add: cheshire-cat configuration, tooling, tests, and documentation

Configuration:
- .env.example, .gitignore, compose.yml (main docker compose)
- docker-compose-amd.yml (ROCm), docker-compose-macos.yml
- start.sh, stop.sh convenience scripts
- LICENSE (Apache 2.0, from upstream Cheshire Cat)

Memory management utilities:
- analyze_consolidation.py, manual_consolidation.py, verify_consolidation.py
- check_memories.py, extract_declarative_facts.py, store_declarative_facts.py
- compare_systems.py (system comparison tool)
- benchmark_cat.py, streaming_benchmark.py, streaming_benchmark_v2.py

Test suite:
- quick_test.py, test_setup.py, test_setup_simple.py
- test_consolidation_direct.py, test_declarative_recall.py, test_recall.py
- test_end_to_end.py, test_full_pipeline.py
- test_phase2.py, test_phase2_comprehensive.py

Documentation:
- README.md, QUICK_START.txt, TEST_README.md, SETUP_COMPLETE.md
- PHASE2_IMPLEMENTATION_NOTES.md, PHASE2_TEST_RESULTS.md
- POST_OPTIMIZATION_ANALYSIS.md
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================================================================================
🐱 CHESHIRE CAT TEST ENVIRONMENT - QUICK START GUIDE
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📍 Location: /home/koko210Serve/docker/miku-discord/cheshire-cat
🎯 Purpose: Test Cheshire Cat as memory/context system for Miku Bot
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⚡ QUICK START (3 Commands)
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1. Start services:
./start.sh
2. Configure and upload knowledge:
python3 test_setup.py
3. Run benchmarks:
python3 benchmark_cat.py
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📊 WHAT TO LOOK FOR
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✅ GOOD (Proceed with integration):
- Mean latency < 1500ms
- P95 latency < 2000ms
- RAG retrieval is accurate
⚠️ BORDERLINE (Try GPU embeddings):
- Mean latency 1500-2000ms
- Consider hybrid approach
❌ POOR (Stick with current system):
- Mean latency > 2000ms
- RAG quality is poor
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🔗 USEFUL LINKS
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Admin Panel: http://localhost:1865/admin
API Docs: http://localhost:1865/docs
Qdrant: http://localhost:6333/dashboard
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📝 FILES CREATED
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Configuration:
✓ .env Environment variables
✓ docker-compose.test.yml Docker services
Scripts:
✓ start.sh Start services
✓ stop.sh Stop services
✓ test_setup.py Configure Cat & upload knowledge
✓ benchmark_cat.py Performance benchmarks
✓ compare_systems.py Compare Cat vs current system
Documentation:
✓ SETUP_COMPLETE.md Full setup guide
✓ TEST_README.md Testing documentation
✓ QUICK_START.txt This file
================================================================================
🎯 EXPECTED RESULTS (FX-6100)
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With CPU embeddings:
Mean: 1600-2200ms ⚠️ Borderline for voice chat
With GPU embeddings:
Mean: 900-1400ms ✅ Good for voice chat
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🛠️ TROUBLESHOOTING
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Services won't start:
docker logs miku_cheshire_cat_test
Can't connect to llama-swap:
Edit test_setup.py line 10 with correct URL
Embeddings too slow:
Try GPU acceleration (requires spare VRAM)
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🧹 CLEANUP
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Stop services:
./stop.sh
Remove all data:
docker-compose -f docker-compose.test.yml down -v
================================================================================
📚 DETAILED DOCS
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Full guide: cat SETUP_COMPLETE.md
Test docs: cat TEST_README.md
View all files: ls -lah
================================================================================