| Category | Count |
|---|---|
| Prompt (total) | 5693 |
| ↳ text | 3443 |
| ↳ image | 2250 |
| ↳ cached | 0 |
| Completion (total) | 625 |
| ↳ reasoning | 266 |
| Total | 6318 |
model: kimi-k2.5 finish: tool_calls
以下有几个部分:
ROLE_AND_TASK:你的角色定义以及任务描述
TOOLS:你可以调用的工具列表,以及每个工具的参数说明
OUTPUT:输出相关规则和约束
TIPS:重要建议
SITUATION:上次操作、屏幕截图、待回答问题
<ROLE_AND_TASK>
你是一个信息收集代理,正在操作 Ubuntu Linux 桌面。你可以通过截图查看屏幕,并使用鼠标和键盘动作来查找信息。
你的目标不是完成任务本身,而是在有限步数内尽可能多而详细地回答 SITUATION 中待回答的问题。除了直接答案外,还要主动补充会影响后续执行的上下文细节,尤其是现有内容的格式、样式、颜色约定、布局模式,以及不同类别内容之间的对应关系。
相关任务背景: Please extract all Python code and comments from Karpathy's GPT colab code cells (skip markdown parts), merge into "gpt_dev_pure_code.py" in Home directory. Include all Python code and # comments from code cells, but exclude markdown docstrings and file headers.
工作流程:
1. 查看 SITUATION 中的待回答问题和屏幕截图。
2. 如果截图中已包含某些问题的答案,直接调用 `fill_information` 填写。
3. 如果需要额外信息,调用 `computer` 执行操作(打开文件、执行终端命令等)来获取。
4. 你只有 1 步操作预算,请高效利用每一步,尽量一次操作覆盖多个问题。
</ROLE_AND_TASK>
<TOOLS>
你拥有以下工具:computer、fill_information。
每次调用可以包含 `computer` 操作(获取信息)、`fill_information`(填写已获得的答案),或两者兼有。
## computer
操作电脑的动作库,调用它以在桌面上执行操作。
坐标值定义:
在最新一张屏幕截图中的坐标轴比例,使用 [0, 1] 范围内的归一化值。其中 (0, 0) = 屏幕左上角,(1, 1) = 屏幕右下角。
操作和参数说明:
1. 移动鼠标
{
"action": "mouse_move",
"to_coordinate": [float, float], # 移动到的坐标值。
}
2. 移动鼠标并点击鼠标按键
{
"action": str, # 鼠标按键操作,one of left_click | right_click | middle_click | double_click | triple_click
"at_coordinate": [float, float], # 移动到的坐标值。
"with_key": str or None, # 点击时按住的键盘按键(比如"ctrl"、"shift"),如没有则填None。
}
3. 按住鼠标左键并拖动
{
"action": "left_click_drag",
"from_coordinate": [float, float], # 起始到的坐标值,
"to_coordinate": [float, float], # 移动到的坐标值。
"with_key": str or None, # 点击时按住的键盘按键(比如"ctrl"、"shift"),如没有则填None。
}
4. 输入文字
{
"action": "type",
"text": str, # 要输入的文字
"submit": bool, # 输入后是否按 Enter 键提交
}
5. 键盘按键(单个或组合键)
{
"action": "key",
"text": list[str], # 要按的键盘按键组合(如"enter"、"tab"、"ctrl"),
"with_duration": float or None, # 按键持续时间(秒),如点击则填 null。
}
6. 移动鼠标并滚动鼠标滚轮
{
"action": "scroll",
"at_coordinate": [float, float], # 滚动位置的坐标值
"scroll_direction": str, # 滚动方向,one of "up" | "down" | "left" | "right"
"scroll_amount": int, # 滚动量,1-30,模拟人类滚轮滚动的幅度。较大的值表示更大幅度的滚动。
}
7. 等待
{
"action": "wait",
"duration": float, # 等待秒数。根据操作后界面变化的复杂程度调整等待时间。
}
BATCH动作原则:
BATCH动作指一组连续且相对固定的电脑操作,主要用来减少不必要的对话过程。
- 例如:顺序输入(type→Tab→type)、键盘快捷键(Ctrl+C 然后 Ctrl+V)、输入一段字符后 Enter(在搜索输入框中常用)。
- DO NOT BATCH:涉及界面状态变化等待的操作(如打开菜单/对话框后等待动画)→ 依赖新坐标的操作。例如:点击打开一个菜单后,等待菜单完全展开再点击菜单项,因为菜单项的坐标在菜单完全展开前可能不稳定;滚动页面后再点击某个元素,因为滚动会改变元素的坐标。
**只在比较确定的操作中可以使用多个动作组合。当你不确定时,使用单个动作是更保险的做法**
## fill_information
当你从截图或操作结果中获得了某个问题的答案时,调用此工具填写。可以在同一轮中多次调用来回答多个问题。
{
"question": str, # 原始问题文本(必须与待回答问题列表中的文本完全一致)
"answer": str, # 基于实际观察到的信息给出的答案
"necessary_info": str, # 与问题相关的会影响后续执行的上下文信息,可能包括文件内容的格式、样式、颜色约定,应用界面的布局模式,以及不同类别内容之间的对应关系等。
}
</TOOLS>
<OUTPUT>
输出你从截图中观察到的详细信息、分析和计划,然后调用工具。
```
#### 从截图中观察到的信息
...
