Video yükleniyor...

Video Yüklenemedi

Ana Sayfaya Dön

Reflex (Reflex) is an AI app builder for creating production-grade web apps entirely in Python, powered by its own open-source framework. Just connect your data and enter a prompt. It generates production-ready apps that integrate any data source, API, or Python package. Reflex has over 1M apps created, 27k...

18,251 görüntüleme • 10 ay önce •via X (Twitter)

16 Yorum

Kunal Kushwaha profil fotoğrafı
Kunal Kushwaha10 ay önce

@getreflex Congrats!

Igor Buinevici profil fotoğrafı
Igor Buinevici10 ay önce

@getreflex To more new heights, guys!!!

Bhavishya Pandit profil fotoğrafı
Bhavishya Pandit10 ay önce

@getreflex Congratulations team! To the moon ✨

Sumanth profil fotoğrafı
Sumanth10 ay önce

@getreflex Congrats team, Let's go! 🔥

Arindam Majumder 𝕏 profil fotoğrafı
Arindam Majumder 𝕏10 ay önce

@getreflex This is Amazing!

Ritika profil fotoğrafı
Ritika10 ay önce

@getreflex Reflex proves how fast AI is remaking fintech-automation is urgent, ethical adaptation even more so. Now's the time to prioritize upskilling so no one is left behind in this new landscape.

The Longer Game profil fotoğrafı
The Longer Game10 ay önce

@getreflex Impressive stats and a solid use case. Being able to generate production-ready web apps entirely in Python and integrate any data source or API could massively streamline internal tools development.

Gleb Molchanov profil fotoğrafı
Gleb Molchanov10 ay önce

@getreflex Great work — we’ve been building the mental health equivalent: an AI therapist trained to understand, remember, and adapt to each user like a personalized system.

Murad profil fotoğrafı
Murad10 ay önce

@getreflex Curious this could make building fully functional Python apps almost effortless for non-experts.

Waqas | Ex-Google profil fotoğrafı
Waqas | Ex-Google10 ay önce

@getreflex Phenomenal growth 👀

Greg Coquillo profil fotoğrafı
Greg Coquillo10 ay önce

@getreflex Awesome

Afiz ⚡️ profil fotoğrafı
Afiz ⚡️10 ay önce

@getreflex Congrats on the 1M apps creation.

wyswyswys profil fotoğrafı
wyswyswys10 ay önce

@getreflex Is YC really that desperate?

sai kumar bysani profil fotoğrafı
sai kumar bysani10 ay önce

@getreflex Yayy!! This is amazing:)

Neo Kim profil fotoğrafı
Neo Kim10 ay önce

@getreflex congrats + all the best!

Mehul Agarwal profil fotoğrafı
Mehul Agarwal10 ay önce

@getreflex The neck snap at the start 😂

Benzer Videolar

New course: MCP: Build Rich-Context AI Apps with Anthropic. Learn to build AI apps that access tools, data, and prompts using the Model Context Protocol in this short course, created in partnership with Anthropic Anthropic and taught by Elie Schoppik Elie Schoppik, its Head of Technical Education. Connecting AI applications to external systems that bring rich context to LLM-based applications has often meant writing custom integrations for each use case. MCP is an open protocol that standardizes how LLMs access tools, data, and prompts from external sources, and simplifies how you provide context to your LLM-based applications. For example, you can provide context via third-party tools that let your LLM make API calls to search the web, access data from local docs, retrieve code from a GitHub repo, and so on. MCP, developed by Anthropic, is based on a client-server architecture that defines the communication details between an MCP client, hosted inside the AI application, and an MCP server that exposes tools, resources, and prompt templates. The server can be a subprocess launched by the client that runs locally or an independent process running remotely. In this hands-on course, you'll learn the core architecture behind MCP. You’ll create an MCP-compatible chatbot, build and deploy an MCP server, and connect the chatbot to your MCP server and other open-source servers. Here’s what you’ll do: - Understand why MCP makes AI development less fragmented and standardizes connections between AI applications and external data sources - Learn the core components of the client-server architecture of MCP and the underlying communication mechanism - Build a chatbot with custom tools for searching academic papers, and transform it into an MCP-compatible application - Build a local MCP server that exposes tools, resources, and prompt templates using FastMCP, and test it using MCP Inspector - Create an MCP client inside your chatbot to dynamically connect to your server - Connect your chatbot to reference servers built by Anthropic’s MCP team, such as filesystem, which implements filesystem operations, and fetch, which extracts contents from the web as markdown - Configure Claude Desktop to connect to your server and others, and explore how it abstracts away the low-level logic of MCP clients - Deploy your MCP server remotely and test it with the Inspector or other MCP-compatible applications - Learn about the roadmap for future MCP development, such as multi-agent architecture, MCP registry API, server discovery, authorization, and authentication MCP is an exciting and important technology that lets you build rich-context AI applications that connect to a growing ecosystem of MCP servers, with minimal integration work. Please sign up here!

Andrew Ng

142,234 görüntüleme • 1 yıl önce