embeddings_queries now records the embedding request's token count (the unit
upstream providers bill on) instead of an operation count, and fires on the
indexing path too. Previously only semantic search recorded it (value=1), so a
re-indexing run produced no embeddings_queries events at all — only pages_chunks.
- Provider layer: additive embed_with_usage / embed_batch_with_usage surface the
per-request token count (Mistral/OpenAI usage.total_tokens, Bedrock Titan
inputTextTokenCount, Ollama prompt_eval_count); a char-based estimate is the
fallback (Simple, and any provider/response without a token field). Gateway and
EmbeddingService forward through. The count travels as a return value / a
per-request SearchAlgorithm attribute — never on the singleton — so concurrent
indexing + search can't mis-attribute bills.
- Indexing (vector/processor.py): records embeddings_queries (value=batch tokens)
alongside the existing pages_chunks event.
- Search (server/semantic.py): value is now the query embedding's token count,
relayed from BM25HybridSearchAlgorithm via query_token_count.
The astrolabe_embeddings_queries Stripe meter (sum aggregation) now sums tokens
with no CP/Terraform change. The meter "queries"->tokens naming/unit
clarification (homelab-terraform #254) + CP rollup/portal copy is a follow-up.
Deck #67.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
EMBEDDING_GATEWAY_URL is configured as a bare origin (scheme://host:port) —
the deployment's Service URL. GatewayProvider now appends the gateway's /v1
base path before handing the URL to the OpenAI SDK, so both embed posts
({base}/embeddings) and dimension discovery ({base}/models) land under /v1.
Idempotent: a URL already ending in /v1 is left unchanged.
This lets EMBEDDING_GATEWAY_URL stay a bare domain (matching the gitops
Service URLs) instead of requiring a hand-appended /v1.
Also align the `embedding_gateway_model` field default with _DEFAULTS
("mistral/mistral-embed"). The gateway catalog is provider-namespaced, and
_detect_dimension matches `entry.id == embedding_model`; the stale
un-namespaced default would silently miss the catalog entry and leave the
dimension unresolved (re-triggering the external-mode startup crash).
Tests: bare / trailing-slash / idempotent normalization + a bare-origin
discovery test asserting /v1/models. 16 gateway-provider tests pass;
providers + vector suites green (129 total); ruff clean.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
External-mode tenant pods CrashLoop at startup: Qdrant collection init calls
get_dimension() before any embed(), but GatewayProvider only learns its
dimension lazily after the first embed, and the gateway model isn't an OpenAI
model so the base class can't know it statically.
- Add GatewayProvider._detect_dimension() — the async startup hook the
vector-sync bootstrap already invokes (vector/qdrant_client.py:
hasattr(provider, "_detect_dimension")) for Ollama. It GETs the gateway's
GET /v1/models and sets _dimension from the entry whose id matches the
configured model. Best-effort: any failure (old gateway, model absent,
network) leaves _dimension unset so the inherited lazy detect-on-first-embed
still applies — never fatal. Presents the M2M bearer when configured.
- Switch the default embedding_gateway_model to the gateway's provider-
namespaced id "mistral/mistral-embed" (the gateway routes on the "/"-prefix
and sends "mistral-embed" upstream); collapse a duplicated config field.
Pairs with astrolabe-cloud-website#229 (gateway /v1/models, namespaced ids).
Tests: discovery sets dim w/o embed, sends bearer, non-fatal on
404/absent/error, skips when already known.
- gateway_client: guard token cache with a lazy anyio.Lock so concurrent
embed calls share one M2M token request instead of racing
- status subscriber: distinguish idle fetch timeouts from real broker
errors (log + 5s backoff) instead of swallowing all and spinning
- nats: warn when the bus URL uses unencrypted transport (non-tls://)
- collection_metadata: accept an optional shared httpx client, make TLS
verify explicit, document the unauthenticated control-plane contract
- replace python -O-stripped asserts with explicit ValueError in the bus
status builder and the api metadata source
- document why the nil-UUID sentinel point can't collide with content ids
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
SonarCloud:
- Resolve 6 S5332 hotspots (http→https in test fixture URLs).
- S6418: hoist the unauthenticated AsyncOpenAI placeholder to a named constant
+ NOSONAR (genuine non-secret; gateway ignores it when unauthenticated).
- Fix two reliability bugs: None-index guard in the gateway token-cache test
(S2259) and float `> 0.0` instead of `!= 0.0` in the sentinel test (S1244).
- status.py idle path sleeps 0.1s instead of sleep(0) (S7491); NOSONAR on the
protocol-required async no-await aclose() stubs (S7503).
Claude review:
- Remove three leftover debug print() calls in app.py (logger.info already
covers them).
