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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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📖 Books in the DiamantAI Series

<a href="https://europe-west1-rag-techniques-views-tracker.cloudfunctions.net/rag-techniques-tracker?notebook=agents-towards-production--readme&click=book-buy-amazon-image&target=https%3A%2F%2Fwww.amazon.com%2Fdp%2FB0D76734SZ%3Ftag%3Ddiamantai-atp-20&text=Best%20Seller%20Image"><img src="images/rag_book_best_seller.png" alt="RAG Made Simple - Amazon bestseller in Generative AI" width="500"></a>

RAG Made Simple - the production reference for RAG systems
A 400-page visual guide to 22 RAG techniques. If you're shipping agents that need to retrieve and ground on real data, this is the structured reference behind the patterns in this repo.
1,500+ copies sold · Hit #1 in Generative AI on Amazon at launch · ⭐ 4.4 stars
Kindle $9.99 · Paperback $24.99 · Free with Kindle Unlimited

👉 Get RAG Made Simple on Amazon

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Prompt Engineering: Master the Art of AI Interaction - the prompting foundation
22 hands-on prompting techniques explained in depth. The companion book to RAG Made Simple. The prompting layer that determines how reliably your production agents behave.

👉 See Prompt Engineering on Amazon

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

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💼 Apply for open AI engineering jobs

AI-first companies are hiring through the DiamantAI Collective.

