Hidden Model Settings That Will Transform Your Agents

Join AI Dev Skool & Launch Your AI Startup Today! https://skool.com/ai-software-developers is the community for founders, builders, and AI innovators ready to take their projects to the next level. If you're launching an AI startup or working on a side project, stop wasting time on endless tutorials and start focusing on what really matters. Inside AI Dev Skool, you'll: ✅ Get expert guidance on the best AI frameworks ✅ Cut through the hype and go straight to what works ✅ Maximize your time with curated resources and real-world insights ✅ Build strong connections with like-minded developers and founders Our best members actively engage, share, and build—gaining skills while turning ideas into real businesses. If you're serious about AI development and want a shortcut to success, this is the place for you. 🚀 Join now and start building smarter: https://skool.com/ai-software-developers Today we're taking a detailed look at how to customize advanced model settings to optimize your AI application performance. Model settings allow fine-grained control over model behavior, enabling us, developers to balance accuracy, speed, and resource consumption for specific use cases. We'll explore how parameter adjustment impacts model outputs, from temperature and top-p settings to more specialized configurations like context window optimization and token management. And stick around, because I will show you a nifty way to encourage or discorage the use of certain tokens by your model. Before we dive further, let's talk about the importance of model settings. We’ll start with a "Hello, World!" example and progressively build towards more complex model settings. 💡 Examples: 1️⃣ Hello, World! - Basic Model Settings 2️⃣ OpenAI Model Settings 3️⃣ Gemini Model Settings Masterclass Series: ▶️ Part 1: https://youtu.be/xVe87QpNE80 ▶️ Part 2: https://youtu.be/TTNT3rnuZp0 ▶️ Part 3: https://youtu.be/PXO9_nWZYrc ▶️ Part 4: https://youtu.be/WQqsiB0xUXk ▶️ Part 5: https://youtu.be/4UN2emXnxN4 ▶️ Part 6: https://youtu.be/2B5uDly91gY ▶️ Part 7: https://youtu.be/wSHX-a-aCmk ▶️ Part 8: https://youtu.be/7E-nR_l53yo ▶️ Part 9: https://youtu.be/-WicGJ9JRwc ▶️ Part 10: https://youtu.be/sFKWjx_ITIg ▶️ Part 11: https://youtu.be/Ah2bs0urf6A ▶️ Part 12: https://youtu.be/Q1ljY_tALZU ▶️ Part 13: Multi-Model Agents in PydanticAI: Unlocking Next-Gen AI Capabilities ▶️ Part 14: Mastering RAG in PydanticAI: Better AI Agents with Real-Time Data ▶️ Part 15: Masterclass Final Project: AI Resume Writing with Multiple Agents 🎯 Whether you're building a chatbot, an AI agent, or any other LLM-powered system, this tutorial provides practical examples to elevate your application’s ability to get better outputs from AI. What agents are you building? Join the conversation at https://discord.gg/eQXBaCvTA9 🔗 Links & Resources: - Skool: https://www.skool.com/ai-software-developers - Code the Revolution: Newsletter - https://aidev9.substack.com/ - Discord server: https://discord.gg/eQXBaCvTA9 - PydanticAI: https://ai.pydantic.dev - OpenAI Logit Bias: https://help.openai.com/en/articles/5247780-using-logit-bias-to-alter-token-probability-with-the-openai-api #ai #openai #pydantic #ollama #pydanticai #mistral #llm #developer #software #tutorial #genai #llama #local #private #chatgpt #prompt #validation #sql #python #generation #code