refactor: reorgnize all examples/ and test/

benchmarks/README.md

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+# 🧪 Leann Sanity Checks
+
+This directory contains comprehensive sanity checks for the Leann system, ensuring all components work correctly across different configurations.
+
+## 📁 Test Files
+
+### `test_distance_functions.py`
+Tests all supported distance functions across DiskANN backend:
+- ✅ **MIPS** (Maximum Inner Product Search)
+- ✅ **L2** (Euclidean Distance)
+- ✅ **Cosine** (Cosine Similarity)
+
+```bash
+uv run python tests/sanity_checks/test_distance_functions.py
+```
+
+### `test_l2_verification.py`
+Specifically verifies that L2 distance is correctly implemented by:
+- Building indices with L2 vs Cosine metrics
+- Comparing search results and score ranges
+- Validating that different metrics produce expected score patterns
+
+```bash
+uv run python tests/sanity_checks/test_l2_verification.py
+```
+
+### `test_sanity_check.py`
+Comprehensive end-to-end verification including:
+- Distance function testing
+- Embedding model compatibility
+- Search result correctness validation
+- Backend integration testing
+
+```bash
+uv run python tests/sanity_checks/test_sanity_check.py
+```
+
+## 🎯 What These Tests Verify
+
+### ✅ Distance Function Support
+- All three distance metrics (MIPS, L2, Cosine) work correctly
+- Score ranges are appropriate for each metric type
+- Different metrics can produce different rankings (as expected)
+
+### ✅ Backend Integration
+- DiskANN backend properly initializes and builds indices
+- Graph construction completes without errors
+- Search operations return valid results
+
+### ✅ Embedding Pipeline
+- Real-time embedding computation works
+- Multiple embedding models are supported
+- ZMQ server communication functions correctly
+
+### ✅ End-to-End Functionality
+- Index building → searching → result retrieval pipeline
+- Metadata preservation through the entire flow
+- Error handling and graceful degradation
+
+## 🔍 Expected Output
+
+When all tests pass, you should see:
+
+```
+📊 测试结果总结:
+  mips      : ✅ 通过
+  l2        : ✅ 通过
+  cosine    : ✅ 通过
+
+🎉 测试完成!
+```
+
+## 🐛 Troubleshooting
+
+### Common Issues
+
+**Import Errors**: Ensure you're running from the project root:
+```bash
+cd /path/to/leann
+uv run python tests/sanity_checks/test_distance_functions.py
+```
+
+**Memory Issues**: Reduce graph complexity for resource-constrained systems:
+```python
+builder = LeannBuilder(
+    backend_name="diskann",
+    graph_degree=8,  # Reduced from 16
+    complexity=16    # Reduced from 32
+)
+```
+
+**ZMQ Port Conflicts**: The tests use different ports to avoid conflicts, but you may need to kill existing processes:
+```bash
+pkill -f "embedding_server"
+```
+
+## 📊 Performance Expectations
+
+### Typical Timing (3 documents, consumer hardware):
+- **Index Building**: 2-5 seconds per distance function
+- **Search Query**: 50-200ms
+- **Recompute Mode**: 5-15 seconds (higher accuracy)
+
+### Memory Usage:
+- **Index Storage**: ~1-2 MB per distance function
+- **Runtime Memory**: ~500MB (including model loading)
+
+## 🔗 Integration with CI/CD
+
+These tests are designed to be run in automated environments:
+
+```yaml
+# GitHub Actions example
+- name: Run Sanity Checks
+  run: |
+    uv run python tests/sanity_checks/test_distance_functions.py
+    uv run python tests/sanity_checks/test_l2_verification.py
+```
+
+The tests are deterministic and should produce consistent results across different platforms.