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Jupyter Notebook agents
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Jupyter Notebook agents — page 14 of 21
Mental Health Assistant RAG Application
Multi-Agent AI Orchestration Workshop
Official implementation of 'A knowledge-based Multi-agent approach for Vietnamese VQA with rationale explanations' (AICI 2026).
AWS Bedrock AgentCore with Langbase
A Retrieval-Augmented Generation (RAG) based Medical Chatbot. With the base model as Llama2 from Meta, the Retrieval system uses a medical document as corpus to generate context-rich output.
A collection of advanced LangChain modules and utilities in Python, enhancing LLM applications with custom tools, memory management, and RAG integrations. Includes code examples and tutorials for building sophisticated AI-driven workflows and applications.
Python notebook for solving overlapping tables problem with Azure document intelligence , semantic chunking, RAG , Azure AI Search
A set of reference implementations for various ML related tasks
news research tool that processes and analyzes news articles from given URLs. It leverages LangChain, Cohere embeddings, and Streamlit to provide insights and answers based on the content of the articles.
The contents of this repository showcase how to extract table data from a PDF file and preprocess it to facilitate word embedding. This preprocessing step enhances the readability of table data for language models and enables us to extract more contextual information from the tables.
Comparing vector DBs Pinecone, FAISS & pgvector in combination with OpenAI Embeddings for semantic search
Different summarization techniques that you can apply on your corpus using language models
Crash course on LangChain for LLM Application Developement by DeepLearningAI
PostgreSQL and LangChain OpenAI example
Resume Chain: Upload a Resume, Add a Job Description and Get Details or Get A Cover letter
This CrewAI project uses AI agents to review contracts, flag risks, classify clauses, and create a “Review Brief” for legal professionals.
A chat bot to summarize, fetch and give the pre requisites for a research paper
🍱 The aim of this project is to build a chatbot for a food delivery app client.
My solutions to the lab assignments in the Generative AI with Large Language Models course offered by Amazon Web Services.
Develop a basic chatbot using predefined rules, if-else statements, or pattern matching techniques. Explore natural language processing concepts and conversation flow within the chatbot's functionality.
국군 장병을 위한 AI 기반 비대면 의료 서비스 Meditact💊
It shows a question/answering chatbot using Amazon Bedrock with RAG based on Amazon Kendra.
This is Accent bot. It can score your english accent and give you hints to enhance your pronunciation!
Intents-Based Chatbot with Streamlit
A Feed Forward Neural Network which a ReLU activation, Cross Entropy Loss & Adam Optimizer
This repository contains the examples of deploying AI, ML models using Python, Django and other techniques.
Repository for creating and managing custom ChatGPT instances using OpenAI's GPTs. Includes documentation, configuration guides, and examples for users to build personalized AI applications with a focus on data handling and visualization capabilities.
My solutions to the Practical Reinforcement Learning course by Coursera/HSE.
Book on Generative Pre-trained Transformers 🦜
Getting Started with GPT4 API, GPT4 RAG, OpenAI GPT4 Assistant, OpenAI Models
This is an example of implementing the RAG feature based on OpenAI Assistant V2 and Anthropic's PDF feature.
This code demonstrates how to use GPT-3 from OpenAI to classify the sentiment of tweets using Google Sheets and the OpenAI API.
Prometheus AI Assistant para ajudar na criação de Alertas para sua infraestrutura!
Run a RAG system locally on your device and chat with your LLM!
A simple demonstration of how you can implement retrieval augmented generation (RAG) for a book.
Cofone is a small python library to manage RAG
MovieMatch helps you discover films similar to ones you love. Search by title, get a ranked top-10 list, sort results, and optionally generate AI-powered insights for each pick via a local Ollama model.
"🚀 Full-stack Medical AI Chatbot using Retrieval-Augmented Generation (RAG). Built with FastAPI, LangChain, and Groq. Features automated CI/CD via GitHub Actions to Docker Hub and scalable vector search with Pinecone."
RegulAId is an AI-powered compliance assistant that helps organizations navigate the complexity of the EU AI Act.
A machine learning system for classifying customer intents in Vietnamese conversations, designed for e-commerce customer service applications.
Synthesizing classical guitar pieces using custom tokenization and transformer-based architecture.
A comprehensive end-to-end tutorial series covering the complete lifecycle of building, deploying, and monitoring AI agents using modern GenAI frameworks.
A collection of courses on different topics in Generative AI.
Open Research Agent for Operations Research Problems
Production-ready Llama 2 AI toolkit — SQL query generator, email assistant, invoice extractor & LLM deployment on Google Colab | MLOps | LLMOps | Azure AI
Demo of a Fiber Cut Response Agent using Azure Content Understanding to process multi-modal field documents (PDFs, photos, diagrams, audio) and reason with Foundry models for incident triage. From Microsoft Build 2026.
AI-powered career assistant with XGBoost ML model (78.14% accuracy) trained on 6K+ resume-job pairs. Features advanced NLP skill extraction, GPT-4 resume enhancement, and intelligent job matching with real-time predictions.
Tested Azure cloud and Microsoft AI engineering scenarios: deployable architectures, runnable demos, benchmarks, and evidence-backed investigations.
Versioned educational project for building an AI agent, with Jupyter notebooks, IT/EN reports and architecture diagrams.
Run a free 35B multimodal LLM on Kaggle GPU — accessible from any OpenAI-compatible client
A highly customizable AI companion for Telegram. Create digital clones with unique personalities, voice, and vision directly from Google Colab.
