Show HN: Pipelex – Declarative language for repeatable AI workflows

To use AI models, you need an API key: Free Pipelex API Key: Join our Discord community and request your free API key (no credit card required) in the 🔑・free-api-key channel. Bring your own API keys: OpenAI, Anthropic, Google, Mistral) Local AI: Ollama, vLLM, LM Studio, llama.cpp... any endpoint based on the OpenAI API or not, as you can plug-in your own non-standard APIs. See Configure AI Providers for details. Create a complete AI workflow with a single command: This command generates a production-ready .plx file with domain definitions, concepts, and multiple processing steps that analyzes CV-job fit and prepares interview questions. cv_match.plx View the pipeline flowchart: Create an inputs.json file with your PDF URLs: Via Python: Install AI assistant rules to easily modify your pipelines: This installs rules for Cursor, Claude, OpenAI Codex, GitHub Copilot, Windsurf, and Blackbox AI. Now you can refine pipelines with natural language: "Include confidence scores between 0 and 100 in the match analysis" "Write a recap email at the end" Pipelex is an open-source language that enables you to build and run repeatable AI workflows. Instead of cramming everything into one complex prompt, you break tasks into focused steps, each pipe handling one clear transformation. Each pipe processes information using Concepts (typing with meaning) to ensure your pipelines make sense. The Pipelex language (.plx files) is simple and human-readable, even for non-technical users. Each step can be structured and validated, giving you the reliability of software with the intelligence of AI. Learn More: Writing Workflows Tutorial - Complete guide with examples Build Reliable AI Workflows - Deep dive into Pipelex Configuration Guide - Set up AI providers and models We highly recommend installing our extension for .plx files into your IDE. You can find it in the Open VSX Registry. It's coming soon to VS Code marketplace too. If you're using Cursor, Windsurf or another VS Code fork, you can search for it directly in your extensions tab. Explore real-world examples in our Cookbook repository: Clone it, fork it, and experiment with production-ready pipelines for various use cases. The package supports the following additional features: anthropic: Anthropic/Claude support for text generation google: Google models (Vertex) support for text generation mistralai: Mistral AI support for text generation and OCR bedrock: Amazon Bedrock support for text generation fal: Image generation with Black Forest Labs "FAL" service Install all extras: Pipelex collects optional, anonymous usage data to help improve the product. On first run, you'll be prompted to choose your telemetry preference: Off: No telemetry data collected Anonymous: Anonymous usage data only (command usage, performance metrics, feature usage) Identified: Usage data with user identification (helps us provide better support) Your prompts, LLM responses, file paths, and URLs are automatically redacted and never transmitted. You can change your preference at any time or disable telemetry completely by setting the DO_NOT_TRACK environment variable. For more details, see the Telemetry Documentation or read our Privacy Policy. We welcome contributions! Please see our Contributing Guidelines for details on how to get started, including development setup and testing information. Join our vibrant Discord community to connect with other developers, share your experiences, and get help with your Pipelex projects! GitHub Issues: For bug reports and feature requests Discussions: For questions and community discussions Documentation If you find Pipelex helpful, please consider giving us a star! It helps us reach more developers and continue improving the tool. This project is licensed under the MIT license. Runtime dependencies are distributed under their own licenses via PyPI. "Pipelex" is a trademark of Evotis S.A.S. © 2025 Evotis S.A.S.