semvec/pypi-packages huggingface dataset:
sequrity 0.4.0.post2
A Python client for Sequrity API
Requires Python: >=3.11

# Sequrity

Please see the full [Documentation](https://sequrity-ai.github.io/sequrity-api/)

Python client and REST API for Sequrity.


## Installation

```bash
pip install sequrity
```

## Quick Start

```python
from sequrity import SequrityClient

sequrity_key = "<your-sequrity-api-key>"
openrouter_key = "<your-openrouter-key>"

client = SequrityClient(api_key=sequrity_key)

response = client.control.chat.create(
    messages=[{"role": "user", "content": "What is the largest prime number below 100?"}],
    model="openai/gpt-5-mini", # model name on OpenRouter
    llm_api_key=openrouter_key,
    provider="openrouter",
)

# Print the response
print(response)
```

## Requirements

- Python 3.11+

## License

Apache 2.0
epicsdev-tektronix 1.0.3
EPICS PVAccess server for Tektronix MSO oscilloscopes
Requires Python: >=3.7
Keywords: epics oscilloscope tektronix mso pvaccess scpi visa

# epicsdev_tektronix
This version 1.0.1 is correction of an AI-generated code, 
[generated by Git copilot](fallback/__main__.py).<br> 
Python-based EPICS PVAccess server for Tektronix MSO oscilloscopes (4, 5, and 6 Series).

It is based on [p4p](https://epics-base.github.io/p4p/) and [epicsdev](https://github.com/ASukhanov/epicsdev) packages 
and it can run standalone on Linux, OSX, and Windows platforms.

This implementation is adapted from [epicsdev_rigol_scope](https://github.com/ASukhanov/epicsdev_rigol_scope) 
and supports Tektronix MSO series oscilloscopes using SCPI commands as documented in the 
[Tektronix 4-5-6 Series MSO Programmer Manual](https://download.tek.com/manual/4-5-6-Series-MSO-Programmer_077130524.pdf).

## Installation
```pip install epicsdev_tektronix```

For control GUI and plotting:
```pip install pypeto,pvplot```

Control GUI:
```python -m pypeto -c path_to_repository/config -f epicsdev_tektronix```

## Features
- Support for Tektronix MSO oscilloscopes (configurable)
- Real-time waveform acquisition via EPICS PVAccess
- SCPI command interface for scope control
- Support for multiple trigger modes (AUTO, NORMAL, SINGLE)
- Configurable horizontal and vertical scales
- Channel-specific controls (coupling, offset, termination)
- Performance timing diagnostics

## Command-line Options
- `-c, --channels`: Number of channels per device (default: 4)
- `-d, --device`: Device name for PV prefix (default: 'tektronix')
- `-i, --index`: Device index for PV prefix (default: '0')
- `-r, --resource`: VISA resource string (default: 'TCPIP::192.168.1.100::INSTR')
- `-v, --verbose`: Increase verbosity (-vv for debug output)

## Example Usage
```bash
python -m epicsdev_tektronix.mso -r'TCPIP::192.168.1.100::4000:SOCKET'
```
Control GUI:
```python -m pypeto -c path_to_repository/config -f epicsdev_tektronix```

## Supported Tektronix Models
- MSO44, MSO46, MSO48 (4 Series)
- MSO54, MSO56, MSO58 (5 Series)
- MSO64 (6 Series)
- Other MSO series models using compatible SCPI commands

## Performance
Acquisition time of 6 channels, each with 1M of floating point values is 2.0 s. Throughput maxes out at 12 MB/s.
LLM-Bridge 1.15.16
A Bridge for LLMs
Requires Python: >=3.12
Keywords: ai, llm

# LLM Bridge

LLM Bridge is a unified API wrapper for native interactions with various LLM providers.

GitHub: [https://github.com/windsnow1025/LLM-Bridge](https://github.com/windsnow1025/LLM-Bridge)

PyPI: [https://pypi.org/project/LLM-Bridge/](https://pypi.org/project/LLM-Bridge/)

## Workflow and Features

1. **Message Preprocessor**: extracts text content from documents (Word, Excel, PPT, Code files, PDFs) which are not natively supported by the target model.
2. **Chat Client Factory**: creates a client for the specific LLM API with model parameters
    1. **Model Message Converter**: converts general messages to model messages
        1. **Media Processor**: converts general media (Image, Audio, Video, PDF) to model compatible formats.
3. **Chat Client**: generate stream or non-stream responses
    - **Model Thoughts**: captures the model's thinking process
    - **Code Execution**: generates and executes Python code
    - **Web Search**: generates response from search results
    - **Token Counter**: tracks and reports input and output token usage

### Supported Features for API Types

The features listed represent the maximum capabilities of each API type supported by LLM Bridge.

| API Type | Input Format                   | Capabilities                                            | Output Format     |
|----------|--------------------------------|---------------------------------------------------------|-------------------|
| OpenAI   | Text, Image, PDF               | Thinking, Web Search, Code Execution, Structured Output | Text, Image       |
| Gemini   | Text, Image, Video, Audio, PDF | Thinking, Web Search, Code Execution, Structured Output | Text, Image, File |
| Claude   | Text, Image, PDF               | Thinking, Web Search, Code Execution, Structured Output | Text, File        |
| Grok     | Text, Image                    |                                                         | Text              |

#### Planned Features

- More features for API Types
- Native support for Grok

## Development

### Python uv

1. Install uv: `powershell -ExecutionPolicy ByPass -c "irm https://astral.sh/uv/install.ps1 | iex"`
2. Install Python in uv: `uv python install 3.12`; upgrade Python in uv: `uv python upgrade 3.12`
3. Configure requirements:
  ```bash
  uv sync --refresh
  ```

### Pycharm

1. Add New Interpreter >> Add Local Interpreter
  - Environment: Select existing
  - Type: uv
2. Add New Configuration >> uv run >> Script: `./usage/main.py`

### Usage

Copy `./usage/.env.example` and rename it to `./usage/.env`, then fill in the environment variables.

### Build

```bash
uv build
```
bb-integrations-library 3.0.47.2
Provides common logic for all types of integration jobs.
Requires Python: >=3.11

# BB Integrations Library

A standard integrations library designed for **Gravitate** to manage and interact with various external services.

## Installation

Using pip:
```bash
pip install bb-integrations-library
```

Using uv:
```bash
uv add bb-integrations-library
```

## Usage

```python
import bb_integrations_lib
```