What's new in v0.2.0
Skill evolution pipeline
WikiSkillAdapter — pull curated skills from a WikiSkill knowledge base into AgentDB's SkillStore
SkillOptAdapter — push post-training skill signals from SkillOpt back into AgentDB
SkillEvolutionManager with advisory lock primitives to prevent concurrent write conflicts
origin, validation_score, and metadata fields on Skill; health score blends all three signals
- Auto-propose skill drafts from ungoverned consolidation clusters
Memory lifecycle
- Memory consolidation: clusters related episodic records and surfaces a canonical representation
- Session metadata tracking
- Skill conflict signal: flags skills that diverge from LLM-canonical behaviour
checkpoint() and write_compaction_summary() — persist context compaction events into AgentDB so long-running sessions survive history trimming
Notifications
notifications package with EmailChannel, SlackChannel, and NotificationDispatcher
- Wire notification channels from
memory.yaml notifications: block
Embeddings
- YAML-configurable embeddings via
embeddings: block in memory.yaml — no code change required to enable semantic retrieval
LocalEmbeddingProvider supports multiple models (per-model cache, configurable via YAML or constructor)
- Activation precedence:
embed_fn= kwarg > local_embed=True flag > YAML embeddings.enabled: true
Providers
AnthropicProvider for ingesting Anthropic conversation history directly into AgentDB
providers extra: pip install 'agentdatabase[providers]'
Other
agentdb_stats() now includes total_skills and stale_skill_count
conflict_pending_count fix in stats
- Skill injection removed from
retrieve(); skill staleness anchored on updated_at
Install
pip install agentdatabase==0.2.0
# Optional extras
pip install 'agentdatabase[local-embed]' # semantic retrieval
pip install 'agentdatabase[notifications]' # Slack/email alerts
pip install 'agentdatabase[providers]' # Anthropic ingestion
pip install 'agentdatabase[evolution]' # WikiSkill + SkillOpt