Fabric Intelligence Knowledge (RAG)
Your indexed wikis, sheets, docs and code — plus sources configured in Settings → Knowledge. Weave retrieves the relevant chunks to answer "how do we…" questions.
Weave is the screen-aware assistant in Fabric. You talk to it in plain language; it answers using everything Fabric Intelligence knows — the knowledge index (RAG), what it has learned from past runs, live integration health, the queue, and each agent's confidence. Weave reads, reasons and routes; it never ships anything without your approval.
What it draws on
Weave isn't a generic chatbot bolted on — every reply is grounded in the same signals the agents use.
Your indexed wikis, sheets, docs and code — plus sources configured in Settings → Knowledge. Weave retrieves the relevant chunks to answer "how do we…" questions.
What Fabric Intelligence recorded from past runs: per-character success rates, the archetype it chose for similar tickets, and the decisions you made at the confidence gate.
Integration health, the batch queue, run history, and each agent's Harness confidence — so it answers about now, not a stale snapshot.
Weave knows the ticket, character, agent and screen you're looking at, so "what's the confidence here?" or "why did this hold?" resolve against your current context — you don't have to repeat yourself.
Identity and evidence-basis questions receive direct answers instead of unrelated dashboard summaries. Operational metrics are filtered and labeled by the selected agent and workspace; ordinary questions do not receive global run or health telemetry unless it is relevant to what you asked.
Ask “show me your learnings” for selected-agent outcomes, corrections and governed candidate states. Ask “in a mindmap” or “graphical view” for a native visual map of the evaluation → pilot → promotion → rollback lifecycle. These are live, scoped measurements—not model claims.
Settings → Weave shows context pressure and the exact active turns. Pin decisions that must remain verbatim, compact older unpinned turns into a bounded summary, archive finished context until it is explicitly restored, or permanently forget selected items. These lifecycle changes are durable and audited; archive restore fails closed if its stored digest no longer matches.
Useful cloud results become inert learning candidates. A candidate must pass deterministic server-side checks, accumulate a measured pilot of at least five samples with 80% success and zero regressions, and be explicitly promoted before Weave may reuse it as advisory context. Every transition is digest-bound and audited, and promoted learning can be rolled back. Learning never changes model weights, agents, validators, permissions or approval gates.
The Conversational Orchestrator resolves social dialogue, follow-ups, corrections, scope and requested format before action routing. An authoritative task ledger keeps each Main or branched conversation’s objective, subject, requested format, verified evidence references, decisions, unresolved requirements and next safe step—never credentials, raw prompts or full answers. Branches inherit typed context explicitly and can merge it back without losing their audit trail. Free-form turns receive the smallest relevant Weave specialists plus up to two enabled domain playbooks matched from the repository. Vision, Data, Ticket Investigation and Clarification specialists now join the existing knowledge, code, operations, planning and visual skills. The enforcing Answer Critic repairs or replaces empty, unscoped, unresolved, wrong-format or clearly off-topic model answers before display.
Each answer can expand Sources & skills to show the exact skill set and bounded RAG, Graphify or attachment evidence used. Weave also records privacy-bounded skill effectiveness observations—selection, answer-quality issues and repairs—so skill routing can be evaluated from outcomes instead of intuition.
Weave first separates the user's goal from its subject, then traverses a declarative goal → subject → capability → intent graph. The capability directory resolves specific questions before generic commands—for example, “explain Fabric Intelligence” selects product architecture while “explain the failed run” selects operational evidence. Every selected route includes a bounded, inspectable path instead of depending on ordered keyword exceptions.
Rich, multimodal conversation
Attach files with the + button, drag them onto Weave, or paste an image. Weave keeps each request and its attachments together even when you continue typing while an earlier answer is still processing.
PNG, JPEG and WebP previews appear directly in the conversation and can be examined by local Fabric Intelligence Vision. Image metadata and bounded visual findings ground the answer.
Text, Markdown, code, PDF, Word, CSV/TSV, Excel, JSON/JSONL, YAML, XML and HTML are read through governed parsers. Unknown binary files remain metadata-only and are never executed.
Replies support headings, lists, links, highlighted evidence, tables, code blocks, image cards and local bar or line charts. The top-left resize control cycles through standard, wide and centered-focus views.
Attachments are owner-scoped, short-lived and size/count limited. Their paths are never disclosed to the browser, and a file is never treated as executable input.
Say “load a local file” (common misspellings are accepted) to open the native file picker immediately, or use Attach, drag and drop, or paste. The picker is opened directly from your gesture so browser security does not block it.
