levelbuilder: generate lesson with AI (and project)#72651
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New optional field on the lesson generator: a Web Lab 2 channel id whose project source describes the app the lesson is building toward. When set, the per-level AI prompts get the project's files as additional "final goal" context so each weblab2 level reads as a step on the path to that app, and adjacent panels can motivate or foreshadow concepts that show up in the code. The student never sees the target source; it lands only in the AI prompt. Backend - Add generate_project_channel_id serialized_attr on Lesson, exposed as generateProjectChannelId in summarize_for_lesson_edit and permitted by LessonsController#lesson_params. Frontend - New field on /generate above the prefix row; persisted alongside the outline by the existing saveLessonActivities save path. '' on save clears the value. - helpers/targetProject.ts: format the channel's MultiFileSource into a flat "=== path ===\n<contents>" listing for the prompt. Skips non-user file types and bails to null on shapes that aren't MultiFileSource (Blockly, Excalidraw, missing source). - levelApi.ts: loadProjectSources(channelId) hits GET /v3/sources/<id>/main.json (the same endpoint Lab2 uses at runtime; unauth-gated by abuse-score only). - LessonGenerator fetches once per run, formats, threads through to every panels and weblab2 per-level call. Both AI prompts grow an explicit "Target project" section instructing the model to use it as a destination, not to emit it verbatim — the per-level description still scopes what the current level should build. - Soft-fail end-to-end: a missing channel id, a failed fetch, or an unreadable shape just runs the generator without the extra context. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
The outline phase is the highest-leverage decision in the run (it picks the entire level sequence) and previously didn't see the target project at all. Now it does: generateLessonOutline takes an optional targetProject and quotes it under a "Target project" section telling the model to plan weblab2 milestones as steps from blank to that code, and to pick panels that motivate or recap the concepts the target uses. Refactor the source-fetch out of handleGenerate into a shared loadTargetProject callback used by both handleGenerateOutline and handleGenerate, so each invocation re-fetches (cheap; avoids stale data if the channel id changes mid-session). Errors stay soft-failing: no channel id, a failed fetch, or an unreadable shape just runs the call with no target context — same as before this change. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
The field feeds straight into the Generate-outline call, so putting it inside the same collapsible panel — between the outline textarea and the Generate-outline button — makes the data flow visible. The levelbuilder reads top-to-bottom: describe the lesson, name an optional target app, click Generate. Adds .outlineProjectRow / .outlineProjectInput styles to match the rest of the block (label above, help text below, 360px input). Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
Matches the outline-textarea pattern above it (description prose before the field). Also switches the help element from <small> to <p> so it sits in the normal paragraph flow above the input rather than visually attaching to whatever followed. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
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This builds on #72537 with an idea from @Erin007: an optional weblab2 project ID can be provided, and it's then passed as context to the lesson outline & lesson levels generation steps.
This means a levelbuilder can provide an example project which the generation process can then teach step by step.