•8 min read
Understanding Context Windows in LLMs
Explore how context windows work in Large Language Models and strategies for effective context management.
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AI Engineer | Product
Sharan Babu
AI Engineer at Acolyte AI, architecting multi-modal RAG systems and building production-grade AI solutions. 2+ years of hands-on LLM experience spanning context management, prompt engineering, and dynamic interface generation.
Featured Projects
LLM-focused projects showcasing innovative approaches to context management, dynamic interfaces, and information retrieval.
Pralok
An AI assistant that creates custom interfaces on-the-fly with bi-directional state transfer. Features dynamic code generation workflows, advanced file editing, and sophisticated context management for frictionless chat experiences. One of its core features is bi-directional state transfer which means that the AI can consider the user's actions in the interface as context and take action or manipulate the interface if needed.
LLMClick to view details
UserSubContext
A novel context management technique for Large Language Models (LLMs). Developed to dynamically select only a subset of the current context window for next turn based on previous user messages. Uses 'current user message' to intelligently choose relevant context, reducing token consumption and cost while maintaining accuracy.
LLMClick to view details
Gemini News Search Engine
Built an eclectic news search engine that helps with deduplication of news articles. Used graph database, TigerGraph to model and mine data using custom queries. Worked with NLP models including Semantic Search, Keyword Generation and Sentiment Analysis for enriching news articles. Published in ICIScOIS 2023 conference.
Graph DBClick to view details
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