app.py

import os
import time
import logging
import requests
import json
import concurrent.futures
import threading
from datetime import datetime, timedelta
from apscheduler.schedulers.background import BackgroundScheduler
from flask import Flask, request, jsonify, Response, stream_with_context

os.environ['TZ'] = 'Asia/Shanghai'
time.tzset()

logging.basicConfig(level=logging.INFO,
                    format='%(asctime)s - %(levelname)s - %(message)s')

API_ENDPOINT = "https://api.deepseek.com/user/balance"
TEST_MODEL_ENDPOINT = "https://api.deepseek.com/v1/chat/completions"
MODELS_ENDPOINT = "https://api.deepseek.com/models"

app = Flask(__name__)

text_models = []

invalid_keys_global = []
valid_keys_global = []

executor = concurrent.futures.ThreadPoolExecutor(max_workers=10000)
model_key_indices = {}

request_timestamps = []
token_counts = []
data_lock = threading.Lock()

def get_credit_summary(api_key):
    headers = {
        "Authorization": f"Bearer {api_key}",
        "Content-Type": "application/json"
    }
    try:
        response = requests.get(API_ENDPOINT, headers=headers)
        response.raise_for_status()
        data = response.json()
        if not data.get("is_available", False):
            logging.warning(f"API Key: {api_key} is not available.")
            return None
      
        balance_infos = data.get("balance_infos", [])
        total_balance_cny = 0.0
        usd_balance = 0.0
        for balance_info in balance_infos:
            currency = balance_info.get("currency")
            total_balance = float(balance_info.get("total_balance", 0))

            if currency == "CNY":
                total_balance_cny += total_balance
            elif currency == "USD":
                usd_balance = total_balance

        try:
            exchange_rate = get_usd_to_cny_rate()
            if exchange_rate is not None:
                total_balance_cny += usd_balance * exchange_rate
                logging.info(f"获取美元兑人民币汇率成功，API Key：{api_key}，当前总额度(CNY): {total_balance_cny}")
            else:
                logging.warning(f"获取美元兑人民币汇率失败，无法转换美元余额，API Key：{api_key}")
                total_balance_cny += usd_balance * 7.2
        except Exception as e:
            logging.error(f"获取美元兑人民币汇率失败，API Key：{api_key}，错误信息：{e}")
            total_balance_cny += usd_balance * 7.2 

        return {"total_balance": float(total_balance_cny)}
    except requests.exceptions.RequestException as e:
        logging.error(f"获取额度信息失败，API Key：{api_key}，错误信息：{e}")
        return None
    except Exception as e:
        logging.error(f"处理额度信息失败，API Key：{api_key}，错误信息：{e}")
        return None

def get_usd_to_cny_rate():
    try:
        response = requests.get("https://api.exchangerate-api.com/v4/latest/USD")
        response.raise_for_status()
        data = response.json()
        return data.get("rates", {}).get("CNY")
    except requests.exceptions.RequestException as e:
        logging.error(f"获取美元兑人民币汇率失败，错误信息：{e}")
        return None

def refresh_models():
    text_models = ["deepseek-chat", "deepseek-reasoner"]
    logging.info(f"所有文本模型列表：{text_models}")

def load_keys():
    keys_str = os.environ.get("KEYS")
    keys = [key.strip() for key in keys_str.split(',')]
    unique_keys = list(set(keys))
    keys_str = ','.join(unique_keys) 
    os.environ["KEYS"] = keys_str

    logging.info(f"加载的 keys：{unique_keys}")

    with concurrent.futures.ThreadPoolExecutor(
        max_workers=10000
    ) as executor:
        future_to_key = {
            executor.submit(
                process_key, key
            ): key for key in unique_keys
        }

        invalid_keys = []
        valid_keys = []

        for future in concurrent.futures.as_completed(
            future_to_key
        ):
            key = future_to_key[future]
            try:
                key_type = future.result()
                if key_type == "invalid":
                    invalid_keys.append(key)
                elif key_type == "valid":
                    valid_keys.append(key)
            except Exception as exc:
                logging.error(f"处理 KEY {key} 生成异常: {exc}")

    logging.info(f"无效 KEY：{invalid_keys}")
    logging.info(f"有效 KEY：{valid_keys}")

    global invalid_keys_global, valid_keys_global
    invalid_keys_global = invalid_keys
    valid_keys_global = valid_keys

