This module provides a prompt library manager and API wrapper for interacting with large language models to generate prompts and assistant definitions. It relies on the langchain library as well as the OpenAI and Anthropic APIs.
This package is not currently available on PyPI. To install clone the repo and install Langchain, Anthropic, and OpenAI PyPI packages.
You will also need to obtain API keys for OpenAI and Anthropic to use their models.
To define a new assistant, format an assistant_definition in markdown like this:
<assistant_definition>
<name>Your Assistant Name</name>
<role>Description of your assistant's purpose or role</role>
<system_message>A message from your assistant to the user explaining its purpose</system_message>
<example_input>An example user input or query</example_input>
<example_output>Your assistant's response to the example input</example_output>
</assistant_definition> You can then generate a new LanguageExpert object from this definition using the parse_assistant_definition() function:
definition_text = ... # Your assistant definition markdown
expert = parse_assistant_definition(definition_text)
expert = LanguageExpert(**expert)The LanguageExpert object can then be used to generate responses from your assistant model. You can also improve an existing assistant definition using the improve() function.
Contributions are welcome! Please open an issue or submit a pull request on GitHub with any bugs, feature requests, or changes. As is clearly evident I am not a very good programmer but I am a pretty good prompt engineer. I'm hoping to share what I've learned with others and improve both skillsets in the process.