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.

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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.

🏗️ AI Agent Architecture

This diagram shows the flow of building a production-level agent. The tutorials in this repository cover each of these components step-by-step.

📚 Tutorials

🔌 Tool Integration

Tutorial	Description	View
Secure Tool Calling (Arcade)	Enable agents to securely call external tools (Gmail, Slack, Notion) with OAuth2 authentication and human-in-the-loop safety controls. Learn production-ready tool integration with user isolation and approval workflows.

🏗️ Full-Stack Applications

Tutorial	Description	View
Full-Stack Agent Applications with Portia	Master Portia AI framework for building predictable, stateful, and authenticated agentic workflows. Includes SteelThread evaluation framework for real-time production monitoring and offline testing, with hands-on UXR data analysis and Notion integration examples.

📊 Data Processing

Tutorial	Description	View
Web Data Collection for AI Agents (Bright Data)	Build agents that collect and process web data at scale using enterprise-grade scraping infrastructure. Learn to integrate proxy networks, handle CAPTCHAs, and extract structured data from complex websites.
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.
Browser Automation for AI Agents (Anchor Browser)	Enable agents to interact with web applications through browser automation. Learn to extract data from dashboards, automate form filling, and navigate complex web interfaces using cloud-hosted browsers.

🧠 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.

🔍 RAG & Knowledge Management

Tutorial	Description	View
Production-Ready RAG Agents with Contextual AI (Contextual AI)	Build enterprise-grade RAG systems in 15 minutes using Contextual AI's managed platform. Learn document processing, intelligent indexing, agent deployment, and automated evaluation with LMUnit testing framework for financial document analysis.

👥 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.

🔍 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.

🚀 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.

🔒 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.

🔍 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

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:

# 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:

# 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 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 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