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| import gradio as gr | |
| from huggingface_hub import InferenceClient | |
| import random | |
| models = [ | |
| "yongyi169/yy-gemma-it-ar-20240327", | |
| "google/gemma-7b", | |
| "google/gemma-7b-it", | |
| "google/gemma-2b", | |
| "google/gemma-2b-it" | |
| ] | |
| clients = [] | |
| for model in models: | |
| clients.append(InferenceClient(model)) | |
| def format_prompt(message, history): | |
| prompt = "" | |
| if history: | |
| for user_prompt, bot_response in history: | |
| prompt += f"<start_of_turn>user{user_prompt}<end_of_turn>" | |
| prompt += f"<start_of_turn>model{bot_response}" | |
| prompt += f"<start_of_turn>user{message}<end_of_turn><start_of_turn>model" | |
| return prompt | |
| def chat_inf(system_prompt, prompt, history, client_choice, seed, temp, tokens, top_p, rep_p): | |
| client = clients[int(client_choice) - 1] | |
| if not history: | |
| history = [] | |
| hist_len = 0 | |
| if history: | |
| hist_len = len(history) | |
| print(hist_len) | |
| generate_kwargs = dict( | |
| temperature=temp, | |
| max_new_tokens=tokens, | |
| top_p=top_p, | |
| repetition_penalty=rep_p, | |
| do_sample=True, | |
| seed=seed, | |
| ) | |
| formatted_prompt = format_prompt(f"{system_prompt}, {prompt}", history) | |
| 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 | |
| yield [(prompt, output)] | |
| history.append((prompt, output)) | |
| yield history | |
| def clear_fn(): | |
| return None | |
| rand_val = random.randint(1, 1111111111111111) | |
| def check_rand(inp, val): | |
| if inp is True: | |
| return gr.Slider(label="Seed", minimum=1, maximum=1111111111111111, value=random.randint(1, 1111111111111111)) | |
| else: | |
| return gr.Slider(label="Seed", minimum=1, maximum=1111111111111111, value=int(val)) | |
| with gr.Blocks() as app: | |
| gr.HTML( | |
| """<center><h1 style='font-size:xx-large;'>Google Gemma Models</h1></center>""") | |
| with gr.Group(): | |
| with gr.Row(): | |
| client_choice = gr.Dropdown(label="Models", type='index', choices=[c for c in models], value=models[0], | |
| interactive=True) | |
| chat_b = gr.Chatbot(height=500) | |
| with gr.Group(): | |
| with gr.Row(): | |
| with gr.Column(scale=1): | |
| with gr.Group(): | |
| rand = gr.Checkbox(label="Random Seed", value=True) | |
| seed = gr.Slider(label="Seed", minimum=1, maximum=1111111111111111, step=1, value=rand_val) | |
| tokens = gr.Slider(label="Max new tokens", value=6400, minimum=0, maximum=8000, step=64, | |
| interactive=True, visible=True, info="The maximum number of tokens") | |
| with gr.Column(scale=1): | |
| with gr.Group(): | |
| temp = gr.Slider(label="Temperature", step=0.01, minimum=0.01, maximum=1.0, value=0.9) | |
| top_p = gr.Slider(label="Top-P", step=0.01, minimum=0.01, maximum=1.0, value=0.9) | |
| rep_p = gr.Slider(label="Repetition Penalty", step=0.1, minimum=0.1, maximum=2.0, value=1.0) | |
| with gr.Group(): | |
| with gr.Row(): | |
| with gr.Column(scale=3): | |
| sys_inp = gr.Textbox(label="System Prompt (optional)") | |
| inp = gr.Textbox(label="Prompt") | |
| with gr.Row(): | |
| btn = gr.Button("Chat") | |
| stop_btn = gr.Button("Stop") | |
| clear_btn = gr.Button("Clear") | |
| chat_sub = inp.submit(check_rand, [rand, seed], seed).then(chat_inf, | |
| [sys_inp, inp, chat_b, client_choice, seed, temp, tokens, | |
| top_p, rep_p], chat_b) | |
| go = btn.click(check_rand, [rand, seed], seed).then(chat_inf, | |
| [sys_inp, inp, chat_b, client_choice, seed, temp, tokens, top_p, | |
| rep_p], chat_b) | |
| stop_btn.click(None, None, None, cancels=[go, chat_sub]) | |
| clear_btn.click(clear_fn, None, [chat_b]) | |
| app.queue(default_concurrency_limit=10).launch() | |