One-time mechanical reformat so `ruff format --check .` passes under the
newly pinned ruff. Layout only (assert-message parenthesization etc.),
no behavior change. 29 files: 28 under tests/ + 1 tools helper, no core
mempalace/ modules. Produced by `ruff format .`.
Adds api_key_source provenance ('flag' | 'env' | None) to LLMProvider
so cmd_init can distinguish a key passed via --llm-api-key (explicit
opt-in) from one silently picked up via OPENAI_API_KEY / ANTHROPIC_API_KEY
shell env (stray credential).
When the endpoint is external AND api_key_source == 'env', init now
prints a blocking [y/N] prompt before any data is sent. Anything other
than 'y' drops the LLM and falls back to heuristics-only.
Adds --accept-external-llm flag for CI / non-interactive bypass.
Completes the UX gap in #1224: the URL-based warning was informational
and init kept running, so a user who didn't notice the line had already
leaked. The consent prompt is the actual gate; explicit flag-passed keys
remain treated as already-consented.
2 files changed, 60 insertions, 0 deletions. 2 new tests (RED-first).
Follow-up to #1224's privacy warning. The URL-based heuristic in
``mempalace.llm_client._endpoint_is_local`` shipped without recognizing
Tailscale's CGNAT range (100.64.0.0/10), so a user running LM Studio,
Ollama, or any local LLM accessible via a Tailscale-assigned 100.x.x.x
address would currently get a wrong privacy warning — Tailscale
addresses are network-private (only reachable inside the user's
Tailnet) but they're not RFC1918, so the heuristic was treating them
as external.
This PR adds CGNAT recognition: when the hostname starts with ``100.``
AND the second octet is between 64 and 127 inclusive, it's classified
as local. Addresses in 100.x.x.x outside that range (i.e. second octet
< 64 or > 127) are regular allocated public space and remain external,
so a user pointing at a public 100.0.0.1 still gets the warning.
Concrete user impact:
Before: ``mempalace init --llm-provider openai-compat --llm-endpoint http://100.100.50.50:1234``
(LM Studio on Tailnet) → triggers privacy warning incorrectly.
After: same command → no warning. data stays inside the user's
Tailnet, which is what the warning is supposed to protect against.
TDD: 2 tests added in ``tests/test_llm_client.py``, both RED-first.
1. ``test_openai_compat_provider_tailscale_cgnat_endpoint_is_local``
— covers three Tailscale CGNAT addresses (start, middle, near-end
of the range) and pins they're all classified local. This was the
RED that drove the implementation.
2. ``test_openai_compat_provider_outside_tailscale_cgnat_is_external``
— pins the boundary on both sides: addresses with second octet 0-63
and 128-255 stay external. Prevents future "treat all 100.x.x.x as
local" overcorrection.
Tests: 1388 total mempalace tests pass. 2 pre-existing environmental
failures unrelated to this change (chromadb optional dep). Ruff check
+ format both clean.
Backwards compatible: only widens the local-recognition set. Anything
classified local before is still classified local; anything classified
external before remains so unless it's specifically in the CGNAT range.
Out of scope (tracked for future iteration based on real user feedback,
not built speculatively): pre-init confirmation prompt before sending
to external API, persistent ``private-only`` config flag that refuses
external endpoints entirely, explicit cloud-provider name detection
("Using Anthropic's hosted API at ..." vs the current generic warning).
4 files changed, 248 insertions, 0 deletions. 7 new tests (4 unit + 3 integration), all RED-first.
Per @milla-jovovich's question to @igorls during PR #1221 review: users
running `mempalace init` with an external LLM provider (Anthropic API,
OpenAI hosted, etc.) need a clear, explicit warning that their folder
content will be sent to the provider, that MemPalace doesn't control
how the provider logs/retains/uses that data, and how to opt out.
@igorls confirmed this should be a small follow-up PR scoped to the
warning itself, before the v3.3.4 tag.
This PR adds:
- `_endpoint_is_local(url)` helper in `mempalace/llm_client.py` —
URL-based heuristic returning True if the hostname is on the user's
machine or private network. Covers: localhost, 127.0.0.1, ::1,
hostnames ending in .local (mDNS/Bonjour), IPv4 RFC1918 ranges
(10/8, 172.16-31/12, 192.168/16), and IPv6 unique-local addresses
(fc00::/7).
