| Name | whiskerrag JSON |
| Version |
0.2.10
JSON |
| download |
| home_page | None |
| Summary | A utlity package for RAG operations |
| upload_time | 2025-07-22 12:28:34 |
| maintainer | None |
| docs_url | None |
| author | petercat.ai |
| requires_python | <4.0,>=3.9 |
| license | None |
| keywords |
|
| VCS |
|
| bugtrack_url |
|
| requirements |
No requirements were recorded.
|
| Travis-CI |
No Travis.
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| coveralls test coverage |
No coveralls.
|
# WhiskerRAG
[](https://choosealicense.com/licenses/mit/)
[](https://pypi.org/project/whiskerrag/)
[](https://badge.fury.io/py/whiskerrag)
[](https://codecov.io/gh/petercat-ai/whiskerrag_toolkit)
WhiskerRAG 是为 PeterCat 和 Whisker 项目开发的 RAG（Retrieval-Augmented Generation）工具包，提供完整的 RAG 相关类型定义和方法实现。
## 特性
- 针对通用 RAG 的领域建模类型, 包括任务（Task）、知识（Knowledge）、分段(Chunk)、租户(Tenant)、知识库空间(Space)。
- Whisker rag 插件接口描述。
- Github 仓库、S3 资源管理器。
## 安装
使用 pip 安装：
```bash
pip install whiskerrag
```
## 快速开始
whiskerrag 包含三个子模块，分别是 whiskerrag_utils、whiskerrag_client、whiskerrag_types。它们分别有不同的用途：
### whiskerrag_utils
包含了构建 RAG 系统的常用方法：
```python
from whiskerrag_utils import loader,embedding,retriever
```
### whiskerrag_client
将 RAG 系统服务通过 python sdk 的形式向外暴露。
```python
from whiskerrag_client import APIClient
api_client = APIClient(
base_url="https://api.example.com",
token="your_token_here"
)
knowledge_chunks = await api_client.retrieval.retrieve_knowledge_content(
RetrievalByKnowledgeRequest(knowledge_id="your knowledge uuid here")
)
space_chunks = await api_client.retrieval.retrieve_space_content(
RetrievalBySpaceRequest(space_id="your space id here ")
)
chunk_list = await api_client.chunk.get_chunk_list(
page=1,
size=10,
filters={"status": "active"}
)
task_list = await api_client.task.get_task_list(
page=1,
size=10
)
task_detail = await api_client.task.get_task_detail("task_id_here")
```
### whiskerrag_types
一些辅助开发的类型提示，接口；
```python
from whiskerrag_types.interface import DBPluginInterface, TaskEngineInterface
from whiskerrag_types.model import Knowledge, Task, Tenant, PageParams, PageResponse
```
## 开发者指南
### 环境初始化
1. 克隆项目
```bash
git clone https://github.com/petercat-ai/whiskerrag_toolkit.git
cd whiskerrag_toolkit
```
2. 创建并激活虚拟环境
```bash
# 查看poetry配置
poetry config --list
# 修改 poetry 配置
poetry config virtualenvs.create true
poetry config virtualenvs.in-project true
poetry env use python3.10
# 激活虚拟环境
source .venv/bin/activate
```
3. 安装依赖
```bash
# 安装项目依赖
poetry install
# 安装 pre-commit 工具
pre-commit install
```
4. 运行测试
```bash
# 运行所有测试
poetry run pytest
# 运行指定测试文件
poetry run pytest tests/test_loader.py
```
4. poetry 常用命令
```bash
# 安装依赖
poetry install
# 添加新依赖
poetry add package_name
# 添加新 dev 依赖
poetry add --dev package_name
# 更新依赖
poetry update
