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https://github.com/bayesianinstitute/crypto_finance
Crypto Finance LLM App
https://github.com/bayesianinstitute/crypto_finance
Last synced: about 2 months ago
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Crypto Finance LLM App
- Host: GitHub
- URL: https://github.com/bayesianinstitute/crypto_finance
- Owner: bayesianinstitute
- Created: 2024-04-09T15:23:10.000Z (9 months ago)
- Default Branch: main
- Last Pushed: 2024-06-04T19:28:12.000Z (7 months ago)
- Last Synced: 2024-06-04T21:36:45.398Z (7 months ago)
- Language: Jupyter Notebook
- Homepage:
- Size: 70.3 KB
- Stars: 0
- Watchers: 0
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# Crypto Finance App
## Description
This repository contains a cryptocurrency analysis and trading application powered by AI. The application enables users to download CSV files by specifying a date range and then analyze the data using various features.
## Installation
To set up the project, follow these steps:
1. Ensure you have Python 3.10 installed on your system.
2. Clone the repository to your local machine.
3. Open a terminal or command prompt and navigate to the project directory.
4. Create a virtual environment by running the following command:
```bash
python3 -m venv env
```
5. Activate the virtual environment. On Windows, run:
```bash
.\env\Scripts\activate
```
On macOS and Linux, run:
```bash
source env/bin/activate
```
6. Once the virtual environment is activated, install the required dependencies by running:
```bash
pip install -r requirements.txt
```
## Data Analysis
For data analysis, refer to the notebook named `main.ipynb`.
## App Usage
### Trader and Investor App
To run the Trader and Investor version of the app, follow these steps:
1. Open a terminal or command prompt.
2. Navigate to the project directory.
3. Run the following commands:
```bash
cd app
streamlit run app.py
```
4. Press Enter to continue after the app starts.
5. Select a cryptocurrency and choose a time range for analysis.
## Contributing
Contributions to the Crypto Currency App are welcome! If you encounter any issues or have suggestions for improvements, please open an issue or submit a pull request on the GitHub repository.