| 📅 Today’s Picks |
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
Full Article:
|
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
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