Replace the sample plugin with an AI chat summarizer that renders its
output as a native RichMessage injected into the chat.
Summarization pipeline:
- Fetch chat/topic history via paginated TL requests.
- Send a system prompt, the user's instructions and an anonymized JSON
transcript as three separate roles. Only message text and attachment
names leave the device; senders and message ids are replaced by
indices, and out-of-range reply parents are included with negative ids
so replies keep their context.
- Stream the response over SSE, reading reasoning from reasoning_content,
reasoning or inline <think> tags.
- Substitute the model's {userN}/{msgN} placeholders back into real names
and deep links. Placeholders are used instead of Markdown links because
a half-streamed link renders as broken literal text.
Rendering:
- Compile Markdown into TL_iv page blocks (headings, lists, quotes, code,
dividers, inline styles) since the app's own converter works off
Android Spanned spans rather than Markdown source.
- Show progress stages immediately on click, animate reasoning while it
streams, then collapse it into a tappable details block.
- Attribute the card to a client-side mock sender and insert it directly
after the newest analyzed message, scrolling it into view.
Persistence:
- Store summaries in SQLite keyed by (dialog, topic, anchor) and
re-inject them when the chat is reopened.
Also add tools/release.py and a Gitea workflow that builds, verifies and
publishes dist/<id>.plugin to the Releases tab, and extend
tools/verify_bundle.py to 104 offline checks covering the transcript,
streaming, rendering, injection and storage behaviour.
lyuksovannyy
exteraGramPlugins