Managed Agent Session Info

Unified session schema returned by managed agent backends

The unified retrieve_session() schema applies to both HostedAgent and LocalAgent (the new canonical classes), as well as the deprecated ManagedAgent factory.

retrieve_session() returns the same shape on every managed agent backend so you can write code once and switch providers freely.

from praisonaiagents import Agent
from praisonai import HostedAgent, HostedAgentConfig

hosted = HostedAgent(config=HostedAgentConfig(model="claude-sonnet-4-6"))
agent = Agent(name="assistant", backend=hosted)
agent.start("Summarise this session for my dashboard.")

The user inspects a running session; every backend returns the same SessionInfo fields for tooling and dashboards.

How It Works

Quick Start

1. HostedAgent Usage

   from praisonaiagents import Agent
   from praisonai import HostedAgent, HostedAgentConfig
   
   hosted = HostedAgent(config=HostedAgentConfig(model="claude-sonnet-4-6"))
   agent = Agent(name="assistant", backend=hosted)
   agent.start("Hello!")
   
   info = hosted.retrieve_session()
   print(info["id"], info["status"], info["title"])
   print(info["usage"]["input_tokens"], info["usage"]["output_tokens"])
   
2. LocalAgent Usage

   from praisonai import LocalAgent, LocalAgentConfig
   
   local = LocalAgent(config=LocalAgentConfig(model="gpt-4o-mini"))
   info = local.retrieve_session()
   # Same 4 keys — id, status, title, usage — every time
   

---

Schema

All four fields are always present with sensible defaults:

Field	Type	Default	Values
id	str	""	Session ID, empty if none
status	str	"unknown"	idle, running, error, unknown, none
title	str	""	Session title (Anthropic only sets this)
usage	Dict[str, int]	{"input_tokens": 0, "output_tokens": 0}	Always has both keys

Status Values

Status	Meaning
idle	Session exists and ready for input
running	Session actively processing (Anthropic)
error	Session hit an error (Anthropic)
unknown	No session / status unavailable
none	Local backend with no session ID

Empty Session Defaults

Before starting any turn you still get a valid dict — no KeyError, no .get() guards:

managed = ManagedAgent(config=ManagedConfig())
info = managed.retrieve_session()
# {"id": "", "status": "unknown", "title": "", "usage": {"input_tokens": 0, "output_tokens": 0}}

Building a Custom Backend

Import the protocol directly from praisonaiagents.managed:

from praisonaiagents.managed import ManagedBackendProtocol
from typing import Dict, Any

class MyBackend:
    def retrieve_session(self) -> Dict[str, Any]:
        # Return the unified shape
        return {
            "id": "my-session",
            "status": "idle",
            "title": "My Session",
            "usage": {"input_tokens": 0, "output_tokens": 0},
        }
    # ... implement execute(), stream(), reset_session(), reset_all()

Common Patterns

Cost monitoring

info = managed.retrieve_session()
cost = info["usage"]["input_tokens"] * 3e-6 + info["usage"]["output_tokens"] * 15e-6
print(f"Session {info['id']} spent ${cost:.4f}")

Provider-agnostic logging

def log_session(backend):
    info = backend.retrieve_session()
    print(f"[{info['status']}] {info['title'] or info['id']}")

log_session(anthropic_backend)
log_session(local_backend)  # Same code — both return identical shape

---

Best Practices

Don't guard with .get()

Every key is always present. info["usage"]["input_tokens"] is always safe.

Check status before sending

Use status == "idle" before sending a new message to avoid overlapping turns.

Handle backend differences

LocalManagedAgent always returns title="". Only AnthropicManagedAgent sets it.

Use stable import path

from praisonaiagents.managed import ManagedBackendProtocol is the stable, recommended path.

---

Related

Hosted Agent

Run entire agent loops on Anthropic’s managed runtime

Local Agent

Run agent loops locally with any LLM