GoLC is an open-source Go library that simplifies building LLM-driven pipelines and conversational agents. It offers modular chains, prompt templating, document loaders, vector store integration, retrieval-augmented generation, memory modules, and custom tool-based agent workflows. Developers can seamlessly configure LLM providers, incorporate embedding-based search, and manage conversation state across sessions. GoLC empowers backend engineers to rapidly prototype AI assistants, knowledge bots, and automation agents within a Go-native environment.
GoLC is an open-source Go library that simplifies building LLM-driven pipelines and conversational agents. It offers modular chains, prompt templating, document loaders, vector store integration, retrieval-augmented generation, memory modules, and custom tool-based agent workflows. Developers can seamlessly configure LLM providers, incorporate embedding-based search, and manage conversation state across sessions. GoLC empowers backend engineers to rapidly prototype AI assistants, knowledge bots, and automation agents within a Go-native environment.
GoLC provides developers with a comprehensive toolkit for constructing language model chains and agents in Go. At its core, it includes chain management, customizable prompt templates, and seamless integration with major LLM providers. Through document loaders and vector stores, GoLC enables embedding-based retrieval, powering RAG workflows. The framework supports stateful memory modules for conversational contexts and a lightweight agent architecture to orchestrate multi-step reasoning and tool invocations. Its modular design allows plugging in custom tools, data sources, and output handlers. With Go-native performance and minimal dependencies, GoLC streamlines AI pipeline development, making it ideal for building chatbots, knowledge assistants, automated reasoning agents, and production-grade backend AI services in Go.
Who will use GoLC?
Go developers building AI applications
ML engineers seeking Go-native LLM tooling
Backend engineers integrating AI services
Startups prototyping conversational agents
Researchers implementing RAG systems
How to use the GoLC?
Step1: Install GoLC with `go get github.com/hupe1980/golc`
Step2: Import GoLC modules and configure your LLM provider API key
Step3: Define prompt templates and chain components in Go code
Step4: Set up document loaders and vector store for retrieval use cases
Step5: Compose chains or agents, attach memory modules and tools
Step6: Execute the chain or agent and handle responses in your application