Corrective Retrieval-Augmented Generation (RAG) with Dynamic Adjustments
Corrective Retrieval-Augmented Generation (RAG) enhances response accuracy by dynamically adjusting the retrieval process, ensuring relevant, up-to-date information.
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Project Outcomes
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Built a CRAG system for query processing.
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Enabled document retrieval with Chroma and FAISS.
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Evaluated relevance using GPT-4o.
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Adjusted responses with web searches when needed.
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Generated sourced, concise answers.
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Handled queries like image recognition.
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Integrated LangChain for workflow efficiency.
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Refined knowledge from documents and web.
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Showcased NLP application potential.
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Created a scalable AI research tool.