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import os
import gradio as gr
from ..core.orchestrator import DesignOrchestrator
# Optimize for Hugging Face Spaces
os.environ["GRADIO_ANALYTICS_ENABLED"] = "False"
os.environ["GRADIO_TEMP_DIR"] = "/tmp"
os.environ["TRANSFORMERS_CACHE"] = "/tmp/transformers_cache"
os.environ["HF_HOME"] = "/tmp/hf_home"
class GradioInterface:
def __init__(self):
self.orchestrator = DesignOrchestrator()
def create_interface(self):
with gr.Blocks(title="Agent2Robot - AI-Powered Vehicle Design") as interface:
gr.Markdown("""
# 🤖 Agent2Robot - Real LLM-Physics Integration System
Transform robot design with AI-driven physics simulation!
""")
with gr.Row():
with gr.Column():
prompt = gr.Textbox(
label="Design Requirements",
placeholder="Enter your robot design requirements...",
lines=3
)
vehicle_type = gr.Dropdown(
choices=["wheeled", "tracked", "legged"],
value="wheeled",
label="Vehicle Type"
)
max_iterations = gr.Slider(
minimum=1,
maximum=5,
value=3,
step=1,
label="Max Iterations"
)
submit_btn = gr.Button("🚀 Design Robot")
with gr.Column():
design_json = gr.JSON(label="Design Specifications")
process_log = gr.Textbox(label="Process Log", lines=10)
simulation_gif = gr.Image(label="Simulation Results")
results_json = gr.JSON(label="Simulation Results")
def process_design(prompt_text: str, v_type: str, iterations: int):
if not prompt_text.strip():
return None, "Please enter design requirements", None, None
try:
design_json, process_log, gif_path, results = self.orchestrator.process_design_request(
prompt=prompt_text,
vehicle_type=v_type,
max_iterations=iterations
)
return design_json, process_log, gif_path, results
except Exception as e:
return None, f"Error: {str(e)}", None, None
submit_btn.click(
fn=process_design,
inputs=[prompt, vehicle_type, max_iterations],
outputs=[design_json, process_log, simulation_gif, results_json]
)
gr.Markdown("""
## How it works
1. Enter your design requirements
2. Select vehicle type and max iterations
3. Click "Design Robot" to start the AI-Physics process
4. View the results in real-time
The system will:
- Generate robot designs using AI
- Simulate them in a physics engine
- Optimize based on performance
- Show you the results
""")
return interface
def create_app():
interface = GradioInterface()
return interface.create_interface()
if __name__ == "__main__":
app = create_app()
app.launch(server_name="0.0.0.0", server_port=7861) |