app.py

from huggingface_hub import InferenceClient
import gradio as gr

def hf_chat(api_key, system_prompt, user_prompt, temperature, max_tokens, top_p):
    try:
        # Initialize the Hugging Face Inference Client
        client = InferenceClient(api_key=api_key)

        # Prepare the messages
        messages = [
            {"role": "system", "content": system_prompt},
            {"role": "user", "content": user_prompt}
        ]

        # Stream the response from the Hugging Face model
        stream = client.chat.completions.create(
            model="Qwen/Qwen2.5-72B-Instruct",
            messages=messages,
            temperature=temperature,
            max_tokens=max_tokens,
            top_p=top_p,
            stream=True
        )

        # Concatenate the streamed content
        output = ""
        for chunk in stream:
            output += chunk.choices[0].delta.content

        return output

    except Exception as e:
        return f"Error: {str(e)}"

# Define the Gradio interface
with gr.Blocks() as demo:
    gr.Markdown("""# history prof it is my first appli.
     i am bad in history but to help me for my homework i makeing
    a ai.""")

    api_key_input = gr.Textbox(label="Hugging Face API Key", placeholder="Enter your Hugging Face API key", type="password")
    system_prompt_input = gr.Textbox(label="ethan's history prof", value="You are a history professor 5e in FRENCH.", placeholder="you are a history professor 5e in FRENCH.")
    user_prompt_input = gr.Textbox(label="user chat", placeholder="metez votre question ici.")
   

    temperature_slider = gr.Slider(label="Temperature", minimum=0.0, maximum=1.0, value=0.7, step=0.1)
    max_tokens_slider = gr.Slider(label="Max Tokens", minimum=10, maximum=2048, value=100, step=10)
    top_p_slider = gr.Slider(label="Top P", minimum=0.1, maximum=1.0, value=0.7, step=0.1)

    output = gr.Textbox(label="history prof 👨‍🏫")

    generate_button = gr.Button("📖")

    generate_button.click(
        hf_chat,
        inputs=[
            api_key_input, 
            system_prompt_input, 
            user_prompt_input, 
            temperature_slider, 
            max_tokens_slider, 
            top_p_slider
        ],
        outputs=[output]
    )

if __name__ == "__main__":
    demo.launch()

    #Merci papa de m'avoir offert cet ordi ❤️❤️❤️