584beca22d21d5970ab4ecccf2f4f953708616d5
4 Commits
| Author | SHA1 | Message | Date | |
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 Jaroslav Beneš
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21001f2eb8 |
Knowledge, notes, memory and skills, and a harness to make them used
Four places a model can reach for, differing in who writes a record and how it gets in front of the model. **Knowledge** is uploaded by a person and searched by the model. It goes through `services/files.py:prepare` — the same pipeline as a chat attachment — so the same PDF produces the same text whichever way it arrived, and `Document` carries the same content columns as `Attachment` for the same reason. **Notes** are written by the model and edited by you. Too long to inject, so they are searched. **Memory** is short facts, and every one of them goes into every request. That single decision is where the rest of its design comes from: records are capped short, the block has a budget, there is no search tool because the model is already looking at them, and they are not shareable — a record about a person is not content to hand round. **Skills** are saved procedures. Only the name and description are injected; the body is fetched when the model decides one applies, which is what makes a hundred skills affordable. A model may write and revise its own — the safety story is not a gate but a record: every revision is kept, attributed and revertible. A model that has just read a hostile page can save a skill that outlives the conversation, and the honest mitigation is that it is visible and undoable rather than that it was prevented. **The harness** is why any of it gets used. A model handed a tools array ignores it and answers from recall, because nothing in the request suggests otherwise. `services/harness.py` assembles a preamble from what this chat actually has: when to reach for each tool, the memories, the skill index. This is an exception to "system prompts are precedence, not concatenation", and a deliberate one. That rule governs the three *authored* layers and is untouched — exactly one still wins. The harness is a different axis: it describes the machinery rather than the behaviour, nobody authored it, and there is nothing for it to disagree with. It is prepended to whichever authored prompt won, in one system message, since several endpoints reject a second. Supporting changes: - **Sharing**, in one helper. `visible_to()` is the only definition of who can see a library item and every listing and tool goes through it. Sharing grants *reading*; two people editing one note with no history and no merge is worse than copying it. **Administrators do not bypass this** — they bypass permissions elsewhere because an admin can grant themselves those anyway, but reading somebody's private notes is a different act. - **FTS5**, created by `db/migrations.py:ensure_fts` with the triggers an external-content index needs. Idempotent, like the column sync beside it. Terms are ANDed and then ORed: the caller is usually a model writing a whole question, and requiring every word loses the match on one absent term. - **The attach button is a menu** — file, image, a web page, or a document from the library. Attaching a document copies it, because history must not change when a document is edited later. - **A URL fetcher with an SSRF guard.** This server can reach the router, the other services on the box and LLeMbas itself, and the address can come from a model. Private ranges are refused *after resolution* and redirects are followed by hand so every hop is checked. An admin can open it deliberately. - **Model capabilities split** into protocol support and a toggle per built-in tool. Rows predating the split have no `tool_*` keys, and absent counts as on when `tools` is on — otherwise an upgrade silently takes web search away from every model already configured for it. Also fixes the test fixture, which built the schema with `create_all` and so ran against a database without the FTS tables production has; it now runs `sync_schema`, the same path startup takes. 430 tests, ruff clean. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com> |
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Jaroslav Beneš
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7456525d19 |
PWA, one send/stop button, audio in and out, web search as a tool
Four pieces of work.
**Installable.** A manifest carrying the instance name, PWA icons rasterised
from the existing mark at design time, a service worker and a themed offline
page. The worker caches the shell only and bails out on /api/, /auth/, /admin/
and anything accepting text/event-stream -- passing a reply stream through a
worker turns it into one delivery at the end, or nothing. It is served from
GET /sw.js rather than the static mount because a worker's scope is the path it
came from.
**Send and Stop are one button.** They were two, and the hidden one was never
hidden: `.btn` is display: inline-flex, which outranks the browser's own
`[hidden] { display: none }`, so Stop sat permanently beside Send. app.css now
forces the attribute to win -- every control toggled with `hidden` depended on
that -- and the composer renders one button carrying both icons, with ui.js
flipping data-composer-action and the type with it.
**Audio.** Speech to text and text to speech against any OpenAI-shaped
/v1/audio/* endpoint: dictate into the composer, have a reply read out.
Instance settings in Admin, per-reader overrides in Settings, with the voice
list discovered from the server where it offers one. Recorded audio is capped
and never written to disk -- it is not an attachment, it has no owner, and
nothing would ever sweep it.
**Web search, as a tool.** This is the tool loop PLAN.md described as the real
work: one reply is now a bounded sequence of requests rather than one. The model
asks, the tool runs, the result goes back and it is asked again, up to three
rounds. Providers are DuckDuckGo (no setup), SearXNG and Firecrawl.