#### 下一步计划
...
```
</OUTPUT>
<TIPS>
- 优先从当前截图中提取信息,能直接回答的问题立即用 `fill_information` 填写,不要浪费步骤。
- 尝试一次操作同时获取多个问题的答案(如打开文件既能看到结构又能看到内容)。
- 如果截图与上一张相同,说明操作没有生效,换一种方式。
- 剩余步骤有限,优先回答最容易获取的问题;跳过在预算内无法获取的问题。
</TIPS>
<SITUATION>
## 1. 待回答问题
## Is the gpt-dev.ipynb notebook file available locally on the Ubuntu system? If yes, what is its path?
**回答**: 尚未回答
## If the notebook is not available locally, is the URL https://colab.research.google.com/drive/1JMLa53HDuA-i7ZBmqV7ZnA3c_fvtXnx-?usp=sharing accessible for downloading?
**回答**: 尚未回答
## Does the Home directory exist and is it writable?
**回答**: 尚未回答
## Are there any existing files named gpt_dev_pure_code.py in the Home directory?
**回答**: 尚未回答
## 2. 上一次的决策
### 2.1. 上一次的观察和思考
```
#### 从截图中观察到的信息
1. The Terminal panel on the right side is now active and ready for input (showing a cursor)
2. The command `ls -la ~ | head -20` was typed but may not have been executed yet (no output visible in terminal)
3. The Colab notebook URL https://colab.research.google.com/drive/1JMLa53HDuA-i7ZBmqV7ZnA3c_fvtXnx-?usp=sharing is accessible and loaded
4. The notebook shows Python code cells with comments in green (#) and code for downloading/reading tiny shakespeare dataset
From the current state:
- The URL is confirmed accessible (visible in address bar and notebook loaded)
- The Terminal is active but I need to execute the command to see home directory contents
#### 下一步计划
1. Execute the already-typed command in the terminal by pressing Enter
2. After seeing the results, run another command to search for gpt-dev.ipynb file locally
```
### 2.2. 上一次的操作
{"function": {"name": "computer", "arguments": {"actions": [{"action": "key", "text": ["return"]}]}}}
## 3. 屏幕截图## 3.1 最新屏幕状态(上一次操作后,未压缩)
inline base64 image ~336KB
## 3.2 上一次屏幕状态(上一次操作前,已压缩)
inline base64 image ~86KB
## 4. 上一次操作的前 5 步操作简述
### 步骤 1:
- 描述:
```
#### 从截图中观察到的信息
1. Google Chrome is open with the gpt-dev.ipynb notebook loaded in Google Colab
2. The URL in the address bar shows: `colab.research.google.com/drive/1JMLa53HDuA-i7ZBmqV7ZnA3c_fvtXnx-?usp=sharing` which matches the URL mentioned in the questions
3. The notebook is currently displaying code cells with Python code for downloading and reading the tiny shakespeare dataset
4. There's a "Terminal" tab visible at the bottom of the screen
5. I can see the notebook content includes Python code and comments (green text starting with #)
From the screenshot, I can confirm that the Colab URL is accessible (the notebook is loaded). However, I need to check the local file system to answer questions about local availability of the notebook file and the Home directory status.
