#!/usr/bin/env python3 import json import base64 import time import logging from curl_cffi import requests import random from flask import Flask, render_template, request, Response, stream_with_context, jsonify, g import os import struct import ctypes from wasmtime import Store, Module, Linker import re import transformers import queue import threading # -------------------------- 初始化 tokenizer -------------------------- chat_tokenizer_dir = "THUDM/chatglm2-6b" # 使用现成的模型tokenizer tokenizer = transformers.AutoTokenizer.from_pretrained( chat_tokenizer_dir, trust_remote_code=True, use_fast=False # 使用慢速tokenizer避免fast tokenizer的转换问题 ) # ---------------------------------------------------------------------- # =========================== 日志配置 =========================== logging.basicConfig( level=logging.INFO, format='%(asctime)s [%(levelname)s] %(name)s: %(message)s' ) app = Flask(__name__) # -------------------- 全局添加 CORS 支持 -------------------- @app.before_request def handle_options_request(): if request.method == 'OPTIONS': response = Response() response.headers["Access-Control-Allow-Origin"] = "*" response.headers["Access-Control-Allow-Headers"] = "Content-Type, Authorization" response.headers["Access-Control-Allow-Methods"] = "GET, POST, OPTIONS, PUT, DELETE" return response @app.after_request def add_cors_headers(response): response.headers["Access-Control-Allow-Origin"] = "*" response.headers["Access-Control-Allow-Headers"] = "Content-Type, Authorization" response.headers["Access-Control-Allow-Methods"] = "GET, POST, OPTIONS" return response # ---------------------------------------------------------------------- # 全局集合:记录当前正在对话中的账号(以 email 或 phone 标识),保证同一账号同时只进行一个对话 active_accounts = set() # ---------------------------------------------------------------------- # (1) 配置文件的读写函数 # ---------------------------------------------------------------------- CONFIG_PATH = "config.json" def load_config(): """从环境变量加载配置""" config = { "keys": [], "accounts": [] } # 从环境变量读取API keys api_keys = os.getenv("DEEPSEEK_API_KEYS", "").strip() if api_keys: config["keys"] = [k.strip() for k in api_keys.split(",") if k.strip()] # 从环境变量读取账号信息 # 格式: # - 使用email登录: email:password:token(可选) # - 使用mobile登录: mobile:password:token(可选) accounts_str = os.getenv("DEEPSEEK_ACCOUNTS", "").strip() if accounts_str: for acc in accounts_str.split(","): parts = [p.strip() for p in acc.split(":") if p.strip()] if len(parts) >= 2: # 至少需要账号和密码 account = {} # 根据第一个参数是否包含@判断是email还是mobile if "@" in parts[0]: account["email"] = parts[0] else: account["mobile"] = parts[0] account["password"] = parts[1] # 如果有第三个参数,则为token if len(parts) > 2: account["token"] = parts[2] config["accounts"].append(account) return config def save_config(cfg): """ 由于使用环境变量,此函数仅更新内存中的CONFIG token更新后需要手动同步到环境变量中 """ global CONFIG CONFIG = cfg # 可选:打印提示信息 app.logger.info("[save_config] 配置已更新(仅内存)") CONFIG = load_config() # ---------------------------------------------------------------------- # (2) DeepSeek 相关常量 # ---------------------------------------------------------------------- DEEPSEEK_HOST = "chat.deepseek.com" DEEPSEEK_LOGIN_URL = f"https://{DEEPSEEK_HOST}/api/v0/users/login" DEEPSEEK_CREATE_SESSION_URL = f"https://{DEEPSEEK_HOST}/api/v0/chat_session/create" DEEPSEEK_CREATE_POW_URL = f"https://{DEEPSEEK_HOST}/api/v0/chat/create_pow_challenge" DEEPSEEK_COMPLETION_URL = f"https://{DEEPSEEK_HOST}/api/v0/chat/completion" BASE_HEADERS = { 'Host': "chat.deepseek.com", 'User-Agent': "DeepSeek/1.0.13 Android/35", 'Accept': "application/json", 'Accept-Encoding': "gzip", 'Content-Type': "application/json", 'x-client-platform': "android", 'x-client-version': "1.0.13", 'x-client-locale': "zh_CN", 'accept-charset': "UTF-8", } # WASM 模块文件路径(请确保文件存在) WASM_PATH = "sha3_wasm_bg.7b9ca65ddd.wasm" # ---------------------------------------------------------------------- # 辅助函数:获取账号唯一标识(优先 email,否则 