tablegpt/tablegpt-agent
A pre-built agent for TableGPT2.
What it solves
It provides a user-friendly interface and agentic framework for interacting with TableGPT2, a series of Large Multimodal Models (LMMs) specifically designed for table-based question answering.
How it works
The agent is built using the Langgraph library, acting as a pre-built wrapper that enables users to query and interact with the TableGPT2 models to extract answers from tabular data.
Who it’s for
Developers and researchers who want to implement table-based question answering systems using the TableGPT2 model series.
Highlights
- Built on top of Langgraph for agentic capabilities.
- Integrated with TableGPT2 models for specialized tabular data processing.
- Includes evaluation scripts and datasets for table-related benchmarks via the
realtabbench directory.
Related
- Project
langchain-ai/react-agentA LangGraph template for implementing a ReAct agent that iteratively reasons and executes tool-based actions to solve complex user queries.
- Project
GiovanniPasq/agentic-rag-for-dummiesThe repository provides a concrete, modular example of an Agentic Retrieval‑Augmented Generation (RAG) system built with LangGraph. It covers hierarchical document indexing, multi‑agent query processing, human‑in‑the‑loop clarification, and supports multiple LLM providers (default Ollama). Includes notebooks for setup, evaluation, and observability, making it a solid learning and prototyping resource.
- Project
cqzyys/lang-agentA visual configuration platform based on LangGraph that allows users to build complex AI agents using a drag-and-drop interface with customizable state variables for precise logic control.
- Project
JoshuaC215/agent-service-toolkitA template for building and running AI agents with LangGraph, served via FastAPI and accessed through a Streamlit chat UI. Includes Docker support, multiple agents, RAG, streaming, AG‑UI protocol, and extensible client library.
- Project
CopilotKit/open-multi-agent-canvasAn open-source multi-agent chat interface that lets users manage multiple AI agents in one dynamic conversation using Next.js, LangGraph, and CopilotKit.