Skip to content

Commit c547c1c

Browse files
Fu-JieFu-Jie
committed
docs: fix broken relative links in example cases to resolve mkdocs build warnings
1 parent b04112a commit c547c1c

4 files changed

Lines changed: 48 additions & 20 deletions

File tree

‎docs/plugins/pipes/star-prediction-example.md‎

Lines changed: 12 additions & 5 deletions
Original file line numberDiff line numberDiff line change
@@ -16,39 +16,46 @@ This case study demonstrates how to use the **GitHub Copilot SDK Pipe** with the
1616

1717
- **Plugin Type**: Pipe (GitHub Copilot SDK)
1818
- **Base Model**: Minimax 2.1 (via Pipe integration)
19-
- **Key Capabilities**:
20-
- **File Processing**: Automatically reads and parses multiple CSV data files.
21-
- **Code Generation & Execution**: On-the-fly Python scripting to calculate growth rates, conversion rates, and median trends.
22-
- **Multimodal Output**: Generates Markdown reports, interactive HTML dashboards, and Mermaid timeline charts.
19+
- **Key Capabilities**:
20+
- **File Processing**: Automatically reads and parses multiple CSV data files.
21+
- **Code Generation & Execution**: On-the-fly Python scripting to calculate growth rates, conversion rates, and median trends.
22+
- **Multimodal Output**: Generates Markdown reports, interactive HTML dashboards, and Mermaid timeline charts.
2323

2424
---
2525

2626
## 💬 Conversation Highlights
2727

2828
### 📥 Import Conversation
29+
2930
You can download the raw chat data and import it into your Open WebUI to see the full tool calls and analysis logic:
3031
[:material-download: Download Chat JSON](./star-prediction-chat.json)
3132

3233
> **How to Import?**
3334
> In Open WebUI, click your **User Avatar** (bottom of left sidebar) -> **Settings** -> **Data** -> **Import Chats**, then select the downloaded file.
3435
3536
### 1. Data Submission
37+
3638
The **User** provided traffic source distribution and uploaded:
39+
3740
- `Unique visitors in last 14 days.csv`
3841
- `Total views in last 14 days.csv`
3942
- `star-history.csv`
4043

4144
### 2. Analysis Execution
45+
4246
**Minimax 2.1** received the data and immediately formulated an analysis plan:
47+
4348
1. Calculate star growth trajectory and rates.
4449
2. Analyze visitor-to-star conversion rates.
4550
3. Build linear and median projection models.
4651
4. Generate a milestone timeline.
4752

4853
### 3. Report Generation
54+
4955
The model produced a comprehensive report. Here are the core projections:
5056

5157
#### 🎯 Key Projections
58+
5259
| Metric | Value | Insight |
5360
| :--- | :--- | :--- |
5461
| **Current Stars** | 62 | 62% of the goal reached |
@@ -88,4 +95,4 @@ gantt
8895

8996
---
9097

91-
> [View GitHub Copilot SDK Pipe Source Code](../../../plugins/pipes/github-copilot-sdk/README.md)
98+
> [View GitHub Copilot SDK Pipe Documentation](./github-copilot-sdk.md)

‎docs/plugins/pipes/star-prediction-example.zh.md‎

Lines changed: 12 additions & 5 deletions
Original file line numberDiff line numberDiff line change
@@ -16,39 +16,46 @@
1616

1717
- **插件类型**: Pipe (GitHub Copilot SDK)
1818
- **底层模型**: Minimax 2.1 (通过 Pipe 接入)
19-
- **核心能力**:
20-
- **文件处理**: 自动读取并解析多份 CSV 数据文件。
21-
- **代码生成与执行**: 现场编写 Python 分析代码并执行，计算增长率、转化率及中位趋势。
22-
- **多模态输出**: 生成 Markdown 报告、HTML 交互看板以及 Mermaid 时间轴图表。
19+
- **核心能力**:
20+
- **文件处理**: 自动读取并解析多份 CSV 数据文件。
21+
- **代码生成与执行**: 现场编写 Python 分析代码并执行，计算增长率、转化率及中位趋势。
22+
- **多模态输出**: 生成 Markdown 报告、HTML 交互看板以及 Mermaid 时间轴图表。
2323

2424
---
2525

2626
## 💬 对话实录
2727

2828
### 📥 导入对话记录
29+
2930
你可以下载原始对话数据并导入到你的 Open WebUI 中，查看完整的工具调用和分析逻辑：
3031
[:material-download: 下载原始对话 JSON](./star-prediction-chat.json)
3132

