Context Budgeter CLI

Configure context budget allocation from the CLI

Reserve output tokens and inspect per-segment budgets so long agent runs don’t exhaust context before the model can reply.

from praisonaiagents import Agent

agent = Agent(name="budget-cli", instructions="Respect output token reserves.")
agent.start("Run a long task without exhausting the context budget.")

The user runs the agent from the CLI and checks /context budget to see segment allocation.

How It Works

Quick Start

1. Run an agent, then inspect budget

   from praisonaiagents import Agent
   
   agent = Agent(
       name="Assistant",
       instructions="Answer helpfully within context limits.",
   )
   
   agent.start("Summarise the key points of context budgeting")

   From the CLI session:

   praisonai chat
   > /context budget

2. Increase output reserve for long replies

   praisonai chat --context-output-reserve 16000

   Default output reserve is 8000 tokens. Raise it when the model truncates final answers.

CLI Flags

Interactive Commands

> /context budget   # Allocation breakdown
> /context stats    # Current usage vs budget

Example /context budget output:

Budget Allocation
  Model Limit:     128,000
  Output Reserve:  8,000
  Usable:          120,000

  Segment Budgets:
    System Prompt: 2,000
    History:       84,616
    Tool Outputs:  20,000
    ...

config.yaml

context:
  output_reserve: 8000
  default_tool_output_max: 10000

Environment variable: PRAISONAI_CONTEXT_OUTPUT_RESERVE.

Best Practices

Related