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tiennm99
3ea1b39e44
Rename database services to db and cache services to cache, with their volumes as db-data and cache-data, in litellm, owncloud and goclaw. Rename the couchbase and open-webui volumes to <service>-data. Data on miti-sg was copied into the new volumes beforehand; the old volumes are kept.
84 lines
3.8 KiB
Markdown
84 lines
3.8 KiB
Markdown
# litellm
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[LiteLLM](https://docs.litellm.ai) proxy: one OpenAI-compatible endpoint in
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front of many LLM providers, with virtual keys, spend tracking and an admin UI
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at `/ui`.
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Three containers: `litellm`, `db` (PostgreSQL) for keys, teams, budgets and spend
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logs, and `cache` (Redis) for the response cache.
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## Setup
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1. Set `LITELLM_MASTER_KEY`, `UI_PASSWORD`, `POSTGRES_PASSWORD`,
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`OPENROUTER_API_KEY` and `GEMINI_API_KEY`. Uncomment any other provider key
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whose models you use, in both `compose.yml` and the environment.
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2. Map the domain to port `4000` and deploy. Prisma migrations run on start.
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3. Open `/ui` and log in with `UI_USERNAME` / `UI_PASSWORD`.
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Health check: `GET /health/liveliness`, also the compose healthcheck.
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## Models
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`config.yaml` holds the model list, the `model_group_alias` routing and the
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proxy settings. The `Dockerfile` copies it to `/app/config.yaml`, so editing it
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rebuilds and redeploys the service.
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It is built into the image rather than bind-mounted because Coolify does not
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place repository files beside the compose file it runs: a `./config.yaml` bind
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mount finds nothing there, and Docker mounts an empty directory in its place. Every provider key in it is an `os.environ/` reference,
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so the file carries no secrets.
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Models can also be added in the admin UI. `STORE_MODEL_IN_DB` keeps those in
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PostgreSQL, so they survive a redeploy without touching the file.
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## Environment
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| Variable | Default | Purpose |
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| --- | --- | --- |
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| `LITELLM_MASTER_KEY` | — | Admin API key; must start with `sk-` |
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| `UI_USERNAME` / `UI_PASSWORD` | `admin` / — | Admin UI login |
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| `POSTGRES_USER` / `POSTGRES_PASSWORD` / `POSTGRES_DB` | `litellm` / — / `litellm` | Database credentials, read by both containers |
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| `OPENROUTER_API_KEY` | empty | OpenRouter models, including `openrouter-free`, the alias target |
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| `GEMINI_API_KEY` | empty | Gemini chat models and `gemini-embedding-001` |
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| `STORE_MODEL_IN_DB` | `True` | Keep UI-added models in PostgreSQL |
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| `LITELLM_MODE` | `PRODUCTION` | Skips loading a `.env` inside the container |
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| `LITELLM_LOG` | `ERROR` | Log level |
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| `TOKENROUTER_API_KEY`, `ORCAROUTER_API_KEY`, `KIMI_API_KEY`, `MINIMAX_API_KEY`, `KILO_API_KEY`, `OPENCODE_API_KEY`, `NVIDIA_NIM_API_KEY`, `OLLAMA_API_KEY` | optional | Keys for the other providers in `config.yaml` |
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| `CLOUDFLARE_API_KEY` / `CLOUDFLARE_ACCOUNT_ID` | optional | For the commented-out Cloudflare model |
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`LITELLM_MASTER_KEY` and `UI_PASSWORD` fail fast if unset: the master key is
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the only thing between the domain and every provider key behind the proxy.
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`REDIS_HOST` and `REDIS_PORT` are fixed in `compose.yml`, as properties of this
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layout. Redis runs without a password; it is reachable only on the stack's
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own network.
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OpenRouter and Gemini stay active because the rest of this setup leans on
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them: every `model_group_alias` routes to `openrouter-free`, and
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`gemini-embedding-001` serves embeddings. The other providers are optional. An
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unset key disables only the models that reference it — LiteLLM starts and
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passes its health check with every provider key unset — so a provider is
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enabled by uncommenting its line, without touching `config.yaml`.
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## Storage
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| Volume | Mount | Holds |
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| --- | --- | --- |
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| `db-data` | `/var/lib/postgresql/data` | The database |
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| `cache-data` | `/data` | Redis append-only file |
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## Images
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The `Dockerfile` builds on `ghcr.io/berriai/litellm-database:main-stable`, the variant with the Prisma
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client for PostgreSQL built in. `main-stable` is upstream's moving stable tag.
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`postgres:16-alpine` and `redis:7-alpine` track their major versions. Moving
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PostgreSQL to a new major needs a dump and restore; the data directory does
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not carry across majors.
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## Resources
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`litellm` is capped at 4 GB of memory. Gunicorn runs two workers and recycles
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each after 1000 requests, which bounds the slow memory growth of long-lived
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LiteLLM workers.
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