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ThothII/harness/tests/test_corpus_pipeline.py
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312 lines
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Python

import pytest
from tht.corpus.chunk import ChunkPolicy
from tht.corpus.pipeline import CorpusPipeline, PipelineError
from tht.corpus.store import CorpusStore
from tht.ports.evidence import AcquiredDocument, SourceObject
from tht.ports.vector import VectorCapabilities
class Source:
def __init__(self, documents):
self.documents = documents
self.acquire_calls = []
def discover(self):
return [item[0] for item in self.documents]
def acquire(self, item):
self.acquire_calls.append(item.source_id)
payload = next(payload for source, payload in self.documents if source.source_id == item.source_id)
if isinstance(payload, Exception):
raise payload
return AcquiredDocument(source=item, content=payload.encode())
class Embedder:
def __init__(self, dim=3, fail=False):
self.dim = dim
self.fail = fail
self.calls = []
def embed_documents(self, texts):
self.calls.extend(texts)
if self.fail:
raise RuntimeError("embed failed")
return [[float(i) for i in range(self.dim)] for _ in texts]
class Vectors:
capabilities = VectorCapabilities(search=True, existing_hashes=True, upsert=True)
def __init__(self, fail=False):
self.fail = fail
self.records = []
def upsert(self, collection, records):
self.records.extend(records[:1] if self.fail else records)
if self.fail:
raise RuntimeError("partial write")
return len(records)
def existing_hashes(self, collection, kinds):
return {
value.record.id: value.content_hash for value in self.records
}
def delete_generation(self, collection, generation):
self.records = [
value for value in self.records
if value.record.metadata["vector_generation"] != generation
]
return 0
def item(name, fingerprint):
return SourceObject(
source_id=f"fs:{name}", uri=f"file:///safe/{name}.md", fingerprint=f"sha256:{fingerprint}"
)
def pipeline(tmp_path, source, *, embedder=None, vectors=None, model="model-a", policy=None):
return CorpusPipeline(
store=CorpusStore(tmp_path / "corpus"), sources=[source],
embedder=embedder or Embedder(), vector_store=vectors or Vectors(),
embedding_model=model, embedding_dimensions=3,
chunk_policy=policy or ChunkPolicy(version="chunk-v1", max_chars=100),
pipeline_version="evidence-v1",
)
def test_unchanged_documents_skip_acquire_normalize_chunk_and_embed(tmp_path):
one = item("one", "a")
first_source = Source([(one, "hello")])
first = pipeline(tmp_path, first_source)
first.run()
second_source = Source([(one, "ignored")])
second_embedder = Embedder()
result = pipeline(tmp_path, second_source, embedder=second_embedder).run()
assert result.unchanged == ("fs:one",)
assert second_source.acquire_calls == []
assert second_embedder.calls == []
def test_removed_documents_are_marked_and_absent_from_new_manifest(tmp_path):
one, two = item("one", "a"), item("two", "b")
pipeline(tmp_path, Source([(one, "one"), (two, "two")])).run()
result = pipeline(tmp_path, Source([(one, "one")])).run()
assert result.removed == ("fs:two",)
assert {doc.source_id for doc in result.manifest.documents} == {"fs:one"}
def test_model_or_chunk_policy_change_forces_full_rebuild(tmp_path):
one = item("one", "a")
pipeline(tmp_path, Source([(one, "hello")])).run()
source = Source([(one, "hello")])
changed = pipeline(tmp_path, source, model="model-b").run()
assert changed.changed == ("fs:one",)
assert source.acquire_calls == ["fs:one"]
def test_partial_vector_failure_never_changes_active_or_exposes_generation(tmp_path):
one = item("one", "a")
good = pipeline(tmp_path, Source([(one, "old")]))
old = good.run().generation
changed = item("one", "b")
vectors = Vectors(fail=True)
broken = pipeline(tmp_path, Source([(changed, "new")]), vectors=vectors)
with pytest.raises(PipelineError):
broken.run()
assert broken.store.active_generation() == old
assert vectors.records[0].record.metadata["vector_generation"] != old
def test_dimension_mismatch_fails_before_vector_write_and_publish(tmp_path):
one = item("one", "a")
vectors = Vectors()
candidate = pipeline(tmp_path, Source([(one, "hello")]), embedder=Embedder(dim=2), vectors=vectors)
with pytest.raises(PipelineError, match="dimension"):
candidate.run()
assert vectors.records == []
assert candidate.store.active_generation() is None
def test_dry_run_and_failed_acquire_never_change_active(tmp_path):
one = item("one", "a")
active = pipeline(tmp_path, Source([(one, "old")])).run().generation
changed = item("one", "b")
dry = pipeline(tmp_path, Source([(changed, "new")])).run(dry_run=True)
assert dry.published is False
assert dry.generation is None
assert dry.manifest.documents[0].content == "old"
with pytest.raises(PipelineError):
pipeline(tmp_path, Source([(changed, RuntimeError("boom"))])).run()
assert CorpusStore(tmp_path / "corpus").active_generation() == active
def test_job_pipeline_uses_ordered_plan_and_returns_run_id(tmp_path):
one = item("one", "a")
candidate = pipeline(tmp_path, Source([(one, "hello")]))
result = candidate.run_as_job(
workspace_id="demo", workspace_root=tmp_path,
config_fingerprint="sha256:" + "1" * 64,
