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feat: Added matched_tag field search api results with fuzzy search ca…
…pabilities

Signed-off-by: Aniket Paluskar <apaluska@redhat.com>
  • Loading branch information
aniketpalu committed Dec 11, 2025
commit 71b7ca3b12b4d91c5f5ce76ada49bf807acd2058
28 changes: 27 additions & 1 deletion sdk/python/feast/api/registry/rest/rest_utils.py
Original file line number Diff line number Diff line change
Expand Up @@ -558,13 +558,39 @@ def filter_search_results_and_match_score(
# Search in tags
tags = result.get("tags", {})
tag_match = False
matched_tag = None
best_fuzzy_score = 0.0
best_fuzzy_tag = None

for key, value in tags.items():
if query_lower in key.lower() or query_lower in str(value).lower():
key_lower = key.lower()
value_str = str(value).lower()

# Exact match in key or value
if query_lower in key_lower or query_lower in value_str:
tag_match = True
# Store the matched tag as a dictionary
matched_tag = {key: value}
break

# Fuzzy match for tags (on combined "key:value" string)
tag_combined = f"{key_lower}={value_str}"
tag_fuzzy_score = fuzzy_match(query_lower, tag_combined)

if tag_fuzzy_score > best_fuzzy_score:
best_fuzzy_score = tag_fuzzy_score
best_fuzzy_tag = {key: value}

if tag_match:
result["match_score"] = MATCH_SCORE_TAGS
result["matched_tag"] = matched_tag
filtered_results.append(result)
continue

# Fuzzy tag match
if best_fuzzy_score >= MATCH_SCORE_DEFAULT_THRESHOLD:
result["match_score"] = best_fuzzy_score * 100
result["matched_tag"] = best_fuzzy_tag
filtered_results.append(result)
continue

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103 changes: 103 additions & 0 deletions sdk/python/tests/unit/api/test_search_api.py
Original file line number Diff line number Diff line change
Expand Up @@ -734,6 +734,109 @@ def test_search_by_tags(self, shared_search_responses):
f"Expected to find some of {expected_resources} but found none in {found_resources}"
)

def test_search_matched_tag_exact_match(self, search_test_app):
"""Test that matched_tag field is present when a tag matches exactly"""
# Search for "data" which should match tag key "team" with value "data"
response = search_test_app.get("/search?query=data")
assert response.status_code == 200

data = response.json()
results = data["results"]
print(results)

# Find results that matched via tags (match_score = 60)
tag_matched_results = [
r for r in results if r.get("match_score") == 60 and "matched_tag" in r
]

assert len(tag_matched_results) > 0, (
"Expected to find at least one result with matched_tag from tag matching"
)

# Verify matched_tag is present and has a valid dictionary value
for result in tag_matched_results:
matched_tag = result.get("matched_tag")
assert matched_tag is not None, (
f"matched_tag should not be None for result {result['name']}"
)
assert isinstance(matched_tag, dict), (
f"matched_tag should be a dictionary, got {type(matched_tag)}"
)
# matched_tag should be a dictionary with key:value format
assert len(matched_tag) > 0, "matched_tag should not be empty"
assert len(matched_tag) == 1, (
f"matched_tag should contain exactly one key-value pair, got {len(matched_tag)}"
)

logger.debug(
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f"Found {len(tag_matched_results)} results with matched_tag: {[r['name'] + ' -> ' + str(r.get('matched_tag', 'N/A')) for r in tag_matched_results]}"
)

def test_search_matched_tag_fuzzy_match(self, search_test_app):
"""Test that matched_tag field is present when a tag matches via fuzzy matching"""
# Search for "te" which should fuzzy match tag key "team"
# "te" vs "team": overlap={'t','e'}/union={'t','e','a','m'} = 2/4 = 50% (below threshold)
# Try "tea" which should fuzzy match "team" better
# "tea" vs "team": overlap={'t','e','a'}/union={'t','e','a','m'} = 3/4 = 75% (above threshold)
response = search_test_app.get("/search?query=tea")
assert response.status_code == 200

data = response.json()
results = data["results"]

# Find results that matched via fuzzy tag matching (match_score < 60 but >= 40)
fuzzy_tag_matched_results = [
r
for r in results
if r.get("match_score", 0) >= 40
and r.get("match_score", 0) < 60
and "matched_tag" in r
]

# If we don't find fuzzy matches, try a different query that's more likely to match
if len(fuzzy_tag_matched_results) == 0:
# Try "dat" which should fuzzy match tag value "data"
# "dat" vs "data": overlap={'d','a','t'}/union={'d','a','t','a'} = 3/4 = 75% (above threshold)
response = search_test_app.get("/search?query=dat")
assert response.status_code == 200
data = response.json()
results = data["results"]
fuzzy_tag_matched_results = [
r
for r in results
if r.get("match_score", 0) >= 40
and r.get("match_score", 0) < 60
and "matched_tag" in r
]

if len(fuzzy_tag_matched_results) > 0:
# Verify matched_tag is present for fuzzy matches
for result in fuzzy_tag_matched_results:
matched_tag = result.get("matched_tag")
assert matched_tag is not None, (
f"matched_tag should not be None for fuzzy-matched result {result['name']}"
)
assert isinstance(matched_tag, dict), (
f"matched_tag should be a dictionary, got {type(matched_tag)}"
)
assert len(matched_tag) > 0, "matched_tag should not be empty"
assert len(matched_tag) == 1, (
f"matched_tag should contain exactly one key-value pair, got {len(matched_tag)}"
)
# Verify the match_score is in the fuzzy range
assert 40 <= result.get("match_score", 0) < 60, (
f"Fuzzy tag match should have score in [40, 60), got {result.get('match_score')}"
)

logger.debug(
f"Found {len(fuzzy_tag_matched_results)} results with fuzzy matched_tag: {[r['name'] + ' -> ' + str(r.get('matched_tag', 'N/A')) + ' (score: ' + str(r.get('match_score', 'N/A')) + ')' for r in fuzzy_tag_matched_results]}"
)
else:
# If no fuzzy matches found, log for debugging but don't fail
logger.debug(
"No fuzzy tag matches found - this may be expected depending on test data and fuzzy matching threshold"
)

def test_search_sorting_functionality(self, shared_search_responses):
"""Test search results sorting using pre-computed responses"""
# Test match_score descending sort
Expand Down