# NirDiamant/GenAI_Agents

50+ tutorials and implementations for Generative AI Agent techniques, from basic conversational bots to complex multi-agent systems.

Repository: https://github.com/NirDiamant/GenAI_Agents
Canonical: https://ross.abutalabs.com/products/genai_agents
Homepage: https://diamant-ai.com
Language: Jupyter Notebook
License: NOASSERTION
License Family: other
Topics: agents, genai, tutorials, langchain, langgraph, ai, llms, openai, llm, ai-agents, multi-agent, python, rag, agentic-ai, autonomous-agents, generative-ai, machine-learning, mcp, multi-agent-systems
Last push: 2026-08-19T19:37:06+00:00

## Health v2 (maintenance only)
Score: 67/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 98, release rhythm 35, longevity 51
- inputs: {"age_days": 723, "days_push": 14, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases, no_license
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 23996, forks 4028 (observed 2026-08-28T04:11:35.471311+00:00)

## What it is
A curated collection of 50+ Jupyter notebook tutorials and reference implementations for Generative AI agent techniques, spanning simple conversational bots to complex multi-agent systems. It is an educational resource built with LangChain, LangGraph, and related LLM tooling rather than a production library.

## Use cases
- learn how to build ai agents from scratch
- tutorials for multi-agent systems in python
- examples of langgraph agent workflows
- understand rag and agent design patterns
- study implementations of autonomous agents with llms
- find reference code for tool-using chatbots

## When to choose
- you want hands-on, notebook-based learning of agent techniques from basics to advanced multi-agent patterns
- you need reference implementations to adapt when prototyping your own agents
- you are exploring LangChain, LangGraph, RAG, and MCP concepts with worked examples

## When to avoid
- you need a production-ready agent framework or SDK to ship as a dependency
- you want a maintained application rather than educational notebooks
- you require a permissive license - the repository has no standard license (NOASSERTION)

## Facets
- artifact type: learning-resource
- maturity: active
- function: agent-framework, rag, prompt-engineering, chatbot, mcp
- domain: artificial-intelligence, large-language-models, tutorials
- platform: python
- tags: jupyter-notebooks, multi-agent-systems, langchain, langgraph, educational, generative-ai, ai-agents, retrieval-augmented-generation

## Member repositories
- NirDiamant/GenAI_Agents (main) score 67

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:11:35.471311+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-29T16:56:18.586201+00:00, confidence not recorded.
  - readme: https://github.com/NirDiamant/GenAI_Agents (fetched 2026-08-28T04:11:35.471311+00:00, sha 5e7627929f83)
  - homepage: https://diamant-ai.com (fetched 2026-08-29T07:53:48.068806+00:00, sha b674eb24f089)
- Data as of 2026-08-30T08:39:29.467469+00:00.