diff --git "a/app.py" "b/app.py" --- "a/app.py" +++ "b/app.py" @@ -1,1724 +1,1782 @@ -from flask import Flask, request, jsonify, Response, render_template_string, render_template, redirect, url_for, session as flask_session -import requests -import time -import json -import uuid -import random -import io -import re -from functools import wraps -import hashlib -import jwt -import os -import threading -from datetime import datetime, timedelta - -app = Flask(__name__, template_folder='templates') -app.secret_key = os.environ.get("SECRET_KEY", "abacus_chat_proxy_secret_key") -app.config['PERMANENT_SESSION_LIFETIME'] = timedelta(days=7) - -# 添加tokenizer服务URL -TOKENIZER_SERVICE_URL = "https://malt666-tokenizer.hf.space/count_tokens" - -API_ENDPOINT_URL = "https://abacus.ai/api/v0/describeDeployment" -MODEL_LIST_URL = "https://abacus.ai/api/v0/listExternalApplications" -CHAT_URL = "https://apps.abacus.ai/api/_chatLLMSendMessageSSE" -USER_INFO_URL = "https://abacus.ai/api/v0/_getUserInfo" -COMPUTE_POINTS_URL = "https://apps.abacus.ai/api/_getOrganizationComputePoints" -COMPUTE_POINTS_LOG_URL = "https://abacus.ai/api/v0/_getOrganizationComputePointLog" -CREATE_CONVERSATION_URL = "https://apps.abacus.ai/api/createDeploymentConversation" -DELETE_CONVERSATION_URL = "https://apps.abacus.ai/api/deleteDeploymentConversation" -GET_CONVERSATION_URL = "https://apps.abacus.ai/api/getDeploymentConversation" -COMPUTE_POINT_TOGGLE_URL = "https://abacus.ai/api/v0/_updateOrganizationComputePointToggle" - - -USER_AGENTS = [ - "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/116.0.0.0 Safari/537.36" -] - - -PASSWORD = None -USER_NUM = 0 -USER_DATA = [] -CURRENT_USER = -1 -MODELS = set() - -TRACE_ID = "3042e28b3abf475d8d973c7e904935af" -SENTRY_TRACE = f"{TRACE_ID}-80d9d2538b2682d0" - - -# 添加一个计数器记录健康检查次数 -health_check_counter = 0 - - -# 添加统计变量 -model_usage_stats = {} # 模型使用次数统计 -total_tokens = { - "prompt": 0, # 输入token统计 - "completion": 0, # 输出token统计 - "total": 0 # 总token统计 -} - -# 模型调用记录 -model_usage_records = [] # 每次调用详细记录 -MODEL_USAGE_RECORDS_FILE = "model_usage_records.json" # 调用记录保存文件 - -# 计算点信息 -compute_points = { - "left": 0, # 剩余计算点 - "total": 0, # 总计算点 - "used": 0, # 已使用计算点 - "percentage": 0, # 使用百分比 - "last_update": None # 最后更新时间 -} - -# 计算点使用日志 -compute_points_log = { - "columns": {}, # 列名 - "log": [] # 日志数据 -} - -# 多用户计算点信息 -users_compute_points = [] - -# 记录启动时间 -START_TIME = datetime.utcnow() + timedelta(hours=8) # 北京时间 - - -# 自定义JSON编码器，处理datetime对象 -class DateTimeEncoder(json.JSONEncoder): - def default(self, obj): - if isinstance(obj, datetime): - return obj.strftime('%Y-%m-%d %H:%M:%S') - return super(DateTimeEncoder, self).default(obj) - - -# 加载模型调用记录 -def load_model_usage_records(): - global model_usage_records - try: - if os.path.exists(MODEL_USAGE_RECORDS_FILE): - with open(MODEL_USAGE_RECORDS_FILE, 'r', encoding='utf-8') as f: - records = json.load(f) - if isinstance(records, list): - model_usage_records = records - print(f"成功加载 {len(model_usage_records)} 条模型调用记录") - else: - print("调用记录文件格式不正确，初始化为空列表") - except Exception as e: - print(f"加载模型调用记录失败: {e}") - model_usage_records = [] - -# 保存模型调用记录 -def save_model_usage_records(): - try: - with open(MODEL_USAGE_RECORDS_FILE, 'w', encoding='utf-8') as f: - json.dump(model_usage_records, f, ensure_ascii=False, indent=2, cls=DateTimeEncoder) - print(f"成功保存 {len(model_usage_records)} 条模型调用记录") - except Exception as e: - print(f"保存模型调用记录失败: {e}") - - -def update_conversation_id(user_index, conversation_id): - """更新用户的conversation_id并保存到配置文件""" - try: - with open("config.json", "r") as f: - config = json.load(f) - - if "config" in config and user_index < len(config["config"]): - config["config"][user_index]["conversation_id"] = conversation_id - - # 保存到配置文件 - with open("config.json", "w") as f: - json.dump(config, f, indent=4) - - print(f"已将用户 {user_index+1} 的conversation_id更新为: {conversation_id}") - else: - print(f"更新conversation_id失败: 配置文件格式错误或用户索引越界") - except Exception as e: - print(f"更新conversation_id失败: {e}") - - -def resolve_config(): - # 从环境变量读取多组配置 - config_list = [] - i = 1 - while True: - cookie = os.environ.get(f"cookie_{i}") - if not cookie: - break - - # 为每个cookie创建一个配置项，conversation_id初始为空 - config_list.append({ - "conversation_id": "", # 初始为空，将通过get_or_create_conversation自动创建 - "cookies": cookie - }) - i += 1 - - # 如果环境变量存在配置，使用环境变量的配置 - if config_list: - print(f"从环境变量加载了 {len(config_list)} 个配置") - return config_list - - # 如果环境变量不存在，从文件读取 - try: - with open("config.json", "r") as f: - config = json.load(f) - config_list = config.get("config") - return config_list - except FileNotFoundError: - print("未找到config.json文件") - return [] - except json.JSONDecodeError: - print("config.json格式错误") - return [] - - -def get_password(): - global PASSWORD - # 从环境变量读取密码 - env_password = os.environ.get("password") - if env_password: - PASSWORD = hashlib.sha256(env_password.encode()).hexdigest() - return - - # 如果环境变量不存在，从文件读取 - try: - with open("password.txt", "r") as f: - PASSWORD = f.read().strip() - except FileNotFoundError: - with open("password.txt", "w") as f: - PASSWORD = None - - -def require_auth(f): - @wraps(f) - def decorated(*args, **kwargs): - if not PASSWORD: - return f(*args, **kwargs) - - # 检查Flask会话是否已登录 - if flask_session.get('logged_in'): - return f(*args, **kwargs) - - # 如果是API请求，检查Authorization头 - auth = request.authorization - if not auth or not check_auth(auth.token): - # 如果是浏览器请求，重定向到登录页面 - if request.headers.get('Accept', '').find('text/html') >= 0: - return redirect(url_for('login')) - return jsonify({"error": "Unauthorized access"}), 401 - return f(*args, **kwargs) - - return decorated - - -def check_auth(token): - return hashlib.sha256(token.encode()).hexdigest() == PASSWORD - - -def is_token_expired(token): - if not token: - return True - - try: - # Malkodi tokenon sen validigo de subskribo - payload = jwt.decode(token, options={"verify_signature": False}) - # Akiru eksvalidiĝan tempon, konsideru eksvalidiĝinta 5 minutojn antaŭe - return payload.get('exp', 0) - time.time() < 300 - except: - return True - - -def refresh_token(session, cookies): - """Uzu kuketon por refreŝigi session token, nur revenigu novan tokenon""" - headers = { - "accept": "application/json, text/plain, */*", - "accept-language": "zh-CN,zh;q=0.9", - "content-type": "application/json", - "reai-ui": "1", - "sec-ch-ua": "\"Chromium\";v=\"116\", \"Not)A;Brand\";v=\"24\", \"Google Chrome\";v=\"116\"", - "sec-ch-ua-mobile": "?0", - "sec-ch-ua-platform": "\"Windows\"", - "sec-fetch-dest": "empty", - "sec-fetch-mode": "cors", - "sec-fetch-site": "same-site", - "x-abacus-org-host": "apps", - "user-agent": random.choice(USER_AGENTS), - "origin": "https://apps.abacus.ai", - "referer": "https://apps.abacus.ai/", - "cookie": cookies - } - - try: - response = session.post( - USER_INFO_URL, - headers=headers, - json={}, - cookies=None - ) - - if response.status_code == 200: - response_data = response.json() - if response_data.get('success') and 'sessionToken' in response_data.get('result', {}): - return response_data['result']['sessionToken'] - else: - print(f"刷新token失败: {response_data.get('error', '未知错误')}") - return None - else: - print(f"刷新token失败，状态码: {response.status_code}") - return None - except Exception as e: - print(f"刷新token异常: {e}") - return None - - -def get_model_map(session, cookies, session_token): - """Akiru disponeblan modelan liston kaj ĝiajn mapajn rilatojn""" - headers = { - "accept": "application/json, text/plain, */*", - "accept-language": "zh-CN,zh;q=0.9", - "content-type": "application/json", - "reai-ui": "1", - "sec-ch-ua": "\"Chromium\";v=\"116\", \"Not)A;Brand\";v=\"24\", \"Google Chrome\";v=\"116\"", - "sec-ch-ua-mobile": "?0", - "sec-ch-ua-platform": "\"Windows\"", - "sec-fetch-dest": "empty", - "sec-fetch-mode": "cors", - "sec-fetch-site": "same-site", - "x-abacus-org-host": "apps", - "user-agent": random.choice(USER_AGENTS), - "origin": "https://apps.abacus.ai", - "referer": "https://apps.abacus.ai/", - "cookie": cookies - } - - if session_token: - headers["session-token"] = session_token - - model_map = {} - models_set = set() - - try: - response = session.post( - MODEL_LIST_URL, - headers=headers, - json={}, - cookies=None - ) - - if response.status_code != 200: - print(f"获取模型列表失败，状态码: {response.status_code}") - raise Exception("API请求失败") - - data = response.json() - if not data.get('success'): - print(f"获取模型列表失败: {data.get('error', '未知错误')}") - raise Exception("API返回错误") - - applications = [] - if isinstance(data.get('result'), dict): - applications = data.get('result', {}).get('externalApplications', []) - elif isinstance(data.get('result'), list): - applications = data.get('result', []) - - for app in applications: - app_name = app.get('name', '') - app_id = app.get('externalApplicationId', '') - prediction_overrides = app.get('predictionOverrides', {}) - llm_name = prediction_overrides.get('llmName', '') if prediction_overrides else '' - - if not (app_name and app_id and llm_name): - continue - - model_name = app_name - model_map[model_name] = (app_id, llm_name) - models_set.add(model_name) - - if not model_map: - raise Exception("未找到任何可用模型") - - return model_map, models_set - - except Exception as e: - print(f"获取模型列表异常: {e}") - raise - - -def init_session(): - get_password() - global USER_NUM, MODELS, USER_DATA - - config_list = resolve_config() - user_num = len(config_list) - all_models = set() - - for i in range(user_num): - user = config_list[i] - cookies = user.get("cookies") - conversation_id = user.get("conversation_id") - session = requests.Session() - - session_token = refresh_token(session, cookies) - if not session_token: - print(f"无法获取cookie {i+1}的token") - continue - - try: - model_map, models_set = get_model_map(session, cookies, session_token) - all_models.update(models_set) - USER_DATA.append((session, cookies, session_token, conversation_id, model_map, i)) - - # 对第一个成功配置的用户，初始化计算点数记录功能 - if i == 0: - try: - headers = { - "accept": "application/json, text/plain, */*", - "accept-language": "zh-CN,zh;q=0.9", - "content-type": "application/json", - "reai-ui": "1", - "sec-ch-ua": "\"Chromium\";v=\"116\", \"Not)A;Brand\";v=\"24\", \"Google Chrome\";v=\"116\"", - "sec-ch-ua-mobile": "?0", - "sec-ch-ua-platform": "\"Windows\"", - "sec-fetch-dest": "empty", - "sec-fetch-mode": "cors", - "sec-fetch-site": "same-site", - "x-abacus-org-host": "apps", - "session-token": session_token - } - - response = session.post( - COMPUTE_POINT_TOGGLE_URL, - headers=headers, - json={"alwaysDisplay": True}, - cookies=None - ) - - if response.status_code == 200: - result = response.json() - if result.get("success"): - print("成功初始化计算点数记录功能为开启状态") - else: - print(f"初始化计算点数记录功能失败: {result.get('error', '未知错误')}") - else: - print(f"初始化计算点数记录功能失败，状态码: {response.status_code}") - except Exception as e: - print(f"初始化计算点数记录功能时出错: {e}") - except Exception as e: - print(f"配置用户 {i+1} 失败: {e}") - continue - - USER_NUM = len(USER_DATA) - if USER_NUM == 0: - print("No user available, exiting...") - exit(1) - - MODELS = all_models - print(f"启动完成，共配置 {USER_NUM} 个用户") - - -def update_cookie(session, cookies): - cookie_jar = {} - for key, value in session.cookies.items(): - cookie_jar[key] = value - cookie_dict = {} - for item in cookies.split(";"): - key, value = item.strip().split("=", 1) - cookie_dict[key] = value - cookie_dict.update(cookie_jar) - cookies = "; ".join([f"{key}={value}" for key, value in cookie_dict.items()]) - return cookies - - -user_data = init_session() - - -@app.route("/v1/models", methods=["GET"]) -@require_auth -def get_models(): - if len(MODELS) == 0: - return jsonify({"error": "No models available"}), 500 - model_list = [] - for model in MODELS: - model_list.append( - { - "id": model, - "object": "model", - "created": int(time.time()), - "owned_by": "Elbert", - "name": model, - } - ) - return jsonify({"object": "list", "data": model_list}) - - -@app.route("/v1/chat/completions", methods=["POST"]) -@require_auth -def chat_completions(): - openai_request = request.get_json() - stream = openai_request.get("stream", False) - messages = openai_request.get("messages") - if messages is None: - return jsonify({"error": "Messages is required", "status": 400}), 400 - model = openai_request.get("model") - if model not in MODELS: - return ( - jsonify( - { - "error": "Model not available, check if it is configured properly", - "status": 404, - } - ), - 404, - ) - message = format_message(messages) - think = ( - openai_request.get("think", False) if model == "Claude Sonnet 3.7" else False - ) - return ( - send_message(message, model, think) - if stream - else send_message_non_stream(message, model, think) - ) - - -def get_user_data(): - global CURRENT_USER - CURRENT_USER = (CURRENT_USER + 1) % USER_NUM - print(f"使用配置 {CURRENT_USER+1}") - - # Akiru uzantajn datumojn - session, cookies, session_token, conversation_id, model_map, user_index = USER_DATA[CURRENT_USER] - - # Kontrolu ĉu la tokeno eksvalidiĝis, se jes, refreŝigu ĝin - if is_token_expired(session_token): - print(f"Cookie {CURRENT_USER+1}的token已过期或即将过期，正在刷新...") - new_token = refresh_token(session, cookies) - if new_token: - # Ĝisdatigu la globale konservitan tokenon - USER_DATA[CURRENT_USER] = (session, cookies, new_token, conversation_id, model_map, user_index) - session_token = new_token - print(f"成功更新token: {session_token[:15]}...