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from huggingface_hub import InferenceClient | |
import gradio as gr | |
import prompts | |
client = InferenceClient( | |
"mistralai/Mixtral-8x7B-Instruct-v0.1" | |
) | |
def format_prompt(message, history): | |
prompt = "<s>" | |
for user_prompt, bot_response in history: | |
prompt += f"[INST] {user_prompt} [/INST]" | |
prompt += f" {bot_response}</s> " | |
prompt += f"[INST] {message} [/INST]" | |
return prompt | |
agents =[ | |
"WEB_DEV", | |
"AI_SYSTEM_PROMPT", | |
] | |
def generate( | |
prompt, history, sys_prompt, temperature=0.9, max_new_tokens=256, top_p=0.95, repetition_penalty=1.0, agent_name=agents[0], | |
): | |
agent=prompt.AI_SYSTEM_PROMPT | |
if agent_name == "WEB_DEV": | |
agent = prompts.WEB_DEV | |
if agent_name == "AI_SYSTEM_PROMPT": | |
agent = prompts.AI_SYSTEM_PROMPT | |
system_prompt=agent | |
temperature = float(temperature) | |
if temperature < 1e-2: | |
temperature = 1e-2 | |
top_p = float(top_p) | |
generate_kwargs = dict( | |
temperature=temperature, | |
max_new_tokens=max_new_tokens, | |
top_p=top_p, | |
repetition_penalty=repetition_penalty, | |
do_sample=True, | |
seed=42, | |
) | |
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 output | |
return output | |
additional_inputs=[ | |
gr.Textbox( | |
label="System Prompt", | |
max_lines=1, | |
interactive=True, | |
), | |
gr.Slider( | |
label="Temperature", | |
value=0.9, | |
minimum=0.0, | |
maximum=1.0, | |
step=0.05, | |
interactive=True, | |
info="Higher values produce more diverse outputs", | |
), | |
gr.Slider( | |
label="Max new tokens", | |
value=1048*10, | |
minimum=0, | |
maximum=1048*10, | |
step=64, | |
interactive=True, | |
info="The maximum numbers of new tokens", | |
), | |
gr.Slider( | |
label="Top-p (nucleus sampling)", | |
value=0.90, | |
minimum=0.0, | |
maximum=1, | |
step=0.05, | |
interactive=True, | |
info="Higher values sample more low-probability tokens", | |
), | |
gr.Slider( | |
label="Repetition penalty", | |
value=1.2, | |
minimum=1.0, | |
maximum=2.0, | |
step=0.05, | |
interactive=True, | |
info="Penalize repeated tokens", | |
), | |
gr.Dropdown( | |
label="Agents", | |
choices=[s for s in agents], | |
value=agents[0], | |
interactive=True, | |
), | |
] | |
examples=[["I'm planning a vacation to Japan. Can you suggest a one-week itinerary including must-visit places and local cuisines to try?", None, None, None, None, None, ], | |
["Can you write a short story about a time-traveling detective who solves historical mysteries?", None, None, None, None, None,], | |
["I'm trying to learn French. Can you provide some common phrases that would be useful for a beginner, along with their pronunciations?", None, None, None, None, None,], | |
["I have chicken, rice, and bell peppers in my kitchen. Can you suggest an easy recipe I can make with these ingredients?", None, None, None, None, None,], | |
["Can you explain how the QuickSort algorithm works and provide a Python implementation?", None, None, None, None, None,], | |
["What are some unique features of Rust that make it stand out compared to other systems programming languages like C++?", None, None, None, None, None,], | |
] | |
gr.ChatInterface( | |
fn=generate, | |
chatbot=gr.Chatbot(show_label=False, show_share_button=False, show_copy_button=True, likeable=True, layout="panel"), | |
additional_inputs=additional_inputs, | |
title="Mixtral 46.7B", | |
examples=examples, | |
concurrency_limit=20, | |
).launch(show_api=False) | |