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main.py
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main.py
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# 导入所需的库
from flask import Flask, request, jsonify, Response, send_from_directory
from flask_cors import CORS, cross_origin
import requests
import uuid
import json
import time
import os
from datetime import datetime
from PIL import Image
import io
import re
import threading
from queue import Queue, Empty
import logging
from logging.handlers import TimedRotatingFileHandler
import uuid
import hashlib
import requests
import json
import hashlib
from PIL import Image
from io import BytesIO
from urllib.parse import urlparse, urlunparse
import base64
from fake_useragent import UserAgent
import os
from urllib.parse import urlparse
# 读取配置文件
def load_config(file_path):
with open(file_path, 'r', encoding='utf-8') as file:
return json.load(file)
CONFIG = load_config('./data/config.json')
LOG_LEVEL = CONFIG.get('log_level', 'INFO').upper()
NEED_LOG_TO_FILE = CONFIG.get('need_log_to_file', 'true').lower() == 'true'
# 使用 get 方法获取配置项，同时提供默认值
BASE_URL = CONFIG.get('upstream_base_url', '')
PROXY_API_PREFIX = CONFIG.get('upstream_api_prefix', '')
if PROXY_API_PREFIX != '':
PROXY_API_PREFIX = "/" + PROXY_API_PREFIX
UPLOAD_BASE_URL = CONFIG.get('backend_container_url', '')
KEY_FOR_GPTS_INFO = CONFIG.get('key_for_gpts_info', '')
API_PREFIX = CONFIG.get('backend_container_api_prefix', '')
GPT_4_S_New_Names = CONFIG.get('gpt_4_s_new_name', 'gpt-4-s').split(',')
GPT_4_MOBILE_NEW_NAMES = CONFIG.get('gpt_4_mobile_new_name', 'gpt-4-mobile').split(',')
GPT_3_5_NEW_NAMES = CONFIG.get('gpt_3_5_new_name', 'gpt-3.5-turbo').split(',')
BOT_MODE = CONFIG.get('bot_mode', {})
BOT_MODE_ENABLED = BOT_MODE.get('enabled', 'false').lower() == 'true'
BOT_MODE_ENABLED_MARKDOWN_IMAGE_OUTPUT = BOT_MODE.get('enabled_markdown_image_output', 'false').lower() == 'true'
BOT_MODE_ENABLED_BING_REFERENCE_OUTPUT = BOT_MODE.get('enabled_bing_reference_output', 'false').lower() == 'true'
BOT_MODE_ENABLED_CODE_BLOCK_OUTPUT = BOT_MODE.get('enabled_plugin_output', 'false').lower() == 'true'
BOT_MODE_ENABLED_PLAIN_IMAGE_URL_OUTPUT = BOT_MODE.get('enabled_plain_image_url_output', 'false').lower() == 'true'
NEED_DELETE_CONVERSATION_AFTER_RESPONSE = CONFIG.get('need_delete_conversation_after_response', 'true').lower() == 'true'
USE_OAIUSERCONTENT_URL = CONFIG.get('use_oaiusercontent_url', 'false').lower() == 'true'
# USE_PANDORA_FILE_SERVER = CONFIG.get('use_pandora_file_server', 'false').lower() == 'true'
CUSTOM_ARKOSE = CONFIG.get('custom_arkose_url', 'false').lower() == 'true'
ARKOSE_URLS = CONFIG.get('arkose_urls', "")
DALLE_PROMPT_PREFIX = CONFIG.get('dalle_prompt_prefix', '')
# redis配置读取
REDIS_CONFIG = CONFIG.get('redis', {})
REDIS_CONFIG_HOST = REDIS_CONFIG.get('host', 'redis')
REDIS_CONFIG_PORT = REDIS_CONFIG.get('port', 6379)
REDIS_CONFIG_PASSWORD = REDIS_CONFIG.get('password', '')
REDIS_CONFIG_DB = REDIS_CONFIG.get('db', 0)
REDIS_CONFIG_POOL_SIZE = REDIS_CONFIG.get('pool_size', 10)
REDIS_CONFIG_POOL_TIMEOUT = REDIS_CONFIG.get('pool_timeout', 30)
# 设置日志级别
log_level_dict = {
'DEBUG': logging.DEBUG,
'INFO': logging.INFO,
'WARNING': logging.WARNING,
'ERROR': logging.ERROR,
'CRITICAL': logging.CRITICAL
}
log_formatter = logging.Formatter('%(asctime)s [%(levelname)s] - %(message)s')
logger = logging.getLogger()
logger.setLevel(log_level_dict.get(LOG_LEVEL, logging.DEBUG))
import redis
# 假设您已经有一个Redis客户端的实例
redis_client = redis.StrictRedis(host=REDIS_CONFIG_HOST,
port=REDIS_CONFIG_PORT,
