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| import gradio as gr | |
| import random | |
| import spaces | |
| import os | |
| os.environ["KERAS_BACKEND"] = "jax" | |
| os.environ["XLA_PYTHON_CLIENT_MEM_FRACTION"]="1.00" | |
| import keras_hub | |
| import keras | |
| models = [ | |
| "hf://tatihden/gemma_mental_health_2b_it_en", | |
| "hf://tatihden/gemma_mental_health_2b_en", | |
| "hf://tatihden/gemma_mental_health_7b_it_en" | |
| ] | |
| clients = [] | |
| for model in models: | |
| clients.append(keras_hub.models.GemmaCausalLM.from_preset(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_k): | |
| client = clients[int(client_choice) - 1] | |
| if not history: | |
| history = [] | |
| hist_len = 0 | |
| if history: | |
| hist_len = len(history) | |
| print(hist_len) | |
| sampler = keras_hub.samplers.TopKSampler(k=top_k, seed=seed, temperature=temp) | |
| client.compile(sampler=sampler) | |
| formatted_prompt = format_prompt(f"{system_prompt}, {prompt}", history) | |
| stream = client.generate(formatted_prompt) | |
| output = "" | |
| for response in stream: | |
| output += response | |
| yield [(prompt, output)] | |
| history.append((prompt, output)) | |
| yield history | |
| def clear_fn(): | |
| return None | |
| rand_val = random.randint(1, 1111) | |
| def check_rand(inp, val): | |
| if inp is True: | |
| return gr.Slider(label="Seed", minimum=1, maximum=1111, value=random.randint(1, 1111)) | |
| else: | |
| return gr.Slider(label="Seed", minimum=1, maximum=1111, value=int(val)) | |
| with gr.Blocks(css=".gradio-container {background-color: rgb(187 247 208)}") as app: | |
| gr.HTML( | |
| """<center><h1 style='font-size:xx-large;'>CalmChat: A Mental Health Conversational Agent</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=300) | |
| 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=1111, 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_k = gr.Slider(label="Top-K", step=1, minimum=1, maximum=10, value=5) | |
| 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_k], chat_b) | |
| go = btn.click(check_rand, [rand, seed], seed).then(chat_inf, | |
| [sys_inp, inp, chat_b, client_choice, seed, temp, tokens, | |
| top_k], 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() |