Feature Request: Implement Prompt Caching for Improved Performance and Cost Efficiency

[twalderman]

Description:
We propose implementing prompt caching functionality in the "BMO" chat application to optimize API usage, reduce processing time, and lower costs for repetitive tasks or prompts with consistent elements.

Key Features:

Cache Control Integration:

Add support for the cache_control parameter in API requests.
Allow users to designate specific sections of their prompts for caching.
Beta Header Support:

Implement the ability to include the anthropic-beta: prompt-caching-2024-07-31 header in API requests.
Caching Mechanism:

Develop a system to check for cached prompt prefixes before processing full prompts.
Implement a 5-minute cache lifetime with automatic refresh on usage.
User Interface Updates:

Add options in the UI for users to enable/disable prompt caching.
Provide visual indicators for cached content in the chat interface.
Performance Tracking:

Integrate new API response fields (cache_creation_input_tokens and cache_read_input_tokens) into the application's analytics.
Display cache performance metrics to users.
Pricing Integration:

Update the pricing calculator to reflect the new token pricing structure for cached content.
Documentation and Guides:

Create in-app documentation explaining prompt caching concepts and best practices.
Develop interactive tutorials demonstrating effective use of caching in different scenarios.
Error Handling and Troubleshooting:

Implement robust error handling for cache-related issues.
Provide clear error messages and troubleshooting guides for common caching problems.
Multi-Model Support:

Ensure compatibility with Claude 3.5 Sonnet and Claude 3 Haiku.
Prepare for future integration with Claude 3 Opus.
Cache Management:

Develop tools for users to view and manage their cached content.
Implement cache invalidation mechanisms for consistency across API calls.
Benefits:

Reduced API costs for users with repetitive or context-heavy prompts.
Improved response times for cached content.
Enhanced ability to work with large datasets or complex instructions within prompts.
Better support for extended conversations and iterative processes.
Implementation Considerations:

Ensure strict privacy and data separation measures in the caching system.
Design the caching system to be compatible with other beta features and future API updates.
Conduct thorough testing to verify cache consistency and performance gains.
Next Steps:

Detailed technical design and architecture planning.
Prototype development and internal testing.
Limited beta release to select users for feedback.
Refinement based on beta feedback.
Full feature release with comprehensive documentation and user guides.
By implementing prompt caching, we can significantly enhance the efficiency and cost-effectiveness of the "BMO" chat application, providing users with a more powerful and responsive tool for AI-assisted tasks.

Ref: https://docs.anthropic.com/en/docs/build-with-claude/prompt-caching#can-i-use-prompt-caching-with-other-api-features