In this we implements a Retrieval-Augmented Generation (RAG) based conversational AI agent designed for intelligent knowledge extraction from PDF documents. Leveraging LangChain and Google’s Gemini LLM
A RAG app with streamlit as UI app, flask as backend api. Bot trả lời về document, về data cụ thể. Bot trả lời về document của công ty, trả lời về tờ hướng dẫn sử dụng hay gì đó. Data: bot có khả năng query để lấy dữ liệu (dạng dữ liệu có cấu trúc) như csv
A modular Python project that uses LangChain and Groq LLMs to extract and process information from PDFs, text files, directories, and web pages using dedicated loaders and prompt templates.
Agentic AI + RAG (Retrieval-Augmented Generation) chatbot built with LangGraph, LangChain, Google Gemini, and FAISS.
Modular RAG system with Factory Pattern - Load PDF/Word docs, configure embedders (Ollama) and vector stores (ChromaDB) via YAML
PDF Loader in android using kotlin. Compatible with all android versions
CLI-based RAG application for querying PDF documents using ChromaDB, embeddings, and OpenRouter.
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