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Promptotype
The platform for structured prompt engineering

What is Promptotype?

Promptotype offers a comprehensive environment dedicated to structured prompt engineering. It equips users with the necessary tools to develop, rigorously test, and effectively monitor tasks involving Large Language Models (LLMs). The platform simplifies the process of designing intricate prompt templates through an extended playground interface, enhancing the development workflow.

Users can define specific test queries, validate outputs against expected JSON schemas or values, and leverage an automatic fill feature for expected results. Promptotype supports batch testing of prompts across entire query collections, suitable for both development cycles and production readiness checks. It centralizes the management of prompt templates and model configurations, tracks the history of runs and tests, and integrates support for function calling, providing a robust solution for LLM application development.

Features

  • Structured Prompt Engineering Playground: Design prompt templates in an advanced interface.
  • Automated Testing: Define test queries with expected JSON schemas or values and test against entire collections.
  • Function Calling Support: Integrate and test prompts using function calling capabilities.
  • Run & Test History Tracking: Maintain a history of all runs and test results (available in paid plans).
  • Scheduled Automated Tests: Set up periodic tests with email summaries (available in paid plans).
  • UI for Fine-Tuning: Automatically create fine-tuned models from query collections (available in paid plans).
  • Prompt & Model Management: Keep prompt templates and model configurations organized in one place.

Use Cases

  • Developing and refining prompts for LLM applications.
  • Testing LLM performance against specific criteria and expected outputs.
  • Monitoring the consistency and reliability of LLM responses over time.
  • Managing prompt versions and model configurations for different tasks.
  • Fine-tuning models based on successful query collections.
  • Collaborating on prompt engineering projects within a team (Team plan).

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