Update app.py

app.py

@@ -1,4 +1,3 @@
-# File: main/app.py
 # Purpose: One Space that offers four tools/tabs (all exposed as MCP tools):
 #   1) Fetch — extract relevant page content (title, metadata, clean text, hyperlinks)
 #   2) DuckDuckGo Search — compact JSONL search output (short keys to minimize tokens)
@@ -344,13 +343,8 @@ def Fetch_Webpage(  # <-- MCP tool #1 (Fetch)
     return md or "No content could be extracted."
 
 
-# ===============================
-# DuckDuckGo Search (JSONL lines)
-# ===============================
-
-
 # ============================================
-# Concise DDG: ultra-succinct JSONL for tokens
+# DuckDuckGo Search: ultra-succinct JSONL
 # ============================================
 
 def Search_DuckDuckGo(  # <-- MCP tool #2 (DDG Search)
@@ -416,7 +410,7 @@ def Search_DuckDuckGo(  # <-- MCP tool #2 (DDG Search)
 
 
 # ======================================
-# Code Execution: Python (MCP tool #6)
+# Code Execution: Python (MCP tool #3)
 # ======================================
 
 def Execute_Python(code: Annotated[str, "Python source code to run; stdout is captured and returned."]) -> str:
@@ -605,7 +599,7 @@ concise_interface = gr.Interface(
     submit_btn="Search",
 )
 
-## Removed Structured, Raw, and Sitemap tabs
+##
 
 # --- Execute Python tab (simple code interpreter) ---
 code_interface = gr.Interface(
@@ -657,7 +651,7 @@ kokoro_interface = gr.Interface(
     outputs=gr.Audio(label="Audio", type="numpy"),
     title="Kokoro TTS",
     description=(
-        "<div style=\"text-align:center\">Generate English speech with Kokoro-82M. 30 Second max output. Runs on CPU.</div>"
+        "<div style=\"text-align:center\">Generate English speech with Kokoro-82M. 30 second max output. Runs on CPU or CUDA if available.</div>"
     ),
     api_description=(
         "Synthesize speech from text using Kokoro-82M. Returns (sample_rate, waveform) suitable for playback."