mobile) # ---------------------------------------------------------------------- def get_account_identifier(account): """返回账号的唯一标识,优先使用 email,否则使用 mobile""" return account.get("email", "").strip() or account.get("mobile", "").strip() # ---------------------------------------------------------------------- # (3) 登录函数:支持使用 email 或 mobile 登录 # ---------------------------------------------------------------------- def login_deepseek_via_account(account): """使用 account 中的 email 或 mobile 登录 DeepSeek, 成功后将返回的 token 写入 account 并保存至配置文件,返回新 token。""" email = account.get("email", "").strip() mobile = account.get("mobile", "").strip() password = account.get("password", "").strip() if not password or (not email and not mobile): raise ValueError("账号缺少必要的登录信息(必须提供 email 或 mobile 以及 password)") if email: app.logger.info(f"[login_deepseek_via_account] 正在使用 email 登录账号:{email}") payload = { "email": email, "mobile": "", "password": password, "area_code": "", "device_id": "deepseek_to_api", "os": "android" } else: app.logger.info(f"[login_deepseek_via_account] 正在使用 mobile 登录账号:{mobile}") payload = { "mobile": mobile, "area_code": None, "password": password, "device_id": "deepseek_to_api", "os": "android" } # 增加 timeout 参数,防止请求阻塞过久 resp = requests.post(DEEPSEEK_LOGIN_URL, headers=BASE_HEADERS, json=payload, timeout=30) app.logger.debug(f"[login_deepseek_via_account] 状态码: {resp.status_code}") app.logger.debug(f"[login_deepseek_via_account] 响应体: {resp.text}") resp.raise_for_status() data = resp.json() if data.get("code") != 0: raise ValueError(f"登录失败, code={data.get('code')}, msg={data.get('msg')}") new_token = data["data"]["biz_data"]["user"]["token"] account["token"] = new_token save_config(CONFIG) identifier = email if email else mobile app.logger.info(f"[login_deepseek_via_account] 成功登录账号 {identifier},token: {new_token}") return new_token # ---------------------------------------------------------------------- # -------------------------- 全局账号队列 -------------------------- account_queue = [] # 维护所有可用账号 def init_account_queue(): """初始化时从配置加载账号""" global account_queue account_queue = CONFIG.get("accounts", [])[:] # 深拷贝 random.shuffle(account_queue) # 初始随机排序 init_account_queue() def choose_new_account(): """选择策略: 1. 遍历队列,找到第一个未被 exclude_ids 包含的账号 2. 从队列中移除该账号 3. 返回该账号(由后续逻辑保证最终会重新入队) """ for i in range(len(account_queue)): acc = account_queue[i] acc_id = get_account_identifier(acc) if acc_id: # 从队列中移除并返回 return account_queue.pop(i) app.logger.warning("[choose_new_account] 没有可用的账号或所有账号都在使用中") return None def release_account(account): """将账号重新加入队列末尾""" account_queue.append(account) # ---------------------------------------------------------------------- # (5) 判断调用模式:配置模式 vs 用户自带 token # ---------------------------------------------------------------------- def determine_mode_and_token(): """根据请求头 Authorization 判断使用哪种模式: - 如果 Bearer token 出现在 CONFIG["keys"] 中,则为配置模式,从 CONFIG["accounts"] 中随机选择一个账号(排除已尝试账号), 检查该账号是否已有 token,否则调用登录接口获取; - 否则,直接使用请求中的 Bearer 值作为 DeepSeek token。 结果存入 g.deepseek_token;配置模式下同时存入 g.account 与 g.tried_accounts。 """ auth_header = request.headers.get("Authorization", "") if not auth_header.startswith("Bearer "): return Response(json.dumps({"error": "Unauthorized: missing Bearer token."}), status=401, mimetype="application/json") caller_key = auth_header.replace("Bearer ", "", 1).strip() config_keys = CONFIG.get("keys", []) if caller_key in config_keys: g.use_config_token = True g.tried_accounts = [] # 初始化已尝试账号 selected_account = choose_new_account() if not selected_account: return Response(json.dumps({"error": "No accounts configured or all accounts are busy."}), status=429, mimetype="application/json") if not selected_account.get("token", "").strip(): try: login_deepseek_via_account(selected_account) except Exception as e: app.logger.error(f"[determine_mode_and_token] 账号 {get_account_identifier(selected_account)} 登录失败:{e}") return Response(json.dumps({"error": "Account login failed."