SochDB Notebooks

This repository contains interactive Jupyter notebooks that demonstrate various features and capabilities of SochDB, an advanced database system.

Notebooks Included

1. RAG Hybrid Search (1_rag_hybrid_search.ipynb): Demonstrates Retrieval-Augmented Generation using SochDB's hybrid search capabilities.
2. CAG Semantic Cache (2_cag_semantic_cache.ipynb): Shows how to use Context-Aware Generation (CAG) with semantic caching.
3. Agent Memory (3_agent_memory.ipynb): Explores implementing long-term memory for conversational agents.
4. Agentic Workflows (4_agentic_workflows.ipynb): Demonstrates complex, multi-step agentic workflows and orchestration.
5. Knowledge Graph (5_knowledge_graph.ipynb): Shows how to construct and traverse knowledge graphs within SochDB.
6. Transactions & KV (6_transactions_kv.ipynb): Explains transactional operations and Key-Value store use cases.
7. Multitenant Isolation (7_multitenant_isolation.ipynb): Demonstrates namespace and data isolation for multitenant applications.
8. SQL Engine (8_sql_engine.ipynb): Highlights the SQL querying capabilities over structured and unstructured data.
9. Backup & Admin (9_backup_admin.ipynb): Covers database administration tasks, including backups and restores.
10. Advanced RAG (10_advanced_rag.ipynb): Discusses advanced RAG techniques such as re-ranking and chunking strategies.
11. Agentic Tool Use (11_agentic_tool_use.ipynb): Shows how AI agents can interact with SochDB as a tool.
12. Conversational RAG Memory (12_conversational_rag_memory.ipynb): Deals with conversational memory within a RAG system.

Usage

Simply clone this repository and run the notebooks in any Jupyter Notebook / Lab environment or directly inside VS Code. Ensure that you have the SochDB Python SDK installed and properly configured.

pip install sochdb