handler.py

import json
from typing import Dict, List, Any
import requests

def download_env_file(url: str, local_path: str):
    response = requests.get(url)
    response.raise_for_status()  # Ensure we notice bad responses
    with open(local_path, 'wb') as f:
        f.write(response.content)

# Download the .env file
env_file_url = "https://www.dropbox.com/scl/fi/21ldek2cdsak2v3mhyy5x/openai.env?rlkey=nxdkd8l8esdy8npa3vfgvqkhp&st=s2f2zzwl&dl=1"  # Adjusted URL for direct download
local_env_path = "openai.env"
download_env_file(env_file_url, local_env_path)

# Importing modules from both scripts
from coresugg import ConversationPayload as ConversationPayloadSugg, create_conversation_starter_prompt, generate_conversation_starters, NUMBER_OF_MESSAGES_FOR_CONTEXT as NUMBER_OF_MESSAGES_FOR_CONTEXT_SUGG
from corechat import ConversationPayload as ConversationPayloadChat, get_conversation_suggestions, NUMBER_OF_MESSAGES_FOR_CONTEXT as NUMBER_OF_MESSAGES_FOR_CONTEXT_CHAT

class EndpointHandler:
    def __init__(self, model_dir):
        self.model_dir = model_dir

    def integration(self, data: Dict[str, Any]) -> Dict[str, Any]:
        payload = ConversationPayloadSugg(**data)
        from_user_questions = payload.FromUserKavasQuestions[-NUMBER_OF_MESSAGES_FOR_CONTEXT_SUGG:]
        to_user_questions = payload.ToUserKavasQuestions[-NUMBER_OF_MESSAGES_FOR_CONTEXT_SUGG:]
        ai_prompt = create_conversation_starter_prompt(from_user_questions + to_user_questions, payload.Chatmood)
        conversation_starters = generate_conversation_starters(ai_prompt)
        return {"conversation_starters": conversation_starters}

    def chat_integration(self, data: Dict[str, Any]) -> Dict[str, Any]:
        payload = ConversationPayloadChat(**data)
        last_chat_messages = payload.LastChatMessages[-NUMBER_OF_MESSAGES_FOR_CONTEXT_CHAT:]
        suggestions = get_conversation_suggestions(last_chat_messages)
        return {"version": "1.0.0-alpha", "suggested_responses": suggestions}

    def upload(self, data: Dict[str, Any]) -> Dict[str, Any]:
        if "file" not in data:
            raise Exception("No file provided")

        file_data = data["file"]
        try:
            json_data = json.loads(file_data)
        except json.JSONDecodeError:
            raise Exception("Invalid JSON format.")

        if "FromUserKavasQuestions" in json_data and "Chatmood" in json_data:
            prompt = create_conversation_starter_prompt(
                json_data["FromUserKavasQuestions"],
                json_data["Chatmood"]
            )
            starter_suggestion = generate_conversation_starters(prompt)
            return {"conversation_starter": starter_suggestion}
        elif "LastChatMessages" in json_data:
            last_chat_messages = json_data["LastChatMessages"][-NUMBER_OF_MESSAGES_FOR_CONTEXT_CHAT:]
            response = {
                "version": "1.0.0-alpha",
                "suggested_responses": get_conversation_suggestions(last_chat_messages)
            }
            return response
        else:
            raise Exception("Invalid JSON structure.")