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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.

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1

Cross Platform Node Guide

Improve front-end engineer workflow & standard, powered by TypeScript

...With 80+ WEB/IOS/Andriod stable users, the cumulative production project reached 240+. Feflow refers to the thinking of Pipeline and divides work into five steps: init, develop, build, test, deploy. And corresponding to five basic commands: init, dev, build, test, and deploy. In addition to serving basic development workflows and specifications, Feflow provides an easy-to-expand plug-in mechanism for creating a team-wide toolchain ecosystem. Feflow only provides a CLI and kernel. The CLI is responsible for interacting with the command line terminal.

Downloads: 0 This Week

Last Update: 2023-06-30
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2

OpenAPI-to-GraphQL

Translate APIs described by OpenAPI Specifications (OAS) into GraphQL

Translate APIs described by OpenAPI Specifications (OAS) into GraphQL. The Command Line Interface (CLI) provides a convenient way to start a GraphQL server wrapping an API for a given OpenAPI Specification. Use OpenAPI-to-GraphQL as a library in your application to generate GraphQL schemas. The GraphQL interface is created around the data definitions in the given OAS, not around the endpoints, leading to a natural use of GraphQL. Nested data Links defined in the OAS are used to create nested...

Downloads: 0 This Week

Last Update: 2023-03-03
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