To set up a virtual environment for your forex trading analysis project, you'll first need to decide on a folder structure that organizes your work efficiently. I'll guide you through creating this structure, setting up a virtual environment, and providing a basic `requirements.txt` file.

### Project Folder Structure

Here's a suggested structure to keep your project organized:

```plaintext
forex_analysis_project/
│
├── data/                        # Store raw and processed forex data
│   ├── raw/
│   └── processed/
│
├── notebooks/                   # Jupyter notebooks for exploration and analysis
│
├── src/                         # Source code for the project
│   ├── data_retrieval/          # Scripts for fetching and preprocessing data
│   │   ├── __init__.py
│   │   └── fetch_forex_data.py
│   │
│   ├── feature_engineering/     # Generate features from forex data
│   │   ├── __init__.py
│   │   └── features.py
│   │
│   ├── models/                  # Machine learning and deep learning models
│   │   ├── __init__.py
│   │   ├── lstm_model.py        # LSTM for time series prediction
│   │   └── rag_model.py         # RAG model integration
│   │
│   ├── inference/               # Inference logic for making predictions
│   │   ├── __init__.py
│   │   └── predict.py
│   │
│   └── utils/                   # Utility functions and classes
│       ├── __init__.py
│       └── utils.py
│
├── tests/                       # Unit and integration tests
│   ├── __init__.py
│   └── test_fetch_forex_data.py
│
├── requirements.txt             # Project dependencies
│
└── Dockerfile                   # Containerize your project (optional)
```

### Setting Up a Virtual Environment

**1. Creating a Virtual Environment:**

First, navigate to your project directory in the terminal, then run:

```bash
python3 -m venv venv
```

This command creates a virtual environment named `venv` within your project directory.

**2. Activating the Virtual Environment:**

- **On Windows:**

```bash
venv\Scripts\activate
```

- **On macOS and Linux:**

```bash
source venv/bin/activate
```

Once activated, you'll see the name of the virtual environment (`venv`) in your terminal prompt, indicating that any Python or pip commands will use the environments' packages and settings.

**3. Deactivating the Virtual Environment:**

When you're done working in the virtual environment, you can deactivate it by running:

```bash
deactivate
```

### `requirements.txt` File

Create a `requirements.txt` file in your project root directory (`forex_project/`) with the following content to specify the project dependencies:

```
pandas
numpy
matplotlib
seaborn
requests
oandapyV20
jupyterlab
```

**Installing Dependencies:**

With your virtual environment activated, install the project dependencies by running:

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

This command reads the `requirements.txt` file and installs the specified versions of the packages into your virtual environment.

### Final Steps

- **Developing Your Project:** Place your Python scripts in the `src/` directory, Jupyter notebooks in `notebooks/`, and any tests in `tests/`. Use the `data/` directory to store fetched data, such as CSV files.
- **Using Jupyter Notebook:** If you want to use Jupyter Notebook for analysis, start it with `jupyter notebook` or `jupyter lab` if you're using JupyterLab, and it will open in your web browser. Ensure you're doing this with your virtual environment activated so that Jupyter can access your project's dependencies.

This setup provides a solid foundation for developing your forex trading analysis project, offering a clear separation of concerns and making it easier to manage dependencies and share your work with others.