chain_app.py

import chainlit as cl
from gradio_client import Client
from openai import OpenAI
from groq import Groq
import requests
from chainlit.input_widget import Select, Slider
import os
import cohere 
from huggingface_hub import InferenceClient


hf_token = os.environ.get("HF_TOKEN")
hf_token_llama_3_1 = os.environ.get('HF_TOKEN_FOR_31')
openai_api_key = os.environ.get('OPENAI_API_KEY')
groq_api_key = os.environ.get('GROQ_API_KEY')
cohere_api_key = os.environ.get('COHERE_API_KEY')


hf_text_client = Client("Artin2009/text-generation", hf_token=hf_token)
# hf_image_client = Client('Artin2009/image-generation')
openai_client = OpenAI(api_key=openai_api_key)
groq_client = Groq(api_key=groq_api_key)

co = cohere.Client(
  api_key=cohere_api_key,
) 

# API_URL = "https://api-inference.huggingface.co/models/PartAI/TookaBERT-Large"
# headers = {"Authorization": f"Bearer {hf_token}"}


# def query(payload):
# 	response = requests.post(API_URL, headers=headers, json=payload)
# 	return response.json()

@cl.set_starters
async def set_starters():
    return [
        cl.Starter(
            label="Morning routine ideation",
            message="Can you help me create a personalized morning routine that would help increase my productivity throughout the day? Start by asking me about my current habits and what activities energize me in the morning.",
            ),

        cl.Starter(
            label="Explain superconductors",
            message="Explain superconductors like I'm five years old.",
            ),
        cl.Starter(
            label="Python script for daily email reports",
            message="Write a script to automate sending daily email reports in Python, and walk me through how I would set it up.",
            ),
        cl.Starter(
            label="Text inviting friend to wedding",
            message="Write a text asking a friend to be my plus-one at a wedding next month. I want to keep it super short and casual, and offer an out.",
            )
        ]


@cl.set_chat_profiles
async def chat_profile():
    return [
        cl.ChatProfile(
            name="None",
            markdown_description="None",
        ),
        cl.ChatProfile(
            name="neural-brain-AI",
            markdown_description="The main model of neural brain",
            starters = [
                cl.Starter(
                    label="Morning routine ideation",
                    message="Can you help me create a personalized morning routine that would help increase my productivity throughout the day? Start by asking me about my current habits and what activities energize me in the morning.",
                    ),
        
                cl.Starter(
                    label="Explain superconductors",
                    message="Explain superconductors like I'm five years old.",
                    ),
                cl.Starter(
                    label="Python script for daily email reports",
                    message="Write a script to automate sending daily email reports in Python, and walk me through how I would set it up.",
                    ),
                cl.Starter(
                    label="Text inviting friend to wedding",
                    message="Write a text asking a friend to be my plus-one at a wedding next month. I want to keep it super short and casual, and offer an out.",
            )
         ]
        ),
        cl.ChatProfile(
            name="Dorna-AI",
            markdown_description="One of the open-sourced models that neural brain team fine-tuned",
        ),
        # cl.ChatProfile(
        #     name='Image-Generation',
        #     markdown_description='Our image generation model, has a performance like midjourney',
        # ),
        cl.ChatProfile(
            name="gpt4-o-mini",
            markdown_description="The best state of the art openai model",
        ),
        cl.ChatProfile(
            name="GPT-4",
            markdown_description="OpenAI's GPT-4 model",
        ),
        cl.ChatProfile(
            name="gpt-3.5-turbo",
            markdown_description="OpenAI's GPT-3.5 Turbo model",
        ),
        # cl.ChatProfile(
        #     name="GPT-3.5-turbo-0125",
        #     markdown_description="OpenAI's GPT-3.5 Turbo 0125 model",
        # ),
        cl.ChatProfile(
            name="gpt-3.5-turbo-1106",
            markdown_description="OpenAI's GPT-3.5 Turbo 1106 model",
        ),
        # cl.ChatProfile(
        #     name="davinci-002",
        #     markdown_description="OpenAI's Davinci-002 model",
        # ),
        cl.ChatProfile(
            name="TTS",
            markdown_description="OpenAI's Text-to-Speech model",
        ),
        cl.ChatProfile(
            name="Qwen2-57B",
            markdown_description="Qwen second generation model with 57B parameters",
        ),
        cl.ChatProfile(
            name="Qwen2-7B",
            markdown_description="Qwen second generation model with 7B parameters",
        ),
        cl.ChatProfile(
            name="Qwen2-1.5B",
            markdown_description="Qwen second generation model with 1.5B parameters",
        ),
        cl.ChatProfile(
            name="Qwen2-0.5B",
            markdown_description="Qwen second generation model with 0.5B parameters",
        ),
        cl.ChatProfile(
            name="Qwen1.5-110B",
            markdown_description="Qwen first generation improved model with 110B parameters",
        ),
        # cl.ChatProfile(
        #     name="Qwen1.5-72B",
        #     markdown_description="Qwen first generation improved model with 72B parameters",
        # ),
        cl.ChatProfile(
            name="Qwen1.5-32B",
            markdown_description="Qwen first generation improved model with 32B parameters",
        ),
        cl.ChatProfile(
            name="Qwen1.5-2.7B",
            markdown_description="Qwen first generation improved model with 2.7B parameters",
        ),
        # cl.ChatProfile(
        #     name="Qwen-72B",
        #     markdown_description="Qwen first generation model with 72B parameters",
        # ),
        # cl.ChatProfile(
        #     name="Qwen-14B",
        #     markdown_description="Qwen first generation model with 14B parameters",
        # ),
        # cl.ChatProfile(
        #     name="Qwen-7B",
        #     markdown_description="Qwen first generation model with 7B parameters",
        # ),
        cl.ChatProfile(
            name="Llama-3.1-405B",
            markdown_description="Meta Open Source Model Llama with 405B parameters",
        ),
        cl.ChatProfile(
            name="Llama-3.1-70B",
            markdown_description="Meta Open Source Model Llama with 70B parameters",
        ),
        cl.ChatProfile(
            name="Llama-3.1-8B",
            markdown_description="Meta Open Source Model Llama with 8B parameters",
        ),
        cl.ChatProfile(
            name="Llama-3-70B",
            markdown_description="Meta Open Source model Llama-3 with 70B parameters",
        ),
        cl.ChatProfile(
            name='Aya-35B',
            markdown_description='Cohere open sourced AI model with 35B parameters'
        ),
        cl.ChatProfile(
            name='Aya-23B',
            markdown_description='Cohere open sourced AI model with 23B parameters'
        ),
        cl.ChatProfile(
            name='Command-R-Plus',
            markdown_description='Cohere open sourced AI model named Command R plus'

