refactor api and dashboard (#149)

* refactor api and dashbaord

* update dashboard to dashboards, and add dashboard_2

There was a discrepancy - the streamlit dashboard was also named dashboard_1, changed this to dashboard_2 to match the name in the directory

* rename dashboard to dashboards

* Update .bumpversion.cfg

* Update setup.py

* Bump version: 1.0.46 → 1.0.47 [skip ci] (#154)

Co-authored-by: BumpVersion Action <bumpversion@github-actions>

* Create README.md

* added video

* Update README.md

---------

Co-authored-by: Aryan Bhosale <[email protected]>
Co-authored-by: Aryan Bhosale <[email protected]>
Co-authored-by: BumpVersion Action <bumpversion@github-actions>

README.md

@@ -205,14 +205,16 @@ It is also available on [YouTube](https://www.youtube.com/watch?v=NAZ2VeiN1N8)
 ## Running the dashboard locally
 
 Start the API first (port 8000):
-`cd backend`
+`cd api`
 `python main.py`
 
 Start the frontend (port 5137):
-`cd frontend`
+`cd dashboards/dashboard_1`
 `npm install`
 `npm run dev`
 
+There is also a steamlit dashboard in `dashboards/dashboard_2` that can be used. 
+
 ## Contribution
 
 We welcome other models.

dashboards/dashboard_2/README.md

@@ -0,0 +1,72 @@
+# Streamlit Dashboard for Open Source Quartz Solar Forecast
+
+This Streamlit Dashboard provides an interactive interface for running and visualizing solar forecasts using the [Open Source Quartz Solar Forecast](https://github.com/openclimatefix/Open-Source-Quartz-Solar-Forecast) model developed by [Open Climate Fix](https://openclimatefix.org/).
+
+
+https://github.com/user-attachments/assets/940ca4a7-65a4-40ea-a602-ea0f65e96746
+
+
+## Features
+
+- Configure PV site parameters (latitude, longitude, capacity)
+- Select inverter type (No Inverter or Enphase)
+- Enphase API authentication flow (if applicable)
+- Run solar forecast
+- Visualize forecast results with interactive charts
+- Compare forecasts with and without recent PV data (if applicable)
+- Display raw forecast data and provide an option to download it as CSV
+
+## How to Run
+
+1. Clone the repository and install all the dependencies in a virtual environment on a Linux System(or WSL):
+   `pip install -e .` and `pip install -r requirements.txt`
+
+2. Set up environment variables (if applicable):
+
+- Create a `.env` file in your root directory
+- Add the following variables:
+  ```
+  ENPHASE_CLIENT_ID=your_client_id
+  ENPHASE_CLIENT_SECRET=your_client_secret
+  ENPHASE_API_KEY=your_api_key
+  ENPHASE_SYSTEM_ID=your_system_id
+  ```
+
+3. Navigate to the `dashboards/dashboard_2` directory.
+
+4. Run the Streamlit app: `streamlit run app.py`
+
+5. Open your web browser and go to the URL provided by Streamlit (usually `http://localhost:8501`).
+
+## Using the App
+
+1. **Configure PV Site:**
+
+- Use the sidebar to input latitude, longitude, and capacity of the PV site.
+- Alternatively, check "Use Default Values" to use pre-set values.
+
+2. **Select Inverter Type:**
+
+- Choose between "No Inverter" and "Enphase" from the dropdown menu.
+
+3. **Enphase Authorization (if applicable):**
+
+- If you select Enphase, follow the authorization process:
+  - Click the provided authorization URL
+  - Grant permissions on the Enphase website
+  - Copy the redirect URL and paste it back into the app
+
+4. **Run Forecast:**
+
+- Click the "Run Forecast" button to generate predictions.
+
+5. **View Results:**
+
+- See current power, total forecasted energy, and peak forecasted power.
+- Examine the interactive line chart comparing forecasts with and without recent PV data.
+- Review the raw forecast data table and optionally download it as CSV for further processing.
+
+## Additional Information
+
+- Forecasts are generated for the next 48 hours in 15-minute intervals.
+- The app demonstrates the impact of using recent PV data (from Enphase) on forecast accuracy.