semvec/pypi-packages huggingface dataset:
shapesinc 0.3.4
A module for interacting with shapes.inc API.
License: MIT
Requires Python: >=3.8

# shapesinc-py

## Installation

From PyPI:
```
pip install shapesinc -U
```

From GitHub:
```
pip install git+https://github.com/Rishiraj0100/shapesinc-py.git
```

## Examples

### Synchronous Shape Example
```py
from shapesinc import (
  shape,
  ShapeUser as User,
  ShapeChannel as Channel
)

my_shape = shape("API_KEY", "my_shape")
user = User("u0")
channel = Channel("cli")

while True:
  inp = input(" >>> ")
  r = my_shape.prompt(inp, user = user, channel=channel)
  print(r.choices[0].message)
```
### Asynchronous Shape Example
```py
from shapesinc import (
  shape,
  ShapeUser as User,
  ShapeChannel as Channel
)

my_shape = shape("API_KEY", "my_shape", synchronous=False)
user = User("u0")
channel = Channel("cli")

async def run():
  while True:
    inp = input(" >>> ")
    r = await my_shape.prompt(inp, user = user, channel=channel)
    print(r.choices[0].message)

import asyncio
asyncio.run(run())
```
### Image Examples
```py
from shapesinc import Message, MessageContent, ContentType as C

msg = Message.new("Explain this image!", [dict(url = "URL OF IMAGE", type = c.image)])

resp = my_shape.prompt(msg)
```
### Audio Messages
```py
from shapesinc import Message, MessageContent, ContentType as C

msg = Message.new(files = [dict(url = "URL OF AUDIO FILE", type = c.audio)])

resp = my_shape.prompt(msg)
```

## Note
- When both audio and image files are given in one message, only audio will be processed!
- Commands like `!wack` can be normally used with `Shape.prompt` method.
qubitflow 0.1.0
A modular and scalable quantum computing framework inspired by TensorFlow and PyTorch.
License: MIT
Requires Python: >=3.8

# QubitFlow

**QubitFlow** is an open-source quantum computing framework based on python designed to be intuitive, scalable, and modular — bringing the simplicity of TensorFlow and PyTorch to the quantum world.

🚧 **Currently Under Active Development**  
We are laying the foundations for a robust, user-friendly quantum programming interface. The initial push will be live soon!

---

## 🔍 About the Project

QubitFlow aims to simplify quantum circuit design, simulation, and integration with classical machine learning workflows. Our mission is to:

- Make quantum programming **accessible** to developers and researchers
- Provide a **modular architecture** for rapid experimentation
- Support both **quantum simulation** and **real quantum hardware backends**
- Enable **hybrid quantum-classical models** in a seamless fashion

---

## 📌 Planned Features

- Quantum Circuit API (Tensor-like syntax)
- Backend support for simulators and real quantum processors (Qiskit, Braket, etc.)
- Parameterized gates and optimization routines
- Integration with NumPy, PyTorch, and JAX
- Quantum datasets and benchmarking tools
- Visualization of quantum states and circuits

---

## 📦 Installation

Coming soon: `pip install qubitflow`

---

## 👷 Roadmap

- [x] Project Initialization
- [ ] Core Quantum Circuit API
- [ ] Backend Plugin System
- [ ] Hybrid Model Examples
- [ ] Documentation and Tutorials
- [ ] First Release (v0.1.0)

---

## 🤝 Contributing

Interested in contributing? We'd love to collaborate! Stay tuned for contributing guidelines once the repo is live.

---

## 📬 Stay Updated

Watch the repository for the first release, documentation, and usage examples.

---

> _QubitFlow – Building the bridge between classical and quantum intelligence._