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import asyncio
import logging
import os
import threading
import time
import gradio as gr
import uvicorn
from fastapi import FastAPI
from fastapi.middleware.cors import CORSMiddleware
from fastapi.responses import RedirectResponse
# Import our existing components
from inference_server.main import app as fastapi_app
from inference_server.main import session_manager
logger = logging.getLogger(__name__)
# Configuration
DEFAULT_PORT = 7860
DEFAULT_TRANSPORT_SERVER_URL = os.getenv(
"TRANSPORT_SERVER_URL", "http://localhost:8000"
)
# Global server thread
server_thread = None
server_started = False
def start_api_server_thread(port: int = 8001):
"""Start the API server in a background thread."""
global server_thread, server_started
if server_thread and server_thread.is_alive():
return
def run_server():
global server_started
logger.info(f"Starting AI server on port {port}")
uvicorn.run(fastapi_app, host="0.0.0.0", port=port, log_level="warning")
server_started = False
server_thread = threading.Thread(target=run_server, daemon=True)
server_thread.start()
server_started = True
# Wait a moment for server to start
time.sleep(2)
def create_gradio(
transport_server_url: str = DEFAULT_TRANSPORT_SERVER_URL,
) -> gr.Blocks:
"""Create an enhanced Gradio interface with step-by-step workflow."""
server_manager = ServerManagement()
custom_css = """
.gradio-container {
max-width: 1200px !important;
margin: 0 auto !important;
padding: 20px !important;
}
.main-header {
text-align: center;
margin-bottom: 30px;
padding: 20px;
border-radius: 10px;
}
.main-header h1 {
margin: 0;
font-size: 2.5em;
font-weight: bold;
}
.main-header p {
margin: 10px 0 0 0;
font-size: 1.1em;
opacity: 0.8;
}
.status-display {
font-family: monospace;
font-size: 0.9em;
}
"""
with gr.Blocks(
title="๐ค RobotHub AI Control Center",
theme=gr.themes.Soft(),
css=custom_css,
) as demo:
# Main header
with gr.Row():
with gr.Column():
gr.HTML("""
<div class="main-header">
<h1>๐ค RobotHub AI Control Center</h1>
<p>Control your robot with AI using ACT (Action Chunking Transformer) models</p>
</div>
""")
# Step 1: Server Status
with gr.Group():
gr.Markdown("## ๐ก Step 1: AI Server Status")
with gr.Row():
with gr.Column(scale=3):
server_status_display = gr.Textbox(
label="Server Status",
value="โ
Integrated server ready",
interactive=False,
lines=2,
elem_classes="status-display",
)
with gr.Column(scale=1, min_width=200):
check_status_btn = gr.Button(
"๐ Check Status", variant="secondary", size="lg"
)
# Step 2: Robot Setup
with gr.Group():
gr.Markdown("## ๐ค Step 2: Set Up Robot AI")
with gr.Row():
with gr.Column(scale=2):
session_name = gr.Textbox(
label="Session Name",
placeholder="my-robot-session",
value="my-robot-01",
)
model_path = gr.Textbox(
label="AI Model Path",
placeholder="LaetusH/act_so101_beyond",
value="LaetusH/act_so101_beyond",
)
camera_names = gr.Textbox(
label="Camera Names (comma-separated)",
placeholder="front, wrist, overhead",
value="front",
)
transport_server_url = gr.Textbox(
label="Transport Server URL",
placeholder="http://localhost:8000",
value=transport_server_url,
)
with gr.Row():
create_btn = gr.Button(
"๐ฏ Create & Start AI Control", variant="primary", size="lg"
)
with gr.Column(scale=2):
setup_result = gr.Textbox(
label="Setup Result",
lines=12,
interactive=False,
placeholder="Click 'Create & Start AI Control' to begin...",
elem_classes="status-display",
)
# Step 3: Control Session
with gr.Group():
gr.Markdown("## ๐ฎ Step 3: Control Session")
with gr.Row():
with gr.Column(scale=2):
session_id_input = gr.Textbox(
label="Session ID",
placeholder="Will be auto-filled",
interactive=True,
)
with gr.Column(scale=2), gr.Row():
start_btn = gr.Button("โถ๏ธ Start", variant="primary")
stop_btn = gr.Button("โน๏ธ Stop", variant="secondary")
status_btn = gr.Button("๐ Status", variant="secondary")
session_status_display = gr.Textbox(
label="Session Status",
lines=10,
interactive=False,
elem_classes="status-display",
)
# Event handlers
check_status_btn.click(
fn=server_manager.check_server_status,
