MAESTRO: Implement FormatScorer with json, markdown, length, and structure format checks

Adds format.py scorer supporting four validation modes:
- json: validates parseable JSON
- markdown: checks for headers (0.5) and lists (0.5)
- length: proportional scoring against min/max token bounds
- structure: JSON schema validation via jsonschema library

Includes 38 passing tests covering all format types, edge cases, and async delegation.
This commit is contained in:
John Lightner 2026-04-07 03:00:56 -05:00
parent 7fc2a2b8c3
commit bc1d41e3a6
5 changed files with 406 additions and 2 deletions

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@ -20,7 +20,8 @@ Implement the core experiment execution engine: LLM adapters, response caching,
- [x] Implement backend/engine/scorers/embedding.py — uses a configurable embedding endpoint (Ollama nomic-embed-text or any OpenAI-compatible embedding API) to compute cosine similarity between output and reference answer. Normalize to 0.01.0 range. - [x] Implement backend/engine/scorers/embedding.py — uses a configurable embedding endpoint (Ollama nomic-embed-text or any OpenAI-compatible embedding API) to compute cosine similarity between output and reference answer. Normalize to 0.01.0 range.
<!-- Completed: EmbeddingScorer using httpx async calls to OpenAI-compatible /embeddings endpoint, cosine similarity normalized to [0,1]. Reads reference from context["reference"]. 19 tests in test_scorer_embedding.py, all passing. --> <!-- Completed: EmbeddingScorer using httpx async calls to OpenAI-compatible /embeddings endpoint, cosine similarity normalized to [0,1]. Reads reference from context["reference"]. 19 tests in test_scorer_embedding.py, all passing. -->
- [ ] Implement backend/engine/scorers/format.py — checks if output matches expected format. Supports: json (valid JSON parse), markdown (has headers, lists), length (within min/max token count), structure (matches a provided JSON schema). - [x] Implement backend/engine/scorers/format.py — checks if output matches expected format. Supports: json (valid JSON parse), markdown (has headers, lists), length (within min/max token count), structure (matches a provided JSON schema).
<!-- Completed: FormatScorer with 4 format checks (json, markdown, length, structure). JSON schema validation via jsonschema library with basic fallback. 38 tests in test_scorer_format.py, all passing. -->
- [ ] Implement backend/engine/scorers/keyword.py — checks for presence/absence of required keywords in output. Configurable with required_present and required_absent lists. Score = (found / required) ratio. - [ ] Implement backend/engine/scorers/keyword.py — checks for presence/absence of required keywords in output. Configurable with required_present and required_absent lists. Score = (found / required) ratio.

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@ -2,5 +2,6 @@
from engine.scorers.base import BaseScorer from engine.scorers.base import BaseScorer
from engine.scorers.embedding import EmbeddingScorer from engine.scorers.embedding import EmbeddingScorer
from engine.scorers.format import FormatScorer
__all__ = ["BaseScorer", "EmbeddingScorer"] __all__ = ["BaseScorer", "EmbeddingScorer", "FormatScorer"]

