vellum-ai

What it is and what it does

Vellum is a Python SDK for building and managing production AI applications. It provides two main layers: a low-level Client SDK for direct interaction with the Vellum API, and a high-level Workflows SDK for defining the control flow and structure of AI systems as declarative graphs. The package includes built-in support for prompt management, evaluation frameworks, retrieval services, deployment, and real-time observability.

The Workflows SDK can be used independently without a Vellum account to define and debug AI system control flow, though a paid account unlocks additional features like UI-based editing, managed retrieval, and deployment integration. The package is actively maintained, supports Python 3.9 through 3.12, and has low installation friction with a pure Python wheel distribution.

Use it for:

• Define and orchestrate multi-step AI workflows with declarative graph syntax without requiring a Vellum account.
• Iterate on and compare prompts across different LLM providers using the built-in prompt playground.
• Measure and evaluate the quality of AI system outputs at scale with the evaluations framework.
• Monitor and debug production AI applications in real-time with detailed logs, metrics, and user feedback.
• Deploy AI system updates independently from application code using one-click deployment.
• Transform unstructured content into context-aware retrieval solutions optimized for AI systems.

Worth the install?

AI-flagged interpretation of the facts on this page — verify before relying

Vellum is an SDK for building and deploying production-grade AI applications, providing orchestration, prompt management, evaluations, retrieval, and observability through both a low-level client API and a high-level workflow engine.

Yes, if you are building production AI applications and want a structured SDK for orchestration and observability. The Workflows SDK alone justifies installation for control-flow definition without vendor lock-in. MIT licensing, active maintenance, and low install friction make it a low-risk addition. A Vellum account is required to unlock full platform features (prompt management, deployment, managed retrieval), so evaluate whether the free tier meets your needs before committing to paid features.

Install

vellum-ai on PyPI

pip install vellum-ai

uv add vellum-ai

poetry add vellum-ai

Installing vellum-ai

Before you install

Low install friction with a pure Python wheel distribution. Active maintenance with recent commits (2026-04-06) and steady releases. Requires Python 3.9 or later and brings in 17 runtime dependencies including common utilities like pydantic, httpx, and pyyaml.

License in practice

MIT license (permissive) allows free use, modification, and distribution with minimal restrictions. No license-based barriers to adoption.

Quickstart

pip install vellum-ai

from vellum.workflows import Workflow, Node

# Define a workflow with nodes and relationships
workflow = Workflow(name="my_ai_app")
node = Node(name="example_node")
workflow.add_node(node)

Requires Python 3.9 or later. Most features require a Vellum account and API key; however, the Workflows SDK can be used without an account to define control flow.

Verify before relying

• Whether the 17 runtime dependencies introduce any transitive security concerns beyond the direct package.
• Performance characteristics and scalability limits for the workflow engine with large or complex graphs.
• Specific integrations or LLM providers supported by the orchestration layer.

Package facts

Evidence: vellum_ai-1.14.7-py3-none-any.whl

Tags

More Python Modules packages