{session_token[-15:]}") - else: - print(f"警告：无法刷新Cookie {CURRENT_USER+1}的token，继续使用当前token") - - return (session, cookies, session_token, conversation_id, model_map, user_index) - - -def create_conversation(session, cookies, session_token, external_application_id=None, deployment_id=None): - """创建新的会话""" - if not (external_application_id and deployment_id): - print("无法创建新会话: 缺少必要参数") - return None - - headers = { - "accept": "application/json, text/plain, */*", - "accept-language": "zh-CN,zh;q=0.9", - "content-type": "application/json", - "cookie": cookies, - "user-agent": random.choice(USER_AGENTS), - "x-abacus-org-host": "apps" - } - - if session_token: - headers["session-token"] = session_token - - create_payload = { - "deploymentId": deployment_id, - "name": "New Chat", - "externalApplicationId": external_application_id - } - - try: - response = session.post( - CREATE_CONVERSATION_URL, - headers=headers, - json=create_payload - ) - - if response.status_code == 200: - data = response.json() - if data.get("success", False): - new_conversation_id = data.get("result", {}).get("deploymentConversationId") - if new_conversation_id: - print(f"成功创建新的conversation: {new_conversation_id}") - return new_conversation_id - - print(f"创建会话失败: {response.status_code} - {response.text[:100]}") - return None - except Exception as e: - print(f"创建会话时出错: {e}") - return None - - -def delete_conversation(session, cookies, session_token, conversation_id, deployment_id="14b2a314cc"): - """删除指定的对话""" - if not conversation_id: - print("无法删除对话: 缺少conversation_id") - return False - - headers = { - "accept": "application/json, text/plain, */*", - "accept-language": "zh-CN,zh;q=0.9", - "content-type": "application/json", - "cookie": cookies, - "user-agent": random.choice(USER_AGENTS), - "x-abacus-org-host": "apps" - } - - if session_token: - headers["session-token"] = session_token - - delete_payload = { - "deploymentId": deployment_id, - "deploymentConversationId": conversation_id - } - - try: - response = session.post( - DELETE_CONVERSATION_URL, - headers=headers, - json=delete_payload - ) - - if response.status_code == 200: - data = response.json() - if data.get("success", False): - print(f"成功删除对话: {conversation_id}") - return True - - print(f"删除对话失败: {response.status_code} - {response.text[:100]}") - return False - except Exception as e: - print(f"删除对话时出错: {e}") - return False - - -def get_or_create_conversation(session, cookies, session_token, conversation_id, model_map, model, user_index): - """获取对话ID，如果不存在则创建；返回是否是使用现有会话""" - print(f"\n----- 获取会话ID (用户 {user_index+1}) -----") - # 如果有现有的会话ID，直接使用 - if conversation_id: - print(f"使用现有会话ID: {conversation_id}") - return conversation_id, True - - # 如果没有会话ID，创建新的 - print("没有会话ID，创建新会话...") - deployment_id = "14b2a314cc" - - # 确保模型信息存在 - if model not in model_map or len(model_map[model]) < 2: - print(f"错误: 无法获取模型 {model} 的信息") - return None, False - - external_app_id = model_map[model][0] - - # 创建新会话 - new_conversation_id = create_conversation( - session, cookies, session_token, - external_application_id=external_app_id, - deployment_id=deployment_id - ) - - if new_conversation_id: - print(f"成功创建新会话ID: {new_conversation_id}") - - # 更新全局存储的会话ID - global USER_DATA, CURRENT_USER - session, cookies, session_token, _, model_map, _ = USER_DATA[CURRENT_USER] - USER_DATA[CURRENT_USER] = (session, cookies, session_token, new_conversation_id, model_map, user_index) - - # 保存到配置文件 - update_conversation_id(user_index, new_conversation_id) - - return new_conversation_id, False - - print("创建新会话失败") - return None, False - - -def generate_trace_id(): - """Generu novan trace_id kaj sentry_trace""" - trace_id = str(uuid.uuid4()).replace('-', '') - sentry_trace = f"{trace_id}-{str(uuid.uuid4())[:16]}" - return trace_id, sentry_trace - - -def send_message(message, model, think=False): - """Flua traktado kaj plusendo de mesaĝoj""" - print("\n===== 开始处理消息 =====") - print(f"模型: {model}") - print(f"思考模式: {think}") - - (session, cookies, session_token, conversation_id, model_map, user_index) = get_user_data() - print(f"使用用户配置: {user_index + 1}") - - # 获取会话ID，并判断是否使用现有会话 - conversation_id, is_existing = get_or_create_conversation( - session, cookies, session_token, conversation_id, model_map, model, user_index - ) - - # 如果没有有效的会话ID，返回错误 - if not conversation_id: - return jsonify({"error": "Failed to get a valid conversation ID"}), 500 - - print(f"会话ID: {conversation_id} (是否为现有会话: {is_existing})") - - trace_id, sentry_trace = generate_trace_id() - - # 计算输入token - print("\n----- 计算输入token -----") - prompt_tokens, calculation_method = num_tokens_from_string(message, model) - print(f"输入token数: {prompt_tokens}") - print(f"计算方法: {calculation_method}") - completion_buffer = io.StringIO() # 收集所有输出用于计算token - - headers = { - "accept": "text/event-stream", - "accept-language": "zh-CN,zh;q=0.9", - "baggage": f"sentry-environment=production,sentry-release=975eec6685013679c139fc88db2c48e123d5c604,sentry-public_key=3476ea6df1585dd10e92cdae3a66ff49,sentry-trace_id={trace_id}", - "content-type": "text/plain;charset=UTF-8", - "cookie": cookies, - "sec-ch-ua": "\"Chromium\";v=\"116\", \"Not)A;Brand\";v=\"24\", \"Google Chrome\";v=\"116\"", - "sec-ch-ua-mobile": "?0", - "sec-ch-ua-platform": "\"Windows\"", - "sec-fetch-dest": "empty", - "sec-fetch-mode": "cors", - "sec-fetch-site": "same-origin", - "sentry-trace": sentry_trace, - "user-agent": random.choice(USER_AGENTS), - "x-abacus-org-host": "apps" - } - - if session_token: - headers["session-token"] = session_token - - # 构建基础请求 - payload = { - "requestId": str(uuid.uuid4()), - "deploymentConversationId": conversation_id, - "message": message, - "isDesktop": False, - "chatConfig": { - "timezone": "Asia/Shanghai", - "language": "zh-CN" - }, - "llmName": model_map[model][1], - "externalApplicationId": model_map[model][0] - } - - # 如果是使用现有会话，添加regenerate和editPrompt参数 - if is_existing: - payload["regenerate"] = True - payload["editPrompt"] = True - print("为现有会话添加 regenerate=True 和 editPrompt=True") - - if think: - payload["useThinking"] = think - - try: - response = session.post( - CHAT_URL, - headers=headers, - data=json.dumps(payload), - stream=True, - cookies=None - ) - - response.raise_for_status() - - def extract_segment(line_data): - try: - data = json.loads(line_data) - if "segment" in data: - if isinstance(data["segment"], str): - return data["segment"] - elif isinstance(data["segment"], dict) and "segment" in data["segment"]: - return data["segment"]["segment"] - return "" - except: - return "" - - def generate(): - id = "" - think_state = 2 - - yield "data: " + json.dumps({"object": "chat.completion.chunk", "choices": [{"delta": {"role": "assistant"}}]}) + "\n\n" - - for line in response.iter_lines(): - if line: - decoded_line = line.decode("utf-8") - try: - if think: - data = json.loads(decoded_line) - if data.get("type") != "text": - continue - elif think_state == 2: - id = data.get("messageId") - segment = "\n" + data.get("segment", "") - completion_buffer.write(segment) # 收集输出 - yield f"data: {json.dumps({'object': 'chat.completion.chunk', 'choices': [{'delta': {'content': segment}}]})}\n\n" - think_state = 1 - elif think_state == 1: - if data.get("messageId") != id: - segment = data.get("segment", "") - completion_buffer.write(segment) # 收集输出 - yield f"data: {json.dumps({'object': 'chat.completion.chunk', 'choices': [{'delta': {'content': segment}}]})}\n\n" - else: - segment = "\n\n" + data.get("segment", "") - completion_buffer.write(segment) # 收集输出 - yield f"data: {json.dumps({'object': 'chat.completion.chunk', 'choices': [{'delta': {'content': segment}}]})}\n\n" - think_state = 0 - else: - segment = data.get("segment", "") - completion_buffer.write(segment) # 收集输出 - yield f"data: {json.dumps({'object': 'chat.completion.chunk', 'choices': [{'delta': {'content': segment}}]})}\n\n" - else: - segment = extract_segment(decoded_line) - if segment: - completion_buffer.write(segment) # 收集输出 - yield f"data: {json.dumps({'object': 'chat.completion.chunk', 'choices': [{'delta': {'content': segment}}]})}\n\n" - except Exception as e: - print(f"处理响应出错: {e}") - - yield "data: " + json.dumps({"object": "chat.completion.chunk", "choices": [{"delta": {}, "finish_reason": "stop"}]}) + "\n\n" - yield "data: [DONE]\n\n" - - # 在流式传输完成后计算token并更新统计 - completion_result, _ = num_tokens_from_string(completion_buffer.getvalue(), model) - - # 保存对话历史并获取计算点数 - _, compute_points_used = save_conversation_history(session, cookies, session_token, conversation_id) - - # 更新统计信息 - update_model_stats(model, prompt_tokens, completion_result, calculation_method, compute_points_used) - - return Response(generate(), mimetype="text/event-stream") - except requests.exceptions.RequestException as e: - error_details = str(e) - if hasattr(e, 'response') and e.response is not None: - if hasattr(e.response, 'text'): - error_details += f" - Response: {e.response.text[:200]}" - print(f"发送消息失败: {error_details}") - - # 如果是使用现有会话失败，尝试创建新会话重试一次 - if is_existing: - print("使用现有会话失败，尝试创建新会话...") - # 创建新会话 - deployment_id = "14b2a314cc" - external_app_id = model_map[model][0] if model in model_map and len(model_map[model]) >= 2 else None - - if external_app_id: - new_conversation_id = create_conversation( - session, cookies, session_token, - external_application_id=external_app_id, - deployment_id=deployment_id - ) - - if new_conversation_id: - print(f"成功创建新会话ID: {new_conversation_id}，重试请求") - # 更新全局存储的会话ID - global USER_DATA, CURRENT_USER - session, cookies, session_token, _, model_map, _ = USER_DATA[CURRENT_USER] - USER_DATA[CURRENT_USER] = (session, cookies, session_token, new_conversation_id, model_map, user_index) - - # 保存到配置文件 - update_conversation_id(user_index, new_conversation_id) - - # 修改payload使用新会话ID，并移除regenerate和editPrompt - payload["deploymentConversationId"] = new_conversation_id - if "regenerate" in payload: - del payload["regenerate"] - if "editPrompt" in payload: - del payload["editPrompt"] - - try: - # 非流式重试逻辑与流式类似，但需要重新提取响应内容 - response = session.post( - CHAT_URL, - headers=headers, - data=json.dumps(payload), - stream=True, - cookies=None - ) - - response.raise_for_status() - # 重用现有提取逻辑... - # 但这里代码重复太多，实际应该重构为共享函数 - buffer = io.StringIO() - - for line in response.iter_lines(): - if line: - decoded_line = line.decode("utf-8") - segment = extract_segment(decoded_line) - if segment: - buffer.write(segment) - - response_content = buffer.getvalue() - - # 计算输出token并更新统计信息 - completion_result, _ = num_tokens_from_string(response_content, model) - - # 保存对话历史并获取计算点数 - _, compute_points_used = save_conversation_history(session, cookies, session_token, new_conversation_id) - - # 更新统计信息 - update_model_stats(model, prompt_tokens, completion_result, calculation_method, compute_points_used) - - return jsonify({ - "id": f"chatcmpl-{str(uuid.uuid4())}", - "object": "chat.completion", - "created": int(time.time()), - "model": model, - "choices": [{ - "index": 0, - "message": { - "role": "assistant", - "content": response_content - }, - "finish_reason": "stop" - }], - "usage": { - "prompt_tokens": prompt_tokens, - "completion_tokens": completion_result, - "total_tokens": prompt_tokens + completion_result - } - }) - except Exception as retry_e: - print(f"重试失败: {retry_e}") - - return jsonify({"error": f"Failed to send message: {error_details}"}), 500 - - -def