AdalFlow: The library to build & auto-optimize LLM applications.

Financial Domain Question Answering with pre-trained BERT Language Model

1st Place Solution for Eedi - Mining Misconceptions in Mathematics Kaggle Competition

Code for the paper “Towards Mixed-Modal Retrieval for Universal Retrieval-Augmented Generation”

Adding InMemoryCaching, Ensemble Retrievers,langchain, faiss for a open domain chatbot

InfoSage is a Question and Answering (Q&A) model using the Retriever-Reader approach. The application is built using the Streamlit framework and utilizes several modules and functionalities along with a database to store user information and feedback.

A lightweight and modular Retrieval-Augmented Generation (RAG) agent built with LangGraph and OpenAI. It supports document indexing with FAISS, and structured tool use. Ideal for prototyping question-answering systems over custom documents.

A simple langchain chatbot

Knowledgebase AI Assistant

Open-Domain QA

Codes for manipulating the London Crime dataset.

💬 Build a powerful chatbot with LangChain and Streamlit, enabling seamless conversations and actionable insights from your documents.

A Python3 script that retrieves all COTS names and versions in the Windows registry.

Just playing with AI Python, ChatOpenAI, AgentExecutor & Retriever tools