This article describes how the author scaled a FastAPI service to handle 200,000 requests per minute using Gunicorn + Uvicorn workers and Kubernetes Horizontal Pod Autoscaler, with async endpoint optimization and autoscaling strategies ➤ https://t.co/28cAQzN4iA

クラウド無し、DGX Spark一台で完結する3D音声チャットボット作ってみた STT(whisper)→RAG(FAISS)→LLM(gpt-oss-20b@llama.cpp)→TTS(fish speech)をFastAPIで繋いでthree-vrmで表示、docker composeで一発起動する感じ 現状の消費VRAMは35G 今後は応答速度の最適化とかアニメーション生成とかやる

Every AI/ML engineer needs to know this. 58 tutorials. Free. Why AI/ML engineers need FastAPI: You built an amazing model. Now what? → Serve predictions via API → Build model monitoring dashboards → Deploy ML apps to production → Create data annotation tools FastAPI is

a lot of people in AI/ML struggle when it comes to the dev / product side if you want to explore dev here's my suggestion : > pick up reactjs or next js > basic tailwind for styling > get comfortable with fastapi or nextjs server > postgres as database > docker for

MODERN FULL-STACK AI TECH STACK Frontend: React Next.js TailwindCSS TypeScript Backend: Node.js Express FastAPI Python (for AI microservices) Database: MongoDB PostgreSQL Redis (for caching) AI & ML Layer: OpenAI API LangChain Vector Databases (Pinecone / Weaviate) Hugging

Client is hiring for a Full-Stack Developer. Compensation: USD 15–20k Location: Remote Experience: 0–3 years Work Hours: US shift Tech Stack: Next.js, FastAPI, Node.js, Azure, PostgreSQL Share your GitHub, resume, or portfolio URL. I will only be able to forward a limited number

Started learning springboot👨‍💻 once again in depth Still wondering 🤔 is it worth it when you already know python django and fastAPI Spring boot devs let's connect✅ #springboot #Java

You've seen @FastAPI popping up here and there & you're still wondering how it works? Its creator, Sebastián (@tiangolo) explains... 👀

FastAPI is hands down the best for backend and APIs: simple, lightweight, friendly syntax, supports async.

building API already with fastapi, it cool to learn, DAY15 python

Enterprise backend architecture solution for FastAPI https://t.co/w043SIp8CC

math & statistics ↓ python ↓ classical ml ↓ advanced ml ↓ nlp ↓ deep learning ↓ transformers ↓ langchain ↓ langgraph ↓ mcps ↓ finetuning ↓ fastapi congrats you are an ai engineer now

🚀 I’m looking for a talented #Backend Python (#FastAPI) Developer or a React Native Mobile Engineer to join an #AI-driven project in the e-commerce space. The product vision, functional scope, architecture, and technical documentation are already finalized ⬇️

The full-stack-fastapi-template now uses @shadcn / ui (with @tailwindcss) for the frontend 🚀🎉 There's still dark mode too, and all the nice things 🦇 Thanks @alejsdev ! 🙌 https://t.co/o20d40hCPD

Yo, #OCaml web devs! You no longer have to shy away from those beautiful FastAPI docs. With tapak, you get automatic OpenAPI generation and OCaml's robust type system. Checkmate, Python! 😉 #OpenAPI

FastAPI is underrated.

Bug fix releases: FastAPI 0.124.3 and 0.124.4 🐛 The highlight: YuriiMotov fixed support for @pydantic aliases (validation and serialization) in multiple edge cases. 🚀 If there are no new reports, FastAPI will drop support for Python 3.8 next week. ⚰️ https://t.co/LfpZnNf9MT

5 reasons why you are struggling with learning MLOps: - No prior knowledge of modular Python scripting - Not breaking ML projects into smaller pieces - Lacking knowledge of FastAPI - No understanding of DevOps concepts - Chasing tools without designing systems

Ever wondered how @FastAPI became one of the go-to frameworks for Python developers? 🚀 In this mini-documentary, @tiangolo shares the story behind the project, from solving his developer headaches to powering code at Netflix, Uber, and the James Webb Space Telescope. It’s a