haylan
9e9cac254b
OmniRoute's memory feature is self-contained: its bundled sqlite-vec vector store plus a local ONNX embedding model (Transformers.js, ~400MB, fetched into the omniroute-data volume on first use) replace the external qdrant + bge-small-en-v1.5 embedding-server pair, which was never wired up in the dashboard. Two fewer containers, no second GGUF download, no EMBEDDING_MODEL_FILE var. Memory stays opt-in via the dashboard (Settings -> Memory, transformers source); nothing here changes the gateway's static config.
41 lines
4.0 KiB
Markdown
41 lines
4.0 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 the OmniRoute AI gateway, 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/update.sh
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```
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`update.sh` creates `.env` from `.env.example` if missing, fills in every random secret it can generate itself (via `openssl`, `SEARXNG_LAN_IP` resolved from `search.home` on this host), downloads the model GGUF into the `models` volume if it's not there yet, then pulls/builds/brings up the whole stack. Safe to re-run any time — it only fills in what's still blank, skips the model if already downloaded, and only recreates what changed.
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llama.cpp's own API is internal-only — everything routes through the AI gateway 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 gateway (OmniRoute)
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An [AI gateway/proxy](https://git.arthurerlich.de/haylan/LLM-Server/issues/9) fronts llama.cpp: per-workload API keys and usage tracking. As of [issue #31](https://git.arthurerlich.de/haylan/LLM-Server/issues/31) this is [OmniRoute](https://github.com/diegosouzapw/OmniRoute), replacing the original LiteLLM setup. `./scripts/update.sh` handles most of OmniRoute's secrets (see `.env.example`); per-workload API keys still need minting by hand in the dashboard — see [`docs/proxy-key-onboarding.md`](docs/proxy-key-onboarding.md).
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- Gateway API: `http://<this-machine>:${OMNIROUTE_PORT:-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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- Dashboard (key/provider management): LAN/host-only, never published to the internet — 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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Coding CLIs (see [`docs/coding-cli-setup.md`](docs/coding-cli-setup.md)) route through the gateway — llama-server has no published host port. **Not yet verified**: none of this has been smoke-tested on real hardware yet — see [issue #31](https://git.arthurerlich.de/haylan/LLM-Server/issues/31)'s tickets for the open items (provider registration, per-workload key minting).
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**Note on this choice**: OmniRoute's own docs (`docs/security/STEALTH_GUIDE.md`, `MITM-TPROXY-DECRYPT.md`, `PUBLIC_CREDS.md` in its repo) describe shipped features for evading AI-provider client detection, system-wide HTTPS interception via a locally-installed root CA, and hiding credentials from secret scanners. None of that is used by this stack's configuration, but it's a real characteristic of the upstream project — see issue #31's Notes for the full research trail before extending this integration further.
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### Web search
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The gateway also fronts SearXNG-backed web search — see `docs/research/litellm-searxng-search.md` for the original research (still applicable — same standalone-endpoint pattern, see issue #31's #35).
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## What's not here
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- **Open WebUI** — this stack has no chat UI; every client is a coding CLI. Removed rather than kept idle.
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- **Gateway-level knowledgebase/memory** (`litellm-pgvector`, `pgvector-db`, a dedicated embedding model) — removed as unwanted, unrelated to OmniRoute's own lack of parity with it (see issue #31's #34). Superseded by OmniRoute's own built-in memory feature (opt-in via the dashboard, Settings → Memory): vector store is its bundled `sqlite-vec`, embeddings are a local ONNX model (Transformers.js, ~400MB, downloaded into the `omniroute-data` volume on first use) — no external services, no static config here.
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