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DigiPal - Advanced AI Monster Companion with 3D Generation
Unified application with all features enabled by default
"""
import asyncio
import json
import logging
import os
import sys
from pathlib import Path
from typing import Dict, Any, Optional, List
from datetime import datetime
import uvicorn
from fastapi import FastAPI, WebSocket, WebSocketDisconnect, HTTPException
from fastapi.middleware.cors import CORSMiddleware
from fastapi.responses import JSONResponse
from pydantic import BaseModel
import gradio as gr
import torch
import spaces
# Add src to path
sys.path.insert(0, os.path.join(os.path.dirname(__file__), 'src'))
# Configure logging
logging.basicConfig(
level=logging.INFO,
format='%(asctime)s - %(name)s - %(levelname)s - %(message)s'
)
logger = logging.getLogger(__name__)
# Environment configuration - All features enabled by default
ENV_CONFIG = {
"LOG_LEVEL": os.getenv("LOG_LEVEL", "INFO"),
"SERVER_NAME": os.getenv("SERVER_NAME", "0.0.0.0"),
"SERVER_PORT": int(os.getenv("SERVER_PORT", "7860")),
"API_PORT": int(os.getenv("API_PORT", "7861")),
"SHARE": os.getenv("SHARE", "false").lower() == "true",
"DEBUG": os.getenv("DEBUG", "false").lower() == "true",
"MAX_THREADS": int(os.getenv("MAX_THREADS", "40")),
"MCP_ENDPOINT": os.getenv("MCP_ENDPOINT", ""),
"MCP_API_KEY": os.getenv("MCP_API_KEY", "")
}
# HuggingFace Spaces detection
IS_SPACES = os.getenv("SPACE_ID") is not None
# API Models
class CreateMonsterRequest(BaseModel):
name: str
personality: str
class MonsterActionRequest(BaseModel):
action: str
params: Dict[str, Any] = {}
class MonsterTalkRequest(BaseModel):
message: str
class Generate3DRequest(BaseModel):
description: Optional[str] = None
# Import core modules after environment setup
try:
from src.core.monster_engine_dw1 import Monster, PersonalityType
from src.core.evolution_system import EvolutionSystem
from src.ai.qwen_processor import QwenProcessor
from src.ai.speech_engine import SpeechEngine
from src.ui.state_manager import StateManager
from src.deployment.zero_gpu_optimizer import get_optimal_device
from src.pipelines.text_to_3d_pipeline import Text3DPipeline
from src.pipelines.hunyuan3d_pipeline import Hunyuan3DClient
from src.pipelines.opensource_3d_pipeline_v2 import (
OpenSourcePipelineV2,
PipelineConfig,
ModelProvider
)
# UI imports
from src.ui.gradio_interface_v2 import create_interface
except ImportError as e:
logger.error(f"Failed to import required modules: {e}")
sys.exit(1)
# Initialize FastAPI app
app = FastAPI(title="DigiPal API", version="1.0.0")
# Add CORS middleware for frontend communication
app.add_middleware(
CORSMiddleware,
allow_origins=["*"], # In production, replace with specific origins
allow_credentials=True,
allow_methods=["*"],
allow_headers=["*"],
)
# Global state management
class AppState:
def __init__(self):
self.monsters: Dict[str, Monster] = {}
self.state_manager = StateManager()
self.qwen_processor = None
self.speech_engine = None
self.evolution_system = EvolutionSystem()
self.text3d_pipeline = None
self.active_connections: Dict[str, WebSocket] = {}
self.initialized = False
async def initialize(self):
"""Initialize AI components and pipelines"""
if self.initialized:
return
logger.info("Initializing AI components...")
