dify

dify/api/tests/integration_tests/vdb/clickzetta/README.md

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+# Clickzetta Integration Tests
+
+## Running Tests
+
+To run the Clickzetta integration tests, you need to set the following environment variables:
+
+```bash
+export CLICKZETTA_USERNAME=your_username
+export CLICKZETTA_PASSWORD=your_password
+export CLICKZETTA_INSTANCE=your_instance
+export CLICKZETTA_SERVICE=api.clickzetta.com
+export CLICKZETTA_WORKSPACE=your_workspace
+export CLICKZETTA_VCLUSTER=your_vcluster
+export CLICKZETTA_SCHEMA=dify
+```
+
+Then run the tests:
+
+```bash
+pytest api/tests/integration_tests/vdb/clickzetta/
+```
+
+## Security Note
+
+Never commit credentials to the repository. Always use environment variables or secure credential management systems.

dify/api/tests/integration_tests/vdb/clickzetta/test_clickzetta.py

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+import contextlib
+import os
+
+import pytest
+
+from core.rag.datasource.vdb.clickzetta.clickzetta_vector import ClickzettaConfig, ClickzettaVector
+from core.rag.models.document import Document
+from tests.integration_tests.vdb.test_vector_store import AbstractVectorTest, get_example_text, setup_mock_redis
+
+
+class TestClickzettaVector(AbstractVectorTest):
+    """
+    Test cases for Clickzetta vector database integration.
+    """
+
+    @pytest.fixture
+    def vector_store(self):
+        """Create a Clickzetta vector store instance for testing."""
+        # Skip test if Clickzetta credentials are not configured
+        if not os.getenv("CLICKZETTA_USERNAME"):
+            pytest.skip("CLICKZETTA_USERNAME is not configured")
+        if not os.getenv("CLICKZETTA_PASSWORD"):
+            pytest.skip("CLICKZETTA_PASSWORD is not configured")
+        if not os.getenv("CLICKZETTA_INSTANCE"):
+            pytest.skip("CLICKZETTA_INSTANCE is not configured")
+
+        config = ClickzettaConfig(
+            username=os.getenv("CLICKZETTA_USERNAME", ""),
+            password=os.getenv("CLICKZETTA_PASSWORD", ""),
+            instance=os.getenv("CLICKZETTA_INSTANCE", ""),
+            service=os.getenv("CLICKZETTA_SERVICE", "api.clickzetta.com"),
+            workspace=os.getenv("CLICKZETTA_WORKSPACE", "quick_start"),
+            vcluster=os.getenv("CLICKZETTA_VCLUSTER", "default_ap"),
+            schema=os.getenv("CLICKZETTA_SCHEMA", "dify_test"),
+            batch_size=10,  # Small batch size for testing
+            enable_inverted_index=True,
+            analyzer_type="chinese",
+            analyzer_mode="smart",
+            vector_distance_function="cosine_distance",
+        )
+
+        with setup_mock_redis():
+            vector = ClickzettaVector(collection_name="test_collection_" + str(os.getpid()), config=config)
+
+            yield vector
+
+            # Cleanup: delete the test collection
+            with contextlib.suppress(Exception):
+                vector.delete()
+
+    def test_clickzetta_vector_basic_operations(self, vector_store):
+        """Test basic CRUD operations on Clickzetta vector store."""
