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open-research-ANA

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Basic Information

open-research-ANA is a demo Agent Native Application (ANA) that provides a research-focused canvas combining human-in-the-loop workflows with real-time search and an agentic interface. The project showcases how to orchestrate an interactive research agent using LangGraph for orchestration, Tavily for real-time search, and CopilotKit for the agent interface. The repository contains two main components to run locally: an agent service and a frontend application. The README documents prerequisites, required API keys, and step-by-step local startup commands so developers and researchers can run the demo, open a tunnel to a locally running agent, and interact with the canvas. It is positioned as a practical example for building and experimenting with interactive, agent-driven research tools rather than a production product.

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App URL
https://github.com/CopilotKit/open-research-ANA
Github Repository
https://github.com/CopilotKit/open-research-ANA/blob/main/README.md

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App Details

Features
The README highlights a set of concrete features and integrations demonstrated by the demo. It integrates Tavily to provide real-time search capabilities and CopilotKit to supply an agentic, human-facing interface. LangGraph is used to define and run the agent orchestration. The repo separates agent and frontend components, with instructions to run the agent via langgraph up and the frontend via pnpm run dev. Development tooling and environment requirements are listed, including pnpm, Docker, and the LangGraph CLI. The README also documents how to create environment files with required API keys and demonstrates opening a tunnel to the local agent using a CopilotKit CLI command for local testing.
Use Cases
This repository is helpful as a hands-on reference and starting point for building interactive research agents that combine automated retrieval with human oversight. It simplifies complex research tasks by wiring together a search service, an agentic UI, and LangGraph orchestration so users can prototype workflows that involve real-time search and human-in-the-loop adjustments. The provided quick start steps, explicit API key requirements, and runtime commands reduce setup friction for developers and researchers who want to explore agent-native interfaces and end-to-end demos. Because the project is a demo, it is useful for learning integration patterns, testing local deployments, and iterating on research-oriented agent interfaces.

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