How You Can Integrate Bandit with CircleCI Why It’s Valuable Things to Watch Out For / Trade-Offs Example Snippet (Pseudo config.yml) version: 2.1jobs: security_scan: docker: – image: cimg/python:3.9 steps: – checkout – run: name: Install Bandit command: pip install bandit – run: name: Run Bandit command: bandit -r . -f json -o bandit-report.json – store_artifacts:Continue reading “Bandit and CircleCI”
Tag Archives: artificial-intelligence
TensorFlow vs. PyTorch
Development Philosophy TensorFlow takes a production-first approach, emphasizing scalability, deployment, and enterprise features. Originally built around static computational graphs, though TensorFlow 2.0 introduced eager execution by default. PyTorch prioritizes research flexibility and intuitive development. Built from the ground up with dynamic computational graphs and a “Pythonic” design philosophy that feels natural to Python developers. EaseContinue reading “TensorFlow vs. PyTorch”
AI Agent Loop
Option One An AI Agent Loop refers to the cyclical process by which an autonomous AI agent perceives its environment, plans actions, executes those actions, and reflects on the results. This loop enables the agent to operate intelligently in dynamic environments by continually adapting its behavior based on feedback and outcomes. It is foundational toContinue reading “AI Agent Loop”
RAG pipeline building frameworks comparison
When building a Retrieval-Augmented Generation (RAG) pipeline, the “best” tool depends on your goals, level of abstraction, and control you want over the components. Here’s a breakdown of LangChain, Hugging Face, and PyTorch, to help you choose: 🧱 1. LangChain: Best for: Rapid prototyping and production-ready apps with modular components ✅ Use LangChain if youContinue reading “RAG pipeline building frameworks comparison”
Notes from San Francisco 