Learn harness orchestration: seven notebooks that climb from one agent call to a system that writes its own execution graph. Companion to the AlphaSignal talk.
Retrieval-Augmented Generation (RAG) Explained, covering its working principles, components, benefits, applications, challenges, and future prospects.
AI-powered cloud architect agent that analyzes codebases and generates optimized infrastructure as code.
Deep learning models implemented as web services for integration in Rhino Grasshopper
Simple Streamlit application that parses the data from Invoice images and returns it in JSON format
A WhatsApp chatbot for real estate inquiries, built using Twilio API, Flask, and a BERT intent classifier. It uses LangChain and RAG for managing context and delivering accurate property information, automating client interactions while easing the workload for agents.
A Graph RAG implementation using Neo4j and LangChain
Python script utilizing the OpenAI API and LangChain to summarize emails. User inputs email and subject, and function returns sender, role, tone, summary, and spam classification.
🧩 Interfacing with different LLMs-chains, vectorstore databases, and autonomous agents.
RAG Evaluation Pipeline with RAGAS
I shared exercises about Langchain!🦜🔗
A template to set up, build and deploy a RAG-API including frontend and backend with docker compose.
Converso is a LangChain extension that streamlines data acquisition and action execution through natural language
SQL Agent is an intelligent chatbot that interprets natural language queries and converts them into SQL, interacts with your database, and handles query verification and execution with user confirmation. SQL-Agent simplifies database interaction, allowing users to interact conversationally instead of writing SQL.
It shows how to use langchain for sagemaker endpoint.
An Agentic RAG implementation using Langchain and a telegram client to send/receive messages from the chatbot
Notebooks for the Built Multi-Agent Applications with AutoGen Course
Bu depo; Microsoft AutoGen ile yaptığım/deneysel çalışmalar, entegrasyon denemeleri ve çoklu LLM sağlayıcı karşılaştırmalı örneklerini içeren bir çalışma alanıdır.
Foundational bootcamp on LLM usage (prompting & inference) → tooling & orchestration (LangChain, agents) → Retrieval-Augmented Generation (RAG) → advanced multi-tool/agent patterns.
Code repository for examples of implementing quick machine learning solutions to real-world problems
A Kotlin Spring AI demo uses the Agentic approach to demonstrate "Let LLM think on graph schema"
Build a chatbot based on gender with Seq2Seq and Schedule-Sampling Seq2Seq with PyTorch
Meet Pyter, The Machine Learning Chatbot Tutor with Interactive Jupyter Notebook
seq2seq 모델과 pytorch로 제작한 chatbot 생성 튜토리얼
An intent-based chatbot in python with tflearn and TensorFlow. It can be trained for a specific purpose and works well within that specific scope.
A chatbot that can take one of the 16 Myers-Briggs personalities
it provides Nao Robot conversation abilities to handle a free open-domain dialogue.
A deep learning chatbot that generates sarcastic and comical answers to your questions.
A Flask and Deep Learning Project that recognizes the emotion/mood of the user via either a photo or voice or text given as input by the user. It also contains a chatbot!
Team - Brogrammers. Won cash prize of INR 20000 at GE Healthcare Challenge
A chatbot developed using seq2seq encoder-decoder
ChatPod - Q&A over your Podcasts
An Advanced RAG Pipeline
Thread-Safe OpenAI Cost Logger
Use of parallel Function Calling with Azure OpenAI GPT models to manage vehicle's controls, simulated by Flask APIs.
A fashion search AI system utilizing Myntra dataset for providing detailed and user-friendly responses to fashion-related queries.
A comprehensive comparison of multimodal models - llama3.2-vision, minicpm-v, llava-llama3, llava, llava13:b and closed source models for animal classification tasks. This project evaluates various models' performance in classifying 10 different animal species, ranging from common to rare animals.
Practical use of Azure API Management's AI Gateway to manage Azure OpenAI operations.
Decrypting Passwords to Access Lost Bitcoin Wallets Using Gauss-Jacobi Method and Machine Learning Process BitcoinChatGPT
Building RAG With OpenAI GPT-4o(omni) Model Using Objectbox Vector Database
This repository develops a RAG-powered chatbot that answers questions based on a specific PDF document. Key objectives include: Chatbot Development: Chatbot using Retrieval-Augmented Generation (RAG) Dataset Creation, Performance Evaluation
Retrieval-Augmented Generation system: ask a question, retrieve relevant documents, and generate precise answers. RAG demo: document retrieval + LLM answering
Code for the USDA Branded Food Dataset pipeline and the USDA Food Assistant. This project consolidates USDA FoodData Central data into a structured dataset, along with an interactive tool that allows for conversational exploration of food items, nutrients, and ingredients.
Leverage vector databases to swiftly construct a diverse range of applications through "Building Applications with Vector Databases" course!
Multi-provider LLaMA 3.1 70B benchmark for dental knowledge — latency, consistency, and factual accuracy across 7 hosts, tracked in Weights & Biases.
🧹 Automated Filtering of Undesirable Web Data to Update LLM Knowledge
TinyRAG is a minimalist Python library that enables developers to rapidly build RAG-powered applications. It supports a flexible range of LLM endpoints and provides a clean API for combining retrieval with generation.
AI-Powered Study Plan and Book Summarization is a powerful repository that combines two cutting-edge AI solutions: a personalized study plan generator and a hierarchical book summarization system.