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.

Rags provides a modular pipeline to build retrieval-augmented generative applications. It integrates with popular vector stores (e.g., FAISS, Pinecone), offers configurable prompt templates, and includes memory modules to maintain conversational context. Developers can switch between LLM providers like Llama-2, GPT-4, and Claude2 through a unified API. Rags supports streaming responses, custom preprocessing, and evaluation hooks. Its extensible design enables seamless integration into production services, allowing automated document ingestion, semantic search, and generation tasks for chatbots, knowledge assistants, and document summarization at scale.

This innovative extension leverages the capabilities of OpenAI's advanced language model to enhance your search experience. By integrating directly with popular search engines like Google, Bing, and DuckDuckGo, it enables users to receive concise, informative answers in real-time while browsing. Whether you're seeking solutions to complex queries or just exploring new information, ChatGPT for Search offers a seamless and efficient way to make the most of your online searches.

Knower automatically performs a range of knowledge management tasks including identification, classification, indexing, and organization. With its AI algorithms, the extension can analyze content from web pages and documents, allowing users to save and retrieve information efficiently. It works seamlessly to enhance the learning experience, making it faster and easier to absorb and recall knowledge.

Knowledge Hunter acts as a knowledge assistant that transforms static online content and documents into interactive AI-driven datasets. By simply providing a URL or uploading PDF files, the plugin crawls and parses text, tables, images, and hierarchical structures. It builds semantic indexes on-the-fly, allowing ChatGPT to answer complex queries, highlight passages, and export insights. Users can ask follow-up questions, request bullet-point summaries, or deep-dive into specific sections with context retained. It supports batch processing of multiple sources, custom document tagging, and universal search capabilities. Seamlessly integrated into ChatGPT's interface, Knowledge Hunter enhances research, data analysis, and customer support by turning raw web pages and documents into a conversational knowledge base.

Leo Page Assistant leverages advanced AI technology to deliver relevant, instant answers while you browse. Whether you need a summary of a webpage, an explanation of complex terms, or quick translations, Leo is designed to assist. It operates directly within your browser for a seamless user experience, understanding context to provide the most pertinent information. This assistant not only enhances comprehension but also promotes efficiency, making it a valuable tool for students, professionals, and anyone looking to navigate the web more effectively.