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Building an Evidence-Based RAG App on Akamai Cloud Analytics Table
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About Building an Evidence-Based RAG App on Akamai Cloud
Explore Building an Evidence-Based RAG App on Akamai Cloud with 52,073 views, 92 likes, and 1 comments. Experience the impact of this video content that has captured audience attention.
In this video, I show you how to build a specialized RAG (Retrieval Augmented Generation) chatbot that reads complex documents and provides evidence-based answers. We are solving a real-world problem, fighting airline bureaucracy, by building a robot that can ingest "Contract of Carriage" PDFs and cite specific clauses to help you claim compensation for delays. This is a complete walkthrough of building a legal expert bot from scratch, covering everything from the Python application logic to secure CI/CD pipelines and network policies. GitHub Code Repository: https://github.com/akamai-developers/rag-langgraph-k8s-quickstart New to Cloud Computing? Get started here with a $100 credit → https://www.linode.com/lp/youtube-viewers/?utm_source=youtube&utm_medium=devrel The Tech Stack: • Application: Python, LangChain, LangGraph • Vector Storage: PostgreSQL with pgvector • Infrastructure: Terraform, Linode Kubernetes Engine (LKE) • Storage: S3-compatible Object Storage • Cloud: Akamai Cloud Follow Lena on LinkedIn: https://www.linkedin.com/in/lena-hall/ #RAG #Python #Kubernetes #DevOps #LangChain #LangGraph #PostgreSQL #Akamai #LLM #LargeLanguageModel #AI #Cloud #tutorial #k8s
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