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* Remove deprecated search/recommend/discover endpoints from OpenAPI Remove deprecated REST API endpoint definitions from the OpenAPI generator. These endpoints were deprecated in v1.13.3 (`f4ced2567`, #5907, 2025-01-30) in favor of the universal `/points/query` endpoint: - POST /points/search - POST /points/search/batch - POST /points/search/groups - POST /points/recommend - POST /points/recommend/batch - POST /points/recommend/groups - POST /points/discover - POST /points/discover/batch Also removes the corresponding request types from the schema generator and updates the expected API count in the consistency check. Co-authored-by: Cursor <cursoragent@cursor.com> * Migrate OpenAPI integration tests to /points/query The deprecated /points/search, /points/recommend and /points/discover endpoints (along with their /batch and /groups variants) were removed from the OpenAPI spec, which caused validation failures in the Python integration test harness. This commit migrates the affected tests to the universal /points/query endpoint: - Delete tests dedicated to the deprecated endpoints: test_recommend.py, test_discover.py, test_multicollection_reco.py, test_recommendation_multivector.py - Refactor remaining tests to call /points/query (and /query/batch, /query/groups), translating request bodies (vector -> query / using, positive/negative -> query.recommend, target/context -> query.discover) and unwrapping the new result.points response shape. - Drop equivalence assertions against the now-removed legacy endpoints. Co-authored-by: Cursor <cursoragent@cursor.com> * Relax non-empty assertions in migrated recommend/discover tests The previous migration added `len(...) > 0` assertions to tests that previously only checked equivalence between the deprecated and new API. These assertions are too strict because the parametrized `query_filter` cases legitimately produce empty result sets. Drop the `> 0` assertion and rely on `request_with_validation` to verify the response is well-formed and HTTP OK. Co-authored-by: Cursor <cursoragent@cursor.com> * Migrate remaining OpenAPI tests off deprecated search endpoints Tests added to dev after the original migration was written still call /points/search and /points/recommend/groups through `request_with_validation`, which resolves the endpoint against the OpenAPI spec and therefore breaks once the endpoint is not in the spec: - test_turbo4_storage.py, test_sparse_idf_corpus.py, test_validation.py: translate /points/search to /points/query (vector{name,vector} -> query + using, result -> result.points). - test_group.py: drop the /points/recommend/groups half of the lookup_from validation test in favour of the query equivalent. test_sparse_idf_corpus.py's test_query_api_supports_idf_corpus goes away: with the helper on /points/query every test in the file now exercises what it asserted. Also record why test_recommend_group cannot assert on its groups: it uses every point in the collection as a recommend example, so all of them are excluded and the result is legitimately empty. Co-Authored-By: Claude Opus 5 <noreply@anthropic.com> * Regenerate openapi.json without the deprecated search endpoints Drops the 8 deprecated paths and the request schemas that only they referenced: Search/Recommend/Discover request (+Batch, +Groups) types and their exclusive dependencies (NamedVector, NamedSparseVector, NamedVectorStruct, UsingVector, RecommendExample, ContextExamplePair). Regenerated output is a strict subset of the previous spec, and every remaining $ref still resolves. Co-Authored-By: Claude Opus 5 <noreply@anthropic.com> * Deprecate the search/recommend/discover RPCs in gRPC The REST counterparts have carried `deprecated: true` since v1.13.3 and are now gone from the OpenAPI spec, while the gRPC RPCs never got any deprecation annotation at all. Mark all 8 with `option deprecated = true` so generated clients warn, and point each doc comment at its `Query` replacement. tonic puts `#[deprecated]` on the generated client methods only; the server trait gets the doc comment alone, so our own `impl` is unaffected. The RPCs keep serving traffic — this is annotation only. Co-Authored-By: Claude Opus 5 <noreply@anthropic.com> * Restore the deleted recommend/discover suites on /points/query The earlier migration deleted these four files outright, but the query-side tests it left behind are all shallow smoke tests (`len(result) > 0`, `"points" in result[0]`). The deleted ones carried invariants with no query-API equivalent anywhere, so deleting them was a real loss of coverage rather than de-duplication: - test_recommend.py: default strategy equals average_vector; batch results identical to sequential singles across six request shapes; best_score with only negatives yields all-negative scores; best_score with a single positive orders identically to a nearest query; raw vectors as examples equal ids as examples. - test_discover.py: context-only scores are all <= 0; target-only orders identically to a nearest query but scores differently; with a fixed context the integer part of the score is stable while the decimal part moves, and vice versa with a fixed target; batch equals singles; lookup_from by id equals by vector. - test_multicollection_reco.py: cross-collection lookup_from, plus wrong-vector-size, unknown-collection and unknown-vector rejections. - test_recommendation_multivector.py: the same recommend invariants over a max_sim multivector collection, which the query suite never covered. Only test_recommend_missing_lookup_from_collection_with_raw_vector is dropped as genuinely redundant — test_query.py's test_query_missing_lookup_from_collection covers query, query/batch and prefetch. Two request-shape differences the translation had to absorb: - Giving no examples at all is 422 (a RecommendInput validation rule), where the legacy API reported 400 from the query itself. A malformed example, such as an empty vector, is still 400. - DiscoverInput requires the `context` key and accepts only an explicit null to mean "no context", so target-only discover must spell it out. The legacy API let it be omitted. Co-Authored-By: Claude Opus 5 <noreply@anthropic.com> --------- Co-authored-by: Cursor <cursoragent@cursor.com> Co-authored-by: Claude Opus 5 <noreply@anthropic.com>
331 lines
10 KiB
Python
331 lines
10 KiB
Python
import pytest
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from .helpers.collection_setup import basic_collection_setup, drop_collection
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from .helpers.helpers import request_with_validation
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@pytest.fixture(scope='module', autouse=True)
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def collection_name2(collection_name):
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return f"{collection_name}_2"
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@pytest.fixture(autouse=True, scope="module")
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def setup(on_disk_vectors, collection_name, collection_name2):
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basic_collection_setup(collection_name=collection_name, on_disk_vectors=on_disk_vectors)
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yield
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drop_collection(collection_name=collection_name)
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# delete potential auxiliary collection as well
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drop_collection(collection_name=collection_name2)
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def test_recommend_with_wrong_vector_size(on_disk_vectors, collection_name, collection_name2):
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response = request_with_validation(
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api='/collections/{collection_name}',
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method="DELETE",
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path_params={'collection_name': collection_name2},
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)
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assert response.ok
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response = request_with_validation(
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api='/collections/{collection_name}',
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method="PUT",
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path_params={'collection_name': collection_name2},
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body={
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"vectors": {
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"other": {
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"size": 5,
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"distance": "Dot",
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"on_disk": on_disk_vectors,
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}
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}
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}
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)
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assert response.ok
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response = request_with_validation(
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api='/collections/{collection_name}/points',
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method="PUT",
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path_params={'collection_name': collection_name2},
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query_params={'wait': 'true'},
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body={
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"points": [
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{
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"id": 1,
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"vector": {"other": [1.0, 0.0, 0.0, 0.0, 0.0]},