- payload_backfill: drop parsed_at from the backfilled-keys docstring (it is
per-document state, not a deployment scalar); add a clean 404 precondition
for BasicAuth deployments without an OAuth token verifier.
- status.py: task_status typed TaskStatus | None (drop type: ignore).
- nats.py: TODO to thread etags for file/deck/news; note etag default → None.
- factory: warn on unknown INGEST_BUS_URL scheme; raise ValueError instead of
assert for the external-mode preconditions.
- docs/configuration.md: document the decomposition hook-point env vars + that
nats-py ships core (lazy-imported) and external+bus uses two NATS connections.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Adds the seven §10.2 hook-point modules + five env vars so Astrolabe Cloud can
offload document processing to the external document-processor / embedding
gateway. Purely additive: with every setting unset the server behaves exactly
as today, so self-hosters are unaffected (Deck #92).
Hook points (all default to current monolith behavior):
- config: EMBEDDING_PROVIDER, INGEST_MODE, STATUS_BACKEND,
COLLECTION_METADATA_SOURCE, FACT_EVENT_EMITTER (+ supporting settings),
validated in Settings.__post_init__ (fail-fast STATUS_BACKEND=local with
INGEST_MODE=external); shared canonical.py.
- vector/payload_keys.py + acl_hash.py: cross-impl NAMESPACE/point_id (§2.2)
and BLAKE2b-128 ACL hash (§11), pinned by fixtures shared with the
document-processor repo.
- embedding/gateway_client.py: OpenAI-compatible GatewayProvider authenticating
via M2M OIDC client-credentials (separate realm); manual-only registry entry.
- vector/collection_metadata.py: sentinel-point / API metadata source with env
fallback.
- vector/queue/: hexagonal ingest producer ports + memory/NATS adapters
(Postgres seam); INGEST_MODE=external publishes mcp.ingest.requested.{tenant}
instead of the in-memory stream and skips the in-process processor pool. The
lifespan becomes a composition root across both deployment branches.
- vector/queue/status.py: STATUS_BACKEND=bus subscriber feeding a StatusStore
the vector-sync status endpoint reads.
- admin/payload_backfill.py: POST /api/v1/admin/payload-backfill (admin scope);
processor writes the new payload keys; query-side ACL pre-filter gated behind
ACL_PREFILTER_ENABLED (default off).
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
- test_registry.py: stub `mistralai.client.Mistral` in
`test_registry_mistral_wins_over_ollama`, mirroring the sibling
picker test, so the test doesn't depend on the SDK accepting
arbitrary keys.
- openai.py: convert remaining f-string `logger.info(...)` calls to
lazy `%s` formatting, aligning with the pattern in mistral.py and
the repo's logging convention.
- test_mistral.py: add four tests covering the defensive RuntimeError
guards in `embed()` and `_embed_batch_request()` — empty
response.data, single null embedding, batch null embedding, and
count-mismatch.
- docs/configuration.md: add `AWS_ACCESS_KEY_ID` and
`AWS_SECRET_ACCESS_KEY` rows to the env-var reference table; they
were already mentioned in prose but missing from the table.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
- _retry.py: replace `assert last_error is not None` with explicit
`if last_error is None: raise RuntimeError(...)` so the original
rate-limit error is preserved under `python -O`.
- openai.py: drop the `_retry_factory` alias chain; rename the bound
decorator to `_retry_429` to match the pattern in mistral.py.
- mistral.py: comment the imports so future reviewers understand why
`from mistralai.client import …` is the canonical path on 2.x (no
top-level `__init__.py`; no `mistralai.models` subpackage either).
- docs/configuration.md: add `OPENAI_GENERATION_MODEL` and
`OLLAMA_GENERATION_MODEL` rows to the env-var reference table.
- test_mistral.py: add direct unit test for the `_is_rate_limit`
predicate (429 → True, 500 → False, missing-attr → False).
- test_registry.py: stub `mistralai.client.Mistral` in the registry
picker test, mirroring the Ollama sibling, so the test doesn't
depend on the SDK accepting arbitrary keys.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
Addresses the Claude Code review on PR #772 plus the SonarCloud S1192 finding:
- Extract `retry_on_rate_limit` into `nextcloud_mcp_server/providers/_retry.py`
as a parametric decorator. OpenAI and Mistral now share the same backoff
loop; future providers can reuse it without copy-paste.
- New `tests/unit/providers/test_retry.py` covers the decorator: 429 retry +
success, non-429 immediate re-raise, MAX_RETRIES exhaustion, default
predicate, and unrelated exception passthrough.
- Tighten Mistral SDK import to `from mistralai.client.errors import SDKError`
(the canonical sub-path; the reviewer's `from mistralai.models import
SDKError` does not exist in mistralai 2.4.5).