def process_key(key):
    credit_summary = get_credit_summary(key)
    if credit_summary is None:
        return "invalid"
    else:
        total_balance = credit_summary.get("total_balance", 0)
        if total_balance <= 0:
            return "invalid"
        else:
            return "valid"

def select_key(model_name):
    available_keys = valid_keys_global

    current_index = model_key_indices.get(model_name, 0)

    for _ in range(len(available_keys)):
        key = available_keys[current_index % len(available_keys)]
        current_index += 1
        model_key_indices[model_name] = current_index
        return key

    model_key_indices[model_name] = 0
    return None

def check_authorization(request):
    authorization_key = os.environ.get("AUTHORIZATION_KEY")
    if not authorization_key:
        logging.warning("环境变量 AUTHORIZATION_KEY 未设置，请设置后重试。")
        return False

    auth_header = request.headers.get('Authorization')
    if not auth_header:
        logging.warning("请求头中缺少 Authorization 字段。")
        return False

    if auth_header != f"Bearer {authorization_key}":
        logging.warning(f"无效的 Authorization 密钥：{auth_header}")
        return False

    return True

scheduler = BackgroundScheduler()
scheduler.add_job(load_keys, 'interval', hours=1)
scheduler.remove_all_jobs()

@app.route('/')
def index():
    current_time = time.time()
    one_minute_ago = current_time - 60

    with data_lock:
        while request_timestamps and request_timestamps[0] < one_minute_ago:
            request_timestamps.pop(0)
            token_counts.pop(0)

        rpm = len(request_timestamps)
        tpm = sum(token_counts)

    return jsonify({"rpm": rpm, "tpm": tpm})
          
@app.route('/handsome/v1/models', methods=['GET'])
def list_models():
    if not check_authorization(request):
        return jsonify({"error": "Unauthorized"}), 401
  
    detailed_models = [
        {
            "id": "deepseek-chat",
            "object": "model",
            "created": 1678888888,
            "owned_by": "openai",
            "root": "deepseek-chat",
            "parent": None
        },
        {
            "id": "deepseek-reasoner",
            "object": "model",
            "created": 1678888889,
            "owned_by": "openai",
            "root": "deepseek-reasoner",
            "parent": None
        },
        {
            "id": "deepseek-reasoner-thinking",
            "object": "model",
            "created": 1678888889,
            "owned_by": "openai",
            "root": "deepseek-reasoner",
            "parent": None
        },
        {
            "id": "deepseek-reasoner-openwebui",
            "object": "model",
            "created": 1678888889,
            "owned_by": "openai",
            "root": "deepseek-reasoner",
            "parent": None
        }
    ]

    return jsonify({
        "success": True,
        "data": detailed_models
    })

def get_billing_info():
    keys = valid_keys_global
    total_balance = 0

    with concurrent.futures.ThreadPoolExecutor(
        max_workers=10000
    ) as executor:
        futures = [
            executor.submit(get_credit_summary, key) for key in keys
        ]

        for future in concurrent.futures.as_completed(futures):
            try:
                credit_summary = future.result()
                if credit_summary:
                    total_balance += credit_summary.get(
                        "total_balance",
                        0
                    )
            except Exception as exc:
                logging.error(f"获取额度信息生成异常: {exc}")

    return total_balance

@app.route('/handsome/v1/dashboard/billing/usage', methods=['GET'])
def billing_usage():
    if not check_authorization(request):
        return jsonify({"error": "Unauthorized"}), 401

    end_date = datetime.now()
    start_date = end_date - timedelta(days=30)

    daily_usage = []
    current_date = start_date
    while current_date <= end_date:
        daily_usage.append({
            "timestamp": int(current_date.timestamp()),
            "daily_usage": 0
        })
        current_date += timedelta(days=1)

    return jsonify({
        "object": "list",
        "data": daily_usage,
        "total_usage": 0
    })

@app.route('/handsome/v1/dashboard/billing/subscription', methods=['GET'])
def billing_subscription():
    if not check_authorization(request):
        return jsonify({"error": "Unauthorized"}), 401

    total_balance = get_billing_info()

    return jsonify({
        "object": "billing_subscription",
        "has_payment_method": False,
        "canceled": False,
        "canceled_at": None,
        "delinquent": None,
        "access_until": int(datetime(9999, 12, 31).timestamp()),
        "soft_limit": 0,
        "hard_limit": total_balance,
        "system_hard_limit": total_balance,
        "soft_limit_usd": 0,
        "hard_limit_usd": total_balance,
        "system_hard_limit_usd": total_balance,
        "plan": {
            "name": "SiliconFlow API",
            "id": "siliconflow-api"
        },
        "account_name": "SiliconFlow User",
        "po_number": None,
        "billing_email": None,
        "tax_ids": [],
        "billing_address": None,
        "business_address": None
    })

