one-liner

src/paperless_ai/base_model.py

@@ -1,7 +1,34 @@
+from typing import Any
+from typing import Final
 from typing import TypedDict
 
 from pydantic import BaseModel
 from pydantic import Field
+from pydantic import ValidationInfo
+from pydantic import field_validator
+from pydantic.fields import FieldInfo
+
+# taxonomy.py MAX_TAG_CANDIDATES = 10, prompt is "up to 3 relevant dates"
+MAX_EXISTING_IDS: Final = 10
+MAX_NEW_NAMES: Final = 8
+MAX_DATES: Final = 3
+# Matches documents.models.Document.title's CharField(max_length=128).
+MAX_TITLE_LENGTH: Final = 128
+
+
+def _truncate_to_field_limit(value: Any, field: FieldInfo) -> Any:
+    """
+    Clip down to its it's declared maximum. Run as a `mode="before"` validator.
+    """
+    limit = next(
+        (m.max_length for m in field.metadata if hasattr(m, "max_length")),
+        None,
+    )
+    return (
+        value
+        if (limit is None or not isinstance(value, (list, str)))
+        else value[:limit]
+    )
 
 
 class TaxonomyChoice(BaseModel):
@@ -14,19 +41,32 @@ class TaxonomyChoice(BaseModel):
     TaxonomyChoiceDict below.
     """
 
-    existing_ids: list[int] = Field(default_factory=list)
+    existing_ids: list[int] = Field(
-    new_names: list[str] = Field(default_factory=list)
+        default_factory=list,
+        max_length=MAX_EXISTING_IDS,
+    )
+    new_names: list[str] = Field(default_factory=list, max_length=MAX_NEW_NAMES)
+
+    @field_validator("existing_ids", "new_names", mode="before")
+    @classmethod
+    def _truncate(cls, value: Any, info: ValidationInfo) -> Any:
+        return _truncate_to_field_limit(value, cls.model_fields[info.field_name])
 
 
 class DocumentClassifierSchema(BaseModel):
     """Schema for document classification suggestions."""
 
-    title: str
+    title: str = Field(max_length=MAX_TITLE_LENGTH)
     tags: TaxonomyChoice = Field(default_factory=TaxonomyChoice)
     correspondents: TaxonomyChoice = Field(default_factory=TaxonomyChoice)
     document_types: TaxonomyChoice = Field(default_factory=TaxonomyChoice)
     storage_paths: TaxonomyChoice = Field(default_factory=TaxonomyChoice)
-    dates: list[str] = Field(default_factory=list)
+    dates: list[str] = Field(default_factory=list, max_length=MAX_DATES)
+
+    @field_validator("title", "dates", mode="before")
+    @classmethod
+    def _truncate(cls, value: Any, info: ValidationInfo) -> Any:
+        return _truncate_to_field_limit(value, cls.model_fields[info.field_name])
 
 
 class TaxonomyChoiceDict(TypedDict):

src/paperless_ai/tests/test_base_model.py

@@ -1,3 +1,7 @@
+from paperless_ai.base_model import MAX_DATES
+from paperless_ai.base_model import MAX_EXISTING_IDS
+from paperless_ai.base_model import MAX_NEW_NAMES
+from paperless_ai.base_model import MAX_TITLE_LENGTH
 from paperless_ai.base_model import ClassificationSuggestions
 from paperless_ai.base_model import DocumentClassifierSchema
 from paperless_ai.base_model import TaxonomyChoice
@@ -63,6 +67,86 @@ def test_document_classifier_schema_json_schema_is_self_contained():
     assert set(taxonomy_choice_properties.keys()) == {"existing_ids", "new_names"}
 
 
+def test_every_sequence_in_the_emitted_schema_is_bounded():
+    """
+    GIVEN:
+        - The DocumentClassifierSchema pydantic model
+    WHEN:
+        - Its JSON schema is generated via model_json_schema()
+    THEN:
+        - Every array property in the schema, including those on the
+          referenced TaxonomyChoice definition, carries a maxItems
+    """
+    schema = DocumentClassifierSchema.model_json_schema()
+
+    unbounded = [
+        f"{owner}.{name}"
+        for owner, definition in [
+            ("DocumentClassifierSchema", schema),
+            *schema.get("$defs", {}).items(),
+        ]
+        for name, prop in definition.get("properties", {}).items()
+        if prop.get("type") == "array" and "maxItems" not in prop
+    ]
+
+    assert unbounded == []
+
+
+def test_dates_bound_matches_what_the_prompt_asks_for():
+    """
+    GIVEN:
+        - The DocumentClassifierSchema pydantic model
+    WHEN:
+        - The emitted maxItems for dates is inspected
+    THEN:
+        - It equals the 3 that build_prompt_without_rag asks the model for
+    """
+    dates_schema = DocumentClassifierSchema.model_json_schema()["properties"]["dates"]
+
+    assert dates_schema["maxItems"] == MAX_DATES == 3
+
+
+def test_over_long_response_is_truncated_rather_than_rejected():
+    """
+    GIVEN:
+        - An LLM response overshooting every declared bound
+    WHEN:
+        - DocumentClassifierSchema is constructed from it
+    THEN:
+        - Each field is clipped to its maximum, with no ValidationError
+    """
+    parsed = DocumentClassifierSchema(
+        title="T" * (MAX_TITLE_LENGTH + 50),
+        tags=TaxonomyChoice(
+            existing_ids=list(range(MAX_EXISTING_IDS + 20)),
+            new_names=["n"] * (MAX_NEW_NAMES + 20),
+        ),
+        dates=[f"2016-{month:02d}-01" for month in range(1, 13)],
+    )
+
+    assert len(parsed.title) == MAX_TITLE_LENGTH
+    assert len(parsed.dates) == MAX_DATES
+    assert len(parsed.tags.existing_ids) == MAX_EXISTING_IDS
+    assert len(parsed.tags.new_names) == MAX_NEW_NAMES
+
+
+def test_truncation_keeps_the_earliest_entries():
+    """
+    GIVEN:
+        - An over-long dates list from an LLM response
+    WHEN:
+        - DocumentClassifierSchema is constructed from it
+    THEN:
+        - The kept entries are the first ones the model emitted
+    """
+    parsed = DocumentClassifierSchema(
+        title="T",
+        dates=["2016-10-01", "2016-09-01", "2016-08-01", "2016-07-01", "2016-06-01"],
+    )
+
+    assert parsed.dates == ["2016-10-01", "2016-09-01", "2016-08-01"]
+
+
 def test_model_dump_matches_typed_dict_keys():
     """
     GIVEN: