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A Python wrapper for managing OpenAI API and other LLM models.

Project description

LLM Tools

This package wraps the OpenAI API and other LLM models that share the completion endpoint feature. It provides a simple interface to generate text from a prompt.

Installation

pip install llm-space

Usage

from llm_space.openai import prompt
from pathlib import Path


# Create a prompt object that will be logged to the `my-task` directory under the
# current working directory.
# The PromptZeros class will use arguments that will maximize the determinism of the outputs.
pz = prompt.PromptZeros(Path("./"), "my-task")

# Send a prompt to the API and return the response.
w = pz.send_prompt("What is the WDI code for GDP?", return_data=True)

# Print the response.
print(w)

# Output:

# {'message': [{'role': 'system', 'content': ''}, {'role': 'user', 'content': 'What is the WDI code for GDP?'}], 'response': {'id': 'chatcmpl-8V0IN0VbeYTrsBAohs309DHJQLJL8', 'choices': [{'finish_reason': 'stop', 'index': 0, 'message': {'content': 'The WDI code for GDP (Gross Domestic Product) is "NY.GDP.MKTP.CD".', 'role': 'assistant', 'function_call': None, 'tool_calls': None}}], 'created': 1702399995, 'model': 'gpt-3.5-turbo-0613', 'object': 'chat.completion', 'system_fingerprint': None, 'usage': {'completion_tokens': 23, 'prompt_tokens': 20, 'total_tokens': 43}}, 'content': 'The WDI code for GDP (Gross Domestic Product) is "NY.GDP.MKTP.CD".', 'api_kwargs': {'temperature': 0, 'top_p': 0, 'n': 1, 'stream': False, 'frequency_penalty': 0, 'presence_penalty': 0, 'model': 'gpt-3.5-turbo', 'max_tokens': 4029}, 'metadata': {}, 'message_hash': '1a5816095c232f29428d4cec70498391'}

NOTE: The output is also logged to the my-task directory under the current working directory.

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