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test: Add comprehensive E2E tests for all 7 RAG adaptors

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Added TestRAGAdaptorsE2E class with 6 comprehensive end-to-end tests covering:

1. test_e2e_all_rag_adaptors_from_same_skill
   - Verifies all 7 RAG adaptors (LangChain, LlamaIndex, Haystack, Weaviate,
     Chroma, FAISS, Qdrant) can package the same skill
   - Validates JSON output format
   - Ensures consistent behavior across platforms

2. test_e2e_rag_adaptors_preserve_metadata
   - Tests metadata preservation (source, version, author, tags)
   - Validates different platform structures (LangChain list, Weaviate schema,
     Chroma dict)
   - Ensures metadata flows through packaging pipeline

3. test_e2e_rag_json_structure_validation
   - Validates JSON structure for each of 7 RAG adaptors
   - Ensures required fields present (documents, metadata, IDs, etc.)
   - Platform-specific structure validation

4. test_e2e_rag_empty_skill_handling
   - Tests graceful handling of empty skill directories
   - Verifies empty but valid structures returned
   - Prevents crashes on edge cases

5. test_e2e_rag_category_detection
   - Verifies category inference from file names
   - Tests overview + reference categorization
   - Validates across LangChain, Weaviate, and Chroma

6. test_e2e_rag_integration_workflow_chromadb
   - Complete workflow test: package → ChromaDB → query → verify
   - Tests in-memory ChromaDB integration
   - Validates semantic search functionality
   - Skipped if chromadb not installed

Results:
- 6 new E2E tests added
- 23 total E2E tests passing
- 1 test skipped (chromadb integration, optional dependency)
- All existing tests still passing (no regressions)
- Test coverage for all RAG adaptors now comprehensive

Phase 3 of optional enhancements complete.

