Search Results for "langchain"

Elixir LangChain is an Elixir-native implementation of the LangChain concept, designed to help developers build applications powered by large language models using the Elixir ecosystem. The library focuses on enabling composable workflows where different processes, APIs, and services can be connected into structured pipelines driven by LLMs. It mirrors the architecture of traditional LangChain frameworks by providing abstractions for chains, tools, agents, and model integrations while adapting them to Elixir’s concurrency model. ...

LangChain.dart is a Dart and Flutter implementation of the LangChain framework, designed to enable developers to build LLM-powered applications for mobile, web, and cross-platform environments. It provides a structured way to integrate language models into applications by offering abstractions for chains, agents, embeddings, and vector stores. The framework supports multiple providers and includes packages for integrating with services such as OpenAI, Google AI, and Firebase, allowing developers to build both local and cloud-based AI workflows. ...

LangChain .NET is a C# implementation of the LangChain framework that enables developers to build LLM-powered applications using the .NET ecosystem. The project aims to replicate the core abstractions of LangChain, such as chains, agents, and vector stores, while adapting them to the conventions and strengths of C#. It emphasizes composability, allowing developers to build complex workflows by combining modular components that interact with language models and external data sources. ...

LangChainGo is a Go-based implementation of the LangChain framework, designed to help developers build applications powered by large language models using the Go programming language. It provides a modular architecture that allows developers to combine components such as language models, chains, agents, memory systems, and vector stores into flexible workflows. The framework emphasizes composability, making it easy to create complex pipelines that integrate LLMs with external data sources, APIs, and tools. ...

LLPhant is a PHP-based generative AI framework designed to bring large language model capabilities into modern PHP applications with a structure inspired by frameworks like LangChain. It provides developers with a set of abstractions for building AI-powered features such as chat systems, retrieval pipelines, and automated workflows while remaining simple enough to integrate into existing Symfony or Laravel projects. The framework focuses on usability by offering straightforward APIs for tasks like embeddings, question answering, and vector search, which are commonly required in real-world applications. ...

The Spring Petclinic is the canonical reference sample application built with Spring Boot and Thymeleaf, demonstrating best practices in building Spring-based web applications; forks also exist showcasing implementations with modern architectures like microservices, reactive stacks, and AI integrations. In its default configuration, Petclinic uses an in-memory database (H2) which gets populated at startup with data. The h2 console is exposed and it is possible to inspect the content of the...