# AI Turn on opendesk's AI features with Anthropic, OpenAI or a local model, and set up semantic search. AI features are off until you configure a provider. Self-hosted instances have no AI balance or usage limits: you pay your provider directly, or nothing at all with a local model. Workspace admins can still turn AI off for their workspace. See [AI features](/guides/ai/). ## Anthropic ```sh ANTHROPIC_API_KEY=sk-ant-... ``` With only this key set, the provider is detected as `anthropic`, and the models default to `claude-sonnet-5-5` (`AI_MODEL`, for drafts, summaries and answers) and `claude-haiku-4-5-20251001` (`AI_FAST_MODEL`, for triage, classification and short rewrites). ## OpenAI and compatible endpoints `AI_PROVIDER=openai` works with any OpenAI-compatible API: OpenAI, Azure OpenAI, Ollama, vLLM or LM Studio. Set the model names your endpoint serves. ```sh # OpenAI OPENAI_API_KEY=sk-... AI_MODEL= AI_FAST_MODEL= ``` ### Local models with Ollama The self-host bundle has an `ollama` compose profile that runs Ollama next to opendesk and pulls the models for you: run the installer with `--ollama`, or see [Docker Compose profiles](/self-hosting/docker-compose/#ollama). To use an Ollama you already run: Run everything on your own hardware, so customer content never leaves your network: ```sh AI_PROVIDER=openai OPENAI_BASE_URL=http://ollama:11434/v1 OPENAI_API_KEY=ollama # any non-empty value AI_MODEL= ``` ### vLLM ```sh AI_PROVIDER=openai OPENAI_BASE_URL=http://vllm:8000/v1 OPENAI_API_KEY= AI_MODEL= ``` When `AI_FAST_MODEL` is empty, `AI_MODEL` is used for everything. ## Embeddings and semantic search Embeddings power semantic search and the chat answer bot's article retrieval. | `EMBEDDINGS_DRIVER` | When | | --- | --- | | `voyage` | Chosen automatically when `VOYAGE_API_KEY` is set. | | `openai` | Chosen automatically with the `openai` provider. Uses the same endpoint. | | `none` | The default otherwise. Search falls back to Postgres full-text search. | Set `EMBEDDINGS_MODEL` to choose the model. Changing the embeddings model reindexes existing content. Published articles are indexed when they are published, and tickets when they are solved. ### pgvector Embeddings are stored in Postgres and need the `vector` extension (pgvector). Managed services such as PlanetScale and Neon have it, and so does the `pgvector/pgvector:pg17` image. On a Postgres without it, opendesk keeps working and semantic search uses full-text search instead. ## Decisions with Jev Triage, the chat answer bot's relevance check and `ai_decide` automation conditions are typed decisions: a choice, a score on ordered levels, or the probability of yes. Ollie makes them using Jev, TypeSafe's decision model, when a TypeSafe key is set. Jev returns calibrated probabilities and a confidence for each answer, so triage applies only what it is sure of and leaves the rest as suggestions. ```sh TYPESAFE_API_KEY=... # optional TYPESAFE_MODEL=jev-latest # or a pinned version such as jev-1.13.0 ``` Through the Vercel AI Gateway: ```sh TYPESAFE_API_KEY= TYPESAFE_API_URL=https://ai-gateway.vercel.sh/typesafe TYPESAFE_MODEL=typesafe-ai/jev ``` `DECISIONS_PROVIDER` picks the engine: `typesafe`, `llm` or `none`. When empty it is `typesafe` with a TypeSafe key, else `llm` when an AI provider is configured, else `none`. On `llm`, the AI provider's fast model answers the same questions as structured output, without a calibrated confidence. Without a TypeSafe key every feature keeps working; nothing depends on Jev. Triage also runs with Jev alone, without an AI provider. ## Privacy - Customer content is sent only to the providers you configure (the AI provider, and TypeSafe when its key is set). - Each request carries only the data that feature needs. - Prompts and completions are never logged. Usage records store counts only. ## Check it works After restarting opendesk, `GET /v1/ai/config` reports `enabled: true` with the provider and models. See the [AI API](/api/resources/ai/).