Q&A over pdf document with HuggingFace pipelines
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Updated
Nov 28, 2023 - Python
Q&A over pdf document with HuggingFace pipelines
LangChain apps | Beginner | Intermediate | Advanced level - OpenAI, LLAMA2, HuggingFace
This AI tool helps you to chat with your PDFs just by uploading it in the web interface.
The implementation of vector store build from scratch with minimal dependencies for text embedding and similarity search.
QA Bot (RAG) + Google Search
a chatbot for your docs & code
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
Code for Embeddings, VectorStore, SemanticSearch, and RAG using Azure OpenAI
Demonstrates various AI functionalities using Spring AI, including chat responses, JSON data handling, image creation and description, real-time data loading, text-to-speech, and vector store usage.
Documaster API is DocumentGPT. Ask questions / get summaries of pdf documents. Powered by OpenAI.
LangChain Documentation Helper
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.
An experimental Simple RAG configurable to use any LLM model and any Embeddings model, using Langchain, Flask-SocketIO, and Llamacpp, ChromaDB, transformers
Chat para hablar con tus datos y OpenAI
A list of almost all LMs (large model),include LLMs
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