Prompt flow
Prompt flow: A capable flow toolkit for Python teams, with retirement planned for April 20, 2027. Ranked #40 of 49 in LLM Application Development Frameworks by our editors (5.4/10); pricing: Free plan; best for python teams maintaining LLM flows through retirement.
At a glance
- Editor score5.4 / 10
- PricingFree plan
- Best forPython teams maintaining LLM flows through retirement
- Free planYes
- Paid fromNone
- RAG supportYes
- Founded1975 · Redmond, Washington, USA
- Facts checked28 Sep 2026
Where it wins
- Combines executable flows, visual design, and DAG or Python definitions
- Includes tracing, dataset evaluation, prompt variants, and CI/CD testing
- Supports retrieval tools and flow deployment to cloud or self-hosted environments
Where it doesn't
- Microsoft ended feature development on April 20, 2026
- Full retirement is planned for April 20, 2027
- Python-focused, with no JavaScript SDK
Our verdict on Prompt flow
Prompt flow is Microsoft’s open-source toolkit for developing LLM applications, aimed at Python teams that need to compose, evaluate, and serve model-driven flows. Developers can link language models, prompts, Python code, and tools in executable flows, using DAG or Python (Flex) definitions. The toolkit also includes a VS Code visual flow designer, so teams can work with either code-based or visual flow design. Its fit is clearest for teams already building in Python; it is not a JavaScript SDK.
The workflow spans development through evaluation and serving: Prompt flow traces and debugs LLM interactions, compares prompt variants, evaluates quality and performance against datasets, and supports CI/CD testing. Retrieval tools include vector database and Faiss lookup, while message support covers LLM tool calls and function calls. Documented integrations include OpenAI, Azure OpenAI, Azure AI Studio model catalog, vector databases, Faiss, and SerpAPI. Cloud and self-hosted deployment options offer flexibility in where flows run, but teams should assess whether these named connections and Python-oriented workflow suit their existing stack.
Lifecycle is the deciding consideration. Microsoft states that feature development ended on April 20, 2026, and full retirement is planned for April 20, 2027; existing flows are expected to continue operating until retirement. Prompt flow is free and open source, but that does not offset the finite support horizon for teams choosing a framework for new long-lived systems. It may suit teams maintaining current flows or evaluating an existing implementation with a transition plan. Teams beginning a new LLM application that needs ongoing framework development should consider alternatives with a longer stated lifecycle.
Prompt flow pricing
Prompt flow fact sheet
| Free plan | Yes |
|---|---|
| Paid from | None |
| Primary language | Python |
| RAG support | Yes |
| Agent and tool use | Yes |
| Workflow graphs | Yes |
| Prompt optimization | Yes |
| Open-source license | Mit |
| JavaScript/TypeScript SDK | No |
| Deployment | Cloud, Self-hosted |
| Platforms | Web |
| Support | Docs |
| Built for | Solo, Small business, Mid-market, Enterprise (editorial estimate) |
| Integrations | 6 integrations: OpenAI, Azure OpenAI, Azure AI Studio model catalog, Vector databases, Faiss, SerpAPI |
| Pricing | Free plan |
| Website | microsoft.github.io |
| Facts checked | 28 Sep 2026 |
Prompt flow integrations
Prompt flow lists 6 integrations on its own site.
- OpenAI
- Azure OpenAI
- Azure AI Studio model catalog
- Vector databases
- Faiss
- SerpAPI
Alternatives to Prompt flow
- LangChainA self-hosted framework for LLM apps, retrieval workflows, and agents.9.4
- LangGraphGraph-based control for developers who need durable, stateful agent workflows.9.2
- Microsoft Agent FrameworkAn open-source framework for multi-agent orchestration, with checkpoints and approval gates.9.1
See all Prompt flow alternatives →
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Reviewed by iTechGuides Editors · Editorial team · Updated Oct 2026
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