trending/ai-memory
1
0
Fork 0
mirror of https://github.com/akitaonrails/ai-memory.git synced 2026-10-02 03:24:46 +08:00
Code Issues Packages Projects Releases Wiki Activity

docs: list embedding provider as a third opt-in egress path

Browse Source 
Addresses review feedback on #744: the embedding-provider config was only
mentioned in a subordinate clause, which undersells it as the broadest
data-egress path (full text of every stored page, including a backfill of
the existing corpus when switching providers). Promote it to a numbered
item alongside assistant capture and reranking, matching the "LLM or
embedding provider" framing SECURITY.md/the processor-relationship section
already use.

Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>
This commit is contained in:
Murilo Pereira
2026-09-16 17:02:48 +02:00
co-authored by Claude Sonnet 5
parent 9605bcb5b7
commit 35abfe1e7b
1 changed files with 37 additions and 12 deletions
Download Patch File Download Diff File Expand all files Collapse all files
DATA_HANDLING.md
+37 -12
View File
@@ -13,20 +13,42 @@ ai-memory does not phone home. There is no analytics, crash reporting, or
usage telemetry built into the binary. Everything it stores — wiki pages and
the SQLite database — lives under a single, operator-controlled data
directory on the local filesystem (`SECURITY.md`, "Local data
confidentiality"). No data leaves the host unless one of the two opt-in
features below is explicitly enabled, or you point ai-memory's own LLM/
embedding-provider config at a cloud API for its core functionality (the same
way any AI coding tool needs a model to call).
confidentiality"). No data leaves the host unless one of the three opt-in
paths below is explicitly enabled — the **embedding provider** being the one
most likely to matter to a reviewer, since it's the default-on question of
whether stored content reaches a cloud API at all.
The out-of-the-box default is local-only: `config.default.toml` configures
in-process local embeddings (all-MiniLM-L6-v2, 384-dim) with no API key and
no data egress. See [`docs/local-embeddings.md`](docs/local-embeddings.md).
There is no encryption at rest in v1; ai-memory relies on OS filesystem
permissions (owner-only directories/files on Unix, ACLs on Windows —
`SECURITY.md`, same section).
## The two opt-in paths that send data externally
## The three opt-in paths that send data externally
Both are off by default and each requires a deliberate step to turn on.
All three are off by default (local embeddings need no key or network call)
and each requires a deliberate config change to turn on.
1. **Assistant/Stop capture** (`SECURITY.md`, "Assistant/Stop capture is
| path | what leaves the host |
|---|---|
| `embedding_provider = openai\|voyage\|google\|openai-compat` | the text of every stored page |
| `capture_assistant` (double opt-in) | the assistant's final-turn text |
| `AI_MEMORY_RERANKER=llm` | each live query + bounded page titles/snippets |
1. **Embedding provider.** This is the broadest path by far, and the one
most likely to answer a reviewer's actual question ("does our source
material reach a cloud provider?"). `OpenAiEmbedder`, `VoyageEmbedder`,
and `GoogleEmbedder` each call their provider's embedding endpoint for
every page that needs a vector. This isn't limited to new writes:
switching a running install from `local` to a cloud provider triggers a
backfill of the **existing corpus** (`POST /admin/embed`, `ai-memory embed
--force`), so changing this setting later can retroactively send content
that was previously local-only. Leave `embedding_provider` on `local` (the
default) to keep this off; see
[`docs/local-embeddings.md`](docs/local-embeddings.md).
2. **Assistant/Stop capture** (`SECURITY.md`, "Assistant/Stop capture is
opt-in and sanitized"). Persisting the coding assistant's final-turn text
requires a double opt-in: `capture_assistant` on the server *and*
`install-hooks --capture-assistant` on the client. Once enabled, captured
@@ -34,16 +56,19 @@ Both are off by default and each requires a deliberate step to turn on.
separately configured a cloud LLM provider — is sent to that provider. The
flag is global to the install; there is no per-project exclusion once it's
on.
2. **LLM-based search reranking** (`SECURITY.md`, "Search reranking is an
3. **LLM-based search reranking** (`SECURITY.md`, "Search reranking is an
outbound-data opt-in"). Setting `AI_MEMORY_RERANKER=llm` sends each live
query plus bounded page titles/snippets to the configured LLM provider.
Leave this unset, or point it at a local provider, to keep queries and
recalled snippets on-host.
Both paths pass through a sanitizer that strips obvious credentials before
anything is transmitted, but the sanitizer is documented as best-effort, not
a guarantee — see the "Stored-content prompt injection" and reranking notes
in `SECURITY.md` for the exact caveats.
Paths 2 and 3 pass through a sanitizer that strips obvious credentials before
anything is transmitted; the sanitizer is documented as best-effort, not a
guarantee — see the "Stored-content prompt injection" and reranking notes in
`SECURITY.md` for the exact caveats. The embedding path (1) sends full page
text to the provider's embedding endpoint and is not sanitized the same way,
so it is the path to leave on `local` when stored content must not leave the
server.
## Is this "personal data" under GDPR?