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💎 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> <!-- ─────────── 1st row – 4 sponsors ─────────── --> <table align="center" cellpadding="20" style="table-layout:fixed; width:100%; border-collapse:collapse;"> <tr align="center" valign="top"> <!-- LangChain --> <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> _{<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>} </td> <!-- Redis --> <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> _{<span style="white-space:nowrap;">Memory &amp; Vector Database</span><br> <a href="https://redis.io/try-free/?utm_source=nir&utm_medium=cpa&utm_campaign=2025-05-ai_in_production-influencer-nir&utm_content=sd-software_download-7013z000001WaRY"> <img src="assets/repos_images/visit-site-badge.svg" width="56" height="16" alt="Visit Redis in-memory database and vector storage website"> </a>} </td> <!-- Contextual AI --> <td width="200" valign="bottom"> <a href="tutorials/agent-RAG-with-Contextual" title="Open Contextual AI tutorial"> <picture> <source media="(prefers-color-scheme: dark)" srcset="assets/repos_images/sponsors_logos/trimmed_padded/trimmed_padded_contextual_white.png"> <img src="assets/repos_images/sponsors_logos/trimmed_padded/trimmed_padded_contextual_black.png" height="44" style="max-width:180px;" alt="Contextual AI - Production-ready RAG platform for building enterprise-grade retrieval augmented generation systems"> </picture> </a><br> _{<span style="white-space:nowrap;">RAG &amp; Knowledge Management</span><br> <a href="https://app.contextual.ai/?utm_campaign=agents-towards-production&utm_source=diamantai&utm_medium=github&utm_content=notebook"> <img src="assets/repos_images/visit-site-badge.svg" width="56" height="16" alt="Visit Contextual AI RAG platform website"> </a>} </td> <!-- Bright Data --> <td width="200" valign="bottom"> <a href="tutorials/agent-with-brightdata" title="Open Bright Data tutorial"> <picture> <source media="(prefers-color-scheme: dark)" srcset="assets/repos_images/sponsors_logos/trimmed_padded/trimmed_padded_brightdata_white.svg"> <img src="assets/repos_images/sponsors_logos/trimmed_padded/trimmed_padded_brightdata.png" height="44" style="max-width:180px;" alt="Bright Data - Web scraping and data collection platform for AI training and agent data gathering"> </picture> </a><br> _{<span style="white-space:nowrap;">Web Data Platform</span><br> <a href="https://brightdata.com/ai?utm_source=brand&utm_campaign=brnd-mkt_github_nirdiamant_logo"> <img src="assets/repos_images/visit-site-badge.svg" width="56" height="16" alt="Visit Bright Data web scraping platform website"> </a>} </td> </tr> </table> <!-- ─────────── 2nd row – 3 sponsors ─────────── --> <table align="center" cellpadding="20" style="table-layout:fixed; width:100%; margin-top:16px; border-collapse:collapse;"> <tr align="center" valign="top"> <!-- Tavily --> <td width="200" valign="bottom"> <a href="tutorials/agent-with-tavily-web-access" title="Open Tavily tutorial"> <picture> <source media="(prefers-color-scheme: dark)" srcset="assets/repos_images/sponsors_logos/trimmed_padded/trimmed_padded_tavily_white.png"> <img src="assets/repos_images/sponsors_logos/trimmed_padded/trimmed_padded_tavily.png" height="44" style="max-width:180px;" alt="Tavily - Real-time web search API for AI agents with intelligent content extraction and summarization"> </picture> </a><br> _{<span style="white-space:nowrap;">Real‑time Web Search API</span><br> <a href="https://app.tavily.com/home/?utm_source=github&utm_medium=referral&utm_campaign=nir_diamant"> <img src="assets/repos_images/visit-site-badge.svg" width="56" height="16" alt="Visit Tavily real-time web search API website"> </a>} </td> <!-- Arcade --> <td width="200" valign="bottom"> <a href="tutorials/arcade-secure-tool-calling" title="Open Arcade tutorial"> <picture> <source media="(prefers-color-scheme: dark)" srcset="assets/repos_images/sponsors_logos/trimmed_padded/trimmed_padded_arcade_white_tight.png"> <img src="assets/repos_images/sponsors_logos/trimmed_padded/trimmed_padded_arcade_black.png" height="44" style="max-width:180px;" alt="Arcade - Multi-user tool calling platform for secure OAuth2 authentication and human-in-the-loop safety controls"> </picture> </a><br> _{<span style="white-space:nowrap;">MCP Runtime</span><br> <a href="https://docs.arcade.dev/en/home?utm_source=github&utm_medium=paid_sponsorship&utm_campaign=agents_toward_prod&utm_content=readme_placement"> <img src="assets/repos_images/visit-site-badge.svg" width="56" height="16" alt="Visit Arcade multi-user tool integration platform website"> </a>} </td> <!-- JetBrains --> <td width="200" valign="bottom"> <a href="tutorials/kotlin-agent-with-koog" title="Open JetBrains Koog tutorial"> <picture> <source media="(prefers-color-scheme: dark)" srcset="assets/repos_images/sponsors_logos/trimmed_padded/trimmed_padded_jetbrains_white.svg"> <img src="assets/repos_images/sponsors_logos/trimmed_padded/trimmed_padded_jetbrains.png" height="44" style="max-width:180px;" alt="JetBrains - Creator of Kotlin and the Koog AI agent framework for building intelligent applications on the JVM"> </picture> </a><br> _{<span style="white-space:nowrap;">Kotlin AI Agent Framework</span><br> <a href="https://kotlinlang.org/?utm_source=github&utm_medium=influencers&utm_campaign=kotlin_nir_supporter_1"> <img src="assets/repos_images/visit-site-badge.svg" width="56" height="16" alt="Visit Kotlin website"> </a>} </td> </tr> </table> <!-- ─────────── 3rd row – 3 sponsors ─────────── --> <table align="center" cellpadding="20" style="table-layout:fixed; width:100%; margin-top:16px; border-collapse:collapse;"> <tr align="center" valign="top"> <!-- Mem0 --> <td width="200" valign="bottom"> <a href="tutorials/agent-memory-with-mem0" title="Open Mem0 tutorial"> <picture> <source media="(prefers-color-scheme: dark)" srcset="assets/repos_images/sponsors_logos/trimmed_padded/Mem0%20Word%20Logo.png"> <img src="assets/repos_images/sponsors_logos/trimmed_padded/Mem0 Word Logo Dark.png" height="44" style="max-width:180px;" alt="Mem0 - Self-improving memory system for AI agents with hybrid vector and graph storage"> </picture> </a><br> _{<span style="white-space:nowrap;">Self-Improving AI Memory</span><br> <a href="https://mem0.dev/github/nir"> <img src="assets/repos_images/visit-site-badge.svg" width="56" height="16" alt="Visit Mem0 AI memory platform website"> </a>} </td> <!-- RunPod --> <td width="200" valign="bottom"> <a href="tutorials/runpod-gpu-deploy" title="Open RunPod tutorial"> <picture> <source media="(prefers-color-scheme: dark)" srcset="assets/repos_images/sponsors_logos/trimmed_padded/trimmed_padded_runpod_white.svg"> <img src="assets/repos_images/sponsors_logos/trimmed_padded/trimmed_padded_runpod.svg" height="44" style="max-width:180px;" alt="RunPod - GPU cloud computing platform for training and deploying AI models and agents at scale"> </picture> </a><br> _{<span style="white-space:nowrap;">GPU Cloud Computing</span><br> <a href="https://get.runpod.io/nirdiamant"> <img src="assets/repos_images/visit-site-badge.svg" width="56" height="16" alt="Visit RunPod GPU cloud computing website"> </a>} </td> </tr> </table>