        ),
        cl.ChatProfile(
            name='Command-R',
            markdown_description='Cohere open sourced AI model named Command R'

        ),
        cl.ChatProfile(
            name='Command-Light',
            markdown_description='Cohere open sourced AI model named Command R'

        ),
        cl.ChatProfile(
            name='Command-Light-Nightly',
            markdown_description='Cohere open sourced AI model named Command R'

        ),
        cl.ChatProfile(
            name='Command-Nightly',
            markdown_description='Cohere open sourced AI model named Command R'

        ),
        cl.ChatProfile(
            name='Command',
            markdown_description='Cohere open sourced AI model named Command R'

        ),
        cl.ChatProfile(
            name="Llama-3-8B",
            markdown_description="Meta Open Source model Llama-2 with 7B parameters",
        ),
        cl.ChatProfile(
            name = "gemma2-9B",
            markdown_description = 'Google Generation 2 Open Source LLM with 9B parameters'
        ),
        cl.ChatProfile(
            name = "gemma-7B",
            markdown_description = 'Google Generation 1 Open Source LLM with 7B parameters'
        ),
        cl.ChatProfile(
            name="zephyr-7B",
            markdown_description="Open Source model Zephyr with 7B parameters",
        ),
        cl.ChatProfile(
            name='mistral-nemo-12B',
            markdown_description='mistral open source LLM with 12B parameters'
        ),
        cl.ChatProfile(
            name='mixtral-8x7B',
            markdown_description = 'mistral open source LLM with 7B parameters'
        ),
        # cl.ChatProfile(
        #     name="Toka-353M",
        #     markdown_description="PartAI Open Source model Toka with 353M parameters",
        # )
    ]

@cl.on_chat_start
async def on_chat_start():
    chat_profile = cl.user_session.get("chat_profile")
    if not chat_profile:
        await cl.Message(
            content='please choose a model to start'
        ).send()
    
    if chat_profile == 'neural-brain-AI':
        await cl.ChatSettings(
            [
            Select(
                id="NB-Model",
                label="NeuralBrain - Models",
                values=["Neural Brain AI"],
                initial_index=0,
                )
            ]
        ).send()
        await cl.Message(
            content="Hello, I am the main model of neural brain team, i am an instance of ChatGPT-4, This team finetuned me and i am ready to help you"
        ).send()

    if chat_profile == 'Dorna-AI':
        await cl.ChatSettings(
            [
             Select(
                    id="param_3",
                    label="Parameter 3",
                    values=["512"],  # Only one selectable value
                    initial_index=0,
                    tooltip="Config parameter 3 (e.g., max tokens)",
                ),
                Select(
                    id="param_4",
                    label="Parameter 4",
                    values=["0.7"],  # Only one selectable value
                    initial_index=0,
                    tooltip="Config parameter 4 (e.g., temperature)",
                ),
                Select(
                    id="param_5",
                    label="Parameter 5",
                    values=["0.95"],  # Only one selectable value
                    initial_index=0,
                    tooltip="Config parameter 5 (e.g., top_p)",
                ),
                Select(
                    id="api_name",
                    label="API Name",
                    values=["/chat"],
                    initial_index=0,
                ),
            ]
        ).send()

        await cl.Message(
            content='my name is Dorna, Your AI Assistant designed by neural nexus team. i was made by Artin Daneshvar and Sadra Noadoust, 2 iranian students!'
        ).send()
    if chat_profile == 'gpt4-o-mini':
        await cl.ChatSettings(
            [
                Select(
                    id="OpenAI-Model",
                    label="OpenAI - Model",
                    values=["gpt4-o-mini"],
                    initial_index=0,
                ),
                Slider(
                    id="Temperature",
                    label="Model Temperature",
                    initial=0.7,
                    min=0,
                    max=1,
                    step=0.1,
                ),
            ]
        ).send()
        await cl.Message(
            content="Im one of the best models openai have released and i am configured by two iranian boys to help you."
        ).send()

    # if chat_profile == 'Image-Generation':
    #     image = cl.Image(path='cat.png', name="result", display="inline")
    #     await cl.Message(
    #         content="I can make high quality & resoloution images for you, This is an example of what i can do!",
    #         elements=[image],
    #         ).send()
    if chat_profile == 'GPT-4':
        await cl.ChatSettings(
            [
                Select(
                    id="OpenAI-Model",
                    label="OpenAI - Model",
                    values=["gpt-4"],
                    initial_index=0,
                ),
                Slider(
                    id="Temperature",
                    label="Model Temperature",
                    initial=0.7,
                    min=0,
                    max=1,
                    step=0.1,
                ),
            ]
        ).send()
        await cl.Message(
            content="Im OpenAI's latest and biggest model.  i was configured by Artin Daneshvar and Sadra Noadoust, 2 iranian students to help you, how can i assist you today ? "
        ).send()

    if chat_profile == 'gpt-3.5-turbo':
        await cl.ChatSettings(
            [
                Select(
                    id="OpenAI-Model",
                    label="OpenAI - Model",
                    values=["gpt-3.5-turbo"],
                    initial_index=0,
                ),
                Slider(
                    id="Temperature",
                    label="Model Temperature",
                    initial=0.7,
                    min=0,
                    max=1,
                    step=0.1,
                ),
            ]
        ).send()
        await cl.Message(
            content="Im one of the OpenAI's models. one of the best models. i was configured by Artin Daneshvar and Sadra Noadoust, 2 iranian students to help you, how can i assist you today ? "
        ).send()
    # if chat_profile == 'GPT-3.5-turbo-0125':
    #     await cl.ChatSettings(
    #         [
    #             Select(
    #                 id="OpenAI-Model",
    #                 label="OpenAI - Model",
    #                 values=["gpt-3.5-turbo-0125"],
    #                 initial_index=0,
    #             ),
    #             Slider(
    #                 id="Temperature",
    #                 label="Model Temperature",
    #                 initial=0.7,
    #                 min=0,
    #                 max=1,
    #                 step=0.1,
    #             ),
    #         ]
    #     ).send()
        # await cl.Message(
        #     content="Im one of the OpenAI's models. one of the best models. i was configured by Artin Daneshvar and Sadra Noadoust, 2 iranian students to help you, how can i assist you today ? "
        # ).send()

    if chat_profile == 'gpt-3.5-turbo-1106':
        await cl.ChatSettings(
            [
                Select(
                    id="OpenAI-Model",
                    label="OpenAI - Model",
                    values=["gpt-3.5-turbo-1106"],
                    initial_index=0,
                ),
                Slider(
                    id="Temperature",
                    label="Model Temperature",
                    initial=0.7,
                    min=0,
                    max=1,
                    step=0.1,
                ),
            ]
        ).send()
        await cl.Message(
            content="Im one of the OpenAI's models. one of the best models. i was configured by Artin Daneshvar and Sadra Noadoust, 2 iranian students to help you, how can i assist you today ? "
        ).send()

