> For the complete documentation index, see [llms.txt](https://docs.healthuniverse.com/overview/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.healthuniverse.com/overview/building-apps-in-health-universe/developing-your-health-universe-app/streamlit-vs-fastapi-vs-a2a.md). # Streamlit vs FastAPI vs A2A Agents #### **What is Streamlit?** Streamlit is an open-source Python framework for building interactive data apps and dashboards with minimal code. It's optimized for rapid prototyping and visualization, making it ideal for healthcare professionals and data scientists who want to quickly turn scripts into shareable web apps. *** #### **What is FastAPI?** FastAPI is a modern, high-performance web framework for building APIs with Python. It's built on top of Starlette and Pydantic, offering robust support for data validation, async programming, and integration with backend systems. FastAPI is ideal for orchestrating workflows, building microservices, and deploying complex backend logic. *** #### **What are A2A Agents?** A2A (Agent-to-Agent) agents are specialized applications built using the Health Universe A2A SDK. These agents enable AI-driven workflows with features like document processing, progress tracking, inter-agent communication, and long-running background tasks. They're designed specifically for Health Universe's Navigator platform and support advanced workflow orchestration. *** #### **Streamlit vs. FastAPI vs. A2A Agents: Side-by-Side Comparison** | Feature | **Streamlit** | **FastAPI** | **A2A Agents** | | ------------------------ | --------------------------------------------------------------------------------------- | -------------------------------------------------------------------------- | -------------------------------------------------------------------------- | | **Primary Use Case** | Build interactive front-end apps & dashboards | Build RESTful APIs and backend services | AI-driven workflows with document processing and background tasks | | **UI/UX Focus** | Built-in widgets and layout for rapid UI | No native UI; integrates with front-ends | Navigator integration with automatic progress tracking | | **Ease of Use** | Extremely easy to start with; minimal code | Slightly steeper learning curve | Moderate learning curve; specialized for Health Universe workflows | | **Interactivity** | Real-time updates based on widget input | Requires integration with frontend tools such as Health Universe Navigator | Built-in progress updates, artifacts, and real-time status communication | | **Performance** | Ideal for lightweight data apps | Better for high-concurrency, async tasks | Optimized for long-running tasks with automatic timeout and retry handling | | **Deployment Style** | Standalone, self-contained apps | API-first design; fits into larger architectures | Workflow-native; designed for Navigator orchestration | | **Document Processing** | Manual file upload and processing | Basic file handling via endpoints | Built-in document client with NestJS/S3 integration | | **Background Tasks** | Limited; relies on session state | Manual task queuing and management | Automatic background job management with progress persistence | | **Inter-Agent Comm.** | Not supported | Custom implementation required | Built-in agent communication with JWT propagation | | **Workflow Integration** | Limited support for orchestration. Relies on external workflow tools for orchestration. | Full compatibility with tools like Navigator | Native Navigator integration with context-aware autofill | | **Best For** | Data visualization, prototypes, solo apps | Backend services, orchestrated workflows | AI workflows, document analysis, complex healthcare processes | *** #### **When to Use Streamlit vs. FastAPI vs. A2A Agents in Health Universe** **✅ Use Streamlit when:** * You want to build a **standalone healthcare app or dashboard** (e.g., a clinical decision support tool). * You need to **rapidly prototype and iterate** on a data-driven UI. * Your users are **healthcare professionals or analysts** interacting directly with the interface. * You are focused on **visualizing health data or models** rather than orchestrating complex backend logic. * You need **immediate user feedback** and interactive data exploration. **✅ Use FastAPI when:** * You are developing a **backend API** that integrates with other systems (EHRs, analytics engines, etc.). * Your application needs **asynchronous processing**, scalability, or robust data validation. * You are building services that are **part of a larger ecosystem**, such as APIs consumed by multiple apps. * You need **custom API endpoints** with fine-grained control over request/response handling. **✅ Use A2A Agents when:** * You are building **AI-driven healthcare workflows** that process documents or clinical data. * You need **long-running background tasks** (analyzing large datasets, generating reports, etc.). * Your workflow involves **multiple agents communicating** with each other to complete complex processes. * You want **automatic progress tracking** and status updates for users during lengthy operations. * You are working with **clinical documents** that require extraction, analysis, and structured data output. * You need **Navigator integration** with context-aware autofill and workflow orchestration. * Your application requires **document persistence** and **artifact management** in Health Universe threads. *** #### **Migration Paths** **Streamlit → A2A Agents:** * Convert UI logic to agent processing methods * Replace file uploads with document client operations * Add progress tracking for long-running operations * Integrate with Navigator for workflow orchestration **FastAPI → A2A Agents:** * Wrap existing API logic in agent `process_message()` methods * Replace custom background tasks with built-in async processing * Add document operations and inter-agent communication * Leverage automatic progress persistence and artifact management While FastAPI apps can be accessed directly from your own infrastructure through Health Universe API calls, FastAPI apps work best as part of AI-driven workflows within Navigator. For advanced AI workflows with document processing and background tasks, A2A agents provide the most comprehensive solution with built-in Health Universe platform integration. --- # Agent Instructions This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com. ## Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. 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