4.8 out of 5 stars
(64 Ratings)
SurveyJS comprises a collection of four open-source JavaScript libraries that provide the advantages of a customized, in-house survey application while significantly minimizing the time and resources required for deployment. These libraries function independently of specific server code or database needs, allowing for seamless integration with well-known JavaScript frameworks such as React, Angular, Vue.js, jQuery, Knockout, and others. They are built to interact with any server capable of processing JSON requests, thereby ensuring compatibility with a wide range of server setups and databases.
This product suite includes:
- An open-source library licensed under MIT that facilitates the rendering of dynamic JSON-based forms within your web application and captures user responses.
- A self-hosted form builder featuring drag-and-drop functionality, an integrated CSS theme editor, and a graphical user interface for setting conditional rules; it also generates JSON definitions of your forms in real time.
- A PDF Generator library that allows for the conversion of SurveyJS surveys and forms into PDF files directly in the browser.
- The Dashboard library, which enhances survey data analysis through interactive and customizable charts and tables.
We invite you to explore our website and experience our comprehensive demo at no cost. This opportunity will allow you to assess the full capabilities of SurveyJS firsthand.
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4.8 out of 5 stars
(1859 Ratings)
Apify offers a comprehensive platform for web scraping, browser automation, and data extraction at scale. The platform combines managed cloud infrastructure with a marketplace of over 10,000 ready-to-use automation tools called Actors, making it suitable for both developers building custom solutions and business users seeking turnkey data collection.
Actors are serverless cloud programs that handle the technical complexities of modern web scraping: proxy rotation, CAPTCHA solving, JavaScript rendering, and headless browser management. Users can deploy pre-built Actors for popular use cases like scraping Amazon product data, extracting Google Maps listings, collecting social media content, or monitoring competitor pricing. For specialized needs, developers can build custom Actors using JavaScript, Python, or Crawlee, Apify's open-source web crawling library.
The platform operates a developer marketplace where programmers publish and monetize their automation tools. Apify manages infrastructure, usage tracking, and monthly payouts, creating a revenue stream for thousands of active contributors.
Enterprise features include 99.95% uptime SLA, SOC2 Type II certification, and full GDPR and CCPA compliance. The platform integrates with workflow automation tools like Zapier, Make, and n8n, supports LangChain for AI applications, and provides an MCP server that allows AI assistants to dynamically discover and execute Actors.
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Deep Agents
Deep Agents is an open-source library and agent framework that facilitates the development of agents powered by large language models (LLMs) to perform complex, multi-step tasks. The library includes an agent loop that offers features such as planning, persistent memory, access to the file system, and the capability to assign tasks to subagents, allowing developers to easily integrate various model providers and tools. Targeted at software developers and teams aiming to create customized agent applications, it accommodates a wide range of workflows, including research, software programming, and any other situations that require structured planning and action over several steps. Moreover, developers can further expand the framework's functionalities by adding their own tools, middleware, and backend systems, as well as seamlessly integrating with LangGraph and LangSmith for efficient orchestration, tracing, and deployment. In essence, Deep Agents serves as a robust software development framework that enables users to design and manage agents tailored to their specific applications and environments, rather than offering a ready-made solution for end-users. This adaptability and extensive range of features position Deep Agents as a crucial resource for innovators in the field of agent-based application development, fostering creativity and efficiency in their projects. As the demand for sophisticated agent solutions grows, the importance of frameworks like Deep Agents becomes even more pronounced.
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Mastra
Mastra is an open-source TypeScript framework designed to help software developers build production-ready AI agents, intelligent applications, and autonomous workflow systems. The framework provides a modular development environment for defining AI agents with configurable instructions, language models, tools, memory, and runtime behavior. Its agent execution capabilities allow applications to process user requests, reason about complex problems, select appropriate tools, and perform actions across connected systems. Mastra's workflow engine enables developers to organize operations into structured steps with branching logic, retries, error handling, and persistent execution state. Human-in-the-loop functionality allows workflows to pause for user input or approval and resume execution without losing their previous progress. Its memory system supports conversation history, structured working memory, semantic retrieval, and observational memory that summarizes previous interactions to maintain useful context. The platform also provides an agent harness for coordinating long-running agents with multiple operating modes, shared state, persistent threads, and task management capabilities. Model integration features enable developers to work with different AI providers through a unified router, while Model Context Protocol support connects agents to external tools, resources, and compatible applications. Built-in observability includes distributed tracing, execution logs, latency measurements, token usage monitoring, cost tracking, and detailed visibility into model calls and tool interactions. Its evaluation framework supports automated scoring, test datasets, experiments, feedback collection, and regression testing to help development teams measure and improve agent performance.
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