# 查看环境信息
poetry env info
# 查看已安装的包
poetry show
```
### 开发工作流
1. 创建新分支
2. 开发新功能，补充单元测试，确保代码质量。注意，请确保单元测试覆盖率不低于 80%。
3. 提交代码，并创建 Pull Request。
4. 等待代码审查，并根据反馈进行修改。
5. 合并 Pull Request。
## 项目结构
```
whiskerRAG-toolkit/
├── src/
│ ├── whiskerrag_utils/
│ └── whiskerrag_types/
│ └── whiskerrag_client/
└── pyproject.toml
```
## 贡献指南
1. Fork 本仓库
2. 创建特性分支 (`make branch name=feature/amazing-feature`)
3. 提交更改 (`git commit -m 'Add some amazing feature'`)
4. 推送到分支 (`git push origin feature/amazing-feature`)
5. 开启 Pull Request
## 许可证
本项目采用 MIT 许可证 - 查看 [LICENSE](LICENSE) 文件了解详情
## 联系方式
项目维护者 - [@petercat-ai](https://github.com/petercat-ai)
项目链接：[https://github.com/petercat-ai/whiskerrag_toolkit](https://github.com/your-username/whiskerrag_toolkit)
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"description": "# WhiskerRAG\n\n[](https://choosealicense.com/licenses/mit/)\n[](https://pypi.org/project/whiskerrag/)\n[](https://badge.fury.io/py/whiskerrag)\n[](https://codecov.io/gh/petercat-ai/whiskerrag_toolkit)\n\nWhiskerRAG \u662f\u4e3a PeterCat \u548c Whisker \u9879\u76ee\u5f00\u53d1\u7684 RAG\uff08Retrieval-Augmented Generation\uff09\u5de5\u5177\u5305\uff0c\u63d0\u4f9b\u5b8c\u6574\u7684 RAG \u76f8\u5173\u7c7b\u578b\u5b9a\u4e49\u548c\u65b9\u6cd5\u5b9e\u73b0\u3002\n\n## \u7279\u6027\n\n- \u9488\u5bf9\u901a\u7528 RAG \u7684\u9886\u57df\u5efa\u6a21\u7c7b\u578b, \u5305\u62ec\u4efb\u52a1\uff08Task\uff09\u3001\u77e5\u8bc6\uff08Knowledge\uff09\u3001\u5206\u6bb5(Chunk)\u3001\u79df\u6237(Tenant)\u3001\u77e5\u8bc6\u5e93\u7a7a\u95f4(Space)\u3002\n- Whisker rag \u63d2\u4ef6\u63a5\u53e3\u63cf\u8ff0\u3002\n- Github \u4ed3\u5e93\u3001S3 \u8d44\u6e90\u7ba1\u7406\u5668\u3002\n\n## \u5b89\u88c5\n\n\u4f7f\u7528 pip \u5b89\u88c5\uff1a\n\n```bash\npip install whiskerrag\n```\n\n## \u5feb\u901f\u5f00\u59cb\n\nwhiskerrag \u5305\u542b\u4e09\u4e2a\u5b50\u6a21\u5757\uff0c\u5206\u522b\u662f whiskerrag_utils\u3001whiskerrag_client\u3001whiskerrag_types\u3002\u5b83\u4eec\u5206\u522b\u6709\u4e0d\u540c\u7684\u7528\u9014\uff1a\n\n### whiskerrag_utils\n\n\u5305\u542b\u4e86\u6784\u5efa RAG \u7cfb\u7edf\u7684\u5e38\u7528\u65b9\u6cd5\uff1a\n\n```python\nfrom whiskerrag_utils import loader,embedding,retriever\n```\n\n### whiskerrag_client\n\n\u5c06 RAG \u7cfb\u7edf\u670d\u52a1\u901a\u8fc7 python sdk \u7684\u5f62\u5f0f\u5411\u5916\u66b4\u9732\u3002\n\n```python\nfrom whiskerrag_client import APIClient\n\napi_client = APIClient(\n base_url=\"https://api.example.com\",\n token=\"your_token_here\"\n)\n\nknowledge_chunks = await api_client.retrieval.retrieve_knowledge_content(\n RetrievalByKnowledgeRequest(knowledge_id=\"your knowledge uuid here\")\n)\n\nspace_chunks = await api_client.retrieval.retrieve_space_content(\n RetrievalBySpaceRequest(space_id=\"your space id