    # if chat_profile == 'davinci-002':
    #     await cl.ChatSettings(
    #         [
    #             Select(
    #                 id="OpenAI-Model",
    #                 label="OpenAI - Model",
    #                 values=["davinci-002"],
    #                 initial_index=0,
    #             ),
    #             Slider(
    #                 id="Temperature",
    #                 label="Model Temperature",
    #                 initial=0.7,
    #                 min=0,
    #                 max=1,
    #                 step=0.1,
    #             ),
    #         ]
    #     ).send()
    #     await cl.Message(
    #         content="Im one of the OpenAI's models. i was configured by Artin Daneshvar and Sadra Noadoust, 2 iranian students to help you, how can i assist you today ? "
    #     ).send()
    if chat_profile == 'TTS':
        await cl.Message(
            content="Im TTS. of the best models OpenAI ever created. i can convert text to speech! . i was configured by Artin Daneshvar and Sadra Noadoust, 2 iranian students to help you, how can i assist you today ? "
        ).send()

    if chat_profile == 'Qwen2-57B':
        await cl.ChatSettings(
            [
                Select(
                    id="Qwen-Model",
                    label="Qwen - Model",
                    values=["Qwen2-57B"],
                    initial_index=0,
                ),
                Slider(
                    id="Temperature",
                    label="Model Temperature",
                    initial=0.7,
                    min=0,
                    max=1,
                    step=0.1,
                ),
            ]
        ).send()
        await cl.Message(
            content='Im Qwens second generation second large model and i am configured by two iranian boys Artin Daneshvar and Sadra Noadoust to help you out!',
        ).send()
        
    if chat_profile == 'Qwen2-7B':
        await cl.ChatSettings(
            [
                Select(
                    id="Qwen-Model",
                    label="Qwen - Model",
                    values=["Qwen2-7B"],
                    initial_index=0,
                ),
                Slider(
                    id="Temperature",
                    label="Model Temperature",
                    initial=0.7,
                    min=0,
                    max=1,
                    step=0.1,
                ),
            ]
        ).send()
        await cl.Message(
            content='Im Qwens second generation third large model and i am configured by two iranian boys Artin Daneshvar and Sadra Noadoust to help you out!',
        ).send()
        
    if chat_profile == 'Qwen2-1.5B':
        await cl.ChatSettings(
            [
                Select(
                    id="Qwen-Model",
                    label="Qwen - Model",
                    values=["Qwen2-1.5B"],
                    initial_index=0,
                ),
                Slider(
                    id="Temperature",
                    label="Model Temperature",
                    initial=0.7,
                    min=0,
                    max=1,
                    step=0.1,
                ),
            ]
        ).send()
        await cl.Message(
            content='Im Qwens second generation small model and i am configured by two iranian boys Artin Daneshvar and Sadra Noadoust to help you out!',
        ).send()

    if chat_profile == 'Qwen2-0.5B':
        await cl.ChatSettings(
            [
                Select(
                    id="Qwen-Model",
                    label="Qwen - Model",
                    values=["Qwen2-0.5B"],
                    initial_index=0,
                ),
                Slider(
                    id="Temperature",
                    label="Model Temperature",
                    initial=0.7,
                    min=0,
                    max=1,
                    step=0.1,
                ),
            ]
        ).send()
        await cl.Message(
            content='Im Qwens second generation small model and i am configured by two iranian boys Artin Daneshvar and Sadra Noadoust to help you out!',
        ).send()

    if chat_profile == 'Qwen1.5-110B':
        await cl.ChatSettings(
            [
                Select(
                    id="Qwen-Model",
                    label="Qwen - Model",
                    values=["Qwen1.5-110B"],
                    initial_index=0,
                ),
                Slider(
                    id="Temperature",
                    label="Model Temperature",
                    initial=0.7,
                    min=0,
                    max=1,
                    step=0.1,
                ),
            ]
        ).send()
        await cl.Message(
            content='Im Qwens 1.5th generation Large model and i am configured by two iranian boys Artin Daneshvar and Sadra Noadoust to help you out!',
        ).send()
        
    # if chat_profile == 'Qwen1.5-72B':
    #     await cl.ChatSettings(
    #         [
    #             Select(
    #                 id="Qwen-Model",
    #                 label="Qwen - Model",
    #                 values=["Qwen1.5-72B"],
    #                 initial_index=0,
    #             ),
    #             Slider(
    #                 id="Temperature",
    #                 label="Model Temperature",
    #                 initial=0.7,
    #                 min=0,
    #                 max=1,
    #                 step=0.1,
    #             ),
    #         ]
    #     ).send()
    #     await cl.Message(
    #         content='Im Qwens 1.5th generation second Large model and i am configured by two iranian boys Artin Daneshvar and Sadra Noadoust to help you out!',
    #     ).send()

    if chat_profile == 'Qwen1.5-32B':
        await cl.ChatSettings(
            [
                Select(
                    id="Qwen-Model",
                    label="Qwen - Model",
                    values=["Qwen1.5-32B"],
                    initial_index=0,
                ),
                Slider(
                    id="Temperature",
                    label="Model Temperature",
                    initial=0.7,
                    min=0,
                    max=1,
                    step=0.1,
                ),
            ]
        ).send()
        await cl.Message(
            content='Im Qwens 1.5th generation third Large model and i am configured by two iranian boys Artin Daneshvar and Sadra Noadoust to help you out!',
        ).send()

    if chat_profile == 'Qwen1.5-2.7B':
        await cl.ChatSettings(
            [
                Select(
                    id="Qwen-Model",
                    label="Qwen - Model",
                    values=["Qwen1.5-2.7B"],
                    initial_index=0,
                ),
                Slider(
                    id="Temperature",
                    label="Model Temperature",
                    initial=0.7,
                    min=0,
                    max=1,
                    step=0.1,
                ),
            ]
        ).send()
        await cl.Message(
            content='Im Qwens 1.5th generation small model and i am configured by two iranian boys Artin Daneshvar and Sadra Noadoust to help you out!',
        ).send()
        
