sageai 1.0.0

File-based functions for ChatGPT's function calling with Pydantic support

File-based functions for ChatGPT's function calling with Pydantic support 🚀

Key Features

• Organization through file-centric functions, organized in directories.
• Strong typing for functions using Pydantic.
• Built-in in-memory FAISS vector database, with the option to integrate your own.
• Easily test each function with an associated test.json file, supporting both unit and integration tests.
• Built with CI/CD in mind, ensuring synchronicity between your vector db and the functions directory across all environments.
• Lightweight implementation with only three dependencies: openai, pydantic, and qdrant-client.

Requirements

python >=3.9, <3.12
pydantic >=1.6, <=1.10.12
openai >=0.27.0
qdrant-client >=1.4.0

Installation

# pip
$ pip install sageai

# poetry
$ poetry add sageai

Functions Directory

SageAI is built around the concept of a functions directory, which contains all of your functions. Each function is defined in a Python file function.py, and is associated with an optional test.json file for testing.

The format of the function.py file must contain two things in order for SageAI to work:

1. The function itself
2. The Function object

Input and output types may be defined using Pydantic models, and are automatically validated by SageAI. They can also be defined outside the function.py file, and imported into the file.

Below is a minimal example of a function that returns the current weather in a given location.

# function.py
from pydantic import BaseModel, Field

from sageai.types.function import Function


class FunctionInput(BaseModel):
    location: str = Field(
        ...,
        # Required, will be used in the request to OpenAI
        description="The city and state, e.g. San Francisco, CA."
    )


class FunctionOutput(BaseModel):
    weather: str


def get_current_weather(params: FunctionInput) -> FunctionOutput:
    weather = (
        f"The weather in {params.location} is currently 22 degrees {params.unit.value}."
    )
    return FunctionOutput(weather=weather)


function = Function(
    function=get_current_weather,
    # Required, will be used in the request to OpenAI
    description="Get the current weather in a given location.",
)

As for the test.json file,

Setup

Create a functions directory in the root directory, and add your functions as described in the section above.

Then initialize SageAI.

from sageai import SageAI

sageai = SageAI(openai_key="")

Then index the vector database.

sageai.index()

That's it! Just start chatting 🚀

message = "What's the weather like in Boston right now?"
response = sageai.chat(
    messages=[dict(role="user", content=message)],
    model="gpt-3.5-turbo-0613",
    sageai=dict(k=5),
)
# The weather in Boston, MA is currently 22 degrees Celsius.

Documentation

SageAI.init()

Pass

SageAI.index()

Pass

SageAI.chat()

Pass

Examples

• basic
• advanced

Limitations

Roadmap

• Add tests and code coverage
• Support streaming
• Support asyncio
• Add debug flag for logger
• Support Pydantic V2
• Write Chainlit example
• Write fullstack example

Contributing

Please see our CONTRIBUTING.md.