- Replace `MistralProvider.close()`'s direct `__aexit__` call with a no-op +
comment — the Speakeasy-generated client has no public close hook and the
underlying httpx client is closed by GC.
- Extract the duplicated "Embedding not supported" message to a module-level
constant (SonarCloud S1192).
- Align `Settings.get_embedding_model_name()` Bedrock check with the registry
by also considering `bedrock_generation_model`.
- Add the `mock_mistral_client` fixture to
`test_mistral_no_embeddings_disabled` for parity with the rest of the file.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
Adds a hosted Mistral embedding option (mistral-embed, 1024-dim) alongside
the existing Bedrock / OpenAI / Ollama / Simple providers. Implementation
mirrors OpenAIProvider: lazy dimension detection with a known-models lookup,
chunked batch requests, defensive index sort, and a 429-aware retry decorator.
In the same change, ProviderRegistry switches from os.getenv to the
dynaconf-backed Settings dataclass so all five providers share a single
configuration path. config.py gains the previously-uncovered Bedrock keys,
the new Mistral keys, the missing OPENAI_GENERATION_MODEL /
OLLAMA_GENERATION_MODEL, and SIMPLE_EMBEDDING_DIMENSION.
Auto-detection priority: Bedrock → OpenAI → Mistral → Ollama → Simple.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
Adds OpenAI provider to the unified provider architecture (ADR-015),
supporting:
- OpenAI API (api.openai.com)
- GitHub Models API (models.github.ai/inference)
- OpenAI-compatible endpoints (Fireworks, Together, etc.)
Features:
- Embedding support with text-embedding-3-small/large models
- Text generation via chat completions API
- Automatic retry with exponential backoff for rate limits
- Provider auto-detection in registry (priority after Bedrock)
Environment variables:
- OPENAI_API_KEY: API key (required)
- OPENAI_BASE_URL: Base URL override (optional)
- OPENAI_EMBEDDING_MODEL: Embedding model (default: text-embedding-3-small)
- OPENAI_GENERATION_MODEL: Generation model (default: gpt-4o-mini)
Also adds:
- Integration tests for RAG pipeline with MCP sampling
- MCP client sampling support for integration tests
- Ground truth Q&A pairs for Nextcloud User Manual
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude <noreply@anthropic.com>
Refactored LLM provider infrastructure to support sustainable additions of new providers with both embedding and text generation capabilities.
## Major Changes
### Unified Provider Architecture (ADR-015)
- Created `nextcloud_mcp_server/providers/` with unified Provider ABC
- Providers now support optional capabilities (embeddings and/or generation)
- Auto-detection registry with priority: Bedrock → Ollama → Simple
- Backward compatible - existing code continues to work
### New Providers
- **BedrockProvider**: Full Amazon Bedrock integration
- Embeddings: Titan Embed, Cohere Embed models
- Generation: Claude, Llama, Titan Text, Mistral models
- Model-specific request/response handling
- AWS credential chain integration
- **OllamaProvider**: Migrated with both capabilities support
- **AnthropicProvider**: Moved from test code to production providers
- **SimpleProvider**: Migrated in-memory fallback provider
### Breaking Changes
None - full backward compatibility maintained:
- `embedding.get_embedding_service()` still works
- RAG evaluation tests updated to use unified providers
- All existing tests pass (127 unit tests)
### Testing
- Added 9 comprehensive Bedrock unit tests with mocked boto3
- All existing unit tests pass
- Type checking (ty) and linting (ruff) pass
- Verified backward compatibility
### Documentation
- `docs/ADR-015-unified-provider-architecture.md`: Comprehensive ADR
- `docs/bedrock-setup.md`: AWS setup guide with IAM permissions
- `CLAUDE.md`: Updated with provider architecture section
### Dependencies
- Added `boto3>=1.35.0` to dev dependencies (optional)
## Environment Variables
### Bedrock
- `AWS_REGION`: AWS region (e.g., "us-east-1")
- `BEDROCK_EMBEDDING_MODEL`: Model ID for embeddings
- `BEDROCK_GENERATION_MODEL`: Model ID for generation
- `AWS_ACCESS_KEY_ID`, `AWS_SECRET_ACCESS_KEY`: Optional credentials
### Ollama
- `OLLAMA_BASE_URL`: API URL
- `OLLAMA_EMBEDDING_MODEL`: Embedding model (default: "nomic-embed-text")
- `OLLAMA_GENERATION_MODEL`: Generation model
## AWS Bedrock Permissions Required
Minimal IAM policy:
```json
{
"Effect": "Allow",
"Action": ["bedrock:InvokeModel"],
"Resource": ["arn:aws:bedrock:*::foundation-model/*"]
}
```
See `docs/bedrock-setup.md` for detailed setup instructions.
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude <noreply@anthropic.com>