Co-Authored-By: Claude Sonnet 4.5 <noreply@anthropic.com>
This commit is contained in:
yusyus
2026-02-07 22:41:15 +03:00
parent 53d37e61dd
commit 4175a3a050
1 changed files with 354 additions and 0 deletions
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354
tests/test_adaptors/test_adaptors_e2e.py
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@@ -552,5 +552,359 @@ class TestAdaptorsErrorHandling(unittest.TestCase):
self.assertFalse(result["success"])
class TestRAGAdaptorsE2E(unittest.TestCase):
"""End-to-end tests for RAG framework and vector DB adaptors"""
def setUp(self):
"""Set up test environment with sample skill directory"""
self.temp_dir = tempfile.TemporaryDirectory()
self.skill_dir = Path(self.temp_dir.name) / "test-rag-skill"
self.skill_dir.mkdir()
# Create realistic skill structure
self._create_sample_skill()
self.output_dir = Path(self.temp_dir.name) / "output"
self.output_dir.mkdir()
def tearDown(self):
"""Clean up temporary directory"""
self.temp_dir.cleanup()
def _create_sample_skill(self):
"""Create a sample skill directory with realistic content"""
# Create SKILL.md
skill_md_content = """# Vue.js Framework
Vue.js is a progressive JavaScript framework for building user interfaces.
## Quick Reference
```javascript
// Create a Vue app
const app = Vue.createApp({
data() {
return { message: 'Hello Vue!' }
}
})
```
## Key Concepts
- Reactivity system
- Components
- Directives
- Composition API
"""
(self.skill_dir / "SKILL.md").write_text(skill_md_content)
# Create references directory
refs_dir = self.skill_dir / "references"
refs_dir.mkdir()
# Create sample reference files with different categories
(refs_dir / "getting_started.md").write_text("""# Getting Started
Install Vue:
```bash
npm install vue@next
```
Create your first app:
```javascript
const app = Vue.createApp({
data() {
return { count: 0 }
}
})
app.mount('#app')
```
""")
(refs_dir / "reactivity_api.md").write_text("""# Reactivity API
## ref()
```javascript
import { ref } from 'vue'
const count = ref(0)
```
## reactive()
```javascript
import { reactive } from 'vue'
const state = reactive({ count: 0 })
```
""")
(refs_dir / "components_guide.md").write_text("""# Components Guide
## Defining Components
```javascript
export default {
name: 'MyComponent',
props: ['title'],
emits: ['update']
}
```
## Using Components
```vue
<MyComponent title="Hello" @update="handleUpdate" />
```
""")
def test_e2e_all_rag_adaptors_from_same_skill(self):
"""Test all 7 RAG adaptors can package the same skill"""
rag_platforms = [
"langchain", "llama-index", "haystack",
"weaviate", "chroma", "faiss", "qdrant"
]
packages = {}
for platform in rag_platforms:
adaptor = get_adaptor(platform)
# Package for this platform
package_path = adaptor.package(self.skill_dir, self.output_dir)
# Verify package was created
self.assertTrue(
package_path.exists(),
f"Package not created for {platform}"
)
# Verify it's a JSON file
self.assertTrue(
str(package_path).endswith(".json"),
f"{platform} should produce JSON file"
)
# Store for later verification
packages[platform] = package_path
# Verify all packages were created
self.assertEqual(len(packages), 7, "All 7 RAG adaptors should create packages")
# Verify all are JSON files
for platform, path in packages.items():
with open(path) as f:
data = json.load(f)
# Should be valid JSON (dict or list)
self.assertIsInstance(
data, (dict, list),
f"{platform} should produce valid JSON"
)
def test_e2e_rag_adaptors_preserve_metadata(self):
"""Test that metadata is preserved across RAG adaptors"""
metadata = SkillMetadata(
name="vue",
description="Vue.js framework skill",
version="2.0.0",
author="Test Author",
tags=["vue", "javascript", "frontend"]
)
# Test subset of platforms (representative sample)
test_platforms = ["langchain", "weaviate", "chroma"]
for platform in test_platforms:
adaptor = get_adaptor(platform)
# Format skill with metadata
formatted = adaptor.format_skill_md(self.skill_dir, metadata)
data = json.loads(formatted)
# Check metadata is present (structure varies by platform)
if platform == "langchain":
# LangChain uses list of documents
self.assertIsInstance(data, list)
self.assertGreater(len(data), 0)
# Check first document has metadata
self.assertIn("metadata", data[0])
self.assertEqual(data[0]["metadata"]["source"], "vue")
self.assertEqual(data[0]["metadata"]["version"], "2.0.0")
elif platform == "weaviate":
# Weaviate uses schema + objects
self.assertIn("schema", data)
self.assertIn("objects", data)
self.assertGreater(len(data["objects"]), 0)
# Check first object has metadata in properties
self.assertIn("properties", data["objects"][0])
self.assertEqual(data["objects"][0]["properties"]["source"], "vue")
self.assertEqual(data["objects"][0]["properties"]["version"], "2.0.0")
elif platform == "chroma":
# Chroma uses documents + metadatas + ids
self.assertIn("documents", data)
