---
title: "agents-towards-production"
type: "tool"
slug: "nirdiamant-agents-towards-production"
canonical_url: "https://www.graphcanon.com/tools/nirdiamant-agents-towards-production"
github_url: "https://github.com/NirDiamant/agents-towards-production"
homepage_url: null
stars: 20930
forks: 2784
primary_language: "Jupyter Notebook"
license: "Other"
categories: ["ai-agents", "developer-tools"]
tags: ["llms", "genai", "deployment", "llm", "generative-ai", "multi-agent-systems", "agent", "ai-agents"]
updated_at: "2026-07-07T18:26:28.390365+00:00"
---

# agents-towards-production

> End-to-end, code-first tutorials for constructing production-grade GenAI agents.

A repository offering comprehensive instructions on converting AI prototypes into robust enterprise systems through stateful workflows, vector memory, real-time web search APIs, Docker deployment, security measures, GPU scaling, multi-agent coordination, and user interface development.

## Facts

- Repository: https://github.com/NirDiamant/agents-towards-production
- Stars: 20,930 · Forks: 2,784 · Open issues: 10 · Watchers: 233
- Primary language: Jupyter Notebook
- License: Other
- Last pushed: 2026-07-04T12:53:24+00:00

## Categories

- [AI Agents](/categories/ai-agents.md)
- [Developer Tools](/categories/developer-tools.md)

## Tags

llms, genai, deployment, llm, generative-ai, multi-agent-systems, agent, ai-agents

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## README (excerpt)

```text
<div align="center">

# Agents Towards Production

### _The open-source playbook for turning AI agents into real-world products._

**Agents Towards Production is your go‑to resource for building production‑ready GenAI agents that scale from prototype to enterprise.** Tutorials cover stateful workflows, vector memory, real‑time web search APIs, Docker deployment, FastAPI endpoints, security guardrails, GPU scaling, browser automation, fine‑tuning, multi‑agent coordination, observability, evaluation, and UI development.

### ⭐ **If you find value in this project, PLEASE STAR IT to help others discover these tutorials!** 








</div>

---

## 🎓 From prototype to production, as a method

<div align="center">

**[Prompt to Production](https://europe-west1-rag-techniques-views-tracker.cloudfunctions.net/rag-techniques-tracker?notebook=agents-towards-production--readme&click=course-waitlist-cta&target=https%3A%2F%2Fdiamant-ai.com%2Fcourses%3Futm_source%3Dgithub%26utm_medium%3Dreadme%26utm_campaign%3Dagents-towards-production&retarget=0&text=course-waitlist-cta)** - my full course on building software with AI the way professionals do: the methods and paradigms behind reliable, efficient, modular production systems, taught systematically. 16 lectures, each with a hands-on lab, from your first structured prompt to a working production system.

**[Join the waiting list →](https://europe-west1-rag-techniques-views-tracker.cloudfunctions.net/rag-techniques-tracker?notebook=agents-towards-production--readme&click=course-waitlist-cta&target=https%3A%2F%2Fdiamant-ai.com%2Fcourses%3Futm_source%3Dgithub%26utm_medium%3Dreadme%26utm_campaign%3Dagents-towards-production&retarget=0&text=course-waitlist-cta)** · everyone on the list locks in the founding price, lower than public launch

</div>


---

<div align="center">

> **28 production-grade tutorials** covering stateful workflows, vector memory, web search APIs, Docker deployment, security guardrails, GPU scaling, multi-agent coordination, and more.

## 💎 Tutorial Sponsors

<p align="center"><em>
Companies that have contributed step-by-step tutorials to this repository.<br>
Click a logo to open the tutorial. Use Ctrl‑/⌘‑click to keep this page open.
</em></p>


<table align="center" cellpadding="20"
       style="table-layout:fixed; width:100%; border-collapse:collapse;">
<tr align="center" valign="top">

  
  <td width="200" valign="bottom">
    <a href="tutorials/LangGraph-agent" title="Open LangChain tutorial">
      <picture>
        <source media="(prefers-color-scheme: dark)"
                srcset="assets/repos_images/sponsors_logos/trimmed_padded/trimmed_padded_langchain_white.png">
        <img src="assets/repos_images/sponsors_logos/trimmed_padded/trimmed_padded_langchain.png"
             height="44" style="max-width:180px;" alt="LangChain - AI agent framework and workflow orchestration platform for building production-ready language model applications">
      </picture>
    </a><br>
    <sub><span style="white-space:nowrap;">Agent Framework &amp; Workflows</span><br>
      <a href="https://langchain.com">
        <img src="assets/repos_images/visit-site-badge.svg" width="56" height="16" alt="Visit LangChain AI agent framework website">
      </a>
    </sub>
  </td>

  
  <td width="200" valign="bottom">
    <a href="tutorials/agent-memory-with-redis" title="Open Redis tutorial">
      <picture>
        <source media="(prefers-color-scheme: dark)"
                srcset="assets/repos_images/sponsors_logos/trimmed_padded/trimmed_padded_Redis_white.svg">
        <img src="assets/repos_images/sponsors_logos/trimmed_padded/trimmed_padded_Redis.png"
             height="44" style="max-width:180px;" alt="Redis - In-memory database and vector storage for AI agent memory, caching, and real-time data processing">
      </picture>
    </a><br>
    <sub><span style="white-space:nowrap;">Memory &amp; Vector Database</span><br>
      <a href="https://redis.io/try-free/?utm_source=nir&utm_med
```

---

**Machine-readable endpoints**

- JSON: [`/api/graphcanon/tools/nirdiamant-agents-towards-production`](/api/graphcanon/tools/nirdiamant-agents-towards-production)
- LLM index: [/llms.txt](/llms.txt)
- Full corpus: [/llms-full.txt](/llms-full.txt)

_GraphCanon - The knowledge graph for AI development. https://www.graphcanon.com/_