Files
qdrant/tests/openapi/test_query_formula.py
Kumar ShivenduandClaude Opus 5 83fe47c90a feat: add a dedicated min operator to score formulas (#10296)
Follow-up to #10287, which added `max`. Expressing a minimum still
required spelling out `(a + b - |a - b|) / 2`, the sign flip of the max
identity — drop the `neg` and you silently get a maximum instead. It also
only works for two operands and mentions each one twice, so the scorer
walks every sub-tree twice per candidate point.

The pair is what makes clamping expressible:

    {"max": [0.0, {"min": [1.0, "$score"]}]}

`min` mirrors `max` throughout, and both guard helpers introduced in
#10287 already took an `operator: &str`, so they are reused unchanged: an
empty operand list is rejected at parse time rather than folding to
+infinity, and the Edge FFI rejects it at construction time. The result
needs no `is_finite` check, since `min` cannot produce a non-finite value
from finite inputs.

The unindexed-field walker shares one arm for `Max | Min` as the bodies
are identical, with a test pinning `min` separately so a later split
cannot silently drop it.

Co-authored-by: Claude Opus 5 (1M context) <noreply@anthropic.com>
2026-08-21 22:51:44 +05:30

320 lines
11 KiB
Python

import pytest
from math import acosh, isclose
from .helpers.collection_setup import basic_collection_setup, drop_collection
from .helpers.helpers import request_with_validation
@pytest.fixture(autouse=True, scope="module")
def setup(on_disk_vectors, collection_name):
basic_collection_setup(
collection_name=collection_name, on_disk_vectors=on_disk_vectors
)
response = request_with_validation(
api="/collections/{collection_name}/index",
method="PUT",
path_params={"collection_name": collection_name},
query_params={"wait": 'true'},
body={"field_name": "price", "field_schema": "float"},
)
assert response.ok
yield
drop_collection(collection_name=collection_name)
@pytest.mark.parametrize(
"formula,expecting",
[
(
{"sum": [{"mult": ["$score", 0.4]}, {"mult": ["price", 0.6]}]},
lambda score, price: 0.4 * score + 0.6 * price,
),
(
{
"sum": [
"$score",
# fast sigmoid formula
{
"div": {
"left": "price",
"right": {"sum": [1.0, {"abs": "price"}]},
}
},
],
},
lambda score, price: score + (price / (1.0 + abs(price))),
),
(
{"acosh": {"sum": [1.0, {"abs": "price"}]}},
lambda score, price: acosh(1.0 + abs(price)),
),
(
{"max": ["$score", "price"]},
lambda score, price: max(score, price),
),
# More than two operands, and nested sub-expressions
(
{"max": [{"mult": ["$score", 3.0]}, "price", 0.0]},
lambda score, price: max(3.0 * score, price, 0.0),
),
(
{"min": ["$score", "price"]},
lambda score, price: min(score, price),
),
# More than two operands, and nested sub-expressions
(
{"min": [{"mult": ["$score", 3.0]}, "price", 0.0]},
lambda score, price: min(3.0 * score, price, 0.0),
),
# max and min of the same operands bracket the operands from both sides
(
{"sum": [{"max": ["$score", "price"]}, {"min": ["$score", "price"]}]},
lambda score, price: max(score, price) + min(score, price),
),
],
)
def test_formula(collection_name, formula, expecting):
point_id = 8
# Get original scores
response = request_with_validation(
api="/collections/{collection_name}/points/query",
method="POST",
path_params={"collection_name": collection_name},
body={"query": point_id},
)
points = response.json()["result"]["points"]
orig_scores = {point.get("id"): point.get("score") for point in points}
query = {
"prefetch": {"query": point_id},
"query": {"formula": formula, "defaults": {"price": 0.0}},
"with_payload": True,
}
# Formula query
response = request_with_validation(
api="/collections/{collection_name}/points/query",
method="POST",
path_params={"collection_name": collection_name},
body=query,
)
assert response.ok, response.json()
# Assert that the response is in descending order
points = response.json()["result"]["points"]
scores = [point.get("score") for point in points]
assert all(scores[i] >= scores[i + 1] for i in range(len(scores) - 1)), (
"Results should be ordered by score descending"
)
# Sanity check that the evaluation was correct
for point in points:
orig_score = orig_scores[point.get("id")]
price_value = point.get("payload").get("price")
if price_value is list:
price = price_value[0]
else:
price = price_value
if price is None:
price = 0.0
# Calculate expected score according to formula
expected_score = expecting(orig_score, price)
point_score = point.get("score")
# Compare with actual score within floating point precision
assert isclose(point_score, expected_score, rel_tol=1e-5), (
f"Expected score {expected_score}, got {point_score}. Point: {point}"
)
# Assert that the response contains all points
assert len(points) == len(orig_scores), "Response should contain all points"
def test_formula_with_score_threshold(collection_name):
# Insert 4 test points with numeric payload "price" and a group tag
points = [
{"id": 1001, "vector": [0.1, 0.1, 0.1, 0.1], "payload": {"price": 0.1, "group": "threshold_test"}},
{"id": 1002, "vector": [0.2, 0.2, 0.2, 0.2], "payload": {"price": 0.6, "group": "threshold_test"}},