password=REDIS_CONFIG_PASSWORD,
db=REDIS_CONFIG_DB,
retry_on_timeout=True
)
# 如果环境变量指示需要输出到文件
if NEED_LOG_TO_FILE:
log_filename = './log/access.log'
file_handler = TimedRotatingFileHandler(log_filename, when="midnight", interval=1, backupCount=30)
file_handler.setFormatter(log_formatter)
logger.addHandler(file_handler)
# 添加标准输出流处理器（控制台输出）
stream_handler = logging.StreamHandler()
stream_handler.setFormatter(log_formatter)
logger.addHandler(stream_handler)
# 创建FakeUserAgent对象
ua = UserAgent()
def generate_unique_id(prefix):
# 生成一个随机的 UUID
random_uuid = uuid.uuid4()
# 将 UUID 转换为字符串，并移除其中的短横线
random_uuid_str = str(random_uuid).replace('-', '')
# 结合前缀和处理过的 UUID 生成最终的唯一 ID
unique_id = f"{prefix}-{random_uuid_str}"
return unique_id
def get_accessible_model_list():
return [config['name'] for config in gpts_configurations]
def find_model_config(model_name):
for config in gpts_configurations:
if config['name'] == model_name:
return config
return None
# 从 gpts.json 读取配置
def load_gpts_config(file_path):
with open(file_path, 'r', encoding='utf-8') as file:
return json.load(file)
# 根据 ID 发送请求并获取配置信息
def fetch_gizmo_info(base_url, proxy_api_prefix, model_id):
url = f"{base_url}{proxy_api_prefix}/backend-api/gizmos/{model_id}"
headers = {
"Authorization": f"Bearer {KEY_FOR_GPTS_INFO}"
}
response = requests.get(url, headers=headers)
# logger.debug(f"fetch_gizmo_info_response: {response.text}")
if response.status_code == 200:
return response.json()
else:
return None
# gpts_configurations = []
# 将配置添加到全局列表
def add_config_to_global_list(base_url, proxy_api_prefix, gpts_data):
global gpts_configurations
# print(f"gpts_data: {gpts_data}")
for model_name, model_info in gpts_data.items():
# print(f"model_name: {model_name}")
# print(f"model_info: {model_info}")
model_id = model_info['id']
# 首先尝试从 Redis 获取缓存数据
cached_gizmo_info = redis_client.get(model_id)
if cached_gizmo_info:
gizmo_info = eval(cached_gizmo_info) # 将字符串转换回字典
logger.info(f"Using cached info for {model_name}, {model_id}")
else:
logger.info(f"Fetching gpts info for {model_name}, {model_id}")
gizmo_info = fetch_gizmo_info(base_url, proxy_api_prefix, model_id)
# 如果成功获取到数据，则将其存入 Redis
if gizmo_info:
redis_client.set(model_id, str(gizmo_info))
logger.info(f"Cached gizmo info for {model_name}, {model_id}")
if gizmo_info:
gpts_configurations.append({
'name': model_name,
'id': model_id,
'config': gizmo_info
})
def generate_gpts_payload(model, messages):
model_config = find_model_config(model)
if model_config:
gizmo_info = model_config['config']
gizmo_id = gizmo_info['gizmo']['id']
payload = {
"action": "next",
"messages": messages,
"parent_message_id": str(uuid.uuid4()),
"model": "gpt-4-gizmo",
"timezone_offset_min": -480,
"history_and_training_disabled": False,
"conversation_mode": {
"gizmo": gizmo_info,
"kind": "gizmo_interaction",
"gizmo_id": gizmo_id
},
"force_paragen": False,
"force_rate_limit": False
}
return payload
else:
return None
# 创建 Flask 应用
app = Flask(__name__)
CORS(app, resources={r"/images/*": {"origins": "*"}})
# PANDORA_UPLOAD_URL = 'files.pandoranext.com'
VERSION = '0.7.7'
# VERSION = 'test'
UPDATE_INFO = '增加Arkose请求头'
# UPDATE_INFO = '【仅供临时测试使用】 '
# 解析响应中的信息
def parse_oai_ip_info():
tmp_ua = ua.random
res = requests.get("https://auth0.openai.com/cdn-cgi/trace", headers={"User-Agent":tmp_ua}, proxies=proxies)
lines = res.text.strip().split("\n")
info_dict = {line.split('=')[0]: line.split('=')[1] for line in lines if '=' in line}
return {key: info_dict[key] for key in ["ip", "loc", "colo", "warp"] if key in info_dict}
with app.app_context():
