update.sh now creates .env from .env.example if missing, idempotently fills in every random secret (same logic generate-secrets.sh had, now removed), resolves SEARXNG_LAN_IP from search.home via the host's own DNS, and mints OPENWEBUI_LITELLM_KEY / MEMORY_RETRIEVAL_EMBEDDING_KEY through LiteLLM's own /key/generate API once litellm is up — no more manual Admin UI step for the stack's own two workload keys. Docs updated to point at update.sh as the one command; docs/proxy-key-onboarding.md keeps the manual/API steps as the fallback and for onboarding other workloads. Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>
37 lines
3.3 KiB
Markdown
37 lines
3.3 KiB
Markdown
# LLM-Server
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Local AI inference stack: llama.cpp (ROCm) serving Qwen3.8-27B on an AMD Radeon AI PRO R9700, fronted by Open WebUI (RAG + Memory via Qdrant), with Lazytainer auto-suspending the inference container when idle.
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See the wayfinder map ([issue #1](https://git.arthurerlich.de/haylan/LLM-Server/issues/1)) for the full architecture rationale and open questions.
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## Quickstart
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```bash
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./scripts/download-model.sh
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./scripts/update.sh
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```
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`update.sh` creates `.env` from `.env.example` if missing, fills in every secret and per-workload virtual key it can generate itself (random secrets via `openssl`, `OPENWEBUI_LITELLM_KEY`/`MEMORY_RETRIEVAL_EMBEDDING_KEY` minted through LiteLLM's own `/key/generate` API, `SEARXNG_LAN_IP` resolved from `search.home` on this host), then pulls/builds/brings up the whole stack. Safe to re-run any time — it only fills in what's still blank and only recreates what changed. See [`docs/proxy-key-onboarding.md`](docs/proxy-key-onboarding.md) if a key mint fails and needs doing by hand.
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- Open WebUI: `http://<this-machine>:3000` locally, or `ai.home` / `ai.haylan.ch` once routed through Nginx Proxy Manager — see [`docs/network-access.md`](docs/network-access.md). First signup becomes the admin account (`WEBUI_AUTH` is on).
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- llama.cpp's own API is internal-only now — everything routes through the AI proxy below.
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Pointing Claude Code CLI, Kimi CLI, or OpenCode CLI at the local endpoint: see [`docs/coding-cli-setup.md`](docs/coding-cli-setup.md).
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**Known risk**: Qwen3.8-27B's tool-calling reliability against llama.cpp's Anthropic shim is not yet verified (open upstream parser bugs against its model lineage) — see `docs/research/qwen3.8-27b-tool-calling.md`.
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## AI proxy (LiteLLM)
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An [AI gateway/proxy](https://git.arthurerlich.de/haylan/LLM-Server/issues/9) fronts llama.cpp: per-workload virtual keys, usage tracking, and a shadow cost estimate ("what this would have cost on Claude Sonnet 5"). `./scripts/update.sh` handles `LITELLM_MASTER_KEY`/`LITELLM_SALT_KEY` and every other secret (see `.env.example`).
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- Proxy API: `http://<this-machine>:4000/v1` locally, or `proxy.ai.home` / `proxy.ai.haylan.ch` once routed through NPM — see [`docs/network-access.md`](docs/network-access.md).
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- Admin UI (`/ui`, key/budget management): LAN-only — see `docs/network-access.md`.
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- Issuing a key for a new workload: [`docs/proxy-key-onboarding.md`](docs/proxy-key-onboarding.md).
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- Request priority across workloads: [`docs/proxy-request-priority.md`](docs/proxy-request-priority.md).
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Open WebUI and the coding CLIs (see [`docs/coding-cli-setup.md`](docs/coding-cli-setup.md)) route through the proxy now — llama-server has no published host port anymore. **Not yet verified**: none of this has been smoke-tested on real hardware (LiteLLM's priority scheduler in particular is beta — see `docs/proxy-request-priority.md`) — see [issue #17](https://git.arthurerlich.de/haylan/LLM-Server/issues/17).
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### Web search, knowledgebase, and memory
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The gateway also fronts SearXNG-backed web search and a pgvector-backed knowledgebase (loaded with `data/memory.md` / `data/claude-legacy-memory.md`), wired at the LiteLLM layer so every client gets them, not just Open WebUI — see [`docs/memory-knowledgebase.md`](docs/memory-knowledgebase.md). **Not yet verified on real hardware** — see [issue #24](https://git.arthurerlich.de/haylan/LLM-Server/issues/24).
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