Production RAG with Semantic Kernel: Patterns, Chunking, and Retrieval Strategies
📰 Dev.to · Brian Spann
Learn to implement Production RAG with Semantic Kernel for effective LLMs in enterprise settings
Action Steps
- Build a RAG pipeline using Semantic Kernel
- Configure chunking strategies for efficient text processing
- Apply retrieval strategies to improve model performance
- Test and evaluate the RAG model using relevant metrics
- Compare different retrieval strategies to optimize results
Who Needs to Know This
Data scientists and machine learning engineers on a team can benefit from this to improve their LLM models, while product managers can use this to inform their product strategy
Key Insight
💡 RAG with Semantic Kernel can significantly improve the usefulness of LLMs in enterprise settings
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🚀 Boost your LLMs with Production RAG and Semantic Kernel!
Key Takeaways
Learn to implement Production RAG with Semantic Kernel for effective LLMs in enterprise settings
Full Article
Retrieval-Augmented Generation (RAG) is the pattern that makes LLMs genuinely useful for enterprise...
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