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Merge pull request #1 from MervinPraison/develop
MervinPraison
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- Fix #1: MemoryConfig Pydantic validation - add _prepare_mem0_config() to strip PraisonAI-specific reranker fields (enabled, default_rerank) before passing to mem0, which only accepts provider and config fields - Fix #2: LLM Reranker 'Chat' object not callable - check if client.chat is callable, not just if it exists. OpenAI client has chat as namespace object. Also handle max_completion_tokens vs max_tokens for different model versions. - Fix #3: Chroma vector store metadata validation - ensure non-empty metadata dicts by adding placeholder key when metadata is empty or None - Fix test file issues: add user_id parameter (required by mem0 API), handle dict return type from knowledge.search, use gpt-4o-mini for reranker test (gpt-5-nano returns empty responses with max_completion_tokens=10)
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praisonai-triage-agent Bot
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This addresses architectural gaps #1-3 by implementing: 1. LLMProviderAdapter protocol to replace scattered provider dispatch 2. UnifiedLLMProtocol to consolidate dual execution paths 3. Memory and Knowledge adapter registries for protocol-driven backends Changes: - Add LLMProviderAdapter and UnifiedLLMProtocol to llm/protocols.py - Create memory/adapters/registry.py with thread-safe adapter registration - Create knowledge/adapters/registry.py with thread-safe adapter registration - Register core adapters (sqlite, in_memory) in core SDK - Heavy implementations (chromadb, mem0) to be moved to wrapper Follows AGENTS.md protocol-driven core principle. Backward compatible. Co-authored-by: MervinPraison <MervinPraison@users.noreply.github.com>
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Core SDK Gap #3: Memory/Knowledge adapter protocols exist but bypassed by core implementations
#1306
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