feat: 实现 OpenAI 兼容 API 端点和批量代理删除

新增与 OpenAI 规范兼容的 API 端点:
- `/openai/v1/models`
- `/openai/v1/chat/completions` (支持流式传输、重试和密钥切换)
- `/openai/v1/embeddings`
- `/openai/v1/images/generations`

包含:
- 在 `app/router/openai_compatiable_routes.py` 中新增路由。
- `OpenAICompatiableService` 用于处理请求逻辑、日志记录和错误管理。
- 更新 `OpenaiApiClient` 以支持新方法和代理使用。
- 修改 `app/domain/openai_models.py` 以实现兼容性。
- 为新 API 添加专用日志记录器 (`openai_compatible`)。
- 为新路由 (`/openai`, `/api/version/check`) 添加认证中间件豁免。

增强配置编辑器 UI:
- 在 `app/static/js/config_editor.js` 和 `app/templates/config_editor.html` 中添加批量代理删除功能。
This commit is contained in:
snaily
2025-04-30 20:39:47 +08:00
parent 7da9110704
commit 83ce50975a
9 changed files with 562 additions and 22 deletions
+97 -4
View File
@@ -47,9 +47,9 @@ class GeminiApiClient(ApiClient):
proxy_to_use = None
if settings.PROXIES:
proxy_to_use = random.choice(settings.PROXIES)
logger.info(f"using proxy: {proxy_to_use}")
logger.info(f"Using proxy: {proxy_to_use}")
async with httpx.AsyncClient(timeout=timeout, proxy=proxy_to_use) as client: # 修改:直接传递代理字符串
async with httpx.AsyncClient(timeout=timeout, proxy=proxy_to_use) as client:
url = f"{self.base_url}/models/{model}:generateContent?key={api_key}"
response = await client.post(url, json=payload)
if response.status_code != 200:
@@ -64,9 +64,9 @@ class GeminiApiClient(ApiClient):
proxy_to_use = None
if settings.PROXIES:
proxy_to_use = random.choice(settings.PROXIES)
logger.info(f"using proxy: {proxy_to_use}")
logger.info(f"Using proxy: {proxy_to_use}")
async with httpx.AsyncClient(timeout=timeout, proxy=proxy_to_use) as client: # 修改:直接传递代理字符串
async with httpx.AsyncClient(timeout=timeout, proxy=proxy_to_use) as client:
url = f"{self.base_url}/models/{model}:streamGenerateContent?alt=sse&key={api_key}"
async with client.stream(method="POST", url=url, json=payload) as response:
if response.status_code != 200:
@@ -75,3 +75,96 @@ class GeminiApiClient(ApiClient):
raise Exception(f"API call failed with status code {response.status_code}, {error_msg}")
async for line in response.aiter_lines():
yield line
class OpenaiApiClient(ApiClient):
"""OpenAI API客户端"""
def __init__(self, base_url: str, timeout: int = DEFAULT_TIMEOUT):
self.base_url = base_url
self.timeout = timeout
async def get_models(self, api_key: str) -> Dict[str, Any]:
timeout = httpx.Timeout(self.timeout, read=self.timeout)
async with httpx.AsyncClient(timeout=timeout) as client:
url = f"{self.base_url}/openai/models"
headers = {"Authorization": f"Bearer {api_key}"}
response = await client.get(url, headers=headers)
if response.status_code != 200:
error_content = response.text
raise Exception(f"API call failed with status code {response.status_code}, {error_content}")
return response.json()
async def generate_content(self, payload: Dict[str, Any], api_key: str) -> Dict[str, Any]:
timeout = httpx.Timeout(self.timeout, read=self.timeout)
proxy_to_use = None
if settings.PROXIES:
proxy_to_use = random.choice(settings.PROXIES)
logger.info(f"Using proxy: {proxy_to_use}")
async with httpx.AsyncClient(timeout=timeout, proxy=proxy_to_use) as client:
url = f"{self.base_url}/openai/chat/completions"
headers = {"Authorization": f"Bearer {api_key}"}
response = await client.post(url, json=payload, headers=headers)
if response.status_code != 200:
error_content = response.text
raise Exception(f"API call failed with status code {response.status_code}, {error_content}")
return response.json()
async def stream_generate_content(self, payload: Dict[str, Any], api_key: str) -> AsyncGenerator[str, None]:
timeout = httpx.Timeout(self.timeout, read=self.timeout)
proxy_to_use = None
if settings.PROXIES:
