| import gradio as gr |
| import time |
| import requests |
| import json |
| import os |
| from urllib3.util.retry import Retry |
| from requests.adapters import HTTPAdapter |
|
|
| API_URL = os.getenv("API_URL") |
| API_KEY = os.getenv("API_KEY") |
|
|
| print(f"API_URL: {API_URL}") |
| print(f"API_KEY: {API_KEY}") |
|
|
| url = f"{API_URL}/v1/chat/completions" |
|
|
| |
| headers = { |
| "accept": "application/json", |
| "Content-Type": "application/json", |
| "Authorization": f"Bearer {API_KEY}", |
| } |
|
|
|
|
| def is_valid_json(data): |
| try: |
| parsed_data = json.loads(data) |
| return True, parsed_data |
| except ValueError as e: |
| return False, str(e) |
|
|
|
|
| with gr.Blocks() as demo: |
|
|
| markup = gr.Markdown( |
| """ |
| # Mistral 7B Instruct v0.2 |
| This is a demo of the Mistral 7B Instruct quantized model in GGUF (Q2) hosted on K8s cluster. |
| |
| The original models can be found [MaziyarPanahi/Mistral-7B-Instruct-v0.2-GGUF](https://huggingface.co/MaziyarPanahi/Mistral-7B-Instruct-v0.2-GGUF)""" |
| ) |
| chatbot = gr.Chatbot(height=500) |
| msg = gr.Textbox(lines=1, label="User Message") |
| clear = gr.Button("Clear") |
| with gr.Row(): |
|
|
| with gr.Column(scale=2): |
| system_prompt_input = gr.Textbox( |
| label="System Prompt", |
| placeholder="Type system prompt here...", |
| value="You are a helpful assistant.", |
| ) |
| temperature_input = gr.Slider( |
| label="Temperature", minimum=0.0, maximum=1.0, value=0.9, step=0.01 |
| ) |
| max_new_tokens_input = gr.Slider( |
| label="Max New Tokens", minimum=0, maximum=1024, value=256, step=1 |
| ) |
|
|
| with gr.Column(scale=2): |
| top_p_input = gr.Slider( |
| label="Top P", minimum=0.0, maximum=1.0, value=0.95, step=0.01 |
| ) |
| top_k_input = gr.Slider( |
| label="Top K", minimum=1, maximum=100, value=50, step=1 |
| ) |
| repetition_penalty_input = gr.Slider( |
| label="Repetition Penalty", |
| minimum=1.0, |
| maximum=2.0, |
| value=1.1, |
| step=0.01, |
| ) |
|
|
| def update_globals( |
| system_prompt, temperature, max_new_tokens, top_p, top_k, repetition_penalty |
| ): |
| global global_system_prompt, global_temperature, global_max_new_tokens, global_top_p, global_repetition_penalty, global_top_k |
| global_system_prompt = system_prompt |
| global_temperature = temperature |
| global_max_new_tokens = max_new_tokens |
| global_top_p = top_p |
| global_top_k = top_k |
| global_repetition_penalty = repetition_penalty |
|
|
| def user(user_message, history): |
| return "", history + [[user_message, None]] |
|
|
| def bot( |
| history, |
| system_prompt, |
| temperature, |
| max_new_tokens, |
| top_p, |
| top_k, |
| repetition_penalty, |
| ): |
| print(f"History in bot: {history}") |
| print(f"System Prompt: {system_prompt}") |
| print(f"Temperature: {temperature}") |
| print(f"Max New Tokens: {max_new_tokens}") |
| print(f"Top P: {top_p}") |
| print(f"Top K: {top_k}") |
| print(f"Repetition Penalty: {repetition_penalty}") |
|
|
| history_messages = [{"content": h[0], "role": "user"} for h in history if h[0]] |
| history[-1][1] = "" |
| sys_msg = [ |
| { |
| "content": ( |
| system_prompt if system_prompt else "You are a helpful assistant." |
| ), |
| "role": "system", |
| } |
| ] |
| history_messages = sys_msg + history_messages |
| print(history_messages) |
|
|
| |
| session = requests.Session() |
|
|
| |
| retries = Retry( |
| total=5, |
| backoff_factor=1, |
| status_forcelist=[ |
| 500, |
| 502, |
| 503, |
| 504, |
| ], |
| allowed_methods=[ |
| "HEAD", |
| "GET", |
| "OPTIONS", |
| "POST", |
| ], |
| ) |
| data = { |
| "messages": history_messages, |
| "stream": True, |
| "temprature": temperature, |
| "top_k": top_k, |
| "top_p": top_p, |
| "seed": 42, |
| "repeat_penalty": repetition_penalty, |
| "chat_format": "mistral-instruct", |
| "max_tokens": max_new_tokens, |
| |
| |
| |
| } |
|
|
| |
| session.mount("http://", HTTPAdapter(max_retries=retries)) |
|
|
| |
| try: |
| response = session.post( |
| url, |
| headers=headers, |
| data=json.dumps(data), |
| stream=True, |
| timeout=(10, 30), |
| ) |
| if response.status_code == 200: |
| for line in response.iter_lines(): |
| |
| if line: |
| data = line.decode("utf-8").lstrip("data: ") |
| |
| valid_check = is_valid_json(data) |
| if valid_check[0]: |
| try: |
| |
| |
| json_data = valid_check[1] |
|
|
| delta_content = ( |
| json_data.get("choices", [{}])[0] |
| .get("delta", {}) |
| .get("content", "") |
| ) |
|
|
| if delta_content: |
| history[-1][1] += delta_content |
| time.sleep(0.05) |
| yield history |
| except json.JSONDecodeError as e: |
| print(f"Error decoding JSON: {e} date: {data}") |
| except requests.exceptions.RequestException as e: |
| print(f"An error occurred: {e}") |
|
|
| msg.submit( |
| user, [msg, chatbot], [msg, chatbot], queue=True, concurrency_limit=10 |
| ).then( |
| bot, |
| inputs=[ |
| chatbot, |
| system_prompt_input, |
| temperature_input, |
| max_new_tokens_input, |
| top_p_input, |
| top_k_input, |
| repetition_penalty_input, |
| ], |
| outputs=chatbot, |
| ) |
|
|
| clear.click(lambda: None, None, chatbot, queue=False) |
|
|
|
|
| demo.queue(default_concurrency_limit=20, max_size=20, api_open=False) |
| if __name__ == "__main__": |
| demo.launch(show_api=False, share=False) |
|
|