langchain and LangChain-for-LLM-Application-Development
These are ecosystem siblings—one is a language-specific implementation (Elixir) of the LangChain framework architecture, while the other is a Python educational resource for applying LangChain's core patterns (agents, chains, memories) to LLM applications.
About langchain
brainlid/langchain
Elixir implementation of a LangChain style framework that lets Elixir projects integrate with and leverage LLMs.
Supports multiple LLM providers (OpenAI, Claude, Gemini, Grok, Ollama, and local models via Bumblebee) with a modular component architecture that prioritizes functional design patterns over object-oriented parity with JavaScript/Python ports. Built around the `LLMChain` abstraction for composing language models with data sources and tool integrations, with features like prompt caching across providers and streaming response support.
About LangChain-for-LLM-Application-Development
ksm26/LangChain-for-LLM-Application-Development
Apply LLMs to your data, build personal assistants, and expand your use of LLMs with agents, chains, and memories.
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