agents-towards-production
This repository delivers end-to-end, code-first tutorials covering every layer of production-grade GenAI agents, guiding you from spark to scale with proven patterns and reusable blueprints for real-world launches.
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Agents Towards Production is an open-source playbook 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.
README:
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.
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Click a logo to open the step‑by‑step tutorial.
A regular click on "Visit Site" leaves the repo (use Ctrl‑/⌘‑click to keep this page open).
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Agent Framework & Workflows |
Memory & Vector Database |
RAG & Knowledge Management |
Web Data Platform |
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Real‑time Web Search API |
Secure Tool Calling |
AI Agent Framework |
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AI Memory & Knowledge Graphs |
GPU Cloud Computing |
| 🚀 Cutting-edge Updates |
💡 Expert Insights |
🎯 Top 0.1%Content |
Join over 25,000 of AI enthusiasts getting unique cutting-edge insights and free tutorials!
Plus, subscribers get exclusive early access and special 33% discounts to my book and upcoming courses!
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Join our growing community discussing cutting-edge AI research, agent development, and production insights!
Agents Towards Production is your hands-on guide to every building block of a GenAI agent stack.
All knowledge is delivered through runnable tutorials covering orchestration, memory, observability, deployment, security, and more. Each tutorial lives in its own folder with ready-to-run notebooks or code files, so you can move from concept to working agent in minutes.
This diagram shows the flow of building a production-level agent. The tutorials in this repository cover each of these components step-by-step.
| Tutorial | Description | View |
|---|---|---|
| Multi-Agent Communication with A2A Protocol | Simulate collaborative agent workflows and message exchange using open communication protocols for interoperability. |
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| Tutorial | Description | View |
|---|---|---|
| Building a Chatbot UI with Streamlit | Build a beginner-friendly chatbot web app with a chat interface, file upload, and session state for interactive agent demos. |
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Transform your AI agent ideas into production-ready systems using our battle-tested patterns and implementations.
Explore tutorials directly on GitHub to understand production-grade implementations, architectural decisions, and integration patterns. Each tutorial includes comprehensive documentation and code that you can study and adapt to your specific requirements without any local setup.
Download the repository to run tutorials locally, experiment with configurations, customize implementations, and integrate proven patterns directly into your agent development workflow.
1. Get the Code
git clone https://github.com/NirDiamant/agents-towards-production.git
cd agents-towards-production2. Install Dependencies Navigate to your target tutorial and set up the environment:
# Example: Multi-tool agent orchestration
cd tutorials/agentic-applications-by-xpander.ai
pip install -r meeting-recorder-agent/requirements.txt3. Deploy and Test Launch tutorials through their preferred interface:
# Run interactive notebooks for experimentation
jupyter notebook tutorial.ipynb
# Execute production scripts for integration testing
python app.pyWe welcome contributions of tools, infrastructure, and frameworks that support agent development. This includes monitoring, deployment platforms, security tools, databases, APIs, and other horizontal services that enable production agent systems.
Please see our Contributing Guidelines for more details.
Educational use only. Authors disclaim all responsibility for use, misuse, or consequences. We do not endorse, verify, or guarantee third-party companies, tools, or services referenced herein. Not liable for damages, losses, security breaches, or fraudulent activities by referenced parties.
Your responsibility: Conduct due diligence, verify legitimacy, test in isolation, ensure legal compliance. Security tools require ethical use with proper authorization.
By using this repository, you agree to this disclaimer.
This project is licensed under a custom non-commercial license - see the LICENSE file for details.
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