mirror of
https://github.com/fawney19/Aether.git
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refactor: 移除 Python 后端源码,全面迁移至 Rust gateway 架构
- 删除全部 Python 源码 (src/) 及 Alembic 迁移脚本,归档至 _deprecated_py_src/ - 重构 Rust gateway ai_pipeline: 拆分 planner/finalize 模块,新增 contracts/adaptation 层 - 重组 handlers 模块为 admin/public/proxy/internal/shared 子模块结构 - 新增 executor 模块,引入 Rust 原生数据库迁移 (aether-data/migrations) - 简化 CI/Docker 构建流程,移除 base image 二级构建,统一为单一 app image - 移除 Python 相关基础设施文件 (entrypoint.sh, gunicorn_conf.py, Dockerfile.base)
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"""
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Collector definitions (config-file mode).
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Goal:
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- Developers define dimension collectors in code, grouped by api_format.
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- Adding support for a new api_format should only require adding a new file here.
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- No DB seeding required.
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Each module should export:
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- COLLECTORS: list[dict[str, Any]]
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Each dict supports keys (aligned with DimensionCollector):
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- api_format: "openai:chat" (canonical family:kind)
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- task_type: "chat" | "cli" | "video" | "image" | "audio"
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- dimension_name: string
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- source_type: "request" | "response" | "metadata" | "computed"
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- source_path: string | None
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- value_type: "float" | "int" | "string"
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- transform_expression: string | None
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- default_value: string | None
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- priority: int
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- is_enabled: bool
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"""
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from __future__ import annotations
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from typing import Any
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# This package is discovered dynamically by `src.services.billing.presets`.
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COLLECTORS: list[dict[str, Any]] = []
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@@ -0,0 +1,27 @@
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from __future__ import annotations
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from typing import Any
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# Anthropic / Claude messages
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COLLECTORS: list[dict[str, Any]] = [
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{
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"api_format": "claude:chat",
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"task_type": "chat",
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"dimension_name": "input_tokens",
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"source_type": "response",
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"source_path": "usage.input_tokens",
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"value_type": "int",
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"priority": 10,
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"is_enabled": True,
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},
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{
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"api_format": "claude:chat",
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"task_type": "chat",
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"dimension_name": "output_tokens",
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"source_type": "response",
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"source_path": "usage.output_tokens",
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"value_type": "int",
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"priority": 10,
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"is_enabled": True,
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},
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]
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@@ -0,0 +1,27 @@
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from __future__ import annotations
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from typing import Any
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# Gemini generateContent
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COLLECTORS: list[dict[str, Any]] = [
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{
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"api_format": "gemini:chat",
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"task_type": "chat",
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"dimension_name": "input_tokens",
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"source_type": "response",
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"source_path": "usageMetadata.promptTokenCount",
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"value_type": "int",
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"priority": 10,
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"is_enabled": True,
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},
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{
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"api_format": "gemini:chat",
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"task_type": "chat",
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"dimension_name": "output_tokens",
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"source_type": "response",
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"source_path": "usageMetadata.candidatesTokenCount",
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"value_type": "int",
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"priority": 10,
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"is_enabled": True,
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},
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]
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@@ -0,0 +1,27 @@
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from __future__ import annotations
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from typing import Any
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# OpenAI chat completions
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COLLECTORS: list[dict[str, Any]] = [
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{
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"api_format": "openai:chat",
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"task_type": "chat",
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"dimension_name": "input_tokens",
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"source_type": "response",
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"source_path": "usage.prompt_tokens",
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"value_type": "int",
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"priority": 10,
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"is_enabled": True,
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},
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{
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"api_format": "openai:chat",
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"task_type": "chat",
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"dimension_name": "output_tokens",
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"source_type": "response",
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"source_path": "usage.completion_tokens",
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"value_type": "int",
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"priority": 10,
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"is_enabled": True,
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},
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]
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@@ -0,0 +1,116 @@
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from __future__ import annotations
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from typing import Any
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# Async video finalize flow: extra dims from metadata (base_dimensions already provided by caller).
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#
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# Note:
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# - DimensionCollectorService has a "video -> base api_format fallback" that may query
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# base api_format collectors when api_format is "openai:video"/"gemini:video" etc.
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COLLECTORS: list[dict[str, Any]] = [
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# Prefer size as "resolution key" (e.g. 1024x1792), fallback to resolution label (e.g. 720p/4k).
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{
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"api_format": "openai:chat",
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"task_type": "video",
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"dimension_name": "video_resolution_key",
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"source_type": "metadata",
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"source_path": "task.size",
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"value_type": "string",
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"priority": 10,
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"is_enabled": True,
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},
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{
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"api_format": "openai:chat",
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"task_type": "video",
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"dimension_name": "video_resolution_key",
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"source_type": "metadata",
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"source_path": "task.resolution",
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"value_type": "string",
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"priority": 0,
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"is_enabled": True,
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},
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{
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"api_format": "openai:chat",
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"task_type": "video",
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"dimension_name": "video_size_bytes",
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"source_type": "metadata",
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"source_path": "task.video_size_bytes",
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"value_type": "int",
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"priority": 0,
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"is_enabled": True,
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},
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# 实际视频时长(秒),优先使用从 provider 响应中提取的实际时长
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{
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"api_format": "openai:chat",
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"task_type": "video",
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"dimension_name": "video_duration_seconds",
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"source_type": "metadata",
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"source_path": "task.video_duration_seconds",
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"value_type": "float",
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"priority": 10,
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"is_enabled": True,
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},
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# 回退到请求的 duration_seconds(如果没有实际时长)
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{
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"api_format": "openai:chat",
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"task_type": "video",
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"dimension_name": "video_duration_seconds",
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"source_type": "metadata",
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"source_path": "task.duration_seconds",
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"value_type": "int",
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"priority": 0,
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"is_enabled": True,
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},
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{
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"api_format": "gemini:chat",
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"task_type": "video",
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"dimension_name": "video_resolution_key",
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"source_type": "metadata",
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"source_path": "task.size",
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"value_type": "string",
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"priority": 10,
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"is_enabled": True,
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},
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{
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"api_format": "gemini:chat",
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"task_type": "video",
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"dimension_name": "video_resolution_key",
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"source_type": "metadata",
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"source_path": "task.resolution",
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"value_type": "string",
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"priority": 0,
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"is_enabled": True,
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},
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{
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"api_format": "gemini:chat",
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"task_type": "video",
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"dimension_name": "video_size_bytes",
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"source_type": "metadata",
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"source_path": "task.video_size_bytes",
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"value_type": "int",
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"priority": 0,
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"is_enabled": True,
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},
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# 实际视频时长(秒),优先使用从 provider 响应中提取的实际时长
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{
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"api_format": "gemini:chat",
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"task_type": "video",
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"dimension_name": "video_duration_seconds",
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"source_type": "metadata",
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"source_path": "task.video_duration_seconds",
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"value_type": "float",
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"priority": 10,
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"is_enabled": True,
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},
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# 回退到请求的 duration_seconds(如果没有实际时长)
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{
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"api_format": "gemini:chat",
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"task_type": "video",
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"dimension_name": "video_duration_seconds",
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"source_type": "metadata",
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"source_path": "task.duration_seconds",
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"value_type": "int",
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"priority": 0,
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"is_enabled": True,
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},
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]
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