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@ -0,0 +1,173 @@
"""Format scorer — checks if LLM output matches expected formats.
Supports four format checks:
- json: valid JSON parse
- markdown: has headers and/or lists
- length: within min/max token count
- structure: matches a provided JSON schema
"""
import json
import re
from typing import Any
from engine.scorers.base import BaseScorer
class FormatScorer(BaseScorer):
"""Score outputs based on format compliance.
Args:
format_type: One of "json", "markdown", "length", "structure".
min_tokens: Minimum token count (for "length" mode).
max_tokens: Maximum token count (for "length" mode).
json_schema: JSON schema dict (for "structure" mode).
"""
VALID_FORMATS = {"json", "markdown", "length", "structure"}
def __init__(
self,
format_type: str = "json",
min_tokens: int | None = None,
max_tokens: int | None = None,
json_schema: dict | None = None,
) -> None:
if format_type not in self.VALID_FORMATS:
raise ValueError(
f"Invalid format_type '{format_type}'. "
f"Must be one of: {', '.join(sorted(self.VALID_FORMATS))}"
)
self.format_type = format_type
self.min_tokens = min_tokens
self.max_tokens = max_tokens
self.json_schema = json_schema
@property
def name(self) -> str:
return "format"
def score(self, input_data: Any, output: str, context: dict) -> float:
"""Score output based on format compliance.
Returns 1.0 if the output matches the expected format, 0.0 otherwise.
For length checks, returns a proportional score based on how close the
output is to the acceptable range.
"""
checkers = {
"json": self._check_json,
"markdown": self._check_markdown,
"length": self._check_length,
"structure": self._check_structure,
}
return checkers[self.format_type](output)
def _check_json(self, output: str) -> float:
"""Check if output is valid JSON."""
try:
json.loads(output.strip())
return 1.0
except (json.JSONDecodeError, ValueError):
return 0.0
def _check_markdown(self, output: str) -> float:
"""Check if output contains markdown formatting (headers and/or lists).
Scoring:
- 0.5 for having headers (lines starting with #)
- 0.5 for having lists (lines starting with - or * or numbered)
- 1.0 for having both
"""
score = 0.0
# Check for headers
if re.search(r"^#{1,6}\s+\S", output, re.MULTILINE):
score += 0.5
# Check for lists (unordered or ordered)
if re.search(r"^[\s]*[-*]\s+\S", output, re.MULTILINE) or re.search(
r"^[\s]*\d+[.)]\s+\S", output, re.MULTILINE
):
score += 0.5
return score
def _check_length(self, output: str) -> float:
"""Check if output length is within min/max token bounds.
Uses whitespace tokenization as an approximation.
Returns 1.0 if within bounds, scaled score if outside.
"""
token_count = len(output.split())
if self.min_tokens is None and self.max_tokens is None:
return 1.0
min_t = self.min_tokens or 0
max_t = self.max_tokens or float("inf")
if min_t <= token_count <= max_t:
return 1.0
# Score proportionally based on distance from acceptable range
if token_count < min_t:
return max(0.0, token_count / min_t) if min_t > 0 else 0.0
# token_count > max_t
if max_t > 0 and max_t != float("inf"):
# Linearly decay: at 2x max, score = 0
ratio = max_t / token_count
return max(0.0, 2 * ratio - 1.0)
return 0.0
def _check_structure(self, output: str) -> float:
"""Check if output matches a JSON schema.
Returns 1.0 if valid against the schema, 0.0 otherwise.
"""
if self.json_schema is None:
return 0.0
try:
parsed = json.loads(output.strip())
except (json.JSONDecodeError, ValueError):
return 0.0
try:
import jsonschema
jsonschema.validate(instance=parsed, schema=self.json_schema)
return 1.0
except ImportError:
# Fallback: basic type and required-field checking without jsonschema
return self._basic_schema_check(parsed, self.json_schema)
except jsonschema.ValidationError:
return 0.0
def _basic_schema_check(self, data: Any, schema: dict) -> float:
"""Basic JSON schema validation without jsonschema library.
Checks type and required fields only.
"""
schema_type = schema.get("type")
if schema_type:
type_map = {
"object": dict,
"array": list,
"string": str,
"number": (int, float),
"integer": int,
"boolean": bool,
"null": type(None),
}
expected = type_map.get(schema_type)
if expected and not isinstance(data, expected):
return 0.0
if schema_type == "object" and isinstance(data, dict):
required = schema.get("required", [])
if required:
present = sum(1 for k in required if k in data)
return present / len(required)
return 1.0

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@ -15,3 +15,4 @@ psycopg2-binary>=2.9,<3.0
aiosqlite>=0.20,<1.0 aiosqlite>=0.20,<1.0
python-multipart>=0.0.9 python-multipart>=0.0.9
jinja2>=3.1,<4.0 jinja2>=3.1,<4.0
jsonschema>=4.20,<5.0

