Embedding Providers

RepoRelay supports multiple embedding providers, selected via the EMBEDDING_PROVIDER environment variable.

Provider	Value	Description
Ollama (default)	ollama	Local embedding via Ollama
OpenAI-compatible	openai	Any OpenAI-compatible API (OpenAI, Azure OpenAI, Together AI, Mistral, etc.)

Ollama

Ollama runs natively on macOS with Metal GPU acceleration — no Docker needed for the embedding model.

brew install ollama
ollama serve
ollama pull nomic-embed-text

Add to .env:

EMBEDDING_PROVIDER=ollama          # default, can be omitted
EMBEDDING_URL=http://localhost:11434
EMBEDDING_MODEL=nomic-embed-text

OpenAI-compatible

Works with any provider that implements the OpenAI POST /v1/embeddings endpoint format — OpenAI, Azure OpenAI, Together AI, Mistral, etc.

Add to .env:

EMBEDDING_PROVIDER=openai
EMBEDDING_MODEL=text-embedding-3-small
OPENAI_API_KEY=sk-...

Optional settings

# Custom base URL for OpenAI-compatible providers (default: https://api.openai.com/v1)
EMBEDDING_URL=https://my-proxy.example.com/v1

# Request a specific number of dimensions from the API.
# Only supported by text-embedding-3 and later models.
# Must produce vectors matching DB_EMBEDDING_DIMENSIONS (768) or init() will report a mismatch.
EMBEDDING_DIMENSIONS=768

Model compatibility

The database schema stores embeddings as 768-dimensional vectors. At startup, RepoRelay probes the configured model and verifies the returned vector width matches. If there is a dimension mismatch, the embedder logs a warning and embedding features are disabled until the configuration is corrected.

For OpenAI models:

• text-embedding-3-small (1536-d default) — set EMBEDDING_DIMENSIONS=768 to reduce to 768-d
• text-embedding-3-large (3072-d default) — set EMBEDDING_DIMENSIONS=768 to reduce to 768-d
• text-embedding-ada-002 (1536-d fixed) — does not support the dimensions parameter; cannot be used with the default 768-d schema