    # if chat_profile == 'Qwen-72B':
    #     await cl.ChatSettings(
    #         [
    #             Select(
    #                 id="Qwen-Model",
    #                 label="Qwen - Model",
    #                 values=["Qwen-72B"],
    #                 initial_index=0,
    #             ),
    #             Slider(
    #                 id="Temperature",
    #                 label="Model Temperature",
    #                 initial=0.7,
    #                 min=0,
    #                 max=1,
    #                 step=0.1,
    #             ),
    #         ]
    #     ).send()
    #     await cl.Message(
    #         content='Im Qwens open source Ai model and i am configured by two iranian boys Artin Daneshvar and Sadra Noadoust to help you out!',
    #     ).send()

    # if chat_profile == 'Qwen-14B':
    #     await cl.ChatSettings(
    #         [
    #             Select(
    #                 id="Qwen-Model",
    #                 label="Qwen - Model",
    #                 values=["Qwen-14B"],
    #                 initial_index=0,
    #             ),
    #             Slider(
    #                 id="Temperature",
    #                 label="Model Temperature",
    #                 initial=0.7,
    #                 min=0,
    #                 max=1,
    #                 step=0.1,
    #             ),
    #         ]
    #     ).send()
    #     await cl.Message(
    #         content='Im Qwens open source Ai model and i am configured by two iranian boys Artin Daneshvar and Sadra Noadoust to help you out!',
    #     ).send()

    # if chat_profile == 'Qwen-7B':
    #     await cl.ChatSettings(
    #         [
    #             Select(
    #                 id="Qwen-Model",
    #                 label="Qwen - Model",
    #                 values=["Qwen-7B"],
    #                 initial_index=0,
    #             ),
    #             Slider(
    #                 id="Temperature",
    #                 label="Model Temperature",
    #                 initial=0.7,
    #                 min=0,
    #                 max=1,
    #                 step=0.1,
    #             ),
    #         ]
    #     ).send()
    #     await cl.Message(
    #         content='Im Qwens open source Ai model and i am configured by two iranian boys Artin Daneshvar and Sadra Noadoust to help you out!',
    #     ).send()

    if chat_profile == 'Llama-3.1-405B':
        await cl.ChatSettings(
            [
                Select(
                    id="Meta-Model",
                    label="Meta - Model",
                    values=["Llama-3.1-405B"],
                    initial_index=0,
                ),
                Slider(
                    id="Temperature",
                    label="Model Temperature",
                    initial=0.7,
                    min=0,
                    max=1,
                    step=0.1,
                ),
            ]
        ).send()
        await cl.Message(
            content="Im the big Llama-3.1!. one of the best open source models released by Meta! i am the Big version of meta's open source LLMs., i was configured by Artin Daneshvar and Sadra Noadoust, 2 iranian students to help you, how can i assist you today ? "
        ).send()
        
    if chat_profile == 'Llama-3.1-70B':
        await cl.ChatSettings(
            [
                Select(
                    id="Meta-Model",
                    label="Meta - Model",
                    values=["Llama-3.1-70B"],
                    initial_index=0,
                ),
                Slider(
                    id="Temperature",
                    label="Model Temperature",
                    initial=0.7,
                    min=0,
                    max=1,
                    step=0.1,
                ),
            ]
        ).send()
        await cl.Message(
            content="Im the second-big Llama-3.1!. one of the best open source models released by Meta! i am the Big version of meta's open source LLMs., i was configured by Artin Daneshvar and Sadra Noadoust, 2 iranian students to help you, how can i assist you today ? "
        ).send()
    if chat_profile == 'Llama-3.1-8B':
        await cl.ChatSettings(
            [
                Select(
                    id="Meta-Model",
                    label="Meta - Model",
                    values=["Llama-3.1-8B"],
                    initial_index=0,
                ),
                Slider(
                    id="Temperature",
                    label="Model Temperature",
                    initial=0.7,
                    min=0,
                    max=1,
                    step=0.1,
                ),
            ]
        ).send()
        await cl.Message(
            content="Im the small Llama-3.1!. one of the best open source models released by Meta! i am the Big version of meta's open source LLMs., i was configured by Artin Daneshvar and Sadra Noadoust, 2 iranian students to help you, how can i assist you today ? "
        ).send()
        
    if chat_profile == 'Llama-3-70B':
        await cl.ChatSettings(
            [
                Select(
                    id="Meta-Model",
                    label="Meta - Model",
                    values=["Llama-3-70B"],
                    initial_index=0,
                ),
                Slider(
                    id="Temperature",
                    label="Model Temperature",
                    initial=0.7,
                    min=0,
                    max=1,
                    step=0.1,
                ),
            ]
        ).send()
        await cl.Message(
            content="Im the big Llama-3!. one of the best open source models released by Meta! i am the Big version of meta's open source LLMs., i was configured by Artin Daneshvar and Sadra Noadoust, 2 iranian students to help you, how can i assist you today ? "
        ).send()
    if chat_profile == 'Llama-3-8B':
        await cl.ChatSettings(
            [
                Select(
                    id="Meta-Model",
                    label="Meta - Model",
                    values=["Llama-3-8B"],
                    initial_index=0,
                ),
                Slider(
                    id="Temperature",
                    label="Model Temperature",
                    initial=0.7,
                    min=0,
                    max=1,
                    step=0.1,
                ),
            ]
        ).send()        

        await cl.Message(
            content="Im The small Llama!. one of the best open source models released by Meta! i am the small version of meta's open source LLMs. i was configured by Artin Daneshvar and Sadra Noadoust, 2 iranian students to help you, how can i assist you today ? "
        ).send()

    if chat_profile == 'Aya-23B':
        await cl.ChatSettings(
            [
                Select(
                    id="Cohere-Model",
                    label="Cohere - Model",
                    values=["Aya-23B"],
                    initial_index=0,
                ),
                Slider(
                    id="Temperature",
                    label="Model Temperature",
                    initial=0.7,
                    min=0,
                    max=1,
                    step=0.1,
                ),
            ]
        ).send() 
        await cl.Message(
            content='Im one of the best open source models that cohere released. i am configured by 2 iranian boys named Artin Daneshvar and Sadra Noadosut to help you out!'
        ).send()

    if chat_profile == 'Aya-35B':
        await cl.ChatSettings(
            [
                Select(
                    id="Cohere-Model",
                    label="Cohere - Model",
                    values=["Aya-35B"],
                    initial_index=0,
                ),
                Slider(
                    id="Temperature",
                    label="Model Temperature",
                    initial=0.7,
                    min=0,
                    max=1,
                    step=0.1,
                ),
            ]
        ).send() 
        await cl.Message(
            content='Im one of the best open source models that cohere released. i am configured by 2 iranian boys named Artin Daneshvar and Sadra Noadosut to help you out!'
        ).send()
        
