Models, Agents, Sessions, And Chat
Use this flow after onboarding finishes. The control model is:1. Agent Models
Open/agents, select the Agent, then open Models.
Use it to:
- sign in to a provider
- paste an API key or token
- configure local/manual endpoints such as Ollama, LM Studio, vLLM, LiteLLM, Cloudflare AI, or Custom Provider
- inspect whether credentials are ready
- choose this Agent’s primary, fallback, and task model refs
Agent > Models.
2. Agents
Stay in/agents after at least one provider is ready.
Use it to:
- create or select an Agent
- choose the Agent’s default provider route and model
- attach skills and services
- route channels to the Agent
- configure memory, hooks, tasks, and wallet policy for that Agent
3. Sessions
Sessions are the working contexts under an Agent. Examples:/session new, /session list, and /session switch.
Tasks should attach to a Session, not to a Channel.
4. Chat
Open/chat to talk to an Agent/session directly.
Chat uses the selected Agent’s default model unless you override the model for
the current chat session. A session override affects that chat session; it does
not rewrite the Agent default unless you save the model from /agents.
Chat should only show provider routes and models from the current Fased provider
registry. Old runtime provider catalogs are compatibility data, not normal
picker entries.
Use Schedule this in the Chat composer to create a scheduled task for the
current Agent/session. If the selected session came from a channel, the task can
optionally deliver back there.
5. Channels
OpenAgent > Channels to connect external apps.
Each channel route should target an Agent. Example:
6. Tasks
Tasks are scheduled work attached to Agent + Session. Create and manage them from:- Chat composer: Schedule this
- channel chat:
/task new,/task list,/task show,/task run,/task cancel /sessionsandAgent > Sessions: edit, run, cancel session-owned tasksAgent > Tasks: full scheduler view for the selected Agent
Local Models
For local models:- use vLLM when you run a vLLM server
- use Ollama when you run local, cloud, or hybrid Ollama
- use LM Studio when you run its localhost:1234 server
- use LiteLLM when you proxy multiple model backends
- use Custom Provider for SGLang or another OpenAI-compatible endpoint