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ThothII/harness/tht/evidence/canonical.py
T

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Python

"""Typed, reviewable Evidence units stored in the workspace repository."""
from __future__ import annotations
import re
from pathlib import Path, PurePosixPath
from typing import Literal
import sqlglot
import yaml
from pydantic import AnyHttpUrl, BaseModel, ConfigDict, Field, field_validator, model_validator
from sqlglot import exp
from tht.evidence.contracts import validate_canonical_uri
class StrictModel(BaseModel):
"""Reject undeclared fields in the repository's canonical format."""
model_config = ConfigDict(extra="forbid")
EvidenceKind = Literal[
"glossary",
"domain",
"enum",
"example",
"mapping",
"normalization",
"formula",
"reference",
]
EvidencePurpose = Literal[
"disambiguation",
"rewriting",
"schema_linking",
"sql_generation",
]
_IDENTIFIER = r"[A-Za-z_][A-Za-z0-9_$]*"
_TABLE_IDENTIFIER = re.compile(rf"^{_IDENTIFIER}\.{_IDENTIFIER}$")
_COLUMN_IDENTIFIER = re.compile(rf"^{_IDENTIFIER}\.{_IDENTIFIER}\.{_IDENTIFIER}$")
MAX_CURATED_FILE_BYTES = 10 * 1024 * 1024
class EvidenceScope(StrictModel):
concepts: tuple[str, ...] = ()
tables: tuple[str, ...] = ()
columns: tuple[str, ...] = ()
@field_validator("tables")
@classmethod
def _validate_tables(cls, value: tuple[str, ...]) -> tuple[str, ...]:
return _validate_identifiers(value, _TABLE_IDENTIFIER, "tables")
@field_validator("columns")
@classmethod
def _validate_columns(cls, value: tuple[str, ...]) -> tuple[str, ...]:
return _validate_identifiers(value, _COLUMN_IDENTIFIER, "columns")
class EvidenceProvenance(StrictModel):
model_config = ConfigDict(extra="forbid", frozen=True)
source_file: str
source_sha256: str
supporting_excerpts: tuple[str, ...]
@field_validator("source_file")
@classmethod
def _validate_source_file(cls, value: str) -> str:
return validate_source_file(value)
@field_validator("source_sha256")
@classmethod
def _validate_sha256(cls, value: str) -> str:
if not re.fullmatch(r"sha256:[0-9a-f]{64}", value):
raise ValueError("source_sha256 must be a sha256 digest")
return value
@field_validator("supporting_excerpts")
@classmethod
def _validate_excerpts(cls, value: tuple[str, ...]) -> tuple[str, ...]:
if not 1 <= len(value) <= 5:
raise ValueError("supporting_excerpts must contain one to five items")
if any(not excerpt.strip() or len(excerpt) > 1000 for excerpt in value):
raise ValueError("supporting excerpts must be nonempty and at most 1000 characters")
return value
class ReviewItem(StrictModel):
code: str
message: str
field: str | None = None
class FormulaPayload(StrictModel):
concept: str
columns: tuple[str, ...]
sql: str
@field_validator("columns")
@classmethod
def _validate_columns(cls, value: tuple[str, ...]) -> tuple[str, ...]:
return _validate_identifiers(value, _COLUMN_IDENTIFIER, "columns")
@field_validator("sql")
@classmethod
def _validate_expression(cls, value: str) -> str:
try:
statements = [statement for statement in sqlglot.parse(value, read="postgres") if statement]
except sqlglot.errors.ParseError as error:
raise ValueError("formula.sql must be valid PostgreSQL") from error
if len(statements) != 1:
raise ValueError("formula.sql must contain exactly one expression")
expression = statements[0]
if expression.find(exp.Select) is not None or expression.find(exp.With) is not None:
raise ValueError("formula.sql must not contain a query")
if any(
expression.find(statement_type) is not None
for statement_type in (
exp.Insert,
exp.Update,
exp.Delete,
exp.Create,
exp.Drop,
exp.Alter,
exp.Merge,
exp.TruncateTable,
exp.Grant,
exp.Revoke,
exp.Command,
exp.Values,
exp.Set,
exp.Table,
)
):
raise ValueError("formula.sql must not contain DDL or DML")
return value
class ReferencePayload(StrictModel):
url: AnyHttpUrl
label: str
description: str
@field_validator("url")
@classmethod
def _reject_credentials(cls, value: AnyHttpUrl) -> AnyHttpUrl:
validate_canonical_uri(str(value))
return value
class GlossaryPayload(StrictModel):
definition: str
synonyms: tuple[str, ...] = ()
variants: tuple[str, ...] = ()
class DomainPayload(StrictModel):
rule: str
class EnumPayload(StrictModel):
column: str
values: dict[str, str]
@field_validator("column")
@classmethod
def _validate_column(cls, value: str) -> str:
_validate_identifiers((value,), _COLUMN_IDENTIFIER, "column")
return value
class ExamplePayload(StrictModel):
question: str
interpretation: str
class MappingPayload(StrictModel):
concept: str
tables: tuple[str, ...]
columns: tuple[str, ...]
