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Description:

promptfunctions 0.1.27

Prompt Functions ⚙️
prompt-functions aims to make it easy to build functions with LLMs that have structured I/O, and to move prompts out of the code into serialized and versioned formats.
Getting Started
1. Installation
Install the package using pip:
pip install prompt-functions

2. Setting Up Your First Function
Let's create a sentiment classification function:
Step 1: Create a directory named sentiment. Inside this directory, you need two files:
└─ sentiment
├── function_args.json
├── model_args.json
└── template.txt

Step 2: Define your prompt template in template.txt:
Aalyze and determine whether the sentiment of the following sentence is positive, negative, or neutral.
Sentence:
{sentence}

Step 3: Set model paramters in model_args.json:
{
"temperature": 0.0,
"model": "gpt-3.5-turbo"
}

Step 4: Specify the function's output format in function_args.json:
{
"function_name": "sentiment_classifier",
"description": "Classify the sentiment of a sentence",
"properties": {
"thoughts": {
"type": "string",
"description": "Your thoughts when classifying sentiment of the given sentence."
},
"sentiment": {
"type": "string",
"enum": ["positive", "negative", "neutral"],
"description": "The sentiment of the given sentence."
}
}
}

3. Using Your Prompt Function in Python
Here's how you can load and use your prompt function:
from prompt_functions import PromptFunction

# Load your function
sentiment = PromptFunction.from_dir("./sentiment/")

# Make a prediction
pred = sentiment(sentence="I am super happy!")

# Expected Output:
# {
# "thoughts": "The sentiment in the sentence is positive",
# "sentiment": "positive"
# }

Prompt Versioning
Coming up..