3233
> **如何导入？**
3334
> 在 Open WebUI 首页点击 **左侧侧边栏底部个人头像** -> **设置** -> **数据** -> **导入记录**，选择下载的文件即可。
3435
3536
### 1. 提交原始数据
37+
3638
**用户**提供了项目的流量来源分布表，并上传了：
39+
3740
- `Unique visitors in last 14 days.csv`
3841
- `Total views in last 14 days.csv`
3942
- `star-history.csv`
4043

4144
### 2. 模型执行分析
45+
4246
**Minimax 2.1** 接收到数据后，立即制定了分析计划：
47+
4348
1. 计算 Star 增长轨迹和增长率。
4449
2. 分析访问者到 Star 的转化率。
4550
3. 构建线性与中位增长模型进行预测。
4651
4. 生成里程碑时间轴。
4752

4853
### 3. 生成分析报告
54+
4955
模型输出了一份详尽的报告，以下是其核心预测：
5056

5157
#### 🎯 关键预测结果
58+
5259
| 指标 | 数值 | 洞察 |
5360
| :--- | :--- | :--- |
5461
| **当前 Star 数** | 62 | 已完成目标的 62% |
@@ -88,4 +95,4 @@ gantt
8895

8996
---
9097

91-
> [查看 GitHub Copilot SDK Pipe 源码](../../../plugins/pipes/github-copilot-sdk/README.md)
98+
> [查看 GitHub Copilot SDK Pipe 开发文档](./github-copilot-sdk.zh.md)

‎docs/plugins/pipes/video-processing-example.md‎

Lines changed: 12 additions & 5 deletions
Original file line numberDiff line numberDiff line change
@@ -16,33 +16,38 @@ This case study demonstrates how to use the **GitHub Copilot SDK Pipe** with **M
1616

1717
- **Plugin Type**: Pipe (GitHub Copilot SDK)
1818
- **Base Model**: Minimax 2.1
19-
- **Key Capabilities**:
20-
- **System Tool Access**: Automatically detects and invokes `ffmpeg` within the container.
21-
- **Two-Pass Optimization**:
19+
- **Key Capabilities**:
20+
- **System Tool Access**: Automatically detects and invokes `ffmpeg` within the container.
21+
- **Two-Pass Optimization**:
2222
1. **Pass 1**: Analyzes all frames to generate a custom 256-color palette (`palettegen`).
2323
2. **Pass 2**: Applies the palette for superior quantization and dithering (`paletteuse`).
24-
- **Precision Parameters**: Implements 1.4x PTS scaling, Lanczos scaling, and 20fps rate control.
24+
- **Precision Parameters**: Implements 1.4x PTS scaling, Lanczos scaling, and 20fps rate control.
2525

2626
---
2727

2828
## 💬 Conversation Highlights
2929

3030
### 📥 Import Conversation
31+
3132
You can download the raw chat data and import it into your Open WebUI to see how the model debugs and optimizes the FFmpeg parameters:
3233
[:material-download: Download Chat JSON](./video-processing-chat.json)
3334

3435
> **How to Import?**
3536
> In Open WebUI, click your **User Avatar** (bottom of left sidebar) -> **Settings** -> **Data** -> **Import Chats**, then select the downloaded file.
3637
3738
### 1. Processing Requirements
39+
3840
The **User** provided an input file and specific parameters:
41+
3942
- Speed: 1.4x (setpts=PTS/1.4)
4043
- Resolution: 1280px width, auto height
4144
- Optimization: Must use palette generation technology
4245
- Constraint: File size < 20MB
4346

4447
### 2. Analysis Execution
48+
4549
**Minimax 2.1** generated and executed the following core logic:
50+
4651
```bash
4752
# Pass 1: Generate optimal palette
4853
ffmpeg -i input.mov -vf "fps=20,scale=1280:-1:flags=lanczos,setpts=PTS/1.4,palettegen" palette.png
@@ -51,6 +56,7 @@ ffmpeg -i input.mov -i palette.png -lavfi "[0:v]fps=20,scale=1280:-1:flags=lancz
5156
```
5257

5358
### 3. Result Summary
59+
5460
| Metric | Original Video | Processed GIF | Status |
5561
| :--- | :--- | :--- | :--- |
5662
| **File Size** | 38 MB | **14 MB** | ✅ Success |
@@ -63,11 +69,12 @@ ffmpeg -i input.mov -i palette.png -lavfi "[0:v]fps=20,scale=1280:-1:flags=lancz
6369
## 💡 Why This Case Matters
6470