}), status=500, mimetype="application/json") g.deepseek_token = selected_account.get("token") g.account = selected_account else: g.use_config_token = False g.deepseek_token = caller_key return None def get_auth_headers(): """返回 DeepSeek 请求所需的公共请求头""" return { **BASE_HEADERS, "authorization": f"Bearer {g.deepseek_token}" } # ---------------------------------------------------------------------- # (6) 封装对话接口调用的重试机制 # ---------------------------------------------------------------------- def call_completion_endpoint(payload, headers, stream, max_attempts=3): attempts = 0 while attempts < max_attempts: try: deepseek_resp = requests.post(DEEPSEEK_COMPLETION_URL, headers=headers, json=payload, stream=stream) except Exception as e: app.logger.warning(f"[call_completion_endpoint] 请求异常: {e}") time.sleep(1) attempts += 1 continue if deepseek_resp.status_code == 200: return deepseek_resp else: app.logger.warning(f"[call_completion_endpoint] 调用对话接口失败, 状态码: {deepseek_resp.status_code}") deepseek_resp.close() time.sleep(1) attempts += 1 return None # ---------------------------------------------------------------------- # (7) 创建会话 & 获取 PoW(重试时,配置模式下错误会切换账号;用户自带 token 模式下仅重试) # ---------------------------------------------------------------------- def create_session(max_attempts=3): attempts = 0 while attempts < max_attempts: headers = get_auth_headers() try: resp = requests.post(DEEPSEEK_CREATE_SESSION_URL, headers=headers, json={"agent": "chat"}, timeout=30) except Exception as e: app.logger.error(f"[create_session] 请求异常: {e}") attempts += 1 continue try: data = resp.json() except Exception as e: app.logger.error(f"[create_session] JSON解析异常: {e}") data = {} if resp.status_code == 200 and data.get("code") == 0: session_id = data["data"]["biz_data"]["id"] app.logger.info(f"[create_session] 新会话 chat_session_id={session_id}") resp.close() return session_id else: code = data.get("code") app.logger.warning(f"[create_session] 创建会话失败, code={code}, msg={data.get('msg')}") resp.close() if g.use_config_token: current_id = get_account_identifier(g.account) if not hasattr(g, 'tried_accounts'): g.tried_accounts = [] if current_id not in g.tried_accounts: g.tried_accounts.append(current_id) new_account = choose_new_account() if new_account is None: break try: login_deepseek_via_account(new_account) except Exception as e: app.logger.error(f"[create_session] 账号 {get_account_identifier(new_account)} 登录失败:{e}") attempts += 1 continue g.account = new_account g.deepseek_token = new_account.get("token") else: attempts += 1 continue attempts += 1 return None # ---------------------------------------------------------------------- # (7.1) 使用 WASM 模块计算 PoW 答案的辅助函数 # ---------------------------------------------------------------------- def compute_pow_answer(algorithm: str, challenge_str: str, salt: str, difficulty: int, expire_at: int, signature: str, target_path: str, wasm_path: str) -> int: """ 使用 WASM 模块计算 DeepSeekHash 答案(answer)。 根据 JS 逻辑: - 拼接前缀: "{salt}_{expire_at}_" - 将 challenge 与前缀写入 wasm 内存后调用 wasm_solve 进行求解, - 从 wasm 内存中读取状态与求解结果, - 若状态非 0,则返回整数形式的答案,否则返回 None。 """ if algorithm != "DeepSeekHashV1": raise ValueError(f"不支持的算法:{algorithm}") prefix = f"{salt}_{expire_at}_" # --- 加载 wasm 模块 --- store = Store() linker = Linker(store.engine) try: with open(wasm_path, "rb") as f: wasm_bytes = f.read() except Exception as e: raise RuntimeError(f"加载 wasm 文件失败: {wasm_path}, 错误: {e}") module = Module(store.engine, wasm_bytes) instance = linker.instantiate(store, module) exports = instance.exports(store) try: memory = exports["memory"] add_to_stack = exports["__wbindgen_add_to_stack_pointer"] alloc = exports["__wbindgen_export_0"] wasm_solve = exports["wasm_solve"] except KeyError as e: raise RuntimeError(f"缺少 wasm 导出函数: {e}") def write_memory(offset: int, data: bytes): size = len(data) base_addr = ctypes.cast(memory.data_ptr(store), ctypes.c_void_p).value ctypes.memmove(base_addr + offset, data, size) def read_memory(offset: int, size: int) -> bytes: base_addr = ctypes.cast(memory.data_ptr(store), ctypes.c_void_p).value return ctypes.string_at(base_addr + offset, size) def encode_string(text: str): data = text.encode("utf-8") length = len(data) ptr_val = alloc(store, length, 1) ptr = int(ptr_val.value) if hasattr(ptr_val, "value") else int(ptr_val) write_memory(ptr, data) return ptr, length # 1. 