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Merge remote-tracking branch 'origin' into feat/rag-eval

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This commit is contained in:
Wenjie Zhang 2025-12-09 22:12:20 +08:00
commit 6f630782e1
5 changed files with 11 additions and 11 deletions
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8
docs/latest/advanced/configuration.md
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@ -37,7 +37,7 @@ class Config(BaseModel):
enable_content_guard: bool = Field(default=False, description="是否启用内容审查")
# 模型配置
default_model: str = Field(default="siliconflow/deepseek-ai/DeepSeek-V3.2-Exp")
default_model: str = Field(default="siliconflow/deepseek-ai/DeepSeek-V3.2")
embed_model: str = Field(default="siliconflow/BAAI/bge-m3")
# 运行时状态 (不持久化)
@ -105,10 +105,10 @@ DEFAULT_CHAT_MODEL_PROVIDERS: dict[str, ChatModelProvider] = {
name="SiliconFlow",
url="https://cloud.siliconflow.cn/models",
base_url="https://api.siliconflow.cn/v1",
default="deepseek-ai/DeepSeek-V3.2-Exp",
default="deepseek-ai/DeepSeek-V3.2",
env="SILICONFLOW_API_KEY",
models=[
"deepseek-ai/DeepSeek-V3.2-Exp",
"deepseek-ai/DeepSeek-V3.2",
"Qwen/Qwen3-235B-A22B-Instruct-2507",
# ...
],
@ -130,7 +130,7 @@ enable_content_guard = true
# 模型配置修改
[model_names.siliconflow]
models = [
"deepseek-ai/DeepSeek-V3.2-Exp",
"deepseek-ai/DeepSeek-V3.2",
"custom-model-name",
]
```

2
docs/latest/intro/model-config.md
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@ -26,7 +26,7 @@
系统的默认对话模型通过配置项 `default_model` 指定，格式统一为 `模型提供商/模型名称`，例如：
```yaml
default_model: siliconflow/deepseek-ai/DeepSeek-V3.2-Exp
default_model: siliconflow/deepseek-ai/DeepSeek-V3.2
```
在 Web 界面中选择模型时也会自动按照这一格式保存。

2
src/config/app.py
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@ -47,7 +47,7 @@ class Config(BaseModel):
# 模型配置
# ============================================================
default_model: str = Field(
default="siliconflow/deepseek-ai/DeepSeek-V3.2-Exp",
default="siliconflow/deepseek-ai/DeepSeek-V3.2",
description="默认对话模型",
)
fast_model: str = Field(

8
src/config/static/models.py
View File

@ -73,10 +73,10 @@ DEFAULT_CHAT_MODEL_PROVIDERS: dict[str, ChatModelProvider] = {
name="SiliconFlow",
url="https://cloud.siliconflow.cn/models",
base_url="https://api.siliconflow.cn/v1",
default="deepseek-ai/DeepSeek-V3.2-Exp",
default="deepseek-ai/DeepSeek-V3.2",
env="SILICONFLOW_API_KEY",
models=[
"deepseek-ai/DeepSeek-V3.2-Exp",
"deepseek-ai/DeepSeek-V3.2",
"Qwen/Qwen3-235B-A22B-Thinking-2507",
"Qwen/Qwen3-235B-A22B-Instruct-2507",
"moonshotai/Kimi-K2-Instruct-0905",
@ -146,9 +146,9 @@ DEFAULT_CHAT_MODEL_PROVIDERS: dict[str, ChatModelProvider] = {
name="ModelScope",
url="https://www.modelscope.cn/docs/model-service/API-Inference/intro",
base_url="https://api-inference.modelscope.cn/v1/",
default="deepseek-ai/DeepSeek-V3.2-Exp",
default="deepseek-ai/DeepSeek-V3.2",
env="MODELSCOPE_ACCESS_TOKEN",
models=["Qwen/Qwen3-32B", "deepseek-ai/DeepSeek-V3.2-Exp"],
models=["Qwen/Qwen3-32B", "deepseek-ai/DeepSeek-V3.2"],
),
}

2
src/knowledge/implementations/lightrag.py
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@ -201,7 +201,7 @@ class LightRagKB(KnowledgeBase):
"""获取 embedding 函数"""
config_dict = get_embedding_config(embed_info)
if config_dict["model_id"].startswith("ollama"):
if config_dict.get("model_id") and config_dict["model_id"].startswith("ollama"):
from lightrag.llm.ollama import ollama_embed
from src.utils import get_docker_safe_url