Build an LLM Application From Scratch | Mistral 7B + RAG + FastAPI | Part 11

How do you turn everything you've learned about LLMs into a real AI application? 🤖 In the final episode of LLMs Explained From Zero, we put everything together and build an LLM application using Mistral 7B, RAG and FastAPI. 🔥 You'll learn: ✅ How an LLM application is architected ✅ Frontend vs backend vs AI model ✅ Building an API with FastAPI ✅ Connecting Mistral 7B to an application ✅ RAG with your own documents ✅ Conversation history ✅ Tool calling and external APIs ✅ How LoRA fits into an AI application ✅ Context windows and memory ✅ Scaling an LLM application ✅ Model serving, streaming and logging ✅ AI application security ✅ How to evaluate an AI system 💻 We'll build the complete flow: User → Frontend → FastAPI → RAG → Mistral → Answer And we'll connect the concepts from all 11 parts into one practical AI application. 🚀 LLMs Explained From Zero Part 1 — How ChatGPT & LLMs Actually Work Part 2 — What Are AI Tokens? Part 3 — What Are Embeddings? Part 4 — How Attention Works Part 5 — Transformers & Mistral 7B Architecture Part 6 — How LLMs Learn: Train a Tiny LLM Part 7 — How LLMs Generate Text Part 8 — Run Mistral 7B on a GPU Part 9 — RAG: Give Your LLM Your Own Knowledge Part 10 — Fine-Tuning Mistral with LoRA & QLoRA 👉 Part 11 — Build an LLM Application From Scratch 🌐 Skillcef: https://skillcef.com 📱 Skillcef App: https://play.google.com/store/apps/de... #LLM #Mistral7B #RAG #FastAPI #AI #GenerativeAI #Python #LLMApplication #MachineLearning #HuggingFace #LoRA #QLoRA #ArtificialIntelligence #LLMsExplained #Skillcef