import json
from langchain_core.prompts import MessagesPlaceholder
from langchain_core.prompts import ChatPromptTemplate
from langchain_core.messages import AIMessage, HumanMessage
from langchain.agents.format_scratchpad.openai_tools import (
    format_to_openai_tool_messages,
) 
from langchain import PromptTemplate, LLMChain
import os
from dotenv import load_dotenv
from langchain.memory import ConversationBufferWindowMemory
from langchain.prompts import ChatPromptTemplate, MessagesPlaceholder, HumanMessagePromptTemplate
from langchain.chains import ConversationChain
from langchain_mongodb.chat_message_histories import MongoDBChatMessageHistory
from pymongo import MongoClient
from langchain_openai import ChatOpenAI
load_dotenv()


default_json = {}

class FormFillingBot:
    def __init__(self):
        self.llm = ChatOpenAI(model="gpt-3.5-turbo", openai_api_key=os.getenv("OPENAI_API_KEY"), temperature=0)
    def get_current_form_json(self,uuid):
    
        CONNECTION_STRING = "mongodb+srv://dharasolanki:8apF57ZCeX16fKny@cluster0.egh8f3k.mongodb.net/?retryWrites=true&w=majority&appName=Cluster0"

            # Connect to the MongoDB client
        client = MongoClient(CONNECTION_STRING)

            # Select the database and collection
        db = client['benefitboost']
        collection = db['currentFormJson']
        # The UUID to search for
        uuid_to_find = uuid

        # Find the document with the specified UUID
        document =collection.find_one({"uuid": uuid_to_find})

        if document:
            currentformjson = document.get('currentformjson', None)
            if currentformjson:
                print("Current Form JSON:", currentformjson)
            else:
                print("The 'currentformjson' field is not found in the document.")
        else:
            print(f"No document found with UUID: {uuid_to_find}")
        return currentformjson 

    def form_filling(self, form_data,default_json):
        "Use this tool for form filling task"
        friendly_prompt = PromptTemplate(
            input_variables=["user_input", "default_json"],
            template="""You are a form-filling expert that takes the data from user input and finds the related field in {default_json} and returns the json provided with the details of the user. If you do not encounter fields of form then give response as you are a question-answering bot. If you do not find the details put it blank, do not try to fill every detail if it is not present in user_input. Here are the details entered by the user: {user_input}"""
        )
        friendly_chain = LLMChain(llm=self.llm, prompt=friendly_prompt)
        response = friendly_chain.invoke({"user_input": form_data, "default_json": default_json})
        return response["text"]