global gpts_configurations # 移到作用域的最开始
global proxies
global proxy_type
global proxy_host
global proxy_port
# 获取环境变量
proxy_url = CONFIG.get('proxy', None)
logger.info(f"==========================================")
if proxy_url and proxy_url != '':
parsed_url = urlparse(proxy_url)
scheme = parsed_url.scheme
hostname = parsed_url.hostname
port = parsed_url.port
# 构建requests支持的代理格式
if scheme in ['http']:
proxy_address = f"{scheme}://{hostname}:{port}"
proxies = {
'http': proxy_address,
'https': proxy_address,
}
proxy_type = scheme
proxy_host = hostname
proxy_port = port
elif scheme in ['socks5']:
proxy_address = f"{scheme}://{hostname}:{port}"
proxies = {
'http': proxy_address,
'https': proxy_address,
}
proxy_type = scheme
proxy_host = hostname
proxy_port = port
else:
raise ValueError("Unsupport proxy scheme: " + scheme)
# 打印当前使用的代理设置
logger.info(f"Use Proxy: {scheme}://{proxy_host}:{proxy_port}")
else:
# 如果没有设置代理
proxies = {}
proxy_type = None
http_proxy_host = None
http_proxy_port = None
logger.info("No Proxy")
ip_info = parse_oai_ip_info()
logger.info(f"The ip you are using to access oai is: {ip_info['ip']}")
logger.info(f"The location of this ip is: {ip_info['loc']}")
logger.info(f"The colo is: {ip_info['colo']}")
logger.info(f"Is this ip a Warp ip: {ip_info['warp']}")
# 输出版本信息
logger.info(f"==========================================")
logger.info(f"Version: {VERSION}")
logger.info(f"Update Info: {UPDATE_INFO}")
logger.info(f"LOG_LEVEL: {LOG_LEVEL}")
logger.info(f"NEED_LOG_TO_FILE: {NEED_LOG_TO_FILE}")
logger.info(f"BOT_MODE_ENABLED: {BOT_MODE_ENABLED}")
if BOT_MODE_ENABLED:
logger.info(f"enabled_markdown_image_output: {BOT_MODE_ENABLED_MARKDOWN_IMAGE_OUTPUT}")
logger.info(f"enabled_plain_image_url_output: {BOT_MODE_ENABLED_PLAIN_IMAGE_URL_OUTPUT}")
logger.info(f"enabled_bing_reference_output: {BOT_MODE_ENABLED_BING_REFERENCE_OUTPUT}")
logger.info(f"enabled_plugin_output: {BOT_MODE_ENABLED_CODE_BLOCK_OUTPUT}")
if not BASE_URL:
raise Exception('upstream_base_url is not set')
else:
logger.info(f"upstream_base_url: {BASE_URL}")
if not PROXY_API_PREFIX:
logger.warning('upstream_api_prefix is not set')
else:
logger.info(f"upstream_api_prefix: {PROXY_API_PREFIX}")
if USE_OAIUSERCONTENT_URL == False:
# 检测./images和./files文件夹是否存在，不存在则创建
if not os.path.exists('./images'):
os.makedirs('./images')
if not os.path.exists('./files'):
os.makedirs('./files')
if not UPLOAD_BASE_URL:
if USE_OAIUSERCONTENT_URL:
logger.info("backend_container_url 未设置，将使用 oaiusercontent.com 作为图片域名")
else:
logger.warning("backend_container_url 未设置，图片生成功能将无法正常使用")
else:
logger.info(f"backend_container_url: {UPLOAD_BASE_URL}")
if not KEY_FOR_GPTS_INFO:
logger.warning("key_for_gpts_info 未设置，请将 gpts.json 中仅保留 “{}” 作为内容")
else:
logger.info(f"key_for_gpts_info: {KEY_FOR_GPTS_INFO}")
if not API_PREFIX:
logger.warning("backend_container_api_prefix 未设置，安全性会有所下降")
logger.info(f'Chat 接口 URI: /v1/chat/completions')
logger.info(f'绘图接口 URI: /v1/images/generations')
else:
logger.info(f"backend_container_api_prefix: {API_PREFIX}")
logger.info(f'Chat 接口 URI: /{API_PREFIX}/v1/chat/completions')
logger.info(f'绘图接口 URI: /{API_PREFIX}/v1/images/generations')
logger.info(f"need_delete_conversation_after_response: {NEED_DELETE_CONVERSATION_AFTER_RESPONSE}")
logger.info(f"use_oaiusercontent_url: {USE_OAIUSERCONTENT_URL}")
logger.info(f"use_pandora_file_server: False")
logger.info(f"custom_arkose_url: {CUSTOM_ARKOSE}")
if CUSTOM_ARKOSE:
logger.info(f"arkose_urls: {ARKOSE_URLS}")
logger.info(f"DALLE_prompt_prefix: {DALLE_PROMPT_PREFIX}")
