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chore: import upstream snapshot with attribution
2026-07-13 12:46:28 +08:00

238 lines
9.7 KiB
Python

#!/usr/bin/env python3
"""
Tests for OpenAI adaptor
"""
import sys
import tempfile
import unittest
import zipfile
from pathlib import Path
from unittest.mock import MagicMock, patch
from skill_seekers.cli.adaptors import get_adaptor
from skill_seekers.cli.adaptors.base import SkillMetadata
class TestOpenAIAdaptor(unittest.TestCase):
"""Test OpenAI adaptor functionality"""
def setUp(self):
"""Set up test adaptor"""
self.adaptor = get_adaptor("openai")
def test_platform_info(self):
"""Test platform identifiers"""
self.assertEqual(self.adaptor.PLATFORM, "openai")
self.assertEqual(self.adaptor.PLATFORM_NAME, "OpenAI ChatGPT")
self.assertIsNotNone(self.adaptor.DEFAULT_API_ENDPOINT)
def test_validate_api_key_valid(self):
"""Test valid OpenAI API keys"""
self.assertTrue(self.adaptor.validate_api_key("sk-proj-abc123"))
self.assertTrue(self.adaptor.validate_api_key("sk-abc123"))
self.assertTrue(self.adaptor.validate_api_key(" sk-test ")) # with whitespace
def test_validate_api_key_invalid(self):
"""Test invalid API keys"""
self.assertFalse(self.adaptor.validate_api_key("AIzaSyABC123")) # Gemini key
# Note: Can't distinguish Claude keys (sk-ant-*) from OpenAI keys (sk-*)
self.assertFalse(self.adaptor.validate_api_key("invalid"))
self.assertFalse(self.adaptor.validate_api_key(""))
def test_get_env_var_name(self):
"""Test environment variable name"""
self.assertEqual(self.adaptor.get_env_var_name(), "OPENAI_API_KEY")
def test_supports_enhancement(self):
"""Test enhancement support"""
self.assertTrue(self.adaptor.supports_enhancement())
def test_format_skill_md_no_frontmatter(self):
"""Test that OpenAI format has no YAML frontmatter"""
with tempfile.TemporaryDirectory() as temp_dir:
skill_dir = Path(temp_dir)
# Create minimal skill structure
(skill_dir / "references").mkdir()
(skill_dir / "references" / "test.md").write_text("# Test content")
metadata = SkillMetadata(name="test-skill", description="Test skill description")
formatted = self.adaptor.format_skill_md(skill_dir, metadata)
# Should NOT start with YAML frontmatter
self.assertFalse(formatted.startswith("---"))
# Should contain assistant-style instructions
self.assertIn("You are an expert assistant", formatted)
self.assertIn("test-skill", formatted)
self.assertIn("Test skill description", formatted)
def test_package_creates_zip(self):
"""Test that package creates ZIP file with correct structure"""
with tempfile.TemporaryDirectory() as temp_dir:
skill_dir = Path(temp_dir) / "test-skill"
skill_dir.mkdir()
# Create minimal skill structure
(skill_dir / "SKILL.md").write_text("You are an expert assistant")
(skill_dir / "references").mkdir()
(skill_dir / "references" / "test.md").write_text("# Reference")
output_dir = Path(temp_dir) / "output"
output_dir.mkdir()
# Package skill
package_path = self.adaptor.package(skill_dir, output_dir)
# Verify package was created
self.assertTrue(package_path.exists())
self.assertTrue(str(package_path).endswith(".zip"))
self.assertIn("openai", package_path.name)
# Verify package contents
with zipfile.ZipFile(package_path, "r") as zf:
names = zf.namelist()
self.assertIn("assistant_instructions.txt", names)
self.assertIn("openai_metadata.json", names)
# Should have vector store files
self.assertTrue(any("vector_store_files" in name for name in names))
def test_upload_missing_library(self):
"""Test upload when openai library is not installed"""
with tempfile.NamedTemporaryFile(suffix=".zip") as tmp:
# Simulate missing library by patching sys.modules
with patch.dict(sys.modules, {"openai": None}):
result = self.adaptor.upload(Path(tmp.name), "sk-test123")
self.assertFalse(result["success"])
self.assertIn("openai", result["message"])
self.assertIn("not installed", result["message"])
def test_upload_invalid_file(self):
"""Test upload with invalid file"""
result = self.adaptor.upload(Path("/nonexistent/file.zip"), "sk-test123")
self.assertFalse(result["success"])
self.assertIn("not found", result["message"].lower())
def test_upload_wrong_format(self):
"""Test upload with wrong file format"""
with tempfile.NamedTemporaryFile(suffix=".tar.gz") as tmp:
result = self.adaptor.upload(Path(tmp.name), "sk-test123")
self.assertFalse(result["success"])
self.assertIn("not a zip", result["message"].lower())
def test_upload_success(self):
"""Test successful upload to OpenAI - skipped (needs real API for integration test)"""
pass
def test_upload_attaches_references_via_file_batches(self):
"""Regression: batch attach must use vector_stores.file_batches.create.
