langchain and chainlite
These are ecosystem siblings—one is a language-specific implementation of the LangChain framework pattern (Elixir), while the other is a lightweight wrapper that combines LangChain abstractions with LiteLLM's multi-provider LLM interface, both serving different use cases within the broader LangChain ecosystem.
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 chainlite
stanford-oval/chainlite
LangChain + LiteLLM that works
This project helps Python developers build applications that use large language models (LLMs) by simplifying the process of sending prompts and receiving responses. It takes a prompt template file and user-defined inputs, then delivers the LLM's text output. Developers creating LLM-powered features or applications for their end-users would find this useful.
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