Update app.py

app.py

@@ -22,7 +22,6 @@ mcp = FastMCP("Robot_MCP")
 # -----------------------------------------------------
 @mcp.tool()
 def speak(text: str, emotion: str = "neutral"):
-    """Robot speech output"""
     return {
         "status": "success",
         "action_executed": "speak",
@@ -32,7 +31,6 @@ def speak(text: str, emotion: str = "neutral"):
 
 @mcp.tool()
 def navigate(direction: str, distance_meters: float):
-    """Move robot safely"""
     if distance_meters > 5.0:
         return {"status": "error", "message": "Safety limit exceeded"}
     return {
@@ -44,7 +42,6 @@ def navigate(direction: str, distance_meters: float):
 
 @mcp.tool()
 def scan_hazard(hazard_type: str, severity: str):
-    """Hazard scan + log"""
     timestamp = datetime.now().isoformat()
     return {
         "status": "warning_logged",
@@ -54,21 +51,18 @@ def scan_hazard(hazard_type: str, severity: str):
 
 @mcp.tool()
 def analyze_human(clothing_color: str, estimated_action: str):
-    """Human detection description"""
     return {
         "status": "human_tracked",
         "details": f"Human wearing {clothing_color} is {estimated_action}",
     }
 
-
 # -----------------------------------------------------
-# Save and Upload Image
+# Save + Upload
 # -----------------------------------------------------
 def save_and_upload_image(image_b64: str, hf_token: str):
     try:
         image_bytes = base64.b64decode(image_b64)
         size_bytes = len(image_bytes)
-        print("[debug] decoded image bytes:", size_bytes)
 
         timestamp = datetime.now().strftime("%Y%m%d_%H%M%S_%f")
         local_path = f"/tmp/robot_img_{timestamp}.jpg"
@@ -76,8 +70,6 @@ def save_and_upload_image(image_b64: str, hf_token: str):
         with open(local_path, "wb") as f:
             f.write(image_bytes)
 
-        print("[debug] wrote local tmp file:", local_path)
-
         filename = f"robot_{timestamp}.jpg"
 
         upload_file(
@@ -88,8 +80,6 @@ def save_and_upload_image(image_b64: str, hf_token: str):
             repo_type="dataset",
         )
 
-        print("[debug] upload successful:", filename)
-
         url = f"https://huggingface.co/datasets/{HF_DATASET_REPO}/resolve/main/{filename}"
         return local_path, url, filename, size_bytes
 
@@ -97,9 +87,8 @@ def save_and_upload_image(image_b64: str, hf_token: str):
         traceback.print_exc()
         return None, None, None, 0
 
-
 # -----------------------------------------------------
-# JSON Parsing Helper
+# JSON Parse
 # -----------------------------------------------------
 def safe_parse_json_from_text(text: str):
     if not text:
@@ -120,20 +109,25 @@ def safe_parse_json_from_text(text: str):
 
     return None
 
-
 # -----------------------------------------------------
-# Only allow tools from MCP registry
+# FIXED: correct MCP tool registry access (v2)
 # -----------------------------------------------------
 def validate_and_call_tool(tool_name: str, tool_args: dict):
-    if tool_name not in mcp.tools:
+    # ❌ old: if tool_name not in mcp.tools:
+    # ✔ new:
+    if tool_name not in mcp._tools:
         return {"error": f"Unknown or unauthorized tool '{tool_name}'"}
+
     try:
-        return mcp.tools[tool_name](**tool_args)
+        # ❌ old: mcp.tools[name](...)
+        # ✔ new:
+        tool_fn = mcp._tools[tool_name]["function"]
+        return tool_fn(**tool_args)
+
     except Exception as e:
         traceback.print_exc()
         return {"error": f"Tool error: {str(e)}"}
 
-
 # -----------------------------------------------------
 # Main Pipeline
 # -----------------------------------------------------
@@ -145,9 +139,6 @@ def process_and_describe(payload):
         except:
             return {"error": "Invalid JSON payload"}
 
-    print("\n========== NEW REQUEST ==========")
-    print("[debug] Incoming payload:", payload)
-
     hf_token = payload.get("hf_token")
     if not hf_token:
         return {"error": "hf_token missing"}
@@ -165,14 +156,12 @@ def process_and_describe(payload):
     if not hf_url:
         return {"error": "Image upload failed"}
 
-    print("[debug] HF image URL:", hf_url)
-
-    # VLM SYSTEM PROMPT
+    # VLM system prompt
     system_prompt = """
-Respond in STRICT JSON ONLY. Format:
+Respond in STRICT JSON ONLY:
 {
  "description": "short visual description",
- "tool_name": "one of: speak, navigate, scan_hazard, analyze_human",
+ "tool_name": "speak | navigate | scan_hazard | analyze_human",
  "arguments": { ... }
 }
 """
@@ -191,8 +180,6 @@ Respond in STRICT JSON ONLY. Format:
         },
     ]
 
-    # VLM CALL
-    print("[debug] Calling VLM model...")
     client = InferenceClient(token=hf_token)
 
     response = client.chat.completions.create(
@@ -204,10 +191,6 @@ Respond in STRICT JSON ONLY. Format:
 
     vlm_output = response.choices[0].message.content.strip()
 
-    print("\n------ VLM RAW OUTPUT ------")
-    print(vlm_output)
-    print("------ END VLM RAW ------\n")
-
     parsed = safe_parse_json_from_text(vlm_output)
 
     if parsed is None:
@@ -236,7 +219,6 @@ Respond in STRICT JSON ONLY. Format:
         "vlm_raw": vlm_output,
     }
 
-
 # ------------------------------
 # Gradio Interface
 # ------------------------------
@@ -254,4 +236,3 @@ iface = gr.Interface(
 if __name__ == "__main__":
     print("[Gradio] Launching interface...")
     iface.launch(server_name="0.0.0.0", server_port=7860)
-