Documentation Index
Fetch the complete documentation index at: https://docs.livepeer.org/llms.txt
Use this file to discover all available pages before exploring further.
This tutorial is adapted from the Livepeer Agent SPE guide on Mirror.xyz, published as part of the Agent SPE incentive programme. The original tutorial was written by the Agent SPE team and made available under an open licence.
meta-llama/Meta-Llama-3.1-8B-Instruct (or any Ollama-compatible model) on the network.
Prerequisites
- Node.js 22 or later
- pnpm (
npm install -g pnpm) - For development: no API key required (the community gateway at
dream-gateway.livepeer.cloudis unauthenticated) - For production: an API key from a gateway provider
Build your agent
Extending the agent
Switch the model. Changesettings.model in your character file to any Ollama-compatible model available on the Livepeer network. See model support for supported variants and warm availability.
Add memory and knowledge. Eliza supports RAG (retrieval-augmented generation) via knowledge files and vector stores. Add entries to the knowledge array in your character file to give the agent domain-specific context.
Integrate with Slack or Discord. The Eliza framework includes client connectors for Slack, Discord, and Twitter. Add "slack" or "discord" to the clients array and configure the respective credentials in .env.
Build a multi-agent swarm. The SwarmZero framework integrates with Livepeer’s inference APIs and supports multi-agent orchestration. See the SwarmZero Livepeer example for a working YouTube video generator swarm.
Supported LLM models
The Livepeer LLM pipeline uses an Ollama-based runner. Any Ollama-compatible model works. Warm models respond immediately; cold models load on the first request (30 seconds to 5 minutes).| Model | Warm on network | VRAM required |
|---|---|---|
meta-llama/Meta-Llama-3.1-8B-Instruct | Yes | 8 GB |
mistralai/Mistral-7B-Instruct-v0.3 | Check network | 8 GB |
google/gemma-2-9b-it | Check network | 10 GB |
Qwen/Qwen2.5-7B-Instruct | Check network | 8 GB |