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https://github.com/nirdiamant/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.
https://github.com/nirdiamant/agents-towards-production

agent agent-framework agents ai-agents genai generative-ai llm llms mlops multi-agent production tool-integration tutorials

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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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README 

          
![](https://europe-west1-atp-views-tracker.cloudfunctions.net/working-analytics?notebook=main-readme)




# Agents Towards Production



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



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Agents Towards Production is your go-to resource for building GenAI agents that scale - from zero to production.  

Whether you're just starting out or refining your deployment stack, this repo gives you the tools, patterns, and code examples to do it right.



⭐ If you find value in this project, **give it a star** to help others discover it too






---






## 💎 Sponsors





Support from our sponsors helps make this project possible.


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).




  

  

    

      LangChain logo

    


    Agent Framework & Workflows


      

        Visit LangChain site

      

    

  



  

  

    

      Redis logo

    


    Memory & Vector Database


      

        Visit Redis site

      

    

  



  

  

    

      Tavily logo

    


    Real‑time Web Search API


      

        Visit Tavily site

      

    

  



  

  

    

      Bright Data logo

    


    Web Data Platform


      

        Visit Bright Data site

      

    

  



  

  

    

      RunPod logo

    


    GPU Cloud Computing


      

        Visit RunPod site

      

    

  



  

  

    

      

        

        xpander.ai logo

      

    


    Agent Orchestration Platform


      

        Visit xpander.ai site

      

    

  



  

  

    

      Qualifire logo

    


    Security & Observability


      

        Visit Qualifire site

      

    

  





  Become a sponsor →







---






## 📫 Stay Updated!



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---



## ✨ Introduction

**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.



---



## 🔑 Key Features



| | |

|---|---|

| **Tutorial-first learning** | Every topic comes with a practical walkthrough you can run locally |

| **Full lifecycle coverage** | All the capabilities required to take agents from prototype to production |

| 🚀 **GPU Deployment** | Deploy to scalable GPU infrastructure for high-performance agent workloads |

| 🔍 **Real-Time Monitoring** | Gain end-to-end tracing, monitoring, and debugging for agent workflows |

| 🔌 **Tool Integration** | Connect agents to real-time web data, databases, and external APIs |

| 🧠 **Memory** | Implement both short- and long-term stores with semantic search |

| 🔄 **Orchestration** | Design multi-tool, memory-aware workflows and agent-to-agent messaging |

| 🔒 **Security** | Apply real-time guardrails and injection defenses |

| 🧩 **Agent Frameworks** | Create stateful graphs, expose agents as REST endpoints, and package reusable tools |

| 🚀 **Deployment** | Ship to containers and on-prem servers with containerization patterns |

| 🛠️ **Model Customization** | Fine-tune language models for specialized agent behavior and domain expertise |

| 👥 **Multi-agent Coordination** | Enable message passing and shared planning |

| 🔍 **Tracing & Debugging** | Add comprehensive observability to debug and improve agent performance |

| 📊 **Evaluation** | Automate behavioral testing and metric tracking |

| 🖥️ **UI & Frontend** | Build chat or dashboard front-ends in minutes |



---



## 📚 Tutorials



### 🚀 GPU Deployment



  

    Tutorial

    Description

    View

  

  

    Scalable GPU Deployment for AI Agents (Runpod)

    Deploy AI agents on scalable GPU infrastructure. Learn to set up cost-effective, high-performance environments for demanding agent workloads.

    

      

    

  



### 🔍 Real-Time Monitoring



  

    Tutorial

    Description

    View

  

  

    Agent Observability: Tracing, Monitoring & Debugging (Qualifire)

    Gain end-to-end tracing, real-time monitoring, and debugging for agent workflows. Learn to capture logs, traces, and quality metrics for troubleshooting and optimization.

    

      

    

  



### 🔌 Tool Integration



  

    Tutorial

    Description

    View

  

  

    Real-Time Web Data Integration for Agents (Tavily)

    Enable agents to access, search, and extract real-time web data. Build workflows that combine live web information with private knowledge for research, monitoring, and up-to-date recommendations.

    

      

    

  



### 🧠 Memory



  

    Tutorial

    Description

    View

  

  

    Agent Memory: Dual-Memory & Semantic Search (Redis)

    Implement dual-memory (short-term and long-term), semantic search, and persistent state for agents that remember user preferences and learn from conversations.

    

      

    

  



### 🔄 Orchestration



  

    Tutorial

    Description

    View

  

  

    Agent Orchestration: Multi-Tool, Memory & Messaging Workflows (xpander.ai)

    Learn to orchestrate tools, memory, multi-user state, and agent-to-agent messaging for production-ready AI agents. Example: Automate meeting recording and reporting workflows.

