Chunk metadata inserted into the vector DB carries arbitrary client-
supplied fields (e.g. custom metadata from file uploads), so it needs
the same size cap, type coercion and null-byte sanitization every
other backend already applies through process_metadata(). Four
backends never called it: Qdrant, Qdrant multitenancy, Milvus
multitenancy and Oracle23ai, so an oversized or malformed metadata
blob went into those unfiltered.
Wire process_metadata() in at each backend's single insert/upsert
chokepoint, matching the pattern already used by the other eleven
backends.
With `DATABASE_ENABLE_IAM_TOKEN_AUTH=true` and `VECTOR_DB=pgvector`, startup failed at vector store initialisation with `fe_sendauth: no password supplied`, so the two features could not be used together.
`PgvectorClient` builds its own engine and never got the `do_connect` listener that refreshes the RDS IAM token, and the `ScopedSession` branch that would have reused the instrumented main engine is unreachable because `PGVECTOR_DB_URL` defaults to `DATABASE_URL` and is therefore never falsy.
The pgvector engine now goes through `enable_iam_token_auth()` like the main and Alembic engines. Since a token authenticates exactly one host/port/user, that function now attaches the listener only to engines pointing at the same target, so a `PGVECTOR_DB_URL` aimed at a separate database keeps the password from its own URL instead of having it overwritten; the skip is logged with both identities.
Fixes#27752
SRC_LOG_LEVELS became an empty dict when per-module log levels were dropped, and env.py keeps it only as a legacy name. opengauss.py is the last thing in the tree that still indexes it, at module scope, so importing the module raises KeyError: 'RAG' and any deployment on VECTOR_DB=opengauss dies the first time it touches the vector store. The factory imports it lazily, which is why nothing else trips over it. Deleting the line is the whole fix: every other vector backend takes getLogger(__name__) and inherits the root level.
colbert.py passes an argument to a message with no placeholder to consume it:
log.info('ColBERT: Loading model', name)
At INFO, which is the default, logging evaluates 'ColBERT: Loading model' % ('colbert-ir/colbertv2.0',) and raises TypeError: not all arguments converted during string formatting. The record is swallowed by handleError, so loading a ColBERT reranker prints '--- Logging error ---' plus a traceback to stderr instead of the model name. Adding %s prints the name and drops the traceback.
Create and publish Docker images with specific build args / build (map[arch:linux/amd64 runner:ubuntu-latest], map[build_args: free_disk:false name:main suffix:]) (push) Has been cancelled
Create and publish Docker images with specific build args / build (map[arch:linux/amd64 runner:ubuntu-latest], map[build_args:USE_CUDA=true
USE_CUDA_VER=cu126
free_disk:true name:cuda126 suffix:-cuda126]) (push) Has been cancelled
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Create and publish Docker images with specific build args / build (map[arch:linux/arm64 runner:ubuntu-24.04-arm], map[build_args:USE_CUDA=true
USE_CUDA_VER=cu126
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Raising GLOBAL_LOG_LEVEL to WARNING buys quieter output but not less work: 241 INFO call sites interpolate their payload into an f-string before the logging call gets to drop it. The heaviest is get_doc, which logs every chunk id and metadata dict in a collection, so on the full-context retrieval path that is the entire knowledge base, once per chat request.
That one line at WARNING, CPython 3.12:
| knowledge base | payload | before | after |
| -------------- | ------- | -------- | ------- |
| top-k of 3 | 1.2 kB | 3.8 us | 0.07 us |
| 500 chunks | 201 kB | 583.6 us | 0.08 us |
| 5000 chunks | 2.0 MB | 5.8 ms | 0.15 us |
The lazy form log.info('query_doc:result %s %s', result.ids, result.metadatas) hands the payload to record.getMessage(), which the InterceptHandler only reaches once a record has passed the level check. Output at INFO is byte-identical. Two sites that already built their message eagerly, one str concat and one % operator, move to the same lazy form.
GLOBAL_LOG_LEVEL defaults to INFO, so every log.debug(...) in the backend is discarded, but the message is built first: 187 call sites interpolate their payload into an f-string before the logging call runs, so the work happens on every request and the result is thrown away. The worst one sits in process_chat_payload and stringifies the whole request body, full conversation history included, once per chat completion.
That one line with DEBUG disabled, CPython 3.12:
| conversation | payload | before | after |
| ------------ | ------- | -------- | ------- |
| 4 messages | 1.2 kB | 3.4 us | 0.07 us |
| 20 messages | 17 kB | 24.8 us | 0.07 us |
| 60 messages | 123 kB | 216.6 us | 0.07 us |
The lazy form log.debug('form_data: %s', form_data) hands the payload to record.getMessage(), which the InterceptHandler only reaches once a record has passed the level check. With DEBUG enabled the emitted lines are byte-identical, f'{x=}' sites included: those map to %r. MistralLoader._debug_log callers get the same treatment, since that wrapper already forwards *args.
