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zapomni

Verified Safe

by alienxs2

Overview

An intelligent memory processing and knowledge management system that uses LLMs and vector databases to chunk text, generate embeddings, extract entities, and build a knowledge graph for semantic search and retrieval.

Installation

Run Command
python -m zapomni_mcp

Environment Variables

  • ZAPOMNI_FALKORDB_HOST
  • ZAPOMNI_FALKORDB_PORT
  • ZAPOMNI_FALKORDB_PASSWORD
  • ZAPOMNI_OLLAMA_BASE_URL
  • ZAPOMNI_OLLAMA_EMBEDDING_MODEL
  • ZAPOMNI_OLLAMA_LLM_MODEL
  • ZAPOMNI_REDIS_HOST
  • ZAPOMNI_REDIS_PORT
  • ZAPOMNI_LOG_LEVEL
  • ZAPOMNI_SSE_BIND_HOST
  • ZAPOMNI_SSE_CORS_ORIGINS

Security Notes

The project demonstrates good security practices including explicit input validation, parameterized database queries (Cypher), and the use of Pydantic's `SecretStr` for sensitive configurations like database passwords. It also implements a `DNSRebindingProtectionMiddleware` to mitigate DNS rebinding attacks on its SSE server. While `subprocess.run` is used for git commands, it's done without `shell=True` and with direct arguments, reducing command injection risk. External dependencies like Ollama, FalkorDB, and Redis are assumed to be locally hosted or trusted network services.

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Stats

Interest Score0
Security Score9
Cost ClassHigh
Avg Tokens2000
Stars0
Forks0
Last Update2025-12-05

Tags

Knowledge GraphSemantic SearchLLM IntegrationVector DatabaseCode AnalysisDocument ProcessingHybrid SearchInformation Retrieval