from langchain.chat_models import ChatOpenAI
from langchain.schema import AIMessage, HumanMessage
import openai
import gradio as gr
from full_chain import get_response

import os

api_key = os.getenv("OPENAI_API_KEY")
client = openai.OpenAI(api_key=api_key)


def create_hyperlink(url, title, domain):
    return f"<a href='{url}'>{title}</a>" + " (" + domain + ")"


def predict(message, history):
    print("get_responses: ")
    # print(get_response(message, rerank_type="crossencoder"))
    responder, links, titles, domains = get_response(message, rerank_type="crossencoder")
    for i in range(len(links)):
        links[i] = create_hyperlink(links[i], titles[i], domains[i])

    out = responder + "\n" + "\n".join(links)

    return out


gr.ChatInterface(predict,
                examples = [
                    "How many Americans Smoke?",
                    "What are some measures taken by the Indian Government to reduce the smoking population?",
                    "Does smoking negatively affect my health?"
                ]
                ).launch()