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# FastAPI + Gradio + FastMCP MCP server main entry point
import modal
from contextlib import asynccontextmanager
from fastapi import FastAPI
from gradio.routes import mount_gradio_app
import os
from dotenv import load_dotenv
import uvicorn
from mcp.server.fastmcp import FastMCP
# Import modules
from .tools import mcp_tools # Import the module, not get_mcp_server function
from .ui.gradio_ui import create_gradio_interface
from .config.config import is_modal_mode, is_local_mode
# Always import modal config since this module might be imported in modal context
try:
from .config.modal_config import app, image, volume, cache_dir, secrets
_modal_available = True
except ImportError:
_modal_available = False
# ==================== Application Creation Function ====================
def create_app():
"""Create and return complete Gradio + MCP application"""
print("🚀 Starting Gradio + FastMCP server")
# 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 ====================
# Create a separate Modal app for the Gradio interface
if _modal_available:
gradio_mcp_app = modal.App(name="gradio-mcp-ui")
@gradio_mcp_app.function(
image=image,
cpu=2, # Adequate CPU for UI operations
memory=4096, # 4GB memory for stable UI performance
max_containers=5, # Reduced to control resource usage
min_containers=1, # Keep minimum containers for faster response
scaledown_window=600, # 20 minutes before scaling down
timeout=1800, # 30 minutes timeout to prevent preemption
volumes={cache_dir: volume},
secrets=secrets,
)
@modal.concurrent(max_inputs=100)
@modal.asgi_app()
def app_entry():
"""Modal deployment function - create and return complete Gradio + MCP application"""
return create_app()
# ==================== Main Entry Point ====================
def main():
"""Main entry point for all deployment modes"""
if is_modal_mode():
print("☁️ Modal mode: Use 'modal deploy src.app::gradio_mcp_app'")
return None
else:
print("🏠 Starting in local mode")
print("💡 GPU functions will be routed to Modal endpoints")
app = create_app()
return app
def run_local():
"""Run local server with uvicorn (for direct execution)"""
app = main()
if app:
uvicorn.run(
app,
host="0.0.0.0",
port=8000,
reload=False
)
# ==================== Hugging Face Spaces Support ====================
# For Hugging Face Spaces, directly create the app
def get_app():
"""Get app instance for HF Spaces"""
if "DEPLOYMENT_MODE" not in os.environ:
os.environ["DEPLOYMENT_MODE"] = "local"
return main()
# Create app for HF Spaces when imported
if __name__ != "__main__":
app = get_app()
if __name__ == "__main__":
run_local() |