agno-agi shipped Agno v3.0.11 on 2026-09-23 (PyPI agno 3.0.11). Knowledge.search() now runs a knowledge-level retrieval pipeline that can widen candidates before reranking, with new MMRReranker (relevance vs diversity) and pgvector-focused RecencyReranker (score × exponential time decay); adds hostname migration for indexed page sources (dry-run by default), typed PageCommandResult with truncation/completeness metadata, and machine-readable cancellation_stage on Run/Team/Workflow outputs. Per-vector-db reranker is deprecated in favor of Knowledge-level rerankers.
Key Takeaways
- ✓Shipped: v3.0.11 / PyPI 3.0.11
- ✓Retrieval: knowledge-level pipeline + MMRReranker (#10115)
- ✓Recency: RecencyReranker with exponential time decay; page-source migrate dry-run by default
- ✓Observability: cancellation_stage enum + typed PageCommandResult metadata
- ✓Migration: deprecate vector-db reranker → Knowledge-level; see Knowledge overview docs
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Project Links & Resources
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Core Background & Industry Pain Points
Per-vector-db rerankers force rewrites when swapping stores; near-duplicate chunks crowd diverse hits; hostname moves often mean full reindex; cancellation text matching is brittle across PENDING/EXECUTING/INTERRUPTED.
Architecture Highlights & Internals
v3.0.11 runs a knowledge-level retrieval pipeline in Knowledge.search() (#10115), adds MMRReranker and pgvector-oriented RecencyReranker, page-source inspect/migrate (dry-run default), typed PageCommandResult / MCP structured search results, cancellation_stage on run outputs, optional use_previous_response_id for OpenAI Responses, and Y-API provider. Vector-db reranker is deprecated.
Authoritative Benchmarks & Measured Scores
No public Recall/nDCG or agent success rates. Measure duplicate-rate/diversity with MMR on/off, recency skew, and assert on cancellation_stage enums.
Developer Hands-on Guide
pip install agno==3.0.11; attach rerankers on Knowledge per Knowledge overview and reference. Release: GitHub.
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