semvec/pypi-packages huggingface dataset:
safi 0.0.2
Safi is a versatile and super fast Ai Platform. This is a Python library for Safi API.
Requires Python: >=3.6

safi - Pure

Safi is a versatile and high performance Ai Platform. This is a Python library for Safi APIs.

Installation

You can install this package using pip:

```sh
pip install safi


##Usage

from safi import Safi

# Get your api key from your account dashbaord on safi.insolify.com

# Basic Usage for 
safi = Safi(api_key)
response = safi.chat('Hi Safi').go()
print(response....)


# Usage with voice input
safi = Safi(api_key, lang='pidgin')
response = safi.chat(record.mp3).go()
print(response.......)

#Transcription/Dictation
safi = safi(api_key, lang='pidgin')
response = safi.listen(input_audio) 
print(response[0]....) #chunks..
#This can be real time audio stream from speaker or microphone or direct audio.

Other use cases can be explored from your dashboard.
substrate 220240617.1.8
Substrate Python SDK
Requires Python: >=3.9

# Substrate Python SDK

[![PyPI version](https://img.shields.io/pypi/v/substrate.svg)](https://pypi.org/project/substrate/)

Substrate is a **powerful SDK** for building with AI, with [batteries included](https://substrate.run/nodes): language models, image generation, built-in vector storage, sandboxed code execution, and more. To use Substrate, you simply connect tasks, and then run the workflow. With this simple approach, we can create AI systems (from RAG, to agents, to multi-modal generative experiences) by simply describing the computation, with **zero additional abstractions**.

Substrate is also a **workflow execution** and **inference** engine, optimized for running compound AI workloads. Wiring together multiple inference APIs is inherently slow – whether you do it yourself, or use a framework like LangChain. Substrate lets you ditch the framework, write less code, and run compound AI fast. 

## Documentation

If you're just getting started, head to [docs.substrate.run](https://docs.substrate.run/).

For a detailed API reference covering the nodes available on Substrate, see [substrate.run/nodes](https://www.substrate.run/nodes).

## Installation

```sh
# install from PyPI
pip install substrate
```

## Usage

```python
from substrate import Substrate, ComputeText, sb
```

Initialize the Substrate client.

```python
substrate = Substrate(api_key=SUBSTRATE_API_KEY)
```

Generate a story using the [`ComputeText`](https://www.substrate.run/nodes#ComputeText) node.

```python
story = ComputeText(prompt="tell me a story")
```

Summarize the output of the `story` node using another `ComputeText` node. Because `story` has not yet been run, we use `sb.concat` to work with its future output.

```python
summary = ComputeText(prompt=sb.concat("summarize this story in one sentence: ", story.future.text))
```

Run the graph chaining `story` → `summary` by passing the terminal node to `substrate.run`.

```python
response = substrate.run(story, summary)
```

(To run the graph asynchronously, simply use `async_run` and `await`.)

```python
response = await substrate.async_run(story, summary)
```

Get the output of the summary node by passing it to `response.get`.

```python
summary_out = response.get(summary)
print(summary_out.text)
# Princess Lily, a kind-hearted young princess, discovers a book of spells and uses it to grant her family and kingdom happiness.
```

## Examples

To run the above example as a notebook, navigate to the `examples/notebooks` directory and run:

```sh
make ensure                         # install dependencies
poetry run marimo edit basic.py     # run the notebook
```

Many more examples are included in the `/examples` directory.
macsploit 0.0.3
A small example package
Requires Python: >=3.6

```markdown
# msapi

A Python package for executing scripts with Macsploit's API.

## Overview

This package provides a simple way to execute Roblox scripts (with Macsploit API) via a local server connection. It is designed to work with Roblox's Lua scripting language.

## Installation

You can install the package via pip:

```sh
pip3 install msapi
```