#jupyter_notebook#ai#llm#llms#multi_modal#openai#python#rag
Retrieval-Augmented Generation (RAG) is a technique that helps improve the accuracy of large language models by fetching relevant information from databases or documents. This approach ensures that the model's responses are based on up-to-date and accurate data, reducing errors and "hallucinations" where the model might provide false information. For users, RAG offers more reliable and trustworthy responses, allowing them to verify the sources used to generate those responses. This method also saves resources by avoiding the need to retrain models with new data.
https://github.com/FareedKhan-dev/all-rag-techniques
#php
You can easily set up a WordPress development environment using GitHub Codespaces or locally with Docker. Codespaces lets you start coding in a ready-made cloud environment directly from your browser, saving setup time and letting you work anywhere. For local setup, you need Node.js, npm, and Docker installed. After cloning the WordPress development repository, you run simple commands to install dependencies, build the project, and start the environment. You can access your WordPress site at http8889, run tests, and manage the environment with commands. This setup helps you develop, test, and contribute to WordPress efficiently without complex manual configuration.
https://github.com/WordPress/wordpress-develop
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