💎 General Sponsors

<p align="center"><em> Companies that support this project through partnerships and resources.<br> Click a logo to visit their website. </em></p> <!-- ─────────── General sponsors ─────────── --> <table align="center" cellpadding="20" style="table-layout:fixed; width:100%; border-collapse:collapse;"> <tr align="center" valign="top"> <!-- CodeRabbit --> <td width="200" valign="bottom"> <a href="https://coderabbit.link/nir" title="Visit CodeRabbit"> <picture> <source media="(prefers-color-scheme: dark)" srcset="assets/repos_images/sponsors_logos/trimmed_padded/coderabbit_Dark_Type_Mark.png"> <img src="assets/repos_images/sponsors_logos/trimmed_padded/coderabbit_Light_Type_Mark_Orange.png" height="44" style="max-width:180px;" alt="CodeRabbit - AI-powered code review and automated pull request analysis"> </picture> </a><br> _{<span style="white-space:nowrap;">AI Code Review</span><br> <a href="https://coderabbit.link/nir"> <img src="assets/repos_images/visit-site-badge.svg" width="56" height="16" alt="Visit CodeRabbit AI code review platform"> </a>} </td> </table> <div align="center">

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💬 Join Our Community

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Join our growing community discussing cutting-edge AI research, agent development, and production insights!

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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.

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📑 Related deep-dive write-ups

Free long-form guides on DiamantAI that complement these production tutorials:

• Why AI agents need to check their own work
• This simple trick makes AI agents far more reliable
• Memory optimization strategies in AI agents
• Agent Memory Techniques — 30 runnable notebooks on giving production agents memory: buffers, vector stores, knowledge graphs, Mem0, MemGPT/Letta, Zep, and Graphiti
• Browse all 130+ tutorials → · Read the blog →

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🏗️ AI Agent Architecture

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

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📚 Tutorials

🔌 Tool Integration

<table width="100%"> <tr style="background-color:#f8f9fa"> <th width="30%">Tutorial</th> <th width="50%">Description</th> <th width="20%">View</th> </tr> <tr> <td>Secure Tool Calling (Arcade) <img src="https://img.shields.io/badge/NEW-brightgreen" height="16"></td> <td>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.</td> <td align="center"> <a href="tutorials/arcade-secure-tool-calling"><img src="https://img.shields.io/badge/GitHub-View-blue" height="20"></a> </td> </tr> </table>

📊 Data Processing

<table width="100%"> <tr style="background-color:#f8f9fa"> <th width="30%">Tutorial</th> <th width="50%">Description</th> <th width="20%">View</th> </tr> <tr> <td>Web Data Collection for AI Agents (Bright Data) <img src="https://img.shields.io/badge/NEW-brightgreen" height="16"></td> <td>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.</td> <td align="center"> <a href="https://github.com/NirDiamant/agents-towards-production/tree/main/tutorials/agent-with-brightdata"><img src="https://img.shields.io/badge/GitHub-View-blue" height="20"></a> </td> </tr> <tr> <td>Real-Time Web Data Integration for Agents (Tavily)</td> <td>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.</td> <td align="center"> <a href="https://github.com/NirDiamant/agents-towards-production/tree/main/tutorials/agent-with-tavily-web-access"><img src="https://img.shields.io/badge/GitHub-View-blue" height="20"></a> </td> </tr> </table>

🔍 RAG & Knowledge Management

<table width="100%"> <tr style="background-color:#f8f9fa"> <th width="30%">Tutorial</th> <th width="50%">Description</th> <th width="20%">View</th> </tr> <tr> <td>Production-Ready RAG Agents with Contextual AI (Contextual AI)</td> <td>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.</td> <td align="center"> <a href="tutorials/agent-RAG-with-Contextual"><img src="https://img.shields.io/badge/GitHub-View-blue" height="20"></a> </td> </tr> </table>

