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On the recordRead 9 Oct 202619 facts
Promptimal
On the record
- API requirement
- The README says to add an OpenAI API key to the environment before using Promptimal.github.com · read 9 Oct 2026
- Configuration
- The number of iterations, candidate samples per iteration, and score threshold can be configured from the command line.github.com · read 9 Oct 2026
- Current integrations
- The README documents OpenAI API key configuration and does not describe other current provider integrations.github.com · read 9 Oct 2026
- Custom evaluators
- Users can supply a Python evaluator that accepts a prompt and returns a score between 0 and 1.github.com · read 9 Oct 2026
- Default threshold
- The README says the default stopping threshold is 1.0.github.com · read 9 Oct 2026
- Evaluation
- By default, an LLM evaluates candidate prompts using a self-consistency approach.github.com · read 9 Oct 2026
- How to install
- The README gives `pipx install promptimal` as the installation command.github.com · read 9 Oct 2026
- How to start
- Users can launch Promptimal in a terminal and enter a prompt and an improvement description, or provide them as command-line arguments.github.com · read 9 Oct 2026
- Installation
- The README gives `pipx install promptimal` as the installation command.github.com · read 9 Oct 2026
- License
- The GitHub repository identifies the project as MIT licensed.github.com · read 9 Oct 2026
- OpenAI setup
- The README instructs users to set an OpenAI API key in their environment before running Promptimal.github.com · read 9 Oct 2026
- Optimization
- It uses a genetic algorithm to iteratively refine a prompt based on a description of what the user wants to improve.github.com · read 9 Oct 2026
- Optimization controls
- Command-line options control the number of iterations, candidate prompts per iteration, and score threshold for stopping.github.com · read 9 Oct 2026
- Product
- Promptimal is a command-line tool for improving AI prompts without needing a dataset.github.com · read 9 Oct 2026
- Progress UI
- The optimization process can be monitored in a UI opened in the terminal.github.com · read 9 Oct 2026
- Provider roadmap
- The README lists support for other LLM providers, including Anthropic, Groq, and Ollama, as roadmap items.github.com · read 9 Oct 2026
- Roadmap
- The roadmap lists support for other LLM providers, including Anthropic and Groq, and local models through Ollama, as planned work.github.com · read 9 Oct 2026
- Terminal interface
- After starting an optimization, users can monitor its progress in a UI in their terminal.github.com · read 9 Oct 2026