`_json_to_metadata` parses the metadata of every result row returned by search and get. It now goes through `JSONCodec`, which selects orjson when `ENABLE_ORJSON` is set.
The text it parses is produced by Oracle's own `JSON_SERIALIZE`, and the column is a native `JSON` type, so the database normalises whatever was written and the reader never depends on the writer's escaping.
The matching `_metadata_to_json` write deliberately keeps stdlib `json`: it passes `default=self._decimal_handler`, orjson accepts none of stdlib's keyword arguments, and dropping the handler would turn a currently successful insert of a `Decimal` into a hard failure. The read side has no such constraint.
With `ENABLE_ORJSON` unset, which is the default, `JSONCodec` is stdlib `json` and this call site behaves exactly as before.
Fourteen modules import `json` without using it. Ruff flags every one with F401, and a word-boundary search for `json` in each file matches only the import line itself, including inside strings, comments and annotations.
Two exclusions, both deliberate. Migration files are left alone: the import is equally dead there, but those files are frozen history and not worth the churn. `models/chats.py` has the same dead import and is handled in its own change, so it is skipped here to avoid two changes touching the same line.
No behaviour change.
The Valkey backend serializes chunk metadata on every insert and parses it back on every result row in `get` and `query`. Both directions now go through `JSONCodec`, which selects orjson when `ENABLE_ORJSON` is set.
The stored `metadata_json` field is never matched against as text. `_build_filter_expression` only emits TAG predicates, and the TAG fields are `id`, `hash`, `file_id`, `source` and `knowledge_base_id`; `metadata_json` appears only as a return field that is immediately re-parsed. So rows written with escaped non-ASCII and rows written raw are indistinguishable to every reader, and no migration is needed.
`process_metadata` already stringifies datetimes and strips null bytes and lone surrogates before the write, so the two backends cannot disagree about what is serializable here.
Both read `except` clauses widen from `(json.JSONDecodeError, TypeError)` to `(ValueError, TypeError)`. The codec falls back to engineio's codec, which installs `parse_int=_safe_int` and raises a bare `ValueError` for integer literals longer than 100 characters; the narrower clause would have let that escape and abort a search instead of yielding empty metadata. `json.JSONDecodeError` is a `ValueError` subclass, so this is a strict superset. That removes the module's last use of stdlib `json`, so the import goes with it.
With `ENABLE_ORJSON` unset, which is the default, `JSONCodec` is stdlib `json` and this call site behaves exactly as before.
* refac: use MilvusClient instead of deprecated ORM-style PyMilvus APIs
PyMilvus 2.6 emits a PyMilvusDeprecationWarning for every ORM-style call (`connections.connect`, `utility.*`, `Collection` and its methods) and will remove those APIs in PyMilvus 3.1. Both Milvus backends still used them, so a running instance floods its logs with deprecation warnings during indexing and retrieval, and would break outright once PyMilvus 3.1 lands.
Both vector clients now go through `MilvusClient`:
- `milvus_multitenancy.py`: collection creation, index creation, has_collection, insert, search, query iteration, delete and reset.
- `milvus.py`: the remaining ORM calls in `query()` (`connections.connect`, `Collection(...).load()`, `Collection.query_iterator`), plus the now-unused `FieldSchema` import.
Behaviour is unchanged: same schema, same index parameters and the same two-step scalar-index fallback, same filter expressions, same result shapes. Verified against embedded Milvus (milvus-lite, pymilvus 2.6.14) with a functional harness over both clients: insert, get, query by string/int/bool metadata filters, vector search, tenant isolation, oversized-text truncation, delete by id and by filter, delete_collection and reset all return identical results before and after, while the deprecation warnings drop from 57 to 0 for the multi-tenancy client and from 16 to 0 for the standard one.
One Milvus Lite nuance worth recording: `MilvusClient` sends index build parameters (`M`, `efConstruction`, `nlist`) as flat keys rather than as a nested `params` blob. A Milvus server accepts both forms, Milvus Lite only reads the nested one, so those tuning values are ignored on Lite. `MilvusClient` offers no way to send the nested form, and `milvus.py` already built its index parameters this way, so both backends are now consistent.
Fixes#26978
* refac: correct the Milvus scalar-index comment
The comment claimed that embedded Milvus Lite requires an explicit scalar index type. It does not: Milvus Lite rejects `create_index` on a VARCHAR field outright ("create_index only supports vector fields"), for every index type and with or without a metric type, so neither the parameterless call nor the explicit INVERTED fallback can succeed there. Filtered queries on `resource_id` still work on Lite, just unindexed.
Only the accurate half is kept, which is the reason the parameterless call is deliberate rather than an omission.
