Agentic RAG: Reduce Cost and Improve Speed of Retrieval
Code: https://github.com/KannamSridharKumar...
Summary:
Build an agentic retriever to reduce cost and improve retrieval speed in RAG systems by dynamically selecting relevant data sources.
Use Hugging Face tools and embeddings to create the retriever, with the agent filtering data sources dynamically.
Agent identifies the right data sources, reducing the search scope from thousands to a few relevant chunks.
If no results appear, default to searching all data sources to ensure retrieval.
Keywords:
RAG, Agentic RAG, Hugging Face, Dynamic Data Filtering, Latency Optimization
Semantic Search, OpenAI, Vector Database, Embedding Model
#datascience #machinelearning #deeplearning #datanalytics #predictiveanalytics #artificialintelligence #generativeai #largelanguagemodels #computervision #naturallanguageprocessing #agents #transformers #embedding #graphml #graphdatascience #datavisualization #businessintelligence #optimization #montecarlosimulation #simulation #LLMs #python #aws #azure #gcp