feat: CrewAI incident response example with KD6 memory backend - #6
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Add examples/crewai-memory/ demonstrating CrewAI multi-agent crews using KD6 as a persistent, layered memory backend via the StorageBackend protocol. Components: - Kd6StorageBackend: full StorageBackend protocol adapter translating CrewAI's path-based scopes to KD6's structured MemoryScope hierarchy, with upsert-based idempotent saves and metadata envelope preservation - Incident response simulation: 4-agent crew (Incident Commander, Platform Engineer, Backend Developer, Communications Lead) investigating a production checkout service failure - Smoke test: non-LLM connectivity test validating all CRUD operations - GitHub Models integration: both LLM inference and embeddings via GITHUB_TOKEN with openai/gpt-4o-mini and text-embedding-3-small Also adds Python-specific entries to .gitignore (__pycache__, .venv, .env). Signed-off-by: David Justice <david@justice.dev>
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Summary
CrewAI multi-agent example using KD6 as the persistent memory backend via the
StorageBackendprotocol.What's Included
Kd6StorageBackend(src/kd6_backend.py)Full implementation of CrewAI's
StorageBackendprotocol:/org/team/agent) to KD6's structuredMemoryScopeupsert_keyfor idempotent saves with CrewAI record IDscontent.crewai_metadata)create_edge,traverse_graph) beyond the protocolIncident Response Simulation (
src/main.py)4-agent crew investigating a production incident at fictional "ShopStream":
GitHub Models Integration
Both LLM and embeddings use GitHub Models (
GITHUB_TOKEN):openai/gpt-4o-miniviahttps://models.github.ai/inferenceopenai/text-embedding-3-smallvia same endpointSmoke Test (
src/smoke_test.py)Non-LLM connectivity test validating all CRUD operations against a running KD6 server.
KD6 Features Demonstrated