publish_ai_models.py produces the CDN artifacts for every AI_MODELS
entry — GPG-signed .meta4 sidecars (reusing the map trust chain) and
the signed ai/models.json manifest — and uploads them with s3cmd.
The bundled catalog now carries the real sha256/size of the two Qwen
GGUFs, which match Hugging Face's LFS records for the Apache 2.0
unsloth quants, and whose signed meta4s verify against the committed
public key.
Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
Every MCP tool is now one /api/ai call with minimal text rendering;
the formatting, link building, and truncation logic it used to carry
untested lives (tested) in modules/ai. Tool names are unchanged for
external clients; a source-scan test guards the names and that the
proxy only reaches /api/ai. New lean blueprint endpoints back the two
tools that had no equivalent: GET archives/{id} (detail + snapshot
history) and GET videos/{id}/comments (paged author lines). Paged
content is read up to the old 50k-char bound. get_inventory_items now
takes the inventory slug (inventories are config-only; the old
numeric-id endpoint no longer exists). This also brings wrolpi_mcp
into version control (venv/ is already gitignored).
Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
Tool definitions are generated in-process from the /api/ai blueprint's
own OpenAPI operations (operationId = tool name, description = tool
description, dataclass bodies + declared parameters = one flat JSON
schema) — the spec IS the catalog, nothing to drift. Manage endpoints
never become tools. A mode is a server-enforced system prompt + tool
allowlist (Help / Research / System per ai.md); the executor can only
reach allowlisted /api/ai endpoints, path parameters are encoded and
traversal-rejected so a crafted argument cannot escape an endpoint.
POST /api/chat streams SSE (status/token/tool_call/tool_result/done/
error), starts llama-server on demand, validates tool args server-side
with instructive errors the model can retry on, caps tool results with
a paging hint, and bounds the loop by ai.yaml max_tool_calls plus a
hard timeout. Caddy passes the stream unbuffered (flush_interval -1)
in both deployments.
Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
install_llama_cpp.sh builds llama-server from the SHA-pinned v0.3.0
source tarball (single source of truth: on-device upgrade, Pi image,
Live ISO, and the new docker/llm container all call it; version-marker
makes re-runs no-ops). start_llama_server.sh refuses to start unless
ai.yaml enables AI and the active model file exists — which also covers
unmounted media. wrolpi-llm.service is installed but deliberately
never enabled at boot: the Controller starts it on demand (registered
in managed_services; the llm compose service follows the samba
pattern), and the API's perpetual idle-unload worker asks the
Controller to stop it after the configured idle minutes. llama-server
is localhost-only natively, internal-network-only in docker, and never
proxied by Caddy.
Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
ai.yaml is the source of truth (opt-in: enabled=False by default) with
active model, idle-unload minutes, context override, and tool-call
bound. The model catalog follows the map pattern: a bundled constant
keeps the Manage tab working offline, the CDN manifest (ai/models.json
+ detached GPG signature) wins when reachable. GGUF downloads clone
the map-extract flow — the per-file meta4 is GPG-verified once and the
same bytes handed to aria2c, so the verified hash is the enforced one;
unverified downloads are refused. Models land in <media>/ai/models/
(gated by the existing media_mounted download rules). Manage endpoints
(catalog with RAM-tier recommendation, settings) live under
/api/ai/manage/ which the future agent loop excludes from its tool
catalog.
Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
Search the wrolpi-help markdown in-process: files are parsed on demand
and cached by mtime; title matches outrank headings outrank body. No
database table — the corpus is dozens of small files. Pages are read
as paged markdown. The docker api container gets a read-only bind
mount of the help docs at the native /opt/wrolpi-help location; a
missing help directory degrades to empty results with a message.
Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
Proxy the Controller under /api/ai so the model sees one API: an
aggregate /status to start every diagnosis, lean service list, recent
service logs (lines clamped), and disks + SMART. One controller_client
helper resolves the Controller base URL (docker service name vs
localhost). Every proxy degrades to an `errors` entry when the
Controller is unreachable — never a 500.
Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
Lean, flat, LLM-shaped read-only endpoints over the library: global,
video, archive, and doc search; paged captions, archive text, and zim
entries; collections, inventories, and a media-directory text reader.
Links are server-computed; big content is paged, never truncated.
This ports the formatting layer from wrolpi_mcp (untouched for now)
into tested code. First phase of ai.md.
Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
