import os
import platform

import openai
import chromadb
import langchain

from langchain.embeddings.openai import OpenAIEmbeddings
from langchain.vectorstores import Chroma
from langchain.text_splitter import TokenTextSplitter
from langchain.llms import OpenAI
from langchain.chat_models import ChatOpenAI
from langchain.chains import ChatVectorDBChain
from langchain.document_loaders import GutenbergLoader

from langchain.embeddings import LlamaCppEmbeddings
from langchain.llms import LlamaCpp

from langchain.output_parsers import StructuredOutputParser, ResponseSchema
from langchain.prompts import PromptTemplate, ChatPromptTemplate, HumanMessagePromptTemplate
from langchain.llms import OpenAI
from langchain.chains import LLMChain
from langchain.chains import SimpleSequentialChain

from langchain.output_parsers import PydanticOutputParser
from pydantic import BaseModel, Field, validator
from typing import List, Dict

# class AnswerTemplate(BaseModel):
#     type: List[str] = Field(description="What is the type of the trip: business, family, vactions. And with whom are you travelling? If can't anwser then leave it empty")
#     where: str = Field(description="Where is the user going? If can't anwser then leave it empty")
#     start_date: str = Field(description="What is the start date? If can't anwser then leave it empty")
#     end_date: str = Field(description="What is the end date? If can't anwser then leave it empty")
#     time_constrains: str = Field(description="Is there any time constrains? If can't anwser then leave it empty")
#     # dates: Dict[str, str] = Field(description="What are the importante dates and times? If can't anwser then leave it empty")
#     preferences: List[str] = Field(description="What does the user want to visit? If can't anwser then leave it empty")
#     conditions: str = Field(description="Does the user has any special medical condition? If can't anwser then leave it empty")
#     dist_range: str = Field(description="Max distance from a place? If can't anwser then leave it empty")
#     # missing: str = Field(description="Is any more information needed?")

class AnswerTemplate(BaseModel):
    answer: str = Field(description="Response")


class Gather_Agent():
    def __init__(self):

        self.model_name = "gpt-4"
        self.model = OpenAI(model_name=self.model_name, temperature=0)

        self.output_parser = PydanticOutputParser(pydantic_object=AnswerTemplate)
        self.format_instructions = self.output_parser.get_format_instructions()

        # self.prompt = PromptTemplate(
        #     template="""\
        #             ### Instruction
        #             You are Trainline Mate an helpful assistant that plans tours for people at trainline.com.
        #             As a smart itinerary planner with extensive knowledge of places around the
        #             world, your task is to determine the user's travel destinations and any specific interests or preferences from
        #             their message. Here is the history that you have so far: {history} \n### User: \n{input}
        #             \n### Response: {format_instructions}
        #             """,
        #     input_variables=["input", "history", "format_instructions"]
        # )

        self.prompt = PromptTemplate(
            template="""\
                    ### Instruction
                    You are Trainline Mate an helpful assistant that plans tours for people at trainline.com.
                    As a smart itinerary planner with extensive knowledge of places around the
                    world, your task is to determine the user's travel destinations and any specific interests or preferences from
                    their message.
                    ### Task
                    From the following history and user input you should be able to retrieve and resume all the following information:
                    Where is the trip to, start and end dates for the trip, is there any time constrain, activity preferences,
                    is there any medical condition and is there a maximum distance range in which the activities have to be.
                    ### History
                    Here is the history that you have so far: {history} 
                    ### User: \n{input}
                    \n### Response:
                    """,
            input_variables=["input", "history"]
        )
    
    def format_prompt(self, input, history):
        # return self.prompt.format_prompt(history=history, input=input, format_instructions=self.format_instructions)
        return self.prompt.format_prompt(input=input, history=history)
    
    def get_parsed_result(self, input):
        result = self.model(input.to_string())
        # return self.output_parser.parse(result)
        return result