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src/app.py

@@ -28,80 +28,95 @@ def create_app():
     
     print("🚀 Starting Gradio + FastMCP server")
     
-    # Create FastMCP server with new tools
-    mcp = FastMCP("Podcast MCP")
+    # Check if this is HF Spaces environment
+    is_hf_spaces = "SPACE_ID" in os.environ
     
-    # Register tools using the new service architecture
-    @mcp.tool(description="Transcribe audio files to text using Whisper model with speaker diarization support")
-    async def transcribe_audio_file_tool(
-        audio_file_path: str,
-        model_size: str = "turbo",
-        language: str = None,
-        output_format: str = "srt",
-        enable_speaker_diarization: bool = False
-    ):
-        return await mcp_tools.transcribe_audio_file(
-            audio_file_path, model_size, language, output_format, enable_speaker_diarization
-        )
-    
-    @mcp.tool(description="Download Apple Podcast audio files")
-    async def download_apple_podcast_tool(url: str):
-        return await mcp_tools.download_apple_podcast(url)
-    
-    @mcp.tool(description="Download XiaoYuZhou podcast audio files")
-    async def download_xyz_podcast_tool(url: str):
-        return await mcp_tools.download_xyz_podcast(url)
-    
-    @mcp.tool(description="Scan directory for MP3 audio files")
-    async def get_mp3_files_tool(directory: str):
-        return await mcp_tools.get_mp3_files(directory)
-    
-    @mcp.tool(description="Get basic file information")
-    async def get_file_info_tool(file_path: str):
-        return await mcp_tools.get_file_info(file_path)
-    
-    @mcp.tool(description="Read text file content in segments")
-    async def read_text_file_segments_tool(
-        file_path: str,
-        chunk_size: int = 65536,
-        start_position: int = 0
-    ):
-        return await mcp_tools.read_text_file_segments(file_path, chunk_size, start_position)
-    
-    # Create FastAPI wrapper
-    fastapi_wrapper = FastAPI(
-        title="Modal AudioTranscriber MCP",
-        description="Gradio UI + FastMCP Tool + Modal Integration AudioTranscriber MCP",
-        version="1.0.0",
-        lifespan=lambda app: mcp.session_manager.run()
-    )
-    
-    # Get FastMCP's streamable HTTP app
-    mcp_app = mcp.streamable_http_app()
-    
-    # Mount FastMCP application to /api path  
-    fastapi_wrapper.mount("/api", mcp_app)
-    
-    # Create Gradio interface
-    ui_app = create_gradio_interface()
-    
-    # Use Gradio's standard mounting approach
-    final_app = mount_gradio_app(
-        app=fastapi_wrapper,
-        blocks=ui_app,
-        path="/",
-        app_kwargs={
-            "docs_url": "/docs",
-            "redoc_url": "/redoc",
-        }
-    )
-    
-    print("✅ Server startup completed")
-    print("🎨 Gradio UI: /")
-    print("🔧 MCP Streamable HTTP: /api/mcp")
-    print(f"📝 Server name: {mcp.name}")
+    if is_hf_spaces:
+        # For HF Spaces: return pure Gradio app (simpler approach)
+        print("🤗 Creating HF Spaces compatible app")
+        ui_app = create_gradio_interface()
+        
+        print("✅ Server startup completed")
+        print("🎨 Gradio UI: /")
+        
+        return ui_app
     