    

      

    

  



### 🔒 Security



  

    Tutorial

    Description

    View

  

  

    Real-Time Security Guardrails for Agents (Qualifire)

    Block prompt injections, hallucinations, unsafe content, and enforce security policies in real time. Learn to implement robust guardrails for agent safety.

    

      

    

  

  

    Comprehensive Agent Security (LlamaFirewall)

    Apply comprehensive input, output, and tool security guardrails for agents. Covers prompt injection, behavior alignment, and tool access control.

    

      

    

  

  

    Hands-On Agent Security Evaluation (Apex)

    Hands-on prompt injection attacks, defenses, and automated security testing for AI agents.

    

      

    

  



### 🧩 Agent Frameworks



  

    Tutorial

    Description

    View

  

  

    Tool & API Integration via Model Context Protocol (MCP)

    Integrate agents with external tools and APIs using a standardized protocol. Example: Seamless tool and API integration for advanced agent workflows.

    

      

    

  

  

    Stateful Agent Workflows with LangGraph

    Design complex, stateful agent workflows using a directed graph architecture. Example: Multi-step text analysis pipeline with classification, entity extraction, and summarization.

    

      

    

  

  

    Deploying Agents as APIs with FastAPI

    Create and deploy agents as performant APIs, supporting both synchronous and streaming endpoints.

    

      

    

  



### 🚀 Deployment



  

    Tutorial

    Description

    View

  

  

    Containerizing Agents with Docker

    Containerize agents for portability and scalability. Learn foundational patterns for running agents in containers across environments.

    

      

    

  

  

    On-Prem LLM Deployment with Ollama

    Run and interact with large language models locally. Replace cloud APIs with on-prem models for privacy, cost control, and low-latency agent workflows.

    

      

    

  



### 🛠️ Model Customization



  

    Tutorial

    Description

    View

  

  

    Fine-Tuning AI Agents for Domain Expertise & Efficiency

    Learn how to fine-tune language models for specialized agent behavior, domain expertise, and efficient, cost-effective responses. Covers data preparation, training, evaluation, and integration into agent workflows.

    

      

    

  



### 👥 Multi-agent Coordination



  

    Tutorial

    Description

    View

  

  

    Multi-Agent Communication with A2A Protocol

    Simulate collaborative agent workflows and message exchange using open communication protocols for interoperability.

    

      

    

  



### 🔍 Tracing & Debugging



  

    Tutorial

    Description

    View

  

  

    Agent Tracing & Debugging with LangSmith

    Add comprehensive observability to AI systems. Capture detailed traces, decision points, and timing data to debug, monitor, and systematically improve agent performance.

    

      

    

  



### 📊 Evaluation



  

    Tutorial

    Description

    View

  

  

    Automated Agent Evaluation & Behavioral Analysis (IntellAgent)

    Automate agent evaluation with behavioral analysis, performance metrics, and actionable insights for improving agent quality.

    

      

    

  



### 🖥️ UI & Frontend



  

    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.

    

      

    

  



---



## 🚀 Getting Started



Transform your AI agent ideas into production-ready systems using our battle-tested patterns and implementations.



### 📖 Browse Online

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.



### 🛠️ Clone and Build

Download the repository to run tutorials locally, experiment with configurations, customize implementations, and integrate proven patterns directly into your agent development workflow.






#### Quick Setup



**1. Get the Code**



```bash

git clone https://github.com/NirDiamant/agents-towards-production.git

cd agents-towards-production

```



**2. Install Dependencies**

Navigate to your target tutorial and set up the environment:



```bash

# Example: Multi-tool agent orchestration

cd tutorials/agentic-applications-by-xpander.ai

pip install -r meeting-recorder-agent/requirements.txt

```



**3. Deploy and Test**

Launch tutorials through their preferred interface:



```bash

# Run interactive notebooks for experimentation

jupyter notebook tutorial.ipynb



# Execute production scripts for integration testing

python app.py

```






---



## 🤝 Contributing



We 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](CONTRIBUTING.md) for more details.



---



## ⚠️ Disclaimer



**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.



---



## 📜 License



This project is licensed under a custom non-commercial license - see the [LICENSE](LICENSE) file for details.



---






### ⭐️ If you find this repository helpful, please consider giving it a star!







Keywords: AI Agents, Production Deployment, LLM, Orchestration, Multi-agent Systems, Memory Systems, Monitoring, Security, Observability, Agent Frameworks, Infrastructure, Serverless, Enterprise AI, Tool Integration