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},
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{
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"id": "00000000-0000-0000-0000-000000000000",
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"vector": {"other": [0.0, 1.0, 0.0, 0.0, 0.0]},
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}
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]
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}
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)
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assert response.ok, response.text
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response = request_with_validation(
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api='/collections/{collection_name}/points/query',
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method="POST",
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path_params={'collection_name': collection_name},
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body={
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"limit": 3,
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"query": {"recommend": {"positive": [1]}},
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"with_vector": False,
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"with_payload": True,
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"lookup_from": {
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"collection": collection_name2,
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"vector": "other"
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}
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}
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)
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assert response.status_code == 400, response.text
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def test_recommend_from_another_collection(on_disk_vectors, collection_name, collection_name2):
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# Create another collection with the same vector size.
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# Use vectors from the second collection to search in the first collection.
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response = request_with_validation(
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api='/collections/{collection_name}',
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method="DELETE",
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path_params={'collection_name': collection_name2},
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)
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assert response.ok
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response = request_with_validation(
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api='/collections/{collection_name}',
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method="PUT",
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path_params={'collection_name': collection_name2},
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body={
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"vectors": {
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"other": {
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"size": 4,
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"distance": "Dot",
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"on_disk": on_disk_vectors,
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}
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}
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}
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)
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assert response.ok
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response = request_with_validation(
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api='/collections/{collection_name}/points',
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method="PUT",
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path_params={'collection_name': collection_name2},
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query_params={'wait': 'true'},
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body={
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"points": [
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{
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"id": 1,
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"vector": {"other": [1.0, 0.0, 0.0, 0.0]},
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},
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{
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"id": "00000000-0000-0000-0000-000000000000",
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"vector": {"other": [0.0, 1.0, 0.0, 0.0]},
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}
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]
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}
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)
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assert response.ok, response.text
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response = request_with_validation(
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api='/collections/{collection_name}/points/query',
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method="POST",
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path_params={'collection_name': collection_name},
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body={
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"limit": 3,
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"query": {"recommend": {"positive": [1]}},
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"with_vector": False,
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"with_payload": True,
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"lookup_from": {
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"collection": collection_name2,
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"vector": "other"
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}
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}
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)
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assert response.ok, response.text
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assert len(response.json()['result']['points']) == 3
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# vector with the largest 1st element
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assert response.json()['result']['points'][0]['id'] == 8
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response = request_with_validation(
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api='/collections/{collection_name}/points/query/batch',
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method="POST",
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path_params={'collection_name': collection_name},
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body={
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"searches": [
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{
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"limit": 3,
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"query": {"recommend": {"positive": [1]}},
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"with_vector": False,
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"with_payload": True,
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"lookup_from": {
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"collection": collection_name2,
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"vector": "other"
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}
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},
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{
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"limit": 3,
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"query": {"recommend": {"positive": ["00000000-0000-0000-0000-000000000000"]}},
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"with_vector": False,
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"with_payload": True,
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"lookup_from": {
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"collection": collection_name2,
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"vector": "other"
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}
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},
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{
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"limit": 3,
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"query": {"recommend": {"positive": [1]}},
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"with_vector": False,
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"with_payload": True,
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}
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]
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}
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)
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assert response.ok, response.text
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assert len(response.json()['result']) == 3
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assert len(response.json()['result'][0]['points']) == 3
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assert len(response.json()['result'][1]['points']) == 3
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assert len(response.json()['result'][2]['points']) == 3
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# vector with the largest 1st element
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assert response.json()['result'][0]['points'][0]['id'] == 8
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# vector with the largest 2nd element
