Ghost-Coder / app.py
muhammadtlha944's picture
Adding real droplet TIP and real-time simulations
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import gradio as gr
import requests
import time
# --- CONFIGURATION ---
# Replace this with your actual Droplet IP
DROPLET_IP = "134.199.195.151"
API_URL = f"http://{DROPLET_IP}:8080/translate"
# --- LOGIC ---
def ghost_translate(cuda_code):
# Step 1: UI Feedback
yield "👻 Ghost-Coder: Analyzing CUDA Kernel...", "Loading..."
try:
# Step 2: Real API Call to your MI300X
# We wrap this in a try/except in case the bridge isn't reachable
response = requests.post(API_URL, json={"code": cuda_code}, timeout=120)
if response.status_code == 200:
hip_code = response.json().get("hip_code", "// Error: No code returned")
# Step 3: Simulate the 'Self-Healing' steps for visual impact
yield "🔄 Analyzing HIP logic on ROCm stack...", "Generating..."
time.sleep(1.5)
yield "🛠️ Verifying syntax and memory offsets...", "Verifying..."
time.sleep(1.5)
yield "✅ Self-Healing successful! HIP Code generated.", hip_code
else:
yield f"❌ Droplet Error: {response.status_code}", "// Check bridge logs on MI300X"
except Exception as e:
yield f"❌ Connection Error: Ensure bridge is running on {DROPLET_IP}", str(e)
# --- UI DESIGN ---
with gr.Blocks(theme=gr.themes.Soft()) as demo:
gr.Markdown("# 👻 Ghost-Coder: Autonomous CUDA-to-HIP Agent")
gr.Markdown("### Powered by AMD Instinct™ MI300X | Qwen2.5-Coder-32B")
with gr.Row():
with gr.Column():
input_code = gr.Code(label="Paste CUDA Code Here", language="cpp", lines=15)
run_btn = gr.Button("Translate & Verify", variant="primary")
with gr.Column():
output_code = gr.Code(label="Generated HIP Code", language="cpp", lines=15)
logs = gr.Textbox(label="Agent Status & Self-Healing Logs", interactive=False)
run_btn.click(ghost_translate, inputs=[input_code], outputs=[logs, output_code])
demo.queue().launch() # Added .queue() for better streaming performance