Expand description
§Phago RAG
Biological Retrieval-Augmented Generation.
Instead of vector similarity search, queries traverse the Hebbian knowledge graph following strongest connections. The graph learns from usage — frequently traversed paths strengthen, unused ones decay.
§How it differs from standard RAG
| Standard RAG | Phago RAG |
|---|---|
| Chunk → embed → vector search | Digest → wire → graph traversal |
| Static index | Self-reinforcing graph |
| No learning from queries | Traversed paths strengthen |
| No anomaly detection | Sentinels flag what doesn’t fit |
| Flat retrieval | Structured, weighted paths |
Re-exports§
pub use query::Query;pub use query::QueryResult;pub use query::QueryEngine;pub use hybrid::hybrid_query;pub use hybrid::HybridConfig;pub use hybrid::HybridResult;pub use mcp::phago_remember;pub use mcp::phago_recall;pub use mcp::phago_explore;
Modules§
- baseline
- Baseline retrieval methods for comparison against bio-rag.
- code_
query - Code-aware query interface.
- hybrid
- Hybrid scoring — TF-IDF candidate selection + graph structural re-ranking.
- mcp
- MCP Adapter — Model Context Protocol interface for Phago.
- prelude
- Phago RAG Prelude — convenient imports for common usage.
- query
- Query engine — traverses the Hebbian knowledge graph to retrieve relevant concepts.
- scoring
- Information retrieval scoring metrics.