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README.md
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pinned: false
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license: mit
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short_description: Structure recipe information from videos
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---
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Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
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pinned: false
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license: mit
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short_description: Structure recipe information from videos
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---
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# π½οΈ Recipe Extraction API
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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. π
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---
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## π¦ Project Setup
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Follow these steps to set up and run the project on your local machine.
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### 1οΈβ£ Clone the Repository
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```bash
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git clone <your-repo-url>
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cd <your-repo-folder>
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```
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### 2οΈβ£ Install Dependencies
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Make sure you have Python installed (Python 3.8 or above is recommended). Install the required libraries using pip:
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```bash
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pip install -r requirements.txt
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```
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### 3οΈβ£ Install Tesseract OCR
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Ensure **Tesseract OCR** is installed on your system. You can download it here: [Tesseract GitHub](https://github.com/tesseract-ocr/tesseract)
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Add Tesseract to your system path and make sure to note its installation location.
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#### On Windows:
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Add the path to `tesseract.exe` to your environment variables, e.g.:
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```bash
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C:\Program Files\Tesseract-OCR
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```
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#### On MacOS (using Homebrew):
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```bash
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brew install tesseract
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```
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#### On Ubuntu:
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```bash
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sudo apt-get install tesseract-ocr
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```
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### 4οΈβ£ Setup Environment Variables
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Create a `.env` file in the root directory and add your API keys:
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```plaintext
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FIRST_API_KEY=<Your Gemini API Key>
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SECOND_API_KEY=<Your Deepgram API Key>
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```
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### 5οΈβ£ Install FFmpeg
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This project uses **FFmpeg** for converting MP4 videos to WAV audio. Install it via the following:
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#### On MacOS (using Homebrew):
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```bash
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brew install ffmpeg
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```
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#### On Ubuntu:
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```bash
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sudo apt-get install ffmpeg
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```
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#### On Windows:
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Download FFmpeg from [FFmpeg.org](https://ffmpeg.org/download.html) and add it to your system path.
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---
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## π Running the Project
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Start the Flask server with the following command:
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```bash
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python app.py
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```
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If everything is set up correctly, you should see:
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```plaintext
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* Running on http://127.0.0.1:5000/
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```
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---
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## π‘ API Endpoints
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### β
Health Check
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**Endpoint:** `GET /`
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Check if the API is running.
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```bash
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curl http://127.0.0.1:5000/
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```
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**Response:**
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```json
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{
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"status": "success",
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"message": "API is running successfully!"
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}
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```
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### π² Recipe Extraction
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**Endpoint:** `POST /process-video`
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#### Request Body:
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Send a JSON payload with a video URL:
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```json
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{
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"videoUrl": "<URL-of-the-cooking-video>"
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}
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```
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#### Example Using `curl`:
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```bash
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curl -X POST http://127.0.0.1:5000/process-video \
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-H "Content-Type: application/json" \
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-d '{"videoUrl": "https://example.com/video.mp4"}'
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```
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#### Sample Response:
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```json
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{
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"**1. Recipe Name:**": "Beef Wellington",
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"**2. Ingredients List:**": "* Fillet of beef\n* Olive oil\n* Salt\n* Pepper",
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"**3. Steps for Preparation:**": "1. Sear the beef fillet\n2. Brush with mustard",
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"**4. Cooking Techniques Used:**": "* Searing\n* Wrapping",
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"**5. Equipment Needed:**": "* Hot pan\n* Blender",
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"**6. Nutritional Information:**": "High in protein and fat",
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"**7. Serving size:**": "2-4 people",
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"**8. Special Notes or Variations:**": "Use horseradish instead of mustard",
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"**9. Festive or Thematic Relevance:**": "Christmas alternative to roast turkey"
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}
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```
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---
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## π οΈ Key Features
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- **Deepgram API** for accurate audio transcription.
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- **Tesseract OCR** for extracting text from video frames.
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- **Gemini API** for generating structured recipe information.
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- **FFmpeg** for seamless MP4-to-WAV conversion.
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- Supports both audio and video analysis for enhanced accuracy. π―
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---
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## π§ͺ Testing
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Use tools like **Postman** or **curl** to test the API endpoints.
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---
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## π€ Contributions
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Contributions are welcome! Feel free to submit a pull request or open an issue for any enhancements or bug fixes.
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---
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## π License
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This project is licensed under the MIT License.
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---
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### π Happy Coding and Bon AppΓ©tit! π¨βπ³π©βπ³
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Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
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