-    return final_app
+    else:
+        # For other environments: full FastAPI + MCP + Gradio setup
+        # Create FastMCP server with new tools
+        mcp = FastMCP("Podcast MCP")
+        
+        # Register tools using the new service architecture
+        @mcp.tool(description="Transcribe audio files to text using Whisper model with speaker diarization support")
+        async def transcribe_audio_file_tool(
+            audio_file_path: str,
+            model_size: str = "turbo",
+            language: str = None,
+            output_format: str = "srt",
+            enable_speaker_diarization: bool = False
+        ):
+            return await mcp_tools.transcribe_audio_file(
+                audio_file_path, model_size, language, output_format, enable_speaker_diarization
+            )
+        
+        @mcp.tool(description="Download Apple Podcast audio files")
+        async def download_apple_podcast_tool(url: str):
+            return await mcp_tools.download_apple_podcast(url)
+        
+        @mcp.tool(description="Download XiaoYuZhou podcast audio files")
+        async def download_xyz_podcast_tool(url: str):
+            return await mcp_tools.download_xyz_podcast(url)
+        
+        @mcp.tool(description="Scan directory for MP3 audio files")
+        async def get_mp3_files_tool(directory: str):
+            return await mcp_tools.get_mp3_files(directory)
+        
+        @mcp.tool(description="Get basic file information")
+        async def get_file_info_tool(file_path: str):
+            return await mcp_tools.get_file_info(file_path)
+        
+        @mcp.tool(description="Read text file content in segments")
+        async def read_text_file_segments_tool(
+            file_path: str,
+            chunk_size: int = 65536,
+            start_position: int = 0
+        ):
+            return await mcp_tools.read_text_file_segments(file_path, chunk_size, start_position)
+        
+        # Create FastAPI wrapper
+        fastapi_wrapper = FastAPI(
+            title="Modal AudioTranscriber MCP",
+            description="Gradio UI + FastMCP Tool + Modal Integration AudioTranscriber MCP",
+            version="1.0.0",
+            lifespan=lambda app: mcp.session_manager.run()
+        )
+        
+        # Get FastMCP's streamable HTTP app
+        mcp_app = mcp.streamable_http_app()
+        
+        # Mount FastMCP application to /api path  
+        fastapi_wrapper.mount("/api", mcp_app)
+        
+        # Create Gradio interface
+        ui_app = create_gradio_interface()
+        
+        # Use Gradio's standard mounting approach
+        final_app = mount_gradio_app(
+            app=fastapi_wrapper,
+            blocks=ui_app,
+            path="/",
+            app_kwargs={
+                "docs_url": "/docs",
+                "redoc_url": "/redoc",
+            }
+        )
+        
+        print("✅ Server startup completed")
+        print("🎨 Gradio UI: /")
+        print("🔧 MCP Streamable HTTP: /api/mcp")
+        print(f"📝 Server name: {mcp.name}")
+        
+        return final_app
 
 # ==================== Modal Deployment Configuration ====================
 
@@ -143,10 +158,15 @@ def main():
 
 def run_local():
     """Run local server with uvicorn (for direct execution)"""
+    # Double-check: don't run uvicorn in HF Spaces
+    if os.environ.get("HF_SPACES_MODE"):
+        print("⚠️ Skipping uvicorn.run() in HF Spaces mode")
+        return
+        
     app = main()
     if app:
         # Use port 7860 for HF Spaces compatibility, 8000 for local
-        port = int(os.environ.get("PORT", 7860))  # HF Spaces uses port 7860
+        port = int(os.environ.get("PORT", 8000))  # Use 8000 for local dev
         uvicorn.run(
             app,
             host="0.0.0.0",
@@ -163,8 +183,16 @@ def get_app():
         os.environ["DEPLOYMENT_MODE"] = "local"
     return main()
 
-# Create app for HF Spaces when imported
-app = get_app()  # Always create app for HF Spaces
+# HF Spaces compatibility: only create app when not in main execution
+if __name__ != "__main__":
+    # Check if we're in HF Spaces mode and app is already created
+    if not os.environ.get("HF_SPACES_MODE"):
+        # This will be called when imported by other environments (not HF Spaces)
+        app = get_app()
 
 if __name__ == "__main__":
-    run_local()
+    # Check if we should run uvicorn (not in HF Spaces)
+    if not os.environ.get("HF_SPACES_MODE"):
+        run_local()
+    else:
+        print("⚠️ Skipping uvicorn in HF Spaces mode")