promptLM is an open-source framework that streamlines the development, testing, and deployment of AI prompt engineering workflows. Integrate with CI/CD pipelines for automated testing and evaluation of prompts against various language models.
Your prompt asking ChatGPT “What’s the capital of France?” doesn’t need a lifecycle management tool. You read the reply and move on.
But when prompts run inside your application — and their responses determine whether the application says “yes” or “no” — it’s a completely different story.
Then you want to have something better than your text editor to manage your prompts.
You’ll iteratively develop your prompts – often against different models, with different variations and wordings. You’ll want to version those prompts and run evals on the responses to automatically decide which variants are “good enough” and discard the rest. And you’ll need a way to get prompts into your application – and update them – without changing the application itself, because prompts follow a different lifecycle than code. And then...
you finally have your evaluated and versioned prompts ready for your application. Yay.
Now, you better make sure that your application works as expected with the responses created by your prompts. That’s when you run integration tests against a real LLM endpoint — and that’s when you start spending real money. Those tests add up fast...
And your agents will probably use MCP or other tools as well, right? Suddenly your test surface gets even bigger, more complex, and even more expensive.
This is the reason why we’re building promptLM — to cover all of this, for you and for ourselves.
From concept to deployment, promptLM provides everything you need to build, test, and deploy reliable AI prompts.
Create and iterate on prompt specifications with powerful templating and MCP & tools support.
Use existing or provide custom evals for the prompt responses.
Track changes, manage versions, and maintain prompt evolution with full audit trails.
Deploy tested prompts to production environments with confidence.
Prompt Server, dependency or Repository access - pick your retrieval.
Replay LLM responses for cost saving and deterministic tests for your agent and workflow code.
Create sophisticated prompt specifications through command line interface or web-ui, backed by MCP and tool integrations. Define templates, placeholders, and evaluation hooks to verify expected outputs without leaving your editor.
Combine built-in evaluations with your own checks to inspect prompt responses across multiple language models. Measure behaviour across scenarios, edge cases, and regressions with rich reporting.
Track every change to your prompts with full version history. Compare versions, roll back changes, and maintain complete audit trails for compliance and debugging purposes.
Deploy tested prompts to production environments with confidence using automated guardrails and approvals tailored for prompt releases.
Publish prompts through a prompt server, dependency packages, or repository access—letting teams choose the retrieval flow that fits their stack.
Replay captured LLM responses to slash evaluation costs and keep your tests deterministic across CI, staging, and local development.
Join the growing community of developers using promptLM to build better AI applications.