logger.info(f"==========================================")
# 更新 gpts_configurations 列表，支持多个映射
gpts_configurations = []
for name in GPT_4_S_New_Names:
gpts_configurations.append({
"name": name.strip(),
"ori_name": "gpt-4-s"
})
for name in GPT_4_MOBILE_NEW_NAMES:
gpts_configurations.append({
"name": name.strip(),
"ori_name": "gpt-4-mobile"
})
for name in GPT_3_5_NEW_NAMES:
gpts_configurations.append({
"name": name.strip(),
"ori_name": "gpt-3.5-turbo"
})
logger.info(f"GPTS 配置信息")
# 加载配置并添加到全局列表
gpts_data = load_gpts_config("./data/gpts.json")
add_config_to_global_list(BASE_URL, PROXY_API_PREFIX, gpts_data)
# print("当前可用GPTS：" + get_accessible_model_list())
# 输出当前可用 GPTS name
# 获取当前可用的 GPTS 模型列表
accessible_model_list = get_accessible_model_list()
logger.info(f"当前可用 GPTS 列表: {accessible_model_list}")
# 检查列表中是否有重复的模型名称
if len(accessible_model_list) != len(set(accessible_model_list)):
raise Exception("检测到重复的模型名称，请检查环境变量或配置文件。")
logger.info(f"==========================================")
# print(f"GPTs Payload 生成测试")
# print(f"gpt-4-classic: {generate_gpts_payload('gpt-4-classic', [])}")
# 定义获取 token 的函数
def get_token():
# 从环境变量获取 URL 列表，并去除每个 URL 周围的空白字符
api_urls = [url.strip() for url in ARKOSE_URLS.split(",")]
for url in api_urls:
if not url:
continue
full_url = f"{url}/api/arkose/token"
payload = {'type': 'gpt-4'}
try:
response = requests.post(full_url, data=payload)
if response.status_code == 200:
token = response.json().get('token')
# 确保 token 字段存在且不是 None 或空字符串
if token:
logger.debug(f"成功从 {url} 获取 arkose token")
return token
else:
logger.error(f"获取的 token 响应无效: {token}")
else:
logger.error(f"获取 arkose token 失败: {response.status_code}, {response.text}")
except requests.RequestException as e:
logger.error(f"请求异常: {e}")
raise Exception("获取 arkose token 失败")
return None
import os
def get_image_dimensions(file_content):
with Image.open(BytesIO(file_content)) as img:
return img.width, img.height
def determine_file_use_case(mime_type):
multimodal_types = ["image/jpeg", "image/webp", "image/png", "image/gif"]
my_files_types = ["text/x-php", "application/msword", "text/x-c", "text/html",
"application/vnd.openxmlformats-officedocument.wordprocessingml.document",
"application/json", "text/javascript", "application/pdf",
"text/x-java", "text/x-tex", "text/x-typescript", "text/x-sh",
"text/x-csharp", "application/vnd.openxmlformats-officedocument.presentationml.presentation",
"text/x-c++", "application/x-latext", "text/markdown", "text/plain",
"text/x-ruby", "text/x-script.python"]
if mime_type in multimodal_types:
return "multimodal"
elif mime_type in my_files_types:
return "my_files"
else:
return "ace_upload"
def upload_file(file_content, mime_type, api_key):
logger.debug("文件上传开始")
width = None
height = None
if mime_type.startswith('image/'):
try:
width, height = get_image_dimensions(file_content)
except Exception as e:
logger.error(f"图片信息获取异常, 切换为text/plain： {e}")
mime_type = 'text/plain'
# logger.debug(f"文件内容: {file_content}")
file_size = len(file_content)
logger.debug(f"文件大小: {file_size}")
file_extension = get_file_extension(mime_type)
logger.debug(f"文件扩展名: {file_extension}")
sha256_hash = hashlib.sha256(file_content).hexdigest()
logger.debug(f"sha256_hash: {sha256_hash}")
file_name = f"{sha256_hash}{file_extension}"
logger.debug(f"文件名: {file_name}")
logger.debug(f"Use Case: {determine_file_use_case(mime_type)}")
if determine_file_use_case(mime_type) == "ace_upload":
mime_type = ''
logger.debug(f"非已知文件类型，MINE置空")
# 第1步：调用/backend-api/files接口获取上传URL
upload_api_url = f"{BASE_URL}{PROXY_API_PREFIX}/backend-api/files"
upload_request_payload = {
