utils.py

import requests
import json
import os
from datetime import datetime
from copy import copy

def clear_chat():
    return '', []

async def model_response(
        content,
        chat_history,
        s3_session,
        initialized_models,
        gen_lib,
        model_name,
        model_params
        ):
    print(f'{model_name} response')
    chat_history.append([content])
    res = gen_lib[model_name](initialized_models[model_name], chat_history, model_params)
    chat_history[-1].append(res)
    send_to_s3(res, f'protobench/{model_name}_{str(datetime.now()).replace(" ", "_")}.json', s3_session)
    return '', chat_history

def send_to_s3(data, name, session):
    session.put_object(Bucket=os.getenv('S3_BUCKET'), Key=name, Body=json.dumps(data))

# def giga_gen(content, chat_history, model, s3_session):
#     chat_history.append([content])
#     res = response_gigachat(chat_history,'auth_token.json')
#     chat_history[-1].append(res)
#     send_to_s3(res, f'protobench/giga_{str(datetime.now()).replace(" ", "_")}.json', s3_session)
#     return '', chat_history

# def tiny_gen(content, chat_history, model, s3_session):
#     chat_history.append([content])
#     res = response_tinyllama(model, chat_history)
#     chat_history[-1].append(res)
#     send_to_s3(res, f'protobench/tiny_{str(datetime.now()).replace(" ", "_")}.json', s3_session)
#     return '', chat_history

# def qwen_gen(content, chat_history, model, s3_session):
#     chat_history.append([content])
#     res = response_qwen2ins1b(model, chat_history)
#     chat_history[-1].append(res)
#     send_to_s3(res, f'protobench/qwen_{str(datetime.now()).replace(" ", "_")}.json', s3_session)
#     return '', chat_history