Skip to main content

A simple GPT interface

Project description

ezgpt

ezgpt is a Python library designed to simplify the interaction with OpenAI's GPT (Generative Pre-trained Transformer) models. It provides a convenient interface for sending prompts to the model and receiving responses, with optional logging for debugging purposes.

Installation

You can install ezgpt via pip:

pip install ezgpt

Usage

To use ezgpt, you need to have an API key from OpenAI. This key must be set as an environment variable OpenAI_APIKey before using the library.

Initialization

First, import the ezgpt module and initialize the gpt class:

import ezgpt

gpt = ezgpt.gpt()

The gpt class constructor accepts the following parameters:

  • model: The identifier of the GPT model to use (default: 'gpt-3.5-turbo').
  • system: An optional system-level prompt that provides instructions or context for the GPT model.
  • temperature: Controls randomness in the response generation (default: 0).
  • top_p: Controls diversity of the response generation (default: 0).
  • max_tokens: The maximum number of tokens to generate in the response (default: 2048).
  • frequency_penalty: Decreases the likelihood of repetition in the response (default: 0).
  • presence_penalty: Encourages the model to talk about new topics (default: 0).
  • logs: Enables or disables logging of the interaction (default: False).

Sending Prompts

To send a prompt to the GPT model, use the get method of the gpt instance:

response = gpt.get(user="Your prompt here")

The get method accepts the following parameters:

  • system: Overrides the system-level prompt for this request.
  • user: The user-level prompt to send to the model.
  • messages: A list of previous message exchanges to maintain context.
  • temperature: Overrides the default temperature for this request.
  • top_p: Overrides the default top_p for this request.
  • max_tokens: Overrides the default max_tokens for this request.
  • frequency_penalty: Overrides the default frequency_penalty for this request.
  • presence_penalty: Overrides the default presence_penalty for this request.

Since your last request is stored under self.previous, you can append a message to your conversation like that:

response = gpt.get(messages=gpt.previous, user="Another message")

Logging

If logging is enabled, ezgpt will print the interaction with the GPT model to the console. This includes the prompts sent by the user and system, as well as the responses from the assistant.

Notes

  • The ezgpt library assumes that the OpenAI API key is set in the environment variable OpenAI_APIKey.
  • The gpt class maintains a history of the conversation in the previous attribute, which can be used to provide context for subsequent requests.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

ezgpt-0.1.3.tar.gz (4.0 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

ezgpt-0.1.3-py3-none-any.whl (4.2 kB view details)

Uploaded Python 3

File details

Details for the file ezgpt-0.1.3.tar.gz.

File metadata

  • Download URL: ezgpt-0.1.3.tar.gz
  • Upload date:
  • Size: 4.0 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.11.2

File hashes

Hashes for ezgpt-0.1.3.tar.gz
Algorithm Hash digest
SHA256 2c2a704b93e78cb724969d7d851bf26a774a97503e4fa263343780295666123c
MD5 051de596198382d9cacac26ff56c30be
BLAKE2b-256 f9082dcb6deee1b687e6ed09b074830ae05bb2444cedd8cae2c3c285748fcceb

See more details on using hashes here.

File details

Details for the file ezgpt-0.1.3-py3-none-any.whl.

File metadata

  • Download URL: ezgpt-0.1.3-py3-none-any.whl
  • Upload date:
  • Size: 4.2 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.11.2

File hashes

Hashes for ezgpt-0.1.3-py3-none-any.whl
Algorithm Hash digest
SHA256 c9392cc2c8bf2056eade55026d6bacf34c17383930e11ea9839c6c294d9f155d
MD5 eb41f6807f02293572635b69ac124ea4
BLAKE2b-256 c34875840bcccbd98deef1de83581730fb3a88d454b1663a8e846061b9794d3c

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page