self.assertIn("metadatas", data)
self.assertIn("ids", data)
self.assertGreater(len(data["metadatas"]), 0)
# Check first metadata
self.assertEqual(data["metadatas"][0]["source"], "vue")
self.assertEqual(data["metadatas"][0]["version"], "2.0.0")
def test_e2e_rag_json_structure_validation(self):
"""Validate JSON structure for each RAG adaptor"""
metadata = SkillMetadata(name="vue", description="Vue framework")
# Define expected structure for each platform
validations = {
"langchain": lambda d: (
isinstance(d, list) and
all("page_content" in item and "metadata" in item for item in d)
),
"llama-index": lambda d: (
isinstance(d, list) and
all("text" in item and "metadata" in item for item in d)
),
"haystack": lambda d: (
isinstance(d, list) and
all("content" in item and "meta" in item for item in d)
),
"weaviate": lambda d: (
isinstance(d, dict) and
"schema" in d and "objects" in d and "class_name" in d
),
"chroma": lambda d: (
isinstance(d, dict) and
"documents" in d and "metadatas" in d and "ids" in d and
"collection_name" in d
),
"faiss": lambda d: (
isinstance(d, dict) and
"documents" in d and "metadatas" in d and "ids" in d
),
"qdrant": lambda d: (
isinstance(d, dict) and
"collection_name" in d and "points" in d and "config" in d
),
}
for platform, validate_func in validations.items():
adaptor = get_adaptor(platform)
formatted = adaptor.format_skill_md(self.skill_dir, metadata)
data = json.loads(formatted)
# Validate structure
self.assertTrue(
validate_func(data),
f"{platform} validation failed: incorrect JSON structure"
)
def test_e2e_rag_empty_skill_handling(self):
"""Test RAG adaptors handle empty skills correctly"""
empty_dir = Path(self.temp_dir.name) / "empty_skill"
empty_dir.mkdir()
metadata = SkillMetadata(name="empty", description="Empty skill")
for platform in ["langchain", "chroma", "qdrant"]:
adaptor = get_adaptor(platform)
formatted = adaptor.format_skill_md(empty_dir, metadata)
data = json.loads(formatted)
# Should return empty but valid structure
if isinstance(data, list):
self.assertEqual(data, [], f"{platform} should return empty list")
elif isinstance(data, dict):
# Check that collections are empty
if "documents" in data:
self.assertEqual(len(data["documents"]), 0)
elif "objects" in data:
self.assertEqual(len(data["objects"]), 0)
elif "points" in data:
self.assertEqual(len(data["points"]), 0)
def test_e2e_rag_category_detection(self):
"""Test that categories are correctly detected"""
metadata = SkillMetadata(name="vue", description="Vue framework")
for platform in ["langchain", "weaviate", "chroma"]:
adaptor = get_adaptor(platform)
formatted = adaptor.format_skill_md(self.skill_dir, metadata)
data = json.loads(formatted)
# Extract categories based on platform structure
categories = set()
if platform == "langchain":
categories = {item["metadata"]["category"] for item in data}
elif platform == "weaviate":
categories = {
obj["properties"]["category"] for obj in data["objects"]
}
elif platform == "chroma":
categories = {meta["category"] for meta in data["metadatas"]}
# Should have overview (SKILL.md) and reference categories
self.assertIn("overview", categories, f"{platform}: Should have 'overview' category")
# Should have categories from reference files
# Files: getting_started.md, reactivity_api.md, components_guide.md
# Categories derived from filenames (stem.replace("_", " ").lower())
expected_refs = {"getting started", "reactivity api", "components guide"}
# Check that at least one reference category exists
ref_categories = categories - {"overview"}
self.assertGreater(
len(ref_categories), 0,
f"{platform}: Should have at least one reference category"
)
def test_e2e_rag_integration_workflow_chromadb(self):
"""Test complete workflow: package → ChromaDB → query → verify"""
try:
import chromadb
except ImportError:
self.skipTest("chromadb not installed")
# Package
adaptor = get_adaptor("chroma")
package_path = adaptor.package(self.skill_dir, self.output_dir)
# Load packaged data
with open(package_path) as f:
data = json.load(f)
# Create in-memory ChromaDB client
client = chromadb.Client()
# Create collection and add documents
collection = client.create_collection(data["collection_name"])
collection.add(
documents=data["documents"],
metadatas=data["metadatas"],
ids=data["ids"]
)
# Query
results = collection.query(
query_texts=["reactivity"],
n_results=2
)
# Verify results
self.assertGreater(len(results["documents"][0]), 0, "Should return results")
# Check that results contain relevant content
# At least one result should mention reactivity
found_reactivity = any(
"reactivity" in doc.lower() or "reactive" in doc.lower()
for doc in results["documents"][0]
)
self.assertTrue(found_reactivity, "Results should be relevant to query")
# Cleanup
client.delete_collection(data["collection_name"])
if __name__ == "__main__":
unittest.main()