from huggingface_hub import InferenceClient import gradio as gr import random import prompts client = InferenceClient( "mistralai/Mixtral-8x7B-Instruct-v0.1" ) def format_prompt(message, history): prompt = "" for user_prompt, bot_response in history: prompt += f"[INST] {user_prompt} [/INST]" prompt += f" {bot_response} " prompt += f"[INST] {message} [/INST]" return prompt agents =[ "WEB_DEV", "AI_SYSTEM_PROMPT", "PYTHON_CODE_DEV", "CODE_REVIEW_ASSISTANT ", "CONTENT_WRITER_EDITOR ", "SOCIAL_MEDIA_MANAGER ", ] def generate( prompt, history, agent_name=agents[0], sys_prompt="", temperature=0.9, max_new_tokens=256, top_p=0.95, repetition_penalty=1.0, ): seed = random.randint(1,1111111111111111) agent=prompts.WEB_DEV if agent_name == "WEB_DEV": agent = prompts.WEB_DEV_SYSTEM_PROMPT if agent_name == "CODE_REVIEW_ASSISTANT": agent = prompts.CODE_REVIEW_ASSISTANT if agent_name == "CONTENT_WRITER_EDITOR": agent = prompts.CONTENT_WRITER_EDITOR if agent_name == "SOCIAL_MEDIA_MANAGER": agent = prompts.SOCIAL_MEDIA_MANAGER if agent_name == "AI_SYSTEM_PROMPT": agent = prompts.AI_SYSTEM_PROMPT if agent_name == "PYTHON_CODE_DEV": agent = prompts.PYTHON_CODE_DEV 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=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 output return output additional_inputs=[ gr.Dropdown( label="Agents", choices=[s for s in agents], value=agents[0], interactive=True, ), 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", ), ] examples=[["Write a simple working game in HTML5", agents[0], None, None, None, None, ], ["Choose 3 useful types of AI agents, and create a detailed System Prompt to align each of them.", agents[1], None, None, None, None, ], ["Explain it to me in a childrens story how Nuclear Fission works", agents[4], None, None, None, None, ], ["Show a bunch of examples of catchy ways to post, 'I had a ham sandwich for lunch today'", agents[5], None, None, None, None, ], ["Write high quality personal website to show off my adventure sports hobby", agents[0], None, None, None, None, ], ["I'm planning a vacation to Japan. Can you suggest a one-week itinerary including must-visit places and local cuisines to try?", agents[4], None, None, None, None, ], ["Can you write a short story about a time-traveling detective who solves historical mysteries?", agents[4], 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?", agents[4], 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?", agents[4], None, None, None, None,], ["Can you explain how the QuickSort algorithm works and provide a Python implementation?", agents[2], None, None, None, None,], ["What are some unique features of Rust that make it stand out compared to other systems programming languages like C++?", agents[3], 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)