zackbradshaw / autotemp

A trial-and-error approach to temperature opimization for LLMs. Runs the same prompt at many temperatures and selects the best output automatically.

AutoTemp

AutoTemp is a Python tool that enhances language model interactions by intelligently selecting the optimal temperature setting for generating responses. It leverages multiple temperature settings to produce a variety of outputs and then evaluates these outputs to determine which temperature yields the best result for a given prompt.

Features

• Multi-Temperature Evaluation: Tests multiple temperature settings to find the best output for a given prompt.
• Automatic or Manual Selection: Supports both automatic selection of the best output based on scores and manual selection by presenting options to the user.
• Customizable Temperature Range: Users can define a custom range of temperatures to be tested for each prompt.
• Easy Integration: Designed to work with OpenAI's GPT-3.5 or GPT-4 and is compatible with other language models that support temperature settings.

Installation

To install AutoTemp, you can simply clone the repository and install the required dependencies.

git clone https://github.com/elder-plinius/AutoTemp.git
cd AutoTemp
pip install -r requirements.txt

OpenAI API Key

Before running AutoTemp, you need to set up your API key in an .env file at the root of the project:

OPENAI_API_KEY='your-api-key-here'

This file should not be committed to your version control system as it contains sensitive information.

Usage

To use AutoTemp, simply run the autotemp.py script with Python:

python autotemp.py

You can pass your prompt directly into the AutoTemp class instance within the script.

Configuration

You can customize the behavior of AutoTemp by setting the following parameters when initializing AutoTemp:

default_temp: The default temperature to use for initial output.
alt_temps: A list of alternative temperatures to evaluate.
auto_select: Whether to automatically select the best output or present options to the user.
max_workers: The maximum number of threads to use for concurrent API calls.
model_version: Specifies the model version to use, such as "gpt-3.5-turbo" or "gpt-4".