input_fingerprint="sha256:" + "2" * 64,
)
assert result.status == "succeeded"
assert result.run_id and len(result.run_id) == 32
checkpoint = tmp_path / ".tht-jobs" / "evidence" / "runs" / result.run_id / "checkpoint.json"
payload = __import__("json").loads(checkpoint.read_text())
assert [stage["name"] for stage in payload["stages"]] == [
"discover", "acquire_normalize_chunk", "embed", "vector_upsert",
"stage_validate", "publish", "retention_cleanup",
]
def test_job_pipeline_dry_run_only_discovers_and_reports_changes(tmp_path):
one = item("one", "a")
source = Source([(one, "hello")])
embedder = Embedder()
vectors = Vectors()
result = pipeline(tmp_path, source, embedder=embedder, vectors=vectors).run_as_job(
workspace_id="demo", workspace_root=tmp_path,
config_fingerprint="sha256:" + "1" * 64,
input_fingerprint="sha256:" + "2" * 64,
dry_run=True,
)
assert result.changed == ("fs:one",)
assert source.acquire_calls == []
assert embedder.calls == []
assert vectors.records == []
assert result.generation is None and result.published is False
@pytest.mark.parametrize("crash_stage", [
"discover", "acquire_normalize_chunk", "embed", "vector_upsert",
"stage_validate", "publish", "retention_cleanup",
])
def test_job_pipeline_crash_after_each_stage_resumes_without_duplicate_effects(tmp_path, crash_stage):
one = item("one", "a")
source = Source([(one, "hello")])
embedder = Embedder()
vectors = Vectors()
candidate = pipeline(tmp_path, source, embedder=embedder, vectors=vectors)
class Crash(BaseException):
pass
def fault(_context, stage):
if stage == crash_stage:
raise Crash()
with pytest.raises(Crash):
candidate.run_as_job(
workspace_id="demo", workspace_root=tmp_path,
config_fingerprint="sha256:" + "1" * 64,
input_fingerprint="sha256:" + "2" * 64,
after_stage_return=fault,
)
runs = tmp_path / ".tht-jobs" / "evidence" / "runs"
crashed = next(runs.iterdir()).name
result = candidate.run_as_job(
workspace_id="demo", workspace_root=tmp_path,
config_fingerprint="sha256:" + "1" * 64,
input_fingerprint="sha256:" + "2" * 64,
resume_run_id=crashed,
)
assert result.status == "succeeded"
assert source.acquire_calls == ["fs:one"]
assert len(embedder.calls) == 1
assert len(vectors.records) == 1
def test_job_pipeline_raw_upsert_failure_compensates_and_resumes_with_new_generation(tmp_path):
one = item("one", "a")
vectors = Vectors(fail=True)
candidate = pipeline(tmp_path, Source([(one, "hello")]), vectors=vectors)
first = candidate.run_as_job(
workspace_id="demo", workspace_root=tmp_path,
config_fingerprint="sha256:" + "1" * 64,
input_fingerprint="sha256:" + "2" * 64,
)
assert first.status == "failed"
assert vectors.records == []
old_generation = first.generation
vectors.fail = False
resumed = candidate.run_as_job(
workspace_id="demo", workspace_root=tmp_path,
config_fingerprint="sha256:" + "1" * 64,
input_fingerprint="sha256:" + "2" * 64,
resume_run_id=first.run_id,
)
assert resumed.status == "succeeded", resumed
assert resumed.generation != old_generation
assert candidate.store.active_generation() == resumed.generation
def test_job_pipeline_raw_stage_failure_compensates_vectors_and_resumes(tmp_path, monkeypatch):
one = item("one", "a")
vectors = Vectors()
candidate = pipeline(tmp_path, Source([(one, "hello")]), vectors=vectors)
real_stage = candidate.store.stage
calls = 0
def fail_once(*args, **kwargs):
nonlocal calls
calls += 1
if calls == 1:
raise OSError("raw stage failure")
return real_stage(*args, **kwargs)
monkeypatch.setattr(candidate.store, "stage", fail_once)
first = candidate.run_as_job(
workspace_id="demo", workspace_root=tmp_path,
config_fingerprint="sha256:" + "1" * 64,
input_fingerprint="sha256:" + "2" * 64,
)
assert first.status == "failed" and vectors.records == []
resumed = candidate.run_as_job(
workspace_id="demo", workspace_root=tmp_path,
config_fingerprint="sha256:" + "1" * 64,
input_fingerprint="sha256:" + "2" * 64,
resume_run_id=first.run_id,
)
assert resumed.status == "succeeded", resumed
@pytest.mark.parametrize("stage,filename", [
("discover", "plan.json"),
("acquire_normalize_chunk", "manifest.json"),
("embed", "embeddings.json"),
])
@pytest.mark.parametrize("mutation", ["missing", "tampered"])
def test_job_pipeline_rejects_corrupt_required_artifacts_before_resume(
tmp_path, stage, filename, mutation,
):
one = item("one", "a")
candidate = pipeline(tmp_path, Source([(one, "hello")]))
class Crash(BaseException):
pass
with pytest.raises(Crash):
candidate.run_as_job(
workspace_id="demo", workspace_root=tmp_path,
config_fingerprint="sha256:" + "1" * 64,
input_fingerprint="sha256:" + "2" * 64,
after_stage_return=lambda _context, name: (
(_ for _ in ()).throw(Crash()) if name == stage else None
),
)
runs = tmp_path / ".tht-jobs" / "evidence" / "runs"
crashed = next(runs.iterdir())
target = crashed / "artifacts" / filename
target.unlink() if mutation == "missing" else target.write_text("tampered")
from tht.jobs.runner import CorruptCheckpointError
with pytest.raises(CorruptCheckpointError, match="artifact"):
candidate.run_as_job(
workspace_id="demo", workspace_root=tmp_path,
config_fingerprint="sha256:" + "1" * 64,
input_fingerprint="sha256:" + "2" * 64,
resume_run_id=crashed.name,
)