pipelex 0.3.2

Pipelex is an open-source dev tool based on a simple declarative language that lets you define replicable, structured, composable LLM pipelines.

Lean-code language for repeatable workflows

Pipelex is based on a simple declarative language that lets you define repeatable, structured, composable AI workflows.

Demo - Documentation - Report Bug - Feature Request

📜 The Knowledge Pipeline Manifesto

Read why we built Pipelex to transform unreliable AI workflows into deterministic pipelines 🔗

🚀 See Pipelex in Action

Checkout our Demo

📑 Table of Contents

• Introduction
• Quick start
  • Prerequisites
  • Installation
  • Optional features
• Contributing
• Support
• License

Introduction

Pipelex makes it easy for developers to define and run repeatable AI workflows. At its core is a clear, declarative pipeline language specifically crafted for knowledge-processing tasks.

Build pipelines from modular pipes that snap together. Each pipe can use a different language model (LLM) or software to process knowledge. Pipes consistently deliver structured, predictable outputs at each stage.

Pipelex uses TOML syntax, making workflows readable and shareable. Business professionals, developers, and AI coding agents can all understand and modify the same pipeline definitions.

Example:

[concept]
Buyer = "The person who made the purchase"
PurchaseDocumentText = "Transcript of a receipt, invoice, or order confirmation"

[pipe.extract_buyer]
PipeLLM = "Extract buyer from purchase document"
inputs = { purchase_document_text = "PurchaseDocumentText" }
output = "Buyer"
llm = "llm_to_extract_info"
prompt_template = """
Extract the first and last name of the buyer from this purchase document:
@purchase_document_text
"""

Pipes are modular building blocks that connect sequentially, run in parallel, or call sub-pipes. Like function calls in traditional programming, but with a clear contract: knowledge-in, knowledge-out. This modularity makes pipelines perfect for sharing: fork someone's invoice processor, adapt it for receipts, share it back.

Pipelex is an open-source Python library with a hosted API launching soon. It integrates seamlessly into existing systems and automation frameworks. Plus, it works as an MCP server so AI agents can use pipelines as tools.

🚀 Quick start

:books: Note that you can check out the Pipelex Documentation for more information and clone the Pipelex Cookbook repository for ready-to-run samples.

Follow these steps to get started:

Installation

Prerequisites

• Python ≥3.10
• pip, poetry, or uv package manager

Install the package

# Using pip
pip install pipelex

# Using Poetry
poetry add pipelex

# Using uv (Recommended)
uv pip install pipelex

IDE extension

We highly recommend installing an extension for TOML files into your IDE of choice. For VS Code, the Even Better TOML extension does a great job of syntax coloring and checking.

Optional Features

The package supports the following additional features:

• anthropic: Anthropic/Claude support
• google: Google models (Vertex) support
• mistralai: Mistral AI support
• bedrock: AWS Bedrock support
• fal: Image generation with Black Forest Labs "FAL" service

Install all extras:

Using pip:

pip install "pipelex[anthropic,google,mistralai,bedrock,fal]"

Using poetry:

poetry add "pipelex[anthropic,google,mistralai,bedrock,fal]"

Using uv:

uv pip install "pipelex[anthropic,google,mistralai,bedrock,fal]"

🤝 Contributing

We welcome contributions! Please see our Contributing Guidelines for details on how to get started, including development setup and testing information.

👥 Join the Community

Join our vibrant Discord community to connect with other developers, share your experiences, and get help with your Pipelex projects!

💬 Support

• GitHub Issues: For bug reports and feature requests
• Discussions: For questions and community discussions
• Documentation

⭐ Star Us!

If you find Pipelex helpful, please consider giving us a star! It helps us reach more developers and continue improving the tool.

📝 License

This project is licensed under the MIT license. Runtime dependencies are distributed under their own licenses via PyPI.

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"Pipelex" is a trademark of Evotis S.A.S.

© 2025 Evotis S.A.S.