Python¶

2024/09/26
in Anthropic, LLM Techniques, Python
4 min read

Implementing Anthropic's Contextual Retrieval with Async Processing

Anthropic's Contextual Retrieval technique enhances RAG systems by preserving crucial context.

This post examines the method and demonstrates an efficient implementation using async processing. We'll explore how to optimize your RAG applications with this approach, building on concepts from our async processing guide.

2023/10/23
in Pydantic, Data Validation, Python
11 min read

Good LLM Validation is Just Good Validation

What if your validation logic could learn and adapt like a human, but operate at the speed of software? This is the future of validation and it's already here.

Validation is the backbone of reliable software. But traditional methods are static, rule-based, and can't adapt to new challenges. This post looks at how to bring dynamic, machine learning-driven validation into your software stack using Python libraries like Pydantic and Instructor. We validate these outputs using a validation function which conforms to the structure seen below.

def validation_function(value):
    if condition(value):
        raise ValueError("Value is not valid")
    return mutation(value)