0265de5816
- Formatted 103 files to comply with ruff format requirements - No code logic changes, only formatting/whitespace - Fixes CI formatting check failures
190 lines
6.6 KiB
Python
190 lines
6.6 KiB
Python
#!/usr/bin/env python3
|
|
"""
|
|
Tests for Qdrant Adaptor
|
|
"""
|
|
|
|
import json
|
|
|
|
import pytest
|
|
|
|
from skill_seekers.cli.adaptors import get_adaptor
|
|
from skill_seekers.cli.adaptors.base import SkillMetadata
|
|
|
|
|
|
class TestQdrantAdaptor:
|
|
"""Test suite for QdrantAdaptor class."""
|
|
|
|
def test_adaptor_registration(self):
|
|
"""Test that Qdrant adaptor is registered."""
|
|
adaptor = get_adaptor("qdrant")
|
|
assert adaptor.PLATFORM == "qdrant"
|
|
assert adaptor.PLATFORM_NAME == "Qdrant Vector Database"
|
|
|
|
def test_format_skill_md(self, tmp_path):
|
|
"""Test formatting SKILL.md as Qdrant points."""
|
|
# 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 Qdrant 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 Qdrant points
|
|
adaptor = get_adaptor("qdrant")
|
|
metadata = SkillMetadata(name="test_skill", description="Test skill", version="1.0.0")
|
|
|
|
points_json = adaptor.format_skill_md(skill_dir, metadata)
|
|
|
|
# Parse and validate
|
|
result = json.loads(points_json)
|
|
|
|
assert "collection_name" in result
|
|
assert "points" in result
|
|
assert "config" in result
|
|
assert len(result["points"]) == 3 # SKILL.md + 2 references
|
|
|
|
# Check point structure
|
|
for point in result["points"]:
|
|
assert "id" in point
|
|
assert "vector" in point # Will be None - user needs to add embeddings
|
|
assert "payload" in point
|
|
payload = point["payload"]
|
|
assert "content" in payload
|
|
assert payload["source"] == "test_skill"
|
|
assert payload["version"] == "1.0.0"
|
|
assert "category" in payload
|
|
assert "file" in payload
|
|
assert "type" in payload
|
|
|
|
# Check categories
|
|
categories = {point["payload"]["category"] for point in result["points"]}
|
|
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("qdrant")
|
|
output_path = adaptor.package(skill_dir, tmp_path)
|
|
|
|
# Verify output
|
|
assert output_path.exists()
|
|
assert output_path.suffix == ".json"
|
|
assert "qdrant" in output_path.name
|
|
|
|
# Verify content
|
|
with open(output_path) as f:
|
|
result = json.load(f)
|
|
|
|
assert isinstance(result, dict)
|
|
assert "points" in result
|
|
assert len(result["points"]) > 0
|
|
assert "id" in result["points"][0]
|
|
assert "payload" in result["points"][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("qdrant")
|
|
|
|
# Test directory output
|
|
output_path = adaptor.package(skill_dir, tmp_path)
|
|
assert output_path.name == "react-qdrant.json"
|
|
|
|
# Test with .zip extension (should replace)
|
|
output_path = adaptor.package(skill_dir, tmp_path / "test.zip")
|
|
assert output_path.suffix == ".json"
|
|
assert "qdrant" 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-qdrant.json"
|
|
package_path.write_text("[]")
|
|
|
|
adaptor = get_adaptor("qdrant")
|
|
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 qdrant_client" in result["message"]
|
|
|
|
def test_validate_api_key_returns_false(self):
|
|
"""Test that API key validation returns False (no API needed)."""
|
|
adaptor = get_adaptor("qdrant")
|
|
assert adaptor.validate_api_key("any-key") is False
|
|
|
|
def test_get_env_var_name_returns_empty(self):
|
|
"""Test that env var name is QDRANT_API_KEY (optional for Qdrant Cloud)."""
|
|
adaptor = get_adaptor("qdrant")
|
|
assert adaptor.get_env_var_name() == "QDRANT_API_KEY"
|
|
|
|
def test_supports_enhancement_returns_false(self):
|
|
"""Test that enhancement is not supported."""
|
|
adaptor = get_adaptor("qdrant")
|
|
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("qdrant")
|
|
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("qdrant")
|
|
metadata = SkillMetadata(name="empty_skill", description="Empty", version="1.0.0")
|
|
|
|
points_json = adaptor.format_skill_md(skill_dir, metadata)
|
|
result = json.loads(points_json)
|
|
|
|
# Should return structure with empty points array
|
|
assert "points" in result
|
|
assert result["points"] == []
|
|
|
|
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("qdrant")
|
|
metadata = SkillMetadata(name="refs_only", description="Refs only", version="1.0.0")
|
|
|
|
points_json = adaptor.format_skill_md(skill_dir, metadata)
|
|
result = json.loads(points_json)
|
|
|
|
assert len(result["points"]) == 1
|
|
assert result["points"][0]["payload"]["category"] == "test"
|
|
assert result["points"][0]["payload"]["type"] == "reference"
|
|
|
|
|
|
if __name__ == "__main__":
|
|
pytest.main([__file__, "-v"])
|