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The most basic building block of Honcho’s data model is the Message object. A Message is sent by a Peer and saved in a Session 
from honcho import Honcho

honcho = Honcho()

peer = honcho.peer("sample-peer")

session = honcho.session("sample-session")

message = peer.message("Hello, world!", session_id=session.id)

session.add_messages([message])
Once a Message is saved in Honcho, it will kick off a background task that looks at the new data to generate insights about the Peer that sent the Message This is the default behavior of Honcho and can be turned off by configuring the Peer or Session This pattern of having a Peer, Session, and Messages is highly flexible and works for many different use cases and agent setups. Some use cases may only need a single Peer, but many Sessions. Others will only use a single Session for their entire app. These are flexible components that work in any situation.

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Chat Bots

A common use case for Honcho to is to build a chatbot like ChatGPT or Claude. In this case you can simply
  • Make a Peer for the User
  • Make a Peer for the AI
Then you can make a Session for each thread of conversation and save Messages from the user and assistant in each turn of conversation