Delete app.py

app.py

@@ -1,193 +0,0 @@
-import os
-import json
-import time
-import requests
-import gradio as gr
-
-# Read secrets and sanitize URL
-ENDPOINT_URL = (os.environ.get("ENDPOINT_URL") or "https://erxvjreo1onxvdf7.us-east4.gcp.endpoints.huggingface.cloud").strip().rstrip("/")
-HF_TOKEN = (os.environ.get("HF_TOKEN") or "").strip()
-
-# Debug logging
-print(f"🚀 DEBUG: ENDPOINT_URL set to: {ENDPOINT_URL}")
-print(f"🚀 DEBUG: HF_TOKEN present: {'Yes' if HF_TOKEN else 'No'}")
-
-if not ENDPOINT_URL:
-	raise RuntimeError("Missing ENDPOINT_URL Space secret")
-
-HEADERS = {
-	"Content-Type": "application/json",
-	"Accept": "application/json",
-}
-if HF_TOKEN:
-	HEADERS["Authorization"] = f"Bearer {HF_TOKEN}"
-
-SYSTEM_PROMPT_DEFAULT = (
-	"You are a helpful AI assistant for Isaac Sim 5.0, Isaac Lab 2.1, and Omniverse Kit 107.3 robotics development. "
-	"You specialize in NVIDIA robotics development, computer vision, sensor integration, and simulation workflows. "
-	"Provide practical, code-focused guidance with complete examples and best practices."
-)
-
-DEFAULT_MAX_NEW_TOKENS = 1024
-DEFAULT_MAX_INPUT_TOKENS = 2048
-
-def to_single_turn(messages):
-	lines = []
-	for m in messages:
-		role = m.get("role", "user").capitalize()
-		lines.append(f"{role}: {m.get('content','')}")
-	lines.append("Assistant:")
-	return "\n".join(lines)
-
-def call_endpoint(messages, parameters):
-	start = time.time()
-	
-	# Debug logging
-	print(f"🔍 DEBUG: Calling endpoint: {ENDPOINT_URL}")
-	print(f"🔍 DEBUG: Headers: {HEADERS}")
-	
-	# Prefer single-turn first (matches your handler expectations)
-	payload_inputs = {"inputs": to_single_turn(messages), "parameters": parameters}
-	print(f"🔍 DEBUG: Payload: {payload_inputs}")
-	
-	resp = requests.post(ENDPOINT_URL, headers=HEADERS, json=payload_inputs, timeout=120)
-	latency = time.time() - start
-
-	print(f"🔍 DEBUG: Response status: {resp.status_code}")
-	print(f"🔍 DEBUG: Response body: {resp.text}")
-
-	if resp.status_code == 200:
-		data = resp.json()
-		text = data.get("generated_text") if isinstance(data, dict) else str(data)
-		return text or "", latency
-
-	# Fallback to messages for servers that support chat
-	print(f"🔍 DEBUG: First attempt failed, trying messages format...")
-	resp2 = requests.post(
-		ENDPOINT_URL,
-		headers=HEADERS,
-		json={"messages": messages, "parameters": parameters},
-		timeout=120,
-	)
-	latency = time.time() - start
-	print(f"🔍 DEBUG: Fallback response status: {resp2.status_code}")
-	print(f"🔍 DEBUG: Fallback response body: {resp2.text}")
-	
-	if resp2.status_code == 200:
-		data = resp2.json()
-		text = data.get("generated_text") if isinstance(data, dict) else str(data)
-		return text or "", latency
-
-	return f"HTTP {resp.status_code}/{resp2.status_code}: {resp.text or resp2.text}", latency
-
-def build_messages(chat_history, user_input, system_prompt):
-	messages = []
-	if system_prompt and system_prompt.strip():
-		messages.append({"role": "system", "content": system_prompt.strip()})
-	else:
-		messages.append({"role": "system", "content": SYSTEM_PROMPT_DEFAULT})
-	for u, b in chat_history:
-		if u:
-			messages.append({"role": "user", "content": u})
-		if b:
-			messages.append({"role": "assistant", "content": b})
-	if user_input:
-		messages.append({"role": "user", "content": user_input})
-	return messages
-
-def trim_history(chat_history, max_turns=4):
-	return chat_history[-max_turns:]
-
-def to_chatbot_messages(chat_history):
-	msgs = []
-	for u, a in chat_history:
-		if u:
