semvec/pypi-packages huggingface dataset:
isage-eval 0.1.0.1
SAGE Evaluation Framework - Metrics, profilers, and judges for AI systems
Requires Python: >=3.10
Keywords: evaluation, metrics, profiler, judge, LLM, AI

# sage-eval

**SAGE 平台专用评估工具库** - L3 纯算法库，提供评估指标、性能分析器与 LLM 评审工具。

**PyPI**: `isage-eval`  
**Import**: `sage_eval`  
**Layer**: L3 (Algorithm Library)

> ⚠️ **注意**: 这是评估**工具库**，不是 benchmark。Benchmark 项目请参考 [sage-benchmark](https://github.com/intellistream/sage-benchmark) 及相关仓库。

## 功能模块

### 📊 评估指标 (Metrics)
- **文本指标**: F1 Score, Exact Match, BLEU, ROUGE
- **分类指标**: Precision, Recall, Accuracy
- **检索指标**: Recall@K, MRR, NDCG

### ⚡ 性能分析 (Profiler)
- **延迟分析**: LatencyProfiler
- **内存分析**: MemoryProfiler
- **吞吐量分析**: ThroughputProfiler

### 🤖 LLM 评审 (Judge)
- **点式评估**: PointwiseJudge
- **对比评估**: PairwiseJudge

## Installation
```bash
pip install isage-eval
```

## Quick Start

```python
from sage_eval import F1Score, ROUGE, LatencyProfiler, PointwiseJudge

# 计算 F1 分数
f1 = F1Score()
score = f1.compute(predictions, references)

# 性能分析
profiler = LatencyProfiler()
with profiler.measure("task_name"):
    # 执行操作
    pass
report = profiler.report()

# LLM 评审
judge = PointwiseJudge(model="gpt-4")
score = judge.evaluate(
    question="What is Python?",
    answer="Python is a programming language."
)
```

## Integration with SAGE

本包作为独立的 L3 算法库，可以单独使用或集成到 SAGE 框架中。在 SAGE 框架中，接口层位于 `sage.libs.eval`，本包通过 `_register.py` 自动注册实现。

## License
Apache 2.0
types-icalendar 6.3.2.20260213
Typing stubs for icalendar
Requires Python: >=3.10

## Typing stubs for icalendar

This is a [type stub package](https://typing.python.org/en/latest/tutorials/external_libraries.html)
for the [`icalendar`](https://github.com/collective/icalendar) package. It can be used by type checkers
to check code that uses `icalendar`. This version of
`types-icalendar` aims to provide accurate annotations for
`icalendar==6.3.2`.

*Note:* The `icalendar` package includes type annotations or type stubs
since version 7.0.0. Please uninstall the `types-icalendar`
package if you use this or a newer version.


This package is part of the [typeshed project](https://github.com/python/typeshed).
All fixes for types and metadata should be contributed there.
See [the README](https://github.com/python/typeshed/blob/main/README.md)
for more details. The source for this package can be found in the
[`stubs/icalendar`](https://github.com/python/typeshed/tree/main/stubs/icalendar)
directory.

This package was tested with the following type checkers:
* [mypy](https://github.com/python/mypy/) 1.19.1
* [pyright](https://github.com/microsoft/pyright) 1.1.408

It was generated from typeshed commit
[`da3de3ac0950f967d63a97a2d27de2ab8c1f4fa3`](https://github.com/python/typeshed/commit/da3de3ac0950f967d63a97a2d27de2ab8c1f4fa3).
types-django-filter 25.2.0.20260213
Typing stubs for django-filter
Requires Python: >=3.10

## Typing stubs for django-filter

This is a [type stub package](https://typing.python.org/en/latest/tutorials/external_libraries.html)
for the [`django-filter`](https://github.com/carltongibson/django-filter/) package. It can be used by type checkers
to check code that uses `django-filter`. This version of
`types-django-filter` aims to provide accurate annotations for
`django-filter==25.2.*`.

This package is part of the [typeshed project](https://github.com/python/typeshed).
All fixes for types and metadata should be contributed there.
See [the README](https://github.com/python/typeshed/blob/main/README.md)
for more details. The source for this package can be found in the
[`stubs/django-filter`](https://github.com/python/typeshed/tree/main/stubs/django-filter)
directory.

