README.md

---
title: Dish Decode 2
emoji: 🏃
colorFrom: purple
colorTo: pink
sdk: docker
pinned: false
license: mit
short_description: Structure recipe information from videos

---
# 🍽️ Recipe Extraction API

This project is a Flask-based API that extracts structured recipe information from cooking tutorial videos! It uses the **Deepgram API** for audio transcription, **Tesseract OCR** for text extraction from video frames, and the **Gemini API** to generate a well-structured recipe document. 🚀

---

## 📦 Project Setup

Follow these steps to set up and run the project on your local machine.

### 1️⃣ Clone the Repository

```bash
git clone <your-repo-url>
cd <your-repo-folder>
```

### 2️⃣ Install Dependencies

Make sure you have Python installed (Python 3.8 or above is recommended). Install the required libraries using pip:

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

### 3️⃣ Install Tesseract OCR

Ensure **Tesseract OCR** is installed on your system. You can download it here: [Tesseract GitHub](https://github.com/tesseract-ocr/tesseract)

Add Tesseract to your system path and make sure to note its installation location.

#### On Windows:

Add the path to `tesseract.exe` to your environment variables, e.g.:

```bash
C:\Program Files\Tesseract-OCR
```

#### On MacOS (using Homebrew):

```bash
brew install tesseract
```

#### On Ubuntu:

```bash
sudo apt-get install tesseract-ocr
```

### 4️⃣ Setup Environment Variables

Create a `.env` file in the root directory and add your API keys:

```plaintext
FIRST_API_KEY=<Your Gemini API Key>
SECOND_API_KEY=<Your Deepgram API Key>
```

### 5️⃣ Install FFmpeg

This project uses **FFmpeg** for converting MP4 videos to WAV audio. Install it via the following:

#### On MacOS (using Homebrew):

```bash
brew install ffmpeg
```

#### On Ubuntu:

```bash
sudo apt-get install ffmpeg
```

#### On Windows:

Download FFmpeg from [FFmpeg.org](https://ffmpeg.org/download.html) and add it to your system path.

---

## 🚀 Running the Project

Start the Flask server with the following command:

```bash
python app.py
```

If everything is set up correctly, you should see:

```plaintext
 * Running on http://127.0.0.1:5000/
```

---

## 📡 API Endpoints

### ✅ Health Check

**Endpoint:** `GET /`

Check if the API is running.

```bash
curl http://127.0.0.1:5000/
```

**Response:**

```json
{
    "status": "success",
    "message": "API is running successfully!"
}
```

### 🍲 Recipe Extraction

**Endpoint:** `POST /process-video`

#### Request Body:

Send a JSON payload with a video URL:

```json
{
    "videoUrl": "<URL-of-the-cooking-video>"
}
```

#### Example Using `curl`:

```bash
curl -X POST http://127.0.0.1:5000/process-video \
-H "Content-Type: application/json" \
-d '{"videoUrl": "https://example.com/video.mp4"}'
```

#### Sample Response:

```json
{
    "**1. Recipe Name:**": "Beef Wellington",
    "**2. Ingredients List:**": "* Fillet of beef\n* Olive oil\n* Salt\n* Pepper",
    "**3. Steps for Preparation:**": "1. Sear the beef fillet\n2. Brush with mustard",
    "**4. Cooking Techniques Used:**": "* Searing\n* Wrapping",
    "**5. Equipment Needed:**": "* Hot pan\n* Blender",
    "**6. Nutritional Information:**": "High in protein and fat",
    "**7. Serving size:**": "2-4 people",
    "**8. Special Notes or Variations:**": "Use horseradish instead of mustard",
    "**9. Festive or Thematic Relevance:**": "Christmas alternative to roast turkey"
}
```

---

## 🛠️ Key Features

- **Deepgram API** for accurate audio transcription.
- **Tesseract OCR** for extracting text from video frames.
- **Gemini API** for generating structured recipe information.
- **FFmpeg** for seamless MP4-to-WAV conversion.
- Supports both audio and video analysis for enhanced accuracy. 🎯

---

## 🧪 Testing

Use tools like **Postman** or **curl** to test the API endpoints.

---

## 🤝 Contributions

Contributions are welcome! Feel free to submit a pull request or open an issue for any enhancements or bug fixes.

---

## 📄 License

This project is licensed under the MIT License.

---

### 🌟 Happy Coding and Bon Appétit! 👨‍🍳👩‍🍳


Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference