Agentic RAG: Giảm Chi phí và Cải thiện Tốc độ Truy xuất

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Code: https://github.com/KannamSridharKumar/youtube_misc/blob/main/agentic_retreiver.ipynb

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