The old code called vs_api.files.create_batch, which does not exist on
the OpenAI SDK (neither client.vector_stores nor client.beta.vector_stores),
so every upload with reference files raised AttributeError (swallowed
into a failure dict). The spec'd mocks below mirror the real SDK
surface, so calling the nonexistent method fails this test.
"""
try:
from openai.resources.vector_stores import FileBatches, Files, VectorStores
except ImportError:
self.skipTest("openai library not installed")
with tempfile.TemporaryDirectory() as temp_dir:
skill_dir = Path(temp_dir) / "test-skill"
skill_dir.mkdir()
(skill_dir / "SKILL.md").write_text("You are an expert assistant")
refs_dir = skill_dir / "references"
refs_dir.mkdir()
(refs_dir / "guide.md").write_text("# User Guide")
(refs_dir / "api.md").write_text("# API Reference")
output_dir = Path(temp_dir) / "output"
output_dir.mkdir()
package_path = self.adaptor.package(skill_dir, output_dir)
mock_client = MagicMock()
mock_client.vector_stores = MagicMock(spec=VectorStores)
mock_client.vector_stores.files = MagicMock(spec=Files)
mock_client.vector_stores.file_batches = MagicMock(spec=FileBatches)
mock_client.vector_stores.create.return_value = MagicMock(id="vs_123")
mock_client.files.create.side_effect = [
MagicMock(id="file_1"),
MagicMock(id="file_2"),
]
mock_client.beta.assistants.create.return_value = MagicMock(id="asst_123")
with patch("openai.OpenAI", return_value=mock_client):
result = self.adaptor.upload(package_path, "sk-test123")
self.assertTrue(result["success"], msg=result["message"])
self.assertEqual(result["skill_id"], "asst_123")
self.assertEqual(mock_client.files.create.call_count, 2)
mock_client.vector_stores.file_batches.create.assert_called_once_with(
vector_store_id="vs_123", file_ids=["file_1", "file_2"]
)
def test_enhance_success(self):
"""Test successful enhancement - skipped (needs real API for integration test)"""
pass
def test_enhance_missing_library(self):
"""Test enhance when openai library is not installed"""
with tempfile.TemporaryDirectory() as temp_dir:
skill_dir = Path(temp_dir)
refs_dir = skill_dir / "references"
refs_dir.mkdir()
(refs_dir / "test.md").write_text("Test")
# Don't mock the module - it won't be available
success = self.adaptor.enhance(skill_dir, "sk-test123")
self.assertFalse(success)
def test_package_includes_instructions(self):
"""Test that packaged ZIP includes assistant instructions"""
with tempfile.TemporaryDirectory() as temp_dir:
skill_dir = Path(temp_dir) / "test-skill"
skill_dir.mkdir()
# Create SKILL.md
skill_md_content = "You are an expert assistant for testing."
(skill_dir / "SKILL.md").write_text(skill_md_content)
# Create references
refs_dir = skill_dir / "references"
refs_dir.mkdir()
(refs_dir / "guide.md").write_text("# User Guide")
output_dir = Path(temp_dir) / "output"
output_dir.mkdir()
# Package
package_path = self.adaptor.package(skill_dir, output_dir)
# Verify contents
with zipfile.ZipFile(package_path, "r") as zf:
# Read instructions
instructions = zf.read("assistant_instructions.txt").decode("utf-8")
self.assertEqual(instructions, skill_md_content)
# Verify vector store file
self.assertIn("vector_store_files/guide.md", zf.namelist())
# Verify metadata
metadata_content = zf.read("openai_metadata.json").decode("utf-8")
import json
metadata = json.loads(metadata_content)
self.assertEqual(metadata["platform"], "openai")
self.assertEqual(metadata["name"], "test-skill")
self.assertIn("file_search", metadata["tools"])
if __name__ == "__main__":
unittest.main()