base on # 🏔️🤖 3D-GPT: Procedural 3D Modeling with Large Language Models **🏆 3DV Conference**  ## 👥 Authors **Chunyi Sun👩**\*, **Junlin Han👱**\*, Weijian Deng👱, Xinlong Wang👱, Zishan Qin👩, Stephen Gould‍️👨‍🦱 ## 🔗 Project Page [https://chuny1.github.io/3DGPT/3dgpt.html](https://chuny1.github.io/3DGPT/3dgpt.html) --- ## 🚀 Current & Upcoming Releases This repository is part of the official implementation of our paper, **3D-GPT: Procedural 3D Modeling with Large Language Models**. We are gradually releasing different components of our project according to the following plan: ### ✅ Current Release: Agent Implementation We are currently releasing the agent implementation, which includes: - The core agent logic - Example usage demonstrating how to call the agent to generate a Python script that can control the **Infinigen** generation. - The `LLM/agents/` directory contains the implementation of two agents. - The `LLM/documents/` directory contains the example function documentation format, where you can add functions as many as you want. - Running `LLM/parser.py` will provide detailed output about how different agents interact with each other and how it infers function parameters. ### 🔜 Upcoming Releases We have made significant modifications to many functions, making them easier for LLMs to understand while enhancing their control capabilities. Our upcoming releases include: - **Modified Infinigen (by March 25, before 3DV conference)**: We will provide our modified version of **Infinigen**, improving its adaptability to LLM-generated scripts. - **LLM Parser Enhancement**: Instead of generating Python scripts, the LLM parser will generate a **configuration file** to control Infinigen. This change will make the process more user-friendly and support **human-assisted editing**. Stay tuned for these updates! --- ## 🛠 Installation & Usage Follow the instructions below to set up and run the current release: ### 1️⃣ Install Infinigen Follow the official Infinigen repository for installation and setup: [https://github.com/princeton-vl/infinigen](https://github.com/princeton-vl/infinigen) ### 2️⃣ Install Dependencies ```bash # Clone the repository git clone [email protected]:Chuny1/3DGPT.git # Install required Python packages pip install openai==0.27.8 ``` ### 3️⃣ Setup OpenAI API Key To use OpenAI's LLMs, you need to obtain an API key: - Visit the OpenAI website and generate an API key. - Add your personal API key to `parser.py`. **Do not share your API key.**  ### 4️⃣ Choose GPT Model You can select the GPT model you want to use by visiting: [https://platform.openai.com/docs/api-reference/chat](https://platform.openai.com/docs/api-reference/chat) ### 5️⃣ Run the Agent ```bash python LLM/parser.py ``` --- ## 📚 Citation If you find this work useful, please consider citing our paper: ``` @article{sun20233d, title={3d-gpt: Procedural 3d modeling with large language models}, author={Sun, Chunyi and Han, Junlin and Deng, Weijian and Wang, Xinlong and Qin, Zishan and Gould, Stephen}, journal={arXiv preprint arXiv:2310.12945}, year={2023} } ``` ", Assign "at most 3 tags" to the expected json: {"id":"4170","tags":[]} "only from the tags list I provide: [{"id":77,"name":"3d"},{"id":89,"name":"agent"},{"id":17,"name":"ai"},{"id":54,"name":"algorithm"},{"id":24,"name":"api"},{"id":44,"name":"authentication"},{"id":3,"name":"aws"},{"id":27,"name":"backend"},{"id":60,"name":"benchmark"},{"id":72,"name":"best-practices"},{"id":39,"name":"bitcoin"},{"id":37,"name":"blockchain"},{"id":1,"name":"blog"},{"id":45,"name":"bundler"},{"id":58,"name":"cache"},{"id":21,"name":"chat"},{"id":49,"name":"cicd"},{"id":4,"name":"cli"},{"id":64,"name":"cloud-native"},{"id":48,"name":"cms"},{"id":61,"name":"compiler"},{"id":68,"name":"containerization"},{"id":92,"name":"crm"},{"id":34,"name":"data"},{"id":47,"name":"database"},{"id":8,"name":"declarative-gui "},{"id":9,"name":"deploy-tool"},{"id":53,"name":"desktop-app"},{"id":6,"name":"dev-exp-lib"},{"id":59,"name":"dev-tool"},{"id":13,"name":"ecommerce"},{"id":26,"name":"editor"},{"id":66,"name":"emulator"},{"id":62,"name":"filesystem"},{"id":80,"name":"finance"},{"id":15,"name":"firmware"},{"id":73,"name":"for-fun"},{"id":2,"name":"framework"},{"id":11,"name":"frontend"},{"id":22,"name":"game"},{"id":81,"name":"game-engine "},{"id":23,"name":"graphql"},{"id":84,"name":"gui"},{"id":91,"name":"http"},{"id":5,"name":"http-client"},{"id":51,"name":"iac"},{"id":30,"name":"ide"},{"id":78,"name":"iot"},{"id":40,"name":"json"},{"id":83,"name":"julian"},{"id":38,"name":"k8s"},{"id":31,"name":"language"},{"id":10,"name":"learning-resource"},{"id":33,"name":"lib"},{"id":41,"name":"linter"},{"id":28,"name":"lms"},{"id":16,"name":"logging"},{"id":76,"name":"low-code"},{"id":90,"name":"message-queue"},{"id":42,"name":"mobile-app"},{"id":18,"name":"monitoring"},{"id":36,"name":"networking"},{"id":7,"name":"node-version"},{"id":55,"name":"nosql"},{"id":57,"name":"observability"},{"id":46,"name":"orm"},{"id":52,"name":"os"},{"id":14,"name":"parser"},{"id":74,"name":"react"},{"id":82,"name":"real-time"},{"id":56,"name":"robot"},{"id":65,"name":"runtime"},{"id":32,"name":"sdk"},{"id":71,"name":"search"},{"id":63,"name":"secrets"},{"id":25,"name":"security"},{"id":85,"name":"server"},{"id":86,"name":"serverless"},{"id":70,"name":"storage"},{"id":75,"name":"system-design"},{"id":79,"name":"terminal"},{"id":29,"name":"testing"},{"id":12,"name":"ui"},{"id":50,"name":"ux"},{"id":88,"name":"video"},{"id":20,"name":"web-app"},{"id":35,"name":"web-server"},{"id":43,"name":"webassembly"},{"id":69,"name":"workflow"},{"id":87,"name":"yaml"}]" returns me the "expected json"