Skip to main content

OpenAI Helper for Easy I/O

Project description

OpenAI-Helper

OpenAI Helper for Easy I/O

Github

https://github.com/craigtrim/openai-helper

Usage

Set the OpenAI credentials

import os
os.environ['OPENAI_KEY'] = "<encrypted key>"
os.environ['OPENAI_ORG'] = "<encrypted key>"

Use CryptoBase.encrypt_str("...") from https://pypi.org/project/baseblock/

Initialize the OpenAI Helper:

run = OpenAITextCompletion().run

This will connect to OpenAI and establish performant callbacks.

Call OpenAI:

run(input_prompt="Generate a one random number between 1 and 5000")

or

run(engine="text-ada-001",
    temperature=1.0,
    max_tokens=256,
    input_prompt="Rewrite the input in grammatical English:\n\nInput: You believe I can help you understand what trust yourself? don't you?\nOutput:\n\n")

The output will contain both the input and output values:

{
   "input":{
      "best_of":1,
      "engine":"text-davinci-003",
      "frequency_penalty":0.0,
      "input_prompt":"Rewrite the input in grammatical English:\n\nInput: You believe I can help you understand what trust yourself? don't you?\nOutput:\n\n",
      "max_tokens":256,
      "presence_penalty":2,
      "temperature":1.0,
      "timeout":5,
      "top_p":1.0
   },
   "output":{
      "choices":[
         {
            "finish_reason":"stop",
            "index":0,
            "logprobs":"None",
            "text":"Don't you believe that I can help you understand trust in yourself?"
         }
      ],
      "created":1659051242,
      "id":"cmpl-5Z7IwXM5bCwWj8IuHaGnOLn6bCvHz",
      "model":"text-ada-001",
      "object":"text_completion",
      "usage":{
         "completion_tokens":17,
         "prompt_tokens":32,
         "total_tokens":49
      }
   }
}

Supported Parameters and Defaults

This method signature describes support:

def process(self,
            input_prompt: str,
            engine: str = None,
            best_of: int = None,
            temperature: float = None,
            max_tokens: int = None,
            top_p: float = None,
            frequency_penalty: int = None,
            presence_penalty: int = None) -> dict:
    """ Run an OpenAI event

    Args:
        input_prompt (str): The Input Prompt to execute against OpenAI
        engine (str, optional): The OpenAI model (engine) to run against. Defaults to None.
            Options as of July, 2022 are:
                'text-davinci-003'
                'text-curie-001',
                'text-babbage-001'
                'text-ada-001'
        best_of (int, optional): Generates Multiple Server-Side Combinations and only selects the best. Defaults to None.
            This can really eat up OpenAI tokens so use with caution!
        temperature (float, optional): Control Randomness; Scale is 0.0 - 1.0. Defaults to None.
            Scale is 0.0 - 1.0
            Lower values approach predictable outputs and determinate behavior
            Higher values are more engaging but also less predictable
            Use High Values cautiously
        max_tokens (int, optional): The Maximum Number of tokens to generate. Defaults to None.
            Requests can use up to 4,000 tokens (this takes the length of the input prompt into account)
            The higher this value, the more each request will cost.
        top_p (float, optional): Controls Diversity via Nucleus Sampling. Defaults to None.
            no idea what this means
        frequency_penalty (int, optional): How much to penalize new tokens based on their frequency in the text so far. Defaults to None.
            Scale: 0.0 - 2.0.
        presence_penalty (int, optional): Seems similar to frequency penalty. Defaults to None.

    Returns:
        dict: an output dictionary with two keys:
            input: the input dictionary with validated parameters and default values where appropriate
            output: the output event from OpenAI
    """

Counting Tokens (tiktoken)

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

openai_helper-0.2.4.tar.gz (19.9 kB view details)

Uploaded Source

Built Distribution

openai_helper-0.2.4-py3-none-any.whl (34.2 kB view details)

Uploaded Python 3

File details

Details for the file openai_helper-0.2.4.tar.gz.

File metadata

  • Download URL: openai_helper-0.2.4.tar.gz
  • Upload date:
  • Size: 19.9 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: poetry/1.5.1 CPython/3.8.5 Windows/10

File hashes

Hashes for openai_helper-0.2.4.tar.gz
Algorithm Hash digest
SHA256 e27978ffe6b3ee21b106fa91769cf7efb414696a6555882847457e4fe9b4b4dd
MD5 fb082c01cb2e99f3373afbd6e7a564cd
BLAKE2b-256 518119c41f4ef3eb0a51dfecced84934eeb1dde5fccfdd7530aac4a63e4c3655

See more details on using hashes here.

Provenance

File details

Details for the file openai_helper-0.2.4-py3-none-any.whl.

File metadata

  • Download URL: openai_helper-0.2.4-py3-none-any.whl
  • Upload date:
  • Size: 34.2 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: poetry/1.5.1 CPython/3.8.5 Windows/10

File hashes

Hashes for openai_helper-0.2.4-py3-none-any.whl
Algorithm Hash digest
SHA256 22c7c089c0049c9105d4fae8c51fc139cb4bebd0f777235c97b7a4aec4d00338
MD5 38eaa7024141d89c89bba5089f854414
BLAKE2b-256 58374e2025f280db737a21ec3a48eaf2dff4c334418e955856acc3537f6fbce9

See more details on using hashes here.

Provenance

Supported by

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