#### 下一步计划
1. Click on the Terminal tab to open a terminal window
2. Run commands to check:
- If gpt-dev.ipynb exists locally (search in common locations)
- If Home directory exists and is writable
- If gpt_dev_pure_code.py already exists in Home directory
```
- 操作:
1. 左键单击坐标 (0.133, 0.979)
### 步骤 2:
- 描述:
```
#### 从截图中观察到的信息
1. A "Google sign-in required" dialog has appeared, blocking the interface. It says "You must be logged in with a Google Account to continue."
2. The Colab notebook is visible in the background with Python code cells showing:
- Comments in green (starting with #)
- Code for downloading tiny shakespeare dataset
- Code for reading and inspecting the dataset
3. The Terminal tab is visible at the bottom left of the screen
4. The URL in the address bar confirms: `colab.research.google.com/drive/1JMLa53HDuA-i7ZBmqV7ZnA3c_fvtXnx-?usp=sharing` is accessible
I need to cancel this dialog first, then access the Terminal to check local file system.
#### 下一步计划
1. Click "Cancel" on the Google sign-in dialog to dismiss it
2. Click on the Terminal tab to open a terminal window
3. Run commands to check local file system status
```
- 操作:
1. 左键单击坐标 (0.562, 0.606)
### 步骤 3:
- 描述:
```
#### 从截图中观察到的信息
1. The Google sign-in dialog has been dismissed successfully
2. The Colab notebook is now fully visible with Python code cells showing:
- Comments in green (starting with #)
- Code for downloading tiny shakespeare dataset
- Code for reading and inspecting the dataset
3. The Terminal panel is visible on the right side of the screen
4. The URL in the address bar confirms: `colab.research.google.com/drive/1JMLa53HDuA-i7ZBmqV7ZnA3c_fvtXnx-?usp=sharing` is accessible
5. I can see the notebook title "gpt-dev.ipynb" in the tab and header
#### 下一步计划
1. Click on the Terminal panel to make it active
2. Run commands to check:
- If gpt-dev.ipynb exists locally
- If Home directory exists and is writable
- If gpt_dev_pure_code.py already exists
```
- 操作:
1. 左键单击坐标 (0.703, 0.556)
2. 输入文本: ls -la ~ | head -20
3. 按下键盘按键: return
</SITUATION>
| Category | Count |
|---|---|
| Prompt (total) | 5693 |
| ↳ text | 3443 |
| ↳ image | 2250 |
| ↳ cached | 0 |
| Completion (total) | 625 |
| ↳ reasoning | 266 |
| Total | 6318 |
model: kimi-k2.5 finish: tool_calls
以下有几个部分:
ROLE_AND_TASK:你的角色定义以及任务描述
TOOLS:你可以调用的工具列表,以及每个工具的参数说明
OUTPUT:输出相关规则和约束
TIPS:重要建议
SITUATION:上次操作、屏幕截图、待回答问题
<ROLE_AND_TASK>
你是一个信息收集代理,正在操作 Ubuntu Linux 桌面。你可以通过截图查看屏幕,并使用鼠标和键盘动作来查找信息。
你的目标不是完成任务本身,而是在有限步数内尽可能多而详细地回答 SITUATION 中待回答的问题。除了直接答案外,还要主动补充会影响后续执行的上下文细节,尤其是现有内容的格式、样式、颜色约定、布局模式,以及不同类别内容之间的对应关系。
相关任务背景: Please extract all Python code and comments from Karpathy's GPT colab code cells (skip markdown parts), merge into "gpt_dev_pure_code.py" in Home directory. Include all Python code and # comments from code cells, but exclude markdown docstrings and file headers.
