CachingConfig

Configure caching behavior for agent responses and prompts

Enable response and prompt caching to improve performance and reduce API costs.

Quick Start

1. Simple Enable

   Enable caching with defaults:

   from praisonaiagents import Agent
   
   agent = Agent(
       name="Cached Agent",
       instructions="Use caching",
       caching=True
   )
   
2. With Configuration

   Configure caching behavior:

   from praisonaiagents import Agent
   from praisonaiagents.config import CachingConfig
   
   agent = Agent(
       name="Cached Agent",
       instructions="Use caching",
       caching=CachingConfig(
           enabled=True,
           prompt_caching=True
       )
   )
   

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Configuration Options

from praisonaiagents.config import CachingConfig

config = CachingConfig(
    # Response caching
    enabled=True,
    
    # Prompt caching (provider-specific)
    prompt_caching=None
)

Parameter	Type	Default	Description
enabled	bool	True	Enable response caching
prompt_caching	Optional[bool]	None	On Anthropic, emits explicit cache_control markers on the system block and the stable history prefix (respecting Anthropic’s 4-breakpoint budget). On OpenAI/Gemini, has no effect at the wire — those providers cache automatically when the prefix is byte-stable.

What gets cached

• System block: instructions, tools, and memory prelude
• Stable conversation-history prefix (Anthropic only) — the two most recent messages stay uncached

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Common Patterns

Pattern 1: Full Caching

from praisonaiagents import Agent
from praisonaiagents.config import CachingConfig

agent = Agent(
    name="Full Cache Agent",
    instructions="Maximum caching",
    caching=CachingConfig(
        enabled=True,
        prompt_caching=True
    )
)

Pattern 2: Auto-Detection with Memory

Even without explicit prompt_caching=True, the SDK auto-detects model support and arranges the prefix accordingly:

from praisonaiagents import Agent

agent = Agent(
    name="Auto Cache Agent",
    instructions="Cache optimization happens automatically",
    llm="openai/gpt-4o",      # SDK detects prompt cache support
    memory=True,              # Enables cache-optimized memory context
    caching=CachingConfig()   # prompt_caching=None means auto-detect
)

Pattern 3: Disable Caching

from praisonaiagents import Agent
from praisonaiagents.config import CachingConfig

agent = Agent(
    name="No Cache Agent",
    instructions="Always fresh responses",
    caching=CachingConfig(enabled=False)
)

---

Best Practices

Enable Prompt Caching for Anthropic

Anthropic Claude supports prompt caching for significant cost savings on repeated prompts.

Disable for Real-Time Data

Turn off caching when agents need fresh, real-time information.

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Related

Performance

Performance optimization tips

ExecutionConfig

Execution limits configuration