update
This commit is contained in:
392
backend/app/services/llm/qwen_client.py
Normal file
392
backend/app/services/llm/qwen_client.py
Normal file
@@ -0,0 +1,392 @@
|
||||
# src/services/llm/qwen_client.py
|
||||
"""Qwen LLM客户端 - 支持OpenAI兼容API格式"""
|
||||
|
||||
import time
|
||||
import json
|
||||
from typing import List, Dict, Optional, Generator, AsyncGenerator
|
||||
from loguru import logger
|
||||
import httpx
|
||||
|
||||
from .base_client import BaseLLMClient, LLMResponse, LLMConfig, LLMProvider
|
||||
|
||||
|
||||
class QwenClient(BaseLLMClient):
|
||||
"""
|
||||
Qwen API客户端（OpenAI兼容格式）
|
||||
|
||||
支持通过new-api等代理服务调用：
|
||||
- qwen-turbo
|
||||
- qwen-plus
|
||||
- qwen-max
|
||||
- qwen3.5-flash (推荐：快速响应)
|
||||
- qwen3.5-plus
|
||||
- qwen-long
|
||||
- qwen2.5系列
|
||||
"""
|
||||
|
||||
SUPPORTED_MODELS = [
|
||||
"qwen-turbo",
|
||||
"qwen-plus",
|
||||
"qwen-max",
|
||||
"qwen-max-longcontext",
|
||||
"qwen-long",
|
||||
"qwen3.5-flash",
|
||||
"qwen3.5-plus",
|
||||
"qwen3-plus",
|
||||
"qwen2.5-72b-instruct",
|
||||
"qwen2.5-32b-instruct",
|
||||
"qwen2.5-14b-instruct",
|
||||
"qwen2.5-7b-instruct"
|
||||
]
|
||||
|
||||
def __init__(self, config: LLMConfig):
|
||||
if config.provider not in [LLMProvider.QWEN, LLMProvider.QWEN_VL]:
|
||||
raise ValueError(f"配置provider应为Qwen，实际为{config.provider}")
|
||||
super().__init__(config)
|
||||
self._init_client()
|
||||
|
||||
def _init_client(self):
|
||||
"""初始化HTTP客户端"""
|
||||
# OpenAI兼容API格式
|
||||
self._client = httpx.Client(
|
||||
base_url=self.config.base_url,
|
||||
headers={
|
||||
"Authorization": f"Bearer {self.config.api_key}",
|
||||
"Content-Type": "application/json"
|
||||
},
|
||||
timeout=self.config.timeout
|
||||
)
|
||||
logger.info(f"Qwen客户端初始化完成: {self.config.base_url} - {self.config.model}")
|
||||
|
||||
def chat(
|
||||
self,
|
||||
messages: List[Dict[str, str]],
|
||||
max_tokens: Optional[int] = None,
|
||||
temperature: Optional[float] = None,
|
||||
**kwargs
|
||||
) -> LLMResponse:
|
||||
"""对话补全（OpenAI兼容格式）"""
|
||||
start_time = time.time()
|
||||
|
||||
try:
|
||||
# OpenAI兼容格式的请求体
|
||||
payload = {
|
||||
"model": self.config.model,
|
||||
"messages": messages,
|
||||
"max_tokens": max_tokens or self.config.max_tokens,
|
||||
"temperature": temperature or self.config.temperature,
|
||||
"top_p": kwargs.get("top_p", self.config.top_p),
|
||||
"stream": False
|
||||
}
|
||||
|
||||
# OpenAI兼容接口路径
|
||||
response = self._client.post("/chat/completions", json=payload)
|
||||
response.raise_for_status()
|
||||
|
||||
data = response.json()
|
||||
|
||||
latency_ms = int((time.time() - start_time) * 1000)
|
||||
|
||||
# OpenAI兼容格式的响应解析
|
||||
choices = data.get("choices", [{}])
|
||||
message = choices[0].get("message", {})
|
||||
|
||||
return LLMResponse(
|
||||