工作流程:
1. 查看 SITUATION 中的待回答问题和屏幕截图。
2. 如果截图中已包含某些问题的答案,直接调用 `fill_information` 填写。
3. 如果需要额外信息,调用 `computer` 执行操作(打开文件、执行终端命令等)来获取。
4. 你只有 1 步操作预算,请高效利用每一步,尽量一次操作覆盖多个问题。
</ROLE_AND_TASK>
<TOOLS>
你拥有以下工具:computer、fill_information。
每次调用可以包含 `computer` 操作(获取信息)、`fill_information`(填写已获得的答案),或两者兼有。
## computer
操作电脑的动作库,调用它以在桌面上执行操作。
坐标值定义:
在最新一张屏幕截图中的坐标轴比例,使用 [0, 1] 范围内的归一化值。其中 (0, 0) = 屏幕左上角,(1, 1) = 屏幕右下角。
操作和参数说明:
1. 移动鼠标
{
"action": "mouse_move",
"to_coordinate": [float, float], # 移动到的坐标值。
}
2. 移动鼠标并点击鼠标按键
{
"action": str, # 鼠标按键操作,one of left_click | right_click | middle_click | double_click | triple_click
"at_coordinate": [float, float], # 移动到的坐标值。
"with_key": str or None, # 点击时按住的键盘按键(比如"ctrl"、"shift"),如没有则填None。
}
3. 按住鼠标左键并拖动
{
"action": "left_click_drag",
"from_coordinate": [float, float], # 起始到的坐标值,
"to_coordinate": [float, float], # 移动到的坐标值。
"with_key": str or None, # 点击时按住的键盘按键(比如"ctrl"、"shift"),如没有则填None。
}
4. 输入文字
{
"action": "type",
"text": str, # 要输入的文字
"submit": bool, # 输入后是否按 Enter 键提交
}
5. 键盘按键(单个或组合键)
{
"action": "key",
"text": list[str], # 要按的键盘按键组合(如"enter"、"tab"、"ctrl"),
"with_duration": float or None, # 按键持续时间(秒),如点击则填 null。
}
6. 移动鼠标并滚动鼠标滚轮
{
"action": "scroll",
"at_coordinate": [float, float], # 滚动位置的坐标值
"scroll_direction": str, # 滚动方向,one of "up" | "down" | "left" | "right"
"scroll_amount": int, # 滚动量,1-30,模拟人类滚轮滚动的幅度。较大的值表示更大幅度的滚动。
}
7. 等待
{
"action": "wait",
"duration": float, # 等待秒数。根据操作后界面变化的复杂程度调整等待时间。
}
BATCH动作原则:
BATCH动作指一组连续且相对固定的电脑操作,主要用来减少不必要的对话过程。
- 例如:顺序输入(type→Tab→type)、键盘快捷键(Ctrl+C 然后 Ctrl+V)、输入一段字符后 Enter(在搜索输入框中常用)。
- DO NOT BATCH:涉及界面状态变化等待的操作(如打开菜单/对话框后等待动画)→ 依赖新坐标的操作。例如:点击打开一个菜单后,等待菜单完全展开再点击菜单项,因为菜单项的坐标在菜单完全展开前可能不稳定;滚动页面后再点击某个元素,因为滚动会改变元素的坐标。
**只在比较确定的操作中可以使用多个动作组合。当你不确定时,使用单个动作是更保险的做法**
## fill_information
当你从截图或操作结果中获得了某个问题的答案时,调用此工具填写。可以在同一轮中多次调用来回答多个问题。
{
"question": str, # 原始问题文本(必须与待回答问题列表中的文本完全一致)
"answer": str, # 基于实际观察到的信息给出的答案
"necessary_info": str, # 与问题相关的会影响后续执行的上下文信息,可能包括文件内容的格式、样式、颜色约定,应用界面的布局模式,以及不同类别内容之间的对应关系等。
}
</TOOLS>
<OUTPUT>
输出你从截图中观察到的详细信息、分析和计划,然后调用工具。
```
#### 从截图中观察到的信息
...
#### 下一步计划
...
```
</OUTPUT>
<TIPS>
- 优先从当前截图中提取信息,能直接回答的问题立即用 `fill_information` 填写,不要浪费步骤。
- 尝试一次操作同时获取多个问题的答案(如打开文件既能看到结构又能看到内容)。
- 如果截图与上一张相同,说明操作没有生效,换一种方式。
- 剩余步骤有限,优先回答最容易获取的问题;跳过在预算内无法获取的问题。
</TIPS>
<SITUATION>
## 1. 待回答问题
## Is the gpt-dev.ipynb notebook file available locally on the Ubuntu system? If yes, what is its path?
**回答**: 尚未回答
## If the notebook is not available locally, is the URL https://colab.research.google.com/drive/1JMLa53HDuA-i7ZBmqV7ZnA3c_fvtXnx-?usp=sharing accessible for downloading?
