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6
Commits
| Author | SHA1 | Date | |
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05abc3291f | ||
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35a8a8d975 | ||
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a003df0ef8 | ||
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f0e48b226a | ||
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669ef1c5ee | ||
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68865e15c5 |
@@ -2,7 +2,12 @@
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Converts one MS-01 from "Proxmox host running a Talos VM" to "Talos on bare
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metal", and swaps its Ceph OSD onto a Samsung PM983 at the same time. Written
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after doing jupiter on 2026-08-25; saturn and neptune remain.
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after doing jupiter on 2026-08-25.
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All three nodes are now on bare metal — `talosctl get systeminformation`
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reports Minisforum MS-01 hardware with distinct chassis serials for k8s-1,
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k8s-2 and k8s-3, with no hypervisor in between. Kept as the procedure for a
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rebuild, not as outstanding work.
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Everything here that reads like an over-specific warning is something that
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actually happened. The conversion itself is straightforward — the failures were
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@@ -111,9 +111,23 @@ statistics max_id=13323904 max_start_ts=1787162400.0
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statistics_short_term max_id=159205762 max_start_ts=1787166000.0
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```
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## Phase 2c — cutover (REMAINING)
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## Phase 2c — cutover: DONE
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Do not start until phase 1 is verified.
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Verified 2026-09-02 against the live database:
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| table | rows | span |
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|---|---|---|
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| `statistics` | 11,092,586 | 2024-03-13 20:00 → current |
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| `statistics_short_term` | 1,883,709 | rolling ~7 days |
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| `statistics_meta` | 1,480 | |
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The 2024-03-13 origin is the proof that matters. It is unchanged from the
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pre-migration count in "What is at risk" above, so the history was copied
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across engines rather than started from zero — which is the failure this
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document exists to prevent. `states` carries current rows, so `db_url` points
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at Postgres.
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The procedure below is kept as the record of what was done.
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**Migrate statistics only.** Copying all 18M `states` rows is slow, needs a long
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HA outage, and buys a table that is discarded within 7 days anyway.
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@@ -56,10 +56,9 @@ spec:
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# Re-rendered on every pod start, so a CNPG password rotation takes
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# effect rather than silently leaving a stale URI behind.
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#
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# INERT until the recorder is repointed: nothing reads this key until
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# `db_url: !secret recorder_db_url` lands in configuration.yaml in the
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# homeassistant repo. That ordering is required — HA refuses to start
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# when a referenced secret is missing.
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# Load-bearing: `db_url: !secret recorder_db_url` in the homeassistant
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# repo's configuration.yaml reads this key, so HA does not start
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# without it. Removing this init container takes the recorder down.
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- name: render-db-url
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image: busybox:1.36
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command:
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@@ -18,12 +18,12 @@
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# That is the point of the move — it attacks the multiplier rather than trimming
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# what gets recorded, which would only hide the problem.
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#
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# STAGING
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# Phase 1 (this manifest): the cluster comes up EMPTY and HA keeps using SQLite.
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# Nothing depends on it, so a failure here is inert. Verify Ready, WAL archiving
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# to Hetzner, and a successful base backup before going further.
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# Phase 2: migrate the statistics tables and repoint recorder.db_url.
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# See MIGRATION-recorder-postgres.md for the sequence and the rollback.
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# This is the live recorder database. HA writes here; the SQLite file is no
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# longer the system of record. The 2.4 years of long-term statistics were
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# copied across engines rather than regenerated — HA does not migrate data
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# between database engines, so an empty Postgres would have silently started
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# from zero and taken the energy dashboard's history with it.
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# MIGRATION-recorder-postgres.md holds the sequence that was followed.
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apiVersion: postgresql.cnpg.io/v1
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kind: Cluster
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metadata:
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@@ -60,9 +60,8 @@ resources:
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- zigbee2mqtt-gate-service.yaml
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- zigbee2mqtt-ingress.yaml
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# Postgres backend for the recorder (MIGRATION-recorder-postgres.md).
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# PHASE 1: this cluster comes up EMPTY and nothing consumes it — HA is still
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# on SQLite. Deploying it is therefore inert; phase 2 migrates the statistics
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# tables and repoints recorder.db_url in the homeassistant repo.
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# Live: recorder.db_url in the homeassistant repo points here, and the
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# long-term statistics carry their full history from 2024.
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- ha-pg-hetzner-creds-externalsecret.yaml
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- ha-pg-objectstore.yaml
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- ha-pg-cluster.yaml
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@@ -44,12 +44,37 @@ spec:
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- Qwen/Qwen3-Embedding-0.6B-GGUF:Q8_0
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# Serves POST /v1/embeddings.
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- --embeddings
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# A short, stable id for consumers. Without it the model is
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# advertised as the whole --hf-repo string, which would end up
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# verbatim in Paperless's config and break on the next model swap.
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# One name only: llama-server keeps aliases in a sorted set and
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# reports the first as the id, so a second name can steal it.
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- --alias
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- qwen3-embedding-0.6b
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# Qwen3-Embedding is trained for last-token pooling. Left
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# unspecified llama-server takes the GGUF's default, which is not
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# visible from outside and would silently produce vectors the model
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# was not trained to emit. Set before anything is indexed: changing
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# pooling later invalidates every stored embedding.
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- --pooling
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- last
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- --n-gpu-layers
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- "99"
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- --threads
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- "2"
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# Paperless chunks documents at 1024 tokens. The defaults are
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# batch 2048 / ubatch 512, and with --embeddings llama-server
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# clamps both down to 512 rather than run them mismatched — below
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# the chunk size. Matching both to 1024 fits a whole chunk in one
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# pass; 2048 is deliberately avoided, since that is where this
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# Vulkan stack fails with ErrorDeviceLost.
