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Prompt engineering is the process of designing and refining input queries to gen AI models, like OpenAI's GPT variants, for achieving desired output. It involves optimizing the phrasing, context, and structure of prompts to improve the AI's understanding while maintaining high-quality & creative results that cater to specific app requirements.
The AI Chat Bot project integrates OpenAI's LangChain Agent with RAG technology, offering a user-friendly interface via Streamlit for seamless communication. It serves diverse functions such as customer service and information retrieval, remaining at the forefront of conversational AI through continuous refinement.
"Explore my personal learning repository, organized by topics, featuring informative READMEs, code snippets, and valuable resources for continuous learning and growth."
A reference containing Styles and Keywords that you can use with Stable diffusion BlueWillow AI. There are also pages showing resolution comparison, image weights, and much more!
Prompty makes it easy to create, manage, debug, and evaluate LLM prompts for your AI applications. Prompty is an asset class and format for LLM prompts designed to enhance observability, understandability, and portability for developers.
LLMOps with Prompt Flow is a "LLMOps template and guidance" to help you build LLM-infused apps using Prompt Flow. It offers a range of features including Centralized Code Hosting, Lifecycle Management, Variant and Hyperparameter Experimentation, A/B Deployment, reporting for all runs and experiments and so on.