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Entities in Honcho can sometimes be configured to change the behavior of the deriver, which is responsible for generating and storing facts, summaries, and user representations. These configurations can be set at the peer, session, and session-peer level (AKA the state of a peer within a specific session).

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Peer Configuration

By default, all peers are “observed” by Honcho. This means that Honcho will derive facts from messages sent by the peer and generate a representation of them. In most cases, this is why you use Honcho! However, sometimes an application requires a peer that should not be observed: for example, an assistant or game NPC that your program will never need to ask questions about. You may therefore disable observation of a peer by setting the observe_me flag in their configuration to false. If the peer has a session-level configuration, it will override this configuration. If the flag is not set, or is set to true, the peer will be observed. 
from honcho import Honcho

# Initialize client
honcho = Honcho()

# Create peer with configuration
peer = honcho.peer("my-peer", config={"observe_me": False})

# Change peer's configuration
peer.set_peer_config({"observe_me": True})

# Note: creating the same peer again will also replace the configuration
peer = honcho.peer("my-peer", config={"observe_me": False})

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Session Configuration

By default, all sessions have the deriver enabled, much like peers. You may create a session that escapes the deriver’s watchful eye by setting the deriver_disabled flag to true. You can update the flag by calling get_or_create on the session with a new configuration. 
from honcho import Honcho

# Initialize client
honcho = Honcho()

# Create session with configuration
session = honcho.session("my-session", config={"deriver_disabled": True})

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Session-Peer Configuration

Configuration at the session-peer level is the most common use case for configuration flags. You will often want to arrange a session such that certain peers observe others in order to form “local representations” of them. There are two flags that can be set at the session-peer level:
  • observe_me: Whether this peer should be observed by others in the session. By default, this is true. This overrides the peer-level observe_me flag.
  • observe_others: Whether this peer should produce local representations of others in the session. By default, this is false. Other peers will only be observed if their observe_me flag is true.
You can combine these flags across multiple peers to arrange any possible permutation of directional observation. Note that in the default case, no local representations are produced. To produce local representations, you must set the observe_others flag to true for at least one peer in the session and at least one other peer must have their observe_me flag set to true. Many applications will work best without local representations, preferring to chat with Honcho’s top-down representation of each peer. Only enable local representations via the observe_others flag if you are doing advanced reasoning on user perspectives. Peer Representations You can dynamically change the configuration of a session-peer by calling set_peer_config on the session with the peer and the configuration you want to set. 
from honcho import Honcho

# Initialize client
honcho = Honcho()

# Create session
session = honcho.session("my-session")

# Create peers
alice = honcho.peer("alice")
bob = honcho.peer("bob")

# Add peers to session with default configuration
session.add_peers([alice, bob])

# Add another peer to the session with a custom configuration
charlie = honcho.peer("charlie")
session.add_peers([charlie, {"observe_me": False, "observe_others": True}])

# Set session-peer configuration
session.set_peer_config(alice, {"observe_others": True})
session.set_peer_config(bob, {"observe_me": False})

# Get session-peer configuration
charlie_config = session.get_peer_config(charlie)
print(charlie_config)