refactor(models):统一请求处理并优化响应处理 (refactor/unified_request)

对 `utils_model.py` 中的请求处理逻辑进行重构,创建统一的请求执行方法 `_execute_request`。该方法集中处理请求构建、重试逻辑和响应处理,替代了 `generate_response`、`generate_response_for_image` 和 `generate_response_async` 中的冗余代码。

关键变更:
- 引入 `_execute_request` 作为 API 请求的单一入口
- 新增支持自定义重试策略和响应处理器
- 通过 `_build_payload` 简化图像和文本载荷构建
- 改进错误处理和日志记录
- 移除已弃用的同步方法
- 加入了`max_response_length`以兼容koboldcpp硬编码的默认值500

此次重构在保持现有功能的同时提高了代码可维护性,减少了重复代码
This commit is contained in:
KawaiiYusora
2025-03-06 23:50:14 +08:00
parent ee414eeaaf
commit 11807fda38
7 changed files with 243 additions and 623 deletions

View File

@@ -64,15 +64,15 @@ class CQCode:
"""初始化LLM实例"""
self._llm = LLM_request(model=global_config.vlm, temperature=0.4, max_tokens=300)
def translate(self):
async def translate(self):
"""根据CQ码类型进行相应的翻译处理"""
if self.type == 'text':
self.translated_plain_text = self.params.get('text', '')
elif self.type == 'image':
if self.params.get('sub_type') == '0':
self.translated_plain_text = self.translate_image()
self.translated_plain_text = await self.translate_image()
else:
self.translated_plain_text = self.translate_emoji()
self.translated_plain_text = await self.translate_emoji()
elif self.type == 'at':
user_nickname = get_user_nickname(self.params.get('qq', ''))
if user_nickname:
@@ -158,7 +158,7 @@ class CQCode:
return None
def translate_emoji(self) -> str:
async def translate_emoji(self) -> str:
"""处理表情包类型的CQ码"""
if 'url' not in self.params:
return '[表情包]'
@@ -167,12 +167,12 @@ class CQCode:
# 将 base64 字符串转换为字节类型
image_bytes = base64.b64decode(base64_str)
storage_emoji(image_bytes)
return self.get_emoji_description(base64_str)
return await self.get_emoji_description(base64_str)
else:
return '[表情包]'
def translate_image(self) -> str:
async def translate_image(self) -> str:
"""处理图片类型的CQ码区分普通图片和表情包"""
#没有url直接返回默认文本
if 'url' not in self.params:
@@ -181,25 +181,27 @@ class CQCode:
if base64_str:
image_bytes = base64.b64decode(base64_str)
storage_image(image_bytes)
return self.get_image_description(base64_str)
return await self.get_image_description(base64_str)
else:
return '[图片]'
def get_emoji_description(self, image_base64: str) -> str:
async def get_emoji_description(self, image_base64: str) -> str:
"""调用AI接口获取表情包描述"""
try:
prompt = "这是一个表情包请用简短的中文描述这个表情包传达的情感和含义。最多20个字。"
description, _ = self._llm.generate_response_for_image_sync(prompt, image_base64)
# description, _ = self._llm.generate_response_for_image_sync(prompt, image_base64)
description, _ = await self._llm.generate_response_for_image(prompt, image_base64)
return f"[表情包:{description}]"
except Exception as e:
print(f"\033[1;31m[错误]\033[0m AI接口调用失败: {str(e)}")
return "[表情包]"
def get_image_description(self, image_base64: str) -> str:
async def get_image_description(self, image_base64: str) -> str:
"""调用AI接口获取普通图片描述"""
try:
prompt = "请用中文描述这张图片的内容。如果有文字请把文字都描述出来。并尝试猜测这个图片的含义。最多200个字。"
description, _ = self._llm.generate_response_for_image_sync(prompt, image_base64)
# description, _ = self._llm.generate_response_for_image_sync(prompt, image_base64)
description, _ = await self._llm.generate_response_for_image(prompt, image_base64)
return f"[图片:{description}]"
except Exception as e:
print(f"\033[1;31m[错误]\033[0m AI接口调用失败: {str(e)}")