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"CAG: Chunked Augmented Generation for Google Chrome's Built-in Gemini Nano"

Below podcast is generated with Google's Illuminate.

Your browser now handles massive documents locally with smart AI chunking

CAG (Chunked Augmented Generation ) enables Chrome's built-in Gemini Nano to process large documents by intelligently chunking content while maintaining semantic coherence, overcoming the 6,144 token context window limitation through browser-optimized processing.

https://arxiv.org/abs/2412.18708

Original Problem 🤔:

→ Chrome's Gemini Nano has a strict 6,144 token context window limit, restricting its ability to process large documents

→ This limitation prevents local AI processing of extensive content within the browser, forcing reliance on external APIs

Key Insights 💡:

→ Sequential processing works better for smaller content (under 24,576 characters)

→ Recursive processing maintains better semantic coherence for larger texts

→ Technical content achieves 75-93% compression ratios

→ Memory utilization stays below 40% even for extensive content

Solution in this Paper 🔧:

→ CAG splits input into optimal chunks based on content type and browser resources

→ Implementation uses RecursiveCharacterTextSplitter for maintaining semantic boundaries

→ Processing happens through sequential or recursive generation based on content size

→ Dynamic memory management keeps browser responsive during processing

Results 📊:

→ Achieves 92.8% success rate for humongous content (>98,304 characters)

→ Maintains sub-2-second latency for small articles

→ ROUGE-N scores reach 0.89 for technical content

→ Peak memory usage stays under 45% of browser resources