Q&A over pdf document with HuggingFace pipelines
-
Updated
Nov 28, 2023 - Python
Q&A over pdf document with HuggingFace pipelines
LangChain apps | Beginner | Intermediate | Advanced level - OpenAI, LLAMA2, HuggingFace
Chat para hablar con tus datos y OpenAI
This AI tool helps you to chat with your PDFs just by uploading it in the web interface.
Documaster API is DocumentGPT. Ask questions / get summaries of pdf documents. Powered by OpenAI.
The implementation of vector store build from scratch with minimal dependencies for text embedding and similarity search.
Ruby on Rails integration for ChromaDB
Customized bot with langchain and gpt4
This project is a reference implementation of the Hierarchical Navigable Small World graph paper by Malkov & Yashunin (2018) as a companion to the AWS presentation by Ben Duncan (Startup Solution Architect) "What you need to know about Vector Databases. From use-cases to a deep dive on the technology."
QA Bot (RAG) + Google Search
a chatbot for your docs & code
Ingest GitHub repo data into vectorstore with LangChain and create seamless Streamlit chatbot using GPT-4
Sample code to demo the use of LlamaIndex with Azure OpenAI GPT-4 and Embedding models in RAG implementation.
Creating a chat application that can handle multiple files using LlamaIndex, OpenAI, and Streamlit involves several steps
Nodejs a REST API is designed to provide users with an interactive chat interface where they can ask questions and receive responses generated by an AI model. The application utilizes OpenAI embeddings and Langchain to process the user's input and generate relevant responses based on the context of the conversation.
Add a description, image, and links to the vectorstore topic page so that developers can more easily learn about it.
To associate your repository with the vectorstore topic, visit your repo's landing page and select "manage topics."