Enabling ENABLE_MILVUS_MULTITENANCY_MODE with the default MILVUS_URI (embedded Milvus Lite at DATA_DIR/vector_db/milvus.db) fails on the first embedding write: _create_shared_collection calls collection.create_index(RESOURCE_ID_FIELD) with no index params. A Milvus server auto-selects a scalar index type in that case, but Milvus Lite rejects the call with "create_index missing required 'index_type' parameter", so shared collection creation raises and every embedding write 500s (memory add, file upload, knowledge writes).
Keep the parameterless call as the first attempt so behavior on Milvus servers is unchanged, fall back to an explicit INVERTED scalar index, and if that also fails log a warning and continue. The scalar index only accelerates resource_id filters; inserts and filtered queries work without it, so a missing index must not break collection creation.
Verified against embedded Milvus Lite: shared collections now create (with the warning), and memory add, file upload and memory query succeed end to end. Against a Milvus server the first attempt is identical to the current code, so nothing changes where it works today.
has_collection did `collection_name in self.client.list_collections()`,
but chromadb's list_collections() returns Collection objects (1.x), not
name strings — so the membership test is always False, even when the
collection exists. Compare against the collection names instead (with a
hasattr guard tolerating versions that yield plain names).
Found via the dependency-contract test suite (unit/deps/test_chromadb.py).
The Qdrant backends implemented delete(ids=...) as a payload filter on
metadata.id, but points are stored with the item id as the Qdrant point id
(see _create_points), and not every point carries an id in its payload.
Memory points store only {created_at} in metadata (KB metadata embeddings
likewise), so deleting a single memory matched nothing and left an orphaned
vector that kept being injected into RAG context.
Delete by point id instead: PointIdsList for the standard backend, and a
tenant-scoped HasIdCondition for multitenancy (point ids are unique, so tenant
isolation is preserved). Filter-based deletion is unchanged.
Co-authored-by: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
* feat: add support for Valkey vector database
Signed-off-by: Riley Des <riley.desserre@improving.com>
* feat: add CLIENT SETNAME to Valkey vector store connections
Set client_name on GlideClientConfiguration for both the main client
and batch client so connections are identifiable in CLIENT LIST,
monitoring dashboards, and CloudWatch metrics.
Signed-off-by: Riley Des <riley.desserre@improving.com>
---------
Signed-off-by: Riley Des <riley.desserre@improving.com>
Open WebUI's collection ACL accepted any unknown name as a
legacy/ephemeral collection. In Milvus multi-tenancy mode that name
becomes the `resource_id` and is interpolated unescaped into a SQL-like
Milvus expression — `resource_id == '<name>'` — so a name like
x' or resource_id != '' or resource_id == 'x
turns the filter into a tautology and returns every tenant's chunks
from the shared collection.
All collection names Open WebUI generates are UUIDs, SHA-256 hex
digests, or fixed-prefix variants of those — they all fit
[A-Za-z0-9_-]. Add a strict format check in
filter_accessible_collections (utils.py) that drops any name outside
that set before any ACL or vector-store lookup, applied even on the
admin bypass path. _validate_collection_access then surfaces the dropped
name as a 403.
As defense in depth, MilvusClient now validates resource_id at every
expression-construction site and escapes single quotes / backslashes in
any other string interpolated into a filter (delete ids, metadata
filter values). Non-string filter values are typed-checked instead of
str()-formatted.
Co-authored-by: Claude <noreply@anthropic.com>
Replace bare except clauses with except Exception to follow Python best practices and avoid catching unexpected system exceptions like KeyboardInterrupt and SystemExit.
In opensearch-py >= 3.0.0, IndicesClient.refresh() no longer accepts the
index name as a positional argument. This causes a TypeError when
uploading documents to knowledge bases with OpenSearch backend.
Changes positional arguments to keyword arguments (index=...) in all
three refresh() calls in the OpenSearch vector DB client.
Fixes#20649
* fix: Use get_index() instead of list_indexes() in has_collection() to handle pagination
Fixes#19233
Replace list_indexes() pagination scan with direct get_index() lookup
in has_collection() method. The previous implementation only checked
the first ~1,000 indexes due to unhandled pagination, causing RAG
queries to fail for indexes beyond the first page.
Benefits:
- Handles buckets with any number of indexes (no pagination needed)
- ~8x faster (0.19s vs 1.53s in testing)
- Proper exception handling for ResourceNotFoundException
- Scales to millions of indexes
* Update s3vector.py
Unneeded exception handling removed to match original OWUI code
* Adding hnsw index type for pgvector, allowing vector dimensions larger than 2000
* remove some variable assignments
* Make USE_HALFVEC variable configurable
* Simplify USE_HALFVEC handling
* Raise runtime error if the index requires rebuilt
---------
Co-authored-by: Moritz <moritz.mueller2@tu-dresden.de>
