There are 0 repository under pineconedb topic.
š¤ An AI bot made for the command line that can read and understand any codebase from your Laravel app.
Kryten is a CLI tool to ask questions and get sourced answers from any .pdf, .doc, .docx, and many more documents.
Develop a python application that allows you to extract valuable insights, engage in meaningful conversations, and explore video content in a whole new way.
A dating (match-making) app for serious daters with embeddings and vector database.
Terraform Provider for managing resources on Pinecone.io
PDFInsights is an AI-powered chat application that allows users to interact with PDF documents. This application enables users to ask questions and get insights from PDF documents using natural language, making it a valuable tool for students, researchers, and professionals
Develop an advanced chatbot leveraging cutting-edge technologies capable of file uploads, enabling users to receive tailored responses based on the content of the uploaded files. Integrate various tools and agents to enhance the chatbot's capability for comprehensive and accurate responses.
The Medical Chatbot, built with Flask, integrates NLP libraries like Langchain and Hugging Face Transformers for text processing and embedding generation. Utilizing Pinecone as a vector database, it efficiently stores and retrieves data, offering users an interactive platform for medical inquiries.
Digital Twin for job recruiters to chat with.
SaaS based NextJS application for uploading and questioning about Pdfs with OpenAI
AI-Companion is a cool software that lets you create your own custom AI models of people you admire, like actors or celebrities. It's a tool to make personalized artificial intelligence companions based on your favorite individuals.
An ai-chat-app to virtually create/train your custom imaginary friend/character and have realtime converstaion.
š Mindstride is a RAG-based chat assistant designed to support mental health, personal growth, and self-improvement. This project leverages advanced AI technologies to provide a personalized and insightful experience, drawing from the wisdom of over 70 books on mental well-being, personal development, and self-discovery.
Meet Casia, the AI plant assistant š±
NitroGPT Navigator is an advanced chatbot that leverages cutting-edge technologies, including OpenAI's GPT-3.5, LangChain, and Pinecone Vector Database. It's designed to provide accurate and context-aware answers to any questions related to the content on routerprotocol.com.
š Hermes harnesses the power of GPT technology to create interactive conversations with your PDF documents. This innovative open-source tool transforms your PDFs into dynamic chatbots!
This is Document Querying Chatbot which can chat with documents on given prompts
LangChain ķė«ķ¼ģ ķµķ LLM, źø°ģµģ ģ„ģ, ķė”¬ķķø ģģ§ėģ“ė§ źµ¬ķ ķØķ¤ģ§
AI chat with uploaded documents. Code-along + mods by Brent L. Original project by Elliott Chong.
Learning NextJs 14 with app router. Messing with proper server/client component architecture, Next API routes, Next streaming, Next cache beta, retrieval augmented generation with OpenAI embeddings API, PineconeDB to store context/query embeddings, and chatbot with OpenAI prompt.
Next.js 14 Custom Chatbot (OpenAI ChatGPT, Vercel AI SDK, Pinecone, Shadcn UI, TypeScript, Tailwind)
šš This document processing system is designed to efficiently analyze user documents and provide accurate responses to user queries related to the content. Powered by advanced algorithms, it offers a seamless experience for users seeking insights or information within their documents.
Workshop LLM and Database Vector at Google DevFest Cerrado 2023, GoiĆ¢nia, GoiĆ”s, Brazil.
A package to vectorize pdf files and interact with Pinecone DB
Chatbot built using generative-ai
EmoCare ( "Emotion" + "Care" ) is a project about attending the patients appointment and give a solution how their emotional behavior is and gives the conclusion using Facial Recognition.
A repository for setting up and initializing LLM using langcahain and HuggingFace, generating document embeddings, and connecting to Pinecone for vector database operations. Includes an example of using a Retrieval-Augmented Generation (RAG) model.
This is an experiment in learning langchain, pinecone and stuff, don't mind
Created a custom chatbot that will reply to your question based on the data stored in it's memory.Technology used are prisma ORM, mongoDB, pineconeDB to store vectors, openAI Text-embedding-ada-002-v2 to embed the text. I have followed a youtube tutorial to learn this.