proxy_to_use = random.choice(settings.PROXIES)
logger.info(f"Using proxy: {proxy_to_use}")
async with httpx.AsyncClient(timeout=timeout, proxy=proxy_to_use) as client:
url = f"{self.base_url}/openai/chat/completions"
headers = {"Authorization": f"Bearer {api_key}"}
async with client.stream(method="POST", url=url, json=payload, headers=headers) as response:
if response.status_code != 200:
error_content = await response.aread()
error_msg = error_content.decode("utf-8")
raise Exception(f"API call failed with status code {response.status_code}, {error_msg}")
async for line in response.aiter_lines():
yield line
async def create_embeddings(self, input: str, model: str, api_key: str) -> Dict[str, Any]:
timeout = httpx.Timeout(self.timeout, read=self.timeout)
proxy_to_use = None
if settings.PROXIES:
proxy_to_use = random.choice(settings.PROXIES)
logger.info(f"Using proxy: {proxy_to_use}")
async with httpx.AsyncClient(timeout=timeout, proxy=proxy_to_use) as client:
url = f"{self.base_url}/openai/embeddings"
headers = {"Authorization": f"Bearer {api_key}"}
payload = {
"input": input,
"model": model,
}
response = await client.post(url, json=payload, headers=headers)
if response.status_code != 200:
error_content = response.text
raise Exception(f"API call failed with status code {response.status_code}, {error_content}")
return response.json()
async def generate_images(self, payload: Dict[str, Any], api_key: str) -> Dict[str, Any]:
timeout = httpx.Timeout(self.timeout, read=self.timeout)
proxy_to_use = None
if settings.PROXIES:
proxy_to_use = random.choice(settings.PROXIES)
logger.info(f"Using proxy: {proxy_to_use}")
async with httpx.AsyncClient(timeout=timeout, proxy=proxy_to_use) as client:
url = f"{self.base_url}/openai/images/generations"
headers = {"Authorization": f"Bearer {api_key}"}
response = await client.post(url, json=payload, headers=headers)
if response.status_code != 200:
error_content = response.text
raise Exception(f"API call failed with status code {response.status_code}, {error_content}")
return response.json()
+197
View File
@@ -0,0 +1,197 @@
import datetime
import json
import re
import time
from typing import Any, AsyncGenerator, Dict, Union
from app.config.config import settings
from app.database.services import (
add_error_log,
add_request_log,
)
from app.domain.openai_models import ChatRequest, ImageGenerationRequest
from app.service.client.api_client import OpenaiApiClient
from app.service.key.key_manager import KeyManager
from app.log.logger import get_openai_compatible_logger
logger = get_openai_compatible_logger()
class OpenAICompatiableService:
def __init__(self, base_url: str, key_manager: KeyManager = None):
self.key_manager = key_manager
self.base_url = base_url
self.api_client = OpenaiApiClient(base_url, settings.TIME_OUT)
async def get_models(self, api_key: str) -> Dict[str, Any]:
return await self.api_client.get_models(api_key)
async def create_chat_completion(
self,
request: ChatRequest,
api_key: str,
) -> Union[Dict[str, Any], AsyncGenerator[str, None]]:
"""创建聊天完成"""
request_dict = request.model_dump()
# 移除值为null的
request_dict = {k: v for k, v in request_dict.items() if v is not None}
del request_dict["top_k"] # 删除top_k参数,目前不支持该参数
if request.stream:
return self._handle_stream_completion(request.model, request_dict, api_key)
return await self._handle_normal_completion(request.model, request_dict, api_key)
async def generate_images(
self,
request: ImageGenerationRequest,
) -> Dict[str, Any]:
"""生成图片"""
request_dict = request.model_dump()
# 移除值为null的
request_dict = {k: v for k, v in request_dict.items() if v is not None}
api_key = settings.PAID_KEY
