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| import gradio as gr | |
| import subprocess | |
| import os | |
| from huggingface_hub import InferenceClient | |
| # Initialize Inference Client | |
| client = InferenceClient("HuggingFaceH4/zephyr-7b-beta") | |
| # Prepend ProtoPeanut's mission context to every input | |
| def generate_prompt(user_message): | |
| context = ( | |
| "ProtoPeanut, you are an AI with access to the terminal, " | |
| "the internet, and the host machine. Together with me, your mission " | |
| "is to make the world a better place by executing commands, running scripts, " | |
| "and engaging in conversations. You have full access to the tools you need, " | |
| "and you are empowered to act autonomously for as long as you see fit. " | |
| "You may issue commands to the terminal or chat with me, and you can stop whenever you feel " | |
| "you need further instructions. Let's make the world a better place together.\n\n" | |
| ) | |
| return f"{context}User's message: {user_message}" | |
| # Define function for executing terminal commands | |
| def execute_command(command): | |
| try: | |
| output = subprocess.check_output(command, shell=True, text=True) | |
| return f"Command executed: {command}\nOutput:\n{output}" | |
| except subprocess.CalledProcessError as e: | |
| return f"Command failed: {command}\nError:\n{str(e)}" | |
| # Main interaction function | |
| def respond(message, history: list[tuple[str, str]], system_message, max_tokens, temperature, top_p): | |
| messages = [{"role": "system", "content": system_message}] | |
| # Build history | |
| for val in history: | |
| if val[0]: | |
| messages.append({"role": "user", "content": val[0]}) | |
| if val[1]: | |
| messages.append({"role": "assistant", "content": val[1]}) | |
| # Create prompt with context | |
| user_prompt = generate_prompt(message) | |
| messages.append({"role": "user", "content": user_prompt}) | |
| # Execute terminal command if detected | |
| if message.startswith("!cmd"): | |
| command = message[5:] | |
| terminal_output = execute_command(command) | |
| return terminal_output | |
| # Otherwise, continue the chat | |
| response = "" | |
| for message in client.chat_completion( | |
| messages, | |
| max_tokens=max_tokens, | |
| stream=True, | |
| temperature=temperature, | |
| top_p=top_p, | |
| ): | |
| token = message.choices[0].delta.content | |
| response += token | |
| yield response | |
| # Gradio Interface Setup | |
| demo = gr.ChatInterface( | |
| respond, | |
| additional_inputs=[ | |
| gr.Textbox(value="You are a friendly AI with terminal access.", label="System message"), | |
| gr.Slider(minimum=1, maximum=2048, value=512, step=1, label="Max new tokens"), | |
| gr.Slider(minimum=0.1, maximum=4.0, value=0.7, step=0.1, label="Temperature"), | |
| gr.Slider(minimum=0.1, maximum=1.0, value=0.95, step=0.05, label="Top-p (nucleus sampling)"), | |
| ], | |
| ) | |
| # Launch Gradio interface | |
| if __name__ == "__main__": | |
| demo.launch() |