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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() |