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1.优化AI请求替换OpenAI SDK调用，使用httpx和自定义头请求，避免触发部分公益站的cloudflare

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2.修复deepseek模型调用问题，舍弃思考过程AI响应内容，只获取结果内容
3.新增会话过期机制，更新后添加到.env中
4.支持用户在生成章节内容时设置字数
This commit is contained in:
xiamuceer
2025-11-03 15:28:51 +08:00
parent e02e61ed6b
commit 1cde345ed9
21 changed files with 1118 additions and 251 deletions
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backend/app/services/ai_service.py
+167 -98
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@@ -41,58 +41,7 @@ class AIService:
# 初始化OpenAI客户端
openai_key = api_key if api_provider == "openai" else app_settings.openai_api_key
if openai_key:
# 创建自定义的httpx客户端来避免proxies参数问题
try:
# 配置连接池限制，支持高并发
# max_keepalive_connections: 保持活跃的连接数（提高复用率）
# max_connections: 最大并发连接数（防止资源耗尽）
limits = httpx.Limits(
max_keepalive_connections=50, # 保持50个活跃连接
max_connections=100, # 最多100个并发连接
keepalive_expiry=30.0 # 30秒后过期未使用的连接
)
# 使用httpx.AsyncClient并设置超时和连接池
# connect: 连接超时10秒
# read: 读取超时180秒（3分钟，适合长文本生成）
# write: 写入超时10秒
# pool: 连接池超时10秒
http_client = httpx.AsyncClient(
timeout=httpx.Timeout(
connect=10.0,
read=180.0,
write=10.0,
pool=10.0
),
limits=limits
)
client_kwargs = {
"api_key": openai_key,
"http_client": http_client
}
# 优先使用用户提供的base_url，否则使用全局配置
base_url = api_base_url if api_provider == "openai" else app_settings.openai_base_url
if base_url:
client_kwargs["base_url"] = base_url
self.openai_client = AsyncOpenAI(**client_kwargs)
logger.info("✅ OpenAI客户端初始化成功")
logger.info(" - 超时设置：连接10s，读取180s")
logger.info(" - 连接池：50个保活连接，最大100个并发")
except Exception as e:
logger.error(f"OpenAI客户端初始化失败: {e}")
self.openai_client = None
else:
self.openai_client = None
logger.warning("OpenAI API key未配置")
# 初始化Anthropic客户端
anthropic_key = api_key if api_provider == "anthropic" else app_settings.anthropic_api_key
if anthropic_key:
try:
# 为Anthropic设置相同的超时和连接池配置
limits = httpx.Limits(
max_keepalive_connections=50,
max_connections=100,
@@ -100,13 +49,56 @@ class AIService:
)
http_client = httpx.AsyncClient(
timeout=httpx.Timeout(
connect=10.0,
read=180.0,
write=10.0,
pool=10.0
),
limits=limits
timeout=httpx.Timeout(connect=60.0, read=180.0, write=60.0, pool=60.0),
limits=limits,
headers={
"User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/120.0.0.0 Safari/537.36"
}
)
client_kwargs = {
"api_key": openai_key,
"http_client": http_client
}
base_url = api_base_url if api_provider == "openai" else app_settings.openai_base_url
if base_url:
client_kwargs["base_url"] = base_url
self.openai_client = AsyncOpenAI(**client_kwargs)
self.openai_http_client = http_client
self.openai_api_key = openai_key
self.openai_base_url = base_url
logger.info("✅ OpenAI客户端初始化成功")
except Exception as e:
logger.error(f"OpenAI客户端初始化失败: {e}")
self.openai_client = None
self.openai_http_client = None
self.openai_api_key = None
self.openai_base_url = None
else:
self.openai_client = None
self.openai_http_client = None
self.openai_api_key = None
self.openai_base_url = None
logger.warning("OpenAI API key未配置")
# 初始化Anthropic客户端
anthropic_key = api_key if api_provider == "anthropic" else app_settings.anthropic_api_key
if anthropic_key:
try:
limits = httpx.Limits(
max_keepalive_connections=50,
max_connections=100,
keepalive_expiry=30.0
)
http_client = httpx.AsyncClient(
timeout=httpx.Timeout(connect=60.0, read=180.0, write=60.0, pool=60.0),
