• PromptLayer is a comprehensive platform for prompt engineers and teams developing LLM-based applications.
• Functions as middleware, logging API requests and metadata, and offering a visual dashboard for prompt management.
• Features include prompt versioning, A/B testing, structured output definitions, regression and batch evaluation pipelines, and cost/latency analysis.
• Enables collaboration through shared workspaces and supports streaming and multi-modal models (e.g., GPT-4 Vision).
• Integrates with LangChain and REST APIs, and includes scoring, tagging of requests, and template variable support via Jinja2 or f-strings.
• Provides extensive export and self-hosting options.
• Utilized by thousands of teams, including engineers, writers, and support staff, to enhance development, minimize engineering overhead, and continually improve prompt quality.
Prompt Registry enabling visual version control and template editing
A/B testing for safe gradual rollout of prompt versions
Regression, bulk batch evaluation pipelines for prompt performance
Integration with multi-modal models like GPT-4 Vision and streaming support
Structured outputs using JSON schema for consistent response formats
Shared workspaces to collaborate across teams and roles
Analytics dashboard showing cost, latency, usage, and tagged trends
Support for custom template variables via f-string and Jinja2 formats
Scoring of requests with metadata and custom named score tracking
LangChain and REST API compatibility for flexible integration
What is PromptLayer used for?
It logs and visualizes every API request to LLMs, lets you version and edit prompts, run evaluations, score responses, and monitor usage—all in one centralized system.
Does PromptLayer support multi-modal and streaming model APIs?
Yes—PromptLayer supports multi-modal models like GPT‑4 Vision and full streaming support through its Python and JS SDKs.
Can I perform A/B tests and regression evaluations?
Absolutely—PromptLayer provides tools for A/B testing across prompt versions, regression tests, historical backtesting, and batch evaluations.
How does collaboration work on PromptLayer?
Through Shared Workspaces, teams can share prompt templates, requests, evaluations, and comments; admins control access and collaborate across roles.
Can structured output formats and templating be defined?
Yes—structured outputs can be enforced via JSON schema, and template variables support both f‑string and advanced Jinja2 formats for dynamic content generation.