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import gradio as gr |
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from huggingface_hub import InferenceClient, HfApi |
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from huggingface_hub.utils import HfHubHTTPError |
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import os |
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def check_api_status(model_id, token): |
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try: |
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client = InferenceClient(model_id, token=token) |
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response = client.chat_completion( |
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[{"role": "user", "content": "test"}], |
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max_tokens=1, |
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stream=False |
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) |
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return "API is accessible and responding" |
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except Exception as e: |
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if "rate limit" in str(e).lower(): |
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return "API is accessible (rate limited)" |
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return f"API status: {str(e)}" |
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def get_api_status(): |
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token = os.getenv('HF_TOKEN') |
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model_id = "HuggingFaceH4/zephyr-7b-beta" |
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|
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if not token: |
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return "⚠️ No API token found. Please set HF_TOKEN environment variable." |
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try: |
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status = check_api_status(model_id, token) |
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return f"✅ Connected to {model_id} | {status}" |
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except Exception as e: |
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return f"❌ Error: {str(e)}" |
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def respond( |
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message, |
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history: list[tuple[str, str]], |
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system_message, |
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max_tokens, |
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temperature, |
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top_p, |
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): |
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token = os.getenv('HF_TOKEN') |
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if not token: |
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yield "Error: Please set your HuggingFace API token in the HF_TOKEN environment variable." |
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return |
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client = InferenceClient( |
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"HuggingFaceH4/zephyr-7b-beta", |
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token=token |
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) |
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messages = [{"role": "system", "content": system_message}] |
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for val in history: |
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if val[0]: |
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messages.append({"role": "user", "content": val[0]}) |
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if val[1]: |
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messages.append({"role": "assistant", "content": val[1]}) |
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messages.append({"role": "user", "content": message}) |
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try: |
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response = "" |
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for message in client.chat_completion( |
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messages, |
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max_tokens=max_tokens, |
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stream=True, |
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temperature=temperature, |
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top_p=top_p, |
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): |
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token = message.choices[0].delta.content |
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response += token |
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yield response |
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except Exception as e: |
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yield f"Error during chat completion: {str(e)}" |
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with gr.Blocks() as demo: |
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chatbot = gr.ChatInterface( |
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respond, |
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additional_inputs=[ |
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gr.Textbox( |
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value="You are a friendly Chatbot.", |
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label="System message" |
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), |
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gr.Slider( |
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minimum=1, |
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maximum=2048, |
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value=512, |
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step=1, |
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label="Max new tokens" |
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), |
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gr.Slider( |
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minimum=0.1, |
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maximum=4.0, |
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value=0.7, |
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step=0.1, |
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label="Temperature" |
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), |
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gr.Slider( |
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minimum=0.1, |
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maximum=1.0, |
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value=0.95, |
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step=0.05, |
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label="Top-p (nucleus sampling)", |
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), |
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], |
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) |
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footer = gr.HTML( |
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value=f"<div style='text-align: center; padding: 10px; background-color: #f0f0f0; border-top: 1px solid #ddd;'>{get_api_status()}</div>", |
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every=30 |
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) |
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if __name__ == "__main__": |
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demo.launch() |
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