Two decisions worth stating. Tools are only offered to models flagged `tools`,
because an endpoint without support rejects the whole request rather than
ignoring the array -- the same reason images only reach models flagged
`vision`. And tool results are not replayed as context on the next turn, for the
same reasons reasoning is not: the answer already contains what the model made
of them, and replaying stale results into every later request wastes the window
and reliably sends a small model into a search loop. The sources stay visible in
the transcript instead.
Search results are untrusted third-party text and are treated as such: escaped,
and only http/https URLs rendered as links.
338 tests, ruff clean.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
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Jaroslav Beneš
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bdce2764b1 |
File attachments: images for vision, PDFs and text into the prompt
Drag, paste or pick a file in the composer. Images go to vision models as multimodal content parts; PDFs and text files have their content extracted and placed in the prompt. Verified end to end against gemma4-e4b-q8 on llama-swap: given a drawing and a text file, it named the red square and blue circle and read the number out of the document. Type is decided by inspecting the bytes, never the filename or the browser's Content-Type -- a .png full of text is stored as text. Images are downscaled to 1400px and re-encoded: a phone photo is several megabytes of base64, which is slow and a large slice of the context window. PDF text is extracted once, at upload, and stored; re-extracting per request would let a reply change because a parser was upgraded. Design points worth keeping: - Images are only sent to models an administrator has marked `vision`. This is not graceful degradation -- most endpoints reject the entire request rather than ignoring an image part. A plain text turn stays a plain string for the same reason: the list form 400s on endpoints that do not implement it. - Images reach the model as base64 data URIs, not links. A local endpoint has no route back to LLeMbas, and a hosted one has no credentials for it. - Non-images are served Content-Disposition: attachment with nosniff, so an uploaded .html can never execute in this origin. Stored names are random; the uploader's name is a label and never a path. - Uploads are unbound until the message is sent, which is what lets a file be removed beforehand. claim() only takes unclaimed rows owned by the sender, so a forged id cannot pull in someone else's file. Abandoned uploads are swept at startup. - A scanned PDF says so rather than silently contributing nothing, and truncation is declared to the model in the document tag so it can admit it did not see page 400. - "Here, look at this" with no words is a legitimate turn, so a message is only empty when it carries neither text nor files. Also fixes auto-titling, which read message["content"] as a string and would have broken on the first multimodal turn. 186 tests, ruff clean. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com> |
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Jaroslav Beneš
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d6c87ac811 |
Users, groups, permissions, model settings and reasoning display
Four features, plus the schema machinery they needed. **Schema sync.** The first live instance had data in it, and create_all only creates missing *tables* -- a new column silently never appeared. db/migrations.py now diffs the declared models against the database and ALTER TABLE ... ADD COLUMN for what is missing, deriving a backfill default from the column type (SQLite refuses a NOT NULL column without one, and a Python-side `default=dict` cannot be expressed in DDL). Verified against a copy of the live database: eight changes applied, all rows preserved, second run a no-op. Renames, drops and retypes are still manual and say so. **Permissions.** A flat set of named booleans: an instance baseline widened by each group the user belongs to. A group grants and never denies -- with denies, "why can this user not do X" cannot be answered without simulating every group. Admins bypass entirely, because an admin can grant it back to themselves in two clicks and pretending otherwise is theatre. Model *access* is separate: public, or granted to groups. The picker is not the boundary -- switching a chat to a model you cannot reach is a 403. **Model settings.** Ordering, pinned-first, an instance default and a per-user default, display names, descriptions, capability flags, and uploaded images. Images are stored and served locally rather than by URL: a remote URL makes every page render a request to a third party. Uploads are validated by magic number, not the declared content type, and stored under a random name. Models with no image get a generated initial whose hue is derived from the model id, so it is stable. **Reasoning display.** Streams into its own collapsible block above the answer, labelled "Thought for 14 seconds", collapsed once finished, and never replayed as context on the next turn. Two sources: the reasoning_content delta field, and <think> tags inline in content -- the latter needs a streaming splitter because the tags arrive split across chunks. Models emitting no reasoning show nothing, via a :has() rule rather than JavaScript. Verified against qwen35-9b on llama-swap: 694 reasoning events, 52 answer tokens, cleanly separated. Two bugs found and fixed while testing: - A bare `Mapped[list]` relationship is treated by SQLAlchemy as a scalar and returns None instead of []. It needs the element type. - FastAPI substitutes the default for an empty form value, so with `x: str | None = Form(None)` a submitted `x=` is indistinguishable from an absent field. That silently broke clearing a system prompt or a temperature. update_chat now reads the raw form and checks key presence. 143 tests, ruff clean. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com> |