langchain and LangChain-for-LLM-Application-Development
An Elixir framework implementation and an educational course/tutorial repository are ecosystem siblings, as both provide different entry points (language binding vs. learning resource) into the LangChain ecosystem rather than competing or being used together.
About langchain
brainlid/langchain
Elixir implementation of a LangChain style framework that lets Elixir projects integrate with and leverage LLMs.
This project helps Elixir developers integrate advanced AI capabilities into their applications. It takes input from various large language models (LLMs) like OpenAI, Anthropic, or locally hosted models and allows you to chain them together with other application logic. The result is more intelligent, data-aware, and agentic Elixir applications that can understand and interact with their environment.
About LangChain-for-LLM-Application-Development
Ryota-Kawamura/LangChain-for-LLM-Application-Development
In LangChain for LLM Application Development, you will gain essential skills in expanding the use cases and capabilities of language models in application development using the LangChain framework.
This course teaches developers how to build sophisticated applications using large language models (LLMs) and the LangChain framework. It covers how to integrate LLMs into applications, manage conversation history, chain multiple operations, and perform question-answering on custom data. The target audience is software developers looking to leverage LLMs for new application functionalities.
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