@app.route('/handsome/v1/chat/completions', methods=['POST'])
def handsome_chat_completions():
    if not check_authorization(request):
        return jsonify({"error": "Unauthorized"}), 401

    data = request.get_json()
    if not data or 'model' not in data:
        return jsonify({"error": "Invalid request data"}), 400

    model_name = data['model']
    if model_name == "deepseek-reasoner-thinking" or model_name == "deepseek-reasoner-openwebui":
        model_realname = "deepseek-reasoner"
    else:
        model_realname = model_name

    data['model'] = model_realname

    api_key = select_key(model_realname)

    if not api_key:
        return jsonify(
            {
                "error": (
                    "No available API key for this "
                    "request type or all keys have "
                    "reached their limits"
                )
            }
        ), 429

    headers = {
        "Authorization": f"Bearer {api_key}",
        "Content-Type": "application/json"
    }

    try:
        start_time = time.time()
        response = requests.post(
            TEST_MODEL_ENDPOINT,
            headers=headers,
            json=data,
            stream=data.get("stream", False),
            timeout=120
        )

        if response.status_code == 429:
            return jsonify(response.json()), 429

        if data.get("stream", False):
            def generate():
                if model_name == "deepseek-reasoner": 
                    first_chunk_time = None
                    full_response_content = ""
                    for chunk in response.iter_content(chunk_size=2048):
                        if chunk:
                            if first_chunk_time is None:
                                first_chunk_time = time.time()
                            full_response_content += chunk.decode("utf-8")
                            yield chunk

                    end_time = time.time()
                    first_token_time = (
                        first_chunk_time - start_time
                        if first_chunk_time else 0
                    )
                    total_time = end_time - start_time

                    prompt_tokens = 0
                    completion_tokens = 0
                    response_content = ""
                    for line in full_response_content.splitlines():
                        if line.startswith("data:"):
                            line = line[5:].strip()
                            if line == "[DONE]":
                                continue
                            try:
                                response_json = json.loads(line)

                                if (
                                    "usage" in response_json and
                                    "completion_tokens" in response_json["usage"]
                                ):
                                    completion_tokens = response_json[
                                        "usage"
                                    ]["completion_tokens"]

                                if (
                                    "choices" in response_json and
                                    len(response_json["choices"]) > 0 and
                                    "delta" in response_json["choices"][0] and
                                    "content" in response_json[
                                        "choices"
                                    ][0]["delta"]
                                ):
                                    response_content += response_json[
                                        "choices"
                                    ][0]["delta"]["content"]

                                if (
                                    "usage" in response_json and
                                    "prompt_tokens" in response_json["usage"]
                                ):
                                    prompt_tokens = response_json[
                                        "usage"
                                    ]["prompt_tokens"]

                            except (
                                KeyError,
                                ValueError,
                                IndexError
                            ) as e:
                                logging.error(
                                    f"解析流式响应单行 JSON 失败: {e}, "
                                    f"行内容: {line}"
                                )

                    user_content = extract_user_content(data.get("messages", []))

                    user_content_replaced = user_content.replace(
                        '\n', '\\n'
                    ).replace('\r', '\\n')
                    response_content_replaced = response_content.replace(
                        '\n', '\\n'
                    ).replace('\r', '\\n')

                    logging.info(
                        f"使用的key: {api_key}, "
                        f"提示token: {prompt_tokens}, "
                        f"输出token: {completion_tokens}, "
                        f"首字用时: {first_token_time:.4f}秒, "
                        f"总共用时: {total_time:.4f}秒, "
                        f"使用的模型: {model_name}, "
                        f"用户的内容: {user_content_replaced}, "
                        f"输出的内容: {response_content_replaced}"
                    )

                    with data_lock:
                        request_timestamps.append(time.time())
                        token_counts.append(prompt_tokens+completion_tokens)
                        request_timestamps_day.append(time.time())
                        token_counts_day.append(prompt_tokens+completion_tokens)

                    return Response(
                        stream_with_context(generate()),
                        content_type=response.headers['Content-Type']
                    )

                if model_name == "deepseek-reasoner-openwebui": 
                    first_chunk_time = None
                    full_response_content = ""
                    reasoning_content_accumulated = ""
                    content_accumulated = ""
                    first_reasoning_chunk = True
                    
                    for chunk in response.iter_lines():
                        if chunk:
                            if first_chunk_time is None:
                                first_chunk_time = time.time()
                            full_response_content += chunk.decode("utf-8")
                            
