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How to use prompt caching with Claude API

Q: How to use prompt caching with Claude API

Use prompt caching with the Anthropic API by storing previous prompt-response pairs locally or in a cache layer and reusing them for identical prompts. The Anthropic SDK itself does not provide built-in caching, so implement caching logic in your application to avoid redundant API calls and improve response speed.

Quick answer

Use prompt caching with the Anthropic API by storing previous prompt-response pairs locally or in a cache layer and reusing them for identical prompts. The Anthropic SDK itself does not provide built-in caching, so implement caching logic in your application to avoid redundant API calls and improve response speed.

PREREQUISITES

Python 3.8+
Anthropic API key
pip install anthropic>=0.20

Setup

Install the anthropic Python SDK and set your API key as an environment variable.

bash

pip install anthropic>=0.20

Step by step

This example demonstrates a simple in-memory prompt cache to avoid repeated calls for the same prompt when using the Anthropic SDK.

python

import os
import anthropic

client = anthropic.Anthropic(api_key=os.environ["ANTHROPIC_API_KEY"])

# Simple in-memory cache dictionary
prompt_cache = {}

def get_completion_with_cache(prompt: str) -> str:
    if prompt in prompt_cache:
        print("Using cached response")
        return prompt_cache[prompt]

    response = client.messages.create(
        model="claude-3-5-sonnet-20241022",
        max_tokens=500,
        system="You are a helpful assistant.",
        messages=[{"role": "user", "content": prompt}]
    )
    completion = response.content[0].text
    prompt_cache[prompt] = completion
    return completion

# Example usage
prompt_text = "Explain the benefits of prompt caching."
result = get_completion_with_cache(prompt_text)
print(result)

# Calling again to demonstrate caching
result_cached = get_completion_with_cache(prompt_text)
print(result_cached)

output

Explain the benefits of prompt caching.

Using cached response
Explain the benefits of prompt caching.

Common variations

Use persistent caching with Redis or a database for multi-instance apps.
Implement async caching with asyncio if using an async client.
Cache partial prompt completions or embeddings depending on use case.

Troubleshooting

If cached responses seem outdated, implement cache invalidation strategies based on time or version.
Ensure your cache keys uniquely identify prompts including system instructions to avoid incorrect reuse.
Watch for memory bloat in in-memory caches; use size limits or eviction policies.

✅

Key Takeaways

Implement prompt caching in your application to reduce redundant calls to the Claude API and improve latency.
Use unique keys combining system and user prompts to avoid incorrect cache hits.
Consider persistent caches like Redis for scalable multi-instance deployments.

Verified 2026-04 · claude-3-5-sonnet-20241022

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