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4 dépôts

Awesome GitHub RepositoriesStructured Collection Streams

Yields individual items from a generated list incrementally to reduce latency.

Distinct from Real-Time Data Streaming: Distinct from Real-Time Data Streaming: focuses on streaming structured list items from LLM outputs rather than general event-driven data.

Explore 4 awesome GitHub repositories matching data & databases · Structured Collection Streams. Refine with filters or upvote what's useful.

Awesome Structured Collection Streams GitHub Repositories

Trouvez les meilleurs dépôts grâce à l'IA.Nous recherchons les dépôts les plus pertinents grâce à l'IA.
  • instructor-ai/instructorAvatar de instructor-ai

    instructor-ai/instructor

    13,181Voir sur GitHub↗

    Instructor is a schema enforcement and validation library designed to transform language model outputs into structured, type-safe data formats. It functions as a validation layer that uses Pydantic to ensure model responses conform to specific data models, acting as a tool for forcing large language models to return data in predefined schemas. The project differentiates itself through a recursive error-feedback loop that automatically retries requests when structural errors occur, passing validation failure messages back to the model to guide corrections. It also includes a streaming parser c

    Processes fragments of structured objects incrementally as they are generated by the model.

    Python
    Voir sur GitHub↗13,181
  • 567-labs/instructorAvatar de 567-labs

    567-labs/instructor

    13,176Voir sur GitHub↗

    Instructor is a framework designed for structured data extraction, validation, and language model integration. It functions as a library that transforms unstructured text into validated, type-safe objects by leveraging schema definitions and model-specific tool-calling capabilities. By acting as a validation middleware, the project ensures that language model outputs strictly conform to defined data structures. The library distinguishes itself through a robust validation-based retry loop that automatically re-submits failed responses with error feedback to iteratively correct schema complianc

    Yields individual items from a generated list incrementally to reduce latency.

    Pythonopenaiopenai-function-calliopenai-functions
    Voir sur GitHub↗13,176
  • reactivex/rxkotlinAvatar de ReactiveX

    ReactiveX/RxKotlin

    7,041Voir sur GitHub↗

    RxKotlin is a reactive programming library and asynchronous stream processor that provides Kotlin language extensions for composing event-based data streams. It serves as a set of Kotlin bindings for RxJava, allowing developers to transform, filter, and flatten sequences of data emitted over time. The library focuses on integrating RxJava patterns into Kotlin projects by applying language-specific conventions and idioms. It utilizes extension functions to simplify reactive programming patterns, reduce boilerplate, and optimize workflows within the reactive ecosystem. The toolkit covers a bro

    Transforms arrays, iterables, and iterators into asynchronous streams for reactive processing.

    Kotlinkotlinrxjava
    Voir sur GitHub↗7,041
  • messagepack-csharp/messagepack-csharpAvatar de MessagePack-CSharp

    MessagePack-CSharp/MessagePack-CSharp

    6,607Voir sur GitHub↗

    MessagePack-CSharp is a high-performance binary serializer for .NET that converts C# objects to and from the compact MessagePack format. It uses compile-time source generation to produce AOT-safe formatters and resolvers, eliminating runtime reflection and enabling ahead-of-time compilation scenarios. The serializer encodes object fields as integer indices instead of string keys, producing compact binary output with deterministic field ordering, and provides stack-allocated reader and writer structs for direct encoding and decoding of MessagePack primitives without heap allocations. The libra

    Reads consecutive MessagePack structures from a single stream using boundary-aware reading.

    C#c-sharplz4messagepack
    Voir sur GitHub↗6,607
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  2. Data & Databases
  3. Real-Time Data Streaming
  4. Structured Collection Streams

Explorer les sous-tags

  • Collection-to-Stream ConversionTransformation of standard collection types into incremental data streams. **Distinct from Structured Collection Streams:** Focuses on converting generic collections to streams, unlike the LLM-specific structured output of the candidate.