    if chat_profile == 'Command-R-Plus':
        await cl.ChatSettings(
            [
                Select(
                    id="Cohere-Model",
                    label="Cohere - Model",
                    values=["Command-R-Plus"],
                    initial_index=0,
                ),
                Slider(
                    id="Temperature",
                    label="Model Temperature",
                    initial=0.7,
                    min=0,
                    max=1,
                    step=0.1,
                ),
            ]
        ).send() 
        await cl.Message(
            content='Im one of the best open source models that cohere released. i am configured by 2 iranian boys named Artin Daneshvar and Sadra Noadosut to help you out!'
        ).send()

    if chat_profile == 'Command-Nightly':
        await cl.ChatSettings(
            [
                Select(
                    id="Cohere-Model",
                    label="Cohere - Model",
                    values=["Command-Nightly"],
                    initial_index=0,
                ),
                Slider(
                    id="Temperature",
                    label="Model Temperature",
                    initial=0.7,
                    min=0,
                    max=1,
                    step=0.1,
                ),
            ]
        ).send() 
        await cl.Message(
            content='Im one of the best open source models that cohere released. i am configured by 2 iranian boys named Artin Daneshvar and Sadra Noadosut to help you out!'
        ).send()

    if chat_profile == 'Command-Light-Nightly':
        await cl.ChatSettings(
            [
                Select(
                    id="Cohere-Model",
                    label="Cohere - Model",
                    values=["Command-Light-Nigtly"],
                    initial_index=0,
                ),
                Slider(
                    id="Temperature",
                    label="Model Temperature",
                    initial=0.7,
                    min=0,
                    max=1,
                    step=0.1,
                ),
            ]
        ).send() 
        await cl.Message(
            content='Im one of the best open source models that cohere released. i am configured by 2 iranian boys named Artin Daneshvar and Sadra Noadosut to help you out!'
        ).send()

    if chat_profile == 'Command-Light':
        await cl.ChatSettings(
            [
                Select(
                    id="Cohere-Model",
                    label="Cohere - Model",
                    values=["Command-Light"],
                    initial_index=0,
                ),
                Slider(
                    id="Temperature",
                    label="Model Temperature",
                    initial=0.7,
                    min=0,
                    max=1,
                    step=0.1,
                ),
            ]
        ).send() 
        await cl.Message(
            content='Im one of the best open source models that cohere released. i am configured by 2 iranian boys named Artin Daneshvar and Sadra Noadosut to help you out!'
        )

    if chat_profile == 'Command-R':
        await cl.ChatSettings(
            [
                Select(
                    id="Cohere-Model",
                    label="Cohere - Model",
                    values=["Command-R"],
                    initial_index=0,
                ),
                Slider(
                    id="Temperature",
                    label="Model Temperature",
                    initial=0.7,
                    min=0,
                    max=1,
                    step=0.1,
                ),
            ]
        ).send() 
        await cl.Message(
            content='Im one of the best open source models that cohere released. i am configured by 2 iranian boys named Artin Daneshvar and Sadra Noadosut to help you out!'
        ).send()

    if chat_profile == 'Command':
        await cl.ChatSettings(
            [
                Select(
                    id="Cohere-Model",
                    label="Cohere - Model",
                    values=["Command"],
                    initial_index=0,
                ),
                Slider(
                    id="Temperature",
                    label="Model Temperature",
                    initial=0.7,
                    min=0,
                    max=1,
                    step=0.1,
                ),
            ]
        ).send() 
        await cl.Message(
            content='Im one of the best open source models that cohere released. i am configured by 2 iranian boys named Artin Daneshvar and Sadra Noadosut to help you out!'
        ).send()
        
    if chat_profile == 'gemma2-9B':
        await cl.ChatSettings(
            [
                Select(
                    id="Google-Model",
                    label="Google - Model",
                    values=["Gemma-9B"],
                    initial_index=0,
                ),
                Slider(
                    id="Temperature",
                    label="Model Temperature",
                    initial=0.7,
                    min=0,
                    max=1,
                    step=0.1,
                ),
            ]
        ).send()
        await cl.Message(
            content="Im Gemma2. the 9B version of google second generation open source LLMs. i was configured by Artin Daneshvar and Sadra Noadoust, 2 iranian students to help you, how can i assist you today ? "
        ).send()
        
    if chat_profile == 'gemma-7B':
        await cl.ChatSettings(
            [
                Select(
                    id="Google-Model",
                    label="Google - Model",
                    values=["Gemma-7B"],
                    initial_index=0,
                ),
                Slider(
                    id="Temperature",
                    label="Model Temperature",
                    initial=0.7,
                    min=0,
                    max=1,
                    step=0.1,
                ),
            ]
        ).send()
        await cl.Message(
            content="Im Gemma. the small version of google open source LLMs. i was configured by Artin Daneshvar and Sadra Noadoust, 2 iranian students to help you, how can i assist you today ? "
        ).send()
    if chat_profile == 'zephyr-7B':
        await cl.ChatSettings(
            [
                Select(
                    id="zephyr-Model",
                    label="zephyr - Model",
                    values=["zephyr-7B"],
                    initial_index=0,
                ),
                Slider(
                    id="Temperature",
                    label="Model Temperature",
                    initial=0.7,
                    min=0,
                    max=1,
                    step=0.1,
                ),
            ]
        ).send()
        await cl.Message(
            content="Im Zephyr. One of the best open source LLMs. i was configured by Artin Daneshvar and Sadra Noadoust, 2 iranian students to help you, how can i assist you today ? "
        ).send()
    if chat_profile == 'mixtral-8x7B':
        await cl.ChatSettings(
            [
                Select(
                    id="Mistral-Model",
                    label="Mistral - Model",
                    values=["mixtral-8x7B"],
                    initial_index=0,
                ),
                Slider(
                    id="Temperature",
                    label="Model Temperature",
                    initial=0.7,
                    min=0,
                    max=1,
                    step=0.1,
                ),
            ]
        ).send()
        await cl.Message(
            content="Im Mistral. the small version of Mistral Family. i was configured by Artin Daneshvar and Sadra Noadoust, 2 iranian students to help you, how can i assist you today ? "
        ).send()

