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Add dedicated VLM model configuration and wire it through multi-tenant VLM creation #10

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Merged
BukeLy merged 4 commits into from
Dec 15, 2025
Merged

Add dedicated VLM model configuration and wire it through multi-tenant VLM creation #10

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b7b1960
Initial plan
Copilot Dec 15, 2025
de4c36f
拆分VLM模型配置
Copilot Dec 15, 2025
e5548d2
完善VLM配置独立化
Copilot Dec 15, 2025
bb21225
优化VLM密钥回退一致性
Copilot Dec 15, 2025
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6 changes: 5 additions & 1 deletion env.example
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Expand Up @@ -15,6 +15,11 @@ LLM_API_KEY="your_llm_api_key_here"
LLM_BASE_URL="https://ark.ap-southeast.bytepluses.com/api/v3"
# 使用的模型名称
LLM_MODEL=seed-1-6-250615
# 用于多模态图片理解的 VLM 模型（必填，独立于 LLM_MODEL）
VLM_MODEL=seed-1-6-250615
Comment on lines +18 to +19
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Copilot AI Dec 15, 2025

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The documentation says VLM_MODEL is required (必填), but in the code at src/config.py:24, vlm_model uses Field(...) which makes it required at the pydantic validation level. However, the comment also says it should be "independent from LLM_MODEL" (独立于 LLM_MODEL), but the default value for LLM_MODEL and the example value for VLM_MODEL are both the same: seed-1-6-250615. This creates confusion about whether they should actually be different models. Consider clarifying whether VLM_MODEL can use the same model as LLM_MODEL (for models that support both text and vision), or if they must be different models.

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# 用于多模态图片理解的 VLM 模型（必填，独立于 LLM_MODEL）
VLM_MODEL=seed-1-6-250615
# 用于多模态图片理解的 VLM 模型（必填，独立于 LLM_MODEL，需支持图片输入）
VLM_MODEL=seed-vlm-1-6-250615 # 示例：与 LLM_MODEL 不同，需为支持视觉的模型

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# 可选：VLM 使用独立的密钥/域名（未设置时复用 LLM 配置）
# VLM_API_KEY="your_vlm_api_key_here"
# VLM_BASE_URL="https://api.example.com/v1"
# LLM 供应商标识（ark/openai/claude）
LLM_PROVIDER=ark
# VLM 图片理解 API 超时时间（秒，默认 120 秒）
Expand Down Expand Up @@ -318,4 +323,3 @@ TZ=Asia/Shanghai

# --- Python 配置 ---
PYTHONUNBUFFERED=1 # 禁用输出缓冲，实时查看日志

4 changes: 3 additions & 1 deletion src/config.py
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Expand Up @@ -8,7 +8,6 @@
重构原因: 统一配置管理，从服务商导向改为功能导向命名
"""

import os
from typing import Optional
from pydantic import Field
from pydantic_settings import BaseSettings
Expand All @@ -22,6 +21,9 @@ class LLMConfig(BaseSettings):
api_key: str = Field(..., description="LLM API Key")
base_url: str = Field(..., description="LLM API Base URL")
model: str = Field(default="seed-1-6-250615", description="LLM Model Name")
vlm_model: str = Field(..., description="VLM Model Name", alias="VLM_MODEL")
vlm_api_key: Optional[str] = Field(default=None, description="VLM API Key", alias="VLM_API_KEY")
vlm_base_url: Optional[str] = Field(default=None, description="VLM API Base URL", alias="VLM_BASE_URL")
Comment on lines +24 to +26
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The VLM fields use explicit aliases (VLM_MODEL, VLM_API_KEY, VLM_BASE_URL) that don't follow the LLM_ prefix defined in the Config class. For these aliases to work correctly, the LLMConfig.Config class needs populate_by_name = True. Without this setting, pydantic-settings will not be able to load these environment variables. Other config classes in this file that use aliases (like DeepSeekOCRConfig at line 158) already include this setting.

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vlm_timeout: int = Field(default=120, description="VLM Image Understanding Timeout (seconds)")
timeout: int = Field(default=60, description="General LLM Timeout (seconds)")

Expand Down
23 changes: 13 additions & 10 deletions src/multi_tenant.py
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Expand Up @@ -48,9 +48,12 @@ def __init__(
self._creation_locks: defaultdict = defaultdict(asyncio.Lock)

# 共享配置（从集中配置管理读取）
self.ark_api_key = config.llm.api_key
self.ark_base_url = config.llm.base_url
self.ark_model = config.llm.model
self.llm_api_key = config.llm.api_key
self.llm_base_url = config.llm.base_url
self.llm_model = config.llm.model
self.vlm_model = config.llm.vlm_model
self.vlm_api_key = config.llm.vlm_api_key or config.llm.api_key
self.vlm_base_url = config.llm.vlm_base_url or config.llm.base_url

self.sf_api_key = config.embedding.api_key
self.sf_base_url = config.embedding.base_url
Expand Down Expand Up @@ -85,9 +88,9 @@ def _create_llm_func(self, llm_config: Dict):
import asyncio

# 从配置中提取参数（支持租户覆盖）
model = llm_config.get("model", self.ark_model)
api_key = llm_config.get("api_key", self.ark_api_key)
base_url = llm_config.get("base_url", self.ark_base_url)
model = llm_config.get("model", self.llm_model)
api_key = llm_config.get("api_key", self.llm_api_key)
base_url = llm_config.get("base_url", self.llm_base_url)

# 获取 RateLimiter 参数（租户可配置）
# 注意：这里的 max_async 是 RateLimiter 的并发控制，不是 LightRAG 的
Expand Down Expand Up @@ -278,9 +281,9 @@ def _create_vision_model_func(self, llm_config: Dict):
import aiohttp

# 从配置中提取参数（支持租户覆盖）
model = llm_config.get("model", self.ark_model)
api_key = llm_config.get("api_key", self.ark_api_key)
base_url = llm_config.get("base_url", self.ark_base_url)
model = llm_config.get("vlm_model", self.vlm_model)
api_key = llm_config.get("vlm_api_key") or llm_config.get("api_key") or self.vlm_api_key
base_url = llm_config.get("vlm_base_url") or llm_config.get("base_url") or self.vlm_base_url
vlm_timeout = llm_config.get("vlm_timeout", self.vlm_timeout)

# 获取速率限制器（VLM 使用 LLM 的限制）
Expand Down Expand Up @@ -552,4 +555,4 @@ async def get_tenant_lightrag(tenant_id: str) -> LightRAG:
LightRAG: 该租户的实例
"""
manager = get_multi_tenant_manager()
return await manager.get_instance(tenant_id)
return await manager.get_instance(tenant_id)
3 changes: 3 additions & 0 deletions src/tenant_config.py
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Expand Up @@ -301,6 +301,9 @@ def _merge_llm_config(self, tenant_config: Optional[TenantConfigModel]) -> Dict[
"""
base = {
"model": config.llm.model,
"vlm_model": config.llm.vlm_model,
"vlm_api_key": config.llm.vlm_api_key,
"vlm_base_url": config.llm.vlm_base_url,
"api_key": config.llm.api_key,
"base_url": config.llm.base_url,
"timeout": config.llm.timeout,
Expand Down