outputs=[server_status_display],
)
create_btn.click(
fn=server_manager.create_and_start_session,
inputs=[session_name, model_path, camera_names, transport_server_url],
outputs=[session_id_input, setup_result],
)
start_btn.click(
fn=server_manager.start_session,
inputs=[session_id_input],
outputs=[session_status_display],
)
stop_btn.click(
fn=server_manager.stop_session,
inputs=[session_id_input],
outputs=[session_status_display],
)
status_btn.click(
fn=server_manager.get_session_status,
inputs=[session_id_input],
outputs=[session_status_display],
)
# Auto-refresh on load
demo.load(server_manager.check_server_status, outputs=[server_status_display])
# Add helpful instructions
with gr.Group():
gr.Markdown("""
---
### ๐ Quick Guide:
1. **Server Status**: The integrated server is ready by default
2. **Configure Your Robot**: Enter your model path and camera setup (Step 2)
3. **Create Session**: Click "Create & Start AI Control" to begin
4. **Monitor & Control**: Use Step 3 to start/stop and monitor your session
๐ก **Tips**:
- Make sure your ACT model path exists before creating a session
- Camera names should match your robot's camera configuration
- Session will automatically start after creation
- All components run in a single integrated process for simplicity
""")
return demo
class ServerManagement:
"""Enhanced session management with better error handling and status display."""
def check_server_status(self):
"""Check the status of the integrated server."""
try:
# Since we're running integrated, we can check session_manager directly
if hasattr(session_manager, "sessions"):
active_count = len([
s
for s in session_manager.sessions.values()
if s.status == "running"
])
total_count = len(session_manager.sessions)
return f"โ
Integrated server running - {active_count}/{total_count} sessions active"
return "โ
Integrated server ready - No active sessions"
except Exception as e:
return f"โ ๏ธ Server check failed: {e!s}"
def create_and_start_session(
self, session_name: str, model_path: str, camera_names: str, transport_url: str
):
"""Create and start a new session with enhanced error handling."""
try:
# Input validation
if not session_name.strip():
return "", "โ Session name cannot be empty"
if not model_path.strip():
return "", "โ Model path cannot be empty"
# Parse camera names
cameras = [c.strip() for c in camera_names.split(",") if c.strip()]
if not cameras:
cameras = ["front"]
# Create session directly using session_manager
# Use asyncio.run to handle the async function
try:
room_info = asyncio.run(
session_manager.create_session(
session_id=session_name.strip(),
policy_path=model_path.strip(),
camera_names=cameras,
transport_server_url=transport_url.strip(),
)
)
# Start the session
asyncio.run(session_manager.start_inference(session_name.strip()))
success_msg = f"""โ
Session '{session_name}' created and started!
๐ก Configuration:
โข Model: {model_path}
โข Cameras: {", ".join(cameras)}
โข Transport: {transport_url}
โข Workspace: {room_info["workspace_id"]}
๐ Rooms Created:
โข Camera rooms: {", ".join(f"{k}:{v}" for k, v in room_info["camera_room_ids"].items())}
โข Joint input: {room_info["joint_input_room_id"]}
โข Joint output: {room_info["joint_output_room_id"]}
๐ค Ready for robot control!"""
return session_name.strip(), success_msg
except Exception as e:
error_msg = f"โ Error creating/starting session: {e!s}"
logger.exception(error_msg)
return "", error_msg
except Exception as e:
error_msg = f"โ Error creating session: {e!s}"
logger.exception(error_msg)
return "", error_msg
def start_session(self, session_id: str):
"""Start an existing session with better error handling."""
if not session_id.strip():
return "โ ๏ธ Please provide a session ID"
try:
import asyncio
asyncio.run(session_manager.start_inference(session_id.strip()))
return f"โ
Session `{session_id}` started successfully!"
except Exception as e:
error_msg = f"โ Failed to start session: {e!s}"
logger.exception(error_msg)
return error_msg
def stop_session(self, session_id: str):
"""Stop an existing session with better error handling."""
