ChatWeb can crawl web pages, read PDF, DOCX, TXT, and extract the main content, then answer your questions based on the content, or summarize the key points.
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Updated
Jun 25, 2024 - Python
ChatWeb can crawl web pages, read PDF, DOCX, TXT, and extract the main content, then answer your questions based on the content, or summarize the key points.
ID-based RAG FastAPI: Integration with Langchain and PostgreSQL/pgvector
A RAG app to ask questions about rows in a database table. Deployable on Azure Container Apps with PostgreSQL Flexible Server.
A web UI Project In order to learn the large language model. This project includes features such as chat, quantization, fine-tuning, prompt engineering templates, and multimodality.
Prototype app enabling job description search using natural language description of a job seeker.
Opinionated sample on how to build/deploy a RAG web app on AWS powered by Amazon Bedrock and PGVector (on Amazon RDS)
An intellligent AI assistant that can do anything!
Examples of vector DB indexing and query with various vector databases.
Extensible API and framework to build your Retrieval Augmented Generation (RAG) and Information Extraction (IE) applications with LLMs
Pip-installable, embedded-like postgres server for your python app
An application that enable the users to upload PDF files and ask questions regarding their content using Retrieval Augmented Generation (RAG)
Question Answering application with Large Language Models (LLMs) and Amazon Postgresql using pgvector
Knowledge base Q&A program using LangChain for retrieval-augmented prompting and PGVector as vector store.
Using tools like selenium and other scrapping libraries, as well as a Vector Data Base PGVector and docker, I will create an ETL that can be used once a week to populate this vector database with the releases of the week
E-commerce fashion assistant with Chatgpt, Hugging Face, Ltree and Pgvector.
Question Answering application with Large Language Models (LLMs) and Amazon Aurora Postgresql using pgvector
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