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assert response.json()['result'][1]['points'][0]['id'] == 7
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response = request_with_validation(
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api='/collections/{collection_name}/points/query',
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method="POST",
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path_params={'collection_name': collection_name},
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body={
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"limit": 3,
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"query": {"recommend": {"positive": [1]}},
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"lookup_from": {
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"collection": "unknown_collection",
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"vector": "other"
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}
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}
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)
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assert response.status_code == 404
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response = request_with_validation(
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api='/collections/{collection_name}/points/query',
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method="POST",
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path_params={'collection_name': collection_name},
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body={
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"limit": 3,
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"query": {"recommend": {"positive": [1]}},
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"lookup_from": {
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"collection": collection_name2,
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"vector": "unknown_vector"
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}
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}
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)
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assert response.status_code == 400, response.text
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response = request_with_validation(
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api='/collections/{collection_name}/points/query',
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method="POST",
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path_params={'collection_name': collection_name},
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body={
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"limit": 3,
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"query": {"recommend": {"positive": [2]}},
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"lookup_from": {
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"collection": collection_name2,
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"vector": "unknown_vector"
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}
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}
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)
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assert response.status_code == 404, response.text
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response = request_with_validation(
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api='/collections/{collection_name}',
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method="DELETE",
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path_params={'collection_name': collection_name2},
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)
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assert response.ok
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def test_recommend_lookup(collection_name, collection_name2):
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# delete lookup collection if exists
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response = request_with_validation(
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api='/collections/{collection_name}',
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method="DELETE",
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path_params={'collection_name': collection_name2},
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)
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assert response.ok, response.text
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# re-create lookup collection
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response = request_with_validation(
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api='/collections/{collection_name}',
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method="PUT",
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path_params={'collection_name': collection_name2},
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body={
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"vectors": {
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"other": {
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"size": 4,
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"distance": "Dot",
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}
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}
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}
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)
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assert response.ok, response.text
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# insert vectors to lookup collection
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response = request_with_validation(
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api='/collections/{collection_name}/points',
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method="PUT",
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path_params={'collection_name': collection_name2},
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query_params={'wait': 'true'},
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body={
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"points": [
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{
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"id": 1,
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"vector": {"other": [1.0, 0.0, 0.0, 0.0]},
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},
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{
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"id": 2,
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"vector": {"other": [0.0, 0.0, 0.0, 2.0]},
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},
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]
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}
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)
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assert response.ok, response.text
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# check recommend by id + lookup_from
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response = request_with_validation(
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api="/collections/{collection_name}/points/query",
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method="POST",
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path_params={"collection_name": collection_name},
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body={
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"query": {"recommend": {"positive": [1], "negative": [2]}},
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"limit": 10,
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"lookup_from": {
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"collection": collection_name2,
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"vector": "other"
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}
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},
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)
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assert response.ok, response.text
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recommend_result_by_id = response.json()["result"]["points"]
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# check recommend by vector + lookup_from
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response = request_with_validation(
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api="/collections/{collection_name}/points/query",
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method="POST",
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path_params={"collection_name": collection_name},
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body={
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"query": {
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"recommend": {
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"positive": [[1.0, 0.0, 0.0, 0.0]],
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"negative": [[0.0, 0.0, 0.0, 2.0]],
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}
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},
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"limit": 10,
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},
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)
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assert response.ok, response.text
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recommend_result_by_vector = response.json()["result"]["points"]
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# results should be equivalent
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assert recommend_result_by_id == recommend_result_by_vector, \
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f"recommend_result_by_id: {recommend_result_by_id}, recommend_result_by_vector: {recommend_result_by_vector}"
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