                            for line in chunk.decode("utf-8").splitlines():
                                if line.startswith("data:"):
                                    try:
                                        chunk_json = json.loads(line.lstrip("data: ").strip())
                                        if "choices" in chunk_json and len(chunk_json["choices"]) > 0:
                                            delta = chunk_json["choices"][0].get("delta", {})
                                            
                                            if delta.get("reasoning_content") is not None:
                                                reasoning_chunk = delta["reasoning_content"]
                                                if first_reasoning_chunk:
                                                    think_chunk = f"<"
                                                    yield f"data: {json.dumps({'choices': [{'delta': {'content': think_chunk}, 'index': 0}]})}\n\n"
                                                    think_chunk = f"think"
                                                    yield f"data: {json.dumps({'choices': [{'delta': {'content': think_chunk}, 'index': 0}]})}\n\n"
                                                    think_chunk = f">\n"
                                                    yield f"data: {json.dumps({'choices': [{'delta': {'content': think_chunk}, 'index': 0}]})}\n\n"
                                                    first_reasoning_chunk = False
                                                yield f"data: {json.dumps({'choices': [{'delta': {'content': reasoning_chunk}, 'index': 0}]})}\n\n"
                                                
                                            if delta.get("content") is not None:
                                                if not first_reasoning_chunk:
                                                    reasoning_chunk = f"\n</think>\n"
                                                    yield f"data: {json.dumps({'choices': [{'delta': {'content': reasoning_chunk}, 'index': 0}]})}\n\n"
                                                    first_reasoning_chunk = True
                                                yield f"data: {json.dumps({'choices': [{'delta': {'content': delta["content"]}, 'index': 0}]})}\n\n"

                                    except (KeyError, ValueError, json.JSONDecodeError) as e:
                                        continue

                    end_time = time.time()
                    first_token_time = (
                        first_chunk_time - start_time
                        if first_chunk_time else 0
                    )
                    total_time = end_time - start_time

                    prompt_tokens = 0
                    completion_tokens = 0
                    for line in full_response_content.splitlines():
                        if line.startswith("data:"):
                            line = line[5:].strip()
                            if line == "[DONE]":
                                continue
                            try:
                                response_json = json.loads(line)

                                if (
                                    "usage" in response_json and
                                    "completion_tokens" in response_json["usage"]
                                ):
                                    completion_tokens += response_json[
                                        "usage"
                                    ]["completion_tokens"]
                                if (
                                    "usage" in response_json and
                                    "prompt_tokens" in response_json["usage"]
                                ):
                                    prompt_tokens = response_json[
                                        "usage"
                                    ]["prompt_tokens"]

                            except (
                                KeyError,
                                ValueError,
                                IndexError
                            ) as e:
                                logging.error(
                                    f"解析流式响应单行 JSON 失败: {e}, "
                                    f"行内容: {line}"
                                )

                    user_content = ""
                    messages = data.get("messages", [])
                    for message in messages:
                        if message["role"] == "user":
                            if isinstance(message["content"], str):
                                user_content += message["content"] + " "
                            elif isinstance(message["content"], list):
                                for item in message["content"]:
                                    if (
                                        isinstance(item, dict) and
                                        item.get("type") == "text"
                                    ):
                                        user_content += (
                                            item.get("text", "") +
                                            " "
                                        )

                    user_content = user_content.strip()

                    user_content_replaced = user_content.replace(
                        '\n', '\\n'
                    ).replace('\r', '\\n')
                    response_content_replaced = (f"```Thinking\n{reasoning_content_accumulated}\n```\n" if reasoning_content_accumulated else "") + content_accumulated
                    response_content_replaced = response_content_replaced.replace(
                        '\n', '\\n'
                    ).replace('\r', '\\n')

