Extract insights from your journal by replacing 'dummy_journal_data.csv' with your own journal csv. Also replace where this data is referenced in journal_rag_helpers.py by changing the name there (line 10). The journal data must be in csv format with Year, Month (as a string fully spelt out), Day, Entry. See the dummy_journal_data.csv for examples. Dummy data is only from January 2023 to March 2023 if you use the app with it.

This application can be run in two ways: using Docker or directly with Python. Choose the method that best suits your environment and follow the corresponding steps.

1. Set up the .env file

   First, you need to create a .env file in the root directory of the project. This file should contain your OpenAI API key. Create the file and add the following line:

   OPENAI_API_KEY=your_openai_api_key_here

   Replace your_openai_api_key_here with your actual OpenAI API key.

2. Build and Run the Docker Container

   Open a terminal in the project directory. Build the Docker image and run the container using the following commands:

   docker build -t rag-journal-app .
   docker run --env-file .env -p 8501:8501 rag-journal-app

   This will start the Streamlit app, which you can access by navigating to http://localhost:8501 in your web browser.

1. Set the OPENAI_API_KEY Environment Variable

   Before running the app, you need to set the OPENAI_API_KEY environment variable to your OpenAI API key. This can be done in your terminal as follows:

   • On Linux/Mac:

     export OPENAI_API_KEY=your_openai_api_key_here

   • On Windows:

     set OPENAI_API_KEY=your_openai_api_key_here

   Replace your_openai_api_key_here with your actual OpenAI API key.

2. Create a Virtual Environment

   Navigate to the project directory and create a Python virtual environment:

   python -m venv journal

   Activate the virtual environment:

   • On Linux/Mac:

     source journal/bin/activate

   • On Windows:

     .\journal\Scripts\activate

3. Install the Requirements

   Install the required Python packages using:

   pip install -r requirements.txt

4. Run the Streamlit App

   With the setup complete, you can now run the Streamlit app:

   streamlit run app.py

   The app should now be running and accessible via http://localhost:8501 in your web browser. If using dummy data, try asking "What were some things I loved doing in January 2023?"