AIConfig Tools: Configuring and Interacting AIConfigs

Overview

AIConfig Tools is a package that simplifies Prompt, Model, and Parameter Management by allowing you to create and manage AIConfigs.

Table of Contents

1. Installation
2. Creating AIConfig Runtime
3. Creating and Managing Prompts
4. Updating Model Settings
5. Executing and Displaying Output
6. Saving Configuration to Disk

1) Installation

First, you need to install the AIConfig Tools package and any required dependencies. Use the following command to install it. :

Python

pip install python-aiconfig

2) Creating AIConfig Runtime

To start using AIConfig Tools, create an AIConfig Runtime instance. This runtime will allow you to manage prompts, model settings, and execute AI tasks. Here's how you can create it:

from aiconfig.Config import AIConfigRuntime
aiconfig = AIConfigRuntime.create("demo", "this is a demo AIConfig")

Loading an existing config is easy too.

from aiconfig.Config import AIConfigRuntime
aiconfig = AIConfigRuntime.from_config("/path/to/config")

3) Creating and Managing Prompts

Prompts are input messages or queries you send to a Large Language model. You can create and manage prompts using AIConfig Tools. Here's an example of creating a prompt:

from aiconfig.schema import ModelMetadata, Prompt

prompt = Prompt(
    name="prompt1",
    input="Hi! What are transformers?",
    metadata={
        "model": "gpt-3.5-turbo",
    }
)

aiconfig.add_prompt(prompt.name, prompt)

4) Updating Model Settings

You can also update the settings of Large Language models, such as temperature and top-k. Here's an example of updating the model settings:

model_name = "gpt-3.5-turbo"
model_settings = {
    "top_k": 40,
    "top_p": 0.95,
    "model": "gpt-3.5-turbo",
    "temperature": 0.9
}

aiconfig.add_model(model_name, model_settings)

5) Executing and Displaying Output

Once you have created prompts and updated model settings, you can execute prompts and retrieve the output. Here's an example of executing a prompt and displaying the output:

import asyncio
parameters = {"name": "Demo"}
asyncio.run(aiconfig.run("prompt1", parameters))

latest_output = aiconfig.get_latest_output("prompt1")
output_text = aiconfig.get_output_text("prompt1", latest_output)
print(output_text)

6) Saving Configuration to Disk

You can save your AIConfig configuration to disk for later use or to share with others. This allows you to persist your prompts, model settings, and other configurations. Here's how you can save your AIConfig configuration to a file:

# Save the configuration to a file
aiconfig.save_config("my_aiconfig.json")

More Demos

Checkout the demo folder for example configs and example python notebooks.

aiconfig

aiconfig -- for prompt, model and parameter management

• Motivation
• Why use aiconfig
• Getting Started
• Core Components
• Capabilities
  • Version Control
  • Model parser
  • Routing
  • Evaluation
• Debugging
• Roadmap
  • Multi-modal model support (use with image, audio generation models as well as multi-modal models like GPT-V)
  • Routing
  • Evaluation