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- --batch-size
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- "1024"
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- --ubatch-size
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- "1024"
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# Room for a full chunk plus overhead rather than exactly one.
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- --ctx-size
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- "2048"
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- "4096"
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# No browser ever talks to this Service, so the WebUI is dead weight
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# and one more unauthenticated surface.
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- --no-webui
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@@ -57,6 +57,20 @@ spec:
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protocol: UDP
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- port: "53"
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protocol: TCP
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# The cluster's own LLM, for AI suggestions and RAG embeddings. Scoped to
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# the two pods and the one port rather than the ai namespace as a whole, so
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# this grant cannot widen if something else is ever placed there.
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- toEndpoints:
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- matchLabels:
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"k8s:io.kubernetes.pod.namespace": ai
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app.kubernetes.io/name: llama-server
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- matchLabels:
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"k8s:io.kubernetes.pod.namespace": ai
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app.kubernetes.io/name: llama-embed
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toPorts:
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- ports:
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- port: "8080"
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protocol: TCP
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# External HTTPS only — Tika model downloads, runtime image
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# fetches, etc. RFC1918 + ULA are excluded from `world` via the
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# CIDR-deny pattern. `world` covers public IPs / DNS-resolvable
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@@ -46,6 +46,44 @@ data:
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PAPERLESS_TIKA_ENABLED: "1"
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PAPERLESS_TIKA_ENDPOINT: "http://tika:9998"
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PAPERLESS_TIKA_GOTENBERG_ENDPOINT: "http://gotenberg:3000"
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# AI suggestions against the cluster's own LLM (kubernetes/apps/llama-server).
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# Nothing leaves the cluster: both endpoints are ClusterIP Services, so
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# document text is never sent to a third party and there is no API key to
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# rotate — llama-server has no authentication, and the ai namespace's network
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# policy is what restricts who may reach it.
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#
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# CAVEAT, and it is a real one: paperless reads these from an
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# ApplicationConfiguration row in the database and falls back to the
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# environment only when that row is empty. A value set in the admin UI
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# therefore overrides this ConfigMap silently. Configure AI in ONE place —
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# here — and leave those fields untouched in the UI.
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PAPERLESS_AI_ENABLED: "true"
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PAPERLESS_AI_LLM_BACKEND: "openai-like"
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PAPERLESS_AI_LLM_ENDPOINT: "http://llama-server.ai.svc.cluster.local:8080/v1"
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# Must match --alias in kubernetes/apps/llama-server/deployment.yaml. The
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# server ignores the field on the wire, but paperless sends it and the value
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# is what appears in its logs.
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PAPERLESS_AI_LLM_MODEL: "qwen3.6-35b-a3b"
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# ClusterIP addresses are private, and paperless blocks non-public endpoints
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# unless this is set. Default is already true; explicit because the whole
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# integration silently stops working if it ever flips.
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PAPERLESS_AI_LLM_ALLOW_INTERNAL_ENDPOINTS: "true"
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# Under llama-server's own 16384, leaving room for the response.
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PAPERLESS_AI_LLM_CONTEXT_SIZE: "12288"
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# The 120s default is too tight at ~11 tok/s: a classification is roughly
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# 2-4k prompt tokens plus a second round trip for localisation.
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PAPERLESS_AI_LLM_REQUEST_TIMEOUT: "300"
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# Matched against Django's settings.LANGUAGES, so the region is required —
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# "de" alone does not resolve. Without it the model returns German tags but
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# English document types, which was reproducible against this endpoint.
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PAPERLESS_AI_LLM_OUTPUT_LANGUAGE: "de-de"
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# RAG embeddings from llama-embed. Its Qwen3-Embedding covers 100+ languages,
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# where paperless's default all-MiniLM-L6-v2 is documented as suited to
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# primarily English archives — the better fit for a German corpus.
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PAPERLESS_AI_LLM_EMBEDDING_BACKEND: "openai-like"
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PAPERLESS_AI_LLM_EMBEDDING_ENDPOINT: "http://llama-embed.ai.svc.cluster.local:8080/v1"
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PAPERLESS_AI_LLM_EMBEDDING_MODEL: "qwen3-embedding-0.6b"
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PAPERLESS_AI_LLM_EMBEDDING_CHUNK_SIZE: "1024"
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---
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apiVersion: apps/v1
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kind: Deployment
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@@ -58,6 +96,13 @@ metadata:
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# Reloader restarts paperless when paperless-secrets changes (e.g. after a
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# secret-key rotation). See kubernetes/infrastructure/openbao/rotation/paperless.yaml.
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secret.reloader.stakater.com/reload: paperless-secrets
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# And when paperless-config changes. The ConfigMap is consumed with
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# envFrom, and Kubernetes does not restart a pod when a ConfigMap it reads
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# that way is updated — the running container keeps the environment it
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# started with. Without this, a settings change applies cleanly in git and
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# in the cluster while the application never sees it, which is how the AI
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# settings landed with no effect at all.
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configmap.reloader.stakater.com/reload: paperless-config
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spec:
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replicas: 1
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strategy:
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@@ -24,6 +24,16 @@ spec:
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- ports:
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- port: "8080"
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protocol: TCP
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# Paperless calls both models for AI suggestions and RAG embeddings. The
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# matching egress grant on its side is scoped to these two pods on :8080.
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- fromEndpoints:
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- matchLabels:
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"k8s:io.kubernetes.pod.namespace": paperless
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app.kubernetes.io/name: paperless
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toPorts:
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- ports:
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- port: "8080"
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protocol: TCP
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- fromEndpoints:
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- matchLabels:
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"k8s:io.kubernetes.pod.namespace": monitoring
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Reference in New Issue
Block a user