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Context for your AI agents
Crawl websites, sync to vector databases, and power RAG applications. Pre-built integrations for LLM pipelines and AI assistants.
Build data pipelines that feed your AI models and agents without managing infrastructure. Crawl any website, transform content, and push directly to your preferred vector store. Use 10,000+ tools for RAG applications, AI assistants, and real-time knowledge bases. Monitor site changes, trigger workflows on new data, and keep your AIs fed with fresh, structured information. Cloud-native, API-first, and free to start until you need to scale.
...The API accepts typical HTTP verbs and returns JSON in a consistent format, making it easy to swap with a real server later. It’s widely used in examples, workshops, and automated tests where a dependable dummy service accelerates iteration. With zero setup, it removes a major friction point for learning HTTP clients and front-end data flows.
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Requirements:
For the Java HTTP server:
- J2SE (SDK for compilation)
For the exampe web app:
- Apache2 with mod_rewrite and mod_proxy
Client-side for the web app:
- www browser supporting JS with jQuery
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Setup:
- run Server.class from Java server files (java Server) in a terminal/console
- unpack example app files under/within your apache2 document root file structure
- open index.html (with a www browser, from a www server)
- observe terminal output
Servlet framework for creating standalone restful CRUD services
...You can use it to quickly create RESTful JSON & XML based CRUD services for your web applications by writing short scripts.
It is downloadable as a windows installer package for quick no-hassle setup.
It runs as a servlet in an app-server. By default it sets itself up to run inside its own standalone (jetty) server.
Code contributions most welcome!