# Initialize AI processors
try:
self.qwen_processor = QwenProcessor()
self.speech_engine = SpeechEngine()
# Initialize 3D pipeline with MCP if available
if ENV_CONFIG["MCP_ENDPOINT"]:
logger.info("Using MCP for 3D generation")
pipeline_config = PipelineConfig(
model_provider=ModelProvider.MCP,
mcp_endpoint=ENV_CONFIG["MCP_ENDPOINT"],
mcp_api_key=ENV_CONFIG["MCP_API_KEY"]
)
else:
logger.info("Using local models for 3D generation")
pipeline_config = PipelineConfig(
model_provider=ModelProvider.HUGGINGFACE
)
self.text3d_pipeline = Text3DPipeline(
pipeline_type="opensource_v2",
config=pipeline_config
)
self.initialized = True
logger.info("All components initialized successfully")
except Exception as e:
logger.error(f"Failed to initialize components: {e}")
raise
# Create global app state
app_state = AppState()
# WebSocket connection manager
class ConnectionManager:
def __init__(self):
self.active_connections: Dict[str, WebSocket] = {}
async def connect(self, websocket: WebSocket, monster_id: str):
await websocket.accept()
self.active_connections[monster_id] = websocket
def disconnect(self, monster_id: str):
if monster_id in self.active_connections:
del self.active_connections[monster_id]
async def send_update(self, monster_id: str, data: dict):
if monster_id in self.active_connections:
try:
await self.active_connections[monster_id].send_json(data)
except:
self.disconnect(monster_id)
manager = ConnectionManager()
# API Endpoints
@app.on_event("startup")
async def startup_event():
"""Initialize app state on startup"""
await app_state.initialize()
@app.get("/health")
async def health_check():
"""Health check endpoint"""
return {"status": "healthy", "initialized": app_state.initialized}
@app.get("/api/monsters")
async def list_monsters():
"""List all available saved monsters"""
try:
saved_monsters = await app_state.state_manager.list_saved_monsters()
return {"monsters": saved_monsters}
except Exception as e:
logger.error(f"Error listing monsters: {e}")
raise HTTPException(status_code=500, detail=str(e))
@app.post("/api/monsters")
async def create_monster(request: CreateMonsterRequest):
"""Create a new monster"""
try:
# Create new monster
personality = PersonalityType[request.personality.upper()]
monster = Monster(name=request.name, personality=personality)
# Save to state
app_state.monsters[monster.id] = monster
# Save to database
await app_state.state_manager.save_monster(monster)
return {
"id": monster.id,
"name": monster.name,
"personality": monster.personality.value,
"stage": monster.stage.value,
"stats": monster.get_stats()
}
except Exception as e:
logger.error(f"Error creating monster: {e}")
raise HTTPException(status_code=500, detail=str(e))
@app.get("/api/monsters/{monster_id}")
async def get_monster(monster_id: str):
"""Load a specific monster's full state"""
try:
# Check if already loaded
if monster_id in app_state.monsters:
monster = app_state.monsters[monster_id]
else:
# Load from database
monster = await app_state.state_manager.load_monster_by_id(monster_id)
if not monster:
raise HTTPException(status_code=404, detail="Monster not found")
app_state.monsters[monster_id] = monster
return {
"id": monster.id,
"name": monster.name,
"personality": monster.personality.value,
"stage": monster.stage.value,
"stats": monster.get_stats(),
"model_url": monster.model_url,
"conversation_history": monster.conversation_history[-10:] # Last 10 messages
}
except HTTPException:
raise
except Exception as e:
logger.error(f"Error loading monster: {e}")
raise HTTPException(status_code=500, detail=str(e))
@app.post("/api/monsters/{monster_id}/action")
async def perform_action(monster_id: str, request: MonsterActionRequest):
"""Perform a care action on the monster"""
try:
if monster_id not in app_state.monsters:
raise HTTPException(status_code=404, detail="Monster not found")
monster = app_state.monsters[monster_id]
result = {}
# Handle different actions
if request.action == "feed":
food_type = request.params.get("food_type", "balanced")
result = monster.feed(food_type)
elif request.action == "train":
training_type = request.params.get("training_type", "strength")
result = monster.train(training_type)
elif request.action == "play":
result = monster.play()
elif request.action == "clean":
result = monster.clean()
elif request.action == "heal":
result = monster.heal()
elif request.action == "discipline":
result = monster.discipline()
elif request.action == "rest":
result = monster.rest()
else:
raise HTTPException(status_code=400, detail=f"Unknown action: {request.action}")
# Save state
await app_state.state_manager.save_monster(monster)
# Send real-time update
await manager.send_update(monster_id, {
"type": "stats_update",
"stats": monster.get_stats(),
"stage": monster.stage.value
})
return {
"success": True,
"result": result,
"stats": monster.get_stats()
