What is AI PDF chatbot agent built with LangChain ?
This AI PDF Chatbot agent is a customizable solution that enables users to upload and parse PDF documents, store vector embeddings in a database, and query these documents through a chat interface. It integrates with OpenAI or other LLM providers to generate answers with references to the relevant content. The system utilizes LangChain for language model orchestration and LangGraph for managing agent workflows. Its architecture includes a backend service that handles ingestion and retrieval graphs, a frontend with a Next.js UI to upload files and chat, and Supabase for vector storage. It supports real-time streaming responses and allows customization of retrievers, prompts, and storage configurations.
AI PDF chatbot agent built with LangChain Core Features
PDF document ingestion and embedding storage
Conversational retrieval with OpenAI and vector search
Real-time streaming chat responses
LangGraph orchestration for agent workflows
Next.js frontend UI with file upload and chat
AI PDF chatbot agent built with LangChain Pro & Cons
The Cons
Requires setup of vector database and API keys
No native mobile or desktop apps, web only
Initial setup complexity for beginners
Chat history is session-based, not persistent by default
Dependency on third-party APIs may incur costs
The Pros
Open-source and highly customizable
Supports powerful LLMs and vector search
Well-structured backend and frontend architecture
Real-time streaming improves interactivity
Comprehensive example with LangChain and LangGraph