Google Gemini also supports caching, using an explicit API where you pay for the time your content is cached: https://
ai.google.dev/gemini-api/doc
s/caching?lang=python
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@jeremyphoward
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Google Gemini API Caching: Explicit Payment Model Explained
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Deepseek Introduces Fully Automated Prompt Caching Feature
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BTW Deepseek also provides prompt caching — and theirs is fully automated, which is pretty cool!
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Anthropic Releases Official API Documentation on Prompt Caching Pricing
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Here's the official API docs with details on pricing: https://
docs.anthropic.com/en/docs/build-
with-claude/prompt-caching
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Prompt Caching in Claude: Cost-Effective Token Optimization
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Something that nearly everyone is sleeping on is the importance of prompt caching. We've just added support for it to Claudette, so @AnthropicAI caching is now *very* easy to use — cached tokens are 90% cheaper, and faster! Docs here: https://
claudette.answer.ai/#prompt-caching -
Exploring Llama Recipes Repository for LLM Implementation
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Did you look at the llama-recipes repo?
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Using XML for organizing inputs instead of markdown fences
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I understand- hence the 2nd part of my response. I don’t think that helps. Claude has read loads of fenced markdown blocks and is good at using them. So I just use xml for organising my inputs.
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Claude Projects XML Document Integration Best Practices
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If you add them to a Claude project I assume Claude adds xml for each doc. I don’t think there’s a benefit to putting xml within each doc
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Context Documents Matter More Than Expected in AI
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I didn’t find it mattered much at all – context docs were the important thing
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Claude Projects Excel at FastHTML Questions Beyond Knowledge Cutoff
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I've discovered that when I create an @AnthropicAI Claude project with one example .py file and a few of the markdown files, it does a great job of answering FastHTML questions, even although the lib predates Claude's knowledge cutoff!
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Advanced Python Library Example with Comprehensive Documentation
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Also in that zip is `adv_app.py`, a single file example that shows nearly all the features of the lib, including detailed comments on how/why everything is the way it is. It's designed for both humans and LLMs to read.