limits=limits,
headers={
"User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/120.0.0.0 Safari/537.36"
}
)
client_kwargs = {
@@ -114,15 +106,12 @@ class AIService:
"http_client": http_client
}
# 优先使用用户提供的base_url，否则使用全局配置
base_url = api_base_url if api_provider == "anthropic" else app_settings.anthropic_base_url
if base_url:
client_kwargs["base_url"] = base_url
self.anthropic_client = AsyncAnthropic(**client_kwargs)
logger.info("✅ Anthropic客户端初始化成功")
logger.info(" - 超时设置：连接10s，读取180s")
logger.info(" - 连接池：50个保活连接，最大100个并发")
except Exception as e:
logger.error(f"Anthropic客户端初始化失败: {e}")
self.anthropic_client = None
@@ -219,7 +208,7 @@ class AIService:
system_prompt: Optional[str]
) -> str:
"""使用OpenAI生成文本"""
if not self.openai_client:
if not self.openai_http_client:
raise ValueError("OpenAI客户端未初始化，请检查API key配置")
messages = []
@@ -228,39 +217,76 @@ class AIService:
messages.append({"role": "user", "content": prompt})
try:
logger.info(f"🔵 开始调用OpenAI API")
logger.info(f"🔵 开始调用OpenAI API（直接HTTP请求）")
logger.info(f" - 模型: {model}")
logger.info(f" - 温度: {temperature}")
logger.info(f" - 最大tokens: {max_tokens}")
logger.info(f" - Prompt长度: {len(prompt)} 字符")
logger.info(f" - 消息数量: {len(messages)}")
response = await self.openai_client.chat.completions.create(
model=model,
messages=messages,
temperature=temperature,
max_tokens=max_tokens
)
url = f"{self.openai_base_url}/chat/completions"
headers = {
"Authorization": f"Bearer {self.openai_api_key}",
"Content-Type": "application/json"
}
payload = {
"model": model,
"messages": messages,
"temperature": temperature,
"max_tokens": max_tokens
}
logger.debug(f" - 请求URL: {url}")
logger.debug(f" - 请求头: Authorization=Bearer ***")
response = await self.openai_http_client.post(url, headers=headers, json=payload)
response.raise_for_status()
data = response.json()
logger.info(f"✅ OpenAI API调用成功")
logger.info(f" - 响应ID: {response.id if hasattr(response, 'id') else 'N/A'}")
logger.info(f" - 选项数量: {len(response.choices)}")
logger.info(f" - 响应ID: {data.get('id', 'N/A')}")
logger.info(f" - 选项数量: {len(data.get('choices', []))}")
if not response.choices:
if not data.get('choices'):
logger.error("❌ OpenAI返回的choices为空")
return ""
raise ValueError("API返回的响应格式错误：choices字段为空")
content = response.choices[0].message.content
logger.info(f" - 返回内容长度: {len(content) if content else 0} 字符")
choice = data['choices'][0]
message = choice.get('message', {})
finish_reason = choice.get('finish_reason')
# DeepSeek R1特殊处理：只使用content（最终答案），忽略reasoning_content（思考过程）
# reasoning_content是AI的思考过程，不是我们需要的JSON结果
content = message.get('content', '')
# 检查是否因达到长度限制而截断
if finish_reason == 'length':
logger.warning(f"⚠️ 响应因达到max_tokens限制而被截断")
logger.warning(f" - 当前max_tokens: {max_tokens}")
logger.warning(f" - 建议: 增加max_tokens参数（推荐2000+）")
if content:
logger.info(f" - 返回内容长度: {len(content)} 字符")
logger.info(f" - 完成原因: {finish_reason}")
logger.info(f" - 返回内容预览（前200字符）: {content[:200]}")
return content
else:
logger.error("❌ OpenAI返回了空内容")
logger.error(f" - 完整响应: {response}")
raise ValueError("AI返回了空内容，请检查API配置或稍后重试")
logger.error("❌ AI返回了空内容")
logger.error(f" - 完整响应: {data}")
logger.error(f" - 完成原因: {finish_reason}")
# 提供更详细的错误信息
if finish_reason == 'length':
raise ValueError(f"AI响应被截断且无有效内容。请增加max_tokens参数（当前: {max_tokens}，建议: 2000+）")
else:
raise ValueError(f"AI返回了空内容（finish_reason: {finish_reason}），请检查API配置或稍后重试")
