Update app.py

app.py

@@ -3,17 +3,11 @@ import base64
 import gradio as gr
 from huggingface_hub import upload_file, InferenceClient
 import json
-from fastmcp import FastMCP
 
 # --- Config ---
 HF_DATASET_REPO = "OppaAI/Robot_MCP"
 HF_VLM_MODEL = "Qwen/Qwen2.5-VL-7B-Instruct"
 
-# --- MCP server instance ---
-mcp = FastMCP(name="Robot MCP")
-
-# --- MCP Tool ---
-@mcp.tool()
 def say_hi(greeting_text: str = "Hi there!") -> dict:
     """Return a greeting command in JSON."""
     return {"command": "say_hi", "text": greeting_text}
@@ -55,7 +49,6 @@ def process_and_describe(payload: dict):
         # Initialize HF client
         hf_client = InferenceClient(token=hf_token)
 
-        # System prompt (without stio.describe_tools because not using STIO here)
         system_prompt = """
         You are a helpful robot assistant.
         When you receive an image, you must:
@@ -93,12 +86,6 @@ def process_and_describe(payload: dict):
         except json.JSONDecodeError:
             action_data = {"description": vlm_text, "action": None, "greeting_text": None}
 
-        # Call the tool if action == say_hi
-        tool_result = None
-        if action_data.get("action") == "say_hi":
-            greeting = action_data.get("greeting_text") or "Hi!"
-            tool_result = say_hi(greeting_text=greeting)
-
         return {
             "saved_to_hf_hub": True,
             "repo_id": HF_DATASET_REPO,
@@ -124,13 +111,4 @@ demo = gr.Interface(
 )
 
 if __name__ == "__main__":
-    # Run FastMCP server *in the same process* (blocking)
-    import threading
-
-    def run_mcp():
-        mcp.run(transport="stdio")
-
-    t = threading.Thread(target=run_mcp, daemon=True)
-    t.start()
-
-    demo.launch(mcp_server=True)
+    demo.launch()