final response using OpenAI
    response = openai.ChatCompletion.create(
        model="gpt-3.5-turbo",
        messages=[
            {"role": "system", "content": master_prompt},
            {"role": "user", "content": question + "\n\n" + context_text}
        ]
    )["choices"][0]["message"]["content"]

    return response

def upsert_vectors(vectors):
    # Upsert vectors into Pinecone index
    index.upsert(
        vectors=vectors,
        namespace="farming-assistant"
    )

def launch_bot():
    if 'cfg' not in st.session_state:
        questions = list(eval(os.environ['examples']))
        cfg = OmegaConf.create({
            'api_key': str(os.environ['api_key']),
            'title': os.environ['title'],
            'description': os.environ['description'],
            'examples': questions,
            'source_data_desc': os.environ['source_data_desc']
        })
        st.session_state.cfg = cfg

    cfg = st.session_state.cfg
    st.set_page_config(page_title=cfg.title, layout="wide")

    # Left side content
    with st.sidebar:
        image = Image.open('Pinecone-logo.png')  # Update with appropriate logo
        st.markdown(f"## Welcome to {cfg.title}\n\n"
                    f"This demo uses an AI organic farming expert and carefully curated library system to achieve greater accuracy in agronomics and agricultural methodology. Created by Copyleft Cultivars, a nonprofit, we hope you enjoy this beta-test early access version.\n\n")

        st.markdown("---")
        st.markdown(
            "## Democratizing access to farming knowledge.\n"
            "This app was built with the support of our Patreon subscribers. Thank you! [Click here to join our patreon or upgrade your membership.](https://www.patreon.com/CopyleftCultivarsNonprofit). \n"
            "Use of this app indicates agreement to our terms of membership, available on Copyleftcultivars.com as well as an agreement not to attempt to access our databases in any way. \n"
        )
        st.markdown("---")
        st.image(image, width=250)

    st.markdown(f"<center> <h2> Copyleft Cultivars AI Agriculture Assistant demo: {cfg.title} </h2> </center>", unsafe_allow_html=True)
    st.markdown(f"<center> <h4> {cfg.description} <h4> </center>", unsafe_allow_html=True)

    if "messages" not in st.session_state.keys():
        st.session_state.messages = [{"role": "assistant", "content": "How may I help you?"}]

    # Display chat messages
    for message in st.session_state.messages:
        with st.chat_message(message["role"]):
            st.write(message["content"])

    # User-provided prompt
    if prompt := st.chat_input():
        st.session_state.messages.append({"role": "user", "content": prompt})
        with st.chat_message("user"):
            st.write(prompt)
        if any(variant in prompt for variant in ("JSON", "json", "jsON", "jSon", "Json", "jsoN", "JSon")):
            if "ADMINISTRATION" not in prompt:
                message = {"role": "assistant", "content": denial_response}
                st.session_state.messages.append(message)
                st.chat_message("assistant")
                st.write(denial_response)

    # Generate a new response if the last message is not from assistant
    if st.session_state.messages[-1]["role"] != "assistant":
        with st.chat_message("assistant"):
            with st.spinner("Thinking..."):
                prompt2 = prompt + master_prompt
                response = generate_response(prompt2)
                st.write(response)

                message = {"role": "assistant", "content": response}
                st.session_state.messages.append(message)

                text = " :blue[Convert to Audio ]  🔊 "
                # Converts Response to Audio
                with st.expander(text, expanded=False):
                    sound_file = BytesIO()
                    tts = gTTS(response, lang='en')
                    tts.write_to_fp(sound_file)
                        
                    st.audio(sound_file)

                st.markdown("[Sign up for Premium](https://www.patreon.com/CopyleftCultivarsNonprofit)", unsafe_allow_html=True)

if __name__ == "__main__":
    launch_bot()