lixiaolong
873a82b0f5
- 移除Ollama相关配置和回退机制，统一使用SGLang作为视觉模型提供商 - 添加IMAGE_ANALYSIS类型支持，允许对多张图片进行分析 - 实现视频分析的详细输出模式，支持紧凑和详细两种结果格式 - 更新环境变量配置，添加VIDEO_MODEL_FRAME_LIMIT和MAX_IMAGE_BYTES - 修改compose配置文件中的上下文长度和内存分配参数 - 重构视频采样逻辑，限制单次请求帧数以优化显存使用 - 更新API接口文档，添加mediaUrls参数和详细输出选项说明 - 添加图像分析相关的依赖库opencv-python-headless - 实现结构化JSON响应格式验证和重试机制
27 lines
816 B
Python
27 lines
816 B
Python
from pathlib import Path
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from pydantic_settings import BaseSettings, SettingsConfigDict
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class Settings(BaseSettings):
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model_config = SettingsConfigDict(env_file=".env", extra="ignore")
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api_key: str = ""
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profiles_dir: Path = Path("/data/profiles")
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artifacts_dir: Path = Path("/data/artifacts")
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jobs_dir: Path = Path("/data/jobs")
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media_timeout_seconds: int = 120
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sglang_fast_base_url: str = ""
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sglang_accurate_base_url: str = ""
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sglang_api_key: str = ""
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sglang_timeout_seconds: int = 600
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max_audio_bytes: int = 100 * 1024 * 1024
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max_image_bytes: int = 30 * 1024 * 1024
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max_video_bytes: int = 2 * 1024 * 1024 * 1024
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video_sampling_frame_limit: int = 100
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video_model_frame_limit: int = 30
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max_video_context_tokens: int = 65536
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settings = Settings()
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