| import gradio as gr | |
| from huggingface_hub import InferenceClient | |
| def generate_response(user_prompt, system_instructions="You are a helpful assistant."): | |
| try: | |
| client = InferenceClient("microsoft/Phi-3-mini-4k-instruct") | |
| generate_kwargs = dict( | |
| max_new_tokens=100, | |
| do_sample=True, | |
| ) | |
| formatted_prompt = f"[SYSTEM] {system_instructions}[QUESTION]{user_prompt}[ANSWER]" | |
| stream = client.text_generation(formatted_prompt, **generate_kwargs, stream=True, details=True, | |
| return_full_text=False) | |
| output = "" | |
| for response in stream: | |
| output += response.token.text | |
| if output.endswith("<|assistant|>"): | |
| output = output[:-13] | |
| elif output.endswith("</s>"): | |
| output = output[:-4] | |
| return output | |
| except Exception as e: | |
| return str(e) | |
| # 使用Gradio创建界面 | |
| with gr.Blocks() as demo: | |
| gr.Markdown("## AI Text Generation") | |
| with gr.Row(): | |
| user_input = gr.Textbox(label="Enter your prompt") | |
| generate_button = gr.Button("Generate") | |
| output_display = gr.Textbox(label="Generated Response") | |
| generate_button.click( | |
| fn=generate_response, | |
| inputs=[user_input], | |
| outputs=output_display | |
| ) | |
| demo.launch() | |