"file_name": file_name,
"file_size": file_size,
"use_case": determine_file_use_case(mime_type)
}
headers = {
"Authorization": f"Bearer {api_key}"
}
upload_response = requests.post(upload_api_url, json=upload_request_payload, headers=headers)
logger.debug(f"upload_response: {upload_response.text}")
if upload_response.status_code != 200:
raise Exception("Failed to get upload URL")
upload_data = upload_response.json()
upload_url = upload_data.get("upload_url")
logger.debug(f"upload_url: {upload_url}")
file_id = upload_data.get("file_id")
logger.debug(f"file_id: {file_id}")
# 第2步：上传文件
put_headers = {
'Content-Type': mime_type,
'x-ms-blob-type': 'BlockBlob' # 添加这个头部
}
put_response = requests.put(upload_url, data=file_content, headers=put_headers, proxies=proxies)
if put_response.status_code != 201:
logger.debug(f"put_response: {put_response.text}")
logger.debug(f"put_response status_code: {put_response.status_code}")
raise Exception("Failed to upload file")
# 第3步：检测上传是否成功并检查响应
check_url = f"{BASE_URL}{PROXY_API_PREFIX}/backend-api/files/{file_id}/uploaded"
check_response = requests.post(check_url, json={}, headers=headers)
logger.debug(f"check_response: {check_response.text}")
if check_response.status_code != 200:
raise Exception("Failed to check file upload completion")
check_data = check_response.json()
if check_data.get("status") != "success":
raise Exception("File upload completion check not successful")
return {
"file_id": file_id,
"file_name": file_name,
"size_bytes": file_size,
"mimeType": mime_type,
"width": width,
"height": height
}
def get_file_metadata(file_content, mime_type, api_key):
sha256_hash = hashlib.sha256(file_content).hexdigest()
logger.debug(f"sha256_hash: {sha256_hash}")
# 首先尝试从Redis中获取数据
cached_data = redis_client.get(sha256_hash)
if cached_data is not None:
# 如果在Redis中找到了数据，解码后直接返回
logger.info(f"从Redis中获取到文件缓存数据")
cache_file_data = json.loads(cached_data.decode())
tag = True
file_id = cache_file_data.get("file_id")
# 检测之前的文件是否仍然有效
check_url = f"{BASE_URL}{PROXY_API_PREFIX}/backend-api/files/{file_id}/uploaded"
headers = {
"Authorization": f"Bearer {api_key}"
}
check_response = requests.post(check_url, json={}, headers=headers)
logger.debug(f"check_response: {check_response.text}")
if check_response.status_code != 200:
tag = False
check_data = check_response.json()
if check_data.get("status") != "success":
tag = False
if tag:
logger.info(f"Redis中的文件缓存数据有效，将使用缓存数据")
return cache_file_data
else:
logger.info(f"Redis中的文件缓存数据已失效，重新上传文件")
else:
logger.info(f"Redis中没有找到文件缓存数据")
# 如果Redis中没有，上传文件并保存新数据
new_file_data = upload_file(file_content, mime_type, api_key)
mime_type = new_file_data.get('mimeType')
# 为图片类型文件添加宽度和高度信息
if mime_type.startswith('image/'):
width, height = get_image_dimensions(file_content)
new_file_data['width'] = width
new_file_data['height'] = height
# 将新的文件数据存入Redis
redis_client.set(sha256_hash, json.dumps(new_file_data))
return new_file_data
def get_file_extension(mime_type):
# 基于 MIME 类型返回文件扩展名的映射表
extension_mapping = {
"image/jpeg": ".jpg",
"image/png": ".png",
"image/gif": ".gif",
"image/webp": ".webp",
"text/x-php": ".php",
"application/msword": ".doc",
"text/x-c": ".c",
"text/html": ".html",
"application/vnd.openxmlformats-officedocument.wordprocessingml.document": ".docx",
"application/json": ".json",
"text/javascript": ".js",
"application/pdf": ".pdf",
"text/x-java": ".java",
"text/x-tex": ".tex",
"text/x-typescript": ".ts",
"text/x-sh": ".sh",
"text/x-csharp": ".cs",
"application/vnd.openxmlformats-officedocument.presentationml.presentation": ".pptx",