except httpx.HTTPStatusError as e:
logger.error(f"❌ OpenAI API调用失败 (HTTP {e.response.status_code})")
logger.error(f" - 错误信息: {e.response.text}")
logger.error(f" - 模型: {model}")
raise Exception(f"API返回错误 ({e.response.status_code}): {e.response.text}")
except Exception as e:
logger.error(f"❌ OpenAI API调用失败")
logger.error(f" - 错误类型: {type(e).__name__}")
@@ -277,7 +303,7 @@ class AIService:
system_prompt: Optional[str]
) -> AsyncGenerator[str, None]:
"""使用OpenAI流式生成文本"""
if not self.openai_client:
if not self.openai_http_client:
raise ValueError("OpenAI客户端未初始化，请检查API key配置")
messages = []
@@ -286,35 +312,78 @@ class AIService:
messages.append({"role": "user", "content": prompt})
try:
logger.info(f"🔵 开始调用OpenAI流式API")
logger.info(f"🔵 开始调用OpenAI流式API（直接HTTP请求）")
logger.info(f" - 模型: {model}")
logger.info(f" - Prompt长度: {len(prompt)} 字符")
logger.info(f" - 最大tokens: {max_tokens}")
stream = await self.openai_client.chat.completions.create(
model=model,
messages=messages,
temperature=temperature,
max_tokens=max_tokens,
stream=True
)
url = f"{self.openai_base_url}/chat/completions"
headers = {
"Authorization": f"Bearer {self.openai_api_key}",
"Content-Type": "application/json"
}
payload = {
"model": model,
"messages": messages,
"temperature": temperature,
"max_tokens": max_tokens,
"stream": True
}
logger.info(f"✅ OpenAI流式API连接成功，开始接收数据...")
chunk_count = 0
async for chunk in stream:
if chunk.choices and len(chunk.choices) > 0:
if chunk.choices[0].delta.content:
chunk_count += 1
yield chunk.choices[0].delta.content
logger.info(f"✅ OpenAI流式生成完成，共接收 {chunk_count} 个chunk")
async with self.openai_http_client.stream('POST', url, headers=headers, json=payload) as response:
response.raise_for_status()
logger.info(f"✅ OpenAI流式API连接成功，开始接收数据...")
chunk_count = 0
has_content = False
finish_reason = None
async for line in response.aiter_lines():
if line.startswith('data: '):
data_str = line[6:]
if data_str.strip() == '[DONE]':
break
try:
import json
data = json.loads(data_str)
if 'choices' in data and len(data['choices']) > 0:
choice = data['choices'][0]
delta = choice.get('delta', {})
finish_reason = choice.get('finish_reason') or finish_reason
# DeepSeek R1特殊处理：只收集content（最终答案），忽略reasoning_content（思考过程）
# reasoning_content是AI的思考过程，不是我们需要的JSON结果
content = delta.get('content', '')
if content:
chunk_count += 1
has_content = True
yield content
except json.JSONDecodeError:
continue
# 检查是否因长度限制截断
if finish_reason == 'length':
logger.warning(f"⚠️ 流式响应因达到max_tokens限制而被截断")
logger.warning(f" - 当前max_tokens: {max_tokens}")
logger.warning(f" - 建议: 增加max_tokens参数（推荐2000+）")
if not has_content:
logger.warning(f"⚠️ 流式响应未返回任何内容")
logger.warning(f" - 完成原因: {finish_reason}")
logger.info(f"✅ OpenAI流式生成完成，共接收 {chunk_count} 个chunk，完成原因: {finish_reason}")
except httpx.TimeoutException as e:
logger.error(f"❌ OpenAI流式API超时")
logger.error(f" - 错误: {str(e)}")
logger.error(f" - 提示: 请检查网络连接或考虑缩短prompt长度")
raise TimeoutError(f"AI服务超时（180秒），请稍后重试或减少上下文长度") from e
except httpx.HTTPStatusError as e:
logger.error(f"❌ OpenAI流式API调用失败 (HTTP {e.response.status_code})")
logger.error(f" - 错误信息: {await e.response.aread()}")
raise
except Exception as e:
logger.error(f"❌ OpenAI流式API调用失败: {str(e)}")
logger.error(f" - 错误类型: {type(e).__name__}")
@@ -389,7 +458,7 @@ class AIService:
raise
# 创建全局AI服务实例（使用环境变量配置，用于向后兼容）
# 创建全局AI服务实例
ai_service = AIService()