    if chat_profile == 'mistral-nemo-12B':
        await cl.ChatSettings(
            [
                Select(
                    id="Mistral-Model",
                    label="Mistral - Model",
                    values=["mistral-nemo-12B"],
                    initial_index=0,
                ),
                Slider(
                    id="Temperature",
                    label="Model Temperature",
                    initial=0.7,
                    min=0,
                    max=1,
                    step=0.1,
                ),
            ]
        ).send()
        await cl.Message(
            content="Im Mistral nemo 12B .i was configured by Artin Daneshvar and Sadra Noadoust, 2 iranian students to help you, how can i assist you today ? "
        ).send()
    # if chat_profile == 'Toka-353M':
    #     await cl.ChatSettings(
    #         [
    #             Select(
    #                 id="PartAI-Model",
    #                 label="PartAI - Model",
    #                 values=["TokaBert-353M"],
    #                 initial_index=0,
    #             ),
    #             Slider(
    #                 id="Temperature",
    #                 label="Model Temperature",
    #                 initial=0.7,
    #                 min=0,
    #                 max=1,
    #                 step=0.1,
    #             ),
    #         ]
    #     ).send()
    #     await cl.Message(
    #         content="Im Toka. An opens source  persian LLM . i was configured by Artin Daneshvar and Sadra Noadoust, 2 iranian students to help you, how can i assist you today ? you should ask me your questions like : the capital of england is <mask> "
    #     ).send()

@cl.on_message  
async def main(message: cl.Message):
    chat_profile = cl.user_session.get("chat_profile")
    if not chat_profile or chat_profile == 'None':
        await cl.Message(
            content="Please select a model first."
        ).send()
        return
    if chat_profile == 'neural-brain-AI':
        completion = openai_client.chat.completions.create(
            model="ft:gpt-3.5-turbo-1106:nb:aria1:9UWDrLJK",
            messages=[
                {"role": "system", "content": "You are neural nexus official chatbot, you are made by Artin Daneshvar and Sadra Noadoust"},
                {"role": "user", "content": message.content}
            ]
        )
        model_response = completion.choices[0].message.content
        await cl.Message(
            content=model_response
        ).send()

    elif chat_profile == "Dorna-AI":
        result = hf_text_client.predict(
            message=message.content,
            request="your name is Dorna,An AI Assistant designed by neural nexus team. i was made by Artin Daneshvar and Sadra Noadoust, 2 iranian students!",
            param_3=512,
            param_4=0.7,
            param_5=0.95,
            api_name="/chat"
        )
        model_response = result.strip("</s>") 
        await cl.Message(
            content=model_response
        ).send()
    elif chat_profile == "gpt4-o-mini":
        completion = openai_client.chat.completions.create(
            model="gpt-4o-mini",
            messages=[
                {"role": "system", "content": "You are neural nexus official chatbot, you are made by Artin Daneshvar and Sadra Noadoust"},
                {"role": "user", "content": message.content}
            ]
        )
        model_response = completion.choices[0].message.content
        await cl.Message(
            content=model_response
        ).send()
  #   elif chat_profile == 'Image-Generation':
  #       result = hf_image_client.predict(
		# prompt=message.content,
		# negative_prompt="",
		# seed=0,
		# randomize_seed=True,
		# width=512,
		# height=512,
		# guidance_scale=0,
		# num_inference_steps=2,
		# api_name="/infer"
  #       )
  #       image = cl.Image(path=result, name="result", display="inline")
  #       await cl.Message(
  #           content="This message has an image!",
  #           elements=[image],
  #       ).send()
    elif chat_profile == 'GPT-4':
        completion = openai_client.chat.completions.create(
            model="gpt-4",
            messages=[
                {"role": "system", "content": "You are neural nexus official chatbot, you are made by Artin Daneshvar and Sadra Noadoust"},
                {"role": "user", "content": message.content}
            ]
        )
        model_response = completion.choices[0].message.content
        await cl.Message(
            content=model_response
        ).send()

    elif chat_profile == 'gpt-3.5-turbo':
        completion = openai_client.chat.completions.create(
            model="gpt-3.5-turbo",
            messages=[
                {"role": "system", "content": "You are neural nexus official chatbot, you are made by Artin Daneshvar and Sadra Noadoust"},
                {"role": "user", "content": message.content}
            ]
        )
        model_response = completion.choices[0].message.content
        await cl.Message(
            content=model_response
        ).send()
    elif chat_profile == 'GPT-3.5-turbo-0125':
        completion = openai_client.chat.completions.create(
            model="GPT-3.5-turbo-0125",
            messages=[
                {"role": "system", "content": "You are neural nexus official chatbot, you are made by Artin Daneshvar and Sadra Noadoust"},
                {"role": "user", "content": message.content}
            ]
        )
        model_response = completion.choices[0].message.content
        await cl.Message(
            content=model_response
        ).send()
    elif chat_profile == 'gpt-3.5-turbo-1106':
        completion = openai_client.chat.completions.create(
            model="gpt-3.5-turbo-1106",
            messages=[
                {"role": "system", "content": "You are neural nexus official chatbot, you are made by Artin Daneshvar and Sadra Noadoust"},
                {"role": "user", "content": message.content}
            ]
        )
        model_response = completion.choices[0].message.content
        await cl.Message(
            content=model_response
        ).send()
    # elif chat_profile == 'davinci-002':
    #     completion = openai_client.chat.completions.create(
    #         model="davinci-002",
    #         messages=[
    #             {"role": "system", "content": "You are neural nexus official chatbot, you are made by Artin Daneshvar and Sadra Noadoust"},
    #             {"role": "user", "content": message.content}
    #         ]
    #     )
    #     model_response = completion.choices[0].message.content
    #     await cl.Message(
    #         content=model_response
    #     ).send()

    elif chat_profile == 'TTS':
        response = openai_client.audio.speech.create(
            model="tts-1",
            voice="alloy",
            input=message.content,
        )

        response.stream_to_file("output.mp3")

        elements = [
            cl.Audio(name="output.mp3", path="./output.mp3", display="inline"),
        ]
        await cl.Message(
            content="Here it is the response!",
            elements=elements,
        ).send()

    elif chat_profile == 'Qwen2-57B':
        client = Client("Qwen/Qwen2-57b-a14b-instruct-demo", hf_token=hf_token)
        result = client.predict(
    		query=message.content,
    		system="You are a helpful AI chatbot made by two iranian boys named Artin Daneshvar and Sadra Noadoust",
    		api_name="/model_chat"
        )
        await cl.Message(
            content=result[1][0][1]
        ).send()
        
    elif chat_profile == 'Qwen2-7B':
        client = Client("Qwen/Qwen2-7b-instruct-demo", hf_token=hf_token)
        result = client.predict(
    		query=message.content,
    		system="You are a helpful AI chatbot made by two iranian boys named Artin Daneshvar and Sadra Noadoust",
    		api_name="/model_chat"
        )
        await cl.Message(
            content=result[1][0][1]