申请 16 字节栈空间 retptr = add_to_stack(store, -16) # 2. 编码 challenge 与 prefix 到 wasm 内存中 ptr_challenge, len_challenge = encode_string(challenge_str) ptr_prefix, len_prefix = encode_string(prefix) # 3. 调用 wasm_solve(注意:difficulty 以 float 形式传入) wasm_solve(store, retptr, ptr_challenge, len_challenge, ptr_prefix, len_prefix, float(difficulty)) # 4. 从 retptr 处读取 4 字节状态和 8 字节求解结果 status_bytes = read_memory(retptr, 4) if len(status_bytes) != 4: add_to_stack(store, 16) raise RuntimeError("读取状态字节失败") status = struct.unpack(" str: """处理消息列表,合并连续相同角色的消息,并添加角色标签: - 对于 assistant 消息,加上 <|Assistant|> 前缀及 结束标签; - 对于 user/system 消息(除第一条外)加上 结束标签; - 如果消息 content 为数组,则提取其中 type 为 "text" 的部分; - 最后移除 markdown 图片格式的内容。 """ processed = [] for m in messages: role = m.get("role", "") content = m.get("content", "") if isinstance(content, list): texts = [item.get("text", "") for item in content if item.get("type") == "text"] text = "\n".join(texts) else: text = str(content) processed.append({"role": role, "text": text}) if not processed: return "" # 合并连续同一角色的消息 merged = [processed[0]] for msg in processed[1:]: if msg["role"] == merged[-1]["role"]: merged[-1]["text"] += "\n\n" + msg["text"] else: merged.append(msg) # 添加标签 parts = [] for idx, block in enumerate(merged): role = block["role"] text = block["text"] if role == "assistant": parts.append(f"<|Assistant|>{text}") elif role in ("user", "system"): if idx > 0: parts.append(f"结束标签") else: parts.append(text) else: parts.append(text) final_prompt = "".join(parts) # 仅移除 markdown 图片格式(不全部移除 !) final_prompt = re.sub(r"!\[(.*?)\]\((.*?)\)", r"[\1](\2)", final_prompt) return final_prompt # ---------------------------------------------------------------------- # (10) 路由:/v1/chat/completions # ---------------------------------------------------------------------- @app.route("/hf/v1/chat/completions", methods=["POST"]) def chat_completions(): mode_resp = determine_mode_and_token() if mode_resp: return mode_resp try: req_data = request.json or {} app.logger.info(f"[chat_completions] 收到请求: {req_data}") model = req_data.get("model") messages = req_data.get("messages", []) if not model or not messages: return jsonify({"error": "Request must include 'model' and 'messages'."}), 400 # 判断是否启用"思考"功能(这里根据模型名称判断) model_lower = model.lower() if model_lower in ["deepseek-v3", "deepseek-chat"]: thinking_enabled = False search_enabled = False elif model_lower in ["deepseek-r1", "deepseek-reasoner"]: thinking_enabled = True search_enabled = False elif model_lower in ["deepseek-v3-search", "deepseek-chat-search"]: thinking_enabled = False search_enabled = True elif model_lower in ["deepseek-r1-search", "deepseek-reasoner-search"]: thinking_enabled = True search_enabled = True else: return Response(json.dumps({"error": f"Model '{model}' is not available."}), status=503, mimetype="application/json") # 使用 messages_prepare 函数构造最终 prompt final_prompt = messages_prepare(messages) app.logger.debug(f"[chat_completions] 最终 Prompt: {final_prompt}") session_id = create_session() if not session_id: return jsonify({"error": "invalid token."}), 401 pow_resp = get_pow_response() if not pow_resp: return jsonify({"error": "Failed to get PoW (invalid token or unknown error)."