{"repo":"waseemhnyc/instagraph-nextjs-fastapi","free":true,"listed":false,"github":"https://github.com/waseemhnyc/instagraph-nextjs-fastapi","clone":"git clone https://github.com/waseemhnyc/instagraph-nextjs-fastapi.git","description":"Generate knowledge graphs. Inspired by @yoheinakajima instagraph.ai","language":"TypeScript","stars":143,"topics":["nextjs","openai","vercel","fastapi","python"],"license":"MIT","category":"ai-agents","readme_excerpt":"InstaGraph 🌐 Next JS and FastAPI Original project and inspiration: Yohei Nakajima - Instagraph Even though I love working with Python apps (previous Django developer), modern frontend technologies like NextJS (and Tailwind CSS, Shadcn etc) enable you to move faster. Also with the popularity of LLMs, streaming and server-sent-endpoints have become more important in AI products. FastAPI is perfect for building backends to support this. Sign up for updates and more information about the deployed app. ) Project made with: - Shadcn - Next JS Template - React Flow Installation 🛠️ 1. Clone the repository 2. Navigate to the project directory 3. Install packages 4. Set environment variables 5. Run Next JS app Now that the frontend is working, it's time to get the backend up and running. 6. Move into the api directory, create a virutalenv and source the environment 7. Install libraries 8. Create a .env file and input your OpenAI API Key in the file 9. Run local server Usage 🎉 Web Interface - Open your web browser and navigate to http://localhost:3000/ . - Type your text in the input box. - Click \"Submit\" and wait for the magic to happen! License 📝 MIT License. See LICENSE for more information.","default_branch":null,"files":null,"tree":[],"storefront":"/r/waseemhnyc","claimed":false,"request_supported":{"post":"https://gitbuyer.com/r/waseemhnyc/instagraph-nextjs-fastapi/request-supported","requests":0},"note":"indexed from public GitHub; nothing is for sale on this page. Clone it from GitHub. Paid listings live at /search."}