"text/x-c++": ".cpp",
"application/x-latext": ".latex", # 这里可能需要根据实际情况调整
"text/markdown": ".md",
"text/plain": ".txt",
"text/x-ruby": ".rb",
"text/x-script.python": ".py",
# 其他 MIME 类型和扩展名...
}
return extension_mapping.get(mime_type, "")
my_files_types = [
"text/x-php", "application/msword", "text/x-c", "text/html",
"application/vnd.openxmlformats-officedocument.wordprocessingml.document",
"application/json", "text/javascript", "application/pdf",
"text/x-java", "text/x-tex", "text/x-typescript", "text/x-sh",
"text/x-csharp", "application/vnd.openxmlformats-officedocument.presentationml.presentation",
"text/x-c++", "application/x-latext", "text/markdown", "text/plain",
"text/x-ruby", "text/x-script.python"
]
# 定义发送请求的函数
def send_text_prompt_and_get_response(messages, api_key, stream, model):
url = f"{BASE_URL}{PROXY_API_PREFIX}/backend-api/conversation"
headers = {
"Authorization": f"Bearer {api_key}"
}
# 查找模型配置
model_config = find_model_config(model)
ori_model_name = ''
if model_config:
# 检查是否有 ori_name
ori_model_name = model_config.get('ori_name', model)
formatted_messages = []
# logger.debug(f"原始 messages: {messages}")
for message in messages:
message_id = str(uuid.uuid4())
content = message.get("content")
if isinstance(content, list) and ori_model_name != 'gpt-3.5-turbo':
logger.debug(f"gpt-vision 调用")
new_parts = []
attachments = []
contains_image = False # 标记是否包含图片
for part in content:
if isinstance(part, dict) and "type" in part:
if part["type"] == "text":
new_parts.append(part["text"])
elif part["type"] == "image_url":
# logger.debug(f"image_url: {part['image_url']}")
file_url = part["image_url"]["url"]
if file_url.startswith('data:'):
# 处理 base64 编码的文件数据
mime_type, base64_data = file_url.split(';')[0], file_url.split(',')[1]
mime_type = mime_type.split(':')[1]
try:
file_content = base64.b64decode(base64_data)
except Exception as e:
logger.error(f"类型为 {mime_type} 的 base64 编码数据解码失败: {e}")
continue
else:
# 处理普通的文件URL
try:
tmp_user_agent = ua.random
logger.debug(f"随机 User-Agent: {tmp_user_agent}")
tmp_headers = {
'User-Agent': tmp_user_agent
}
file_response = requests.get(url=file_url, headers=tmp_headers, proxies=proxies)
file_content = file_response.content
mime_type = file_response.headers.get('Content-Type', '').split(';')[0].strip()
except Exception as e:
logger.error(f"获取文件 {file_url} 失败: {e}")
continue
logger.debug(f"mime_type: {mime_type}")
file_metadata = get_file_metadata(file_content, mime_type, api_key)
mime_type = file_metadata["mimeType"]
logger.debug(f"处理后 mime_type: {mime_type}")
if mime_type.startswith('image/'):
contains_image = True
new_part = {
"asset_pointer": f"file-service://{file_metadata['file_id']}",
"size_bytes": file_metadata["size_bytes"],
"width": file_metadata["width"],
"height": file_metadata["height"]
}
new_parts.append(new_part)
attachment = {
"name": file_metadata["file_name"],
"id": file_metadata["file_id"],
"mimeType": file_metadata["mimeType"],
"size": file_metadata["size_bytes"] # 添加文件大小
}
if mime_type.startswith('image/'):
attachment.update({
"width": file_metadata["width"],
"height": file_metadata["height"]
})
elif mime_type in my_files_types:
attachment.update({"fileTokenSize": len(file_metadata["file_name"])})
attachments.append(attachment)
else:
# 确保 part 是字符串
text_part = str(part) if not isinstance(part, str) else part
new_parts.append(text_part)
content_type = "multimodal_text" if contains_image else "text"
formatted_message = {
"id": message_id,
"author": {"role": message.get("role")},
"content": {"content_type": content_type, "parts": new_parts},
"metadata": {"attachments": attachments}
}
formatted_messages.append(formatted_message)
logger.critical(f"formatted_message: {formatted_message}")
else:
# 处理单个文本消息的情况
formatted_message = {
"id": message_id,
"author": {"role": message.get("role")},
"content": {"content_type": "text", "parts": [content]},
"metadata": {}
}
formatted_messages.append(formatted_message)
# logger.debug(f"formatted_messages: {formatted_messages}")
# return
payload = {}
logger.info(f"model: {model}")
# 查找模型配置
model_config = find_model_config(model)
if model_config:
# 检查是否有 ori_name
ori_model_name = model_config.get('ori_name', model)
logger.info(f"原模型名: {ori_model_name}")
if ori_model_name == 'gpt-4-s':
payload = {
# 构建 payload
"action": "next",
"messages": formatted_messages,
"parent_message_id": str(uuid.uuid4()),
"model":"gpt-4",
"timezone_offset_min": -480,
"suggestions":[],
"history_and_training_disabled": False,
"conversation_mode":{"kind":"primary_assistant"},"force_paragen":False,"force_rate_limit":False
}
elif ori_model_name == 'gpt-4-mobile':
payload = {
# 构建 payload
"action": "next",
"messages": formatted_messages,
"parent_message_id": str(uuid.uuid4()),
"model":"gpt-4-mobile",
"timezone_offset_min": -480,
"suggestions":["Give me 3 ideas about how to plan good New Years resolutions. Give me some that are personal, family, and professionally-oriented.","Write a text asking a friend to be my plus-one at a wedding next month. I want to keep it super short and casual, and offer an out.","Design a database schema for an online merch store.","Compare Gen Z and Millennial marketing strategies for sunglasses."],
"history_and_training_disabled": False,
"conversation_mode":{"kind":"primary_assistant"},"force_paragen":False,"force_rate_limit":False
}
elif ori_model_name =='gpt-3.5-turbo':
payload = {
# 构建 payload
"action": "next",
"messages": formatted_messages,
"parent_message_id": str(uuid.uuid4()),
"model": "text-davinci-002-render-sha",
"timezone_offset_min": -480,
"suggestions": [
"What are 5 creative things I could do with my kids' art? I don't want to throw them away, but it's also so much clutter.",
"I want to cheer up my friend who's having a rough day. Can you suggest a couple short and sweet text messages to go with a kitten gif?",
"Come up with 5 concepts for a retro-style arcade game.",
"I have a photoshoot tomorrow. Can you recommend me some colors and outfit options that will look good on camera?"
