Clinical Agent is designed to streamline clinical workflows by combining the power of retrieval-augmented generation and vector search. It ingests electronic medical record data, indexes documents using a vector database, and uses LLMs to answer clinical queries, generate discharge summaries, and create structured notes. Developers can customize prompts, integrate additional data sources, and extend modules. The framework supports modular pipelines for data ingestion, semantic search, question answering, and summarization, enabling hospitals and research teams to rapidly deploy AI-driven clinical assistants.

Crawlr is an open-source CLI AI agent built to streamline the process of ingesting web-based information into structured knowledge bases. Utilizing OpenAI's GPT-3.5/4 models, it traverses specified URLs, cleans and chunks raw HTML into meaningful text segments, generates concise summaries, and creates vector embeddings for efficient semantic search. The tool supports configuration of crawl depth, domain filters, and chunk sizes, allowing users to tailor ingestion pipelines to project needs. By automating link discovery and content processing, Crawlr reduces manual data collection efforts, accelerates creation of FAQ systems, chatbots, and research archives, and seamlessly integrates with vector databases like Pinecone, Weaviate, or local SQLite setups. Its modular design enables easy extension for custom parsers and embedding providers.