AgentReader is a developer-friendly AI agent framework that enables you to load and index various data sources such as PDFs, text files, markdown documents, and web pages. It integrates seamlessly with major LLM providers to power interactive chat sessions and question-answering over your knowledge base. Features include real-time streaming of model responses, customizable retrieval pipelines, web scraping via headless browser, and a plugin architecture for extending ingestion and processing capabilities.

Saga provides a flexible architecture for building AI agents that plan and execute multi-step workflows. Core components include a planner module that breaks goals into actions, a memory store for conversational and task context, and a tool registry for integrating external services or scripts. Agents run asynchronously, manage state across sessions, and support custom tool development. Saga enables rapid prototyping of autonomous assistants, automating tasks such as data collection, alerting, and interactive Q&A within your own Python environment.