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HR Analytics Dashboard: Employee Attrition, Performance, and Satisfaction Insights
HR Data Analytics portfolio project on a dataset of 80K records that deals with HR KPIs like Performance tracking, attrition rate. Project involved cleaning, transforming data and visualizing it to…
Discover a curated collection of dynamic Power BI dashboards covering financial analytics, HR metrics, streaming service trends, real estate dynamics, and more. Meticulously designed for comprehens…
Developed Power BI dashboards for HR leaders, providing insights for strategic decisions and scenario planning. Optimized resource planning by aligning HR strategies with workforce trends, enhancin…
A simple Python RAG implementation with MongoDB Vector Search, LangChain and OpenAI
Short demo of Retrieval Augmented Generation with AIConfig
This advanced AI-powered chatbot leverages Groq's API and LangChain's React agent to deliver sophisticated natural language processing capabilities. Built with versatility in mind, it offers seamle…
Conversate effortlessly in more than 50 languages!
This web app allowing the user to upload multiple files and then utilizing the OpenAI API GPT 3.5 Turbo language models, the user is able to have a conversation about the uploaded documents. The us…
Gemini PDF Chatbot: A Streamlit-based application powered by the Gemini conversational AI model. Upload multiple PDF files, extract text, and engage in natural language conversations to receive det…
Ingest files for retrieval augmented generation (RAG) with open-source Large Language Models (LLMs), all without 3rd parties or sensitive data leaving your network.
Building an assistant for Boletin Oficial del Estado (BOE) using Retrieval Augmented Generation (RAG)
Advanced Retrieval-Augmented Generation (RAG) through practical notebooks, using the power of the Langchain, OpenAI GPTs ,META LLAMA3 ,Agents.
Streamlit app demonstrating using LangChain and retrieval augmented generation with a vectorstore and hybrid search
Evaluation tools for Retrieval-augmented Generation (RAG) methods.
Metrics to evaluate the quality of responses of your Retrieval Augmented Generation (RAG) applications.
Speech-enabled Retrieval-Augmented Generation solution
A demo Jupyter Notebook showcasing a simple local RAG (Retrieval Augmented Generation) pipeline to chat with your PDFs.
This project aims to introduce and demonstrate the practical applications of RAG using Python code in a Jupyter Notebook environment.
Vision-Augmented Retrieval and Generation (VARAG) - Vision first RAG Engine
Powerful web application that combines Streamlit, LangChain, and Pinecone to simplify document analysis. Powered by OpenAI's GPT-3, RAG enables dynamic, interactive document conversations, making i…
A Retrieval Augmented Generation example with Azure
Retrieval Augmented Generation (RAG) framework and context engine powered by Pinecone
A sample app for the Retrieval-Augmented Generation pattern running in Azure, using Azure AI Search for retrieval and Azure OpenAI large language models to power ChatGPT-style and Q&A experiences.
This repository showcases various advanced techniques for Retrieval-Augmented Generation (RAG) systems. RAG systems combine information retrieval with generative models to provide accurate and cont…