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CSA Loom — the Microsoft Fabric experience for Azure tenants where Fabric isn't yet available: lakehouses, warehouses, notebooks, semantic models, Activator rules, Data Agents, across Commercial, GCC, GCC-High, and DoD IL5

Loom Copilot runtime

The Loom Copilot is the chat assistant that appears throughout the Loom Console as a right-side sidebar drawer (or full-screen chat at /copilot). Same agent infrastructure as the Loom Setup Wizard and Loom Data Agents — different system prompts and tool catalogs per context.

What it does

The Copilot serves multiple personas via system-prompt selection:

Context Persona Tool catalog
Setup Wizard (/setup) "loom-deploy-agent" render_bicepparam, submit_deployment, poll_deployment, MCP tools
Console sidebar (every pane) "loom-copilot" NL2SQL, NL2DAX, NL2KQL, doc-search, workspace-search, capacity-check
Notebook embed "notebook-copilot" /explain, /fix, /comments, /optimize
Warehouse pane "warehouse-copilot" NL2SQL, EXPLAIN, optimize-query
Semantic Model pane (v1.1) "dax-copilot" NL2DAX, DAX-explain, optimize-DAX
KQL pane "kql-copilot" NL2KQL, KQL-explain
Activator pane "activator-copilot" rule-author, threshold-suggest
Data Agents pane "agent-config-copilot" example-query-generate, field-description-generate
Admin pane (v1.1) "ops-copilot" capacity-scale, OAP-toggle, workspace-create

Tech stack

Per PRP-09 Data Agents: reuses the existing csa-inabox copilot scaffold.

  • Agent framework: PydanticAI (existing apps/copilot/)
  • Inference: Azure OpenAI per boundary
  • Chat backend: extended azure-functions/copilot-chat/function_app.py with /api/loom-chat and per-context endpoints
  • Identity: OBO throughout (per AMENDMENTS A15)
  • Security: rate limiting, PII redaction, content safety, telemetry, feedback loops — all inherited from existing copilot-chat infrastructure

Capacity isolation

Boundary AOAI deployment
Commercial / GCC Dedicated "Loom Copilot Capacity" per organization
GCC-High / IL4 / IL5 Per-DLZ AOAI deployment (tighter Gov TPM quotas)

Telemetry + feedback

Reuses the existing feedback + backlog mechanism from azure-functions/copilot-chat/function_app.py:

  • Per-turn telemetry (input length, output length, model invoked, PII detection results, off-topic / refusal detection, session ID, conversation ID)
  • 👍 / 👎 feedback per response
  • Thumbs-down opens improvement-text modal → persisted to backlog
  • Uncovered-question detection (off-topic OR zero grounding hits) → auto-files to backlog as kind=uncovered

In Gov, telemetry feeds the Sentinel pipeline that replaces Defender for Cloud AI Threat Protection.

The Copilot drawer appears on every Console pane (right-side, collapsible). Default closed; user-toggleable. Per-pane context is automatically loaded into the system prompt (e.g., on Warehouse pane, the active query + table schema are included as context).

Full-screen chat

/copilot route opens the Copilot in full-screen mode for extended conversations. Same tool catalog as the active workspace context (or admin context if accessed from Admin).