app.py

import os
import copy
import gradio as gr
from typing import List, Tuple
from llama_cpp import Llama
from huggingface_hub import hf_hub_download


# Load the LLaMA model
llm = Llama(
    model_path=hf_hub_download(
        repo_id=os.environ.get("REPO_ID", "mradermacher/Atlas-Chat-2B-GGUF"),
        filename=os.environ.get("MODEL_FILE", "Atlas-Chat-2B.Q8_0.gguf"),
    ),
    n_ctx=2048,  # context window size
)


# Training prompt template
training_prompt = """<start_of_turn>user
{}<end_of_turn>
<start_of_turn>model
{}<end_of_turn>"""


# Generate response function
def response(
    user_message: str,
    chat_history: List[Tuple[str, str]],
    max_response_length: int,
    temperature: float,
    top_p: float,
):
    if not user_message.strip():
        return "تقدروا تكتبوا الرسالة مرة اخرى؟"

    # Format chat history into the prompt
    formatted_prompt = ""
    for user_input, model_response in chat_history:
        formatted_prompt += training_prompt.format(user_input, model_response)
    
    # Add the current user message to the formatted prompt
    formatted_prompt += training_prompt.format(user_message, "")
    
    try:
        output = llm(
            formatted_prompt,
            max_tokens=max_response_length,
            temperature=temperature,
            top_p=top_p,
            top_k=40,
            repeat_penalty=1.1,
            stop=["<end_of_turn>", "<|endoftext|>"],
            stream=True,
        )

        response_text = ""
        for out in output:
            stream = copy.deepcopy(out)
            response_text += stream["choices"][0]["text"]
        return response_text

    except Exception as e:
        return f"شي خطأ وقع: {str(e)}"

# Create the Gradio chat interface
demo = gr.ChatInterface(
    response,
    title="AtlasChat-mini",
    description="""\
# AtlasChat-mini 2B
This is a demo of [`MBZUAI-Paris/Atlas-Chat-2B`](https://huggingface.co/mbzuai-paris/atlas-chat-2b). For more details, please check [the paper](https://arxiv.org/pdf/2409.17912).

Looking for a larger and more powerful version? Try the 9B version in [HuggingFace](https://huggingface.co/mbzuai-paris/atlas-chat-9b).

This demo was done using the [llama-cpp-python](https://github.com/abetlen/llama-cpp-python) library for efficient inference and is running the [`mradermacher/Atlas-Chat-2B-GGUF`](https://huggingface.co/mradermacher/Atlas-Chat-2B-GGUF) version with 8-bit Q8_0 quantization.
""",
    examples=[
        ['What is the capital of Morocco?'],
        ['كيفاش نوجد شي طاجين ؟'],
        ['واش تقدر تعوض Google؟'],
        ['عاود لي شي نكتة']
    ],
    cache_examples=False,
    additional_inputs=[
        gr.Slider(minimum=1, maximum=1024, value=128, step=1, label="Max New Tokens"),
        gr.Slider(minimum=0.1, maximum=3.0, value=0.5, step=0.1, label="Temperature"),
        gr.Slider(minimum=0.1, maximum=1.0, value=0.90, step=0.05, label="Top-p (nucleus sampling)"),
    ],
)


# Launch the demo
if __name__ == "__main__":
    demo.launch()