send_message_non_stream(message, model, think=False): - """Ne-flua traktado de mesaĝoj""" - print("\n===== 开始处理消息（非流式） =====") - print(f"模型: {model}") - print(f"思考模式: {think}") - - (session, cookies, session_token, conversation_id, model_map, user_index) = get_user_data() - print(f"使用用户配置: {user_index + 1}") - - # 获取会话ID，并判断是否使用现有会话 - conversation_id, is_existing = get_or_create_conversation( - session, cookies, session_token, conversation_id, model_map, model, user_index - ) - - # 如果没有有效的会话ID，返回错误 - if not conversation_id: - return jsonify({"error": "Failed to get a valid conversation ID"}), 500 - - print(f"会话ID: {conversation_id} (是否为现有会话: {is_existing})") - - trace_id, sentry_trace = generate_trace_id() - - # 计算输入token - print("\n----- 计算输入token -----") - prompt_tokens, calculation_method = num_tokens_from_string(message, model) - print(f"输入token数: {prompt_tokens}") - print(f"计算方法: {calculation_method}") - - headers = { - "accept": "text/event-stream", - "accept-language": "zh-CN,zh;q=0.9", - "baggage": f"sentry-environment=production,sentry-release=975eec6685013679c139fc88db2c48e123d5c604,sentry-public_key=3476ea6df1585dd10e92cdae3a66ff49,sentry-trace_id={trace_id}", - "content-type": "text/plain;charset=UTF-8", - "cookie": cookies, - "sec-ch-ua": "\"Chromium\";v=\"116\", \"Not)A;Brand\";v=\"24\", \"Google Chrome\";v=\"116\"", - "sec-ch-ua-mobile": "?0", - "sec-ch-ua-platform": "\"Windows\"", - "sec-fetch-dest": "empty", - "sec-fetch-mode": "cors", - "sec-fetch-site": "same-origin", - "sentry-trace": sentry_trace, - "user-agent": random.choice(USER_AGENTS), - "x-abacus-org-host": "apps" - } - - if session_token: - headers["session-token"] = session_token - - # 构建基础请求 - payload = { - "requestId": str(uuid.uuid4()), - "deploymentConversationId": conversation_id, - "message": message, - "isDesktop": False, - "chatConfig": { - "timezone": "Asia/Shanghai", - "language": "zh-CN" - }, - "llmName": model_map[model][1], - "externalApplicationId": model_map[model][0] - } - - # 如果是使用现有会话，添加regenerate和editPrompt参数 - if is_existing: - payload["regenerate"] = True - payload["editPrompt"] = True - print("为现有会话添加 regenerate=True 和 editPrompt=True") - - if think: - payload["useThinking"] = think - - try: - response = session.post( - CHAT_URL, - headers=headers, - data=json.dumps(payload), - stream=True, - cookies=None - ) - - response.raise_for_status() - buffer = io.StringIO() - - def extract_segment(line_data): - try: - data = json.loads(line_data) - if "segment" in data: - if isinstance(data["segment"], str): - return data["segment"] - elif isinstance(data["segment"], dict) and "segment" in data["segment"]: - return data["segment"]["segment"] - return "" - except: - return "" - - if think: - id = "" - think_state = 2 - think_buffer = io.StringIO() - content_buffer = io.StringIO() - - for line in response.iter_lines(): - if line: - decoded_line = line.decode("utf-8") - try: - data = json.loads(decoded_line) - if data.get("type") != "text": - continue - elif think_state == 2: - id = data.get("messageId") - segment = data.get("segment", "") - think_buffer.write(segment) - think_state = 1 - elif think_state == 1: - if data.get("messageId") != id: - segment = data.get("segment", "") - content_buffer.write(segment) - else: - segment = data.get("segment", "") - think_buffer.write(segment) - think_state = 0 - else: - segment = data.get("segment", "") - content_buffer.write(segment) - except Exception as e: - print(f"处理响应出错: {e}") - - think_content = think_buffer.getvalue() - response_content = content_buffer.getvalue() - - # 计算输出token并更新统计信息 - completion_result, _ = num_tokens_from_string(think_content + response_content, model) - - # 保存对话历史并获取计算点数 - _, compute_points_used = save_conversation_history(session, cookies, session_token, conversation_id) - - # 更新统计信息 - update_model_stats(model, prompt_tokens, completion_result, calculation_method, compute_points_used) - - return jsonify({ - "id": f"chatcmpl-{str(uuid.uuid4())}", - "object": "chat.completion", - "created": int(time.time()), - "model": model, - "choices": [{ - "index": 0, - "message": { - "role": "assistant", - "content": f"\n{think_content}\n\n{response_content}" - }, - "finish_reason": "stop" - }], - "usage": { - "prompt_tokens": prompt_tokens, - "completion_tokens": completion_result, - "total_tokens": prompt_tokens + completion_result - } - }) - else: - for line in response.iter_lines(): - if line: - decoded_line = line.decode("utf-8") - segment = extract_segment(decoded_line) - if segment: - buffer.write(segment) - - response_content = buffer.getvalue() - - # 计算输出token并更新统计信息 - completion_result, _ = num_tokens_from_string(response_content, model) - - # 保存对话历史并获取计算点数 - _, compute_points_used = save_conversation_history(session, cookies, session_token, conversation_id) - - # 更新统计信息 - update_model_stats(model, prompt_tokens, completion_result, calculation_method, compute_points_used) - - return jsonify({ - "id": f"chatcmpl-{str(uuid.uuid4())}", - "object": "chat.completion", - "created": int(time.time()), - "model": model, - "choices": [{ - "index": 0, - "message": { - "role": "assistant", - "content": response_content - }, - "finish_reason": "stop" - }], - "usage": { - "prompt_tokens": prompt_tokens, - "completion_tokens": completion_result, - "total_tokens": prompt_tokens + completion_result - } - }) - except requests.exceptions.RequestException as e: - error_details = str(e) - if hasattr(e, 'response') and e.response is not None: - if hasattr(e.response, 'text'): - error_details += f" - Response: {e.response.text[:200]}" - print(f"发送消息失败: {error_details}") - - # 如果是使用现有会话失败，尝试创建新会话重试一次 - if is_existing: - print("使用现有会话失败，尝试创建新会话...") - # 创建新会话 - deployment_id = "14b2a314cc" - external_app_id = model_map[model][0] if model in model_map and len(model_map[model]) >= 2 else None - - if external_app_id: - new_conversation_id = create_conversation( - session, cookies, session_token, - external_application_id=external_app_id, - deployment_id=deployment_id - ) - - if new_conversation_id: - print(f"成功创建新会话ID: {new_conversation_id}，重试请求") - # 更新全局存储的会话ID - global USER_DATA, CURRENT_USER - session, cookies, session_token, _, model_map, _ = USER_DATA[CURRENT_USER] - USER_DATA[CURRENT_USER] = (session, cookies, session_token, new_conversation_id, model_map, user_index) - - # 保存到配置文件 - update_conversation_id(user_index, new_conversation_id) - - # 修改payload使用新会话ID，并移除regenerate和editPrompt - payload["deploymentConversationId"] = new_conversation_id - if "regenerate" in payload: - del payload["regenerate"] - if "editPrompt" in payload: - del payload["editPrompt"] - - try: - # 非流式重试逻辑与流式类似，但需要重新提取响应内容 - response = session.post( - CHAT_URL, - headers=headers, - data=json.dumps(payload), - stream=True, - cookies=None - ) - - response.raise_for_status() - # 重用现有提取逻辑... - # 但这里代码重复太多，实际应该重构为共享函数 - buffer = io.StringIO() - - for line in response.iter_lines(): - if line: - decoded_line = line.decode("utf-8") - segment = extract_segment(decoded_line) - if segment: - buffer.write(segment) - - response_content = buffer.getvalue() - - # 计算输出token并更新统计信息 - completion_result, _ = num_tokens_from_string(response_content, model) - - # 保存对话历史并获取计算点数 - _, compute_points_used = save_conversation_history(session, cookies, session_token, new_conversation_id) - - # 更新统计信息 - update_model_stats(model, prompt_tokens, completion_result, calculation_method, compute_points_used) - - return jsonify({ - "id": f"chatcmpl-{str(uuid.uuid4())}", - "object": "chat.completion", - "created": int(time.time()), - "model": model, - "choices": [{ - "index": 0, - "message": { - "role": "assistant", - "content": response_content - }, - "finish_reason": "stop" - }], - "usage": { - "prompt_tokens": prompt_tokens, - "completion_tokens": completion_result, - "total_tokens": prompt_tokens + completion_result - } - }) - except Exception as retry_e: - print(f"重试失败: {retry_e}") - - return jsonify({"error": f"Failed to send message: {error_details}"}), 500 - - -def format_message(messages): - buffer = io.StringIO() - role_map, prefix, messages = extract_role(messages) - for message in messages: - role = message.get("role") - role = "\b" + role_map[role] if prefix else role_map[role] - content = message.get("content").replace("\\n", "\n") - pattern = re.compile(r"<\|removeRole\|>\n") - if pattern.match(content): - content = pattern.sub("", content) - buffer.write(f"{content}\n") - else: - buffer.write(f"{role}: {content}\n\n") - formatted_message = buffer.getvalue() - return formatted_message - - -def extract_role(messages): - role_map = {"user": "Human", "assistant": "Assistant", "system": "System"} - prefix = True # 默认添加前缀 - first_message = messages[0]["content"] - pattern = re.compile( - r""" - \s* - (?:user:\s*(?P[^\n]*)\s*)? # Make user optional - (?:assistant:\s*(?P[^\n]*)\s*)? # Make assistant optional - (?:system:\s*(?P[^\n]*)\s*)? # Make system optional - (?:prefix:\s*(?P[^\n]*)\s*)? # Make prefix optional - \n - """, - re.VERBOSE, - ) - match = pattern.search(first_message) - if match: - # 更新 role_map 如果提供了值 - user_role = match.group("user") - assistant_role = match.group("assistant") - system_role = match.group("system") - if user_role: role_map["user"] = user_role - if assistant_role: role_map["assistant"] = assistant_role - if system_role: role_map["system"] = system_role - - # 检查 prefix 值：仅当显式设置为非 "1" 时才将 prefix 设为 False - prefix_value = match.group("prefix") - if prefix_value is not None and prefix_value != "1": - prefix = False - # 如果 prefix_value 是 None (标签不存在) 或 "1", prefix 保持 True - - messages[0]["content"] = pattern.sub("", first_message) - print(f"Extracted role map:") - print( - f"User: {role_map['user']}, Assistant: {role_map['assistant']}, System: {role_map['system']}" - ) - print(f"Using prefix: {prefix}") # 打印语句保持不变，反映最终结果 - # 如果没有匹配到 ，prefix 保持默认值 True - return (role_map, prefix, messages) - - -@app.route("/health", methods=["GET"]) -def health_check(): - global health_check_counter - health_check_counter += 1 - return jsonify({ - "status": "healthy", - "timestamp": datetime.now().isoformat(), - "checks": health_check_counter - }) - - -def keep_alive(): - """每20分钟进行一次自我健康检查""" - while True: - try: - requests.get("http://127.0.0.1:7860/health") - time.sleep(1200) # 20分钟 - except: - pass # 忽略错误，保持运行 - - -@app.route("/", methods=["GET"]) -def index(): - # 如果需要密码且用户未登录，重定向到登录页面 - if PASSWORD and not flask_session.get('logged_in'): - return redirect(url_for('login')) - - # 否则重定向到仪表盘 - return redirect(url_for('dashboard')) - - -def num_tokens_from_string(string, model=""): - try: - print("\n===================== 开始计算token =====================") - print(f"模型: {model}") - print(f"输入内容长度: {len(string)} 字符") - - request_data = { - "model": model, - "messages": [{"role": "user", "content": string}] - } - print(f"发送请求到tokenizer服务: {TOKENIZER_SERVICE_URL}") - print(f"请求数据: {json.dumps(request_data, ensure_ascii=False)}") - - response = requests.post( - TOKENIZER_SERVICE_URL, - json=request_data, - timeout=10 - ) - - print(f"\nTokenizer响应状态码: {response.status_code}") - print(f"Tokenizer响应内容: {response.text}") - - if response.status_code == 200: - result = response.json() - input_tokens = result.get("input_tokens", 0) - print(f"\n成功获取token数: {input_tokens}") - print(f"使用计算方法: 精确") - print("===================== 计算完成 =====================\n") - return input_tokens, "精确" - else: - estimated_tokens = len(string) // 4 - print(f"\nTokenizer服务错误: {response.status_code}") - print(f"错误响应: {response.text}") - print(f"使用估算token数: {estimated_tokens}") - print(f"使用计算方法: 估算") - print("===================== 计算完成 =====================\n") - return estimated_tokens, "估算" - except Exception as e: - estimated_tokens = len(string) // 4 - print(f"\n计算token时发生错误: {str(e)}") - print(f"使用估算token数: {estimated_tokens}") - print(f"使用计算方法: 估算") - print("===================== 计算完成 =====================\n") - return estimated_tokens, "估算" - - -# 更新模型使用统计 -def update_model_stats(model, prompt_tokens, completion_tokens, calculation_method="estimate", compute_points=None): - global model_usage_stats, total_tokens, model_usage_records - - # 添加调用记录 - # 获取UTC时间 - utc_now = datetime.utcnow() - # 转换为北京时间 (UTC+8) - beijing_time = utc_now + timedelta(hours=8) - call_time = beijing_time.strftime('%Y-%m-%d %H:%M:%S') # 北京时间 - - record = { - "model": model, - "call_time": call_time, - "prompt_tokens": prompt_tokens, - "completion_tokens": completion_tokens, - "calculation_method": calculation_method, # 直接使用传入的值 - "compute_points": compute_points - } - model_usage_records.append(record) - - # 限制记录数量，保留最新的500条 - if len(model_usage_records) > 500: - model_usage_records.pop(0) - - # 保存调用记录到本地文件 - save_model_usage_records() - - # 更新聚合统计 - if model not in model_usage_stats: - model_usage_stats[model] = { - "count": 0, - "prompt_tokens": 0, - "completion_tokens": 0, - "total_tokens": 0 - } - - model_usage_stats[model]["count"] += 1 - model_usage_stats[model]["prompt_tokens"] += prompt_tokens - model_usage_stats[model]["completion_tokens"] += completion_tokens - model_usage_stats[model]["total_tokens"] += (prompt_tokens + completion_tokens) - - total_tokens["prompt"] += prompt_tokens - total_tokens["completion"] += completion_tokens - total_tokens["total"] += (prompt_tokens + completion_tokens) - - -# 获取计算点信息 -def get_compute_points(): - global compute_points, USER_DATA, users_compute_points - - if USER_NUM == 0: - return - - # 清空用户计算点列表 - users_compute_points = [] - - # 累计总计算点 - total_left = 0 - total_points = 0 - - # 获取每个用户的计算点信息 - for i, user_data in enumerate(USER_DATA): - try: - session, cookies, session_token, _, _, _ = user_data - - # 检查token是否有效 - if is_token_expired(session_token): - session_token = refresh_token(session, cookies) - if not session_token: - print(f"用户{i+1}刷新token失败，无法获取计算点信息") - continue - USER_DATA[i] = (session, cookies, session_token, user_data[3], user_data[4], i) - - headers = { - "accept": "application/json, text/plain, */*", - "accept-language": "zh-CN,zh;q=0.9", - "baggage": f"sentry-environment=production,sentry-release=93da8385541a6ce339b1f41b0c94428c70657e22,sentry-public_key=3476ea6df1585dd10e92cdae3a66ff49,sentry-trace_id={TRACE_ID}", - "reai-ui": "1", - "sec-ch-ua": "\"Chromium\";v=\"116\", \"Not)A;Brand\";v=\"24\", \"Google Chrome\";v=\"116\"", - "sec-ch-ua-mobile": "?0", - "sec-ch-ua-platform": "\"Windows\"", - "sec-fetch-dest": "empty", - "sec-fetch-mode": "cors", - "sec-fetch-site": "same-origin", - "sentry-trace": SENTRY_TRACE, - "session-token": session_token, - "x-abacus-org-host": "apps", - "cookie": cookies - } - - response = session.get( - COMPUTE_POINTS_URL, - headers=headers - ) - - if response.status_code == 200: - result = response.json() - if result.get("success") and "result" in result: - data = result["result"] - left = data.get("computePointsLeft", 0) - total = data.get("totalComputePoints", 0) - used = total - left - percentage = round((used / total) * 100, 2) if total > 0 else 0 - - # 获取北京时间 - beijing_now = datetime.utcnow() + timedelta(hours=8) - - # 添加到用户列表 - user_points = { - "user_id": i + 1, # 用户ID从1开始 - "left": left, - "total": total, - "used": used, - "percentage": percentage, - "last_update": beijing_now - } - users_compute_points.append(user_points) - - # 累计总数 - total_left += left - total_points += total - - print(f"用户{i+1}计算点信息更新成功: 剩余 {left}, 总计 {total}") - - # 对于第一个用户，获取计算点使用日志 - if i == 0: - get_compute_points_log(session, cookies, session_token) - else: - print(f"获取用户{i+1}计算点信息失败: {result.get('error', '未知错误')}") - else: - print(f"获取用户{i+1}计算点信息失败，状态码: {response.status_code}") - except Exception as e: - print(f"获取用户{i+1}计算点信息异常: {e}") - - # 更新全局计算点信息（所有用户总和） - if users_compute_points: - compute_points["left"] = total_left - compute_points["total"] = total_points - compute_points["used"] = total_points - total_left - compute_points["percentage"] = round((compute_points["used"] / compute_points["total"]) * 100, 2) if compute_points["total"] > 0 else 0 - compute_points["last_update"] = datetime.utcnow() + timedelta(hours=8) # 北京时间 - print(f"所有用户计算点总计: 剩余 {total_left}, 总计 {total_points}") - -# 获取计算点使用日志 -def get_compute_points_log(session, cookies, session_token): - global compute_points_log - - try: - headers = { - "accept": "application/json, text/plain, */*", - "accept-language": "zh-CN,zh;q=0.9", - "content-type": "application/json", - "reai-ui": "1", - "sec-ch-ua": "\"Chromium\";v=\"116\", \"Not)A;Brand\";v=\"24\", \"Google Chrome\";v=\"116\"", - "sec-ch-ua-mobile": "?0", - "sec-ch-ua-platform": "\"Windows\"", - "sec-fetch-dest": "empty", - "sec-fetch-mode": "cors", - "sec-fetch-site": "same-site", - "session-token": session_token, - "x-abacus-org-host": "apps", - "cookie": cookies - } - - response = session.post( - COMPUTE_POINTS_LOG_URL, - headers=headers, - json={"byLlm": True} - ) - - if response.status_code == 200: - result = response.json() - if result.get("success") and "result" in result: - data = result["result"] - compute_points_log["columns"] = data.get("columns", {}) - compute_points_log["log"] = data.get("log", []) - print(f"计算点使用日志更新成功，获取到 {len(compute_points_log['log'])} 条记录") - else: - print(f"获取计算点使用日志失败: {result.get('error', '未知错误')}") - else: - print(f"获取计算点使用日志失败，状态码: {response.status_code}") - except Exception as e: - print(f"获取计算点使用日志异常: {e}") - - -# 添加登录相关路由 -@app.route("/login", methods=["GET", "POST"]) -def login(): - error = None - if request.method == "POST": - password = request.form.get("password") - if password and hashlib.sha256(password.encode()).hexdigest() == PASSWORD: - flask_session['logged_in'] = True - flask_session.permanent = True - return redirect(url_for('dashboard')) - else: - # 密码错误时提示使用环境变量密码 - error = "密码不正确。请使用设置的环境变量 password 或 password.txt 中的值作为密码和API认证密钥。" - - # 传递空间URL给模板 - return render_template('login.html', error=error, space_url=SPACE_URL) - - -@app.route("/logout") -def logout(): - flask_session.clear() - return redirect(url_for('login')) - - -@app.route("/dashboard") -@require_auth -def dashboard(): - # 在每次访问仪表盘时更新计算点信息 - get_compute_points() - - # 计算运行时间（使用北京时间） - beijing_now = datetime.utcnow() + timedelta(hours=8) - uptime = beijing_now - START_TIME - days = uptime.days - hours, remainder = divmod(uptime.seconds, 3600) - minutes, seconds = divmod(remainder, 60) - - if days > 0: - uptime_str = f"{days}天 {hours}小时 {minutes}分钟" - elif hours > 0: - uptime_str = f"{hours}小时 {minutes}分钟" - else: - uptime_str = f"{minutes}分钟 {seconds}秒" - - # 当前北京年份 - beijing_year = beijing_now.year - - return render_template( - 'dashboard.html', - uptime=uptime_str, - health_checks=health_check_counter, - user_count=USER_NUM, - models=sorted(list(MODELS)), - year=beijing_year, - model_stats=model_usage_stats, - total_tokens=total_tokens, - compute_points=compute_points, - compute_points_log=compute_points_log, - space_url=SPACE_URL, # 传递空间URL - users_compute_points=users_compute_points, # 传递用户计算点信息 - model_usage_records=model_usage_records, # 传递模型使用记录 - ) - - -# 添加更新计算点数记录设置的路由 -@app.route("/update_compute_point_toggle", methods=["POST"]) -@require_auth -def update_compute_point_toggle(): - try: - (session, cookies, session_token, conversation_id, model_map, user_index) = get_user_data() - data = request.get_json() - if data and "always_display" in data: - headers = { - "accept": "application/json, text/plain, */*", - "accept-language": "zh-CN,zh;q=0.9", - "content-type": "application/json", - "reai-ui": "1", - "sec-ch-ua": "\"Chromium\";v=\"116\", \"Not)A;Brand\";v=\"24\", \"Google Chrome\";v=\"116\"", - "sec-ch-ua-mobile": "?0", - "sec-ch-ua-platform": "\"Windows\"", - "sec-fetch-dest": "empty", - "sec-fetch-mode": "cors", - "sec-fetch-site": "same-site", - "x-abacus-org-host": "apps" - } - - if session_token: - headers["session-token"] = session_token - - response = session.post( - COMPUTE_POINT_TOGGLE_URL, - headers=headers, - json={"alwaysDisplay": data["always_display"]}, - cookies=None - ) - - if response.status_code == 200: - result = response.json() - if result.get("success"): - print(f"更新计算点数记录设置为: {data['always_display']}") - return jsonify({"success": True}) - - return jsonify({"success": False, "error": "API调用失败"}) - else: - return jsonify({"success": False, "error": "缺少always_display参数"}) - except Exception as e: - print(f"更新计算点数记录设置失败: {e}") - return jsonify({"success": False, "error": str(e)}) - - -# 获取Hugging Face Space URL -def get_space_url(): - # 尝试从环境变量获取 - space_url = os.environ.get("SPACE_URL") - if space_url: - return space_url - - # 如果SPACE_URL不存在，尝试从SPACE_ID构建 - space_id = os.environ.get("SPACE_ID") - if space_id: - username, space_name = space_id.split("/") - # 将空间名称中的下划线替换为连字符 - # 注意：Hugging Face生成的URL会自动将空间名称中的下划线(_)替换为连字符(-) - # 例如："abacus_chat_proxy" 会变成 "abacus-chat-proxy" - space_name = space_name.replace("_", "-") - return f"https://{username}-{space_name}.hf.space" - - # 如果以上都不存在，尝试从单独的用户名和空间名构建 - username = os.environ.get("SPACE_USERNAME") - space_name = os.environ.get("SPACE_NAME") - if username and space_name: - # 将空间名称中的下划线替换为连字符 - # 同上，Hugging Face会自动进行此转换 - space_name = space_name.replace("_", "-") - return f"https://{username}-{space_name}.hf.space" - - # 默认返回None - return None - -# 获取空间URL -SPACE_URL = get_space_url() -if SPACE_URL: - print(f"Space URL: {SPACE_URL}") - print("注意：Hugging Face生成的URL会自动将空间名称中的下划线(_)替换为连字符(-)") - - -def save_conversation_history(session, cookies, session_token, conversation_id, deployment_id="14b2a314cc"): - """保存对话历史，返回使用的计算点数""" - if not conversation_id: - return False, None - - headers = { - "accept": "application/json, text/plain, */*", - "accept-language": "zh-CN,zh;q=0.9", - "baggage": f"sentry-environment=production,sentry-release=946244517de08b08598b94f18098411f5a5352d5,sentry-public_key=3476ea6df1585dd10e92cdae3a66ff49,sentry-trace_id={TRACE_ID}", - "reai-ui": "1", - "sec-ch-ua": "\"Chromium\";v=\"116\", \"Not)A;Brand\";v=\"24\", \"Google Chrome\";v=\"116\"", - "sec-ch-ua-mobile": "?0", - "sec-ch-ua-platform": "\"Windows\"", - "sec-fetch-dest": "empty", - "sec-fetch-mode": "cors", - "sec-fetch-site": "same-origin", - "sentry-trace": f"{TRACE_ID}-800cb7f4613dec52", - "x-abacus-org-host": "apps" - } - - if session_token: - headers["session-token"] = session_token - - params = { - "deploymentId": deployment_id, - "deploymentConversationId": conversation_id, - "skipDocumentBoundingBoxes": "true", - "filterIntermediateConversationEvents": "false", - "getUnusedDocumentUploads": "false" - } - - try: - response = session.get( - GET_CONVERSATION_URL, - headers=headers, - params=params, - cookies=None - ) - - if response.status_code == 200: - data = response.json() - if data.get("success"): - # 从最后一条BOT消息中获取计算点数 - history = data.get("result", {}).get("history", []) - compute_points = None - for msg in reversed(history): - if msg.get("role") == "BOT": - compute_points = msg.get("computePointsUsed") - break - print(f"成功保存对话历史: {conversation_id}, 使用计算点: {compute_points}") - return True, compute_points - else: - print(f"保存对话历史失败: {data.get('error', '未知错误')}") - else: - print(f"保存对话历史失败，状态码: {response.status_code}") - return False, None - except Exception as e: - print(f"保存对话历史时出错: {e}") - return False, None - - -if __name__ == "__main__": - # 启动保活线程 - threading.Thread(target=keep_alive, daemon=True).start() - - # 加载历史模型调用记录 - load_model_usage_records() - - # 获取初始计算点信息 - get_compute_points() - - port = int(os.environ.get("PORT", 9876)) - app.run(port=port, host="0.0.0.0") +from flask import Flask, request, jsonify, Response, render_template_string, render_template, redirect, url_for, session as flask_session +import requests +import time +import json +import uuid +import random +import io +import re +from functools import wraps +import hashlib +import jwt +import os +import threading +from datetime import datetime, timedelta + +app = Flask(__name__, template_folder='templates') +app.secret_key = os.environ.get("SECRET_KEY", "abacus_chat_proxy_secret_key") +app.config['PERMANENT_SESSION_LIFETIME'] = timedelta(days=7) + +# 添加tokenizer服务URL +TOKENIZER_SERVICE_URL = "https://malt666-tokenizer.hf.space/count_tokens" + +API_ENDPOINT_URL = "https://abacus.ai/api/v0/describeDeployment" +MODEL_LIST_URL = "https://abacus.ai/api/v0/listExternalApplications" +CHAT_URL = "https://apps.abacus.ai/api/_chatLLMSendMessageSSE" +USER_INFO_URL = "https://abacus.ai/api/v0/_getUserInfo" +COMPUTE_POINTS_URL = "https://apps.abacus.ai/api/_getOrganizationComputePoints" +COMPUTE_POINTS_LOG_URL = "https://abacus.ai/api/v0/_getOrganizationComputePointLog" +CREATE_CONVERSATION_URL = "https://apps.abacus.ai/api/createDeploymentConversation" +DELETE_CONVERSATION_URL = "https://apps.abacus.ai/api/deleteDeploymentConversation" +GET_CONVERSATION_URL = "https://apps.abacus.ai/api/getDeploymentConversation" +COMPUTE_POINT_TOGGLE_URL = "https://abacus.ai/api/v0/_updateOrganizationComputePointToggle" + + +USER_AGENTS = [ + "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/116.0.0.0 Safari/537.36" +] + + +PASSWORD = None +USER_NUM = 0 +USER_DATA = [] +CURRENT_USER = -1 +MODELS = set() + +# 添加线程锁用于保护 CURRENT_USER 的访问 +user_selection_lock = threading.Lock() + +TRACE_ID = "3042e28b3abf475d8d973c7e904935af" +SENTRY_TRACE = f"{TRACE_ID}-80d9d2538b2682d0" + + +# 添加一个计数器记录健康检查次数 +health_check_counter = 0 + + +# 添加统计变量 +model_usage_stats = {} # 模型使用次数统计 +total_tokens = { + "prompt": 0, # 输入token统计 + "completion": 0, # 输出token统计 + "total": 0 # 总token统计 +} + +# 模型调用记录 +model_usage_records = [] # 每次调用详细记录 +MODEL_USAGE_RECORDS_FILE = "model_usage_records.json" # 调用记录保存文件 + +# 计算点信息 +compute_points = { + "left": 0, # 剩余计算点 + "total": 0, # 总计算点 + "used": 0, # 已使用计算点 + "percentage": 0, # 使用百分比 + "last_update": None # 最后更新时间 +} + +# 计算点使用日志 +compute_points_log = { + "columns": {}, # 列名 + "log": [] # 日志数据 +} + +# 多用户计算点信息 +users_compute_points = [] + +# 记录启动时间 +START_TIME = datetime.utcnow() + timedelta(hours=8) # 北京时间 + + +# 自定义JSON编码器，处理datetime对象 +class DateTimeEncoder(json.JSONEncoder): + def default(self, obj): + if isinstance(obj, datetime): + return obj.strftime('%Y-%m-%d %H:%M:%S') + return super(DateTimeEncoder, self).default(obj) + + +# 加载模型调用记录 +def load_model_usage_records(): + global model_usage_records + try: + if os.path.exists(MODEL_USAGE_RECORDS_FILE): + with open(MODEL_USAGE_RECORDS_FILE, 'r', encoding='utf-8') as f: + records = json.load(f) + if isinstance(records, list): + model_usage_records = records + print(f"成功加载 {len(model_usage_records)} 条模型调用记录") + else: + print("调用记录文件格式不正确，初始化为空列表") + except Exception as e: + print(f"加载模型调用记录失败: {e}") + model_usage_records = [] + +# 保存模型调用记录 +def save_model_usage_records(): + try: + with open(MODEL_USAGE_RECORDS_FILE, 'w', encoding='utf-8') as f: + json.dump(model_usage_records, f, ensure_ascii=False, indent=2, cls=DateTimeEncoder) + print(f"成功保存 {len(model_usage_records)} 条模型调用记录") + except Exception as e: + print(f"保存模型调用记录失败: {e}") + + +def update_conversation_id(user_index, conversation_id): + """更新用户的conversation_id并保存到配置文件""" + try: + with open("config.json", "r") as f: + config = json.load(f) + + if "config" in config and user_index < len(config["config"]): + config["config"][user_index]["conversation_id"] = conversation_id + + # 保存到配置文件 + with open("config.json", "w") as f: + json.dump(config, f, indent=4) + + print(f"已将用户 {user_index+1} 的conversation_id更新为: {conversation_id}") + else: + print(f"更新conversation_id失败: 配置文件格式错误或用户索引越界") + except Exception as e: + print(f"更新conversation_id失败: {e}") + + +def resolve_config(): + # 从环境变量读取多组配置 + config_list = [] + i = 1 + while True: + cookie = os.environ.get(f"cookie_{i}") + if not cookie: + break + + # 为每个cookie创建一个配置项，conversation_id初始为空 + config_list.append({ + "conversation_id": "", # 初始为空，将通过get_or_create_conversation自动创建 + "cookies": cookie + }) + i += 1 + + # 如果环境变量存在配置，使用环境变量的配置 + if config_list: + print(f"从环境变量加载了 {len(config_list)} 个配置") + return config_list + + # 如果环境变量不存在，从文件读取 + try: + with open("config.json", "r") as f: + config = json.load(f) + config_list = config.get("config") + return config_list + except FileNotFoundError: + print("未找到config.json文件") + return [] + except json.JSONDecodeError: + print("config.json格式错误") + return [] + + +def get_password(): + global PASSWORD + # 从环境变量读取密码 + env_password = os.environ.get("password") + if env_password: + PASSWORD = hashlib.sha256(env_password.encode()).hexdigest() + return + + # 如果环境变量不存在，从文件读取 + try: + with open("password.txt", "r") as f: + PASSWORD = f.read().strip() + except FileNotFoundError: + with open("password.txt", "w") as f: + PASSWORD = None + + +def require_auth(f): + @wraps(f) + def decorated(*args, **kwargs): + if not PASSWORD: + return f(*args, **kwargs) + + # 检查Flask会话是否已登录 + if flask_session.get('logged_in'): + return f(*args, **kwargs) + + # 如果是API请求，检查Authorization头 + auth = request.authorization + if not auth or not check_auth(auth.token): + # 如果是浏览器请求，重定向到登录页面 + if request.headers.get('Accept', '').find('text/html') >= 0: + return redirect(url_for('login')) + return jsonify({"error": "Unauthorized access"}), 401 + return f(*args, **kwargs) + + return decorated + + +def check_auth(token): + return hashlib.sha256(token.encode()).hexdigest() == PASSWORD + + +def is_token_expired(token): + if not token: + return True + + try: + # Malkodi tokenon sen validigo de subskribo + payload = jwt.decode(token, options={"verify_signature": False}) + # Akiru eksvalidiĝan tempon, konsideru eksvalidiĝinta 5 minutojn antaŭe + return payload.get('exp', 0) - time.time() < 300 + except: + return True + + +def refresh_token(session, cookies): + """Uzu kuketon por refreŝigi session token, nur revenigu novan tokenon""" + headers = { + "accept": "application/json, text/plain, */*", + "accept-language": "zh-CN,zh;q=0.9", + "content-type": "application/json", + "reai-ui": "1", + "sec-ch-ua": "\"Chromium\";v=\"116\", \"Not)A;Brand\";v=\"24\", \"Google Chrome\";v=\"116\"", + "sec-ch-ua-mobile": "?0", + "sec-ch-ua-platform": "\"Windows\"", + "sec-fetch-dest": "empty", + "sec-fetch-mode": "cors", + "sec-fetch-site": "same-site", + "x-abacus-org-host": "apps", + "user-agent": random.choice(USER_AGENTS), + "origin": "https://apps.abacus.ai", + "referer": "https://apps.abacus.ai/", + "cookie": cookies + } + + try: + response = session.post( + USER_INFO_URL, + headers=headers, + json={}, + cookies=None + ) + + if response.status_code == 200: + response_data = response.json() + if response_data.get('success') and 'sessionToken' in response_data.get('result', {}): + return response_data['result']['sessionToken'] + else: + print(f"刷新token失败: {response_data.get('error', '未知错误')}") + return None + else: + print(f"刷新token失败，状态码: {response.status_code}") + return None + except Exception as e: + print(f"刷新token异常: {e}") + return None + + +def get_model_map(session, cookies, session_token): + """Akiru disponeblan modelan liston kaj ĝiajn mapajn rilatojn""" + headers = { + "accept": "application/json, text/plain, */*", + "accept-language": "zh-CN,zh;q=0.9", + "content-type": "application/json", + "reai-ui": "1", + "sec-ch-ua": "\"Chromium\";v=\"116\", \"Not)A;Brand\";v=\"24\", \"Google Chrome\";v=\"116\"", + "sec-ch-ua-mobile": "?0", + "sec-ch-ua-platform": "\"Windows\"", + "sec-fetch-dest": "empty", + "sec-fetch-mode": "cors", + "sec-fetch-site": "same-site", + "x-abacus-org-host": "apps", + "user-agent": random.choice(USER_AGENTS), + "origin": "https://apps.abacus.ai", + "referer": "https://apps.abacus.ai/", + "cookie": cookies + } + + if session_token: + headers["session-token"] = session_token + + model_map = {} + models_set = set() + + try: + response = session.post( + MODEL_LIST_URL, + headers=headers, + json={}, + cookies=None + ) + + if response.status_code != 200: + print(f"获取模型列表失败，状态码: {response.status_code}") + raise Exception("API请求失败") + + data = response.json() + if not data.get('success'): + print(f"获取模型列表失败: {data.get('error', '未知错误')}") + raise Exception("API返回错误") + + applications = [] + if isinstance(data.get('result'), dict): + applications = data.get('result', {}).get('externalApplications', []) + elif isinstance(data.get('result'), list): + applications = data.get('result', []) + + for app in applications: + app_name = app.get('name', '') + app_id = app.get('externalApplicationId', '') + prediction_overrides = app.get('predictionOverrides', {}) + llm_name = prediction_overrides.get('llmName', '') if prediction_overrides else '' + + if not (app_name and app_id and llm_name): + continue + + model_name = app_name + model_map[model_name] = (app_id, llm_name) + models_set.add(model_name) + + if not model_map: + raise Exception("未找到任何可用模型") + + return model_map, models_set + + except Exception as e: + print(f"获取模型列表异常: {e}") + raise + + +def init_session(): + get_password() + global USER_NUM, MODELS, USER_DATA + + config_list = resolve_config() + user_num = len(config_list) + all_models = set() + + for i in range(user_num): + user = config_list[i] + cookies = user.get("cookies") + conversation_id = user.get("conversation_id") + session = requests.Session() + + session_token = refresh_token(session, cookies) + if not session_token: + print(f"无法获取cookie {i+1}的token") + continue + + try: + model_map, models_set = get_model_map(session, cookies, session_token) + all_models.update(models_set) + USER_DATA.append((session, cookies, session_token, conversation_id, model_map, i)) + + # 对第一个成功配置的用户，初始化计算点数记录功能 + if i == 0: + try: + headers = { + "accept": "application/json, text/plain, */*", + "accept-language": "zh-CN,zh;q=0.9", + "content-type": "application/json", + "reai-ui": "1", + "sec-ch-ua": "\"Chromium\";v=\"116\", \"Not)A;Brand\";v=\"24\", \"Google Chrome\";v=\"116\"", + "sec-ch-ua-mobile": "?0", + "sec-ch-ua-platform": "\"Windows\"", + "sec-fetch-dest": "empty", + "sec-fetch-mode": "cors", + "sec-fetch-site": "same-site", + "x-abacus-org-host": "apps", + "session-token": session_token + } + + response = session.post( + COMPUTE_POINT_TOGGLE_URL, + headers=headers, + json={"alwaysDisplay": True}, + cookies=None + ) + + if response.status_code == 200: + result = response.json() + if result.get("success"): + print("成功初始化计算点数记录功能为开启状态") + else: + print(f"初始化计算点数记录功能失败: {result.get('error', '未知错误')}") + else: + print(f"初始化计算点数记录功能失败，状态码: {response.status_code}") + except Exception as e: + print(f"初始化计算点数记录功能时出错: {e}") + except Exception as e: + print(f"配置用户 {i+1} 失败: {e}") + continue + + USER_NUM = len(USER_DATA) + if USER_NUM == 0: + print("No user available, exiting...") + exit(1) + + MODELS = all_models + print(f"启动完成，共配置 {USER_NUM} 个用户") + + +def update_cookie(session, cookies): + cookie_jar = {} + for key, value in session.cookies.items(): + cookie_jar[key] = value + cookie_dict = {} + for item in cookies.split(";"): + key, value = item.strip().split("=", 1) + cookie_dict[key] = value + cookie_dict.update(cookie_jar) + cookies = "; ".join([f"{key}={value}" for key, value in cookie_dict.items()]) + return cookies + + +user_data = init_session() + + +@app.route("/v1/models", methods=["GET"]) +@require_auth +def get_models(): + if len(MODELS) == 0: + return jsonify({"error": "No models available"}), 500 + model_list = [] + for model in MODELS: + model_list.append( + { + "id": model, + "object": "model", + "created": int(time.time()), + "owned_by": "Elbert", + "name": model, + } + ) + return jsonify({"object": "list", "data": model_list}) + + +@app.route("/v1/chat/completions", methods=["POST"]) +@require_auth +def chat_completions(): + openai_request = request.get_json() + stream = openai_request.get("stream", False) + messages = openai_request.get("messages") + if messages is None: + return jsonify({"error": "Messages is required", "status": 400}), 400 + model = openai_request.get("model") + if model not in MODELS: + return ( + jsonify( + { + "error": "Model not available, check if it is configured properly", + "status": 404, + } + ), + 404, + ) + message = format_message(messages) + think = ( + openai_request.get("think", False) if model == "Claude Sonnet 3.7" else False + ) + return ( + send_message(message, model, think) + if stream + else send_message_non_stream(message, model, think) + ) + + +def get_user_data(): + global CURRENT_USER + + # 使用锁确保线程安全 + with user_selection_lock: + CURRENT_USER = (CURRENT_USER + 1) % USER_NUM + current_user_index_local = CURRENT_USER # 本地副本，避免锁外访问全局变量 + print(f"使用配置 {current_user_index_local+1}") + + # Akiru uzantajn datumojn (使用本地索引) + session, cookies, session_token, conversation_id, model_map, user_index = USER_DATA[current_user_index_local] + + # Kontrolu ĉu la tokeno eksvalidiĝis, se jes, refreŝigu ĝin + if is_token_expired(session_token): + print(f"Cookie {current_user_index_local+1}的token已过期或即将过期，正在刷新...") + new_token = refresh_token(session, cookies) + if new_token: + # Ĝisdatigu la globale konservitan tokenon (加锁保护写入) + with user_selection_lock: + # 重新获取最新的 USER_DATA 状态再更新 + _session, _cookies, _, _conv_id, _model_map, _user_idx = USER_DATA[current_user_index_local] + USER_DATA[current_user_index_local] = (_session, _cookies, new_token, _conv_id, _model_map, _user_idx) + session_token = new_token # 更新函数内部使用的token + print(f"成功更新token: {session_token[:15]}...