WhatsApp AI Agent Tutorial 5: Ava Learns to See | VLM (Llama 3.2 Vision) and text-to-image (FLUX)
Автор: Jesús Copado
Загружено: 2025-03-04
Просмотров: 904
In this fifth tutorial, we upgrade Ava’s multimodal abilities by adding vision and image generation. First, we explore Vision Language Models (VLMs) — specifically Llama 3.2 Vision on Groq — so Ava can interpret images and produce descriptive text. Then, we dive into text-to-image workflows using FLUX schnell from Together.ai, enabling Ava to generate images on the fly. You’ll see an image diagram illustrating how everything ties together, followed by a code overview explaining each step in Ava’s pipeline. Finally, we wrap up with an overview of Together.ai to show how easy it is to plug in advanced image models. By the end, you’ll know how to integrate both image understanding and image creation into your WhatsApp AI agent, making Ava truly see and create in real time!
Links:
• Miguel’s Newsletter: https://theneuralmaze.substack.com
• Project GitHub: https://github.com/neural-maze/ai-com...
• Understanding Multimodal LLMs (Sebastian Raschka): https://sebastianraschka.com/blog/202...
• Text-to-Image Model Comparison: https://artificialanalysis.ai/text-to...
• Together.ai Platform: https://www.together.ai
Chapters:
00:00 Intro
01:22 Image Diagram
02:15 VLM Explanation
07:57 MLLMs vs VLMs
08:53 MLLMs Review
11:06 Text-to-Image Review
14:00 Together.ai Overview
16:54 Code Overview
#aiagents #whatsappagent #multimodal #vision #groq #llama #togetherai #texttoimage #multimodalai #aiagent #python #llm
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