micro-agent provides a minimalistic yet powerful set of abstractions for creating autonomous AI agents. Built in TypeScript, it runs seamlessly in both browser and Node.js contexts, allowing you to define agents with custom prompt templates, decision logic, and extensible tool integrations. Agents can leverage chain-of-thought reasoning, interact with external APIs, and maintain conversational or task-specific memory. The library includes utilities for handling API responses, error management, and session persistence. With micro-agent, developers can prototype and deploy agents for a range of tasks—such as automating workflows, building conversational interfaces, or orchestrating data-processing pipelines—without the overhead of larger frameworks. Its modular design and clear API surface make it easy to extend and integrate into existing applications.

DocGPT is designed to simplify information extraction and Q&A from documents by providing a seamless conversational interface. Users can upload documents in PDF, Word, or PowerPoint formats, which are then processed using text parsers. The content is chunked and embedded with OpenAI's embedding models, stored in a vector database like FAISS or Pinecone. When a user submits a query, DocGPT retrieves the most relevant text chunks via similarity search and leverages ChatGPT to generate accurate, context-aware responses. It features interactive chat, document summarization, customizable prompts for domain-specific needs, and is built on Python with a Streamlit UI for easy deployment and extensibility.