{"id": 1003, "vector": [0.3, 0.3, 0.3, 0.3], "payload": {"price": 0.4, "group": "threshold_test"}},
{"id": 1004, "vector": [0.4, 0.4, 0.4, 0.4], "payload": {"price": 0.9, "group": "threshold_test"}},
]
response = request_with_validation(
api="/collections/{collection_name}/points",
method="PUT",
path_params={"collection_name": collection_name},
query_params={"wait": "true"},
body={"points": points},
)
assert response.ok, response.json()
# Use a formula that sets the score equal to the payload "price"
formula = "price"
# Set a threshold of 0.5: expect ids with price >= 0.5 (1002 and 1004)
threshold = 0.5
expected_ids = {1002, 1004}
query = {
"prefetch": {"limit": 4},
"query": {"formula": formula, "defaults": {"price": 0.0}},
"filter": {"must": [{"key": "group", "match": {"value": "threshold_test"}}]},
"with_payload": True,
"limit": 10,
"score_threshold": threshold,
}
response = request_with_validation(
api="/collections/{collection_name}/points/query",
method="POST",
path_params={"collection_name": collection_name},
body=query,
)
assert response.ok, response.json()
points_resp = response.json()["result"]["points"]
returned_ids = {p.get("id") for p in points_resp}
# Assert returned ids match expected set
assert returned_ids == expected_ids, f"Expected ids {expected_ids}, got {returned_ids}"
# Also assert each returned point has score >= threshold
for p in points_resp:
assert p.get("score") >= threshold - 1e-8, (
f"Point {p.get('id')} with score {p.get('score')} is below threshold {threshold}"
)
def test_max_matches_the_arithmetic_workaround(collection_name):
"""Before `max` existed, users had to spell it as (a + b + |a - b|) / 2.
Both forms must produce identical scores, otherwise `max` is not a drop-in replacement
for the formulas already in the wild.
"""
point_id = 8
boosted = {"mult": [3.0, "$score"]}
workaround = {
"mult": [
0.5,
{
"sum": [
boosted,
"price",
{"abs": {"sum": [boosted, {"neg": "price"}]}},
]
},
]
}
direct = {"max": [boosted, "price"]}
def scores_for(formula):
response = request_with_validation(
api="/collections/{collection_name}/points/query",
method="POST",
path_params={"collection_name": collection_name},
body={
"prefetch": {"query": point_id},
"query": {"formula": formula, "defaults": {"price": 0.0}},
"limit": 10,
},
)
assert response.ok, response.json()
return {
point["id"]: point["score"] for point in response.json()["result"]["points"]
}
workaround_scores = scores_for(workaround)
direct_scores = scores_for(direct)
assert workaround_scores.keys() == direct_scores.keys()
for point_id, expected in workaround_scores.items():
assert isclose(direct_scores[point_id], expected, rel_tol=1e-5), (
f"point {point_id}: max gave {direct_scores[point_id]}, workaround gave {expected}"
)
def test_empty_max_is_rejected(collection_name):
"""`sum: []` is 0 and `mult: []` is 1, but the max of nothing has no sensible value,
so it must be rejected rather than silently scoring every point as -infinity."""
response = request_with_validation(
api="/collections/{collection_name}/points/query",
method="POST",
path_params={"collection_name": collection_name},
body={
"prefetch": {"query": 8},
"query": {"formula": {"max": []}},
},
)
assert not response.ok, response.json()
assert response.status_code == 400, response.json()
def test_empty_min_is_rejected(collection_name):
"""Same as the empty `max` case: no identity element, so it must be rejected rather than
silently scoring every point as +infinity."""
response = request_with_validation(
api="/collections/{collection_name}/points/query",
method="POST",
path_params={"collection_name": collection_name},
body={
"prefetch": {"query": 8},
"query": {"formula": {"min": []}},
},
)
assert not response.ok, response.json()
assert response.status_code == 400, response.json()
def test_min_matches_the_arithmetic_workaround(collection_name):
"""The identity for a minimum is (a + b - |a - b|) / 2, the sign flip of the max one.
Same reasoning as the `max` case: `min` must be a drop-in replacement for formulas
already written out by hand.
"""
point_id = 8
boosted = {"mult": [3.0, "$score"]}
workaround = {
"mult": [
0.5,
{
"sum": [
boosted,
"price",
{"neg": {"abs": {"sum": [boosted, {"neg": "price"}]}}},
]
},
]
}
direct = {"min": [boosted, "price"]}
def scores_for(formula):
response = request_with_validation(
api="/collections/{collection_name}/points/query",
method="POST",
path_params={"collection_name": collection_name},
body={
"prefetch": {"query": point_id},
"query": {"formula": formula, "defaults": {"price": 0.0}},
"limit": 10,
},
)
assert response.ok, response.json()
return {
point["id"]: point["score"] for point in response.json()["result"]["points"]
}
workaround_scores = scores_for(workaround)
direct_scores = scores_for(direct)
assert workaround_scores.keys() == direct_scores.keys()
for point_id, expected in workaround_scores.items():
assert isclose(direct_scores[point_id], expected, rel_tol=1e-5), (
f"point {point_id}: min gave {direct_scores[point_id]}, workaround gave {expected}"
)