# from langchain_community.llms import HuggingFaceEndpoint
# from langchain.prompts import PromptTemplate
# from langchain.schema import AIMessage, HumanMessage
# from langchain.chains import LLMChain
import gradio as gr
import os

from crew import CryptoCrew

from dotenv import load_dotenv

load_dotenv()

def predict(message):
    # company = input(
    #     dedent("""
    #         Which cryptocurrency are you looking to delve into?
    # """))
    # history_langchain_format = []
    # for human, ai in history:
    #     history_langchain_format.append(HumanMessage(content=human))
    #     history_langchain_format.append(AIMessage(content=ai))
    # history_langchain_format.append(HumanMessage(content=message))
    # gpt_response = llm(history_langchain_format)
    # response = llm_chain.invoke(message)['text']

    crypto_crew = CryptoCrew(company)
    response = "## Here is the Report\n\n" + crypto_crew.run()
    
    return response

gr.ChatInterface(predict).launch()

# if __name__ == "__main__":
#     print("## Welcome to Crypto Analysis Crew")
#     print('-------------------------------')
#     company = input(
#         dedent("""
#             Which cryptocurrency are you looking to delve into?
#     """))

#     crypto_crew = CryptoCrew(company)
#     result = crypto_crew.run()
#     print("\n\n########################")
#     print("## Here is the Report")
#     print("########################\n")
    
# print(result)