semvec/pypi-packages huggingface dataset:
openvto 0.1.7
Open-source toolkit for building studio-quality virtual try-ons with generative AI
Requires Python: >=3.10
Keywords: fashion, generative-ai, image-generation, video-generation, virtual-try-on

# OpenVTO SDK

Open-source toolkit for building studio-quality virtual try-ons with generative AI.

## Installation

```bash
pip install openvto
```

## Quick Start

```python
from openvto import OpenVTO

# Initialize client
vto = OpenVTO(provider="google")

# Generate avatar from selfie + posture
avatar = vto.generate_avatar(
    selfie="selfie.jpg",
    posture="fullbody.jpg"
)

# Try on clothes
tryon = vto.generate_tryon(
    avatar=avatar,
    clothes=["shirt.jpg", "pants.jpg"]
)

# Generate video loop
video = vto.generate_videoloop(tryon.image)
```

## Documentation

See the main [README](../../README.md) for full documentation.

## License

MIT
langchain-gigachat-lc1 0.4.0b4
An integration package connecting GigaChat and LangChain
Requires Python: <4,>=3.10

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[English](README.md) | [Русский](README-ru_RU.md)

</div>

# langchain-gigachat

This is a library integration with [GigaChat](https://giga.chat/).

## Installation

```bash
pip install -U langchain-gigachat
```

## Quickstart
Follow these simple steps to get up and running quickly.

### Installation

To install the package use following command:

```shell
pip install -U langchain-gigachat
```

### Initialization

To initialize chat model:

```python
from langchain_gigachat.chat_models import GigaChat

giga = GigaChat(credentials="YOUR_AUTHORIZATION_KEY", verify_ssl_certs=False)
```

To initialize embeddings:

```python
from langchain_gigachat.embeddings import GigaChatEmbeddings

embedding = GigaChatEmbeddings(
    credentials="YOUR_AUTHORIZATION_KEY",
    verify_ssl_certs=False
)
```

### Usage

Use the GigaChat object to generate responses:

```python
print(giga.invoke("Hello, world!"))
```

Now you can use the GigaChat object with LangChain's standard primitives to create LLM-applications.