}
except HTTPException:
raise
except Exception as e:
logger.error(f"Error performing action: {e}")
raise HTTPException(status_code=500, detail=str(e))
@app.post("/api/monsters/{monster_id}/talk")
async def talk_to_monster(monster_id: str, request: MonsterTalkRequest):
"""Send a text message to the monster"""
try:
if monster_id not in app_state.monsters:
raise HTTPException(status_code=404, detail="Monster not found")
monster = app_state.monsters[monster_id]
# Use MCP if available, otherwise use local processor
if ENV_CONFIG["MCP_ENDPOINT"] and hasattr(app_state.qwen_processor, 'use_mcp'):
response = await app_state.qwen_processor.generate_response_mcp(
monster, request.message
)
else:
response = app_state.qwen_processor.generate_response(
monster, request.message
)
# Update conversation history
monster.conversation_history.append({
"role": "user",
"content": request.message,
"timestamp": datetime.now().isoformat()
})
monster.conversation_history.append({
"role": "assistant",
"content": response,
"timestamp": datetime.now().isoformat()
})
# Save state
await app_state.state_manager.save_monster(monster)
return {
"response": response,
"stats": monster.get_stats()
}
except HTTPException:
raise
except Exception as e:
logger.error(f"Error talking to monster: {e}")
raise HTTPException(status_code=500, detail=str(e))
@app.post("/api/monsters/{monster_id}/generate-3d")
async def generate_3d_model(monster_id: str, request: Generate3DRequest):
"""Trigger 3D model generation for the monster"""
try:
if monster_id not in app_state.monsters:
raise HTTPException(status_code=404, detail="Monster not found")
monster = app_state.monsters[monster_id]
# Generate description if not provided
if not request.description:
description = f"A {monster.personality.value} {monster.stage.value} digital monster"
else:
description = request.description
# Generate 3D model
logger.info(f"Generating 3D model for {monster.name}: {description}")
model_path = await app_state.text3d_pipeline.generate(
description,
output_dir=f"data/models/{monster_id}"
)
# Update monster with model URL
monster.model_url = f"/models/{monster_id}/{Path(model_path).name}"
await app_state.state_manager.save_monster(monster)
# Send update via WebSocket
await manager.send_update(monster_id, {
"type": "model_update",
"model_url": monster.model_url
})
return {
"success": True,
"model_url": monster.model_url
}
except HTTPException:
raise
except Exception as e:
logger.error(f"Error generating 3D model: {e}")
raise HTTPException(status_code=500, detail=str(e))
@app.websocket("/api/monsters/{monster_id}/ws")
async def websocket_endpoint(websocket: WebSocket, monster_id: str):
"""WebSocket endpoint for real-time updates"""
await manager.connect(websocket, monster_id)
try:
# Send initial stats
if monster_id in app_state.monsters:
monster = app_state.monsters[monster_id]
await websocket.send_json({
"type": "initial_state",
"stats": monster.get_stats(),
"stage": monster.stage.value,
"model_url": monster.model_url
})
# Keep connection alive and handle stat degradation
while True:
await asyncio.sleep(30) # Update every 30 seconds
if monster_id in app_state.monsters:
monster = app_state.monsters[monster_id]
monster.update_time_based_stats()
await websocket.send_json({
"type": "stats_update",
"stats": monster.get_stats(),
"stage": monster.stage.value
})
except WebSocketDisconnect:
manager.disconnect(monster_id)
# Gradio interface for fallback/admin
def create_gradio_interface():
"""Create Gradio interface as admin panel"""
interface = create_interface()
return interface
# Main entry point
if __name__ == "__main__":
# Create necessary directories
os.makedirs("data/saves", exist_ok=True)
os.makedirs("data/models", exist_ok=True)
os.makedirs("data/cache", exist_ok=True)
os.makedirs("logs", exist_ok=True)
# Log startup info
logger.info("=" * 60)
logger.info("DigiPal - Advanced AI Monster Companion")
logger.info("=" * 60)
logger.info(f"Environment: {'HuggingFace Spaces' if IS_SPACES else 'Local'}")
logger.info(f"API Port: {ENV_CONFIG['API_PORT']}")
logger.info(f"Gradio Port: {ENV_CONFIG['SERVER_PORT']}")
logger.info(f"MCP Enabled: {bool(ENV_CONFIG['MCP_ENDPOINT'])}")
logger.info("=" * 60)
# Run both FastAPI and Gradio
async def run_servers():
# Start FastAPI server
config = uvicorn.Config(
app,
host=ENV_CONFIG["SERVER_NAME"],
port=ENV_CONFIG["API_PORT"],
log_level=ENV_CONFIG["LOG_LEVEL"].lower()
)
server = uvicorn.Server(config)
# Create Gradio interface
gr_interface = create_gradio_interface()
# Run both servers concurrently
await asyncio.gather(
server.serve(),
gr_interface.launch(
server_name=ENV_CONFIG["SERVER_NAME"],
server_port=ENV_CONFIG["SERVER_PORT"],
share=ENV_CONFIG["SHARE"],
max_threads=ENV_CONFIG["MAX_THREADS"],
show_error=True
)
)
# Run the servers
asyncio.run(run_servers()) |