Files
skill-seekers-reference/tests/test_adaptors/test_langchain_adaptor.py
yusyus b0fd1d7ee0 fix: Add tests for 6 RAG adaptors and CLI integration for 4 features
Critical Fixes (P0):
- Add 66 new tests for langchain, llama_index, weaviate, chroma, faiss, qdrant adaptors
- Add CLI integration for streaming_ingest, incremental_updater, multilang_support, quality_metrics
- Add 'haystack' to package target choices
- Add 4 entry points to pyproject.toml

Test Coverage:
- Before: 108 tests, 14% adaptor coverage (1/7 tested)
- After: 174 tests, 100% adaptor coverage (7/7 tested)
- All 159 adaptor tests passing (11 tests per adaptor)

CLI Integration:
- skill-seekers stream - Stream large files chunk-by-chunk
- skill-seekers update - Incremental documentation updates
- skill-seekers multilang - Multi-language documentation support
- skill-seekers quality - Quality scoring for SKILL.md
- skill-seekers package --target haystack - Now selectable

Fixes QA Issues:
- Honors 'never skip tests' requirement (100% adaptor coverage)
- All features now accessible via CLI
- No more dead code - all 4 features usable

Co-Authored-By: Claude Sonnet 4.5 <noreply@anthropic.com>
2026-02-07 22:01:43 +03:00

192 lines
6.5 KiB
Python

#!/usr/bin/env python3
"""
Tests for LangChain Adaptor
"""
import json
import tempfile
from pathlib import Path
import pytest
from skill_seekers.cli.adaptors import get_adaptor
from skill_seekers.cli.adaptors.base import SkillMetadata
class TestLangChainAdaptor:
"""Test suite for LangChainAdaptor class."""
def test_adaptor_registration(self):
"""Test that LangChain adaptor is registered."""
adaptor = get_adaptor("langchain")
assert adaptor.PLATFORM == "langchain"
assert adaptor.PLATFORM_NAME == "LangChain (RAG Framework)"
def test_format_skill_md(self, tmp_path):
"""Test formatting SKILL.md as LangChain Documents."""
# Create test skill directory
skill_dir = tmp_path / "test_skill"
skill_dir.mkdir()
# Create SKILL.md
skill_md = skill_dir / "SKILL.md"
skill_md.write_text(
"# Test Skill\n\nThis is a test skill for LangChain format."
)
# Create references directory with files
refs_dir = skill_dir / "references"
refs_dir.mkdir()
(refs_dir / "getting_started.md").write_text("# Getting Started\n\nQuick start.")
(refs_dir / "api.md").write_text("# API Reference\n\nAPI docs.")
# Format as LangChain Documents
adaptor = get_adaptor("langchain")
metadata = SkillMetadata(
name="test_skill", description="Test skill", version="1.0.0"
)
documents_json = adaptor.format_skill_md(skill_dir, metadata)
# Parse and validate
documents = json.loads(documents_json)
assert len(documents) == 3 # SKILL.md + 2 references
# Check document structure
for doc in documents:
assert "page_content" in doc
assert "metadata" in doc
assert doc["metadata"]["source"] == "test_skill"
assert doc["metadata"]["version"] == "1.0.0"
assert "category" in doc["metadata"]
assert "file" in doc["metadata"]
assert "type" in doc["metadata"]
# Check categories
categories = {doc["metadata"]["category"] for doc in documents}
assert "overview" in categories # From SKILL.md
assert "getting started" in categories or "api" in categories # From references
def test_package_creates_json(self, tmp_path):
"""Test packaging skill into JSON file."""
# Create test skill
skill_dir = tmp_path / "test_skill"
skill_dir.mkdir()
(skill_dir / "SKILL.md").write_text("# Test\n\nTest content.")
# Package
adaptor = get_adaptor("langchain")
output_path = adaptor.package(skill_dir, tmp_path)
# Verify output
assert output_path.exists()
assert output_path.suffix == ".json"
assert "langchain" in output_path.name
# Verify content
with open(output_path) as f:
documents = json.load(f)
assert isinstance(documents, list)
assert len(documents) > 0
assert "page_content" in documents[0]
assert "metadata" in documents[0]
def test_package_output_filename(self, tmp_path):
"""Test package output filename generation."""
skill_dir = tmp_path / "react"
skill_dir.mkdir()
(skill_dir / "SKILL.md").write_text("# React\n\nReact docs.")
adaptor = get_adaptor("langchain")
# Test directory output
output_path = adaptor.package(skill_dir, tmp_path)
assert output_path.name == "react-langchain.json"
# Test with .zip extension (should replace)
output_path = adaptor.package(skill_dir, tmp_path / "test.zip")
assert output_path.suffix == ".json"
assert "langchain" in output_path.name
def test_upload_returns_message(self, tmp_path):
"""Test upload returns instructions (no actual upload)."""
# Create test package
package_path = tmp_path / "test-langchain.json"
package_path.write_text('[]')
adaptor = get_adaptor("langchain")
result = adaptor.upload(package_path, "fake-key")
assert result["success"] is False # No upload capability
assert result["skill_id"] is None
assert "message" in result
assert "from langchain" in result["message"]
def test_validate_api_key_returns_false(self):
"""Test that API key validation returns False (no API needed)."""
adaptor = get_adaptor("langchain")
assert adaptor.validate_api_key("any-key") is False
def test_get_env_var_name_returns_empty(self):
"""Test that env var name is empty (no API needed)."""
adaptor = get_adaptor("langchain")
assert adaptor.get_env_var_name() == ""
def test_supports_enhancement_returns_false(self):
"""Test that enhancement is not supported."""
adaptor = get_adaptor("langchain")
assert adaptor.supports_enhancement() is False
def test_enhance_returns_false(self, tmp_path):
"""Test that enhance returns False."""
skill_dir = tmp_path / "test_skill"
skill_dir.mkdir()
adaptor = get_adaptor("langchain")
result = adaptor.enhance(skill_dir, "fake-key")
assert result is False
def test_empty_skill_directory(self, tmp_path):
"""Test handling of empty skill directory."""
skill_dir = tmp_path / "empty_skill"
skill_dir.mkdir()
adaptor = get_adaptor("langchain")
metadata = SkillMetadata(
name="empty_skill", description="Empty", version="1.0.0"
)
documents_json = adaptor.format_skill_md(skill_dir, metadata)
documents = json.loads(documents_json)
# Should return empty list
assert documents == []
def test_references_only(self, tmp_path):
"""Test skill with references but no SKILL.md."""
skill_dir = tmp_path / "refs_only"
skill_dir.mkdir()
refs_dir = skill_dir / "references"
refs_dir.mkdir()
(refs_dir / "test.md").write_text("# Test\n\nTest content.")
adaptor = get_adaptor("langchain")
metadata = SkillMetadata(
name="refs_only", description="Refs only", version="1.0.0"
)
documents_json = adaptor.format_skill_md(skill_dir, metadata)
documents = json.loads(documents_json)
assert len(documents) == 1
assert documents[0]["metadata"]["category"] == "test"
assert documents[0]["metadata"]["type"] == "reference"
if __name__ == "__main__":
pytest.main([__file__, "-v"])