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refactor(model): replace VolcanoChatOpenAI with CompatibleChatOpenAI for unified omni model support

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Timebomb2018
2026-04-16 17:40:30 +08:00
parent 7ba0726473
commit ccdf7ae81d
2 changed files with 6 additions and 6 deletions
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8
api/app/core/models/base.py
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@@ -14,7 +14,7 @@ from pydantic import BaseModel, Field, model_validator
from app.core.error_codes import BizCode from app.core.error_codes import BizCode
from app.core.exceptions import BusinessException from app.core.exceptions import BusinessException
from app.models.models_model import ModelProvider, ModelType from app.models.models_model import ModelProvider, ModelType
from app.core.models.volcano_chat import VolcanoChatOpenAI from app.core.models.compatible_chat import CompatibleChatOpenAI
T = TypeVar("T") T = TypeVar("T")
@@ -255,11 +255,11 @@ def get_provider_llm_class(config: RedBearModelConfig, type: ModelType = ModelTy
"""根据模型提供商获取对应的模型类""" """根据模型提供商获取对应的模型类"""
provider = config.provider.lower() provider = config.provider.lower()
# dashscope 的 omni 模型使用 OpenAI 兼容模式 # dashscope的omni模型 和 volcano模型使用
if provider == ModelProvider.DASHSCOPE and config.is_omni: if provider == ModelProvider.DASHSCOPE and config.is_omni:
return ChatOpenAI return CompatibleChatOpenAI
if provider == ModelProvider.VOLCANO: if provider == ModelProvider.VOLCANO:
return VolcanoChatOpenAI return CompatibleChatOpenAI
if provider in [ModelProvider.OPENAI, ModelProvider.XINFERENCE, ModelProvider.GPUSTACK]: if provider in [ModelProvider.OPENAI, ModelProvider.XINFERENCE, ModelProvider.GPUSTACK]:
if type == ModelType.LLM: if type == ModelType.LLM:
return OpenAI return OpenAI

4
api/app/core/models/volcano_chat.py → api/app/core/models/compatible_chat.py
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@@ -12,8 +12,8 @@ from langchain_core.outputs import ChatGenerationChunk, ChatResult
from langchain_openai import ChatOpenAI from langchain_openai import ChatOpenAI
class VolcanoChatOpenAI(ChatOpenAI): class CompatibleChatOpenAI(ChatOpenAI):
"""火山引擎 Chat 模型，支持深度思考内容（reasoning_content）的流式和非流式透传。""" """火山和千问的omni兼容模型，支持深度思考内容（reasoning_content）的流式和非流式透传。"""
def _create_chat_result(self, response: Union[dict, Any], generation_info: Optional[dict] = None) -> ChatResult: def _create_chat_result(self, response: Union[dict, Any], generation_info: Optional[dict] = None) -> ChatResult:
result = super()._create_chat_result(response, generation_info) result = super()._create_chat_result(response, generation_info)