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Use Case Library
How to use a Gaia node as the backend service
for an agent framework or app, replacing the OpenAI API.
Use Case Library
How to use a Gaia node as the backend service
for an agent framework or app, replacing the OpenAI API.
Working with Eliza framework
Recently, eliza has integrated Gaia as one of the model service provider. This means you can now use Gaia as the LLM service backend for the Eliza framework.
Working with Coinbase AgentKit
You can use a Gaia node to power the Coinbase AgentKit.
OpenAI ecosystem apps
Since each GaiaNet node provides an OpenAI-compatible API service, it can be a drop-in replacement for OpenAI in almost all LLM applications and frameworks. Checkout the articles in this section for instructions and examples for how to use GaiaNet in popular LLM apps.
Dify + GaiaNet
You can configure the Dify framework using any GaiaNet node as the backend LLM API. That allows you to use your own or community GaiaNet nodes in any application built on Dify.
Open WebUI
You can configure the Open WebUI framework, a self-hosted WebUI, using any GaiaNet node as the backend LLM API. That allows you to use your own or community GaiaNet nodes in any application built on Open WebUI.
Anything LLM
Anything LLM is the all-in-one Desktop & Docker AI application with full RAG and AI Agent capabilities. You can configure Anything LLM using the GaiaNet node as the LLM backend.
FlowiseAI RAG chat
FlowiseAI is a low-code tool for developers to build customized LLM orchestration flows & AI agents. You can configure the FlowiseAI tool to use Gaia nodes as LLM service providers.
FlowiseAI tool call
FlowiseAI is a low-code tool for developers to build customized LLM orchestration flows & AI agents. You can configure the FlowiseAI tool to use a Gaia node that supports LLM tool calling.
LobeChat
You can configure LobeChat to use a GaiaNet node as its backend LLM API. It provides a richer and more customizable UI than the default GaiaNet chatbot UI.
LlamaCloud
LlamaParse is an API created by LlamaIndex to efficiently parse and represent files for efficient retrieval and context augmentation using LlamaIndex frameworks. LlamaParse can support different kinds of files, like pdf, doc, ppt, and other formats.
Obsidian
Obsidian is a note-taking application that enables users to create, link, and visualize ideas directly on their devices. With Obsidian, you can seamlessly sync notes across devices, publish your work, and collaborate with others. The app is highly customizable, allowing users to enhance functionality through a wide range of plugins and themes. Its unique features include a graph view to visualize connections between notes, making it ideal for managing complex information and fostering creativity. Obsidian also emphasizes data privacy by storing notes locally.
AI coding assistant: Continue
Continue is the leading open-source AI code assistant. It is a copilot-like plugin for VSCode and JetBrains to provide custom autocomplete and chat experiences inside those IDEs. You can easily configure it to use Gaia nodes as LLM backends.
Translation Agent + GaiaNet
The Translation Agent originally built by Prof. Andrew Ng, is designed to facilitate accurate and efficient translation across multiple languages. It employs open source LLMs (Large Language Models) to provide high-quality translations. You can use any GaiaNet node as the LLM backend.
A planning agent
The gpt planner is a Python application that demonstrate the planning capabilities of LLMs. When you run it, it will ask the LLM to generate multiple action plans for a goal or a query. It will then ask the LLM to compare and select the best plan, and then rewrite it to answer the user query.
LlamaEdgeBook
LlamaEdgeBook, forked from GroqBook, is an open-source tool that scaffolds the creation of books from a one-line prompt using open-source LLMs. You can configure the LlamaEdgeBook framework using any GaiaNet node as the backend LLM API.
LlamaTutor
The LlamaTutor is a TypeScript application using Llama 3.1 to act as an open-source AI personal tutor. When you run it, it will ask the LLM to search on the web based on your inquiry topic and then generate content for you to learn.
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