Memory and RAG Pattern

Workflow-native memory primitives are available in design_research_agents.workflow:

• MemoryReadStep

• MemoryWriteStep

And a local pluggable persistent memory store:

• SQLiteMemoryStore (default path: artifacts/memory/memory.sqlite3)

Memory retrieval

SQLiteMemoryStore.search(...) always computes lexical relevance. When embeddings are available, the final ranking score uses:

• 0.7 * vector_score + 0.3 * lexical_score

If embeddings are unavailable, retrieval falls back to lexical-only ranking.

RAG orchestration

RAGPattern composes memory and reasoning as:

1. MemoryReadStep

2. DelegateStep reasoning delegate (with retrieved context injection)

3. MemoryWriteStep (optional write-back)

Background reference

• Retrieval-Augmented Generation (RAG)

The original RAG formulation combines a retriever and generator with non-parametric memory; this implementation uses workflow-level retrieval and context injection.

Examples

• examples/patterns/rag.py

• examples/agents/multi_step_json_with_memory.py