What you can say
“are all integrations healthy?” · “is Perforce connected?” · “what's the queue doing?” · “anything stuck / hanging?”
“show me the open GOTL tickets” · “find flat-art tickets for Lyanna” · “run GOTRPG-56000” · “what's the status of GOTRPG-53726?”
“build an agent for GOTRPG-54789” (opens AI Draft, grounded — you Publish) · “delete agent PG Setup” (asks to confirm) · “open Fabric Studio”.
“why is this only 72%?” · “how did Fabric Intelligence decide to ship this?” · “what's Lyanna Mormont's track record?” · “what did we approve last time here?”
“how do we set up a Proving Grounds event?” · “what's the content-stripping step?” — Weave answers from the indexed wiki/docs and cites the source.
“review this screenshot” · “compare these CSV formulas” · “investigate GOTRPG-56000” — Weave selects the matching Vision, Data or Ticket specialist and exposes its sources.
“take me to the queue” · “open pending approvals” · “show history” — Weave drives the UI for you.
Boundaries
Read state, retrieve knowledge, explain a decision, draft an agent for review, queue a run, and navigate. Everything it does is either read-only or lands as a reviewable draft/queued job.
Commit, push, write an agent, or take any outward action without your explicit sign-off. A "build an agent" request produces a draft you Publish; a "run" request queues a job whose irreversible steps still hold at the human gate.
If Weave can't answer from real signals, it says so and points you at the screen or source — it doesn't invent an answer. Free-form reasoning is capability-routed when Fabric Intelligence AI is on — it runs on a local model or, for the reason/code lanes, a cloud specialist under budget, degrading to local automatically; with Fabric Intelligence AI off, Weave stays on the deterministic knowledge/health/queue answers.
When a code question names a file or symbol, Weave can use the governed Code Intelligence seam with Graphify as its first provider. Only bounded, revision-bound findings enter the answer as derived advisory evidence; raw graph artifacts never enter the prompt, and structural evidence never overrides compilation, tests, policy or approval.
Make it smarter
Weave is only as knowledgeable as what Fabric Intelligence has been given. Use Settings → Knowledge to add supported local, web or Google Sheets sources and refresh the index. Index playbooks separately in Settings → Skills. Verify source access, freshness and citations.
Enabled repository skills can be composed into a Weave answer when their name and description strongly match the request. This extends Weave with team-specific procedures without granting those playbooks execution authority; action and approval boundaries remain unchanged.
In Settings → Knowledge · RAG, choose Auto to rebuild the local Graphify AST index when Git HEAD changes, or Manual to keep updates operator-triggered. The status shows the indexed and current revisions. Graph refresh is local, bounded to one build at a time, and has no LLM or API cost.
Reference
| Setting | Effect |
|---|---|
| Automatic context | Prioritize the active node, dialog, agent, screen and workspace. |
| Selected node / Active agent / Active screen / Workspace | Choose which contextual elements are included. |
| Screen vision | Enable one-frame assistance when explicitly requested. Browser screen-sharing confirmation remains mandatory. |
| Capture confirmation | Always required; cannot be disabled by this preference. |
| Close after navigation | Reveal the destination when Weave opens a screen. |
| Rich answers / State icons | Control formatting and semantic status icons. |
| Personality | Professional, Balanced or Expressive presentation. |
| Animated reactions | Optional local reactions; respect reduced motion. |
| Remember conversation | Keep recent messages in this browser; not the same as backend memory retention. |
| Conversation limit | Browser message retention, from 5 to 200. Not the model’s context-window size. |
| Show active model | Display the routed model while working. |
| Keyboard shortcut | Enable Command/Ctrl + K for Weave. |
| Manage policy | Master-level policy defaults/locks. A locked preference requires policy administration, not a UI workaround. |
Reference
Weave’s backend working memory is scoped to the workspace/session. It retains up to 40 active turns and a rolling summary of older context, then selects a token-budgeted slice for each request. The displayed durable capacity is not a promise that all memory enters a single prompt.
Use the memory panel to inspect retained turns and persistence status. Archive session creates a context checkpoint; restore and forget controls act on the selected context/archive. Forgetting conversation context does not erase authoritative run/audit records or undo external work.
Agent stage observations and skill-use evidence are retained separately from conversational recall. Interrupted or review-paused work must stay distinguishable from successful execution. A memory persistence error is a storage problem to investigate, not evidence that the observation was saved.
Reference
Default discovery includes project playbooks and configured writable skill locations. Development code root influences which project is inspected; deployments may override discovery roots. The installed profile can restrict factory/executable skill changes.