        ).send()

    elif chat_profile == 'Qwen2-1.5B':
        client = Client("Qwen/Qwen2-1.5b-instruct-demo", hf_token=hf_token)
        result = client.predict(
    		query=message.content,
    		system="You are a helpful AI chatbot made by two iranian boys named Artin Daneshvar and Sadra Noadoust",
    		api_name="/model_chat"
        )
        await cl.Message(
            content=result[1][0][1]

        ).send()

    elif chat_profile == 'Qwen2-0.5B':
        client = Client("Qwen/Qwen2-0.5B-Instruct", hf_token=hf_token)
        result = client.predict(
    		query=message.content,
    		system="You are a helpful AI chatbot made by two iranian boys named Artin Daneshvar and Sadra Noadoust",
    		api_name="/model_chat"
        )
        await cl.Message(
            content=result[1][0][1]

        ).send()
    elif chat_profile == 'Qwen1.5-110B':
        client = Client("Qwen/Qwen1.5-110B-Chat-demo", hf_token=hf_token)
        result = client.predict(
    		query=message.content,
    		system="You are a helpful AI chatbot made by two iranian boys named Artin Daneshvar and Sadra Noadoust",
    		api_name="/model_chat"
        )
        await cl.Message(
            content=result[1][0][1]

        ).send()

    elif chat_profile == 'Qwen1.5-32B':
        client = Client("Qwen/Qwen1.5-32B-Chat-demo", hf_token=hf_token)
        result = client.predict(
    		query=message.content,
    		system="You are a helpful AI chatbot made by two iranian boys named Artin Daneshvar and Sadra Noadoust",
    		api_name="/model_chat"
        )
        await cl.Message(
            content=result[1][0][1]

        ).send()

    elif chat_profile == 'Qwen1.5-2.7B':
        client = Client("Qwen/qwen1.5-MoE-A2.7B-Chat-demo", hf_token=hf_token)
        result = client.predict(
    		query=message.content,
    		system="You are a helpful AI chatbot made by two iranian boys named Artin Daneshvar and Sadra Noadoust",
    		api_name="/model_chat"
        )
        await cl.Message(
            content=result[1][0][1]

        ).send()

    # elif chat_profile == 'Qwen-14B':
    #     client = Client("Qwen/qwen1.5-MoE-A2.7B-Chat-demo", hf_token=hf_token)
    #     result = client.predict(
    # 		query=message.content,
    # 		system="You are a helpful AI chatbot made by two iranian boys named Artin Daneshvar and Sadra Noadoust",
    # 		api_name="/model_chat"
    #     )
    #     await cl.Message(
    #         content=result[1][0][1]

    #     ).send()

    # elif chat_profile == 'Qwen-7B':
    #     client = Client("Qwen/qwen1.5-MoE-A2.7B-Chat-demo", hf_token=hf_token)
    #     result = client.predict(
    # 		query=message.content,
    # 		system="You are a helpful AI chatbot made by two iranian boys named Artin Daneshvar and Sadra Noadoust",
    # 		api_name="/model_chat"
    #     )
    #     await cl.Message(
    #         content=result[1][0][1]

    #     ).send()
        
    elif chat_profile == 'Llama-3.1-405B':        
        completion = groq_client.chat.completions.create(
            model="llama-3.1-405b-reasoning",
            messages=[
                {
                    "role": "user",
                    "content": message.content
                }
            ],
            temperature=1,
            max_tokens=1024,
            top_p=1,
            stream=True,
            stop=None,
        )
    
        complete_content = ""
    
        # Iterate over each chunk
        for chunk in completion:
            # Retrieve the content from the current chunk
            content = chunk.choices[0].delta.content
            
            # Check if the content is not None before concatenating it
            if content is not None:
                complete_content += content
    
        # Send the concatenated content as a message
        await cl.Message(content=complete_content).send()

    
    elif chat_profile == 'Llama-3.1-70B':
        completion = groq_client.chat.completions.create(
            model="llama-3.1-70b-versatile",
            messages=[
                {
                    "role": "user",
                    "content": message.content
                }
            ],
            temperature=1,
            max_tokens=1024,
            top_p=1,
            stream=True,
            stop=None,
        )
    
        complete_content = ""
    
        # Iterate over each chunk
        for chunk in completion:
            # Retrieve the content from the current chunk
            content = chunk.choices[0].delta.content
            
            # Check if the content is not None before concatenating it
            if content is not None:
                complete_content += content
    
        # Send the concatenated content as a message
        await cl.Message(content=complete_content).send()

    elif chat_profile == 'Llama-3.1-8B':
        completion = groq_client.chat.completions.create(
            model="llama-3.1-8b-instant",
            messages=[
                {
                    "role": "user",
                    "content": message.content
                }
            ],
            temperature=1,
            max_tokens=1024,
            top_p=1,
            stream=True,
            stop=None,
        )
    
        complete_content = ""
    
        # Iterate over each chunk
        for chunk in completion:
            # Retrieve the content from the current chunk
            content = chunk.choices[0].delta.content
            
            # Check if the content is not None before concatenating it
            if content is not None:
                complete_content += content
    
        # Send the concatenated content as a message
        await cl.Message(content=complete_content).send()

    elif chat_profile == 'Llama-3-70B':
        completion = groq_client.chat.completions.create(
            model="llama3-70b-8192",
            messages=[
                {
                    "role": "user",
                    "content": message.content
                }
            ],
            temperature=1,
            max_tokens=1024,
            top_p=1,
            stream=True,
            stop=None,
        )

        complete_content = ""

        # Iterate over each chunk
        for chunk in completion:
            # Retrieve the content from the current chunk
            content = chunk.choices[0].delta.content
            
            # Check if the content is not None before concatenating it
            if content is not None:
                complete_content += content

        # Send the concatenated content as a message
        await cl.Message(content=complete_content).send()

    elif chat_profile == 'Llama-3-8B':
        completion = groq_client.chat.completions.create(
            model="llama3-8b-8192",
            messages=[
                {
                    "role": "user",
                    "content": message.content
                }
            ],
            temperature=1,
            max_tokens=1024,
            top_p=1,
            stream=True,
            stop=None,
        )

        complete_content = ""

        # Iterate over each chunk
        for chunk in completion:
            # Retrieve the content from the current chunk
            content = chunk.choices[0].delta.content
            
