--- id: promptflow version: "1.18.5" license: MIT License license_treatment: permissive maintenance: active --- # promptflow — Prompt flow Python SDK - build high-quality LLM apps License: permissive · Maintenance: active · Downloads: 82.8K/mo ## What it is and what it does Prompt flow is Microsoft's end-to-end development toolkit for LLM applications. It provides a structured way to create flows that combine language models, Python code, and external tools, then test, evaluate, and deploy them. The package includes CLI tools for initializing flows from templates (like chat), managing API connections, and running interactive tests. It emphasizes production-quality development with built-in tracing to debug LLM interactions, evaluation capabilities for assessing flow quality on larger datasets, and integration with CI/CD pipelines. The package depends on three internal subpackages: promptflow-tracing for instrumentation, promptflow-core for runtime execution, and promptflow-devkit for local development and testing. It supports Python 3.9 through 3.11 and is actively maintained by Microsoft, with recent security fixes and improvements documented in the release history. Use it for: - Build and iterate on chatbot flows using the CLI template system and interactive testing mode. - Evaluate LLM application quality by running flows against test datasets and integrating results into CI/CD. - Debug LLM interactions with built-in tracing to understand how prompts and model outputs flow through your application. - Deploy flows to production or integrate them into existing applications with connection management for API keys. - Collaborate on LLM projects using the optional Azure AI cloud version for team-based development. ## Worth the install? AI-flagged interpretation of the facts above — verify before relying. Prompt flow is a development suite for building, testing, and deploying LLM-based applications, integrating prompts, Python code, and external tools into executable flows with built-in tracing and evaluation. Yes. Prompt flow is actively maintained, has no known vulnerabilities, installs with low friction, and is MIT-licensed. It directly addresses the full development lifecycle for LLM applications—from prototyping to production—with a mature CLI and integration points. Install it if you are building or managing LLM-based applications and want structured tooling for testing, evaluation, and deployment. ## Install pip install promptflow uv add promptflow poetry add promptflow ## Installing promptflow Before you install: Low friction installation as a pure Python wheel. Actively maintained with recent releases; last commit 2026-08-05. Depends on three internal subpackages (promptflow-tracing, promptflow-core, promptflow-devkit) that ship together. License in practice: MIT License permits commercial and private use with minimal restrictions, making it suitable for both open-source and proprietary LLM applications. Quickstart: pip install promptflow pf flow init --flow ./my_chatbot --type chat pf connection create --file ./my_chatbot/openai.yaml --set api_key= --name open_ai_connection pf flow test --flow ./my_chatbot --interactive Requires Python 3.9, 3.10, or 3.11; Python 3.8 support was dropped in v1.17.0 for security reasons. Verify before relying: - Whether the three runtime dependencies (promptflow-tracing, promptflow-core, promptflow-devkit) are installable independently or only as part of this package. - Performance characteristics when working with large datasets or complex multi-node flows. - Compatibility with specific LLM providers beyond OpenAI and Azure OpenAI mentioned in the quick start. ## Package facts - License: MIT License (permissive) - Python support: supports_current - Install friction: low - Maintenance: active - Downloads: 82.8K/month (top 15,000 on PyPI) - Known vulnerabilities: none known ## Tags llm application development framework, prompt engineering workflow tool, ai flow orchestration, llm app testing and evaluation, prompt flow builder, end-to-end llm development, flow debugging and tracing, llm-development, prompt-engineering, workflow-orchestration [View on SkillFed](https://skillfed.io/packages/promptflow) · [View on PyPI](https://pypi.org/project/promptflow/)