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Welcome back to the final installment of our "Build Your Own Agents" series at Imantix AI Academy! This is Part 3, where we complete our Voice Agent for Child Tutor by integrating the crucial audio feedback layer: Text-to-Speech (TTS). In the previous parts, we successfully achieved: Speech-to-Text (ASR): Converting the child's question ("How do I tie my shoelaces?") into text. (Using NVIDIA Parakeet, later transitioning to GPT-4o Mini Transcribe). LLM & Image Generation: Using models like Gemma via Ollama and Google's Nano Banana to generate step-by-step instructions and corresponding visual guides (images). In This Episode (Part 3), We Cover: Implementing Text-to-Speech (TTS) to read out the generated instructions for a complete pictorial and audio experience. Exploring open-source TTS models available on Hugging Face. Making an architectural shift to leverage the speed and cost-efficiency of OpenAI's GPT-4o Mini suite (Transcribe, LLM, and TTS) for all core processing layers. Using the GitHub Copilot (powered by Groq code fast) as our new coding agent to quickly implement and iterate on the changes. A practical guide to setting up and managing your OpenAI Platform API keys and cost limits. Troubleshooting and iterating with the AI agent to ensure both the introductory message and the step-by-step guide are fully read out. Follow along to see the final, multi-modal voice agent in action, helping children with special needs master simple tasks like brushing teeth and tying shoelaces! Next Steps: We encourage you to build your own version! Share your feedback, suggestions, and improvements in the comments below! #AIAgents #VoiceAgent #TextToSpeech #TTS #GPT4oMini #OpenAICode #AIforKids #SpecialNeedsTech #MultiModalAI #ImmanticAIAcademy #CodingAgent #GitHubCopilot #AIProject