feat(memory): add Ollama embedding provider (#26349)

Merged via /review-pr -> /prepare-pr -> /merge-pr.

Prepared head SHA: ac413865431614c352c3b29f2dfccc5593f0605a
Co-authored-by: nico-hoff <43175972+nico-hoff@users.noreply.github.com>
Co-authored-by: gumadeiras <5599352+gumadeiras@users.noreply.github.com>
Reviewed-by: @gumadeiras
This commit is contained in:
nico-hoff
2026-03-03 02:56:40 +01:00
committed by GitHub
parent 4ba5937ef9
commit 3eec79bd6c
17 changed files with 367 additions and 25 deletions

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@@ -109,6 +109,8 @@ Defaults:
6. Otherwise memory search stays disabled until configured.
- Local mode uses node-llama-cpp and may require `pnpm approve-builds`.
- Uses sqlite-vec (when available) to accelerate vector search inside SQLite.
- `memorySearch.provider = "ollama"` is also supported for local/self-hosted
Ollama embeddings (`/api/embeddings`), but it is not auto-selected.
Remote embeddings **require** an API key for the embedding provider. OpenClaw
resolves keys from auth profiles, `models.providers.*.apiKey`, or environment
@@ -116,7 +118,9 @@ variables. Codex OAuth only covers chat/completions and does **not** satisfy
embeddings for memory search. For Gemini, use `GEMINI_API_KEY` or
`models.providers.google.apiKey`. For Voyage, use `VOYAGE_API_KEY` or
`models.providers.voyage.apiKey`. For Mistral, use `MISTRAL_API_KEY` or
`models.providers.mistral.apiKey`.
`models.providers.mistral.apiKey`. Ollama typically does not require a real API
key (a placeholder like `OLLAMA_API_KEY=ollama-local` is enough when needed by
local policy).
When using a custom OpenAI-compatible endpoint,
set `memorySearch.remote.apiKey` (and optional `memorySearch.remote.headers`).
@@ -331,7 +335,7 @@ If you don't want to set an API key, use `memorySearch.provider = "local"` or se
Fallbacks:
- `memorySearch.fallback` can be `openai`, `gemini`, `voyage`, `mistral`, `local`, or `none`.
- `memorySearch.fallback` can be `openai`, `gemini`, `voyage`, `mistral`, `ollama`, `local`, or `none`.
- The fallback provider is only used when the primary embedding provider fails.
Batch indexing (OpenAI + Gemini + Voyage):