SaaSHub helps you find the best software and product alternatives Learn more →
Top 23 Jupyter Notebook llm Projects
-
View on GitHub
-
SaaSHub
SaaSHub - Software Alternatives and Reviews. SaaSHub helps you find the best software and product alternatives
-
-
RAG_Techniques
This repository showcases various advanced techniques for Retrieval-Augmented Generation (RAG) systems. Each technique has a detailed notebook tutorial.
Project mention: Building with Generative AI: Lessons from 5 Projects Part 1: RAG | dev.to | 2025-08-08There is also another repo that showcases various advanced techniques for Retrieval-Augmented Generation (RAG) systems.
-
Hands-On-Large-Language-Models
Official code repo for the O'Reilly Book - "Hands-On Large Language Models"
It’s the full code from the book, with notebooks covering LLM basics, training, and fine-tuning. If you like a guided, notebook-first path from foundations to customization, this feels like a friendly trail map. Link: https://github.com/HandsOnLLM/Hands-On-Large-Language-Models
-
GenAI_Agents
50+ tutorials and implementations for Generative AI Agent techniques, from basic conversational bots to complex multi-agent systems.
Clear tutorials and implementations of generative AI agent techniques, from basic builds to advanced strategies. You’ll see how different agent strategies are wired up, which makes design choices feel obvious. Link: https://github.com/NirDiamant/GenAI_Agents
-
agents-towards-production
End-to-end, code-first tutorials for building production-grade GenAI agents. From prototype to enterprise deployment.
Project mention: Show HN: GibRAM an in-memory ephemeral GraphRAG runtime for retrieval | news.ycombinator.com | 2026-01-17GraphRAG's approach certainly makes sense for regulation-heavy documents, where interconnected references can be critical for retrieval quality. The challenge you mentioned about separate systems for graph storage and vector indexing resonates with what we've seen in the field. In practice, this separation often adds unnecessary complexity for ephemeral analysis tasks. One thing we've explored is using a dual-memory architecture, which might be relevant here even in an in-memory context. It allows you to effectively manage recent context and longer-term semantic connections without the overhead of persistent storage. If you're interested in seeing how this approach could be integrated into production systems, I wrote up some patterns that might be useful: https://github.com/NirDiamant/agents-towards-production.
-
Prompt_Engineering
22 prompt engineering techniques with hands-on Jupyter Notebook tutorials, from fundamental concepts to advanced strategies for leveraging LLMs.
View on GitHub
-
Source code of the book: https://github.com/rasbt/reasoning-from-scratch
-
Project mention: Persistent multi-agent conversations with the OpenAI Agents SDK and MongoDB | dev.to | 2026-04-27
Python 3.10+, an OpenAI API key, and either a local mongod or a MongoDB Atlas cluster. Nothing in the demo requires Atlas-only features — a 27017 on localhost is fine.
-
nixtla
TimeGPT-1: production ready pre-trained Time Series Foundation Model for forecasting and anomaly detection. Generative pretrained transformer for time series trained on over 100B data points. It's capable of accurately predicting various domains such as retail, electricity, finance, and IoT with just a few lines of code 🚀.
Project mention: Google's 200M-parameter time-series foundation model with 16k context | news.ycombinator.com | 2026-03-30 -
-
rag-cookbooks
This repository contains various advanced techniques for Retrieval-Augmented Generation (RAG) systems.
-
-
-
vectordb-recipes
Resource, examples & tutorials for multimodal AI, RAG and agents using vector search and LLMs
-
Deepdive-llama3-from-scratch
Achieve the llama3 inference step-by-step, grasp the core concepts, master the process derivation, implement the code.
-
-
-
-
Local-LLM-Langchain
Load local LLMs effortlessly in a Jupyter notebook for testing purposes alongside Langchain or other agents. Contains Oobagooga and KoboldAI versions of the langchain notebooks with examples.
-
-
-
NOTE:
The open source projects on this list are ordered by number of github stars.
The number of mentions indicates repo mentiontions in the last 12 Months or
since we started tracking (Dec 2020).
Jupyter Notebook llms discussion
Jupyter Notebook llms related posts
-
Persistent multi-agent conversations with the OpenAI Agents SDK and MongoDB
-
Building Persistent Memory for Voice AI Agents with MongoDB
-
10 Best AI Engineering GitHub Repos to Build Real Systems
-
A Guide to Securely Exposing Ollama on Colab via Pinggy
-
LangGraph With MongoDB: Building Conversational Long-Term Memory for Intelligent AI Agents
-
What Features Should I Look for in an AI Agent Observability Platform?
-
Added llms.txt and llms-full.txt to My Hugo-built Website
-
A note from our sponsor - SaaSHub
www.saashub.com | 12 Jul 2026
Index
What are some of the best open-source llm projects in Jupyter Notebook? This list will help you:
| # | Project | Stars |
|---|---|---|
| 1 | generative-ai-for-beginners | 112,851 |
| 2 | Made-With-ML | 48,614 |
| 3 | RAG_Techniques | 28,481 |
| 4 | Hands-On-Large-Language-Models | 27,368 |
| 5 | GenAI_Agents | 23,060 |
| 6 | agents-towards-production | 20,939 |
| 7 | Prompt_Engineering | 7,657 |
| 8 | reasoning-from-scratch | 4,703 |
| 9 | GenAI-Showcase | 4,248 |
| 10 | nixtla | 3,943 |
| 11 | mlops-course | 3,356 |
| 12 | rag-cookbooks | 2,517 |
| 13 | llm-applications | 1,856 |
| 14 | tarsier | 1,761 |
| 15 | vectordb-recipes | 965 |
| 16 | Deepdive-llama3-from-scratch | 629 |
| 17 | datablations | 342 |
| 18 | tamingLLMs | 340 |
| 19 | beyondllm | 293 |
| 20 | Local-LLM-Langchain | 216 |
| 21 | PandasAI-Tutorials | 190 |
| 22 | power-attention | 130 |
| 23 | chatXML | 56 |
Sponsored
SaaSHub - Software Alternatives and Reviews
SaaSHub helps you find the best software and product alternatives
www.saashub.com