],
"history_and_training_disabled":False,
"arkose_token":None,
"conversation_mode": {
"kind": "primary_assistant"
},
"force_paragen":False,
"force_rate_limit":False
}
else:
payload = generate_gpts_payload(model, formatted_messages)
if not payload:
raise Exception('model is not accessible')
# 根据NEED_DELETE_CONVERSATION_AFTER_RESPONSE修改history_and_training_disabled
if NEED_DELETE_CONVERSATION_AFTER_RESPONSE:
logger.debug(f"是否保留会话: {NEED_DELETE_CONVERSATION_AFTER_RESPONSE == False}")
payload['history_and_training_disabled'] = True
if ori_model_name != 'gpt-3.5-turbo':
if CUSTOM_ARKOSE:
token = get_token()
payload["arkose_token"] = token
# 在headers中添加新字段
headers["Openai-Sentinel-Arkose-Token"] = token
logger.debug(f"headers: {headers}")
logger.debug(f"payload: {payload}")
response = requests.post(url, headers=headers, json=payload, stream=True)
# print(response)
return response
def delete_conversation(conversation_id, api_key):
logger.info(f"准备删除的会话id： {conversation_id}")
if not NEED_DELETE_CONVERSATION_AFTER_RESPONSE:
logger.info(f"自动删除会话功能已禁用")
return
if conversation_id and NEED_DELETE_CONVERSATION_AFTER_RESPONSE:
patch_url = f"{BASE_URL}{PROXY_API_PREFIX}/backend-api/conversation/{conversation_id}"
patch_headers = {
"Authorization": f"Bearer {api_key}",
}
patch_data = {"is_visible": False}
response = requests.patch(patch_url, headers=patch_headers, json=patch_data)
if response.status_code == 200:
logger.info(f"删除会话 {conversation_id} 成功")
else:
logger.error(f"PATCH 请求失败: {response.text}")
from PIL import Image
import io
def save_image(image_data, path='images'):
try:
# print(f"image_data: {image_data}")
if not os.path.exists(path):
os.makedirs(path)
current_time = datetime.now().strftime('%Y%m%d%H%M%S')
filename = f'image_{current_time}.png'
full_path = os.path.join(path, filename)
logger.debug(f"完整的文件路径: {full_path}") # 打印完整路径
# print(f"filename: {filename}")
# 使用 PIL 打开图像数据
with Image.open(io.BytesIO(image_data)) as image:
# 保存为 PNG 格式
image.save(os.path.join(path, filename), 'PNG')
logger.debug(f"保存图片成功: {filename}")
return os.path.join(path, filename)
except Exception as e:
logger.error(f"保存图片时出现异常: {e}")
def unicode_to_chinese(unicode_string):
# 首先将字符串转换为标准的 JSON 格式字符串
json_formatted_str = json.dumps(unicode_string)
# 然后将 JSON 格式的字符串解析回正常的字符串
return json.loads(json_formatted_str)
import re
# 辅助函数：检查是否为合法的引用格式或正在构建中的引用格式
def is_valid_citation_format(text):
# 完整且合法的引用格式，允许紧跟另一个起始引用标记
if re.fullmatch(r'\u3010\d+\u2020(source|\u6765\u6e90)\u3011\u3010?', text):
return True
# 完整且合法的引用格式
if re.fullmatch(r'\u3010\d+\u2020(source|\u6765\u6e90)\u3011', text):
return True
# 合法的部分构建格式
if re.fullmatch(r'\u3010(\d+)?(\u2020(source|\u6765\u6e90)?)?', text):
return True
# 不合法的格式
return False
# 辅助函数：检查是否为完整的引用格式
# 检查是否为完整的引用格式
def is_complete_citation_format(text):
return bool(re.fullmatch(r'\u3010\d+\u2020(source|\u6765\u6e90)\u3011\u3010?', text))
# 替换完整的引用格式
def replace_complete_citation(text, citations):
def replace_match(match):
citation_number = match.group(1)
for citation in citations:
cited_message_idx = citation.get('metadata', {}).get('extra', {}).get('cited_message_idx')