This package was tested with the following type checkers:
* [mypy](https://github.com/python/mypy/) 1.19.1
* [pyright](https://github.com/microsoft/pyright) 1.1.408

It was generated from typeshed commit
[`da3de3ac0950f967d63a97a2d27de2ab8c1f4fa3`](https://github.com/python/typeshed/commit/da3de3ac0950f967d63a97a2d27de2ab8c1f4fa3).
osis-python 0.1.9
A Python client library for Osis APDL
Requires Python: >=3.11

[简体中文](README.zh-CN.md) | [English](README.md)

# pyosis

Python client library for OSIS Bridge Analysis Platform

## Installation

Due to naming conflicts on PyPI, please install using:

```bash
pip install osis-python
```

If your mirror hasn't synced yet, use:

```bash
pip install osis-python -i https://pypi.org/simple
```

## Usage

First, install the latest version of OSIS (>=5.0) and configure the Python environment variables. pyosis requires Python 3.11 or higher. You need to set PYTHONHOME in the environment variables to your Python installation directory, e.g., C:\Program Files\python, and set PYTHONIOENCODING to utf-8. Then add %PYTHONHOME% and %PYTHONHOME%\Scripts to the Path variable.

Your scripts should be placed in the python folder under the OSIS installation directory, e.g., C:\Program Files\osis\python. Suppose there is a script named test_osis.py with the following content:


```python
import json
from pyosis.core import osis_run    # Import required functions
from pyosis.control import *
from pyosis.general import *
from pyosis.section import *
from pyosis.material import *
from pyosis.node import *
from pyosis.element import *
from pyosis.boundary import *
from pyosis.load import *
from pyosis.post import *

osis_clear()

osis_acel(9.8066)
osis_calc_tendon(1)
osis_calc_con_force(1)
osis_calc_shrink(1)
osis_calc_creep(1)
osis_calc_shear(1)
osis_calc_rlx(1)
osis_mod_loc_coor(0)
osis_inc_tendon(1)
osis_nl(0, 0)
osis_ln_srch(0)
osis_auto_ts(0)
osis_mod_opt(0)

osis_section_circle(1, "Circle Section 1", "CIRCLE", "Hollow", 0.219, 0.012)
osis_section_circle(2, "Circle Section 2", "CIRCLE", "Hollow", 0.180, 0.008)
osis_section_circle(3, "Circle Section 3", "CIRCLE", "Hollow", 0.114, 0.005)
osis_section_circle(4, "Circle Section 4", "CIRCLE", "Hollow", 0.089, 0.004)
osis_section_circle(5, "Circle Section 5", "CIRCLE", "Hollow", 0.045, 0.003)

osis_material_steel(1, "Steel 1", "STEEL", "JTGD64_2015", "Q345", 0.05)

# Fixed nodes (x, y units: m)
osis_node(1, 0, 5, 0)
osis_node(2, 15, 5, 0)
# Load application nodes
osis_node(3, 7.5, 0, 0)
osis_node(4, 20, 0, 0)

osis_element_beam3d(1, "BEAM3D", 1, 3, 1, 4, 4, 1, 1, 0.00, 0, 0.00, 0)
osis_element_beam3d(2, "BEAM3D", 2, 3, 1, 5, 5, 1, 1, 0.00, 0, 0.00, 0)
osis_element_beam3d(3, "BEAM3D", 2, 4, 1, 5, 5, 1, 1, 0.00, 0, 0.00, 0)
osis_element_beam3d(4, "BEAM3D", 3, 4, 1, 5, 5, 1, 1, 0.00, 0, 0.00, 0)

osis_boundary_general(1, "GENERAL", "", 1, 1, 1, 1, 1, 1, 1)
osis_assign_boundary(1, "a", [1, 2])

osis_loadcase("Custom Load Case 1", "USER", 1, "Two forces applied at nodes 3 and 4")
osis_load_nforce("NFORCE", "Custom Load Case 1", 3, 0, -1000000, 0, 0, 0, 0)
osis_load_nforce("NFORCE", "Custom Load Case 1", 4, 200000, 0, 0, 0, 0, 0)

# osis_solve()

print(osis_run())      # Let OSIS execute all preprocessing commands

```

Select and run this script in OSIS. If everything is normal, you will see OSIS finish the preprocessing.
vscotero 0.2.2
VSCode + Zotero literature note ingester
Requires Python: >=3.10

## vscotero

Generate markdown literature notes from your Zotero library (metadata + annotations) for use in VS Code (Foam / wiki links compatible).

![demonstration of vscotero usage](demo.gif)

### Features

- Extract item metadata from a Zotero auto‑exported BibTeX file
- Pull PDF annotations directly from the Zotero `zotero.sqlite` database
- Group annotations by highlight color (configurable colormap)

### Recommended installation: pip

```bash
pip install vscotero
```

Then configure Zotero to auto-export a BibTeX file (Better BibTeX recommended) and create a `config.toml` file (see example below).

### Example `config.toml`
```toml
[notes]
bib_path = "/absolute/path/to/library.bib"   # Zotero auto-export (Better BibTeX)
md_path  = "/absolute/path/to/notes"         # Output folder for generated notes
db_path  = "~/Zotero/zotero.sqlite"           # Zotero database path
```

### Usage
Ingest all notes:
```bash
vscotero ingest --path config.toml
```

### Color Map
Override in `config.toml` (any subset):
```toml
[notes.colormap]
"#ffd400" = "Insights"
"#ff6666" = "Discrepancies"
```

See `CHANGELOG.md` for release notes.