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@ -0,0 +1,228 @@
"""Tests for the FormatScorer."""
import asyncio
import json
from typing import Any
import pytest
from engine.scorers.format import FormatScorer
class TestFormatScorerInit:
def test_valid_format_types(self):
for fmt in ("json", "markdown", "length", "structure"):
scorer = FormatScorer(format_type=fmt)
assert scorer.format_type == fmt
def test_invalid_format_type_raises(self):
with pytest.raises(ValueError, match="Invalid format_type"):
FormatScorer(format_type="xml")
def test_name_property(self):
scorer = FormatScorer()
assert scorer.name == "format"
def test_is_base_scorer(self):
from engine.scorers.base import BaseScorer
scorer = FormatScorer()
assert isinstance(scorer, BaseScorer)
class TestJsonFormat:
def test_valid_json_object(self):
scorer = FormatScorer(format_type="json")
assert scorer.score(None, '{"key": "value"}', {}) == 1.0
def test_valid_json_array(self):
scorer = FormatScorer(format_type="json")
assert scorer.score(None, '[1, 2, 3]', {}) == 1.0
def test_valid_json_string(self):
scorer = FormatScorer(format_type="json")
assert scorer.score(None, '"hello"', {}) == 1.0
def test_valid_json_number(self):
scorer = FormatScorer(format_type="json")
assert scorer.score(None, '42', {}) == 1.0
def test_valid_json_with_whitespace(self):
scorer = FormatScorer(format_type="json")
assert scorer.score(None, ' {"key": "value"} ', {}) == 1.0
def test_invalid_json(self):
scorer = FormatScorer(format_type="json")
assert scorer.score(None, "not json at all", {}) == 0.0
def test_empty_string(self):
scorer = FormatScorer(format_type="json")
assert scorer.score(None, "", {}) == 0.0
def test_partial_json(self):
scorer = FormatScorer(format_type="json")
assert scorer.score(None, '{"key":', {}) == 0.0
class TestMarkdownFormat:
def test_headers_only(self):
scorer = FormatScorer(format_type="markdown")
output = "# Title\n\nSome text here."
assert scorer.score(None, output, {}) == 0.5
def test_lists_only_unordered(self):
scorer = FormatScorer(format_type="markdown")
output = "Some text\n- item one\n- item two"
assert scorer.score(None, output, {}) == 0.5
def test_lists_only_ordered(self):
scorer = FormatScorer(format_type="markdown")
output = "Some text\n1. first\n2. second"
assert scorer.score(None, output, {}) == 0.5
def test_both_headers_and_lists(self):
scorer = FormatScorer(format_type="markdown")
output = "# Title\n\n- item one\n- item two"
assert scorer.score(None, output, {}) == 1.0
def test_no_markdown(self):
scorer = FormatScorer(format_type="markdown")
output = "Just plain text without any formatting."
assert scorer.score(None, output, {}) == 0.0
def test_nested_header_levels(self):
scorer = FormatScorer(format_type="markdown")
output = "## Subtitle\n\nContent here"
assert scorer.score(None, output, {}) == 0.5
def test_asterisk_list(self):
scorer = FormatScorer(format_type="markdown")
output = "Some text\n* item one\n* item two"
assert scorer.score(None, output, {}) == 0.5
def test_ordered_list_with_parenthesis(self):
scorer = FormatScorer(format_type="markdown")
output = "Text\n1) first\n2) second"
assert scorer.score(None, output, {}) == 0.5
class TestLengthFormat:
def test_within_range(self):
scorer = FormatScorer(format_type="length", min_tokens=5, max_tokens=20)
output = "this is a ten word sentence for the test case"
assert scorer.score(None, output, {}) == 1.0
def test_exact_min(self):
scorer = FormatScorer(format_type="length", min_tokens=3, max_tokens=10)
assert scorer.score(None, "one two three", {}) == 1.0
def test_exact_max(self):
scorer = FormatScorer(format_type="length", min_tokens=1, max_tokens=3)
assert scorer.score(None, "one two three", {}) == 1.0
def test_below_min(self):
scorer = FormatScorer(format_type="length", min_tokens=10, max_tokens=20)
output = "only five words here now"
result = scorer.score(None, output, {})
assert 0.0 < result < 1.0
assert result == 5 / 10 # 0.5
def test_above_max(self):
scorer = FormatScorer(format_type="length", min_tokens=1, max_tokens=5)
output = "one two three four five six seven eight nine ten"
result = scorer.score(None, output, {})
assert 0.0 <= result < 1.0
def test_no_bounds(self):
scorer = FormatScorer(format_type="length")
assert scorer.score(None, "any text", {}) == 1.0
def test_only_min(self):
scorer = FormatScorer(format_type="length", min_tokens=3)
assert scorer.score(None, "one two three four", {}) == 1.0
def test_only_max(self):
scorer = FormatScorer(format_type="length", max_tokens=5)
assert scorer.score(None, "one two", {}) == 1.0
def test_empty_output(self):
scorer = FormatScorer(format_type="length", min_tokens=5)
# empty string splits to [''], which has length 1
result = scorer.score(None, "", {})
assert result < 1.0
def test_zero_min(self):
scorer = FormatScorer(format_type="length", min_tokens=0, max_tokens=10)
assert scorer.score(None, "hello", {}) == 1.0
class TestStructureFormat:
def test_valid_structure(self):
schema = {
"type": "object",
"required": ["name", "age"],
"properties": {
"name": {"type": "string"},
"age": {"type": "integer"},
},
}
scorer = FormatScorer(format_type="structure", json_schema=schema)
output = json.dumps({"name": "Alice", "age": 30})
assert scorer.score(None, output, {}) == 1.0
def test_missing_required_field(self):
schema = {
"type": "object",
"required": ["name", "age"],
"properties": {
"name": {"type": "string"},
"age": {"type": "integer"},
},
}
scorer = FormatScorer(format_type="structure", json_schema=schema)
output = json.dumps({"name": "Alice"})
assert scorer.score(None, output, {}) == 0.0
def test_wrong_type(self):
schema = {"type": "array"}
scorer = FormatScorer(format_type="structure", json_schema=schema)
output = json.dumps({"key": "value"})
assert scorer.score(None, output, {}) == 0.0
def test_valid_array_structure(self):
schema = {"type": "array"}
scorer = FormatScorer(format_type="structure", json_schema=schema)
output = json.dumps([1, 2, 3])
assert scorer.score(None, output, {}) == 1.0
def test_no_schema_returns_zero(self):
scorer = FormatScorer(format_type="structure")
assert scorer.score(None, '{"key": "value"}', {}) == 0.0
def test_invalid_json_for_structure(self):
schema = {"type": "object"}
scorer = FormatScorer(format_type="structure", json_schema=schema)
assert scorer.score(None, "not json", {}) == 0.0
def test_complex_schema(self):
schema = {
"type": "object",
"required": ["results"],
"properties": {
"results": {
"type": "array",
"items": {"type": "object"},
},
},
}
scorer = FormatScorer(format_type="structure", json_schema=schema)
output = json.dumps({"results": [{"id": 1}, {"id": 2}]})
assert scorer.score(None, output, {}) == 1.0
class TestAsyncScoring:
def test_async_delegates_to_sync(self):
scorer = FormatScorer(format_type="json")
result = asyncio.get_event_loop().run_until_complete(
scorer.score_async(None, '{"valid": true}', {})
)
assert result == 1.0