- `is_external_service` property on the `LLMProvider` base class.
Subclasses inherit; the URL determines (no provider-specific
hardcoding). This means: Ollama on localhost = local. LM Studio on
LAN = local. Anthropic with default `https://api.anthropic.com` =
external. A user proxying Anthropic through localhost (advanced
setup) = local, no false-positive warning.
- One-line warning print in `cmd_init` after successful provider
acquisition, gated on `is_external_service`:
⚠ {provider_name} is an EXTERNAL API. Your folder content will be
sent to the provider during init. MemPalace does not control how
the provider logs, retains, or uses your data. Pass --no-llm to
keep init fully local.
The warning fires AFTER `LLM enabled: ...` so users see both that
the LLM is engaged AND the privacy implications of where it lives,
before Pass 0 / entity detection actually runs.
LOCAL providers (Ollama on localhost, LM Studio on localhost or LAN,
llama.cpp on localhost, vLLM on localhost) DO NOT trigger the warning —
nothing leaves the user's machine/network in those configurations.
TDD: 7 tests added across 2 files.
Unit tests in `tests/test_llm_client.py` (4 tests, all RED-first):
1. test_ollama_provider_default_endpoint_is_local — pins that the
default `http://localhost:11434` is classified local.
2. test_openai_compat_provider_localhost_endpoint_is_local — covers
the LM Studio / llama.cpp / vLLM common case (localhost,
127.0.0.1, and 192.168.x LAN).
3. test_openai_compat_provider_cloud_endpoint_is_external — pins
that pointing openai-compat at https://api.openai.com (or any
non-local URL) classifies as external.
4. test_anthropic_provider_default_endpoint_is_external — pins that
AnthropicProvider's default endpoint is external (the dominant
user-facing case for `--llm-provider anthropic`).
Integration tests in `tests/test_corpus_origin_integration.py` (3 tests,
RED-first; 1 was the critical RED — the other 2 passed by accident
since nothing printed "EXTERNAL API" before this PR):
5. test_init_prints_privacy_warning_when_provider_is_external —
captures stdout from cmd_init with a mocked external provider,
asserts the warning text contains "EXTERNAL API" + "--no-llm" +
language about MemPalace not controlling provider behavior.
6. test_init_no_privacy_warning_when_provider_is_local — same flow
with a mocked local provider, asserts the warning text does NOT
appear.
7. test_init_no_privacy_warning_with_no_llm_flag — pins the --no-llm
path: no provider acquisition attempted, no warning fires.
Tests: 1382 total mempalace tests pass. 2 pre-existing environmental
failures unrelated to this change (chromadb optional dep). Ruff check +
format both clean.
Backwards compatible: `is_external_service` is a new property; existing
callers don't reference it. The warning is a new print statement that
fires only when an external endpoint is acquired. The `--no-llm` opt-out
existed before this PR and continues to work identically.
Out of scope for follow-up (deliberately not in this PR per Igor's
"small PR" guidance): Tailscale CGNAT (100.64.0.0/10) treatment,
pre-init confirmation prompt, persistent privacy-mode config flag,
explicit cloud-provider name detection. Tracked for future iteration.
Three providers cover the useful space while keeping the zero-API
default:
- `ollama` (default): local models via http://localhost:11434. Works
fully offline. Tag-matching check accepts both `model` and
`model:latest` forms.
- `openai-compat`: any /v1/chat/completions endpoint. Covers
OpenRouter, LM Studio, llama.cpp server, vLLM, Groq, Together,
Fireworks, and most self-hosted frameworks. API key falls back to
$OPENAI_API_KEY. Endpoint normalization is forgiving about trailing
`/v1`.
- `anthropic`: Messages API v2023-06-01. API key falls back to
$ANTHROPIC_API_KEY. Concatenates multi-block text responses.
JSON mode is normalized across providers — Ollama uses
`format: "json"`, OpenAI-compat uses `response_format`, Anthropic uses
prompt-level instruction. Callers request JSON once; this module
handles the provider-specific plumbing.
No external SDK dependency; stdlib `urllib` throughout. HTTP errors
are wrapped into a single `LLMError` class so callers don't need to
distinguish transport, auth, and parse failures at the call site.
26 tests, all with mocked HTTP — suite runs offline with no real
provider required.
Igor Lins e Silva
MSL