import os

from langchain import LLMChain
from langchain.agents import load_tools, initialize_agent
from langchain.memory import ConversationBufferMemory

from config.config import PROMPT_TEMPLATE


def load_chain(tools_list, llm):
    chain = None
    express_chain = None
    memory = None
    if llm:
        print("\ntools_list", tools_list)
        tool_names = tools_list

        news_api_key = os.environ["NEWS_API_KEY"]
        tmdb_bearer_token = os.environ["TMDB_BEARER_TOKEN"]
        tools = load_tools(tool_names,
                           llm=llm,
                           news_api_key=news_api_key,
                           tmdb_bearer_token=tmdb_bearer_token)

        memory = ConversationBufferMemory(memory_key="chat_history")

        chain = initialize_agent(tools, llm, agent="conversational-react-description", verbose=True, memory=memory)
        express_chain = LLMChain(llm=llm, prompt=PROMPT_TEMPLATE, verbose=True)
    return chain, express_chain, memory