generated from coulomb/repo-seed
125 lines
3.4 KiB
Python
125 lines
3.4 KiB
Python
import pytest
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from repo_registry.core.models import ContentChunk, Repository
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from repo_registry.llm_extraction import (
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LLMCandidateExtractor,
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LLMExtractionError,
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create_llm_connect_adapter,
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)
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class Response:
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def __init__(self, content):
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self.content = content
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class FakeAdapter:
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def __init__(self, content):
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self.content = content
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self.last_prompt = ""
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self.last_config = object()
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def execute_prompt(self, prompt, config):
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self.last_prompt = prompt
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self.last_config = config
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return Response(self.content)
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def repository():
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return Repository(
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id=1,
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name="MailRouter",
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url="/tmp/mail-router",
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description="Routes inbound email.",
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branch="main",
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status="analyzed",
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)
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def chunk():
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return ContentChunk(
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id=1,
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repository_id=1,
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analysis_run_id=1,
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snapshot_id=1,
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path="README.md",
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kind="documentation",
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start_line=1,
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end_line=2,
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text="# MailRouter\nRoutes incoming customer email.",
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)
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def test_llm_candidate_extractor_parses_structured_response():
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adapter = FakeAdapter(
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"""
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{
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"abilities": [
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{
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"name": "Business Email Routing",
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"description": "Routes inbound customer email.",
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"source_paths": ["README.md"],
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"capabilities": [
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{
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"name": "Classify Incoming Email",
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"description": "Classify messages.",
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"inputs": ["email body"],
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"outputs": ["intent"],
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"source_paths": ["README.md"],
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"features": [
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{
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"name": "POST /classify",
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"type": "REST endpoint",
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"location": "app.py",
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"source_paths": ["app.py"]
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}
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],
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"evidence": [
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{
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"type": "documentation",
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"reference": "README.md",
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"strength": "medium",
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"source_paths": ["README.md"]
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}
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]
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}
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]
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}
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]
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}
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"""
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)
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extractor = LLMCandidateExtractor(adapter)
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abilities = extractor.extract(repository(), [chunk()])
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assert "Return strict JSON only" in adapter.last_prompt
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assert "README.md:1-2" in adapter.last_prompt
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assert abilities[0].name == "Business Email Routing"
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assert abilities[0].capabilities[0].features[0].name == "POST /classify"
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assert abilities[0].capabilities[0].evidence[0].reference == "README.md"
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def test_llm_candidate_extractor_accepts_fenced_json():
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adapter = FakeAdapter(
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'```json\n{"abilities": [{"name": "A", "capabilities": []}]}\n```'
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)
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abilities = LLMCandidateExtractor(adapter).extract(repository(), [])
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assert abilities[0].name == "A"
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def test_llm_candidate_extractor_rejects_invalid_json():
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adapter = FakeAdapter("not json")
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with pytest.raises(LLMExtractionError):
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LLMCandidateExtractor(adapter).extract(repository(), [])
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def test_llm_connect_factory_reports_missing_dependency():
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with pytest.raises(LLMExtractionError) as exc:
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create_llm_connect_adapter("mock")
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assert "llm-connect is not installed" in str(exc.value)
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