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Newsletter #269: LangChain v1.2.0: Build Multi-Provider Agents with Extras

Newsletter #269: LangChain v1.2.0: Build Multi-Provider Agents with Extras


๐Ÿ“… Today’s Picks

LangChain v1.2.0: Build Multi-Provider Agents with Extras

Code example: LangChain v1.2.0: Build Multi-Provider Agents with Extras

Problem

Different LLM providers require different tool configurations: parallel vs sequential execution, strict mode, token limits.

This creates scattered configs and manual provider switching throughout your code.

Solution

LangChain v1.2.0 introduces the extras attribute that attaches provider-specific configurations directly to tool definitions.

With extras, you can:

  • Define all provider configs in one place
  • Switch providers without touching multiple files
  • Keep configs in sync across environments

GLiNER: Extract Any Entity Type with Zero-Shot NER

Code example: GLiNER: Extract Any Entity Type with Zero-Shot NER

Problem

Named Entity Recognition (NER) extracts key information like names, dates, and organizations from text. But standard models are limited to predefined entity types like PERSON, ORG, and DATE.

If you need to extract something specific, you’d normally have to train a custom model with thousands of labeled examples.

Solution

GLiNER changes that with zero-shot entity extraction, allowing you to extract any entity type without training.

Key benefits:

  • Works out-of-the-box with any text domain
  • Handles multiple entity types in a single pass
  • Returns confidence scores for each extraction
  • Integrates with spaCy and other NLP pipelines

โ˜•๏ธ Weekly Finds

timescaledb [Data Engineer] – PostgreSQL extension for high-performance real-time analytics on time-series and event data

slim [MLOps] – Inspect, optimize, and minify Docker container images without sacrificing functionality

drawdb [Data Engineer] – Free, simple, and intuitive online database diagram editor and SQL generator

Looking for a specific tool? Explore 70+ Python tools โ†’

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    Work with Khuyen Tran