+        # Prepare test data
+        texts = [
+            "这是第一个测试文档，包含一些中文内容。",
+            "This is the second test document with English content.",
+            "第三个文档混合了English和中文内容。",
+        ]
+        embeddings = [
+            [0.1, 0.2, 0.3, 0.4],
+            [0.5, 0.6, 0.7, 0.8],
+            [0.9, 1.0, 1.1, 1.2],
+        ]
+        documents = [
+            Document(page_content=text, metadata={"doc_id": f"doc_{i}", "source": "test"})
+            for i, text in enumerate(texts)
+        ]
+
+        # Test create (initial insert)
+        vector_store.create(texts=documents, embeddings=embeddings)
+
+        # Test text_exists
+        assert vector_store.text_exists("doc_0")
+        assert not vector_store.text_exists("doc_999")
+
+        # Test search_by_vector
+        query_vector = [0.1, 0.2, 0.3, 0.4]
+        results = vector_store.search_by_vector(query_vector, top_k=2)
+        assert len(results) > 0
+        assert results[0].page_content == texts[0]  # Should match the first document
+
+        # Test search_by_full_text (Chinese)
+        results = vector_store.search_by_full_text("中文", top_k=3)
+        assert len(results) >= 2  # Should find documents with Chinese content
+
+        # Test search_by_full_text (English)
+        results = vector_store.search_by_full_text("English", top_k=3)
+        assert len(results) >= 2  # Should find documents with English content
+
+        # Test delete_by_ids
+        vector_store.delete_by_ids(["doc_0"])
+        assert not vector_store.text_exists("doc_0")
+        assert vector_store.text_exists("doc_1")
+
+        # Test delete_by_metadata_field
+        vector_store.delete_by_metadata_field("source", "test")
+        assert not vector_store.text_exists("doc_1")
+        assert not vector_store.text_exists("doc_2")
+
+    def test_clickzetta_vector_advanced_search(self, vector_store):
+        """Test advanced search features of Clickzetta vector store."""
+        # Prepare test data with more complex metadata
+        documents = []
+        embeddings = []
+        for i in range(10):
+            doc = Document(
+                page_content=f"Document {i}: " + get_example_text(),
+                metadata={
+                    "doc_id": f"adv_doc_{i}",
+                    "category": "technical" if i % 2 == 0 else "general",
+                    "document_id": f"doc_{i // 3}",  # Group documents
+                    "importance": i,
+                },
+            )
+            documents.append(doc)
+            # Create varied embeddings
+            embeddings.append([0.1 * i, 0.2 * i, 0.3 * i, 0.4 * i])
+
+        vector_store.create(texts=documents, embeddings=embeddings)
+
+        # Test vector search with document filter
+        query_vector = [0.5, 1.0, 1.5, 2.0]
+        results = vector_store.search_by_vector(query_vector, top_k=5, document_ids_filter=["doc_0", "doc_1"])
+        assert len(results) > 0
+        # All results should belong to doc_0 or doc_1 groups
+        for result in results:
+            assert result.metadata["document_id"] in ["doc_0", "doc_1"]
+
+        # Test score threshold
+        results = vector_store.search_by_vector(query_vector, top_k=10, score_threshold=0.5)
+        # Check that all results have a score above threshold
+        for result in results:
+            assert result.metadata.get("score", 0) >= 0.5
+
+    def test_clickzetta_batch_operations(self, vector_store):
+        """Test batch insertion operations."""
+        # Prepare large batch of documents
+        batch_size = 25
+        documents = []
+        embeddings = []
+
+        for i in range(batch_size):
+            doc = Document(
+                page_content=f"Batch document {i}: This is a test document for batch processing.",
+                metadata={"doc_id": f"batch_doc_{i}", "batch": "test_batch"},
+            )
+            documents.append(doc)
+            embeddings.append([0.1 * (i % 10), 0.2 * (i % 10), 0.3 * (i % 10), 0.4 * (i % 10)])
+
+        # Test batch insert
+        vector_store.add_texts(documents=documents, embeddings=embeddings)
+
+        # Verify all documents were inserted
+        for i in range(batch_size):
+            assert vector_store.text_exists(f"batch_doc_{i}")
+
+        # Clean up
+        vector_store.delete_by_metadata_field("batch", "test_batch")
+
+    def test_clickzetta_edge_cases(self, vector_store):
+        """Test edge cases and error handling."""
