Fri, Apr 5, 2024Advanced port configuration
We recently spent a few months making ports easier to work with on Replit, so you can develop more complex apps predictably. What are ports? When a computer receives a TCP/UDP request, ports define which program that request should route to. (If you need a more basic explanation of TCP ports, start here). On a normal computer, you only have one layer of ports: your programs define a port that they listen to, and when traffic hits that port on your computer from the internet, it gets routed to the appropriate process. Some protocols have defined standard ports — for example, Simple Mail Transfer Protocol Secure (SMTPS), the email protocol, generally listens on port 587, and most web servers listen on either port 80 (HTTP, unencrypted) or port 443 (HTTPS, encrypted). You can think of ports like mailboxes. Imagine those big mailrooms in skyscrapers that ensure the mail lands in the right mailbox — the mail is the data being sent and received, and the mailboxes are the ports.
Wed, Apr 3, 2024Replit Developer Day recap
On April 2nd, we hosted our second annual Developer Day live from San Francisco. We announced our biggest evolution yet – we’re making the power of Replit available for teams. Here’s the full recap. Our mission Replit’s mission is to empower the next billion software creators. We are at an incredibly unique time in history, where for the first time, anyone with basic access to a computer and the internet can learn skills that can fundamentally change their lives. This kind of wealth creation opportunity has not existed before. Soon, what it means to be a software developer is going to look radically different than it does today. Replit is not just for hackers and engineers; we also want to empower builders of all kinds: artists, scientists, and citizen developers. If you have an idea, you should be able to build it and ship it. Empowerment is at the heart of our mission.
Tue, Apr 2, 2024Get early access to Replit Teams
We’re bringing the power of Replit to your team, so that you can collaborate, develop, and deploy software together. The future of collaborative software development is coming soon. We're thrilled to give a set of customers early access to what we've been working on: a new Replit Teams product that will redefine how software is made collaboratively with AI. Some highlights we’re excited about: Organizational intelligence: Unleash AI-powered code completion, chat, and retrieval-augmented generation (RAG) across your team. Ultra-fast workspaces: Access 8vCPUs and 16GB RAM machines, ensuring your team has a smooth workspace experience.
Tue, Apr 2, 2024Building LLMs for Code Repair
Introduction At Replit, we are rethinking the developer experience with AI as a first-class citizen of the development environment. Towards this vision, we are tightly integrating AI tools with our IDE. Currently, LLMs specialized for programming are trained with a mixture of source code and relevant natural languages, such as GitHub issues and StackExchange posts. These models are not trained to interact directly with the development environment and, therefore, have limited ability to understand events or use tools within Replit. We believe that by training models native to Replit, we can create more powerful AI tools for developers. A simple example of a Replit-native model takes a session event as input and returns a well-defined response. We set out to identify a scenario where we could develop a model that could also become a useful tool for our current developers and settled on code repair. Developers spend a significant fraction of their time fixing bugs in software. In 2018, when Microsoft released “A Common Protocol for Languages,” Replit began supporting the Language Server Protocol. Since then, the LSP has helped millions using Replit to find errors in their code. This puts LSP diagnostics among our most common events, with hundreds of millions per day. However, while the LSP identifies errors, it can only provide fixes in limited cases. In fact, only 10% of LSP diagnostic messages in Python projects on Replit have associated fixes. Given the abundance of training data, repairing code errors using LSP diagnostics is therefore the ideal setting to build our first Replit-native AI model. Methodology Data
Mon, Apr 1, 2024Builder Profile: Pietro Schirano
Pietro Schirano is the co-founder of EverArt. By pursuing his ideas on Replit, he’s been able to nurture a curiosity in AI into a startup with multiple apps and functions, run on Replit. After starting his career in civil engineering, Pietro wanted to explore more creative endeavors. This journey would lead him to hold design lead roles across household names like OpenTable, Meta, Uber, and Brex, and eventually, to launch his own startup. An avid social learner, Pietro picked up skills across marketing, business, and engineering in each of his jobs. One topic that particularly grabbed his attention was AI. After ChatGPT launched, Pietro says, “I had an epiphany that the world was never going to be the same.” Immediately, he started to test emerging AI tools, eventually sharing a prototype with his team at Brex that landed him a role as their AI team lead. “Replit was the easiest A to B to get people experimenting with whatever product I wanted to test.”
