Promptflow

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 Repository  11,100  1,100

End-to-end LLM application development — prototyping, testing, evaluation, deployment, monitoring

microsoft azure dag evaluation tracing llm-lifecycle mcp a2a
SDK Hybrid Stable Maintained

Key Features

Multi-Agent
Single Agent
Human-in-the-Loop
Streaming
Async Support
Type Safe
Short-Term Memory
Long-Term Memory
Shared Memory
Plugin System
Custom Tools
MCP Protocol
A2A Protocol
Code Execution
Web Browsing
File System Access
Sandboxing
Guardrails
Structured Output
DAG Workflows
Visual Builder
CLI
API Server
Self-Hosted
Cloud Hosted

Community Feedback

Strengths

  • Strong evaluation and testing capabilities
  • Visual DAG design
  • Deep Azure integration
  • Production tracing

Weaknesses

  • Tightly coupled with Azure
  • Being superseded by Agent Framework for agentic workloads
  • DAG can feel rigid for dynamic workflows

Promptflow Details

OrganizationMicrosoft
Organization TypeCompany
FundingPublic
CategorySDK
SubcategoryOrchestration
DeploymentHybrid
Primary LanguagePython
RuntimePython 3.9+
LicenseMIT
Commercial UseUnrestricted
Install Commandpip install promptflow
GitHub Stars11,100
GitHub Forks1,100
Release CadenceBiweekly
MaturityStable
Pricing ModelFree
Free TierFully open-source MIT
Self-Hosted FreeYes
Cost Modelfree + LLM costs
Community SizeMedium (11k stars)
Community ActivityActive
SentimentPositive
GPU RequiredNo
ConfidenceHigh
Research Date2026-03-24
LLM ProvidersAzure OpenAI, OpenAI, any via integrations
API Keys RequiredAzure OpenAI or OpenAI API key

Use Cases

Similar Tools

LangChainPromptflow DAG-based/Azure-first, LangChain code-first/universal
Semantic KernelPromptflow for LLM app lifecycle, SK for agent orchestration

When to Use

Best for: Azure teams needing LLM app development with evaluation and tracing

Avoid when: Non-Azure environments or need flexible agent workflows

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Release v20260324