6571
Standard LLMs can only "tell you" how to use FFmpeg. However, a Pipe powered by the **GitHub Copilot SDK** can:
72+
6673
1. **Interpret** complex multimedia processing parameters.
6774
2. **Access** raw files within the filesystem.
6875
3. **Execute** resource-intensive binary tool tasks.
6976
4. **Validate** that the output (size, resolution) meets the user's hard constraints.
7077

7178
---
7279

73-
> [View GitHub Copilot SDK Pipe Source Code](../../../plugins/pipes/github-copilot-sdk/README.md)
80+
> [View GitHub Copilot SDK Pipe Documentation](./github-copilot-sdk.md)

‎docs/plugins/pipes/video-processing-example.zh.md‎

Lines changed: 12 additions & 5 deletions
Original file line numberDiff line numberDiff line change
@@ -16,33 +16,38 @@
1616

1717
- **插件类型**: Pipe (GitHub Copilot SDK)
1818
- **底层模型**: Minimax 2.1
19-
- **核心能力**:
20-
- **底层系统访问**: 自动检测并调用容器内的 `ffmpeg` 工具。
21-
- **双阶段优化 (Two-Pass Optimization)**:
19+
- **核心能力**:
20+
- **底层系统访问**: 自动检测并调用容器内的 `ffmpeg` 工具。
21+
- **双阶段优化 (Two-Pass Optimization)**:
2222
1. **阶段一**: 分析全视频帧生成 256 色最优调色板 (`palettegen`)。
2323
2. **阶段二**: 应用调色板进行高质量量化和抖动处理 (`paletteuse`)。
24-
- **参数精准控制**: 实现 1.4 倍 PTS 缩放、Lanczos 滤镜缩放及 20fps 帧率控制。
24+
- **参数精准控制**: 实现 1.4 倍 PTS 缩放、Lanczos 滤镜缩放及 20fps 帧率控制。
2525

2626
---
2727

2828
## 💬 对话实录
2929

3030
### 📥 导入对话记录
31+
3132
你可以下载原始对话数据并导入到你的 Open WebUI 中，查看模型如何一步步调试 FFmpeg 参数：
3233
[:material-download: 下载原始对话 JSON](./video-processing-chat.json)
3334

3435
> **如何导入？**
3536
> 在 Open WebUI 首页点击 **左侧侧边栏底部个人头像** -> **设置** -> **数据** -> **导入记录**，选择下载的文件即可。
3637
3738
### 1. 提交处理需求
39+
3840
**用户**指定了输入文件和详细参数：
41+
3942
- 加速：1.4x (setpts=PTS/1.4)
4043
- 分辨率：宽度 1280px，等比例缩放
4144
- 质量优化：必须使用调色板生成技术
4245
- 约束：文件体积 < 20MB
4346

4447
### 2. 模型执行处理
48+
4549
**Minimax 2.1** 自动编写并执行了以下核心逻辑：
50+
4651
```bash
4752
# 生成优化调色板
4853
ffmpeg -i input.mov -vf "fps=20,scale=1280:-1:flags=lanczos,setpts=PTS/1.4,palettegen" palette.png
@@ -51,6 +56,7 @@ ffmpeg -i input.mov -i palette.png -lavfi "[0:v]fps=20,scale=1280:-1:flags=lancz
5156
```
5257

5358
### 3. 处理结果摘要
59+
5460
| 指标 | 原始视频 | 处理后 GIF | 状态 |
5561
| :--- | :--- | :--- | :--- |
5662
| **文件大小** | 38 MB | **14 MB** | ✅ 达标 |
@@ -63,11 +69,12 @@ ffmpeg -i input.mov -i palette.png -lavfi "[0:v]fps=20,scale=1280:-1:flags=lancz
6369
## 💡 为什么这个案例很有意义？
6470

6571
传统的 LLM 只能“告诉你”怎么做，而基于 **GitHub Copilot SDK** 的 Pipe 能够：
72+
6673
1. **理解** 复杂的多媒体处理参数。
6774
2. **感知** 文件系统中的原始素材。
6875
3. **执行** 耗时、耗能的二进制工具任务。
6976
4. **验证** 产出物（体积、分辨率）是否符合用户的最终约束。
7077

7178
---
7279

73-
> [查看 GitHub Copilot SDK Pipe 源码](../../../plugins/pipes/github-copilot-sdk/README.md)
80+
> [查看 GitHub Copilot SDK Pipe 开发文档](./github-copilot-sdk.zh.md)

0 commit comments

Comments
 (0)