}), 401 app.logger.info(f"获取 PoW 成功: {pow_resp}") headers = { **get_auth_headers(), "x-ds-pow-response": pow_resp } payload = { "chat_session_id": session_id, "parent_message_id": None, "prompt": final_prompt, "ref_file_ids": [], "thinking_enabled": thinking_enabled, "search_enabled": search_enabled } app.logger.debug(f"[chat_completions] -> {DEEPSEEK_COMPLETION_URL}, payload={payload}") deepseek_resp = call_completion_endpoint(payload, headers, stream=bool(req_data.get("stream", False)), max_attempts=3) if not deepseek_resp: return jsonify({"error": "Failed to get completion."}), 500 created_time = int(time.time()) completion_id = f"{session_id}" # 流式响应:SSE 格式返回事件流 if bool(req_data.get("stream", False)): if deepseek_resp.status_code != 200: deepseek_resp.close() return Response(deepseek_resp.content, status=deepseek_resp.status_code, mimetype="application/json") # 添加保活超时配置(5秒) KEEP_ALIVE_TIMEOUT = 5 def sse_stream(): try: final_text = "" final_thinking = "" first_chunk_sent = False result_queue = queue.Queue() last_send_time = time.time() citation_map = {} # 用于存储引用链接的字典 def process_data(): try: for raw_line in deepseek_resp.iter_lines(): try: line = raw_line.decode("utf-8") except Exception as e: app.logger.warning(f"[sse_stream] 解码失败: {e}") busy_content_str = '{"choices":[{"index":0,"delta":{"content":"服务器繁忙,请稍候再试","type":"text"}}],"model":"","chunk_token_usage":1,"created":0,"message_id":-1,"parent_id":-1}' busy_content = json.loads(busy_content_str) result_queue.put(busy_content) result_queue.put(None) break if not line: continue if line.startswith("data:"): data_str = line[5:].strip() if data_str == "[DONE]": result_queue.put(None) # 结束信号 break try: chunk = json.loads(data_str) # 处理搜索索引数据 if chunk.get("choices", [{}])[0].get("delta", {}).get("type") == "search_index": search_indexes = chunk["choices"][0]["delta"].get("search_indexes", []) for idx in search_indexes: citation_map[str(idx.get("cite_index"))] = idx.get("url", "") continue result_queue.put(chunk) # 将数据放入队列 except Exception as e: app.logger.warning(f"[sse_stream] 无法解析: {data_str}, 错误: {e}") busy_content_str = '{"choices":[{"index":0,"delta":{"content":"服务器繁忙,请稍候再试","type":"text"}}],"model":"","chunk_token_usage":1,"created":0,"message_id":-1,"parent_id":-1}' busy_content = json.loads(busy_content_str) result_queue.put(busy_content) result_queue.put(None) break except Exception as e: app.logger.warning(f"[sse_stream] 错误: {e}") busy_content_str = '{"choices":[{"index":0,"delta":{"content":"服务器繁忙,请稍候再试","type":"text"}}],"model":"","chunk_token_usage":1,"created":0,"message_id":-1,"parent_id":-1}' busy_content = json.loads(busy_content_str) result_queue.put(busy_content) result_queue.put(None) finally: deepseek_resp.close() process_thread = threading.Thread(target=process_data) process_thread.start() while True: current_time = time.time() if current_time - last_send_time >= KEEP_ALIVE_TIMEOUT: yield ": keep-alive\n\n" last_send_time = current_time continue try: chunk = result_queue.get(timeout=0.1) if chunk is None: # 发送最终统计信息 prompt_tokens = len(tokenizer.encode(final_prompt)) completion_tokens = len(tokenizer.encode(final_text)) usage = { "prompt_tokens": prompt_tokens, "completion_tokens": completion_tokens, "total_tokens": prompt_tokens + completion_tokens, } finish_chunk = { "id": completion_id, "object": "chat.completion.chunk", "created": created_time, "model": model, "choices": [ { "delta": {}, "index": 0, "finish_reason": "stop", } ], "usage": usage, } yield f"data: {json.dumps(finish_chunk, ensure_ascii=False)}\n\n" yield "data: [DONE]\n\n" last_send_time = current_time break new_choices = [] for choice in chunk.get("choices", []): delta = choice.get("delta", {}) ctype = delta.get("type") ctext = delta.get("content", "") if choice.get("finish_reason") == "backend_busy": ctext = '服务器繁忙,请稍候再试' if search_enabled and ctext.startswith("[citation:"): ctext = "" if ctype == "thinking": if thinking_enabled: final_thinking += ctext elif ctype == "text": final_text += ctext delta_obj = {} if not first_chunk_sent: delta_obj["role"] = "assistant" first_chunk_sent = True if ctype == "thinking": if