| Name | JupyterDebug JSON |
| Version |
0.1.0
JSON |
| download |
| home_page | https://github.com/et22/JupyterDebug |
| Summary | A package for debugging Jupyter notebooks using OpenAI. |
| upload_time | 2025-01-27 02:23:13 |
| maintainer | None |
| docs_url | None |
| author | Ethan |
| requires_python | >=3.6 |
| license | None |
| keywords |
|
| VCS |
 |
| bugtrack_url |
|
| requirements |
No requirements were recorded.
|
| Travis-CI |
No Travis.
|
| coveralls test coverage |
No coveralls.
|
## Documentation for `JupyterDebug`
### Package Overview
`JupyterDebug` is a Python package designed to help users debug Python code in Jupyter notebooks using OpenAI's language models. It provides two main methods:
1. `init()`: Initializes the package by prompting the user for their OpenAI API key and selecting a model.
2. `debug(max_iter=1)`: Automatically debugs the code in the previous cell by calling the selected language model iteratively to fix errors.
---
### Installation
To install `JupyterDebug`, use pip:
```bash
pip install JupyterDebug
```
---
### Usage
#### 1. `init()`
The `init()` method initializes the package by prompting the user for their OpenAI API key and selecting a model. It must be called before using the `debug()` method.
**Syntax**:
```python
import JupyterDebug as jd
jd.init()
```
**Behavior**:
- Prompts the user to enter their OpenAI API key.
- Asks the user to select a model from the following options:
- `gpt-4o-mini` (default)
- `gpt-4o`
- `o1`
- `o1-mini`
- Stores the API key and model selection in environment variables for use in the `debug()` method.
---
#### 2. `debug(max_iter=1)`
The `debug()` method automatically debugs the code in the previous cell by calling the selected language model iteratively to fix errors. It should be called in a new cell immediately after the cell that generated the error.
**Syntax**:
```python
jd.debug(max_iter=1)
```
**Parameters**:
- `max_iter` (optional, default=1): The maximum number of times the language model is called to iteratively debug the code. If the first solution does not fix all errors, the method will retry up to `max_iter` times.
**Behavior**:
- Captures the code from the previous cell and the error trace.
- Calls the selected language model to generate a fix for the code.
- Replaces the code in the previous cell with the fixed version.
- If `max_iter > 1`, the process is repeated until all errors are fixed or the maximum number of iterations is reached.
**Example**:
```python
# Cell 1: Code with an error
x = 10
y = "20"
z = x + y # This will raise a TypeError
```
```python
# Cell 2: Debug the error
jd.debug()
```
---
### Example Workflow
1. Install the package:
```bash
pip install JupyterDebug
```
2. Initialize the package:
```python
import JupyterDebug as jd
jd.init()
```
3. Write and run code in a Jupyter notebook cell:
```python
# Cell 1: Code with an error
x = 10
y = "20"
z = x + y # This will raise a TypeError
```
4. Debug the error in the next cell:
```python
# Cell 2: Debug the error
jd.debug(max_iter=2)
```
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"description": "## Documentation for `JupyterDebug`\n\n### Package Overview\n`JupyterDebug` is a Python package designed to help users debug Python code in Jupyter notebooks using OpenAI's language models. It provides two main methods:\n1. `init()`: Initializes the package by prompting the user for their OpenAI API key and selecting a model.\n2. `debug(max_iter=1)`: Automatically debugs the code in the previous cell by calling the selected language model iteratively to fix errors.\n\n---\n\n### Installation\nTo install `JupyterDebug`, use pip:\n```bash\npip install JupyterDebug\n```\n\n---\n\n### Usage\n\n#### 1. `init()`\nThe `init()` method initializes the package by prompting the user for their OpenAI API key and selecting a model. It must be called before using the `debug()` method.\n\n**Syntax**:\n```python\nimport JupyterDebug as jd\njd.init()\n```\n\n**Behavior**:\n- Prompts the user to enter their OpenAI API key.\n- Asks the user to select a model from the following options:\n - `gpt-4o-mini` (default)\n - `gpt-4o`\n - `o1`\n - `o1-mini`\n- Stores the API key and model selection in environment variables for use in the `debug()` method.\n\n---\n\n#### 2. `debug(max_iter=1)`\nThe `debug()` method automatically debugs the code in the previous cell by calling the selected language model iteratively to fix errors. It should be called in a new cell immediately after the cell that generated the error. \n\n**Syntax**:\n```python\njd.debug(max_iter=1)\n```\n\n**Parameters**:\n- `max_iter` (optional, default=1): The maximum number of times the language model is called to iteratively debug the code. If the first solution does not fix all errors, the method will retry up to `max_iter` times.\n\n**Behavior**:\n- Captures the code from the previous cell and the error trace.\n- Calls the selected language model to generate a fix for the code.\n- Replaces the code in the previous cell with the fixed version.\n- If `max_iter > 1`, the process is repeated until all errors are fixed or the maximum number of iterations is reached.\n\n**Example**:\n```python\n# Cell 1: Code with an error\nx = 10\ny = \"20\"\nz = x + y # This will raise a TypeError\n```\n\n```python\n# Cell 2: Debug the error\njd.debug()\n```\n\n---\n\n### Example Workflow\n1. Install the package:\n ```bash\n pip install JupyterDebug\n ```\n\n2. Initialize the package:\n ```python\n import JupyterDebug as jd\n jd.init()\n ```\n\n3. Write and run code in a Jupyter notebook cell:\n ```python\n # Cell 1: Code with an error\n x = 10\n y = \"20\"\n z = x + y # This will raise a TypeError\n ```\n\n4. Debug the error in the next cell:\n ```python\n # Cell 2: Debug the error\n jd.debug(max_iter=2)\n ```\n",
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