Promptflow
Build high-quality LLM apps - from prototyping, testing to production deployment and monitoring.
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About
Prompt flow
](https://pypi.org/project/promptflow/) [ ](https://pypi.org/project/promptflow/) [ [](https://marketplace.visualstudio.com/items?itemName=prompt-flow.prompt-flow)
](https://microsoft.github.io/promptflow/index.html) [ ](https://github.com/microsoft/promptflow/issues/new/choose) [ [](https://github.com/microsoft/promptflow/blob/main/LICENSE)
Welcome to join us to make prompt flow better by participating discussions, opening issues, submitting PRs.
Prompt flow is a suite of development tools designed to streamline the end-to-end development cycle of LLM-based AI applications, from ideation, prototyping, testing, evaluation to production deployment and monitoring. It makes prompt engineering much easier and enables you to build LLM apps with production quality.
With prompt flow, you will be able to:
- Create and iteratively develop flow
- Create executable flows that link LLMs, prompts, Python code and other tools together.
- Debug and iterate your flows, especially tracing interaction with LLMs with ease.
- Evaluate flow quality and performance
- Evaluate your flow's quality and performance with larger datasets.
- Integrate the testing and evaluation into your CI/CD system to ensure quality of your flow.
- Streamlined development cycle for production
- Deploy your flow to the serving platform you choose or integrate into your app's code base easily.
- (Optional but highly recommended) Collaborate with your team by leveraging the cloud version of Prompt flow in Azure AI.
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Installation
To get started quickly, you can use a pre-built development environment. Click the button below to open the repo in GitHub Codespaces, and then continue the readme!
[](https://codespaces.new/microsoft/promptflow?quickstart=1)
If you want to get started in your local environment, first install the packages:
Ensure you have a python environment, `python>=3.9, --name open_ai_connection
For Azure OpenAI key, establish the connection by running the command, using the `azure_openai.yaml` file:
pf connection create --file ./my_chatbot/azure_openai.yaml --set api_key= api_base= --name open_ai_connection
**Chat with your flow**Don't lose this
Three weeks from now, you'll want Promptflow again. Will you remember where to find it?
Save it to your library and the next time you need Promptflow, it’s one tap away — from any AI app you use. Group it into a bench with the rest of the team for that kind of task and you can pull the whole stack at once.
⚡ Pro tip for geeks: add a-gnt 🤵🏻♂️ as a custom connector in Claude or a custom GPT in ChatGPT — one click and your library is right there in the chat. Or, if you’re in an editor, install the a-gnt MCP server and say “use my [bench name]” in Claude Code, Cursor, VS Code, or Windsurf.
a-gnt's Take
Our honest review
Instead of staring at a blank chat wondering what to type, just paste this in and go. Build high-quality LLM apps - from prototyping, testing to production deployment and monitoring. You can tweak the parts in brackets to make it yours. It's completely free and works across most major AI apps. This one just landed in the catalog — worth trying while it's fresh.
Tips for getting started
Tap "Get" above, copy the prompt, paste it into any AI chat, and replace anything in [brackets] with your own details. Hit send — that's it.
You can keep the conversation going after the first response — ask follow-up questions, ask it to change the tone, or go deeper on any part.
Heads up: this needs an API key to work. You'll get one from the service's website (usually free). The setup guide tells you exactly where.
What's New
Imported from GitHub
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