app.py

import os
import oss2
from pymongo import MongoClient
from pymongo.server_api import ServerApi
import bcrypt
from datetime import datetime
from flask import Flask, request, jsonify
from flask_cors import CORS
import json
import websocket
import uuid
import urllib.request
import urllib.parse
import requests
from bson.objectid import ObjectId
from dotenv import load_dotenv

# 加载 .env 文件中的环境变量
load_dotenv()

app = Flask(__name__)
CORS(app)

# ComfyUI 设置
SERVER_ADDRESS = "paint.aixiao.xyz"
CLIENT_ID = str(uuid.uuid4())

# 从环境变量中获取阿里云 OSS 配置信息
access_key_id = os.getenv("OSS_ACCESS_KEY_ID")
access_key_secret = os.getenv("OSS_ACCESS_KEY_SECRET")
bucket_name = os.getenv("OSS_BUCKET_NAME")
endpoint = os.getenv("OSS_ENDPOINT")

# MongoDB configuration
# 从环境变量中获取 MongoDB 配置信息
uri = os.getenv("MONGO_URI")
client = MongoClient(uri, server_api=ServerApi('1'))

# Create Aliyun OSS bucket object
bucket = oss2.Bucket(oss2.Auth(access_key_id, access_key_secret), endpoint, bucket_name)

try:
    client.admin.command('ping')
    print("Successfully connected to MongoDB!")
except Exception as e:
    print(f"Failed to connect to MongoDB: {e}")
    exit(1)

db = client['ai_image_generator']
images_collection = db['images']

# ComfyUI workflow (省略具体内容)
WORKFLOW = {
    "3": {
        "inputs": {
            "seed": 1048756903667323,
            "steps": 20,
            "cfg": 8,
            "sampler_name": "euler",
            "scheduler": "normal",
            "denoise": 1,
            "model": ["4", 0],
            "positive": ["6", 0],
            "negative": ["7", 0],
            "latent_image": ["5", 0]
        },
        "class_type": "KSampler"
    },
    "4": {
        "inputs": {
            "ckpt_name": "sd_xl_base_1.0.safetensors"
        },
        "class_type": "CheckpointLoaderSimple"
    },
    "5": {
        "inputs": {
            "width": 512,
            "height": 512,
            "batch_size": 1
        },
        "class_type": "EmptyLatentImage"
    },
    "6": {
        "inputs": {
            "text": "",
            "clip": ["4", 1]
        },
        "class_type": "CLIPTextEncode"
    },
    "7": {
        "inputs": {
            "text": "text, watermark",
            "clip": ["4", 1]
        },
        "class_type": "CLIPTextEncode"
    },
    "8": {
        "inputs": {
            "samples": ["3", 0],
            "vae": ["4", 2]
        },
        "class_type": "VAEDecode"
    },
    "9": {
        "inputs": {
            "filename_prefix": "ComfyUI",
            "images": ["8", 0]
        },
        "class_type": "SaveImage"
    }
}

def queue_prompt(prompt):
    p = {"prompt": prompt, "client_id": CLIENT_ID}
    data = json.dumps(p).encode('utf-8')
    req = urllib.request.Request(f"http://{SERVER_ADDRESS}/prompt", data=data)
    return json.loads(urllib.request.urlopen(req).read())

def get_image(filename, subfolder, folder_type):
    data = {"filename": filename, "subfolder": subfolder, "type": folder_type}
    url_values = urllib.parse.urlencode(data)
    with urllib.request.urlopen(f"http://{SERVER_ADDRESS}/view?{url_values}") as response:
        return response.read()

def get_history(prompt_id):
    with urllib.request.urlopen(f"http://{SERVER_ADDRESS}/history/{prompt_id}") as response:
        return json.loads(response.read())

def get_images(ws, prompt):
    prompt_id = queue_prompt(prompt)['prompt_id']
    print(f'Prompt ID: {prompt_id}')
    
    while True:
        out = ws.recv()
        if isinstance(out, str):
            message = json.loads(out)
            if message['type'] == 'executing':
                data = message['data']
                if data['node'] is None and data['prompt_id'] == prompt_id:
                    print('Execution completed')
                    break
        else:
            continue  # Ignore binary data (previews)

    history = get_history(prompt_id)[prompt_id]
    output_images = {}

    for node_id, node_output in history['outputs'].items():
        if 'images' in node_output:
            images_output = []
            for image in node_output['images']:
                image_data = get_image(image['filename'], image['subfolder'], image['type'])
                images_output.append(image_data)
            output_images[node_id] = images_output

    return output_images

def translate_to_english(text):
    url = os.getenv("DEEP_URI")
    payload = json.dumps({
        "text": text,
        "source_lang": "auto",
        "target_lang": "EN"
    })
    headers = {
        'Content-Type': 'application/json'
    }
    try:
        response = requests.post(url, headers=headers, data=payload)
        response.raise_for_status()
        result = response.json()
        return result.get('data', text)
    except requests.RequestException as e:
        print(f"翻译请求失败: {e}")
        return text

@app.route('/generate', methods=['POST'])
def generate_image():
    prompt = request.json['prompt']
    
    english_prompt = translate_to_english(prompt)
    print(f"Original prompt: {prompt}")
    print(f"Translated prompt: {english_prompt}")

    ws = websocket.create_connection(f"ws://{SERVER_ADDRESS}/ws?clientId={CLIENT_ID}")

    workflow = WORKFLOW.copy()
    workflow["6"]["inputs"]["text"] = english_prompt

    images = get_images(ws, workflow)
    ws.close()

    if images:
        image_data = list(images.values())[0][0]
        timestamp = datetime.now().strftime("%Y%m%d%H%M%S")
        filename = f"generated_image_{timestamp}.png"
        oss_path = f"images/{filename}"
        
        # Upload to Aliyun OSS
        bucket.put_object(oss_path, image_data)
        
        # Get the public URL
        image_url = f"https://{bucket_name}.{endpoint}/{oss_path}"
        
        # Save to MongoDB
        image_doc = {
            "prompt": prompt,
            "english_prompt": english_prompt,
            "url": image_url,
            "filename": filename,
            "created_at": datetime.utcnow(),
            "is_public": False
        }
        result = images_collection.insert_one(image_doc)
        
        return jsonify({
            "status": "success", 
            "filename": filename, 
            "url": image_url, 
            "id": str(result.inserted_id)
        })
    else:
        return jsonify({"status": "error", "message": "Failed to generate image"})

@app.route('/add-to-public-gallery', methods=['POST'])
def add_to_public_gallery():
    image_id = request.json['image_id']
    
    # Update the image document in MongoDB
    result = images_collection.update_one(
        {"_id": ObjectId(image_id)},
        {"$set": {"is_public": True}}
    )
    
    if result.modified_count > 0:
        return jsonify({"status": "success", "message": "Image added to public gallery"})
    else:
        return jsonify({"status": "error", "message": "Failed to add image to public gallery"})

@app.route('/api/gallery', methods=['GET'])
def get_gallery_images():
    # Temporarily return all images, regardless of is_public status
    all_images = list(images_collection.find().sort("created_at", -1).limit(20))
    
    # Convert ObjectId to string for JSON serialization
    for image in all_images:
        image['_id'] = str(image['_id'])
    
    print(f"Returning {len(all_images)} images")  # Add this line for debugging
    return jsonify(all_images)

if __name__ == '__main__':
    app.run(host='0.0.0.0', port=7860, debug=True)