📄️ Introduction to LLM Configuration
Every agent has its own LLM. You can mix providers inside a single team: a premium model for the facilitator that orchestrates everything, cheap or local models for experts that do simple lookups. This saves money, improves diversity of reasoning, and protects against single-vendor outages.
📄️ LLM Hosting Options
Three shapes for where LLM inference runs. This page is the decision guide — pick an option, then jump to the per-option reference for configuration details.
📄️ Hosted Providers
Configuration reference for every LLM provider reachable over HTTP. The dashboard asks for the same four fields regardless of provider — Provider, API URL, Model, API Key — only the values change. Configure from ⋮ → Manage LLM settings on any agent.
📄️ Local Models with Ollama
Run open-source LLMs on your own hardware via Ollama. Zero per-request cost, nothing leaves your machine, and the orchestrator talks to it over an OpenAI-compatible API.
📄️ TEE (Trusted Execution Environments)
TEE deployment is on the 6022 roadmap but not yet shipped. No tee-enclave platform value exists in the orchestrator, no enclave routing code, no attestation flow, and no in-orchestrator microtransaction logic.
📄️ LLM Troubleshooting
Common LLM issues and their fixes.