Apply literal contains filters consistently to numeric and textual fields

great_ai/persistence/mongodb_driver.py

@@ -1,3 +1,4 @@
+import re
 from datetime import datetime
 from typing import Any, Dict, List, Optional, Sequence, Tuple
 
@@ -102,6 +103,19 @@ class MongoDbDriver(TracingDatabaseDriver):
             return operator_mapping["="]
         return operator_mapping[filter.operator]
 
+    def _get_filter(self, filter: Filter) -> Dict[str, Any]:
+        if filter.operator == "contains":
+            text_filter = {
+                filter.property: {
+                    "$regex": re.escape(filter.value_as_text),
+                    "$options": "i",
+                }
+            }
+            if isinstance(filter.value, str):
+                return text_filter
+            return {"$or": [{filter.property: {"$eq": filter.value}}, text_filter]}
+        return {filter.property: {self._get_operator(filter): filter.value}}
+
     def query(
         self,
         *,
@@ -121,9 +135,7 @@ class MongoDbDriver(TracingDatabaseDriver):
 
         and_query: List[Dict[str, Any]] = []
         and_query.extend({"tags": tag} for tag in conjunctive_tags)
-        and_query.extend(
+        and_query.extend(self._get_filter(f) for f in conjunctive_filters)
-            {f.property: {self._get_operator(f): f.value}} for f in conjunctive_filters
-        )
         if not and_query:
             and_query.append({})
 

great_ai/persistence/parallel_tinydb_driver.py

@@ -84,10 +84,14 @@ class ParallelTinyDbDriver(TracingDatabaseDriver):
                     getattr(df[f.property], operator_mapping[f.operator])(f.value)
                 ]
             elif operator == "contains":
+                pattern = f.value_as_text.casefold()
                 df = df.loc[
-                    df[f.property].str.contains(
+                    df[f.property].map(
-                        str(int(f.value)) if isinstance(f.value, float) else f.value,
+                        lambda value: (
-                        case=False,
+                            pattern in value.casefold()
+                            if isinstance(value, str)
+                            else not isinstance(f.value, str) and value == f.value
+                        )
                     )
                 ]
 

great_ai/views/filter.py

@@ -1,3 +1,4 @@
+import builtins
 from typing import Union
 
 from pydantic import BaseModel
@@ -9,3 +10,9 @@ class Filter(BaseModel):
     property: str
     operator: Operator
     value: Union[float, str]
+
+    @builtins.property
+    def value_as_text(self) -> str:
+        if isinstance(self.value, float) and self.value.is_integer():
+            return str(int(self.value))
+        return str(self.value)

tests/test_database_regressions.py

@@ -5,10 +5,10 @@ from pathlib import Path
 from typing import Any
 from unittest.mock import patch
 
-from tinydb.table import Table
-
 from great_ai import ParallelTinyDbDriver, Trace
 from great_ai.context import get_context
+from great_ai.views import Filter
+from tinydb.table import Table
 
 
 def write_traces(path: str, index: int, barrier: Any) -> None:
@@ -74,3 +74,45 @@ def test_tinydb_date_queries_normalize_timezones(isolated_context: None) -> None
     noon = datetime(2026, 1, 1, 12, tzinfo=timezone.utc)
     assert database.query(since=noon, until=noon)[1] == 2
     assert database.query(since=noon.replace(hour=13))[1] == 0
+
+
+def test_contains_handles_numbers_and_literal_punctuation(
+    isolated_context: None,
+) -> None:
+    database = get_context().tracing_database
+    database.save(
+        Trace(
+            trace_id="contains",
+            created="2026-01-01",
+            original_execution_time_ms=2.5,
+            models=[],
+            tags=[],
+            logged_values={"text": "A[2.5"},
+        )
+    )
+    for property, value in (
+        ("original_execution_time_ms", 2.5),
+        ("text", "["),
+        ("text", 2.5),
+        ("text", "a["),
+    ):
+        assert (
+            database.query(
+                conjunctive_filters=[
+                    Filter(property=property, operator="contains", value=value)
+                ]
+            )[1]
+            == 1
+        )
+    assert (
+        database.query(
+            conjunctive_filters=[
+                Filter(
+                    property="original_execution_time_ms",
+                    operator="contains",
+                    value="[",
+                )
+            ]
+        )[1]
+        == 0
+    )

tests/test_mongodb_queries.py

@@ -1,10 +1,10 @@
 from datetime import datetime, timedelta, timezone
 from typing import Any, Iterator, Tuple
-from unittest.mock import MagicMock, patch
+from unittest.mock import patch
 
 import pytest
-
 from great_ai import MongoDbDriver
+from great_ai.views import Filter
 
 
 @pytest.fixture
@@ -44,3 +44,24 @@ def test_empty_batch_is_a_noop(mongo: Tuple[MongoDbDriver, Any]) -> None:
     driver, collection = mongo
     assert driver.save_batch([]) == []
     collection.insert_many.assert_not_called()
+
+
+def test_mongo_contains_uses_literal_case_insensitive_patterns(
+    mongo: Tuple[MongoDbDriver, Any],
+) -> None:
+    driver, collection = mongo
+    driver.query(
+        conjunctive_filters=[Filter(property="text", operator="contains", value="a[")]
+    )
+    assert {
+        "text": {"$regex": r"a\[", "$options": "i"}
+    } in collection.find.call_args.kwargs["filter"]["$and"]
+    numeric = driver._get_filter(
+        Filter(property="score", operator="contains", value=2.5)
+    )
+    assert numeric == {
+        "$or": [
+            {"score": {"$eq": 2.5}},
+            {"score": {"$regex": r"2\.5", "$options": "i"}},
+        ]
+    }