            # Check if the content is not None before concatenating it
            if content is not None:
                complete_content += content

        # Send the concatenated content as a message
        await cl.Message(content=complete_content).send()

    elif chat_profile == 'gemma2-9B':
        completion = groq_client.chat.completions.create(
            model="gemma2-9b-it",
            messages=[
                {
                    "role": "user",
                    "content": message.content
                }
            ],
            temperature=1,
            max_tokens=1024,
            top_p=1,
            stream=True,
            stop=None,
        )

        complete_content = ""

        # Iterate over each chunk
        for chunk in completion:
            # Retrieve the content from the current chunk
            content = chunk.choices[0].delta.content
            
            # Check if the content is not None before concatenating it
            if content is not None:
                complete_content += content

        # Send the concatenated content as a message
        await cl.Message(content=complete_content).send()

    elif chat_profile == 'gemma-7B':
        completion = groq_client.chat.completions.create(
            model="gemma-7b-it",
            messages=[
                {
                    "role": "user",
                    "content": message.content
                }
            ],
            temperature=1,
            max_tokens=1024,
            top_p=1,
            stream=True,
            stop=None,
        )

        complete_content = ""

        # Iterate over each chunk
        for chunk in completion:
            # Retrieve the content from the current chunk
            content = chunk.choices[0].delta.content
            
            # Check if the content is not None before concatenating it
            if content is not None:
                complete_content += content

        # Send the concatenated content as a message
        await cl.Message(content=complete_content).send()
    
    elif chat_profile == "zephyr-7B":
        result = hf_text_client.predict(
            message=message.content,
            request="your name is zephyr,An AI Assistant designed by neural nexus team. i was made by Artin Daneshvar and Sadra Noadoust, 2 iranian students!",
            param_3=512,
            param_4=0.7,
            param_5=0.95,
            api_name="/chat"
        )
        model_response = result.strip("</s>") 
        await cl.Message(
            content=model_response
        ).send()

    elif chat_profile == 'mixtral-8x7B':
        completion = groq_client.chat.completions.create(
            model="mixtral-8x7b-32768",
            messages=[
                {
                    "role": "user",
                    "content": message.content
                }
            ],
            temperature=1,
            max_tokens=1024,
            top_p=1,
            stream=True,
            stop=None,
        )

        complete_content = ""

        for chunk in completion:
            content = chunk.choices[0].delta.content
            
            if content is not None:
                complete_content += content

        await cl.Message(content=complete_content).send() 

    elif chat_profile == 'mistral-nemo-12B':
        client = Client("0x7o/Mistral-Nemo-Instruct", hf_token=hf_token)
        result = client.predict(
        		message=message.content,
        		max_new_tokens=512,
        		temperature=0.7,
        		top_p=0.95,
        		api_name="/chat"
        )
        await cl.Message(
            content=result[1][0][1]

        ).send()

    # elif chat_profile == 'Toka-353M':
    #     output = query({
    #     "inputs": message.content,
    # })
    #     await cl.Message(
    #         content=output[0]['sequence']
    #     ).send()

    elif chat_profile == 'Aya-23B':
        stream = co.chat_stream( 
        model='c4ai-aya-23',
        message=message.content,
        temperature=0.3,
        # chat_history=[{"role": "User", "message": "Hello"}, {"role": "Chatbot", "message": "Hello! How can I help you today?"}, {"role": "User", "message": "Hi"}, {"role": "User", "message": "hello"}],
        prompt_truncation='OFF',
        connectors=[],
        ) 

        complete_content = ''
        for event in stream:
            if event.event_type == 'text-generation':
                complete_content += event.text
        await cl.Message(content=complete_content).send()

    elif chat_profile == 'Aya-35B':
        stream = co.chat_stream( 
        model='c4ai-aya-23',
        message=message.content,
        temperature=0.3,
        # chat_history=[{"role": "User", "message": "Hello"}, {"role": "Chatbot", "message": "Hello! How can I help you today?"}, {"role": "User", "message": "Hi"}, {"role": "User", "message": "hello"}],
        prompt_truncation='OFF',
        connectors=[],
        ) 

        complete_content = ''
        for event in stream:
            if event.event_type == 'text-generation':
                complete_content += event.text
        await cl.Message(content=complete_content).send()

    elif chat_profile == 'Command-R-Plus':
        stream = co.chat_stream( 
          model='command-r-plus',
          message=message.content,
          temperature=0.3,
          chat_history=[],
          prompt_truncation='AUTO',
        ) 
        complete_content = ''
        for event in stream:
            if event.event_type == 'text-generation':
                complete_content += event.text
        await cl.Message(content=complete_content).send()

    elif chat_profile == 'Command-R':
        stream = co.chat_stream( 
          model='command-r',
          message=message.content,
          temperature=0.3,
          chat_history=[],
          prompt_truncation='AUTO',
        ) 
        complete_content = ''
        for event in stream:
            if event.event_type == 'text-generation':
                complete_content += event.text
        await cl.Message(content=complete_content).send()

    elif chat_profile == 'Command':
        stream = co.chat_stream( 
          model='command',
          message=message.content,
          temperature=0.3,
          chat_history=[],
          prompt_truncation='AUTO',
        ) 
        complete_content = ''
        for event in stream:
            if event.event_type == 'text-generation':
                complete_content += event.text
        await cl.Message(content=complete_content).send()
        
    elif chat_profile == 'Command-Light':
        stream = co.chat_stream( 
          model='command-light',
          message=message.content,
          temperature=0.3,
          chat_history=[],
          prompt_truncation='AUTO',
        ) 
        complete_content = ''
        for event in stream:
            if event.event_type == 'text-generation':
                complete_content += event.text
        await cl.Message(content=complete_content).send()

    elif chat_profile == 'Command-Light-Nightly':
        stream = co.chat_stream( 
          model='command-light-nightly',
          message=message.content,
          temperature=0.3,
          chat_history=[],
          prompt_truncation='AUTO',
        ) 
        complete_content = ''
        for event in stream:
            if event.event_type == 'text-generation':
                complete_content += event.text
        await cl.Message(content=complete_content).send()

    elif chat_profile == 'Command-Nightly':
        stream = co.chat_stream( 
          model='command-light-nightly',
          message=message.content,
          temperature=0.3,
          chat_history=[],
          prompt_truncation='AUTO',
        ) 
        complete_content = ''
        for event in stream:
            if event.event_type == 'text-generation':
                complete_content += event.text
        await cl.Message(content=complete_content).send()

@cl.on_settings_update
async def setup_agent(settings):
    print("on_settings_update", settings)