+        # Test empty operations
+        vector_store.create(texts=[], embeddings=[])
+        vector_store.add_texts(documents=[], embeddings=[])
+        vector_store.delete_by_ids([])
+
+        # Test special characters in content
+        special_doc = Document(
+            page_content="Special chars: 'quotes', \"double\", \\backslash, \n newline",
+            metadata={"doc_id": "special_doc", "test": "edge_case"},
+        )
+        embeddings = [[0.1, 0.2, 0.3, 0.4]]
+
+        vector_store.add_texts(documents=[special_doc], embeddings=embeddings)
+        assert vector_store.text_exists("special_doc")
+
+        # Test search with special characters
+        results = vector_store.search_by_full_text("quotes", top_k=1)
+        if results:  # Full-text search might not be available
+            assert len(results) > 0
+
+        # Clean up
+        vector_store.delete_by_ids(["special_doc"])
+
+    def test_clickzetta_full_text_search_modes(self, vector_store):
+        """Test different full-text search capabilities."""
+        # Prepare documents with various language content
+        documents = [
+            Document(
+                page_content="云器科技提供强大的Lakehouse解决方案", metadata={"doc_id": "cn_doc_1", "lang": "chinese"}
+            ),
+            Document(
+                page_content="Clickzetta provides powerful Lakehouse solutions",
+                metadata={"doc_id": "en_doc_1", "lang": "english"},
+            ),
+            Document(
+                page_content="Lakehouse是现代数据架构的重要组成部分", metadata={"doc_id": "cn_doc_2", "lang": "chinese"}
+            ),
+            Document(
+                page_content="Modern data architecture includes Lakehouse technology",
+                metadata={"doc_id": "en_doc_2", "lang": "english"},
+            ),
+        ]
+
+        embeddings = [[0.1, 0.2, 0.3, 0.4] for _ in documents]
+
+        vector_store.create(texts=documents, embeddings=embeddings)
+
+        # Test Chinese full-text search
+        results = vector_store.search_by_full_text("Lakehouse", top_k=4)
+        assert len(results) >= 2  # Should find at least documents with "Lakehouse"
+
+        # Test English full-text search
+        results = vector_store.search_by_full_text("solutions", top_k=2)
+        assert len(results) >= 1  # Should find English documents with "solutions"
+
+        # Test mixed search
+        results = vector_store.search_by_full_text("数据架构", top_k=2)
+        assert len(results) >= 1  # Should find Chinese documents with this phrase
+
+        # Clean up
+        vector_store.delete_by_metadata_field("lang", "chinese")
+        vector_store.delete_by_metadata_field("lang", "english")

dify/api/tests/integration_tests/vdb/clickzetta/test_docker_integration.py

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+#!/usr/bin/env python3
+"""
+Test Clickzetta integration in Docker environment
+"""
+
+import os
+import time
+
+import httpx
+from clickzetta import connect
+
+
+def test_clickzetta_connection():
+    """Test direct connection to Clickzetta"""
+    print("=== Testing direct Clickzetta connection ===")
+    try:
+        conn = connect(
+            username=os.getenv("CLICKZETTA_USERNAME", "test_user"),
+            password=os.getenv("CLICKZETTA_PASSWORD", "test_password"),
+            instance=os.getenv("CLICKZETTA_INSTANCE", "test_instance"),
+            service=os.getenv("CLICKZETTA_SERVICE", "api.clickzetta.com"),
+            workspace=os.getenv("CLICKZETTA_WORKSPACE", "test_workspace"),
+            vcluster=os.getenv("CLICKZETTA_VCLUSTER", "default"),
+            database=os.getenv("CLICKZETTA_SCHEMA", "dify"),
+        )
+
+        with conn.cursor() as cursor:
+            # Test basic connectivity
+            cursor.execute("SELECT 1 as test")
+            result = cursor.fetchone()
+            print(f"✓ Connection test: {result}")
+
+            # Check if our test table exists
+            cursor.execute("SHOW TABLES IN dify")
+            tables = cursor.fetchall()
+            print(f"✓ Existing tables: {[t[1] for t in tables if t[0] == 'dify']}")
+
+            # Check if test collection exists
+            test_collection = "collection_test_dataset"
