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| import os | |
| import gradio as gr | |
| from functools import partial | |
| from huggingface_hub import InferenceClient | |
| css = """ | |
| #generate_button { | |
| transition: background-color 1s ease-out, color 1s ease-out; border-color 1s ease-out; | |
| } | |
| """ | |
| def generate(prompt: str, hf_token: str, model: str): | |
| messages = [{"role": "user", "content": prompt}] | |
| if hf_token is None or not hf_token.strip(): | |
| hf_token = os.getenv("HUGGINGFACE_API_KEY") | |
| client = InferenceClient(model, token=hf_token) | |
| model_name = model.split("/")[1] | |
| response = f"**{model_name}**\n\n" | |
| for msg in client.chat_completion(messages, max_tokens=600, stream=True): | |
| token = msg.choices[0].delta.content | |
| response += token | |
| yield response | |
| def clear_token(): | |
| # returns a textbox with visibility set to False | |
| # this will update the hf_token widget thus hiding it | |
| return gr.Textbox(visible=False) | |
| with gr.Blocks(css=css, theme="gradio/soft") as demo: | |
| gr.Markdown("<center><h1>Code LLM Explorer</h1></center>") | |
| prompt = gr.Textbox( | |
| label="Prompt", | |
| lines=2, # default two lines length | |
| max_lines=5, # the Textbox entends upto 5 lines length | |
| info="Type your Prompt here", | |
| show_label=False, | |
| value="Write Bubble Sort in Python", | |
| ) | |
| hf_token = gr.Textbox( | |
| label="HuggingFace Token", | |
| type="password", | |
| placeholder="Your Hugging Face Token", | |
| show_label=False, | |
| ) | |
| # gr.Group() will group the two buttons together | |
| # so there will be no gap between two buttons | |
| with gr.Group(): | |
| with gr.Row() as button_row: | |
| # variant: 'primary' for main call-to-action, 'secondary' for a more subdued style, 'stop' for a stop button. | |
| generate_btn = gr.Button( | |
| "Run", elem_id="generate_button", variant="primary", size="sm" | |
| ) | |
| view_code = gr.Button( | |
| "View Code", elem_id="generate_button", variant="secondary", size="sm" | |
| ) | |
| with gr.Row() as output_row: | |
| codellama_output = gr.Markdown("codellama/CodeLlama-34b-Instruct-hf") | |
| stablecode_output = gr.Markdown("stabilityai/stable-code-instruct-3b") | |
| deepseek_output = gr.Markdown("deepseek-ai/deepseek-coder-33b-instruct") | |
| gr.on( | |
| [prompt.submit, generate_btn.click], clear_token, inputs=None, outputs=hf_token | |
| ).then( | |
| fn=partial(generate, model="codellama/CodeLlama-34b-Instruct-hf"), | |
| inputs=[prompt, hf_token], | |
| outputs=codellama_output, | |
| ) | |
| gr.on( | |
| [prompt.submit, generate_btn.click], clear_token, inputs=None, outputs=hf_token | |
| ).then( | |
| fn=partial(generate, model="stabilityai/stable-code-instruct-3b"), | |
| inputs=[prompt, hf_token], | |
| outputs=stablecode_output, | |
| ) | |
| gr.on( | |
| [prompt.submit, generate_btn.click], clear_token, inputs=None, outputs=hf_token | |
| ).then( | |
| fn=partial(generate, model="microsoft/Phi-3-mini-4k-instruct"), | |
| inputs=[prompt, hf_token], | |
| outputs=deepseek_output, | |
| ) | |
| demo.launch() | |