Mon, Apr 1, 2024Builder Profile: Mason Kim
As a Global DevOps Engineer at Zinus, Mason (Junkuk) Kim’s role is to build software to enable the marketing, business, and customer service teams to deliver their customers the highest quality support experience. Often, the required turnaround time for these projects is extremely short, and Mason will need to have a solution ready within days or even hours. Even more, the teams he is supporting are based in numerous countries around the globe. The speed at which Mason’s team can build and deploy a working web service on Replit is the primary reason he chose the platform. Zinus uses Shopify to host its e-commerce site, which they extend using an external front-end development platform. However, Mason’s team was recently tasked with switching off of their old front-end development platform and finding a new one. Their old platform caused excessively long response times to service requests from Zinus, which harmed their business. Mason had to redevelop the older web pages on the new platform in just a few weeks to ensure a smoother support process. “At that moment, no other platform but Replit came to mind, and I had limited time to complete the development. In our situation, Replit was the best choice.”
Fri, Mar 29, 2024Searching Nixpkgs in Under 30 Milliseconds
Today, we’re releasing the first version of rippkgs, a CLI utility for indexing and searching Nix expressions. With rippkgs, you can quickly search the nixpkgs available to your system with accurate results. Read on for more details about why we created it, how to use it, and how it works. Motivation At Replit, we use Nix to empower millions of users with hundreds of programming languages. The power of Nix’s reproducible expressions allows us to share system packages fearlessly and quickly with ultimate flexibility for end users. However, users are often not familiar with Nix, so we need to give them the tools they need to interact with it comfortably. Experienced Nix users looking to install or use a package may reach for nix-env, nix search, nix-locate, or search.nixos.org. These tools are excellent for visibility into what’s available in the largest package repository, nixpkgs. Unfortunately, none of these tools give us what we need to provide great search for Replit users: nix-env and nix search are bundled with Nix, which means they’re already accessible in Replit environments, but searching for a package can take several seconds - way too long for those of us who are impatient and just want to find what we’re looking for quickly. nix-locate works by indexing built derivation paths, which is great when you know the path you’re looking for (like /bin/jq), but not great when looking for a package with unknown output formats.
Tue, Mar 26, 2024Introducing Scheduled Deployments
Today, we are launching Scheduled Deployments. This service allows you to schedule your applications to run at predetermined time intervals seamlessly. Specify when the application should run in natural language, and Replit will take care of the rest. Scheduling has always been a popular use case on Replit, but configuring an application like this was difficult. Most developers set up schedulers by deploying an infinite loop that constantly checked the time to a Reserved VM. This process not only had a lot of overhead, but was also inefficient and costly. Now, you can write something like, “Run this script every Tuesday and Thursday at 3:00 PM,” and we’ll generate the cron expression for you so that you can focus on building. What you can build In our closed beta, developers have used Scheduled Deployments to build applications like:
Mon, Mar 18, 2024More Reliable Connections to Your Repls
At Replit, session success rate is one of our service level objectives (SLOs). This means that any legitimate incoming request from a client should always be successfully connected to its target Repl. Failure to do so is a bad user experience. To abstract away intermittent infrastructure failures when you connect to a Repl, we use a reverse WebSocket proxy between the user’s client and the remote VM hosting Conman, our container manager that runs all Repls in a container. The high-level view of this proxying looks something like this: In the above diagram, Regional Goval Cluster represents our backend, which is sharded per region for scale and to prevent cross-region latency and egress costs. You can read more about it in this blog post. The diagram illustrates that the reverse WebSocket proxy can attempt a retry if any failures occur during the connection setup with Conman. The proxy is alive throughout the connection and transfers data back and forth between the client and the user’s Repl. The problem Everything seems architecturally sound here, so what was the problem? Conman, technically our container manager and responsible for running Repls in containers on GCE VMs, also doubled up as our reverse WebSocket proxy. Here’s what our architecture and overall flow used to look like:
Thu, Feb 22, 2024Experiment: Figma to Replit Plugin
Today we’re releasing an experimental Figma to Replit plugin. The plugin’s goal is to streamline the process from designing with pixels to prototyping with code — generating visually accurate, responsive, HTML, CSS, and React code from your designs. This was a Hack Week project by Replit Design, and we’re excited to give the community an opportunity to try it out. With this tool, you can now generate a Repl directly from your Figma design, and instantly share a static React app with your team. From there, you can use Replit AI to add functionality and tweak your design before deploying to production. This integration is all about enhancing your workflow, accelerating the prototyping process, and ultimately boosting developer productivity. Using the plugin Design your project: Begin by designing a component or page in Figma. You’ll want to follow these practices to get the most functionality with your export:
Thu, Feb 15, 2024Replit + pip
First-class pip support We’re thrilled to announce that first-class pip support is now available on Replit! This should work out-of-the-box when importing existing repositories from GitHub. For developers who want to switch from poetry to pip: start by deleting poetry.lock, then move your dependencies over from [tool.poetry.dependencies] to requirements.txt (structure hint: flask = "^3.0.2" would become flask>=3.0.2,<4 in requirements.txt), and finally, delete the other [tool.poetry...] sections from pyproject.toml. After that, the packaging infrastructure will use pip for all future operations going forward. Where we started When we first chose how to support Python packaging, we went with poetry: a newer packager, offering a compelling feature set. While we stand by the value of having reproducibility and the stability that brings, we also acknowledge the significance of pip as a tool in the wider Python ecosystem. One challenge we were trying to address in this change came in the form of following suggestions from AI assistants, StackOverflow, or blog posts that were written with the framing of pip being the “standard” packaging interface. Packages installed in this way would exist in an ephemeral state: both immediately available for use, but not yet recorded in the dependency list. This would no doubt result in frustration as a project that ran fine interactively in a Repl resulted in a ModuleNotFoundError during deployment.