here \")\n)\n\nchunk_list = await api_client.chunk.get_chunk_list(\n page=1,\n size=10,\n filters={\"status\": \"active\"}\n)\n\ntask_list = await api_client.task.get_task_list(\n page=1,\n size=10\n)\n\ntask_detail = await api_client.task.get_task_detail(\"task_id_here\")\n```\n\n### whiskerrag_types\n\n\u4e00\u4e9b\u8f85\u52a9\u5f00\u53d1\u7684\u7c7b\u578b\u63d0\u793a\uff0c\u63a5\u53e3\uff1b\n\n```python\nfrom whiskerrag_types.interface import DBPluginInterface, TaskEngineInterface\nfrom whiskerrag_types.model import Knowledge, Task, Tenant, PageParams, PageResponse\n```\n\n## \u5f00\u53d1\u8005\u6307\u5357\n\n### \u73af\u5883\u521d\u59cb\u5316\n\n1. \u514b\u9686\u9879\u76ee\n\n```bash\ngit clone https://github.com/petercat-ai/whiskerrag_toolkit.git\ncd whiskerrag_toolkit\n```\n\n2. \u521b\u5efa\u5e76\u6fc0\u6d3b\u865a\u62df\u73af\u5883\n\n```bash\n# \u67e5\u770bpoetry\u914d\u7f6e\npoetry config --list\n\n# \u4fee\u6539 poetry \u914d\u7f6e\npoetry config virtualenvs.create true\npoetry config virtualenvs.in-project true\n\npoetry env use python3.10\n\n# \u6fc0\u6d3b\u865a\u62df\u73af\u5883\nsource .venv/bin/activate\n```\n\n3. \u5b89\u88c5\u4f9d\u8d56\n\n```bash\n# \u5b89\u88c5\u9879\u76ee\u4f9d\u8d56\npoetry install\n# \u5b89\u88c5 pre-commit \u5de5\u5177\npre-commit install\n```\n\n4. \u8fd0\u884c\u6d4b\u8bd5\n\n```bash\n# \u8fd0\u884c\u6240\u6709\u6d4b\u8bd5\npoetry run pytest\n# \u8fd0\u884c\u6307\u5b9a\u6d4b\u8bd5\u6587\u4ef6\npoetry run pytest tests/test_loader.py\n```\n\n4. poetry \u5e38\u7528\u547d\u4ee4\n\n```bash\n# \u5b89\u88c5\u4f9d\u8d56\npoetry install\n\n# \u6dfb\u52a0\u65b0\u4f9d\u8d56\npoetry add package_name\n\n# \u6dfb\u52a0\u65b0 dev \u4f9d\u8d56\npoetry add --dev package_name\n\n# \u66f4\u65b0\u4f9d\u8d56\npoetry update\n\n# \u67e5\u770b\u73af\u5883\u4fe1\u606f\npoetry env info\n\n# \u67e5\u770b\u5df2\u5b89\u88c5\u7684\u5305\npoetry show\n```\n\n### \u5f00\u53d1\u5de5\u4f5c\u6d41\n\n1. \u521b\u5efa\u65b0\u5206\u652f\n2. \u5f00\u53d1\u65b0\u529f\u80fd\uff0c\u8865\u5145\u5355\u5143\u6d4b\u8bd5\uff0c\u786e\u4fdd\u4ee3\u7801\u8d28\u91cf\u3002\u6ce8\u610f\uff0c\u8bf7\u786e\u4fdd\u5355\u5143\u6d4b\u8bd5\u8986\u76d6\u7387\u4e0d\u4f4e\u4e8e 80%\u3002\n3. \u63d0\u4ea4\u4ee3\u7801\uff0c\u5e76\u521b\u5efa Pull Request\u3002\n4. \u7b49\u5f85\u4ee3\u7801\u5ba1\u67e5\uff0c\u5e76\u6839\u636e\u53cd\u9988\u8fdb\u884c\u4fee\u6539\u3002\n5. \u5408\u5e76 Pull Request\u3002\n\n## \u9879\u76ee\u7ed3\u6784\n\n```\nwhiskerRAG-toolkit/\n\u251c\u2500\u2500 src/\n\u2502 \u251c\u2500\u2500 whiskerrag_utils/\n\u2502 \u2514\u2500\u2500 whiskerrag_types/\n\u2502 \u2514\u2500\u2500 whiskerrag_client/\n\u2514\u2500\u2500 pyproject.toml\n```\n\n## \u8d21\u732e\u6307\u5357\n\n1. 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