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📅 Today’s Picks

ChromaDB: Metadata Filtering for Precise Semantic Search

Problem

Search for “latest ML research” and semantic search might return highly relevant papers from 2019.

That’s because similarity doesn’t understand constraints. You need metadata filtering to enforce “year >= 2024” at the database level.

Solution

ChromaDB’s where clause lets you combine “find similar” with “but only from 2024.” The database filters first, then ranks by similarity.

Key operators:

• $eq, $ne for exact matching
• $gt, $gte, $lt, $lte for range queries
• $in, $nin for set membership
• $and, $or for combining conditions

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🔄 Worth Revisiting

Semantic Search in PostgreSQL with pgvector

Problem

Traditional PostgreSQL keyword queries return limited results because they require exact string matches. This approach misses semantically related data that shares meaning but uses different terminology.

Solution

pgvector enables vector search within PostgreSQL. This allows semantic matching of contextually similar content.

Key benefits:

• Native PostgreSQL integration with existing databases
• Fast exact and approximate nearest neighbor search
• Six distance metrics including L2, cosine, inner product, and Hamming
• Seamless Python integration via SQLAlchemy or psycopg2

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☕️ Weekly Finds

RAGxplorer [LLM] – Open-source tool to visualize RAG embeddings and explore retrieval augmented generation pipelines interactively

CAMEL [LLM] – The first multi-agent framework enabling AI agents to communicate and collaborate while assuming different roles

claude-scientific-skills [LLM] – A set of ready-to-use scientific skills for Claude, enabling advanced research and analysis workflows

Looking for a specific tool? Explore 70+ Python tools →

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📚 Latest Deep Dives

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