Wed, Feb 14, 2024Sharding Infrastructure: The Regional Goval Project
The main task of the infrastructure team at Replit is to ensure your Repls run well. A Repl can be thought of as a Linux container with a filesystem. To run Repls, we need to take care of several pieces of infrastructure: Virtual machines to run Repl containers on Databases to keep track of container and VM states Cloud storage to store Repl contents Reverse proxies to route HTTP requests
Wed, Feb 14, 2024Introducing Multiplayer AI Chat
One of our core beliefs at Replit is that multiplayer collaboration makes building software more creative and efficient. After introducing Replit AI for All last year, we heard from our users how transformative AI has been to their development workflows. Today, we are announcing several updates to our AI Chat product, but most importantly, we are bringing the multiplayer power of Replit to AI. We will continue to offer AI to all users, with advanced models available for Replit Core members, but now with the ability to collaborate with others in multiple, persistent chat sessions. What's new? Multi-session chat with persistence You can now create and manage multiple chat sessions when interacting with Replit AI. Creating multiple threads with our AI products allows you to switch between asking for explanations about files in your codebase, generating code for a new feature, and debugging, all without losing your progress. This was a top feature request, and we’re excited to bring multi-session functionality to the platform so developers can stay organized and engaged, all within the same familiar workspace UI. Collaboration and multiplayer
Mon, Feb 12, 2024Flexible Credits and Usage-Based Billing
Replit has evolved from a simple online editor to a comprehensive end-to-end software development platform trusted by developers worldwide. As we’ve grown, we’ve introduced new tools and payment methods for services. We’ve recognized a desire among developers for greater control over their expenses on Replit, and today, we’re introducing usage-based billing. In January 2024, we enabled usage-based billing for any usage that exceeds your plan’s allotment. This change offers a more flexible and transparent view for managing development and deployment costs on Replit. Replit will continue to offer our powerful Starter and Core plans, and any usage beyond plan allotments will be billed via usage-based credit card payments. We’re confident these improvements will make using Replit to scale your projects easier. What's new? Flexible credits Previously, the Replit Core plan included specific allotments for Static and Autoscale Deployments. Feedback from our Replit Core community highlighted a desire for more versatile hosting options, particularly for bots (such as Discord, Telegram, Slack, etc.)
Tue, Feb 6, 2024Easier Editing for .replit Files
At Replit, we want to make it easy to support any project configuration possible. This includes ensuring your binaries are in the right place and intelligent code completion works. Historically, the .replit file has been at the center of this, but the experience of editing the file is a process shrouded in mystery. While documentation exists for the file and what various configurations imply, it’s much more convenient if the documentation is visible inside the Workspace. Starting today, you’ll be able to edit your .replit file fearlessly. We’re now providing intelligent code completion and documentation for all .replit files, powered by Taplo - an LSP server for TOML files. Happy configuring! How we did it With Taplo, the only requirement for providing TOML linting and LSP functionality is a JSON Schema for the TOML file being described. Since we consume the .replit file in a Go codebase, we could use the Go jsonschema module to use our already-existing field tags for TOML deserialization in our JSON Schema properties. This means we were able to generate a JSON Schema without changing our struct definition!