Update app.py

app.py

@@ -1,32 +1,55 @@
 import gradio as gr
+import subprocess
+import os
 from huggingface_hub import InferenceClient
 
-"""
-For more information on `huggingface_hub` Inference API support, please check the docs: https://huggingface.co/docs/huggingface_hub/v0.22.2/en/guides/inference
-"""
+# 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}"
 
-def respond(
-    message,
-    history: list[tuple[str, str]],
-    system_message,
-    max_tokens,
-    temperature,
-    top_p,
-):
-    messages = [{"role": "system", "content": system_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]})
 
-    messages.append({"role": "user", "content": message})
+    # 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,
@@ -35,30 +58,20 @@ def respond(
         top_p=top_p,
     ):
         token = message.choices[0].delta.content
-
         response += token
         yield response
 
-
-"""
-For information on how to customize the ChatInterface, peruse the gradio docs: https://www.gradio.app/docs/chatinterface
-"""
+# Gradio Interface Setup
 demo = gr.ChatInterface(
     respond,
     additional_inputs=[
-        gr.Textbox(value="You are a friendly Chatbot.", label="System message"),
+        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)",
-        ),
+        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()
+    demo.launch()