### Installing Core Python Dependencies (Shell)

Source: https://github.com/mrgreyfun/local-code-interpreter/blob/main/README.md

This command uses pip to install all core Python packages listed in the `requirements.txt` file. These packages are essential for the basic functionality of the Local Code Interpreter, ensuring all necessary libraries are available.

```shell
pip install -r requirements.txt
```

--------------------------------

### Installing Full Python Dependencies for Data Analysis (Shell)

Source: https://github.com/mrgreyfun/local-code-interpreter/blob/main/README.md

This command installs a comprehensive set of Python packages from `requirements_full.txt`, including those commonly used for data processing and analysis. It's recommended for users who plan to perform advanced data analysis tasks with the Local Code Interpreter.

```shell
pip install -r requirements_full.txt
```

--------------------------------

### Running Local Code Interpreter Web UI (Python)

Source: https://github.com/mrgreyfun/local-code-interpreter/blob/main/README.md

This command initiates the Local Code Interpreter's web user interface. Executing this Python script starts the application, making it accessible via a generated link in your web browser.

```shell
python web_ui.py
```

--------------------------------

### Defining Python Project Dependencies

Source: https://github.com/mrgreyfun/local-code-interpreter/blob/main/requirements.txt

This snippet specifies the Python packages and their exact versions (or minimum versions) required for the project. These dependencies are typically installed using pip from a `requirements.txt` file, ensuring a consistent environment.

```Python
notebook==6.5.4
openai==1.40.3
gradio==3.39.0
ansi2html==1.8.0
tiktoken
Pillow
```

--------------------------------

### Project Dependencies - Python

Source: https://github.com/mrgreyfun/local-code-interpreter/blob/main/requirements_full.txt

This snippet lists the Python packages and their exact versions required for the project. These dependencies are typically installed using pip from a requirements.txt file to ensure a consistent development and execution environment.

```Python
notebook==6.5.4
openai==1.40.3
gradio==3.39.0
ansi2html==1.8.0
tiktoken
Pillow
numpy
scipy
openpyxl
xlrd
xlwt
matplotlib
pandas
opencv-python
PyPDF2
pdfminer.six
sympy
scikit-learn
```

--------------------------------

### Cloning the Local-Code-Interpreter Repository (Shell)

Source: https://github.com/mrgreyfun/local-code-interpreter/blob/main/README.md

This command sequence clones the Local-Code-Interpreter project repository from GitHub to the local machine and then navigates into the newly created project directory. It is the first step required to set up the project for local use.

```shell
git clone https://github.com/MrGreyfun/Local-Code-Interpreter.git
cd Local-Code-Interpreter
```

--------------------------------

### Configuring Empty API Key in config.json

Source: https://github.com/mrgreyfun/local-code-interpreter/blob/main/README.md

This JSON snippet shows how to configure the `API_KEY` field in `config.json` to an empty string. This setting allows users to provide the API key via an environment variable instead of storing it directly in the configuration file, enhancing security.

```json
"API_KEY": ""
```

--------------------------------

### Navigating to Source Directory (Shell)

Source: https://github.com/mrgreyfun/local-code-interpreter/blob/main/README.md

This shell command is used to change the current directory to the `src` directory. This step is a prerequisite for running the main application script, ensuring that the program can locate its necessary files and modules.

```shell
cd src
```

--------------------------------

### Configuring Model Context Window in JSON

Source: https://github.com/mrgreyfun/local-code-interpreter/blob/main/README.md

This JSON snippet demonstrates the format for manually adding context window information for models, particularly for Azure OpenAI service users. The `model_context_window` field is crucial for the program to manage conversation length by slicing conversations when they exceed the model's capacity.

```json
"<YOUR-DEPLOYMENT-NAME>": <contex_window (integer)>
```

--------------------------------

### Setting OpenAI API Key on Windows

Source: https://github.com/mrgreyfun/local-code-interpreter/blob/main/README.md

This shell command demonstrates how to set the `OPENAI_API_KEY` environment variable on a Windows operating system. This method is an alternative to storing the API key directly in the `config.json` file, providing a more secure way to manage credentials.

```shell
set OPENAI_API_KEY=<YOUR-API-KEY>
```

--------------------------------

### Running Web UI with Jupyter Notebook Saving (Python)

Source: https://github.com/mrgreyfun/local-code-interpreter/blob/main/README.md

This command runs the Local Code Interpreter's web UI while enabling the saving of the conversation to a Jupyter notebook. The `-n` or `--notebook` option allows specifying a path to save the notebook, providing a persistent record of interactions and code executions.

```shell
python web_ui.py -n <path_to_notebook>
```

--------------------------------

### Setting OpenAI API Key on Linux

Source: https://github.com/mrgreyfun/local-code-interpreter/blob/main/README.md

This shell command illustrates how to set the `OPENAI_API_KEY` environment variable on a Linux operating system. This approach allows users to avoid hardcoding the API key in `config.json`, promoting better security practices.

```shell
export OPENAI_API_KEY=<YOUR-API-KEY>
```

=== COMPLETE CONTENT === This response contains all available snippets from this library. No additional content exists. Do not make further requests.