Interact

A simple python library to interact and build applications with Large Language Models.

Core Concept

graph LR
    subgraph "HandlerChain"
        A[Handler 1] -->|Message| B[Handler 2]
        B -->|Message| C[Handler 3]
    end
    Input["Input (Message)"] --> A
    C --> Output["Output (Message)"]

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Interact has three main components / assumptions:

• Entities in an application communicate through Messages.
• Messages are passed through Handlers that can modify (transform, format, etc.) the Message.
• Handlers are chained together to form a HandlerChain. HandlerChains hold a sequence of Handlers that are executed in order.

Installation

pip install -U "interact @ git+https://github.com/pritam-dey3/Interact.git"

or, if you use faiss for similarity search

pip install -U "interact[faiss] @ git+https://github.com/pritam-dey3/Interact.git"

Example Usage

import asyncio

from dotenv import load_dotenv

from interact import HandlerChain, Message, handler
from interact.handlers import OpenAiLLM

load_dotenv()  # load openai api key from .env file


@handler
async def company_name(msg: Message, chain: HandlerChain) -> str:
    chain.variables["product"] = msg.primary
    return (
        f"What would be an appropriate name for a business specializing in {msg.primary}?"
        "Only mention the company name and nothing else."
    )


@handler
async def company_tagline(msg: Message, chain: HandlerChain) -> str:
    return (
        f"What would be an appropriate tagline for a business specializing in {chain.variables['product']}"
        f" and with company name {msg.primary}?\nFormat your output in the following"
        f" format:\n{msg.primary}: <tagline>"
    )


def main():
    name_and_tagline_generator = (
        company_name >> OpenAiLLM() >> company_tagline >> OpenAiLLM()
    )

    res = asyncio.run(name_and_tagline_generator("bike"))
    print(res)


if __name__ == "__main__":
    main() # Socket: The best socks in the world

Why Interact?

Applications with Large Language Models can get complex very quickly. You need more customizability and control over the prompts and their execution to satisfactorily build an application.

Interact was created with simplicity and scalability in mind. The core concepts of Messages, Handlers, and HandlerChains are simple to understand and gives You the power to build complex applications with ease.

More popular alternatives like langchain gets frustrating to use when you want to customize either the process or the prompts according to your needs. Interact gives you the control while maintaining a very simple and intuitive API.