🧠 Memory

<table width="100%"> <tr style="background-color:#f8f9fa"> <th width="30%">Tutorial</th> <th width="50%">Description</th> <th width="20%">View</th> </tr> <tr> <td>Agent Memory: Dual-Memory & Semantic Search (Redis)</td> <td>Implement dual-memory (short-term and long-term), semantic search, and persistent state for agents that remember user preferences and learn from conversations.</td> <td align="center"> <a href="https://github.com/NirDiamant/agents-towards-production/tree/main/tutorials/agent-memory-with-redis"><img src="https://img.shields.io/badge/GitHub-View-blue" height="20"></a> </td> </tr> <tr> <td>Self-Improving Memory with Mem0: Hybrid Vector & Graph Storage <img src="https://img.shields.io/badge/NEW-brightgreen" height="16"></td> <td>Build intelligent agents with self-improving memory that automatically extracts insights, resolves conflicts, and evolves with each interaction. Learn hybrid memory architecture combining vector search for semantic recall and graph databases for relationship mapping.</td> <td align="center"> <a href="https://github.com/NirDiamant/agents-towards-production/tree/main/tutorials/agent-memory-with-mem0"><img src="https://img.shields.io/badge/GitHub-View-blue" height="20"></a> </td> </tr> <tr> <td>AI Memory with Cognee</td> <td>Build intelligent AI memory systems that learn from Python's creator and improve your development workflow. Transform scattered development data into unified knowledge graphs with contextual insights.</td> <td align="center"> <a href="https://github.com/NirDiamant/agents-towards-production/tree/main/tutorials/ai-memory-with-cognee"><img src="https://img.shields.io/badge/GitHub-View-blue" height="20"></a> </td> </tr> </table>

🚀 Deployment

<table width="100%"> <tr style="background-color:#f8f9fa"> <th width="30%">Tutorial</th> <th width="50%">Description</th> <th width="20%">View</th> </tr> <tr> <td>AWS Bedrock AgentCore: Managed Agent Deployment <img src="https://img.shields.io/badge/NEW-brightgreen" height="16"></td> <td>Deploy and manage AI agents on AWS Bedrock AgentCore Runtime. Learn to transform local agents into production-ready managed services with automatic infrastructure, request tracking, and standardized communication patterns.</td> <td align="center"> <a href="https://github.com/NirDiamant/agents-towards-production/tree/main/tutorials/aws_agentcore"><img src="https://img.shields.io/badge/GitHub-View-blue" height="20"></a> </td> </tr> <tr> <td>Containerizing Agents with Docker</td> <td>Containerize agents for portability and scalability. Learn foundational patterns for running agents in containers across environments.</td> <td align="center"> <a href="https://github.com/NirDiamant/agents-towards-production/tree/main/tutorials/docker-intro"><img src="https://img.shields.io/badge/GitHub-View-blue" height="20"></a> </td> </tr> <tr> <td>On-Prem LLM Deployment with Ollama</td> <td>Run and interact with large language models locally. Replace cloud APIs with on-prem models for privacy, cost control, and low-latency agent workflows.</td> <td align="center"> <a href="https://github.com/NirDiamant/agents-towards-production/tree/main/tutorials/on-prem-llm-ollama"><img src="https://img.shields.io/badge/GitHub-View-blue" height="20"></a> </td> </tr> </table>

👥 Multi-agent Coordination

<table width="100%"> <tr style="background-color:#f8f9fa"> <th width="30%">Tutorial</th> <th width="50%">Description</th> <th width="20%">View</th> </tr> <tr> <td>Multi-Agent Communication with A2A Protocol</td> <td>Simulate collaborative agent workflows and message exchange using open communication protocols for interoperability.</td> <td align="center"> <a href="https://github.com/NirDiamant/agents-towards-production/tree/main/tutorials/a2a"><img src="https://img.shields.io/badge/GitHub-View-blue" height="20"></a> </td> </tr> </table>

