feat(server): relations from GLiNER relex models, plus GLiNER bi-encoder v2 and PII models - #356
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The cache of precomputed label embeddings was keyed by the set of labels, but the embeddings are matched to labels by position. A request that sent the same labels in a different order reused the other order's embeddings, so its entities came back under the wrong labels. Key the cache by the ordered label list. Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
gliner 0.2.26 is the first release that loads the joint entity-relation (relex) checkpoints. It is also the version the lock already resolves. Raising the floor changes the default bundle's requirements hash. Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
The bi-encoder loads its label tokenizer from the label-encoder repository named in its GLiNER config, at whatever revision is current. Pin that repository with hf_tokenizer_dependencies, as the other GLiNER configs do for the tokenizers they fetch. Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
Adds Knowledgator's gliner-bi-{edge,small,large}-v2.0 bi-encoder NER
models next to the existing gliner-bi-base-v2.0, and the
gliner-pii-{edge,small,base,large}-v1.0 models for personal-data spans.
All are Apache-2.0, load with the existing GLiNER adapters, and pin their
revisions. The bi-encoder configs also pin their label-encoder
tokenizers. The PII configs default to the entity threshold of 0.3 that
the model card uses.
Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
GLiNER relex models extract entities and the relations between them in one pass. The GLiNER adapter now returns those relations when a request names relation types in `options.relation_labels`. They use the existing extract relation format (head, tail, relation, score), highest score first. `options.relation_threshold` sets the relation cutoff: the model configs default it to 0.7, and without a config value it falls back to the entity threshold. Relex models score every pair of entity candidates, so memory grows with the square of the candidate count, and a low entity threshold on a long document can produce thousands of candidates. The adapter slices the candidate tensors to at most 100 per item, in document order, before any pairs are built. Relations among later candidates are dropped, and all entities are still returned. Relex requests need an entity threshold of at least 0.1. The adapter also floors the adjacency threshold at 0.5. Relex models return entities only when a request names no relation types. Other GLiNER models make the same inference call as before, and both GLiNER adapters reject `relation_labels` for models without relations. Caller errors now raise InvalidInputError, so both the HTTP and the queue paths answer INVALID_INPUT. These include missing labels, missing or blank text, an entity or relation threshold outside [0, 1] (for either GLiNER adapter), malformed relation options, and label and relation prompts that leave no room for the document. Metering tokenizes the relation prompt along with the entity prompt so that it counts the document tokens the model actually keeps. The prompt itself is not billed. Adds knowledgator/gliner-relex-large-v1.0 (Apache-2.0), a span-level relex model. The token-level base and multi checkpoints are left out: gliner's token-level span extraction runs before the candidate cap and is not bounded yet. Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
Behavior change: responses from GLiNER bi-encoder models (knowledgator/gliner-bi-*, knowledgator/modern-gliner-bi-*) now carry `usage.input_tokens`, and queued work reports input-token units. Before, the adapter returned no counts, so usage was omitted. A bi-encoder encodes labels separately, so its text input is the document alone. The count is the attended tokens of the word window the GLiNER processor keeps, special tokens included, which is the same document-token contract as the GLiNER adapter. Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
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Included review availability: Your plan provides up to 10 included reviews per hour; 4 remain after this review. 📝 WalkthroughWalkthroughThis change adds GLiNER BI, PII, and ReLEx model configurations. GLiNERAdapter supports joint entity and relation extraction. GLiNER-bi adds input validation, document token counts, and ordered label-embedding cache keys. ChangesGLiNER model support
Sequence Diagram(s)sequenceDiagram
participant SDKClient
participant GLiNERAdapter
participant ReLExModel
SDKClient->>GLiNERAdapter: extract text with relation_labels and thresholds
GLiNERAdapter->>ReLExModel: infer entities and requested relations
ReLExModel-->>GLiNERAdapter: entity and relation batches
GLiNERAdapter-->>SDKClient: entities, relations, and token counts
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✅ Passed checks (4 passed)
Full details: Docstring CoverageExplanation Docstring coverage is 21.05% which is insufficient. The required threshold is 80.00%. Docstring coverage is scoped to functions touched by this diff. Analyzed 76 functions across 7 files. (3 skipped: 3 unsupported.)
✨ Finishing Touches 💡 1📝 Generate docstrings 💡
🧪 Generate unit tests (beta)
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In `@packages/sie_server/src/sie_server/adapters/gliner_bi/__init__.py`:
- Line 254: Update `_doc_input_token_counts` and the `ExtractOutput`
construction in the GLiNER adapter so whitespace-only documents receive a zero
token count, matching inference behavior; preserve the original document
positions when restoring counts. Do not count special tokens for skipped
documents.
