Post Content
In this video we will look at context caching for cost and latency reduction. We will look at Gemini API but same technique can be used with Anthropic and OpenAI.
LINKS:
colab link: https://colab.research.google.com/drive/1lPfeAfXmS8TPclQ8Pd3odb0_7apTG4HU?usp=sharing
https://x.com/_philschmid/status/1917492129007292439
https://github.com/philschmid/gemini-samples/blob/main/examples/gemini-context-caching.ipynb
https://ai.google.dev/gemini-api/docs/caching?lang=python
https://youtu.be/tmiBae2goJM
RAG Beyond Basics Course:
https://prompt-s-site.thinkific.com/courses/rag
Let’s Connect:
Discord: https://discord.com/invite/t4eYQRUcXB
Buy me a Coffee: https://ko-fi.com/promptengineering
|
Patreon: https://www.patreon.com/PromptEngineering
Consulting: https://calendly.com/engineerprompt/consulting-call
Business Contact: engineerprompt@gmail.com
Become Member: http://tinyurl.com/y5h28s6h
Pre-configured localGPT VM: https://bit.ly/localGPT (use Code: PromptEngineering for 50% off).
Signup for Newsletter, localgpt:
https://tally.so/r/3y9bb0
In this video, discover how to significantly cut down your LLM API costs by using context caching. Learn how major API providers like Google, OpenAI, and Anthropic offer context caching to minimize API calls and reduce expenses. The video focuses on Google’s implementation, explaining its benefits, usage, and cost-saving potential. You’ll see a detailed tutorial on how to use context caching for large documents, in-context learning, and practical examples like MCP server creation. With insights into setup, token storage, cache management, and various functionalities, this guide will show you how to harness the power of context caching for optimal performance and cost-efficiency.
00:00 Introduction to Cost Reduction with Context Caching
00:22 Understanding Context Caching
01:06 Google’s Implementation of Context Caching
03:04 Cost Benefits of Context Caching
04:13 Practical Example: Setting Up Context Caching
08:24 Advanced Techniques and Functions
09:16 Example: Caching GitHub Repo Contents
15:42 Conclusion and Additional Resources Read More Prompt Engineering
#AI #promptengineering