                    logging.info(
                        f"使用的key: {api_key}, "
                        f"提示token: {prompt_tokens}, "
                        f"输出token: {completion_tokens}, "
                        f"首字用时: {first_token_time:.4f}秒, "
                        f"总共用时: {total_time:.4f}秒, "
                        f"使用的模型: {model_name}, "
                        f"用户的内容: {user_content_replaced}, "
                        f"输出的内容: {response_content_replaced}"
                    )

                    with data_lock:
                        request_timestamps.append(time.time())
                        token_counts.append(prompt_tokens + completion_tokens)

                    yield "data: [DONE]\n\n"

                    return Response(
                        stream_with_context(generate()),
                        content_type="text/event-stream"
                    )

                first_chunk_time = None
                full_response_content = ""
                reasoning_content_accumulated = ""
                content_accumulated = ""
                first_reasoning_chunk = True
                
                for chunk in response.iter_lines():
                    if chunk:
                        if first_chunk_time is None:
                            first_chunk_time = time.time()
                        full_response_content += chunk.decode("utf-8")
                        
                        for line in chunk.decode("utf-8").splitlines():
                            if line.startswith("data:"):
                                try:
                                    chunk_json = json.loads(line.lstrip("data: ").strip())
                                    if "choices" in chunk_json and len(chunk_json["choices"]) > 0:
                                        delta = chunk_json["choices"][0].get("delta", {})
                                        
                                        if delta.get("reasoning_content") is not None:
                                            reasoning_chunk = delta["reasoning_content"]
                                            reasoning_chunk = reasoning_chunk.replace('\n', '\n> ')
                                            if first_reasoning_chunk:
                                                reasoning_chunk = "> " + reasoning_chunk
                                                first_reasoning_chunk = False
                                            yield f"data: {json.dumps({'choices': [{'delta': {'content': reasoning_chunk}, 'index': 0}]})}\n\n"
                                            
                                        if delta.get("content") is not None:
                                            if not first_reasoning_chunk:
                                                yield f"data: {json.dumps({'choices': [{'delta': {'content': '\n\n'}, 'index': 0}]})}\n\n"
                                                first_reasoning_chunk = True
                                            yield f"data: {json.dumps({'choices': [{'delta': {'content': delta["content"]}, 'index': 0}]})}\n\n"

                                except (KeyError, ValueError, json.JSONDecodeError) as e:
                                    # logging.error(f"解析流式响应单行 JSON 失败: {e}, 行内容: {line}")
                                    continue

                end_time = time.time()
                first_token_time = (
                    first_chunk_time - start_time
                    if first_chunk_time else 0
                )
                total_time = end_time - start_time

                prompt_tokens = 0
                completion_tokens = 0
                for line in full_response_content.splitlines():
                    if line.startswith("data:"):
                        line = line[5:].strip()
                        if line == "[DONE]":
                            continue
                        try:
                            response_json = json.loads(line)

                            if (
                                "usage" in response_json and
                                "completion_tokens" in response_json["usage"]
                            ):
                                completion_tokens += response_json[
                                    "usage"
                                ]["completion_tokens"]
                            if (
                                "usage" in response_json and
                                "prompt_tokens" in response_json["usage"]
                            ):
                                prompt_tokens = response_json[
                                    "usage"
                                ]["prompt_tokens"]

                        except (
                            KeyError,
                            ValueError,
                            IndexError
                        ) as e:
                            logging.error(
                                f"解析流式响应单行 JSON 失败: {e}, "
                                f"行内容: {line}"
                            )

                user_content = ""
                messages = data.get("messages", [])
                for message in messages:
                    if message["role"] == "user":
                        if isinstance(message["content"], str):
                            user_content += message["content"] + " "
                        elif isinstance(message["content"], list):
                            for item in message["content"]:
                                if (
                                    isinstance(item, dict) and
                                    item.get("type") == "text"
                                ):
                                    user_content += (
                                        item.get("text", "") +
                                        " "
                                    )

                user_content = user_content.strip()

                user_content_replaced = user_content.replace(
                    '\n', '\\n'
                ).replace('\r', '\\n')
                response_content_replaced = (f"```Thinking\n{reasoning_content_accumulated}\n```\n" if reasoning_content_accumulated else "") + content_accumulated
                response_content_replaced = response_content_replaced.replace(
                    '\n', '\\n'
                ).replace('\r', '\\n')

