semvec/pypi-packages huggingface dataset:
python-viu-api 0.3.54
gRPC client for VIU API
Requires Python: >=3.8

# Python Client for Viu API

This package provides the generated Python client code for accessing various text embedding services
via gRPC. It is built from proto files found in the `proto` directory.

## Installation

Install the package using pip:

```bash
pip install python-viu-api
```

## Usage

Import the generated modules in your Python code:

```python
from python_viu_api import jinaembed_pb2, viu_api_pb2, viu_api_pb2_grpc
import grpc

# Example: Create a request for Jina embeddings
request = jinaembed_pb2.JinaEmbedRequest(
    texts=["Sample text"],
    task=jinaembed_pb2.RETRIEVAL_QUERY,
    truncate_dim=128
)

# Set up a gRPC channel (adjust the target as needed)
channel = grpc.insecure_channel('localhost:50051')
stub = viu_api_pb2_grpc.ApiServiceStub(channel)

# Call the EmbedJinaEmbeddingsV3 RPC
response = stub.EmbedJinaEmbeddingsV3(request)
print(response)
```

## Supported Models

- NVEmbedV2
- BGEGemma2
- JinaEmbeddingsV3
mheatmap 1.2.5
A package for mosaic/proportional heatmap visualization and matrix analysis
Requires Python: >=3.8

# <img src="docs/assets/mheatmap.png" width="40px" align="center" alt="mheatmap logo"> mheatmap

[![PyPI version](https://badge.fury.io/py/mheatmap.svg)](https://badge.fury.io/py/mheatmap)
[![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT)

A Python package for advanced heatmap visualization and matrix analysis,
featuring mosaic/proportional heatmaps, confusion matrix post-processing,
and spectral reordering capabilities.

---

## 📋 Table of Contents

1. [🚀 Features](#-features)
2. [📦 Installation](#-installation)
    - [Install from PyPI](#install-from-pypi)
    - [Install from Source](#install-from-source)
3. [📘 Documentation](#-documentation)
4. [📚 Examples](#-examples)
5. [🛠 Contributing](#-contributing)
6. [📝 License](#-license)

---

## 🚀 Features

- **Mosaic Heatmap**  
  Visualize matrix values with proportionally-sized cells.  
  ![Comparison between normal and mosaic heatmap](docs/examples/images/basic_mosaic_heatmap.png)

- **Automatic Model Calibration (AMC)**  
  Align, Mask, and Confusion—an algorithm for post-processing confusion matrices.

- **Spectral Reordering**  
  Reorder matrices based on spectral analysis.
  ![Spectral reordering example](docs/examples/images/spectral_permutation.png)

- **RMS (Reverse Merge/Split) Analysis**  
  Perform advanced permutation analysis to explore matrix structures.  
  ![RMS permutation example](docs/examples/images/rms_permutation.png)

---

## 📦 Installation

### Install from PyPI

```bash
pip install mheatmap
```

### Install from source

```bash
git clone https://github.com/qqgjyx/mheatmap.git
cd mheatmap
pip install .
```

## 📘 Documentation

Comprehensive documentation is available [here](https://www.qqgjyx.com/mheatmap).

## 📚 Examples

See [Examples](docs/examples) for more detailed examples.

## 🛠 Contributing

We welcome contributions to improve mheatmap! Please follow these steps:

1. Fork the repository
2. Create a new branch (`feature-branch`)
3. Commit your changes
4. Open a pull request

## 📝 License

This project is licensed under the MIT License.
See the [LICENSE](LICENSE) file for details.