return await self.api_client.generate_images(request_dict, api_key)
async def create_embeddings(
self,
input_text: str,
model: str,
api_key: str,
) -> Dict[str, Any]:
"""创建嵌入"""
return await self.api_client.create_embeddings(input_text, model, api_key)
async def _handle_normal_completion(
self, model: str, request: dict, api_key: str
) -> Dict[str, Any]:
"""处理普通聊天完成"""
start_time = time.perf_counter()
request_datetime = datetime.datetime.now()
is_success = False
status_code = None
response = None
try:
response = await self.api_client.generate_content(request, api_key)
is_success = True
status_code = 200
return response
except Exception as e:
is_success = False
error_log_msg = str(e)
logger.error(f"Normal API call failed with error: {error_log_msg}")
# Try to parse status code from exception
match = re.search(r"status code (\d+)", error_log_msg)
if match:
status_code = int(match.group(1))
else:
status_code = 500
await add_error_log(
gemini_key=api_key,
model_name=model,
error_type="openai-compatiable-non-stream",
error_log=error_log_msg,
error_code=status_code,
request_msg=request,
)
raise e
finally:
end_time = time.perf_counter()
latency_ms = int((end_time - start_time) * 1000)
await add_request_log(
model_name=model,
api_key=api_key,
is_success=is_success,
status_code=status_code,
latency_ms=latency_ms,
request_time=request_datetime,
)
async def _handle_stream_completion(
self, model: str, payload: dict, api_key: str
) -> AsyncGenerator[str, None]:
"""处理流式聊天完成,添加重试逻辑"""
retries = 0
max_retries = settings.MAX_RETRIES
is_success = False
status_code = None
final_api_key = api_key
while retries < max_retries:
start_time = time.perf_counter()
request_datetime = datetime.datetime.now()
current_attempt_key = api_key
final_api_key = current_attempt_key
try:
async for line in self.api_client.stream_generate_content(
payload, current_attempt_key
):
if line.startswith("data:"):
# print(line)
yield line + "\n\n"
logger.info("Streaming completed successfully")
is_success = True
status_code = 200
break # 成功后退出循环
except Exception as e:
retries += 1
is_success = False
error_log_msg = str(e)
logger.warning(
f"Streaming API call failed with error: {error_log_msg}. Attempt {retries} of {max_retries}"
)
# Parse error code for logging
match = re.search(r"status code (\d+)", error_log_msg)
if match:
status_code = int(match.group(1))
else:
status_code = 500
# Log error to error log table
await add_error_log(
gemini_key=current_attempt_key,
model_name=model,
error_type="openai-compatiable-stream",
error_log=error_log_msg,
error_code=status_code,
request_msg=payload,
)
# Attempt to switch API Key
# Ensure key_manager is available (might need adjustment if not always passed)
if self.key_manager:
api_key = await self.key_manager.handle_api_failure(
current_attempt_key, retries
)
if api_key:
logger.info(f"Switched to new API key: {api_key}")
else:
logger.error(
f"No valid API key available after {retries} retries."
)
break
else:
logger.error("KeyManager not available for retry logic.")
break
if retries >= max_retries:
logger.error(f"Max retries ({max_retries}) reached for streaming.")
break
finally:
# Log the final outcome of the streaming request
end_time = time.perf_counter()
latency_ms = int((end_time - start_time) * 1000)
await add_request_log(
model_name=model,
api_key=final_api_key,
is_success=is_success,
status_code=status_code,
latency_ms=latency_ms,
request_time=request_datetime,
)
# If the loop finished due to failure, yield error and DONE
if not is_success and retries >= max_retries:
yield f"data: {json.dumps({'error': 'Streaming failed after retries'})}\n\n"
yield "data: [DONE]\n\n"