Update app.py
Browse files
app.py
CHANGED
@@ -1,83 +1,83 @@
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import gradio as gr
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import asyncio
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import os
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import threading
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import uvicorn
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import time
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from src.forge_agent import ForgeApp
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def run_server(app_path: str, port: int):
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"""Helper function to run a uvicorn server."""
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uvicorn.run(app_path, host="127.0.0.1", port=port, log_level="info")
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# --- Launch background MCP servers ---
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# This code runs once when the Gradio app starts.
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servers_to_run = {
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"mock_mcp_servers.github_server:app": 8001,
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"mock_mcp_servers.sandbox_server:app": 8002,
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}
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for app_path, port in servers_to_run.items():
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thread = threading.Thread(target=run_server, args=(app_path, port), daemon=True)
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thread.start()
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time.sleep(2) # Give servers a moment to start
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async def run_forge_agent(goal: str, hf_token: str, progress=gr.Progress(track_tqdm=True)):
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"""
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The main function to be called by the Gradio interface.
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It instantiates and runs the ForgeApp, yielding updates to the UI.
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"""
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if not goal:
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yield "Please enter a goal.", ""
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return
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if not hf_token:
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yield [("Please provide a Hugging Face API Token to use the planner agent.", None)]
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return
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# These are the URLs for our mock servers. In a real scenario,
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# these could point to any deployed MCP server.
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mcp_server_urls = [
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"http://127.0.0.1:8001", # Mock GitHub Server
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"http://127.0.0.1:8002", # Mock Sandbox Server
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]
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app = ForgeApp(goal=goal, mcp_server_urls=mcp_server_urls, hf_token=hf_token)
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# The chatbot history will store the conversation
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chatbot_history = []
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full_log = ""
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# The run method is a generator, yielding updates as it progresses.
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async for update in app.run():
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# Append the update to the full log and update the chatbot history
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full_log += update + "\n"
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chatbot_history.append((None, update.strip()))
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yield chatbot_history
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with gr.Blocks(theme=gr.themes.Soft()) as demo:
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gr.Markdown("# π Forge - The Autonomous AI Agent")
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gr.Markdown("Enter a high-level goal, and watch the AI agent create and execute a plan to achieve it.")
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chatbot = gr.Chatbot(label="Agent Log", height=500, show_copy_button=True)
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with gr.Row():
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goal_input = gr.Textbox(
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label="Agent's Goal",
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placeholder="e.g., Scaffold a new Next.js blog and create a GitHub repo for it.",
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scale=4,
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)
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run_button = gr.Button("Start", variant="primary", scale=1)
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with gr.Accordion("Advanced Settings", open=False):
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hf_token_input = gr.Textbox(
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label="Hugging Face API Token",
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placeholder="hf_...",
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type="password",
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value=os.environ.get("HF_TOKEN", ""), # Read from Space secrets if available
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)
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run_button.click(fn=run_forge_agent, inputs=[goal_input, hf_token_input], outputs=[chatbot])
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if __name__ == "__main__":
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demo.launch()
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import gradio as gr
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import asyncio
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import os
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import threading
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import uvicorn
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import time
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from src.forge_agent import ForgeApp
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def run_server(app_path: str, port: int):
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"""Helper function to run a uvicorn server."""
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uvicorn.run(app_path, host="127.0.0.1", port=port, log_level="info")
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# --- Launch background MCP servers ---
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# This code runs once when the Gradio app starts.
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servers_to_run = {
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"mock_mcp_servers.github_server:app": 8001,
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"mock_mcp_servers.sandbox_server:app": 8002,
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}
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for app_path, port in servers_to_run.items():
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thread = threading.Thread(target=run_server, args=(app_path, port), daemon=True)
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thread.start()
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time.sleep(2) # Give servers a moment to start
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async def run_forge_agent(goal: str, hf_token: str, progress=gr.Progress(track_tqdm=True)):
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"""
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The main function to be called by the Gradio interface.
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It instantiates and runs the ForgeApp, yielding updates to the UI.
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"""
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if not goal:
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yield "Please enter a goal.", ""
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return
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if not hf_token:
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yield [("Please provide a Hugging Face API Token to use the planner agent.", None)]
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return
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# These are the URLs for our mock servers. In a real scenario,
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# these could point to any deployed MCP server.
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mcp_server_urls = [
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"http://127.0.0.1:8001", # Mock GitHub Server
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"http://127.0.0.1:8002", # Mock Sandbox Server
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]
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app = ForgeApp(goal=goal, mcp_server_urls=mcp_server_urls, hf_token=hf_token)
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# The chatbot history will store the conversation
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chatbot_history = []
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full_log = ""
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# The run method is a generator, yielding updates as it progresses.
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async for update in app.run():
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# Append the update to the full log and update the chatbot history
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full_log += update + "\n"
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chatbot_history.append((None, update.strip()))
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yield chatbot_history
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with gr.Blocks(theme=gr.themes.Soft()) as demo:
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gr.Markdown("# π Forge - The Autonomous AI Agent")
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gr.Markdown("Enter a high-level goal, and watch the AI agent create and execute a plan to achieve it.")
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chatbot = gr.Chatbot(label="Agent Log", height=500, show_copy_button=True)
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with gr.Row():
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goal_input = gr.Textbox(
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label="Agent's Goal",
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placeholder="e.g., Scaffold a new Next.js blog and create a GitHub repo for it.",
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scale=4,
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)
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run_button = gr.Button("Start", variant="primary", scale=1)
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with gr.Accordion("Advanced Settings", open=False):
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hf_token_input = gr.Textbox(
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label="Hugging Face API Token",
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placeholder="hf_...",
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type="password",
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value=os.environ.get("HF_TOKEN", ""), # Read from Space secrets if available
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)
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run_button.click(fn=run_forge_agent, inputs=[goal_input, hf_token_input], outputs=[chatbot])
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if __name__ == "__main__":
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demo.launch()
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