{session_token[-15:]}") + else: + print(f"警告：无法刷新Cookie {current_user_index_local+1}的token，继续使用当前token") + + # 返回获取到的数据 (使用本地索引) + return (session, cookies, session_token, conversation_id, model_map, user_index) + + +def create_conversation(session, cookies, session_token, external_application_id=None, deployment_id=None): + """创建新的会话""" + if not (external_application_id and deployment_id): + print("无法创建新会话: 缺少必要参数") + return None + + headers = { + "accept": "application/json, text/plain, */*", + "accept-language": "zh-CN,zh;q=0.9", + "content-type": "application/json", + "cookie": cookies, + "user-agent": random.choice(USER_AGENTS), + "x-abacus-org-host": "apps" + } + + if session_token: + headers["session-token"] = session_token + + create_payload = { + "deploymentId": deployment_id, + "name": "New Chat", + "externalApplicationId": external_application_id + } + + try: + response = session.post( + CREATE_CONVERSATION_URL, + headers=headers, + json=create_payload + ) + + if response.status_code == 200: + data = response.json() + if data.get("success", False): + new_conversation_id = data.get("result", {}).get("deploymentConversationId") + if new_conversation_id: + print(f"成功创建新的conversation: {new_conversation_id}") + return new_conversation_id + + print(f"创建会话失败: {response.status_code} - {response.text[:100]}") + return None + except Exception as e: + print(f"创建会话时出错: {e}") + return None + + +def delete_conversation(session, cookies, session_token, conversation_id, deployment_id="14b2a314cc"): + """删除指定的对话""" + if not conversation_id: + print("无法删除对话: 缺少conversation_id") + return False + + headers = { + "accept": "application/json, text/plain, */*", + "accept-language": "zh-CN,zh;q=0.9", + "content-type": "application/json", + "cookie": cookies, + "user-agent": random.choice(USER_AGENTS), + "x-abacus-org-host": "apps" + } + + if session_token: + headers["session-token"] = session_token + + delete_payload = { + "deploymentId": deployment_id, + "deploymentConversationId": conversation_id + } + + try: + response = session.post( + DELETE_CONVERSATION_URL, + headers=headers, + json=delete_payload + ) + + if response.status_code == 200: + data = response.json() + if data.get("success", False): + print(f"成功删除对话: {conversation_id}") + return True + + print(f"删除对话失败: {response.status_code} - {response.text[:100]}") + return False + except Exception as e: + print(f"删除对话时出错: {e}") + return False + + +def get_or_create_conversation(session, cookies, session_token, conversation_id, model_map, model, user_index): + """获取对话ID，如果不存在则创建；返回是否是使用现有会话""" + print(f"\n----- 获取会话ID (用户 {user_index+1}) -----") + # 如果有现有的会话ID，直接使用 + if conversation_id: + print(f"使用现有会话ID: {conversation_id}") + return conversation_id, True + + # 如果没有会话ID，创建新的 + print("没有会话ID，创建新会话...") + deployment_id = "14b2a314cc" + + # 确保模型信息存在 + if model not in model_map or len(model_map[model]) < 2: + print(f"错误: 无法获取模型 {model} 的信息") + return None, False + + external_app_id = model_map[model][0] + + # 创建新会话 + new_conversation_id = create_conversation( + session, cookies, session_token, + external_application_id=external_app_id, + deployment_id=deployment_id + ) + + if new_conversation_id: + print(f"成功创建新会话ID: {new_conversation_id}") + + # 更新全局存储的会话ID + global USER_DATA, CURRENT_USER + session, cookies, session_token, _, model_map, _ = USER_DATA[CURRENT_USER] + USER_DATA[CURRENT_USER] = (session, cookies, session_token, new_conversation_id, model_map, user_index) + + # 保存到配置文件 + update_conversation_id(user_index, new_conversation_id) + + return new_conversation_id, False + + print("创建新会话失败") + return None, False + + +def generate_trace_id(): + """Generu novan trace_id kaj sentry_trace""" + trace_id = str(uuid.uuid4()).replace('-', '') + sentry_trace = f"{trace_id}-{str(uuid.uuid4())[:16]}" + return trace_id, sentry_trace + + +def send_message(message, model, think=False): + """Flua traktado kaj plusendo de mesaĝoj""" + print("\n===== 开始处理消息 =====") + print(f"模型: {model}") + print(f"思考模式: {think}") + + (session, cookies, session_token, conversation_id, model_map, user_index) = get_user_data() + print(f"使用用户配置: {user_index + 1}") + + # 获取会话ID，并判断是否使用现有会话 + conversation_id, is_existing = get_or_create_conversation( + session, cookies, session_token, conversation_id, model_map, model, user_index + ) + + # 如果没有有效的会话ID，返回错误 + if not conversation_id: + return jsonify({"error": "Failed to get a valid conversation ID"}), 500 + + print(f"会话ID: {conversation_id} (是否为现有会话: {is_existing})") + + trace_id, sentry_trace = generate_trace_id() + + # 计算输入token + completion_buffer = io.StringIO() # 收集所有输出用于计算token + + headers = { + "accept": "text/event-stream", + "accept-language": "zh-CN,zh;q=0.9", + "baggage": f"sentry-environment=production,sentry-release=975eec6685013679c139fc88db2c48e123d5c604,sentry-public_key=3476ea6df1585dd10e92cdae3a66ff49,sentry-trace_id={trace_id}", + "content-type": "text/plain;charset=UTF-8", + "cookie": cookies, + "sec-ch-ua": "\"Chromium\";v=\"116\", \"Not)A;Brand\";v=\"24\", \"Google Chrome\";v=\"116\"", + "sec-ch-ua-mobile": "?0", + "sec-ch-ua-platform": "\"Windows\"", + "sec-fetch-dest": "empty", + "sec-fetch-mode": "cors", + "sec-fetch-site": "same-origin", + "sentry-trace": sentry_trace, + "user-agent": random.choice(USER_AGENTS), + "x-abacus-org-host": "apps" + } + + if session_token: + headers["session-token"] = session_token + + # 构建基础请求 + payload = { + "requestId": str(uuid.uuid4()), + "deploymentConversationId": conversation_id, + "message": message, + "isDesktop": False, + "chatConfig": { + "timezone": "Asia/Shanghai", + "language": "zh-CN" + }, + "llmName": model_map[model][1], + "externalApplicationId": model_map[model][0] + } + + # 如果是使用现有会话，添加regenerate和editPrompt参数 + if is_existing: + payload["regenerate"] = True + payload["editPrompt"] = True + print("为现有会话添加 regenerate=True 和 editPrompt=True") + + if think: + payload["useThinking"] = think + + try: + response = session.post( + CHAT_URL, + headers=headers, + data=json.dumps(payload), + stream=True, + cookies=None + ) + + response.raise_for_status() + + def extract_segment(line_data): + try: + data = json.loads(line_data) + if "segment" in data: + if isinstance(data["segment"], str): + return data["segment"] + elif isinstance(data["segment"], dict) and "segment" in data["segment"]: + return data["segment"]["segment"] + return "" + except: + return "" + + def generate(): + id = "" + think_state = 2 + + yield "data: " + json.dumps({"object": "chat.completion.chunk", "choices": [{"delta": {"role": "assistant"}}]}) + "\n\n" + + for line in response.iter_lines(): + if line: + decoded_line = line.decode("utf-8") + try: + if think: + data = json.loads(decoded_line) + if data.get("type") != "text": + continue + elif think_state == 2: + id = data.get("messageId") + segment = "\n" + data.get("segment", "") + completion_buffer.write(segment) # 收集输出 + yield f"data: {json.dumps({'object': 'chat.completion.chunk', 'choices': [{'delta': {'content': segment}}]})}\n\n" + think_state = 1 + elif think_state == 1: + if data.get("messageId") != id: + segment = data.get("segment", "") + completion_buffer.write(segment) + yield f"data: {json.dumps({'object': 'chat.completion.chunk', 'choices': [{'delta': {'content': segment}}]})}\n\n" + else: + segment = "\n\n" + data.get("segment", "") + completion_buffer.write(segment) + yield f"data: {json.dumps({'object': 'chat.completion.chunk', 'choices': [{'delta': {'content': segment}}]})}\n\n" + think_state = 0 + else: + segment = data.get("segment", "") + completion_buffer.write(segment) + yield f"data: {json.dumps({'object': 'chat.completion.chunk', 'choices': [{'delta': {'content': segment}}]})}\n\n" + else: + segment = extract_segment(decoded_line) + if segment: + completion_buffer.write(segment) + yield f"data: {json.dumps({'object': 'chat.completion.chunk', 'choices': [{'delta': {'content': segment}}]})}\n\n" + except Exception as e: + print(f"处理响应出错: {e}") + + # ---- Token 计算移到这里 ---- + print("\n----- 计算 Tokens (流式结束后) -----") + prompt_tokens, calculation_method = num_tokens_from_string(message, model) + print(f"输入 token 数: {prompt_tokens} (方法: {calculation_method})") + + completion_content = completion_buffer.getvalue() + completion_tokens, comp_calc_method = num_tokens_from_string(completion_content, model) + print(f"输出 token 数: {completion_tokens} (方法: {comp_calc_method})") + + # 决定最终使用的计算方法 (优先使用精确) + final_calculation_method = "精确" if calculation_method == "精确" and comp_calc_method == "精确" else "估算" + # ---- Token 计算结束 ---- + + yield "data: " + json.dumps({"object": "chat.completion.chunk", "choices": [{"delta": {}, "finish_reason": "stop"}]}) + "\n\n" + yield "data: [DONE]\n\n" + + # 在流式传输完成后计算token并更新统计 + # 注意: 如果客户端在流结束前断开连接，这里的 completion_content 可能不完整， + # 导致 completion_tokens 和 total_tokens 的本地记录不准确。 + # 但 Abacus 的计算点数扣除通常在其服务端完成，不受此影响。 + + # 保存对话历史并获取计算点数 + _, compute_points_used = save_conversation_history(session, cookies, session_token, conversation_id) + + # 更新统计信息 + update_model_stats(model, prompt_tokens, completion_tokens, final_calculation_method, compute_points_used) + + return Response(generate(), mimetype="text/event-stream") + except requests.exceptions.RequestException as e: + error_details = str(e) + if hasattr(e, 'response') and e.response is not None: + if hasattr(e.response, 'text'): + error_details += f" - Response: {e.response.text[:200]}" + print(f"发送消息失败: {error_details}") + + # 如果是使用现有会话失败，尝试创建新会话重试一次 + if is_existing: + print("使用现有会话失败，尝试创建新会话...") + # 创建新会话 + deployment_id = "14b2a314cc" + external_app_id = model_map[model][0] if model in model_map and len(model_map[model]) >= 2 else None + + if external_app_id: + new_conversation_id = create_conversation( + session, cookies, session_token, + external_application_id=external_app_id, + deployment_id=deployment_id + ) + + if new_conversation_id: + print(f"成功创建新会话ID: {new_conversation_id}，重试请求") + # 更新全局存储的会话ID + global USER_DATA, CURRENT_USER + session, cookies, session_token, _, model_map, _ = USER_DATA[CURRENT_USER] + USER_DATA[CURRENT_USER] = (session, cookies, session_token, new_conversation_id, model_map, user_index) + + # 保存到配置文件 + update_conversation_id(user_index, new_conversation_id) + + # 修改payload使用新会话ID，并移除regenerate和editPrompt + payload["deploymentConversationId"] = new_conversation_id + if "regenerate" in payload: + del payload["regenerate"] + if "editPrompt" in payload: + del payload["editPrompt"] + + try: + # 非流式重试逻辑与流式类似，但需要重新提取响应内容 + response = session.post( + CHAT_URL, + headers=headers, + data=json.dumps(payload), + stream=True, + cookies=None + ) + + response.raise_for_status() + # 重用现有提取逻辑... + # 但这里代码重复太多，实际应该重构为共享函数 + buffer = io.StringIO() + + for line in response.iter_lines(): + if line: + decoded_line = line.decode("utf-8") + segment = extract_segment(decoded_line) + if segment: + buffer.write(segment) + + response_content = buffer.getvalue() + + # ---- 重试逻辑中的 Token 计算 ---- + print("\n----- 计算 Tokens (重试成功后) -----") + prompt_tokens, calculation_method = num_tokens_from_string(message, model) + print(f"输入 token 数: {prompt_tokens} (方法: {calculation_method})") + + # 计算输出token并更新统计信息 + completion_tokens, comp_calc_method = num_tokens_from_string(response_content, model) + print(f"输出 token 数: {completion_tokens} (方法: {comp_calc_method})") + + # 决定最终使用的计算方法 + final_calculation_method = "精确" if calculation_method == "精确" and comp_calc_method == "精确" else "估算" + # ---- Token 计算结束 ---- + + # 保存对话历史并获取计算点数 + _, compute_points_used = save_conversation_history(session, cookies, session_token, new_conversation_id) + + # 更新统计信息 + # 注意: 重试逻辑。Token 计算准确性依赖于 response 完整性。 + update_model_stats(model, prompt_tokens, completion_tokens, final_calculation_method, compute_points_used) + + return jsonify({ + "id": f"chatcmpl-{str(uuid.uuid4())}", + "object": "chat.completion", + "created": int(time.time()), + "model": model, + "choices": [{ + "index": 0, + "message": { + "role": "assistant", + "content": response_content + }, + "finish_reason": "stop" + }], + "usage": { + "prompt_tokens": prompt_tokens, + "completion_tokens": completion_tokens, + "total_tokens": prompt_tokens + completion_tokens + } + }) + except Exception as retry_e: + print(f"重试失败: {retry_e}") + + return jsonify({"error": f"Failed to send message: {error_details}"}), 500 + + +def send_message_non_stream(message, model, think=False): + """Ne-flua traktado de mesaĝoj""" + print("\n===== 开始处理消息（非流式） =====") + print(f"模型: {model}") + print(f"思考模式: {think}") + + (session, cookies, session_token, conversation_id, model_map, user_index) = get_user_data() + print(f"使用用户配置: {user_index + 1}") + + # 获取会话ID，并判断是否使用现有会话 + conversation_id, is_existing = get_or_create_conversation( + session, cookies, session_token, conversation_id, model_map, model, user_index + ) + + # 如果没有有效的会话ID，返回错误 + if not conversation_id: + return jsonify({"error": "Failed to get a valid conversation ID"}), 500 + + print(f"会话ID: {conversation_id} (是否为现有会话: {is_existing})") + + trace_id, sentry_trace = generate_trace_id() + + headers = { + "accept": "text/event-stream", + "accept-language": "zh-CN,zh;q=0.9", + "baggage": f"sentry-environment=production,sentry-release=975eec6685013679c139fc88db2c48e123d5c604,sentry-public_key=3476ea6df1585dd10e92cdae3a66ff49,sentry-trace_id={trace_id}", + "content-type": "text/plain;charset=UTF-8", + "cookie": cookies, + "sec-ch-ua": "\"Chromium\";v=\"116\", \"Not)A;Brand\";v=\"24\", \"Google Chrome\";v=\"116\"", + "sec-ch-ua-mobile": "?0", + "sec-ch-ua-platform": "\"Windows\"", + "sec-fetch-dest": "empty", + "sec-fetch-mode": "cors", + "sec-fetch-site": "same-origin", + "sentry-trace": sentry_trace, + "user-agent": random.choice(USER_AGENTS), + "x-abacus-org-host": "apps" + } + + if session_token: + headers["session-token"] = session_token + + # 构建基础请求 + payload = { + "requestId": str(uuid.uuid4()), + "deploymentConversationId": conversation_id, + "message": message, + "isDesktop": False, + "chatConfig": { + "timezone": "Asia/Shanghai", + "language": "zh-CN" + }, + "llmName": model_map[model][1], + "externalApplicationId": model_map[model][0] + } + + # 如果是使用现有会话，添加regenerate和editPrompt参数 + if is_existing: + payload["regenerate"] = True + payload["editPrompt"] = True + print("为现有会话添加 regenerate=True 和 editPrompt=True") + + if think: + payload["useThinking"] = think + + try: + response = session.post( + CHAT_URL, + headers=headers, + data=json.dumps(payload), + stream=True, + cookies=None + ) + + response.raise_for_status() + buffer = io.StringIO() + + def extract_segment(line_data): + try: + data = json.loads(line_data) + if "segment" in data: + if isinstance(data["segment"], str): + return data["segment"] + elif isinstance(data["segment"], dict) and "segment" in data["segment"]: + return data["segment"]["segment"] + return "" + except: + return "" + + if think: + id = "" + think_state = 2 + think_buffer = io.StringIO() + content_buffer = io.StringIO() + + for line in response.iter_lines(): + if line: + decoded_line = line.decode("utf-8") + try: + data = json.loads(decoded_line) + if data.get("type") != "text": + continue + elif think_state == 2: + id = data.get("messageId") + segment = data.get("segment", "") + think_buffer.write(segment) + think_state = 1 + elif think_state == 1: + if data.get("messageId") != id: + segment = data.get("segment", "") + content_buffer.write(segment) + else: + segment = data.get("segment", "") + think_buffer.write(segment) + think_state = 0 + else: + segment = data.get("segment", "") + content_buffer.write(segment) + except Exception as e: + print(f"处理响应出错: {e}") + + think_content = think_buffer.getvalue() + response_content = content_buffer.getvalue() + + # ---- Token 计算移到这里 ---- + print("\n----- 计算 Tokens (非流式, think模式) -----") + prompt_tokens, calculation_method = num_tokens_from_string(message, model) + print(f"输入 token 数: {prompt_tokens} (方法: {calculation_method})") + # 计算输出token并更新统计信息 + completion_tokens, comp_calc_method = num_tokens_from_string(think_content + response_content, model) + print(f"输出 token 数: {completion_tokens} (方法: {comp_calc_method})") + # 决定最终使用的计算方法 + final_calculation_method = "精确" if calculation_method == "精确" and comp_calc_method == "精确" else "估算" + # ---- Token 计算结束 ---- + + # 保存对话历史并获取计算点数 + _, compute_points_used = save_conversation_history(session, cookies, session_token, conversation_id) + + # 更新统计信息 + # 注意: 如果客户端在请求完成前断开连接（理论上非流式不太可能，但网络异常可能发生）， + # Token 计算的准确性取决于 response 是否完整接收。Abacus 点数扣除不受影响。 + update_model_stats(model, prompt_tokens, completion_tokens, final_calculation_method, compute_points_used) + + return jsonify({ + "id": f"chatcmpl-{str(uuid.uuid4())}", + "object": "chat.completion", + "created": int(time.time()), + "model": model, + "choices": [{ + "index": 0, + "message": { + "role": "assistant", + "content": f"\n{think_content}\n\n{response_content}" + }, + "finish_reason": "stop" + }], + "usage": { + "prompt_tokens": prompt_tokens, + "completion_tokens": completion_tokens, + "total_tokens": prompt_tokens + completion_tokens + } + }) + else: + for line in response.iter_lines(): + if line: + decoded_line = line.decode("utf-8") + segment = extract_segment(decoded_line) + if segment: + buffer.write(segment) + + response_content = buffer.getvalue() + + # ---- Token 计算移到这里 ---- + print("\n----- 计算 Tokens (非流式) -----") + prompt_tokens, calculation_method = num_tokens_from_string(message, model) + print(f"输入 token 数: {prompt_tokens} (方法: {calculation_method})") + # 计算输出token并更新统计信息 + completion_tokens, comp_calc_method = num_tokens_from_string(response_content, model) + print(f"输出 token 数: {completion_tokens} (方法: {comp_calc_method})") + # 决定最终使用的计算方法 + final_calculation_method = "精确" if calculation_method == "精确" and comp_calc_method == "精确" else "估算" + # ---- Token 计算结束 ---- + + # 保存对话历史并获取计算点数 + _, compute_points_used = save_conversation_history(session, cookies, session_token, conversation_id) + + # 更新统计信息 + # 注意: 如果客户端在请求完成前断开连接（理论上非流式不太可能，但网络异常可能发生）， + # Token 计算的准确性取决于 response 是否完整接收。Abacus 点数扣除不受影响。 + update_model_stats(model, prompt_tokens, completion_tokens, final_calculation_method, compute_points_used) + + return jsonify({ + "id": f"chatcmpl-{str(uuid.uuid4())}", + "object": "chat.completion", + "created": int(time.time()), + "model": model, + "choices": [{ + "index": 0, + "message": { + "role": "assistant", + "content": response_content + }, + "finish_reason": "stop" + }], + "usage": { + "prompt_tokens": prompt_tokens, + "completion_tokens": completion_tokens, + "total_tokens": prompt_tokens + completion_tokens + } + }) + except requests.exceptions.RequestException as e: + error_details = str(e) + if hasattr(e, 'response') and e.response is not None: + if hasattr(e.response, 'text'): + error_details += f" - Response: {e.response.text[:200]}" + print(f"发送消息失败: {error_details}") + + # 如果是使用现有会话失败，尝试创建新会话重试一次 + if is_existing: + print("使用现有会话失败，尝试创建新会话...") + # 创建新会话 + deployment_id = "14b2a314cc" + external_app_id = model_map[model][0] if model in model_map and len(model_map[model]) >= 2 else None + + if external_app_id: + new_conversation_id = create_conversation( + session, cookies, session_token, + external_application_id=external_app_id, + deployment_id=deployment_id + ) + + if new_conversation_id: + print(f"成功创建新会话ID: {new_conversation_id}，重试请求") + # 更新全局存储的会话ID + global USER_DATA, CURRENT_USER + session, cookies, session_token, _, model_map, _ = USER_DATA[CURRENT_USER] + USER_DATA[CURRENT_USER] = (session, cookies, session_token, new_conversation_id, model_map, user_index) + + # 保存到配置文件 + update_conversation_id(user_index, new_conversation_id) + + # 修改payload使用新会话ID，并移除regenerate和editPrompt + payload["deploymentConversationId"] = new_conversation_id + if "regenerate" in payload: + del payload["regenerate"] + if "editPrompt" in payload: + del payload["editPrompt"] + + try: + # 非流式重试逻辑与流式类似，但需要重新提取响应内容 + response = session.post( + CHAT_URL, + headers=headers, + data=json.dumps(payload), + stream=True, + cookies=None + ) + + response.raise_for_status() + # 重用现有提取逻辑... + # 但这里代码重复太多，实际应该重构为共享函数 + buffer = io.StringIO() + + for line in response.iter_lines(): + if line: + decoded_line = line.decode("utf-8") + segment = extract_segment(decoded_line) + if segment: + buffer.write(segment) + + response_content = buffer.getvalue() + + # ---- 重试逻辑中的 Token 计算 ---- + print("\n----- 计算 Tokens (重试成功后) -----") + prompt_tokens, calculation_method = num_tokens_from_string(message, model) + print(f"输入 token 数: {prompt_tokens} (方法: {calculation_method})") + + # 计算输出token并更新统计信息 + completion_tokens, comp_calc_method = num_tokens_from_string(response_content, model) + print(f"输出 token 数: {completion_tokens} (方法: {comp_calc_method})") + + # 决定最终使用的计算方法 + final_calculation_method = "精确" if calculation_method == "精确" and comp_calc_method == "精确" else "估算" + # ---- Token 计算结束 ---- + + # 保存对话历史并获取计算点数 + _, compute_points_used = save_conversation_history(session, cookies, session_token, new_conversation_id) + + # 更新统计信息 + # 注意: 重试逻辑。Token 计算准确性依赖于 response 完整性。 + update_model_stats(model, prompt_tokens, completion_tokens, final_calculation_method, compute_points_used) + + return jsonify({ + "id": f"chatcmpl-{str(uuid.uuid4())}", + "object": "chat.completion", + "created": int(time.time()), + "model": model, + "choices": [{ + "index": 0, + "message": { + "role": "assistant", + "content": response_content + }, + "finish_reason": "stop" + }], + "usage": { + "prompt_tokens": prompt_tokens, + "completion_tokens": completion_tokens, + "total_tokens": prompt_tokens + completion_tokens + } + }) + except Exception as retry_e: + print(f"重试失败: {retry_e}") + + return jsonify({"error": f"Failed to send message: {error_details}"}), 500 + + +def format_message(messages): + buffer = io.StringIO() + role_map, prefix, messages = extract_role(messages) + for message in messages: + role = message.get("role") + role = "\b" + role_map[role] if prefix else role_map[role] + content = message.get("content").replace("\\n", "\n") + pattern = re.compile(r"<\|removeRole\|>\n") + if pattern.match(content): + content = pattern.sub("", content) + buffer.write(f"{content}\n") + else: + buffer.write(f"{role}: {content}\n\n") + formatted_message = buffer.getvalue() + return formatted_message + + +def extract_role(messages): + role_map = {"user": "Human", "assistant": "Assistant", "system": "System"} + prefix = True # 默认添加前缀 + first_message = messages[0]["content"] + pattern = re.compile( + r""" + \s* + (?:user:\s*(?P[^\n]*)\s*)? # Make user optional + (?:assistant:\s*(?P[^\n]*)\s*)? # Make assistant optional + (?:system:\s*(?P[^\n]*)\s*)? # Make system optional + (?:prefix:\s*(?P[^\n]*)\s*)? # Make prefix optional + \n + """, + re.VERBOSE, + ) + match = pattern.search(first_message) + if match: + # 更新 role_map 如果提供了值 + user_role = match.group("user") + assistant_role = match.group("assistant") + system_role = match.group("system") + if user_role: role_map["user"] = user_role + if assistant_role: role_map["assistant"] = assistant_role + if system_role: role_map["system"] = system_role + + # 检查 prefix 值：仅当显式设置为非 "1" 时才将 prefix 设为 False + prefix_value = match.group("prefix") + if prefix_value is not None and prefix_value != "1": + prefix = False + # 如果 prefix_value 是 None (标签不存在) 或 "1", prefix 保持 True + + messages[0]["content"] = pattern.sub("", first_message) + print(f"Extracted role map:") + print( + f"User: {role_map['user']}, Assistant: {role_map['assistant']}, System: {role_map['system']}" + ) + print(f"Using prefix: {prefix}") # 打印语句保持不变，反映最终结果 + # 如果没有匹配到 ，prefix 保持默认值 True + return (role_map, prefix, messages) + + +@app.route("/health", methods=["GET"]) +def health_check(): + global health_check_counter + health_check_counter += 1 + return jsonify({ + "status": "healthy", + "timestamp": datetime.now().isoformat(), + "checks": health_check_counter + }) + + +def keep_alive(): + """每20分钟进行一次自我健康检查""" + while True: + try: + requests.get("http://127.0.0.1:7860/health") + time.sleep(1200) # 20分钟 + except: + pass # 忽略错误，保持运行 + + +@app.route("/", methods=["GET"]) +def index(): + # 如果需要密码且用户未登录，重定向到登录页面 + if PASSWORD and not flask_session.get('logged_in'): + return redirect(url_for('login')) + + # 否则重定向到仪表盘 + return redirect(url_for('dashboard')) + + +def num_tokens_from_string(string, model=""): + try: + print("\n===================== 开始计算token =====================") + print(f"模型: {model}") + print(f"输入内容长度: {len(string)} 字符") + + request_data = { + "model": model, + "messages": [{"role": "user", "content": string}] + } + print(f"发送请求到tokenizer服务: {TOKENIZER_SERVICE_URL}") + print(f"请求数据: {json.dumps(request_data, ensure_ascii=False)}") + + response = requests.post( + TOKENIZER_SERVICE_URL, + json=request_data, + timeout=10 + ) + + print(f"\nTokenizer响应状态码: {response.status_code}") + print(f"Tokenizer响应内容: {response.text}") + + if response.status_code == 200: + result = response.json() + input_tokens = result.get("input_tokens", 0) + print(f"\n成功获取token数: {input_tokens}") + print(f"使用计算方法: 精确") + print("===================== 计算完成 =====================\n") + return input_tokens, "精确" + else: + estimated_tokens = len(string) // 4 + print(f"\nTokenizer服务错误: {response.status_code}") + print(f"错误响应: {response.text}") + print(f"使用估算token数: {estimated_tokens}") + print(f"使用计算方法: 估算") + print("===================== 计算完成 =====================\n") + return estimated_tokens, "估算" + except Exception as e: + estimated_tokens = len(string) // 4 + print(f"\n计算token时发生错误: {str(e)}") + print(f"使用估算token数: {estimated_tokens}") + print(f"使用计算方法: 估算") + print("===================== 计算完成 =====================\n") + return estimated_tokens, "估算" + + +# 更新模型使用统计 +def update_model_stats(model, prompt_tokens, completion_tokens, calculation_method="estimate", compute_points=None): + global model_usage_stats, total_tokens, model_usage_records + + # 添加调用记录 + # 获取UTC时间 + utc_now = datetime.utcnow() + # 转换为北京时间 (UTC+8) + beijing_time = utc_now + timedelta(hours=8) + call_time = beijing_time.strftime('%Y-%m-%d %H:%M:%S') # 北京时间 + + record = { + "model": model, + "call_time": call_time, + "prompt_tokens": prompt_tokens, + "completion_tokens": completion_tokens, + "calculation_method": calculation_method, # 直接使用传入的值 + "compute_points": compute_points + } + model_usage_records.append(record) + + # 限制记录数量，保留最新的500条 + if len(model_usage_records) > 500: + model_usage_records.pop(0) + + # 保存调用记录到本地文件 + save_model_usage_records() + + # 更新聚合统计 + if model not in model_usage_stats: + model_usage_stats[model] = { + "count": 0, + "prompt_tokens": 0, + "completion_tokens": 0, + "total_tokens": 0 + } + + model_usage_stats[model]["count"] += 1 + model_usage_stats[model]["prompt_tokens"] += prompt_tokens + model_usage_stats[model]["completion_tokens"] += completion_tokens + model_usage_stats[model]["total_tokens"] += (prompt_tokens + completion_tokens) + + total_tokens["prompt"] += prompt_tokens + total_tokens["completion"] += completion_tokens + total_tokens["total"] += (prompt_tokens + completion_tokens) + + +# 获取计算点信息 +def get_compute_points(): + global compute_points, USER_DATA, users_compute_points + + if USER_NUM == 0: + return + + # 清空用户计算点列表 + users_compute_points = [] + + # 累计总计算点 + total_left = 0 + total_points = 0 + + # 获取每个用户的计算点信息 + for i, user_data in enumerate(USER_DATA): + try: + session, cookies, session_token, _, _, _ = user_data + + # 检查token是否有效 + if is_token_expired(session_token): + session_token = refresh_token(session, cookies) + if not session_token: + print(f"用户{i+1}刷新token失败，无法获取计算点信息") + continue + USER_DATA[i] = (session, cookies, session_token, user_data[3], user_data[4], i) + + headers = { + "accept": "application/json, text/plain, */*", + "accept-language": "zh-CN,zh;q=0.9", + "baggage": f"sentry-environment=production,sentry-release=93da8385541a6ce339b1f41b0c94428c70657e22,sentry-public_key=3476ea6df1585dd10e92cdae3a66ff49,sentry-trace_id={TRACE_ID}", + "reai-ui": "1", + "sec-ch-ua": "\"Chromium\";v=\"116\", \"Not)A;Brand\";v=\"24\", \"Google Chrome\";v=\"116\"", + "sec-ch-ua-mobile": "?0", + "sec-ch-ua-platform": "\"Windows\"", + "sec-fetch-dest": "empty", + "sec-fetch-mode": "cors", + "sec-fetch-site": "same-origin", + "sentry-trace": SENTRY_TRACE, + "session-token": session_token, + "x-abacus-org-host": "apps", + "cookie": cookies + } + + response = session.get( + COMPUTE_POINTS_URL, + headers=headers + ) + + if response.status_code == 200: + result = response.json() + if result.get("success") and "result" in result: + data = result["result"] + left = data.get("computePointsLeft", 0) + total = data.get("totalComputePoints", 0) + used = total - left + percentage = round((used / total) * 100, 2) if total > 0 else 0 + + # 获取北京时间 + beijing_now = datetime.utcnow() + timedelta(hours=8) + + # 添加到用户列表 + user_points = { + "user_id": i + 1, # 用户ID从1开始 + "left": left, + "total": total, + "used": used, + "percentage": percentage, + "last_update": beijing_now + } + users_compute_points.append(user_points) + + # 累计总数 + total_left += left + total_points += total + + print(f"用户{i+1}计算点信息更新成功: 剩余 {left}, 总计 {total}") + + # 对于第一个用户，获取计算点使用日志 + if i == 0: + get_compute_points_log(session, cookies, session_token) + else: + print(f"获取用户{i+1}计算点信息失败: {result.get('error', '未知错误')}") + else: + print(f"获取用户{i+1}计算点信息失败，状态码: {response.status_code}") + except Exception as e: + print(f"获取用户{i+1}计算点信息异常: {e}") + + # 更新全局计算点信息（所有用户总和） + if users_compute_points: + compute_points["left"] = total_left + compute_points["total"] = total_points + compute_points["used"] = total_points - total_left + compute_points["percentage"] = round((compute_points["used"] / compute_points["total"]) * 100, 2) if compute_points["total"] > 0 else 0 + compute_points["last_update"] = datetime.utcnow() + timedelta(hours=8) # 北京时间 + print(f"所有用户计算点总计: 剩余 {total_left}, 总计 {total_points}") + +# 获取计算点使用日志 +def get_compute_points_log(session, cookies, session_token): + global compute_points_log + + try: + headers = { + "accept": "application/json, text/plain, */*", + "accept-language": "zh-CN,zh;q=0.9", + "content-type": "application/json", + "reai-ui": "1", + "sec-ch-ua": "\"Chromium\";v=\"116\", \"Not)A;Brand\";v=\"24\", \"Google Chrome\";v=\"116\"", + "sec-ch-ua-mobile": "?0", + "sec-ch-ua-platform": "\"Windows\"", + "sec-fetch-dest": "empty", + "sec-fetch-mode": "cors", + "sec-fetch-site": "same-site", + "session-token": session_token, + "x-abacus-org-host": "apps", + "cookie": cookies + } + + response = session.post( + COMPUTE_POINTS_LOG_URL, + headers=headers, + json={"byLlm": True} + ) + + if response.status_code == 200: + result = response.json() + if result.get("success") and "result" in result: + data = result["result"] + compute_points_log["columns"] = data.get("columns", {}) + compute_points_log["log"] = data.get("log", []) + print(f"计算点使用日志更新成功，获取到 {len(compute_points_log['log'])} 条记录") + else: + print(f"获取计算点使用日志失败: {result.get('error', '未知错误')}") + else: + print(f"获取计算点使用日志失败，状态码: {response.status_code}") + except Exception as e: + print(f"获取计算点使用日志异常: {e}") + + +# 添加登录相关路由 +@app.route("/login", methods=["GET", "POST"]) +def login(): + error = None + if request.method == "POST": + password = request.form.get("password") + if password and hashlib.sha256(password.encode()).hexdigest() == PASSWORD: + flask_session['logged_in'] = True + flask_session.permanent = True + return redirect(url_for('dashboard')) + else: + # 密码错误时提示使用环境变量密码 + error = "密码不正确。请使用设置的环境变量 password 或 password.txt 中的值作为密码和API认证密钥。" + + # 传递空间URL给模板 + return render_template('login.html', error=error, space_url=SPACE_URL) + + +@app.route("/logout") +def logout(): + flask_session.clear() + return redirect(url_for('login')) + + +@app.route("/dashboard") +@require_auth +def dashboard(): + # 在每次访问仪表盘时更新计算点信息 + get_compute_points() + + # 计算运行时间（使用北京时间） + beijing_now = datetime.utcnow() + timedelta(hours=8) + uptime = beijing_now - START_TIME + days = uptime.days + hours, remainder = divmod(uptime.seconds, 3600) + minutes, seconds = divmod(remainder, 60) + + if days > 0: + uptime_str = f"{days}天 {hours}小时 {minutes}分钟" + elif hours > 0: + uptime_str = f"{hours}小时 {minutes}分钟" + else: + uptime_str = f"{minutes}分钟 {seconds}秒" + + # 当前北京年份 + beijing_year = beijing_now.year + + return render_template( + 'dashboard.html', + uptime=uptime_str, + health_checks=health_check_counter, + user_count=USER_NUM, + models=sorted(list(MODELS)), + year=beijing_year, + model_stats=model_usage_stats, + total_tokens=total_tokens, + compute_points=compute_points, + compute_points_log=compute_points_log, + space_url=SPACE_URL, # 传递空间URL + users_compute_points=users_compute_points, # 传递用户计算点信息 + model_usage_records=model_usage_records, # 传递模型使用记录 + ) + + +# 添加更新计算点数记录设置的路由 +@app.route("/update_compute_point_toggle", methods=["POST"]) +@require_auth +def update_compute_point_toggle(): + try: + (session, cookies, session_token, conversation_id, model_map, user_index) = get_user_data() + data = request.get_json() + if data and "always_display" in data: + headers = { + "accept": "application/json, text/plain, */*", + "accept-language": "zh-CN,zh;q=0.9", + "content-type": "application/json", + "reai-ui": "1", + "sec-ch-ua": "\"Chromium\";v=\"116\", \"Not)A;Brand\";v=\"24\", \"Google Chrome\";v=\"116\"", + "sec-ch-ua-mobile": "?0", + "sec-ch-ua-platform": "\"Windows\"", + "sec-fetch-dest": "empty", + "sec-fetch-mode": "cors", + "sec-fetch-site": "same-site", + "x-abacus-org-host": "apps" + } + + if session_token: + headers["session-token"] = session_token + + response = session.post( + COMPUTE_POINT_TOGGLE_URL, + headers=headers, + json={"alwaysDisplay": data["always_display"]}, + cookies=None + ) + + if response.status_code == 200: + result = response.json() + if result.get("success"): + print(f"更新计算点数记录设置为: {data['always_display']}") + return jsonify({"success": True}) + + return jsonify({"success": False, "error": "API调用失败"}) + else: + return jsonify({"success": False, "error": "缺少always_display参数"}) + except Exception as e: + print(f"更新计算点数记录设置失败: {e}") + return jsonify({"success": False, "error": str(e)}) + + +# 获取Hugging Face Space URL +def get_space_url(): + # 尝试从环境变量获取 + space_url = os.environ.get("SPACE_URL") + if space_url: + return space_url + + # 如果SPACE_URL不存在，尝试从SPACE_ID构建 + space_id = os.environ.get("SPACE_ID") + if space_id: + username, space_name = space_id.split("/") + # 将空间名称中的下划线替换为连字符 + # 注意：Hugging Face生成的URL会自动将空间名称中的下划线(_)替换为连字符(-) + # 例如："abacus_chat_proxy" 会变成 "abacus-chat-proxy" + space_name = space_name.replace("_", "-") + return f"https://{username}-{space_name}.hf.space" + + # 如果以上都不存在，尝试从单独的用户名和空间名构建 + username = os.environ.get("SPACE_USERNAME") + space_name = os.environ.get("SPACE_NAME") + if username and space_name: + # 将空间名称中的下划线替换为连字符 + # 同上，Hugging Face会自动进行此转换 + space_name = space_name.replace("_", "-") + return f"https://{username}-{space_name}.hf.space" + + # 默认返回None + return None + +# 获取空间URL +SPACE_URL = get_space_url() +if SPACE_URL: + print(f"Space URL: {SPACE_URL}") + print("注意：Hugging Face生成的URL会自动将空间名称中的下划线(_)替换为连字符(-)") + + +def save_conversation_history(session, cookies, session_token, conversation_id, deployment_id="14b2a314cc"): + """保存对话历史，返回使用的计算点数""" + if not conversation_id: + return False, None + + headers = { + "accept": "application/json, text/plain, */*", + "accept-language": "zh-CN,zh;q=0.9", + "baggage": f"sentry-environment=production,sentry-release=946244517de08b08598b94f18098411f5a5352d5,sentry-public_key=3476ea6df1585dd10e92cdae3a66ff49,sentry-trace_id={TRACE_ID}", + "reai-ui": "1", + "sec-ch-ua": "\"Chromium\";v=\"116\", \"Not)A;Brand\";v=\"24\", \"Google Chrome\";v=\"116\"", + "sec-ch-ua-mobile": "?0", + "sec-ch-ua-platform": "\"Windows\"", + "sec-fetch-dest": "empty", + "sec-fetch-mode": "cors", + "sec-fetch-site": "same-origin", + "sentry-trace": f"{TRACE_ID}-800cb7f4613dec52", + "x-abacus-org-host": "apps" + } + + if session_token: + headers["session-token"] = session_token + + params = { + "deploymentId": deployment_id, + "deploymentConversationId": conversation_id, + "skipDocumentBoundingBoxes": "true", + "filterIntermediateConversationEvents": "false", + "getUnusedDocumentUploads": "false" + } + + try: + response = session.get( + GET_CONVERSATION_URL, + headers=headers, + params=params, + cookies=None + ) + + if response.status_code == 200: + data = response.json() + if data.get("success"): + # 从最后一条BOT消息中获取计算点数 + history = data.get("result", {}).get("history", []) + compute_points = None + for msg in reversed(history): + if msg.get("role") == "BOT": + compute_points = msg.get("computePointsUsed") + break + print(f"成功保存对话历史: {conversation_id}, 使用计算点: {compute_points}") + return True, compute_points + else: + print(f"保存对话历史失败: {data.get('error', '未知错误')}") + else: + print(f"保存对话历史失败，状态码: {response.status_code}") + return False, None + except Exception as e: + print(f"保存对话历史时出错: {e}") + return False, None + + +if __name__ == "__main__": + # 启动保活线程 + threading.Thread(target=keep_alive, daemon=True).start() + + # 加载历史模型调用记录 + load_model_usage_records() + + # 获取初始计算点信息 + get_compute_points() + + port = int(os.environ.get("PORT", 9876)) + app.run(port=port, host="0.0.0.0")