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CLI ToolsMay 11, 2026·2 min de lectura

PromptFlow — Build and Test LLM Apps

PromptFlow is a CLI + framework for building and testing LLM flows. Install `promptflow` + `promptflow-tools`, then run `pf flow init` and `pf flow test`.

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Introducción

PromptFlow is a CLI + framework for building and testing LLM flows. Install promptflow + promptflow-tools, then run pf flow init and pf flow test.

  • Best for: teams shipping LLM apps who want a flow-based dev loop with templates, connections, batch tests, and evaluation paths
  • Works with: Python (repo recommends 3.9–3.11), pf CLI, OpenAI/Azure OpenAI connections (repo quickstart)
  • Setup time: 14 minutes

Quantitative Notes

  • Python 3.9–3.11 recommended (repo)
  • Setup time ~14 minutes
  • CLI commands: pf flow init, pf flow test (repo)

Practical Notes

Adopt PromptFlow as your team’s LLM dev loop: template a flow, store connections as named resources, and run interactive tests locally. Then add batch tests and evaluations so every prompt change is measurable. For agents, model each tool step as a node so you can debug failures with clear inputs/outputs per node.

Safety note: Keep secrets in connections, not in YAML committed to git; rotate keys and restrict scopes.

FAQ

Q: Do I need Azure to use PromptFlow? A: No. The README includes both OpenAI and Azure OpenAI connection examples; you can start locally.

Q: Where should I use flows vs code? A: Use flows for repeatable LLM pipelines (prompt → tool → evaluator). Use code for custom logic and integrations.

Q: How do I keep quality high? A: Use batch tests + evaluation runs; treat prompts as versioned artifacts and gate releases on eval metrics.

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Fuente y agradecimientos

GitHub: https://github.com/microsoft/promptflow Owner avatar: https://avatars.githubusercontent.com/u/6154722?v=4 License (SPDX): MIT GitHub stars (verified via api.github.com/repos/microsoft/promptflow): 11,122

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