@field_validator("tables")
@classmethod
def _validate_tables(cls, value: tuple[str, ...]) -> tuple[str, ...]:
return _validate_identifiers(value, _TABLE_IDENTIFIER, "tables")
@field_validator("columns")
@classmethod
def _validate_columns(cls, value: tuple[str, ...]) -> tuple[str, ...]:
return _validate_identifiers(value, _COLUMN_IDENTIFIER, "columns")
class NormalizationPayload(StrictModel):
input: str
output: str
rule: str
EvidencePayload = (
GlossaryPayload
| DomainPayload
| EnumPayload
| ExamplePayload
| MappingPayload
| NormalizationPayload
| FormulaPayload
| ReferencePayload
)
_PAYLOAD_TYPE_BY_KIND = {
"glossary": GlossaryPayload,
"domain": DomainPayload,
"enum": EnumPayload,
"example": ExamplePayload,
"mapping": MappingPayload,
"normalization": NormalizationPayload,
"formula": FormulaPayload,
"reference": ReferencePayload,
}
_EVIDENCE_ID = re.compile(r"^evidence:[a-z0-9]+(?:-[a-z0-9]+)*$")
class CuratedEvidence(StrictModel):
schema_version: Literal[1]
id: str
title: str
kind: EvidenceKind
purposes: tuple[EvidencePurpose, ...]
applies_to: EvidenceScope = Field(default_factory=EvidenceScope)
language: str
provenance: EvidenceProvenance
review_items: tuple[ReviewItem, ...] = ()
payload: EvidencePayload
@model_validator(mode="after")
def _validate_kind_payload(self) -> CuratedEvidence:
if not is_evidence_id(self.id):
raise ValueError("id must use the evidence:<slug> form")
expected = _PAYLOAD_TYPE_BY_KIND.get(self.kind)
if expected is not None and not isinstance(self.payload, expected):
raise ValueError(f"{self.kind} requires its typed payload")
return self
def parse_curated_markdown(text: str, *, path: Path | None = None) -> CuratedEvidence:
"""Parse the canonical frontmatter representation of one Curated Evidence unit."""
if not text.startswith("---\n"):
raise ValueError("curated evidence requires YAML frontmatter")
try:
_, frontmatter, body = text.split("---\n", 2)
except ValueError as error:
raise ValueError("curated evidence frontmatter is malformed") from error
raw = yaml.safe_load(frontmatter)
try:
data = dict(raw)
except (TypeError, ValueError) as error:
raise ValueError("curated evidence frontmatter must be a mapping") from error
if body.strip():
raise ValueError("curated evidence must not contain an ignored body")
kind = data.get("kind")
if "payload" not in data and kind in _PAYLOAD_TYPE_BY_KIND:
data["payload"] = data.pop(kind, None)
evidence = CuratedEvidence.model_validate(data)
if path is not None:
_validate_kind_directory(path, evidence.kind)
return evidence
def dump_curated_markdown(value: CuratedEvidence) -> str:
"""Render canonical frontmatter with a human-readable kind-specific payload key."""
data = value.model_dump(mode="json", exclude={"payload"})
data[value.kind] = value.payload.model_dump(mode="json")
frontmatter = yaml.safe_dump(data, allow_unicode=True, sort_keys=False)
return f"---\n{frontmatter}---\n"
def load_curated_tree(root: Path) -> list[CuratedEvidence]:
"""Load canonical Evidence units in stable path order from a curated root."""
if not root.is_dir():
return []
documents: list[CuratedEvidence] = []
for path in sorted(root.rglob("*.md")):
if path.name.upper().startswith("README"):
continue
if path.stat().st_size > MAX_CURATED_FILE_BYTES:
raise ValueError("curated evidence exceeds the size limit")
try:
text = path.read_text(encoding="utf-8")
except UnicodeDecodeError as error:
raise ValueError("curated evidence must be UTF-8") from error
documents.append(parse_curated_markdown(text, path=path))
return documents
def _validate_kind_directory(path: Path, kind: EvidenceKind) -> None:
parts = path.parts
try:
curated_index = parts.index("curated")
except ValueError:
return
if len(parts) <= curated_index + 1 or parts[curated_index + 1] != kind:
raise ValueError("curated evidence kind must match its directory")
def _validate_identifiers(
values: tuple[str, ...], pattern: re.Pattern[str], field: str,
) -> tuple[str, ...]:
if any(pattern.fullmatch(value) is None for value in values):
raise ValueError(f"{field} must use canonical schema identifiers")
return values
def validate_source_file(value: str) -> str:
"""Validate a repository-relative, credential-free Source Evidence path."""
path = PurePosixPath(value)
if (
path.is_absolute()
or ".." in path.parts
or not path.parts
or path.parts[0] != "source"
or not value.endswith((".md", ".txt", ".sql.md"))
):
raise ValueError("source_file must be a supported path below source/")
return value
def is_evidence_id(value: str) -> bool:
"""Whether a value uses the stable public Evidence identifier format."""
return _EVIDENCE_ID.fullmatch(value) is not None