🚀 GPU Deployment

<table width="100%"> <tr style="background-color:#f8f9fa"> <th width="30%">Tutorial</th> <th width="50%">Description</th> <th width="20%">View</th> </tr> <tr> <td>Scalable GPU Deployment for AI Agents (Runpod)</td> <td>Deploy AI agents on scalable GPU infrastructure. Learn to set up cost-effective, high-performance environments for demanding agent workloads.</td> <td align="center"> <a href="https://github.com/NirDiamant/agents-towards-production/tree/main/tutorials/runpod-gpu-deploy"><img src="https://img.shields.io/badge/GitHub-View-blue" height="20"></a> </td> </tr> </table>

🔒 Security

<table width="100%"> <tr style="background-color:#f8f9fa"> <th width="30%">Tutorial</th> <th width="50%">Description</th> <th width="20%">View</th> </tr> <tr> <td>Comprehensive Agent Security (LlamaFirewall)</td> <td>Apply comprehensive input, output, and tool security guardrails for agents. Covers prompt injection, behavior alignment, and tool access control.</td> <td align="center"> <a href="https://github.com/NirDiamant/agents-towards-production/tree/main/tutorials/agent-security-with-llamafirewall"><img src="https://img.shields.io/badge/GitHub-View-blue" height="20"></a> </td> </tr> <tr> <td>Hands-On Agent Security Evaluation (Apex)</td> <td>Hands-on prompt injection attacks, defenses, and automated security testing for AI agents.</td> <td align="center"> <a href="tutorials/agent-security-apex"><img src="https://img.shields.io/badge/GitHub-View-blue" height="20"></a> </td> </tr> </table>

👥 Multi-agent Coordination

<table width="100%"> <tr style="background-color:#f8f9fa"> <th width="30%">Tutorial</th> <th width="50%">Description</th> <th width="20%">View</th> </tr> <tr> <td>Multi-Agent Communication with A2A Protocol</td> <td>Simulate collaborative agent workflows and message exchange using open communication protocols for interoperability.</td> <td align="center"> <a href="https://github.com/NirDiamant/agents-towards-production/tree/main/tutorials/a2a"><img src="https://img.shields.io/badge/GitHub-View-blue" height="20"></a> </td> </tr> </table>

🧩 Agent Frameworks

<table width="100%"> <tr style="background-color:#f8f9fa"> <th width="30%">Tutorial</th> <th width="50%">Description</th> <th width="20%">View</th> </tr> <tr> <td>Tool & API Integration via Model Context Protocol (MCP)</td> <td>Integrate agents with external tools and APIs using a standardized protocol. Example: Seamless tool and API integration for advanced agent workflows.</td> <td align="center"> <a href="https://github.com/NirDiamant/agents-towards-production/tree/main/tutorials/agent-with-mcp"><img src="https://img.shields.io/badge/GitHub-View-blue" height="20"></a> </td> </tr> <tr> <td>Stateful Agent Workflows with LangGraph</td> <td>Design complex, stateful agent workflows using a directed graph architecture. Example: Multi-step text analysis pipeline with classification, entity extraction, and summarization.</td> <td align="center"> <a href="https://github.com/NirDiamant/agents-towards-production/tree/main/tutorials/LangGraph-agent"><img src="https://img.shields.io/badge/GitHub-View-blue" height="20"></a> </td> </tr> <tr> <td>Deploying Agents as APIs with FastAPI</td> <td>Create and deploy agents as performant APIs, supporting both synchronous and streaming endpoints.</td> <td align="center"> <a href="https://github.com/NirDiamant/agents-towards-production/tree/main/tutorials/fastapi-agent"><img src="https://img.shields.io/badge/GitHub-View-blue" height="20"></a> </td> </tr> <tr> <td>Building AI Agents in <a href="https://europe-west1-atp-views-tracker.cloudfunctions.net/working-analytics?notebook=agents-towards-production--readme&click=kotlinlang&target=https%3A%2F%2Fkotlinlang.org%2F%3Futm_source%3Dgithub%26utm_medium%3Dinfluencers%26utm_campaign%3Dkotlin_nir_supporter_1&text=Kotlin">Kotlin</a> with Koog <img src="https://img.shields.io/badge/NEW-brightgreen" height="16"></td> <td>Build your first AI agent in <a href="https://europe-west1-atp-views-tracker.cloudfunctions.net/working-analytics?notebook=agents-towards-production--readme&click=kotlinlang&target=https%3A%2F%2Fkotlinlang.org%2F%3Futm_source%3Dgithub%26utm_medium%3Dinfluencers%26utm_campaign%3Dkotlin_nir_supporter_1&text=Kotlin">Kotlin</a> using JetBrains' Koog framework. Step-by-step from hello world to tool calling and structured output in under 30 minutes.</td> <td align="center"> <a href="https://github.com/NirDiamant/agents-towards-production/tree/main/tutorials/kotlin-agent-with-koog"><img src="https://img.shields.io/badge/GitHub-View-blue" height="20"></a> </td> </tr> </table>

