docs

docs/backend.md

@@ -1 +1,52 @@
-# Backend
+# Backend
+
+The backend, which is responsible for the identification based of a picture and streaming that information to the 
+frontend is build in Python 3.12 using poetry as its dependency manager. The backend is a flask application that
+utilizes the Google Lens features by utilizing Selenium to access the Google Lens website and GPT-4o to generate
+a description of the picture. The backend is containerized using Docker and can be run using the following command:
+
+
+## Usage 
+
+The usage of the backend in production requires Docker to be installed.
+
+```bash
+cd lens-gpt-backend
+docker build -t lens-gpt-backend .
+docker run \
+    --rm \                      
+  -e DISPLAY=:99 \
+  -p 3002:5000  \
+  lens-gpt-backend \
+  /bin/bash -c "Xvfb :99 -screen 0 1280x1024x24 & poetry run python -m lens_gpt_backend.main"
+```
+
+The application can then be accessed at `http://localhost:3002` via curl or a web browser. The backend comes with a 
+demo frontend which allows the user to upload a picture and display the raw information that are streamed back 
+from the backend. The classification can be accessed via the `/classify` endpoint and the frontend can be 
+accessed via the `/` endpoint. If the backend should be used just over the API, the following curl command 
+can be used, if the current directory contains an ``img.png``
+
+```bash 
+curl --no-buffer -X POST -F "[email protected]" http://localhost:3002
+```
+
+#### 4. Set Up the Project
+
+Navigate to the `lens-gpt-backend` directory and install the project dependencies:
+
+```bash
+cd path/to/lens-gpt-backend
+poetry install
+```
+
+#### 5. Run the Server
+
+Once all the requirements are met, run the server using the command:
+
+```bash
+poetry run python -m lens_gpt_backend.main
+```
+
+This command starts the server, allowing you to begin development.
+

docs/installation_requirements.md

@@ -0,0 +1,142 @@
+
+# Installation Requirements
+
+This page covers all the steps to install the required software for backend, frontend and production.
+
+## Docker
+
+Docker is used to containerize the code for production which makes it easier to install and to deploy it.
+
+#### For MacOS
+
+1. **Download Docker Desktop:**
+   Visit the [Docker Desktop for Mac](https://www.docker.com/products/docker-desktop) page and download the installer.
+
+2. **Install Docker Desktop:**
+    - Open the downloaded `.dmg` file.
+    - Drag the Docker icon to the Applications folder.
+    - Open Docker from the Applications folder.
+
+3. **Verify Installation:**
+   Open a terminal and run:
+
+   ```bash
+   docker --version
+   docker-compose --version
+   ```
+
+#### For Linux (Debian/Ubuntu)
+
+1. **Update Existing Packages:**
+   ```bash
+   sudo apt update
+   sudo apt install -y apt-transport-https ca-certificates curl software-properties-common
+   ```
+
+2. **Add Docker’s Official GPG Key:**
+   ```bash
+   curl -fsSL https://download.docker.com/linux/ubuntu/gpg | sudo gpg --dearmor -o /usr/share/keyrings/docker-archive-keyring.gpg
+   ```
+
+3. **Set Up the Stable Repository:**
+   ```bash
+   echo "deb [arch=$(dpkg --print-architecture) signed-by=/usr/share/keyrings/docker-archive-keyring.gpg] https://download.docker.com/linux/ubuntu $(lsb_release -cs) stable" | sudo tee /etc/apt/sources.list.d/docker.list > /dev/null
+   ```
+
+4. **Install Docker Engine:**
+   ```bash
+   sudo apt update
+   sudo apt install -y docker-ce docker-ce-cli containerd.io
+   ```
+
+5. **Verify Installation:**
+   ```bash
+   sudo systemctl status docker
+   docker --version
+   docker-compose --version
+   ```
+
+6. **Optional: Manage Docker as a Non-Root User:**
+   ```bash
+   sudo groupadd docker
+   sudo usermod -aG docker $USER
+   newgrp docker
+   ```
+
+   Log out and log back in for the changes to take effect.
+
+Now you should have Docker installed and ready to use on your system.
+
+## Python
+
+The backend is written in Python. If you want to develop the application further, it needs to be installed on your 
+device. You need Python 3.12 or later.
+
+**For MacOS:**
+
+```bash
+brew install python
+```
+
+**For Linux (Debian/Ubuntu):**
+
+```bash
+sudo apt update
+sudo apt install -y python3 python3-pip
+```
+
+Verify the installation:
+
+```bash
+python3 --version
+pip3 --version
+```
+
+## ChromeDriver
+
+ChromeDriver is required for browser automation, and you will need it installed when running the code locally.
+Install ChromeDriver using the following commands:
+
+**For MacOS:**
+
+```bash
+brew install chromedriver
+```
+
+**For Linux (Debian/Ubuntu):**
+
+```bash
+sudo apt-get install -y chromium-chromedriver
+```
+
+Verify the installation:
+
+```bash
+chromedriver --version
+```
+
+## Poetry
+
+Poetry is a dependency management tool for Python. Install Poetry with the following command:
+
+```bash
+curl -sSL https://install.python-poetry.org | python3 -
+```
+
+Add Poetry to your PATH by updating your shell configuration file (e.g., `~/.bashrc`, `~/.zshrc`):
+
+```bash
+export PATH="$HOME/.local/bin:$PATH"
+```
+
+Then, apply the changes:
+
+```bash
+source ~/.bashrc  # or source ~/.zshrc
+```
+
+Verify the installation:
+
+```bash
+poetry --version
+```

frontend/components/image-classification.tsx

@@ -40,7 +40,7 @@ export default function ImageClassification() {
       const formData = new FormData();
       formData.append('file', image);
 
-      fetch(`${Config.apiUrl}/classify`, {
+      fetch('http://localhost:3002/classify', {
         method: 'POST',
         body: formData,
       }).then(async (response) => {

lens-gpt-backend/README.md

@@ -16,10 +16,10 @@ docker build -t lens-gpt-backend .
 To run the docker image, run the following command:
 
 ```bash
-docker run \                      
-  --name your_container_name \
+docker run \
+    --rm \                      
   -e DISPLAY=:99 \
-  -p 5000:5000  \
+  -p 3002:3002  \
   lens-gpt-backend \
   /bin/bash -c "Xvfb :99 -screen 0 1280x1024x24 & poetry run python -m lens_gpt_backend.main"
 

lens-gpt-backend/lens_gpt_backend/main.py

@@ -1,4 +1,4 @@
 from lens_gpt_backend.api import app
 
 if __name__ == '__main__':
-    app.run(debug=True, port=5000, host='0.0.0.0')
+    app.run(debug=True, port=3002, host='0.0.0.0')