omnimodkit 0.0.3

Get structured output from multimodal AI models and integrate them into multitool agents

OmniModKit

Use convenient multimodal toolkit that operates with structured output.

Easily build agent tools on top of that.

Implementation

This package utilizes the implemented langchain structured output pipelines.

Installation

pip install omnimodkit

Usage

• Import ModelsToolkit
• Run appropriate models
• Get structured output response

from omnimodkit import ModelsToolkit

# Initialize the model toolkit
modkit = ModelsToolkit()

# Run the model synchronously
modkit.text_model.run(
    user_input="What is the capital of France?",
)

# Stream responses from the model
for response in modkit.text_model.stream(
    user_input="What is the capital of France?",
):
    print(response, end="|", flush=True)

# Generate images
modkit.image_generation_model.run(
    user_input="Draw a cat",
)

# Use audio recognition
import io
import requests

url = "https://cdn.openai.com/API/examples/data/ZyntriQix.wav"
audio_bytes = io.BytesIO(requests.get(url, timeout=10).content)
audio_bytes.name = "audio.wav"
modkit.audio_recognition_model.run(
    in_memory_audio_stream=audio_bytes,
)

# Use image recognition
import io
import requests

url = "https://raw.githubusercontent.com/Flagro/treefeeder/main/logo.png"
image_bytes = io.BytesIO(requests.get(url, timeout=10).content)
image_bytes.name = "image.png"
modkit.vision_model.run(
    in_memory_image_stream=image_bytes,
)

License

MIT license