content=message.get("content", ""),
|
||||
model=data.get("model", self.config.model),
|
||||
usage=data.get("usage", {}),
|
||||
finish_reason=choices[0].get("finish_reason", "stop"),
|
||||
latency_ms=latency_ms
|
||||
)
|
||||
|
||||
except httpx.HTTPStatusError as e:
|
||||
logger.error(f"Qwen API错误: {e.response.status_code} - {e.response.text}")
|
||||
return LLMResponse(
|
||||
content="",
|
||||
model=self.config.model,
|
||||
error=f"API错误: {e.response.status_code} - {e.response.text[:200]}"
|
||||
)
|
||||
|
||||
except Exception as e:
|
||||
logger.error(f"Qwen调用失败: {e}")
|
||||
return LLMResponse(
|
||||
content="",
|
||||
model=self.config.model,
|
||||
error=str(e)
|
||||
)
|
||||
|
||||
def stream_chat(
|
||||
self,
|
||||
messages: List[Dict[str, str]],
|
||||
max_tokens: Optional[int] = None,
|
||||
temperature: Optional[float] = None,
|
||||
**kwargs
|
||||
) -> Generator[str, None, None]:
|
||||
"""
|
||||
流式对话补全（SSE格式）
|
||||
|
||||
Yields:
|
||||
str: 每次返回一个文本片段
|
||||
|
||||
使用示例:
|
||||
for chunk in client.stream_chat(messages):
|
||||
print(chunk, end="", flush=True)
|
||||
"""
|
||||
try:
|
||||
# OpenAI兼容格式的请求体，启用流式输出
|
||||
payload = {
|
||||
"model": self.config.model,
|
||||
"messages": messages,
|
||||
"max_tokens": max_tokens or self.config.max_tokens,
|
||||
"temperature": temperature or self.config.temperature,
|
||||
"top_p": kwargs.get("top_p", self.config.top_p),
|
||||
"stream": True # 启用流式输出
|
||||
}
|
||||
|
||||
# 使用stream模式发送请求
|
||||
with self._client.stream("POST", "/chat/completions", json=payload) as response:
|
||||
for line in response.iter_lines():
|
||||
if line:
|
||||
line = line.strip()
|
||||
# SSE格式: data: {...}
|
||||
if line.startswith("data: "):
|
||||
data_str = line[6:] # 移除 "data: " 前缀
|
||||
if data_str == "[DONE]":
|
||||
break
|
||||
try:
|
||||
data = json.loads(data_str)
|
||||
choices = data.get("choices", [])
|
||||
if not choices:
|
||||
continue # 跳过空的choices
|
||||
delta = choices[0].get("delta", {})
|
||||
content = delta.get("content", "")
|
||||
if content:
|
||||
yield content
|
||||
except json.JSONDecodeError:
|
||||
continue
|
||||
|
||||
except httpx.HTTPStatusError as e:
|
||||
logger.error(f"Qwen流式API错误: {e.response.status_code}")
|
||||
yield f"[ERROR: API返回错误 {e.response.status_code}]"
|
||||
|
||||
except Exception as e:
|
||||
logger.error(f"Qwen流式调用失败: {e}")
|
||||
yield f"[ERROR: {str(e)}]"
|
||||
|
||||
async def async_stream_chat(
|
||||
self,
|
||||
messages: List[Dict[str, str]],
|
||||
max_tokens: Optional[int] = None,
|
||||
temperature: Optional[float] = None,
|
||||
**kwargs
|
||||
) -> AsyncGenerator[str, None]:
|
||||
"""
|
||||
异步流式对话补全（用于FastAPI SSE响应）
|
||||
|
||||
Yields:
|
||||
str: 每次返回一个文本片段
|
||||
"""
|
||||
import asyncio
|
||||
|
||||
# 使用同步流式方法，包装为异步
|
||||
