058362b87f
Initial skeleton for the deterministic compound-AI pipeline that turns `tolkien deploy <name>` into a valinor scaffold. v0 wires one classifier (`db_kind`) end-to-end against the Ollama-on-radagast backend so we can iterate prompts with confidence before adding the rest. - pyproject.toml: uv project, Python 3.13, httpx/pydantic/typer/pyyaml. - src/tolkien/llm.py: single-turn /api/chat wrapper. JSON-mode + temp 0 + 30m keep-alive. Pydantic schema validation on parse. - src/tolkien/cli.py: `tolkien classify db-kind --doc <file>` runs the classifier and prints JSON. `tolkien deploy <name>` is stubbed. - src/tolkien/prompts/db_kind.md: tight system prompt with 1-shot example and explicit "return ONLY JSON" guard. - src/tolkien/schemas.py: DbKindResult pydantic model. - eval/cases/mealie.yml + run_eval.py: regression harness. Currently one case (mealie); failures print field-level diffs. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
71 lines
2.0 KiB
Python
71 lines
2.0 KiB
Python
"""Run all eval cases and report which pass/fail.
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Each case has a `name`, an `input` string, and an `expected` dict. The current
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v0 only exercises the `db_kind` classifier. As more classifiers come online,
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each case will grow expected sections for them too.
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Run from the repo root:
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uv run python eval/run_eval.py
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"""
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from __future__ import annotations
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import sys
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from pathlib import Path
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import yaml
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from tolkien.llm import classify
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from tolkien.schemas import DbKindResult
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CASES_DIR = Path(__file__).parent / "cases"
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def _diff_fields(expected: dict, actual: dict) -> list[str]:
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"""Return human-readable lines describing field-level mismatches."""
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diffs: list[str] = []
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for key, want in expected.items():
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got = actual.get(key)
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if isinstance(want, list) and isinstance(got, list):
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want_set, got_set = set(want), set(got)
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missing = want_set - got_set
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extra = got_set - want_set
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if missing or extra:
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diffs.append(f" {key}: missing={sorted(missing)} extra={sorted(extra)}")
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elif want != got:
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diffs.append(f" {key}: want={want!r} got={got!r}")
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return diffs
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def main() -> int:
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cases = sorted(CASES_DIR.glob("*.yml"))
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if not cases:
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print(f"No cases found in {CASES_DIR}", file=sys.stderr)
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return 2
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failures = 0
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for case_path in cases:
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case = yaml.safe_load(case_path.read_text())
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name = case["name"]
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result = classify("db_kind", case["input"], DbKindResult)
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actual = result.model_dump()
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diffs = _diff_fields(case["expected"], actual)
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if diffs:
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failures += 1
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print(f"FAIL {name}")
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for line in diffs:
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print(line)
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else:
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print(f"PASS {name}")
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if failures:
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print(f"\n{failures}/{len(cases)} cases failed.", file=sys.stderr)
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return 1
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print(f"\nAll {len(cases)} cases passed.")
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return 0
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if __name__ == "__main__":
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sys.exit(main())
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