#### Build from source

```bash
git clone https://github.com/katnykiel/vscotero
cd vscotero
python -m venv .venv
source .venv/bin/activate
pip install -e .
```

### TODOs

- fix the config system
  - add CLI option, put config.toml in some default path
  - remove .bib path? doesn't db have this info
- confirmation prompt before deletion
- check if it overwrites notes (it does, fix)
- add color hex codes to default config.toml with description
- error handling
- better tests for edge cases / bad config
- add a nix install
iflow-mcp_sligter-mcp_newsnow 0.1.4
MCP server for multi-platform hottest news
Requires Python: >=3.10

[![MseeP.ai Security Assessment Badge](https://mseep.net/pr/sligter-mcp-newsnow-badge.png)](https://mseep.ai/app/sligter-mcp-newsnow)

# MCP NewNow Server

[![MCP Compatible](https://img.shields.io/badge/MCP-Compatible-blue)](https://github.com/anthropics/anthropic-tools)

一个基于 Model Context Protocol (MCP) 的新闻聚合服务器，通过 [Newsnow](https://github.com/ourongxing/newsnow) API 提供多平台热点新闻和趋势话题。

## 功能特点

- **多平台热点聚合**：一站式获取来自酷安、知乎、微博、B站、抖音、GitHub等14+平台的热点内容
- **中英文源名识别**：支持中英文新闻源名称，并提供模糊匹配功能
- **自定义API端点**：通过环境变量或命令行参数配置NewNow API端点


## 安装方法

### 方法一：从 PyPI 安装

```bash
# 使用 pip 安装
pip install mcp-newsnow

# 或使用 uv 安装
uv pip install mcp-newsnow
```

### 方法二：配置 Claude Desktop

在 Claude Desktop 配置文件中添加服务器配置：

**macOS**: `~/Library/Application Support/Claude/claude_desktop_config.json`  
**Windows**: `%APPDATA%\Claude\claude_desktop_config.json`

添加以下配置：

```json
{
  "mcpServers": {
    "get_news": {
      "command": "uvx",
      "args": [
        "mcp-newsnow"
      ]
    }
  }
}
```

## 使用方法

### 使用 Claude Desktop

1. 安装并配置 Claude Desktop
2. 在配置文件中添加上述 MCP 服务器配置
3. 重启 Claude Desktop
4. 在对话中使用新闻相关工具

### 使用 MCP CLI 进行开发

```bash
# 通过环境变量设置API端点
NEWS_API_URL=https://newsnow.example.com

# 运行测试
mcp test server.py
```

## 可用工具

### 1. 获取单一源新闻 (get_newsnow)

```python
async def get_newsnow(source: str) -> dict[str, Any] | None
```

从指定源获取最新新闻。

**参数**:
- `source`: 新闻源名称 (支持中英文，例如"知乎"、"zhihu"、"B站"等)

**返回**: 包含新闻数据的字典

### 2. 获取多源新闻 (get_multi_news)

```python
async def get_multi_news(sources: list[str] = None) -> dict[str, Any]
```

从多个源获取最新新闻 (最多5个)。

**参数**:
- `sources`: 新闻源名称列表

**返回**: 包含多个新闻源数据的字典

### 3. 获取所有源新闻 (get_all_news)

```python
async def get_all_news() -> dict[str, Any]
```

获取所有配置的新闻源数据。

**返回**: 包含所有新闻源数据和元数据的字典

### 4. 列出可用新闻源 (list_sources)

```python
async def list_sources() -> dict[str, str]
```

列出所有可用的新闻源及其中文名称。

**返回**: 新闻源ID到中文名称的映射字典

## 环境变量

- `NEWS_API_URL`: Newsnow API的基础URL (默认: "https://newsnow.busiyi.world/")

## 支持的新闻源

- 酷安 (coolapk)
- B站热搜 (bilibili-hot-search)
- 知乎 (zhihu)
- 微博 (weibo)
- 今日头条 (toutiao)
- 抖音 (douyin)
- GitHub趋势 (github-trending-today)
- Linux热榜 (linuxdo-hot)
- 贴吧 (tieba)
- 华尔街见闻 (wallstreetcn)
- 澎湃新闻 (thepaper)
- 财联社 (cls-hot)
- 雪球 (xueqiu)
- 快手 (kuaishou)

## 贡献指南

欢迎提交问题和拉取请求！以下是一些潜在的改进方向：

- 添加更多新闻源支持
- 增强内容提取和处理能力
- 添加缓存层减少API调用
- 改进错误处理和重试机制
- 添加结果过滤和分类功能

## 许可证

本项目采用 MIT 许可证。