DocChat-Docling is an open-source AI agent that enables users to upload multiple documents and interactively query them through a chatbot interface. Leveraging semantic search and vector embeddings, it delivers accurate, context-aware answers. It supports multiple file formats, maintains conversational context, and scales across large document sets, simplifying knowledge retrieval for diverse applications.
DocChat-Docling is an open-source AI agent that enables users to upload multiple documents and interactively query them through a chatbot interface. Leveraging semantic search and vector embeddings, it delivers accurate, context-aware answers. It supports multiple file formats, maintains conversational context, and scales across large document sets, simplifying knowledge retrieval for diverse applications.
DocChat-Docling is an AI document chatbot framework that transforms static documents into an interactive knowledge base. By ingesting PDFs, text files, and other formats, it indexes content with vector embeddings and enables natural language Q&A. Users can ask follow-up questions, and the agent retains context for accurate dialogue. Built on Python and leading LLM APIs, it offers scalable document processing, customizable pipelines, and easy integration, empowering teams to self-serve information without manual searches or complex queries.
Who will use DocChat-Docling?
Researchers
Students
Knowledge workers
Customer support teams
Developers
How to use the DocChat-Docling?
Step1: Clone the GitHub repo and install Python dependencies.
Step2: Set your OPENAI_API_KEY environment variable.
Step3: Place your documents in the designated folder.
Step4: Run the application script to start the chat interface.
Step5: Interactively query your documents in the chatbot UI.