- Line 256: Move GLiNERBiAdapter and its helper implementations, including
_doc_input_token_counts, from __init__.py into a regular module; update import
sites to use that module and leave __init__.py empty.
In `@packages/sie_server/src/sie_server/adapters/gliner/__init__.py`:
- Around line 510-537: Update _cap_relation_candidates to fail closed when
represent_spans returns an unsupported output layout: raise an error if
outputs[2] is not a two-dimensional tensor instead of returning uncapped
outputs. Preserve the existing slicing behavior for supported layouts so the
candidate limit remains enforced.
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README.mdpackages/sie_sdk/README.mdpackages/sie_server/bundles/default.yamlpackages/sie_server/models/knowledgator__gliner-bi-base-v2.0.yamlpackages/sie_server/models/knowledgator__gliner-bi-edge-v2.0.yamlpackages/sie_server/models/knowledgator__gliner-bi-large-v2.0.yamlpackages/sie_server/models/knowledgator__gliner-bi-small-v2.0.yamlpackages/sie_server/models/knowledgator__gliner-pii-base-v1.0.yamlpackages/sie_server/models/knowledgator__gliner-pii-edge-v1.0.yamlpackages/sie_server/models/knowledgator__gliner-pii-large-v1.0.yamlpackages/sie_server/models/knowledgator__gliner-pii-small-v1.0.yamlpackages/sie_server/models/knowledgator__gliner-relex-large-v1.0.yamlpackages/sie_server/pyproject.tomlpackages/sie_server/src/sie_server/adapters/gliner/__init__.pypackages/sie_server/src/sie_server/adapters/gliner_bi/__init__.pypackages/sie_server/tests/adapters/test_gliner_bi_label_cache.pypackages/sie_server/tests/adapters/test_gliner_bi_metering.pypackages/sie_server/tests/adapters/test_gliner_metering.pypackages/sie_server/tests/adapters/test_gliner_relations.pypackages/sie_server/tests/test_all_models.py
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…coders gliner skips whitespace-only texts without encoding them, but the bi-encoder token count still tokenized them and billed their special tokens. Count only the texts gliner encodes, in its batches of 8, and report zero for the skipped positions. Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
The relation candidate cap slices the tensors that represent_spans returns. If a gliner release changes that layout, the cap used to pass the outputs through unchanged, so relation scoring could run over every candidate. Raise instead, so the bound holds or the request fails. Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
Keep both new SDK README sections (entities and relations, zero-shot classification) and regenerate uv.lock for the gliner and gliclass floors together. Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
Extract batching now keys options by their msgpack encoding and hands the adapter the options as sent, so relation_labels no longer arrive as a tuple rebuilt from the key. Replace the tuple test with one that runs the real handler: identical relation_labels share a key, a different order does not, and the adapter gets the list in request order. Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
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Summary
Relation extraction for GLiNER relex models, plus more Knowledgator GLiNER models, with fixes to the GLiNER bi-encoder adapter.
Relations from GLiNER joint entity-relation models
options.relation_labels, and optionallyoptions.relation_threshold.Relationformat (head/tail text, relation, score), consistent with GLiNER2 and GLiREL.relation_labelsreturn entities only.relation_labelswith a 400.knowledgator/gliner-relex-large-v1.0, pinned, Apache-2.0, withrelation_threshold: 0.7, the model card's recommended range.gliner-relex-base-v1.0,gliner-relex-multi-v1.0). Their span extraction runs before the candidate cap and isn't bounded yet, so they will come in a follow-up.More models
All are Apache-2.0 and pinned:
knowledgator/gliner-bi-{edge,small,large}-v2.0. Their label-encoder tokenizers are pinned throughhf_tokenizer_dependencies, and the existinggliner-bi-base-v2.0now gets the same pin.knowledgator/gliner-pii-{edge,small,base,large}-v1.0, withthreshold: 0.3from the model card.Fixes
usage.input_tokens. Previously they reported none.InvalidInputError: missing labels, missing or blank text, out-of-range thresholds, and relation options sent to models that don't support them.>=0.2.26, the first release that loads the relex models.Validation
test_all_modelsentries pass.mise run lint,mise run typecheckandmise run testpass (7664 passed).🤖 Generated with Claude Code
Summary by CodeRabbit