Multi AI agents for customer support email automation built with Langchain & Langgraph
Local RAG researcher agent built using Langgraph, DeepSeek R1 and Ollama
QueryPilot is an advanced document intelligence platform that combines Large Language Models (LLMs) with vector embeddings to enable natural language querying of your documents. The application processes various file formats (PDFs, DOCXs, TXT files, and images), extracting and embedding content for semantic search and AI-powered analysis.
SYNAPSE: AI-Driven Adaptive Software Engineering
This repository contains the implementation of a Retrieval-Augmented Generation (RAG) agent using Large Language Models (LLMs). RAG agents combine the power of information retrieval with text generation, enabling applications such as intelligent question-answering systems, and more.
Agentic RAG for journalling
A fully local RAG agent that parses PDFs and enables contextual Q&A using LLaMA 3.2 via Ollama, ChromaDB, and Gradio — no internet or API keys required, with faster response time.
AI-powered medical assistant chatbot built using Streamlit, LangChain, and Hugging Face models for interactive health queries.
Multi AI agents for customer support email automation built with Langchain & Langgraph
Python AI Course on LLM, RAG-Agents, LangGraph
Add a description, image, and links to the rag-agents topic page so that developers can more easily learn about it.
To associate your repository with the rag-agents topic, visit your repo's landing page and select "manage topics."