if not session_id.strip():
return "โ ๏ธ Please provide a session ID"
try:
import asyncio
asyncio.run(session_manager.stop_inference(session_id.strip()))
return f"โน๏ธ Session `{session_id}` stopped successfully!"
except Exception as e:
error_msg = f"โ Failed to stop session: {e!s}"
logger.exception(error_msg)
return error_msg
def get_session_status(self, session_id: str):
"""Get detailed session status with enhanced display."""
if not session_id.strip():
return "โ ๏ธ Please provide a session ID"
try:
# Access the session directly from session_manager.sessions
session_id_clean = session_id.strip()
if session_id_clean not in session_manager.sessions:
return f"โ Session `{session_id}` not found"
# Get session and call its get_status method
session = session_manager.sessions[session_id_clean]
status = session.get_status()
# Enhanced status display with emojis
status_emoji = {
"running": "๐ข",
"ready": "๐ก",
"stopped": "๐ด",
"initializing": "๐ ",
"error": "โ",
"timeout": "โฐ",
}.get(status.get("status", "unknown"), "โช")
status_msg = f"""{status_emoji} Session: `{session_id}`
**Status:** {status.get("status", "Unknown").upper()}
**Model:** {status.get("policy_path", "N/A")}
**Policy Type:** {status.get("policy_type", "N/A")}
**Cameras:** {", ".join(status.get("camera_names", []))}
**Workspace:** {status.get("workspace_id", "N/A")}
๐ **Performance:**
โข Inferences: {status.get("stats", {}).get("inference_count", 0)}
โข Commands sent: {status.get("stats", {}).get("commands_sent", 0)}
โข Queue length: {status.get("stats", {}).get("actions_in_queue", 0)}
โข Errors: {status.get("stats", {}).get("errors", 0)}
๐ง **Data Flow:**
โข Images received: {status.get("stats", {}).get("images_received", {})}
โข Joint states received: {status.get("stats", {}).get("joints_received", 0)}
๐ **Rooms:**
โข Camera rooms: {", ".join(f"{k}:{v}" for k, v in status.get("rooms", {}).get("camera_room_ids", {}).items())}
โข Joint input: {status.get("rooms", {}).get("joint_input_room_id", "N/A")}
โข Joint output: {status.get("rooms", {}).get("joint_output_room_id", "N/A")}"""
return status_msg
except Exception as e:
error_msg = f"โ Error getting status: {e!s}"
logger.exception(error_msg)
return error_msg
def launch_simple_integrated_app(
host: str = "0.0.0.0",
port: int = DEFAULT_PORT,
share: bool = False,
transport_server_url: str = DEFAULT_TRANSPORT_SERVER_URL,
):
"""Launch the enhanced integrated application with both FastAPI and Gradio."""
print(f"๐ Starting enhanced integrated app on {host}:{port}")
print(f"๐จ Gradio UI: http://{host}:{port}/")
print(f"๐ FastAPI Docs: http://{host}:{port}/api/docs")
print(f"๐ Health Check: http://{host}:{port}/api/health")
print(f"๐ Transport Server: {transport_server_url}")
print("๐ง Enhanced direct session management + API access!")
# Create enhanced Gradio demo
demo = create_gradio(transport_server_url=transport_server_url)
# Create main FastAPI app
app = FastAPI(
title="๐ค RobotHub AI Control Center",
description="Enhanced Integrated ACT Model Inference Server with Web Interface",
version="1.0.0",
)
# Add CORS middleware
app.add_middleware(
CORSMiddleware,
allow_origins=["*"],
allow_credentials=True,
allow_methods=["*"],
allow_headers=["*"],
)
# Mount the FastAPI AI server under /api
app.mount("/api", fastapi_app)
# Mount Gradio at a subpath
app = gr.mount_gradio_app(app, demo, path="/gradio")
# Add custom root endpoint that redirects to /gradio/
@app.get("/")
def root_redirect():
return RedirectResponse(url="/gradio/", status_code=302)
# Launch with uvicorn
uvicorn.run(
app,
host=host,
port=port,
log_level="info",
)
if __name__ == "__main__":
launch_simple_integrated_app()
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