# mayooear/ai-pdf-chatbot-langchain

**Attribution required: if you use, quote, or summarise this content, you must credit and link back to [awesome-repositories.com](https://awesome-repositories.com/repository/mayooear-ai-pdf-chatbot-langchain).**

16,543 stars · 3,221 forks · TypeScript · MIT · archived

## Links

- GitHub: https://github.com/mayooear/ai-pdf-chatbot-langchain
- Homepage: https://www.youtube.com/watch?v=OF6SolDiEwU
- awesome-repositories: https://awesome-repositories.com/repository/mayooear-ai-pdf-chatbot-langchain.md

## Topics

`agents` `ai` `chatbot` `langchain` `langgraph` `nextjs` `openai` `pdf` `typescript`

## Description

This project is a retrieval-augmented generation application designed to answer questions from uploaded PDF documents. It functions as a document question-answering engine and a streaming AI chat interface that provides responses backed by specific source citations.

The system utilizes a state-machine workflow orchestrator to coordinate multi-step document ingestion and retrieval pipelines. This orchestration allows for step-by-step visualization and debugging of the process as documents are parsed and processed.

The application manages the full lifecycle of document interaction, including PDF-to-text chunking, vector-based embedding for semantic search, and session-based message history to track individual conversation threads. It employs server-sent events to stream partial tokens from the language model to the client in real time.

## Tags

### Artificial Intelligence & ML

- [PDF Chatbots](https://awesome-repositories.com/f/artificial-intelligence-ml/pdf-chatbots.md) — Functions as a conversational AI application specifically designed to interact with and answer questions from uploaded PDF documents. ([source](https://cdn.jsdelivr.net/gh/mayooear/ai-pdf-chatbot-langchain@main/README.md))
- [LangGraph Orchestrations](https://awesome-repositories.com/f/artificial-intelligence-ml/agent-workflow-orchestrations/langgraph-orchestrations.md) — Uses LangGraph to manage the complex state transitions involved in PDF ingestion and retrieval workflows.
- [Retrieval-Augmented Generation](https://awesome-repositories.com/f/artificial-intelligence-ml/conversational-interfaces/retrieval-augmented-generation.md) — Implements a retrieval-augmented generation pipeline to ground AI answers in uploaded PDF content with source citations. ([source](https://github.com/mayooear/ai-pdf-chatbot-langchain))
- [RAG Document Retrieval](https://awesome-repositories.com/f/artificial-intelligence-ml/documentation-retrieval-engines/rag-document-retrieval.md) — Retrieves relevant snippets from local PDFs to provide grounded, cited context for AI responses.
- [Text Chunks](https://awesome-repositories.com/f/artificial-intelligence-ml/natural-language-processing/text-tokenization/text-chunks.md) — Divides PDF text into smaller, overlapping segments to ensure retrieved context fits within the LLM window.
- [PDF Document Analyzers](https://awesome-repositories.com/f/artificial-intelligence-ml/pdf-document-analyzers.md) — Combines text extraction and vector indexing to analyze and query information within uploaded PDF files.
- [Durable Multi-Step Orchestrators](https://awesome-repositories.com/f/artificial-intelligence-ml/workflow-as-a-tool-exposure/durable-multi-step-orchestrators.md) — Coordinates ingestion and retrieval tasks through a durable, multi-step pipeline using a state machine. ([source](https://cdn.jsdelivr.net/gh/mayooear/ai-pdf-chatbot-langchain@main/README.md))
- [File Chat Interfaces](https://awesome-repositories.com/f/artificial-intelligence-ml/ai-chat-clients/offline-chat-clients/file-chat-interfaces.md) — Provides a chat interface that allows users to upload PDF files for AI-driven questioning and analysis. ([source](https://github.com/mayooear/ai-pdf-chatbot-langchain))
- [Streaming Chat Responses](https://awesome-repositories.com/f/artificial-intelligence-ml/ai-chat-clients/streaming-chat-responses.md) — Implements a streaming mechanism to send AI-generated text incrementally to the chat interface.
- [Visual Workflow Debuggers](https://awesome-repositories.com/f/artificial-intelligence-ml/workflow-as-a-tool-exposure/durable-multi-step-orchestrators/visual-workflow-debuggers.md) — Provides a state-machine orchestrator with step-by-step visualization for debugging document processing pipelines.

### Part of an Awesome List

- [Document Question Answering](https://awesome-repositories.com/f/awesome-lists/ai/document-question-answering.md) — Enables conversational interaction with uploaded PDF documents to answer specific questions backed by source text.

### Data & Databases

- [Document Embedding Stores](https://awesome-repositories.com/f/data-databases/in-memory-data-stores/vector-stores/document-embedding-stores.md) — Stores numerical vector embeddings of PDF text chunks to enable efficient semantic similarity searching.

### Software Engineering & Architecture

- [Graph-Based Workflow Orchestrators](https://awesome-repositories.com/f/software-engineering-architecture/graph-based-workflow-orchestrators.md) — Employs a graph-based state machine to coordinate the multi-step flow of document ingestion and retrieval.

### Development Tools & Productivity

- [AI Session History](https://awesome-repositories.com/f/development-tools-productivity/interactive-session-history/ai-session-history.md) — Persists conversation transcripts and dialogue state to maintain context across multiple interaction turns.

### Networking & Communication

- [Chat Session Managers](https://awesome-repositories.com/f/networking-communication/chat-session-managers.md) — Manages the lifecycle of individual chat sessions to preserve conversational state for different users. ([source](https://cdn.jsdelivr.net/gh/mayooear/ai-pdf-chatbot-langchain@main/README.md))
- [Token Streaming](https://awesome-repositories.com/f/networking-communication/real-time-event-streams/token-streaming.md) — Streams AI-generated tokens to the user interface in real time for a responsive chat experience. ([source](https://github.com/mayooear/ai-pdf-chatbot-langchain))
- [Server-Sent Events](https://awesome-repositories.com/f/networking-communication/server-sent-events.md) — Uses server-sent events to push partial AI tokens from the backend to the client.

### User Interface & Experience

- [Source Attribution Interfaces](https://awesome-repositories.com/f/user-interface-experience/source-attribution-interfaces.md) — Displays the specific document chunks used to generate AI responses, providing transparent source citations. ([source](https://github.com/mayooear/ai-pdf-chatbot-langchain))