
Flows.sh
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Break free from duct tape and rigid components. Flows is product adoption infrastructure that lets modern teams build anything, no-code or all-code.
Flows.sh
GitHubNo Flows.sh videos yet. You could help us improve this page by suggesting one.
Flows.sh's answer
Focused on speed, reliability and customization. Build anything you imagine when it comes to user onboarding.
Flows.sh's answer
React, NextJS, NestJS, TypeScript, Drizzle ORM, PostgreSQL
Flows.sh's answer
Flows.sh's answer
Startup founders
Flows.sh's answer
After using IntroJS and being frustrated by all the options developers have these days when it comes to user onboarding, we decided there's room to create something better in every way.
Flows.sh's answer
Based on our record, GitHub seems to be a lot more popular than Flows.sh. While we know about 2476 links to GitHub, we've tracked only 1 mention of Flows.sh. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
Flows is a distinctive tool designed for creating product tours and user onboarding experiences within web applications. It provides a WYSIWYG editor for building flows visually and offers the option to define them directly within your codebase using the SDK, catering to developers with different preferences: The Flows Editor facilitates the process of creating flows with visual guides and live in-app previews.... - Source: dev.to / about 2 years ago
"""Clones a single branch of a GitHub repository into a temporary directory for local scanning.""" Import logging Import shutil Import subprocess Import tempfile Logger = logging.getLogger(__name__) Class RepoFetchError(RuntimeError): """Raised when the target repository/branch cannot be cloned.""" Class RepoFetcher: """Shallow-clones a single branch of a repository so its tests can be scanned... - Source: dev.to / 5 days ago
# video-meta.yml Topic: > Walking through how we cut cold-start time on a Lambda-backed GraphQL API from 2.4s to under 400ms, including the two things that didn't work. Target_keyword: lambda cold start optimization Audience: backend devs who already ship serverless, not beginners Model_channels: - the three channels currently ranking for this keyword Links: repo: https://github.com/... slides:... - Source: dev.to / 6 days ago
Import struct, json, urllib.request REL = "https://github.com/{owner}/{repo}/releases/download/{tag}/" PART = ["...part1.zip.001", "...part2.zip.002", "...part3.zip.003"] SIZE = [1992294400, 1992294400, 1893639808] # from the releases API Def grab(part, start, end, out): # HTTP range fetch req = urllib.request.Request(REL + PART[part], Headers={"Range":... - Source: dev.to / 10 days ago
Is published at https://github.com/.keys so an SSH server to which you connect could do a reverse lookup. This is the reason why my ~/.ssh/config has those 2 lines at the end:- Source: Hacker News / 18 days agoHost *.
All of this assumes you can actually inspect what the agent did โ the real inputs after resolution, the real tool outputs, the real intermediate steps. That is the other half of the workflow. AgentLens captures the trace: every model and tool step, resolved inputs, raw outputs. agent-eval scores and gates the output; AgentLens gives you the unforgeable, agent-didn't-author trace data for Tier 1+2 to score against... - Source: dev.to / 18 days ago
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