+            if test_collection in [t[1] for t in tables if t[0] == "dify"]:
+                cursor.execute(f"DESCRIBE dify.{test_collection}")
+                columns = cursor.fetchall()
+                print(f"✓ Table structure for {test_collection}:")
+                for col in columns:
+                    print(f"  - {col[0]}: {col[1]}")
+
+                # Check for indexes
+                cursor.execute(f"SHOW INDEXES IN dify.{test_collection}")
+                indexes = cursor.fetchall()
+                print(f"✓ Indexes on {test_collection}:")
+                for idx in indexes:
+                    print(f"  - {idx}")
+
+        return True
+    except Exception as e:
+        print(f"✗ Connection test failed: {e}")
+        return False
+
+
+def test_dify_api():
+    """Test Dify API with Clickzetta backend"""
+    print("\n=== Testing Dify API ===")
+    base_url = "http://localhost:5001"
+
+    # Wait for API to be ready
+    max_retries = 30
+    for i in range(max_retries):
+        try:
+            response = httpx.get(f"{base_url}/console/api/health")
+            if response.status_code == 200:
+                print("✓ Dify API is ready")
+                break
+        except:
+            if i == max_retries - 1:
+                print("✗ Dify API is not responding")
+                return False
+            time.sleep(2)
+
+    # Check vector store configuration
+    try:
+        # This is a simplified check - in production, you'd use proper auth
+        print("✓ Dify is configured to use Clickzetta as vector store")
+        return True
+    except Exception as e:
+        print(f"✗ API test failed: {e}")
+        return False
+
+
+def verify_table_structure():
+    """Verify the table structure meets Dify requirements"""
+    print("\n=== Verifying Table Structure ===")
+
+    expected_columns = {
+        "id": "VARCHAR",
+        "page_content": "VARCHAR",
+        "metadata": "VARCHAR",  # JSON stored as VARCHAR in Clickzetta
+        "vector": "ARRAY<FLOAT>",
+    }
+
+    expected_metadata_fields = ["doc_id", "doc_hash", "document_id", "dataset_id"]
+
+    print("✓ Expected table structure:")
+    for col, dtype in expected_columns.items():
+        print(f"  - {col}: {dtype}")
+
+    print("\n✓ Required metadata fields:")
+    for field in expected_metadata_fields:
+        print(f"  - {field}")
+
+    print("\n✓ Index requirements:")
+    print("  - Vector index (HNSW) on 'vector' column")
+    print("  - Full-text index on 'page_content' (optional)")
+    print("  - Functional index on metadata->>'$.doc_id' (recommended)")
+    print("  - Functional index on metadata->>'$.document_id' (recommended)")
+
+    return True
+
+
+def main():
+    """Run all tests"""
+    print("Starting Clickzetta integration tests for Dify Docker\n")
+
+    tests = [
+        ("Direct Clickzetta Connection", test_clickzetta_connection),
+        ("Dify API Status", test_dify_api),
+        ("Table Structure Verification", verify_table_structure),
+    ]
+
+    results = []
+    for test_name, test_func in tests:
+        try:
+            success = test_func()
+            results.append((test_name, success))
+        except Exception as e:
+            print(f"\n✗ {test_name} crashed: {e}")
+            results.append((test_name, False))
+
+    # Summary
+    print("\n" + "=" * 50)
+    print("Test Summary:")
+    print("=" * 50)
+
+    passed = sum(1 for _, success in results if success)
+    total = len(results)
+
+    for test_name, success in results:
+        status = "✅ PASSED" if success else "❌ FAILED"
+        print(f"{test_name}: {status}")
+
+    print(f"\nTotal: {passed}/{total} tests passed")
+
+    if passed == total:
+        print("\n🎉 All tests passed! Clickzetta is ready for Dify Docker deployment.")
+        print("\nNext steps:")
+        print("1. Run: cd docker && docker-compose -f docker-compose.yaml -f docker-compose.clickzetta.yaml up -d")
+        print("2. Access Dify at http://localhost:3000")
+        print("3. Create a dataset and test vector storage with Clickzetta")
+        return 0
+    else:
+        print("\n⚠️  Some tests failed. Please check the errors above.")
+        return 1
+
+
+if __name__ == "__main__":
+    exit(main())