🛠️ Model Customization

<table width="100%"> <tr style="background-color:#f8f9fa"> <th width="30%">Tutorial</th> <th width="50%">Description</th> <th width="20%">View</th> </tr> <tr> <td>Fine-Tuning AI Agents for Domain Expertise & Efficiency</td> <td>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.</td> <td align="center"> <a href="https://github.com/NirDiamant/agents-towards-production/tree/main/tutorials/fine-tuning-agents"><img src="https://img.shields.io/badge/GitHub-View-blue" height="20"></a> </td> </tr> </table>

🔍 Tracing & Debugging

<table width="100%"> <tr style="background-color:#f8f9fa"> <th width="30%">Tutorial</th> <th width="50%">Description</th> <th width="20%">View</th> </tr> <tr> <td>Agent Tracing & Debugging with LangSmith</td> <td>Add comprehensive observability to AI systems. Capture detailed traces, decision points, and timing data to debug, monitor, and systematically improve agent performance.</td> <td align="center"> <a href="https://github.com/NirDiamant/agents-towards-production/tree/main/tutorials/tracing-with-langsmith"><img src="https://img.shields.io/badge/GitHub-View-blue" height="20"></a> </td> </tr> </table>

📊 Evaluation

<table width="100%"> <tr style="background-color:#f8f9fa"> <th width="30%">Tutorial</th> <th width="50%">Description</th> <th width="20%">View</th> </tr> <tr> <td>Automated Agent Evaluation & Behavioral Analysis (IntellAgent)</td> <td>Automate agent evaluation with behavioral analysis, performance metrics, and actionable insights for improving agent quality.</td> <td align="center"> <a href="https://github.com/NirDiamant/agents-towards-production/tree/main/tutorials/agent-evaluation-intellagent"><img src="https://img.shields.io/badge/GitHub-View-blue" height="20"></a> </td> </tr> </table>

🖥️ UI & Frontend

<table width="100%"> <tr style="background-color:#f8f9fa"> <th width="30%">Tutorial</th> <th width="50%">Description</th> <th width="20%">View</th> </tr> <tr> <td>Building a Chatbot UI with Streamlit</td> <td>Build a beginner-friendly chatbot web app with a chat interface, file upload, and session state for interactive agent demos.</td> <td align="center"> <a href="https://github.com/NirDiamant/agents-towards-production/tree/main/tutorials/agent-with-streamlit-ui"><img src="https://img.shields.io/badge/GitHub-View-blue" height="20"></a> </td> </tr> </table>

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🚀 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.

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Quick Setup

1. Get the Code

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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:

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# 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:

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# Run interactive notebooks for experimentation
jupyter notebook tutorial.ipynb

# Execute production scripts for integration testing
python app.py

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📚 Recommended reading

This list contains Amazon affiliate links. As an Amazon Associate I earn from qualifying purchases. Every book below is one I've read and genuinely recommend to engineers working in this space. The companion book to this repo is featured separately at the top of this README.

• Build a Large Language Model (From Scratch) by Sebastian Raschka. Build a GPT-style model end to end in PyTorch.
• AI Engineering: Building Applications with Foundation Models by Chip Huyen. Canonical reference for productionizing foundation-model apps.
• Hands-On Large Language Models by Jay Alammar and Maarten Grootendorst. Visual, practical LLM walkthroughs.
• Natural Language Processing with Transformers by Lewis Tunstall, Leandro von Werra, and Thomas Wolf. From the Hugging Face team.
• Designing Machine Learning Systems by Chip Huyen. ML systems in production, still the standard reference.

🤝 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.

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⚠️ 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.

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📜 License

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

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

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