for chunk in self.stream_chat(messages, max_tokens, temperature, **kwargs):
|
||||
yield chunk
|
||||
# 给async循环一个小延迟，让其他任务有机会执行
|
||||
await asyncio.sleep(0)
|
||||
|
||||
def get_available_models(self) -> List[str]:
|
||||
"""获取可用模型列表"""
|
||||
return self.SUPPORTED_MODELS
|
||||
|
||||
def close(self):
|
||||
"""关闭客户端"""
|
||||
if self._client:
|
||||
self._client.close()
|
||||
|
||||
|
||||
class QwenVLClient(BaseLLMClient):
|
||||
"""
|
||||
Qwen VL多模态客户端（OpenAI兼容格式）
|
||||
|
||||
支持模型：
|
||||
- qwen-vl-plus
|
||||
- qwen-vl-max
|
||||
- qwen3-vl-plus
|
||||
- qwen2-vl-7b-instruct
|
||||
- qwen2-vl-72b-instruct
|
||||
"""
|
||||
|
||||
SUPPORTED_MODELS = [
|
||||
"qwen-vl-plus",
|
||||
"qwen-vl-max",
|
||||
"qwen3-vl-plus",
|
||||
"qwen2-vl-7b-instruct",
|
||||
"qwen2-vl-72b-instruct"
|
||||
]
|
||||
|
||||
def __init__(self, config: LLMConfig):
|
||||
if config.provider != LLMProvider.QWEN_VL:
|
||||
raise ValueError(f"配置provider应为QWEN_VL，实际为{config.provider}")
|
||||
super().__init__(config)
|
||||
self._init_client()
|
||||
|
||||
def _init_client(self):
|
||||
"""初始化HTTP客户端"""
|
||||
self._client = httpx.Client(
|
||||
base_url=self.config.base_url,
|
||||
headers={
|
||||
"Authorization": f"Bearer {self.config.api_key}",
|
||||
"Content-Type": "application/json"
|
||||
},
|
||||
timeout=self.config.timeout
|
||||
)
|
||||
logger.info(f"QwenVL客户端初始化完成: {self.config.base_url} - {self.config.model}")
|
||||
|
||||
def chat(
|
||||
self,
|
||||
messages: List[Dict[str, str]],
|
||||
max_tokens: Optional[int] = None,
|
||||
temperature: Optional[float] = None,
|
||||
**kwargs
|
||||
) -> LLMResponse:
|
||||
"""多模态对话补全（OpenAI兼容格式）
|
||||
|
||||
支持图片输入，消息格式：
|
||||
{
|
||||
"role": "user",
|
||||
"content": [
|
||||
{"type": "image_url", "image_url": {"url": "https://example.com/image.jpg"}},
|
||||
{"type": "text", "text": "描述这张图片"}
|
||||
]
|
||||
}
|
||||
"""
|
||||
start_time = time.time()
|
||||
|
||||
try:
|
||||
# OpenAI兼容格式的请求体
|
||||
payload = {
|
||||
"model": self.config.model,
|
||||
"messages": messages,
|
||||
"max_tokens": max_tokens or self.config.max_tokens,
|
||||
"temperature": temperature or self.config.temperature,
|
||||
"top_p": kwargs.get("top_p", self.config.top_p),
|
||||
"stream": False
|
||||
}
|
||||
|
||||
response = self._client.post("/chat/completions", json=payload)
|
||||
response.raise_for_status()
|
||||
|
||||
data = response.json()
|
||||
latency_ms = int((time.time() - start_time) * 1000)
|
||||
|
||||
choices = data.get("choices", [{}])
|
||||
message = choices[0].get("message", {})
|
||||
|
||||
return LLMResponse(
|
||||
content=message.get("content", ""),
|
||||
model=data.get("model", self.config.model),
|
||||
usage=data.get("usage", {}),
|
||||
finish_reason=choices[0].get("finish_reason", "stop"),
|
||||
latency_ms=latency_ms
|
||||
)
|
||||
|
||||