logger.debug(f"cited_message_idx: {cited_message_idx}")
logger.debug(f"citation_number: {citation_number}")
logger.debug(f"is citation_number == cited_message_idx: {cited_message_idx == int(citation_number)}")
logger.debug(f"citation: {citation}")
if cited_message_idx == int(citation_number):
url = citation.get("metadata", {}).get("url", "")
if ((BOT_MODE_ENABLED == False) or (BOT_MODE_ENABLED == True and BOT_MODE_ENABLED_BING_REFERENCE_OUTPUT == True)):
return f"[[{citation_number}]({url})]"
else:
return ""
# return match.group(0) # 如果没有找到对应的引用，返回原文本
logger.critical(f"没有找到对应的引用，舍弃{match.group(0)}引用")
return ""
# 使用 finditer 找到第一个匹配项
match_iter = re.finditer(r'\u3010(\d+)\u2020(source|\u6765\u6e90)\u3011', text)
first_match = next(match_iter, None)
if first_match:
start, end = first_match.span()
replaced_text = text[:start] + replace_match(first_match) + text[end:]
remaining_text = text[end:]
else:
replaced_text = text
remaining_text = ""
is_potential_citation = is_valid_citation_format(remaining_text)
# 替换掉replaced_text末尾的remaining_text
logger.debug(f"replaced_text: {replaced_text}")
logger.debug(f"remaining_text: {remaining_text}")
logger.debug(f"is_potential_citation: {is_potential_citation}")
if is_potential_citation:
replaced_text = replaced_text[:-len(remaining_text)]
return replaced_text, remaining_text, is_potential_citation
def is_valid_sandbox_combined_corrected_final_v2(text):
# 更新正则表达式以包含所有合法格式
patterns = [
r'.*\(sandbox:\/[^)]*\)?', # sandbox 后跟路径，包括不完整路径
r'.*\(', # 只有 "(" 也视为合法格式
r'.*\(sandbox(:|$)', # 匹配 "(sandbox" 或 "(sandbox:"，确保后面不跟其他字符或字符串结束
r'.*\(sandbox:.*\n*', # 匹配 "(sandbox:" 后跟任意数量的换行符
]
# 检查文本是否符合任一合法格式
return any(bool(re.fullmatch(pattern, text)) for pattern in patterns)
def is_complete_sandbox_format(text):
# 完整格式应该类似于 (sandbox:/xx/xx/xx 或 (sandbox:/xx/xx)
pattern = r'.*\(sandbox\:\/[^)]+\)\n*' # 匹配 "(sandbox:" 后跟任意数量的换行符
return bool(re.fullmatch(pattern, text))
import urllib.parse
from urllib.parse import unquote
def replace_sandbox(text, conversation_id, message_id, api_key):
def replace_match(match):
sandbox_path = match.group(1)
download_url = get_download_url(conversation_id, message_id, sandbox_path)
if download_url == None:
return "\n```\nError: 沙箱文件下载失败，这可能是因为您启用了隐私模式\n```"
file_name = extract_filename(download_url)
timestamped_file_name = timestamp_filename(file_name)
if USE_OAIUSERCONTENT_URL == False:
download_file(download_url, timestamped_file_name)
return f"({UPLOAD_BASE_URL}/files/{timestamped_file_name})"
else:
return f"({download_url})"
def get_download_url(conversation_id, message_id, sandbox_path):
# 模拟发起请求以获取下载 URL
sandbox_info_url = f"{BASE_URL}{PROXY_API_PREFIX}/backend-api/conversation/{conversation_id}/interpreter/download?message_id={message_id}&sandbox_path={sandbox_path}"
headers = {
"Authorization": f"Bearer {api_key}"
}
response = requests.get(sandbox_info_url, headers=headers)
if response.status_code == 200:
logger.debug(f"获取下载 URL 成功: {response.json()}")
return response.json().get("download_url")
else:
logger.error(f"获取下载 URL 失败: {response.text}")
return None