thinking_enabled: delta_obj["reasoning_content"] = ctext elif ctype == "text": delta_obj["content"] = ctext if delta_obj: new_choices.append( { "delta": delta_obj, "index": choice.get("index", 0), } ) if new_choices: out_chunk = { "id": completion_id, "object": "chat.completion.chunk", "created": created_time, "model": model, "choices": new_choices, } yield f"data: {json.dumps(out_chunk, ensure_ascii=False)}\n\n" last_send_time = current_time except queue.Empty: continue except Exception as e: app.logger.error(f"[sse_stream] 异常: {e}") finally: deepseek_resp.close() if g.use_config_token: release_account(g.account) return Response(stream_with_context(sse_stream()), content_type="text/event-stream") else: # 非流式响应处理 think_list = [] text_list = [] result = None citation_map = {} # 用于存储引用链接的字典 data_queue = queue.Queue() def collect_data(): nonlocal result try: for raw_line in deepseek_resp.iter_lines(): try: line = raw_line.decode("utf-8") except Exception as e: app.logger.warning(f"[chat_completions] 解码失败: {e}") ctext = '服务器繁忙,请稍候再试' text_list.append(ctext) data_queue.put(None) break if not line: continue if line.startswith("data:"): data_str = line[5:].strip() if data_str == "[DONE]": data_queue.put(None) break try: chunk = json.loads(data_str) if chunk.get("choices", [{}])[0].get("delta", {}).get("type") == "search_index": search_indexes = chunk["choices"][0]["delta"].get("search_indexes", []) for idx in search_indexes: citation_map[str(idx.get("cite_index"))] = idx.get("url", "") continue for choice in chunk.get("choices", []): delta = choice.get("delta", {}) ctype = delta.get("type") ctext = delta.get("content", "") if choice.get("finish_reason") == "backend_busy": ctext = '服务器繁忙,请稍候再试' if search_enabled and ctext.startswith("[citation:"): ctext = "" if ctype == "thinking" and thinking_enabled: think_list.append(ctext) elif ctype == "text": text_list.append(ctext) except Exception as e: app.logger.warning(f"[collect_data] 无法解析: {data_str}, 错误: {e}") ctext = '服务器繁忙,请稍候再试' text_list.append(ctext) data_queue.put(None) break except Exception as e: app.logger.warning(f"[collect_data] 错误: {e}") ctext = '服务器繁忙,请稍候再试' text_list.append(ctext) data_queue.put(None) finally: deepseek_resp.close() final_reasoning = "".join(think_list) final_content = "".join(text_list) prompt_tokens = len(tokenizer.encode(final_prompt)) completion_tokens = len(tokenizer.encode(final_content)) result = { "id": completion_id, "object": "chat.completion", "created": created_time, "model": model, "choices": [ { "index": 0, "message": { "role": "assistant", "content": final_content, "reasoning_content": final_reasoning, }, "finish_reason": "stop", } ], "usage": { "prompt_tokens": prompt_tokens, "completion_tokens": completion_tokens, "total_tokens": prompt_tokens + completion_tokens, }, } data_queue.put("DONE") collect_thread = threading.Thread(target=collect_data) collect_thread.start() def generate(): last_send_time = time.time() while True: current_time = time.time() if current_time - last_send_time >= KEEP_ALIVE_TIMEOUT: yield "" last_send_time = current_time if not collect_thread.is_alive() and result is not None: yield json.dumps(result) break time.sleep(0.1) return Response(generate(), mimetype="application/json") except Exception as e: app.logger.error(f"[chat_completions] 未知异常: {e}") return jsonify({"error": "Internal Server Error"}), 500 finally: if g.use_config_token: release_account(g.account) # ---------------------------------------------------------------------- # (11) 路由:/ # ---------------------------------------------------------------------- @app.route("/") def index(): return render_template("welcome.html") # ---------------------------------------------------------------------- # 启动 Flask 应用(直接使用 Flask 内置服务器) # ---------------------------------------------------------------------- if __name__ == "__main__": app.run(host="0.0.0.0", port=7860, debug=False)