Portkey vs Streamlit
A detailed comparison to help you choose the right AI tool
P
Portkey
Full-stack LLMOps platform to monitor, manage, and improve LLM-based apps.
Open Source 5 upvotes
S
Streamlit
A faster way to build and share data apps
Freemium 689 upvotes
Key Features
Portkey
- AI Gateway - Centralized access point for LLM-based applications.
- Observability - Real-time monitoring of LLM performance and usage metrics.
- Guardrails - Safety measures to ensure responsible AI usage and output.
- Governance - Compliance tools for managing AI model deployment and usage.
- Prompt Management - Tools for creating, testing, and optimizing prompts.
Streamlit
- Interactive widgets for user input like sliders, buttons, and text boxes.
- Real-time data visualization with support for charts and graphs.
- Easy deployment options to share apps via Streamlit Cloud or local servers.
- Integration with popular data libraries like Pandas, NumPy, and Matplotlib.
- Markdown support for adding formatted text and documentation within apps.
Portkey Pros
- + Unified API access to over 1,600 LLMs simplifies integration.
- + Real-time observability dashboard enhances monitoring and management.
- + Deterministic guardrails ensure consistent AI output quality.
- + Comprehensive governance features support compliance and security.
- + Open-source platform encourages community contributions and transparency.
- + Flexible pricing structure accommodates teams of varying sizes and needs.
Portkey Cons
- − Free tier is limited to prototyping and not suitable for production workloads.
- − Enterprise features may require custom pricing, adding complexity to budgeting.
- − Initial setup and configuration can be complex for new users.
- − Advanced features may have a learning curve for teams new to LLMOps.
- − Limited offline support for environments with strict data isolation requirements.
Streamlit Pros
- + Streamlit's ease of use allows for rapid development and deployment of data applications.
- + The tool's real-time update feature enhances the iterative development process.
- + Streamlit's widget integration simplifies the creation of interactive user interfaces.
- + The Community Cloud offers a free platform for sharing public apps, fostering collaboration.
- + Enterprise deployment options provide robust security and reliability for large organizations.
- + Streamlit's compatibility with a wide range of data visualization tools enhances its utility.
Streamlit Cons
- − Streamlit's reliance on Python may limit accessibility for users unfamiliar with the language.
- − The free tier is limited to public apps, which may not suit all project requirements.
- − Advanced customization may require additional effort or external components.
- − Some users may find the lack of built-in user authentication a limitation for certain applications.
- − Enterprise features are tied to Snowflake, which may not align with all organizational infrastructures.
Which Should You Choose?
Choose Portkey if:
- → You need it for monitor llm app performance for anomalies and improvements.
- → You need it for implement safety guardrails for sensitive applications.
- → You need it for manage compliance and governance for ai model deployments.
Choose Streamlit if:
- → You need it for data scientists creating quick prototypes of data analysis tools.
- → You need it for business analysts sharing interactive dashboards with stakeholders.
- → You need it for educators building teaching tools for data science concepts.