except httpx.HTTPStatusError as e:
|
||||
logger.error(f"QwenVL API错误: {e.response.status_code} - {e.response.text}")
|
||||
return LLMResponse(
|
||||
content="",
|
||||
model=self.config.model,
|
||||
error=f"API错误: {e.response.status_code} - {e.response.text[:200]}"
|
||||
)
|
||||
|
||||
except Exception as e:
|
||||
logger.error(f"QwenVL调用失败: {e}")
|
||||
return LLMResponse(
|
||||
content="",
|
||||
model=self.config.model,
|
||||
error=str(e)
|
||||
)
|
||||
|
||||
def stream_chat(
|
||||
self,
|
||||
messages: List[Dict[str, str]],
|
||||
max_tokens: Optional[int] = None,
|
||||
temperature: Optional[float] = None,
|
||||
**kwargs
|
||||
) -> Generator[str, None, None]:
|
||||
"""流式多模态对话补全"""
|
||||
try:
|
||||
payload = {
|
||||
"model": self.config.model,
|
||||
"messages": messages,
|
||||
"max_tokens": max_tokens or self.config.max_tokens,
|
||||
"temperature": temperature or self.config.temperature,
|
||||
"top_p": kwargs.get("top_p", self.config.top_p),
|
||||
"stream": True
|
||||
}
|
||||
|
||||
with self._client.stream("POST", "/chat/completions", json=payload) as response:
|
||||
for line in response.iter_lines():
|
||||
if line:
|
||||
line = line.strip()
|
||||
if line.startswith("data: "):
|
||||
data_str = line[6:]
|
||||
if data_str == "[DONE]":
|
||||
break
|
||||
try:
|
||||
data = json.loads(data_str)
|
||||
choices = data.get("choices", [])
|
||||
if not choices:
|
||||
continue # 跳过空的choices
|
||||
delta = choices[0].get("delta", {})
|
||||
content = delta.get("content", "")
|
||||
if content:
|
||||
yield content
|
||||
except json.JSONDecodeError:
|
||||
continue
|
||||
|
||||
except Exception as e:
|
||||
logger.error(f"QwenVL流式调用失败: {e}")
|
||||
yield f"[ERROR: {str(e)}]"
|
||||
|
||||
def get_available_models(self) -> List[str]:
|
||||
"""获取可用模型列表"""
|
||||
return self.SUPPORTED_MODELS
|
||||
|
||||
def close(self):
|
||||
"""关闭客户端"""
|
||||
if self._client:
|
||||
self._client.close()
|
||||
|
||||
|
||||
def create_qwen_client(
|
||||
api_key: str,
|
||||
model: str = "qwen3.5-flash",
|
||||
base_url: str = "http://6.86.80.4:30080/v1",
|
||||
**kwargs
|
||||
) -> QwenClient:
|
||||
"""便捷函数：创建Qwen客户端"""
|
||||
config = LLMConfig(
|
||||
provider=LLMProvider.QWEN,
|
||||
model=model,
|
||||
api_key=api_key,
|
||||
base_url=base_url,
|
||||
**kwargs
|
||||
)
|
||||
return QwenClient(config)
|
||||
|
||||
|
||||
def create_qwen_vl_client(
|
||||
api_key: str,
|
||||
model: str = "qwen3-vl-plus",
|
||||
base_url: str = "http://6.86.80.4:30080/v1",
|
||||
**kwargs
|
||||
) -> QwenVLClient:
|
||||
"""便捷函数：创建QwenVL客户端"""
|
||||
config = LLMConfig(
|
||||
provider=LLMProvider.QWEN_VL,
|
||||
model=model,
|
||||
api_key=api_key,
|
||||
base_url=base_url,
|
||||
**kwargs
|
||||
)
|
||||
return QwenVLClient(config)
|
||||
Reference in New Issue
Block a user