-			msgs.append({"role": "user", "content": u})
-		if a:
-			msgs.append({"role": "assistant", "content": a})
-	return msgs
-
-def respond(user_input, chat_history, temperature, top_p, max_new_tokens, max_input_tokens, system_prompt):
-	if not user_input:
-		return gr.update(value=""), chat_history, to_chatbot_messages(chat_history), gr.update(value="")
-
-	chat_history = trim_history(chat_history, max_turns=4)
-
-	params = {
-		"max_new_tokens": int(max_new_tokens),
-		"temperature": float(temperature),
-		"top_p": float(top_p),
-		"max_input_tokens": int(max_input_tokens),
-	}
-	messages = build_messages(chat_history, user_input, system_prompt)
-
-	# Show the user message immediately
-	chat_history = chat_history + [(user_input, None)]
-	reply, latency = call_endpoint(messages, params)
-	chat_history[-1] = (user_input, reply)
-
-	# Clear input, update state, update chatbot (messages format), update latency
-	return "", chat_history, to_chatbot_messages(chat_history), f"{latency:.2f}s"
-
-def new_chat():
-	return [], [], ""
-
-custom_css = """
-#app {max-width: 980px; margin: 0 auto;}
-footer {visibility: hidden;}
-.gradio-container {font-size: 14px;}
-#controls .label-wrap {min-width: 160px;}
-"""
-
-with gr.Blocks(title="Qwen2.5‑Coder‑7B‑Instruct‑Omni1.1 (Isaac Sim Robotics Assistant)", css=custom_css) as demo:
-	gr.Markdown("### Qwen2.5‑Coder‑7B‑Instruct‑Omni1.1\nChat with your Isaac Sim 5.0 robotics development assistant. This Space calls the TomBombadyl/Qwen2.5-Coder-7B-Instruct-Omni1.1 Inference Endpoint powered by NVIDIA L4 GPU.")
-
-	# Chat at the top (messages format to avoid deprecation)
-	chatbot = gr.Chatbot(height=520, show_copy_button=True, type="messages")
-
-	# Input row
-	with gr.Row():
-		user_input = gr.Textbox(placeholder="Ask about Isaac Sim robotics, computer vision, sensors, simulation...", lines=2, scale=8)
-		send_btn = gr.Button("Send", variant="primary", scale=1)
-		new_btn = gr.Button("New chat", scale=1)
-
-	# Right-aligned utility row
-	with gr.Row():
-		latency_lbl = gr.Label(value="", label="Latency")
-
-	# Advanced settings (collapsed)
-	with gr.Accordion("Advanced settings", open=False):
-		with gr.Row(elem_id="controls"):
-			temperature = gr.Slider(0.0, 1.5, value=0.2, step=0.05, label="temperature")
-			top_p = gr.Slider(0.1, 1.0, value=0.7, step=0.01, label="top_p")
-			max_new_tokens = gr.Slider(16, 1024, value=DEFAULT_MAX_NEW_TOKENS, step=128, label="max_new_tokens")
-			max_input_tokens = gr.Slider(256, 8192, value=DEFAULT_MAX_INPUT_TOKENS, step=256, label="max_input_tokens")
-		system_prompt = gr.Textbox(
-			value=SYSTEM_PROMPT_DEFAULT,
-			label="System prompt",
-			lines=3,
-			placeholder="Optional system instruction for the assistant",
-		)
-
-	chat_state = gr.State([])  # still store as list of (user, assistant) tuples
-
-	# Return chatbot directly so responses render immediately
-	send_btn.click(
-		fn=respond,
-		inputs=[user_input, chat_state, temperature, top_p, max_new_tokens, max_input_tokens, system_prompt],
-		outputs=[user_input, chat_state, chatbot, latency_lbl],
-	)
-	user_input.submit(
-		fn=respond,
-		inputs=[user_input, chat_state, temperature, top_p, max_new_tokens, max_input_tokens, system_prompt],
-		outputs=[user_input, chat_state, chatbot, latency_lbl],
-	)
-
-	# New chat resets state and chatbot
-	new_btn.click(fn=new_chat, outputs=[chat_state, chatbot, latency_lbl])
-
-# Enable queuing with defaults (avoid unsupported keyword args on older Gradio)
-demo.queue()
-
-if __name__ == "__main__":
-	demo.launch()