semvec/pypi-packages huggingface dataset:
bsv-language-server 0.1.0
A Language Server for Bluespec SystemVerilog
Requires Python: >=3.10

# Bluespec Language Server.

* Uses bsc for linting.
* Uses tree-sitter for Completion on `.`,`{` and `(` character

![See it in action](images/output.gif)

## Installation
```
pip install bsv-language-server
```
The language server searches upwards from the current folder for for a .bscflags file for setting to use for compilation
The tree-sitter parser is not complete, it currently parses most typedef enum/struct,  interfaces module instantation and assignment statements and fails on everything else. This subset should be enough for type completion.


## How to use

In your project hierarchy create a file `.bscflags` with compile time options e.g. .bscflags
 ```
-p /prj/bsvlib/bdir:bo:+
-bdir bo
-info-dir bo
```

### VIM
In your .vimrc
Add the following plugins e.g. using Vundle
```
Plugin 'prabirshrestha/vim-lsp'
Plugin 'prabirshrestha/asyncomplete.vim'
Plugin 'prabirshrestha/asyncomplete-lsp.vim'
".... other vundle stuff
 if executable('bsv_language_server')
     au User lsp_setup call lsp#register_server({
         \ 'name': 'bsv_language_server',
         \ 'cmd': {server_info->['bsv_language_server']},
         \ 'allowlist': ['bsv'],
         \ 'workspace_config': {
         \   'bluespec': {
         \     'compilerFlags': ['-p', '+:/prj/bsvlib/bdir:bo', '-check']
         \   }
         \ }
     \ })
 endif
 ```
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ginkgo-tools-redis 0.1.1
对redis做了再封装，常规的redis操作和向量操作都做了简化，方便使用
Requires Python: >=3.11
Keywords: tools, redis

# GINKGO-TOOLS-REDIS

对 Redis 进行再封装的工具库，简化了常规的 Redis 操作和向量操作，便于使用。

## 功能特性

- **Redis 向量数据库操作**：支持向量索引创建、KNN 相似性搜索、范围搜索
- **标签过滤查询**：支持基于标签的查询功能
- **模块化架构**：基于 [RedisManager](file://D:\Python_Project\#工具脚本\GINKGO-TOOLS-REDIS\redis_ops.py#L5-L23) 的封装设计
- **向后兼容**：保持与旧版 API 的兼容性
- **简化操作**：提供简化的 Redis 操作接口

## 安装

```bash
pip install ginkgo-tools-redis
```

## 快速开始

```python
from ginkgo_tools_redis import RedisOps

# 创建 Redis 连接实例
redis_ops = RedisOps(host="127.0.0.1", port=6379, db=0)

# 使用向量数据库功能
# 示例：创建向量索引、执行 KNN 搜索等
```

## API 说明

### RedisOps 类

[RedisOps](file://D:\Python_Project\#工具脚本\GINKGO-TOOLS-REDIS\redis_ops.py#L5-L23) 类继承自 [RedisManager](file://D:\Python_Project\#工具脚本\GINKGO-TOOLS-REDIS\redis_manager.py#L4-L123)，提供以下功能：

- 向量索引创建
- 标签过滤查询
- KNN 相似性搜索
- 范围搜索
- 保持与旧版 API 的兼容性

## 依赖

- `ginkgo-tools>=0.1.4`
- `redis[hiredis]==5.0.1`
- Python >= 3.11

## 许可证

MIT License

## 贡献

欢迎提交 Issue 和 Pull Request 来改进此项目。
faq-rai-sdk 0.1.4
RAI Package contains a Prompt Reviewer and Updater and test case generator for faster Copilot Development
Requires Python: <3.13,>=3.10
Keywords: ai, copilot, prompt, testing, rai, agent

# MAQ RAI SDK

RAI Package contains a Prompt Reviewer and Updater and test case generator for faster Copilot Development.

## Installation

```bash
pip install faq-rai-sdk
```

## Quick Start

```python
from faq_rai_sdk import MAQRAISDK

# Initialize the SDK
client = MAQRAISDK(
    # Add your configuration here
)

# Use the SDK for prompt review, updates, and test case generation
# Add usage examples here
```

## Features

- **Prompt Reviewer**: Analyze and review AI prompts for quality and effectiveness
- **Prompt Updater**: Update and optimize prompts for better results
- **Test Case Generator**: Automatically generate test cases for faster Copilot development
- **AI-Powered**: Leverages CrewAI tools for intelligent processing

## Requirements

- Python 3.10, 3.11, or 3.12
- crewai[tools] 0.120.1
- PyYAML 6.0.2
- onnxruntime 1.22.0

## Documentation

For detailed documentation, please visit the [GitHub repository](https://github.com/MAQ-Software-Solutions/maqraisdk).

## Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

## License

This project is licensed under the MIT License - see the LICENSE file for details.

## Author

**Lalit Gour**  
MAQ Software  
Email: lalitg@maqsoftware.com

## Support

For issues and questions, please open an issue on the [GitHub repository](https://github.com/MAQ-Software-Solutions/maqraisdk/issues).

## Keywords

AI, Copilot, Prompt Testing, RAI, Agent, Prompt Engineering