Environment variables

Most things are configured via .repowise/config.yaml (see Configuration; repowise init generates one for you). The handful of settings that make sense as environment variables are below.

LLM provider keys#

All optional. repowise init never requires one: with no provider resolvable it renders the wiki from your code's structure and exits 0. Set a key when you want model-written prose instead. See Deterministic wiki.

Pick one. Pass --provider <name> on init / update / mcp to switch, or set REPOWISE_PROVIDER / REPOWISE_MODEL for repos whose config.yaml names no provider.

Base URLs can also be overridden per provider: ANTHROPIC_BASE_URL, OPENAI_BASE_URL (used for vLLM/SGLang-compatible endpoints), GEMINI_BASE_URL, DEEPSEEK_BASE_URL, KIMI_BASE_URL, LITELLM_BASE_URL, EDENAI_BASE_URL. A base_url in config.yaml takes precedence over all of them.

Provider, model and base URL order#

The CLI, repowise serve chat and jobs, and the MCP server resolve the provider, model and base URL the same way. The first match wins:

Picking a model or base URL for a repo in the web UI writes that repo's config.yaml, so the CLI uses it too. The repo's Settings page lists the provider's live models, accepts any typed id, and has a Test connection button for a base URL.

Local and OpenAI-compatible gateways#

The openai adapter talks to anything that speaks the OpenAI API, so a local model server needs no separate provider. An OpenAI-compatible server on this machine (LM Studio, Ollama, vLLM) needs no API key. The simplest setup is a base URL in the repo's config.yaml:

provider: openai
model: qwen3-coder
openai:
  base_url: http://localhost:1234/v1

Or point OPENAI_BASE_URL at the gateway's /v1 endpoint, put the gateway's key (if it wants one) in OPENAI_API_KEY, and pass the model id that endpoint's /models response returns:

export OPENAI_BASE_URL="http://localhost:8000/v1"
repowise init --provider openai --model qwen3 --reasoning off

export OPENAI_API_KEY="your-gateway-key"
export OPENAI_BASE_URL="http://localhost:20128/v1"
repowise init --provider openai --model ag/gemini-3.7-flash-medium

Namespaced model ids are discovered as-is, so the model does not need to start with gpt-. This covers vLLM, SGLang, LM Studio and gateways such as 9router. In an interactive repowise init, the menu row is OpenAI-compatible (Custom / local gateway): repowise validates the endpoint, takes the key without echoing it, checks /models, and lets you search the discovered models or type an exact id. The endpoint is written to the repo's gitignored .repowise/.env, and the key is saved there only after you confirm; --no-save-key keeps it process-local. Pick the plain openai row instead for the official OpenAI endpoint.

Eden AI#

Eden AI is a hosted gateway with an EU endpoint, so inference can stay in the EU without self-hosting anything. Every other hosted provider listed above terminates in the US; the alternatives for a team working under a DPA are Ollama or LiteLLM on your own infrastructure.

export EDENAI_API_KEY="..."
export EDENAI_BASE_URL="https://api.eu.edenai.run/v3"
repowise init --provider edenai --model mistral/mistral-small-latest

Without EDENAI_BASE_URL the requests go to the global endpoint. One key reaches Mistral, GPT, Claude, Gemini, Cohere, DeepSeek and Llama through a single OpenAI-compatible endpoint, with models addressed as vendor/model. The catalogue is public and needs no authentication: api.edenai.run/v3/models.

EDENAI_BASE_URL covers the embedder too, since both read the same variable. The same key selects edenai as the embedder, defaulting to amazon/amazon.titan-embed-text-v2:0, which is served from an EU region and is the cheapest per token of the models this adapter declares. Override it with REPOWISE_EMBEDDING_MODEL. Only the models the adapter declares dimensions for are accepted, because a wrong dimension count would silently mis-size stored vectors.

The default Kimi Code endpoint supports kimi-for-coding and kimi-for-coding-highspeed. K2.x models use the separate Kimi Open Platform: supply a key from that platform together with KIMI_BASE_URL=https://api.moonshot.ai/v1. Repowise selects the required sampling parameters for either endpoint automatically.

Repowise also persists provider/model choice into .repowise/state.json during init, so the MCP server and update runs reuse the same provider without you re-specifying.

Embedder overrides#

The embedder powers semantic search and the RAG behind get_answer. It's separate from the LLM provider, and defaults to mock (no semantic search) when no key is detected.

When nothing names an embedder, repowise takes the first one with a key set, in the order gemini, openai, openrouter, ollama, edenai, and every model run prints which embedder it uses. The full order, flags and config included, is in Configuration.

Server and database#

Scoped tokens#

REST, MCP streamable HTTP and SSE, and webhooks all resolve a caller to a principal with repository and tool scope. Besides the shared REPOWISE_API_KEY, you can list scoped tokens, stored as SHA-256 digests:

# ~/.repowise/tokens.yaml
tokens:
  - id: ci-reader
    sha256: "<hex SHA-256 of the token>"   # printf %s "$TOKEN" | sha256sum
    repos: [backend]                    # repository ids or names
    tools: [get_context, get_risk]      # MCP tool names
    expires_at: 2027-01-01T00:00:00Z

A token with tools is refused on every REST route except chat, which runs only the tools in its scope. With no key and no tokens file, local callers are served without a credential and every other caller is refused.

Workspace MCP#

Plugins and seams#

Both are read from the real process environment only, never from a repository's .repowise/.env. repowise plugins shows what loaded and which implementation each seam uses.

Telemetry#

Anonymous usage telemetry is enabled by default (opt-out).

Misc#

Hosted version#

If you're using repowise.dev, none of the above apply, because the platform manages keys for you. The only env var you'd set client-side is the API key your editor uses to talk to the hosted MCP endpoint, which the Settings → Editor page generates automatically.