                logging.info(
                    f"使用的key: {api_key}, "
                    f"提示token: {prompt_tokens}, "
                    f"输出token: {completion_tokens}, "
                    f"首字用时: {first_token_time:.4f}秒, "
                    f"总共用时: {total_time:.4f}秒, "
                    f"使用的模型: {model_name}, "
                    f"用户的内容: {user_content_replaced}, "
                    f"输出的内容: {response_content_replaced}"
                )

                with data_lock:
                    request_timestamps.append(time.time())
                    token_counts.append(prompt_tokens + completion_tokens)

                yield "data: [DONE]\n\n"

            return Response(
                stream_with_context(generate()),
                content_type="text/event-stream"
            )
        else:
            response.raise_for_status()
            end_time = time.time()
            response_json = response.json()
            total_time = end_time - start_time

            try:
                prompt_tokens = response_json["usage"]["prompt_tokens"]
                completion_tokens = response_json["usage"]["completion_tokens"]
                response_content = ""

                if model_name == "deepseek-reasoner-thinking" and "choices" in response_json and len(response_json["choices"]) > 0:
                    choice = response_json["choices"][0]
                    if "message" in choice:
                        if "reasoning_content" in choice["message"]:
                            reasoning_content = choice["message"]["reasoning_content"]
                            reasoning_content = reasoning_content.replace('\n', '\n> ')
                            reasoning_content = '> ' + reasoning_content
                            formatted_reasoning = f"{reasoning_content}\n"
                            response_content += formatted_reasoning + "\n"
                        if "content" in choice["message"]:
                            response_content += choice["message"]["content"]
                elif model_name == "deepseek-reasoner-openwebui" and "choices" in response_json and len(response_json["choices"]) > 0:
                    choice = response_json["choices"][0]
                    if "message" in choice:
                        if "reasoning_content" in choice["message"]:
                            reasoning_content = choice["message"]["reasoning_content"]
                            response_content += f"<think>\n{reasoning_content}\n</think>\n"
                        if "content" in choice["message"]:
                            response_content += choice["message"]["content"]
                elif "choices" in response_json and len(response_json["choices"]) > 0:
                    response_content = response_json["choices"][0]["message"]["content"]

            except (KeyError, ValueError, IndexError) as e:
                logging.error(
                    f"解析非流式响应 JSON 失败: {e}, "
                    f"完整内容: {response_json}"
                )
                prompt_tokens = 0
                completion_tokens = 0
                response_content = ""

            user_content = ""
            messages = data.get("messages", [])
            for message in messages:
                if message["role"] == "user":
                    if isinstance(message["content"], str):
                        user_content += message["content"] + " "
                    elif isinstance(message["content"], list):
                        for item in message["content"]:
                            if (
                                isinstance(item, dict) and
                                item.get("type") == "text"
                            ):
                                user_content += (
                                    item.get("text", "") +
                                    " "
                                )

            user_content = user_content.strip()

            user_content_replaced = user_content.replace(
                '\n', '\\n'
            ).replace('\r', '\\n')
            response_content_replaced = response_content.replace(
                '\n', '\\n'
            ).replace('\r', '\\n')

            logging.info(
                f"使用的key: {api_key}, "
                f"提示token: {prompt_tokens}, "
                f"输出token: {completion_tokens}, "
                f"首字用时: 0, "
                f"总共用时: {total_time:.4f}秒, "
                f"使用的模型: {model_name}, "
                f"用户的内容: {user_content_replaced}, "
                f"输出的内容: {response_content_replaced}"
            )
            with data_lock:
                request_timestamps.append(time.time())
                token_counts.append(prompt_tokens + completion_tokens)

            formatted_response = {
                "id": response_json.get("id", ""),
                "object": "chat.completion",
                "created": response_json.get("created", int(time.time())),
                "model": model_name,
                "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
                }
            }

            if model_name == "deepseek-reasoner":
                formatted_response = response_json

            return jsonify(formatted_response)

    except requests.exceptions.RequestException as e:
        logging.error(f"请求转发异常: {e}")
        return jsonify({"error": str(e)}), 500

if __name__ == '__main__':
    logging.info(f"环境变量：{os.environ}")

    invalid_keys_global = []
    valid_keys_global = []

    load_keys()
    logging.info("程序启动时首次加载 keys 已执行")

    scheduler.start()

    logging.info("首次加载 keys 已手动触发执行")

    refresh_models()
    logging.info("首次刷新模型列表已手动触发执行")

    app.run(
        debug=False,
        host='0.0.0.0',
        port=int(os.environ.get('PORT', 7860))
    )