LangChain.rb is the Ruby implementation of the popular LangChain pattern, designed to orchestrate Large Language Models and related AI tools within Rails applications.
It provides abstractions for prompts, chains, agents, tools, memory, and vector databases, making it possible to build advanced features such as conversational chatbots, summarisation services, and semantic search directly in Rails.
Setup involves installing the gem, configuring your API keys (e.g., OpenAI) via environment variables, and using service objects or controllers to wire up chains.
It integrates well with pgvector or external vector stores for embeddings.
The project is actively maintained, with community support through GitHub discussions and issues. Its strengths are rapid prototyping and structured abstractions, while its weaknesses include an additional layer of complexity that may be unnecessary for very simple use cases.
Alternatives include using the ruby-openai gem directly for low-level API access or combining smaller gems for embeddings and vector search.
It provides abstractions for prompts, chains, agents, tools, memory, and vector databases, making it possible to build advanced features such as conversational chatbots, summarisation services, and semantic search directly in Rails.
Setup involves installing the gem, configuring your API keys (e.g., OpenAI) via environment variables, and using service objects or controllers to wire up chains.
It integrates well with pgvector or external vector stores for embeddings.
The project is actively maintained, with community support through GitHub discussions and issues. Its strengths are rapid prototyping and structured abstractions, while its weaknesses include an additional layer of complexity that may be unnecessary for very simple use cases.
Alternatives include using the ruby-openai gem directly for low-level API access or combining smaller gems for embeddings and vector search.