38 lines
2.8 KiB
Markdown
38 lines
2.8 KiB
Markdown
## Context
|
|
The multi-image tool already supports PDF context by caching the uploaded PDF and passing `pdfCacheUrl`, `pdfMimeType`, and `pdfName` into a `TaskType.CHAT` task. `TaskQueueService.buildChatInlineDataParts()` converts that cached PDF to Gemini `inline_data`, so the new popular-video flow should reuse this path instead of introducing a PDF extraction service.
|
|
|
|
The popular video tool stores workflow records as `AnalysisRecord` and downstream pages expect `analysis: VideoAnalysisData`. A prompt-based start can therefore create the same analysis shape without a source video.
|
|
|
|
## Goals
|
|
- Add a first tab/input mode named `提示词生成` before `上传视频`.
|
|
- Let users enter a creative prompt and optionally upload a PDF as Gemini context.
|
|
- Submit prompt generation through the unified task queue.
|
|
- Store the result as a normal popular-video record so Script and Generate pages keep working.
|
|
- Avoid persisting PDF base64 or full provider responses in history.
|
|
|
|
## Non-Goals
|
|
- No new PDF parser or backend endpoint.
|
|
- No new storage table/entity.
|
|
- No changes to video generation semantics after the script is created.
|
|
|
|
## Design
|
|
Extend the video analyzer task action from `analyze | rewrite` to include a prompt-generation action, for example `prompt-generate`. The task params carry:
|
|
- `prompt`: short task label for queue display
|
|
- `videoAnalyzerPrompt`: full Gemini instruction
|
|
- `videoAnalyzerAction: 'prompt-generate'`
|
|
- `videoAnalyzerSource: 'prompt'`
|
|
- optional `pdfCacheUrl`, `pdfMimeType`, `pdfName`
|
|
|
|
The task queue routes this action through the normal text generation path with `buildChatInlineDataParts()`, then finalizes the task with both markdown preview and structured `VideoAnalysisData`. Task sync creates an `AnalysisRecord` with `source: 'prompt'`, a prompt source label, and a lightweight source snapshot containing prompt text plus optional PDF metadata/cache reference.
|
|
|
|
Prompt generation should instruct Gemini to return the same JSON contract as video analysis: total duration, aspect ratio, style, BGM mood, characters, and ordered shots with first/last frame prompts, narration/dialogue, camera movement, and transitions. This keeps existing script editing, versioning, and video generation surfaces compatible.
|
|
|
|
## Error Handling
|
|
- Reject non-PDF uploads and PDFs above the existing multi-image limit.
|
|
- If a PDF is attached but no Gemini text model is available, show the same style of warning as the multi-image tool.
|
|
- If a cached PDF cannot be read while the task runs, fail the queue task with a clear message.
|
|
- If Gemini returns invalid JSON, mark the task failed and keep the current form state.
|
|
|
|
## Performance
|
|
The PDF remains a cached Blob reference until the task executes. Conversion to base64 happens only during Gemini submission, matching current multi-image behavior. No new long-lived large strings should be stored in workflow history.
|