ai
8 items tagged with "ai"
Articles
Diagrams
Building RAG Application with Embedding Models
This diagram illustrates how to build a RAG application with embedding models. Reference Embedding models · Ollama Blog
Semantic Search with FAISS
This diagram illustrates how to build a semantic search engine with FAISS (Facebook AI Similarity Search). Reference Semantic search with FAISS - Hugging Face NLP Course
Text to SQL using duckdb-nsql model via ollama
DuckDB-NSQL is a text-to-SQL model with 7 billion parameters, specifically created for generating SQL queries. It builds upon Meta’s original Llama-2 7B model, undergoing additional pre-training using a dataset of general SQL queries. Subsequently, it is fine-tuned on a dataset containing DuckDB text-to-SQL pairs. This diagram shows you how to use ollama Python client library to call REST APIs to convert text to SQL.
Foundations of Vector Databases
This diagram shows the working principle of a vector database. Vector databases can be used in building a complex RAG (Retrieval Augmented Generation) application.
AI based Chatbot with LLaMA Models and Microsoft Semantic Kernel
This diagram illustrates an idea of implementing an AI based chatbot for Kontext on Azure. It leverages open source frameworks and LLMs (large language models) to implement a RAG (retrieval augmented generation). The chatbot will get the domain specific information from Kontext search engine as context information and provided it into backend API service which leverages Microsoft Semantic Kernel to construct the question and send to LLM service to generate the answers and then sends back to frontend. Alternatives In the diagram, LLMs can be replaced by other models like Open AI services of Azure Open AI services or any other relevant language models. Microsoft Semantic Kernel can also be replaced with LangChain too. References microsoft/SemanticKernelCookBook: This is a Semantic Kernel's book for beginners (github.com) Llama2Chat | 🦜️🔗 Langchain SciSharp/LLamaSharp: Run local LLaMA/GPT model easily and fast in C#!🤗 It's also easy to integrate LLamaSharp with semantic-kernel, unity, WPF and WebApp. (github.com) blazorly/LangChain.NET (github.com)