**回答**: 尚未回答
## Does the Home directory exist and is it writable?
**回答**: 尚未回答
## Are there any existing files named gpt_dev_pure_code.py in the Home directory?
**回答**: 尚未回答
## 2. 上一次的决策
### 2.1. 上一次的观察和思考
```
#### 从截图中观察到的信息
1. The Terminal panel on the right side is now active and ready for input (showing a cursor)
2. The command `ls -la ~ | head -20` was typed but may not have been executed yet (no output visible in terminal)
3. The Colab notebook URL https://colab.research.google.com/drive/1JMLa53HDuA-i7ZBmqV7ZnA3c_fvtXnx-?usp=sharing is accessible and loaded
4. The notebook shows Python code cells with comments in green (#) and code for downloading/reading tiny shakespeare dataset
From the current state:
- The URL is confirmed accessible (visible in address bar and notebook loaded)
- The Terminal is active but I need to execute the command to see home directory contents
#### 下一步计划
1. Execute the already-typed command in the terminal by pressing Enter
2. After seeing the results, run another command to search for gpt-dev.ipynb file locally
```
### 2.2. 上一次的操作
{"function": {"name": "computer", "arguments": {"actions": [{"action": "key", "text": ["return"]}]}}}
## 3. 屏幕截图## 3.1 最新屏幕状态(上一次操作后,未压缩)
inline base64 image ~336KB
## 3.2 上一次屏幕状态(上一次操作前,已压缩)
inline base64 image ~86KB
## 4. 上一次操作的前 5 步操作简述
### 步骤 1:
- 描述:
```
#### 从截图中观察到的信息
1. Google Chrome is open with the gpt-dev.ipynb notebook loaded in Google Colab
2. The URL in the address bar shows: `colab.research.google.com/drive/1JMLa53HDuA-i7ZBmqV7ZnA3c_fvtXnx-?usp=sharing` which matches the URL mentioned in the questions
3. The notebook is currently displaying code cells with Python code for downloading and reading the tiny shakespeare dataset
4. There's a "Terminal" tab visible at the bottom of the screen
5. I can see the notebook content includes Python code and comments (green text starting with #)
From the screenshot, I can confirm that the Colab URL is accessible (the notebook is loaded). However, I need to check the local file system to answer questions about local availability of the notebook file and the Home directory status.
#### 下一步计划
1. Click on the Terminal tab to open a terminal window
2. Run commands to check:
- If gpt-dev.ipynb exists locally (search in common locations)
- If Home directory exists and is writable
- If gpt_dev_pure_code.py already exists in Home directory
```
- 操作:
1. 左键单击坐标 (0.133, 0.979)
### 步骤 2:
- 描述:
```
#### 从截图中观察到的信息
1. A "Google sign-in required" dialog has appeared, blocking the interface. It says "You must be logged in with a Google Account to continue."
2. The Colab notebook is visible in the background with Python code cells showing:
- Comments in green (starting with #)
- Code for downloading tiny shakespeare dataset
- Code for reading and inspecting the dataset
3. The Terminal tab is visible at the bottom left of the screen
4. The URL in the address bar confirms: `colab.research.google.com/drive/1JMLa53HDuA-i7ZBmqV7ZnA3c_fvtXnx-?usp=sharing` is accessible
I need to cancel this dialog first, then access the Terminal to check local file system.
#### 下一步计划
1. Click "Cancel" on the Google sign-in dialog to dismiss it
2. Click on the Terminal tab to open a terminal window
3. Run commands to check local file system status
```
- 操作:
1. 左键单击坐标 (0.562, 0.606)
### 步骤 3:
- 描述:
```
#### 从截图中观察到的信息
1. The Google sign-in dialog has been dismissed successfully
2. The Colab notebook is now fully visible with Python code cells showing:
- Comments in green (starting with #)
- Code for downloading tiny shakespeare dataset
- Code for reading and inspecting the dataset
3. The Terminal panel is visible on the right side of the screen
4. The URL in the address bar confirms: `colab.research.google.com/drive/1JMLa53HDuA-i7ZBmqV7ZnA3c_fvtXnx-?usp=sharing` is accessible
5. I can see the notebook title "gpt-dev.ipynb" in the tab and header
#### 下一步计划
1. Click on the Terminal panel to make it active
2. Run commands to check:
- If gpt-dev.ipynb exists locally
- If Home directory exists and is writable
- If gpt_dev_pure_code.py already exists
```
- 操作:
1. 左键单击坐标 (0.703, 0.556)
2. 输入文本: ls -la ~ | head -20
3. 按下键盘按键: return
</SITUATION>