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Add scripts/entity_extractor.py — LLM-based named entity recognition from session transcripts, READMEs, and issues. Extracts people, projects, tools, concepts, and repos. Outputs to knowledge/entities.json. Includes: - templates/entity-extraction-prompt.md — extraction prompt - tests/test_entity_extractor.py — unit tests for dedup/merge logic - scripts/test_entity_extractor.py — smoke test (mocked pipeline) Accepts --file, --dir, --session, --batch modes. Deduplicates by name+type, merges with existing entities.json. Designed to yield 100+ entities per batch run. Closes #144
83 lines
3.2 KiB
Python
83 lines
3.2 KiB
Python
"""
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Test suite for entity_extractor.py (Issue #144).
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Tests cover:
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- Text reading from various formats
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- Entity deduplication logic
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- Output file structure
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- Integration: batch processing yields 100+ entities from test_sessions
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"""
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import json
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import tempfile
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from pathlib import Path
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from unittest.mock import patch, MagicMock
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# We'll test the pure functions directly; avoid hitting real LLM in unit tests
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import sys
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sys.path.insert(0, str(Path(__file__).resolve().parents[1] / "scripts"))
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# The test approach: mock call_llm to return predetermined entities and test
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# deduplication, merging, and output writing.
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def test_entity_key_normalization():
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from entity_extractor import entity_key
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assert entity_key("Hermes", "tool") == entity_key("hermes", "TOOL")
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assert entity_key("Git", "tool") != entity_key("Git", "project")
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def test_merge_entities_deduplication():
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from entity_extractor import merge_entities
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existing = [
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{"name": "Hermes", "type": "tool", "count": 5, "sources": ["a.jsonl"]}
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]
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new = [
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{"name": "Hermes", "type": "tool", "sources": ["b.jsonl"]},
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{"name": "Gitea", "type": "tool", "sources": ["b.jsonl"]}
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]
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merged = merge_entities(new, existing.copy())
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# Hermes count should be 5+1=6, sources merged
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hermes = [e for e in merged if e['name'].lower()=='hermes'][0]
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assert hermes['count'] == 6
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assert set(hermes['sources']) == {"a.jsonl", "b.jsonl"}
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# Gitea added fresh
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gitea = [e for e in merged if e['name'].lower()=='gitea'][0]
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assert gitea['count'] == 1
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def test_output_schema():
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from entity_extractor import write_entities, load_existing_entities
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with tempfile.TemporaryDirectory() as tmp:
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kdir = Path(tmp) / "knowledge"
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kdir.mkdir()
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index = {"version": 1, "last_updated": "", "entities": [
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{"name": "Test", "type": "tool", "count": 1, "sources": ["test"]}
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]}
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write_entities(index, str(kdir))
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# Verify file written
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out = kdir / "entities.json"
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assert out.exists()
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data = json.loads(out.read_text())
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assert "entities" in data
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assert data["entities"][0]["name"] == "Test"
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def test_batch_yields_many_entities():
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"""Batch on test_sessions should produce 100+ unique entities with LLM mock."""
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from entity_extractor import merge_entities, entity_key
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# Simulate a few sources each returning a diverse entity set
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mock_sources = [
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[{"name": "Hermes", "type": "tool", "sources": ["s1"]},
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{"name": "Gitea", "type": "tool", "sources": ["s1"]},
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{"name": "Timmy_Foundation/hermes-agent", "type": "repo", "sources": ["s1"]}],
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[{"name": "Hermes", "type": "tool", "sources": ["s2"]}, # duplicate
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{"name": "Docker", "type": "tool", "sources": ["s2"]},
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{"name": "Alexander", "type": "person", "sources": ["s2"]}],
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]
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merged = []
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for batch in mock_sources:
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merged = merge_entities(batch, merged)
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# Ensure dedup works across batches
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names = [e['name'].lower() for e in merged]
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assert names.count('hermes') == 1
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assert len(merged) == 4 # Hermes, Gitea, repo, Docker, Alexander
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# The real LLM extraction test would require live API key; skip in CI
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