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README.md
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sdk: docker
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pinned: false
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license: mit
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short_description:
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---
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-
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sdk: docker
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pinned: false
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license: mit
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short_description: It transforms unstructured recipe videos into structured
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---
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---
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# 📝 **Flask Audio and YouTube Video Processing API**
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A Flask-based API that processes audio files and YouTube video transcripts to generate structured recipe information. It utilizes Whisper, Deepgram, and Gemini APIs for transcription and data extraction.
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## 🚀 **Overview**
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This API offers:
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1. **Audio Processing**: Download and transcribe audio files.
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2. **YouTube Transcription**: Extract transcripts from YouTube videos.
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3. **Recipe Data Generation**: Generate detailed recipe data using Gemini API.
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---
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## 🧩 **Features**
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- **Audio URL Processing**: Download and transcribe audio via Deepgram.
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- **YouTube Video Processing**: Extract video transcripts and process them.
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- **Structured Output**: Recipe name, ingredients, steps, techniques, and more.
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- **Logging and Error Handling**: Debugging and comprehensive error responses.
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---
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## ⚙️ **Installation**
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### 1. Clone the Repository
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```bash
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git clone https://github.com/your-repo-name.git
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cd your-repo-name
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```
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### 2. Create a Virtual Environment
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```bash
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python -m venv venv
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source venv/bin/activate # Windows: venv\Scripts\activate
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```
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### 3. Install Dependencies
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```bash
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pip install -r requirements.txt
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```
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### 4. Configure Environment Variables
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Create a `.env` file with 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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---
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## 📡 **API Endpoints**
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### ✅ Health Check
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**GET /**
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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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### 🎧 Process Audio URL
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**POST /process-audio**
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- **Request**:
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```json
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{
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"audioUrl": "https://example.com/audio.wav"
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}
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```
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- **Response**:
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```json
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{
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"structured_data": {
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"Recipe Name": "Pasta Alfredo",
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"Ingredients List": ["Pasta", "Cream", "Garlic"],
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...
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}
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}
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```
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### 📹 Process YouTube Video
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**POST /process-youtube**
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- **Request**:
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```json
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{
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"youtube_url": "https://www.youtube.com/watch?v=example"
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}
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```
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- **Response**:
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```json
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{
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"structured_data": {
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"Recipe Name": "Grilled Cheese Sandwich",
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"Ingredients List": ["Bread", "Cheese", "Butter"],
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...
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}
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}
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```
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---
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## 🛠️ **How It Works**
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1. **Audio Processing**:
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- Downloads the audio file.
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- Transcribes using Deepgram.
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- Sends the transcription to Gemini for structured data.
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2. **YouTube Processing**:
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- Extracts the video ID.
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- Retrieves the transcript.
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- Sends the transcript to Gemini for structured data.
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---
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## 📦 **Dependencies**
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- **Flask**
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- **Whisper**
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- **Deepgram**
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- **Google Gemini API**
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- **YouTube Transcript API**
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- **Requests**
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- **Dotenv**
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Install dependencies via:
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```bash
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pip install -r requirements.txt
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```
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---
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## ▶️ **Run the Application**
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1. **Activate Virtual Environment**:
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```bash
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source venv/bin/activate # Windows: venv\Scripts\activate
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```
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2. **Run the Flask App**:
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```bash
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python app.py
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```
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3. **Access**:
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```
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http://localhost:5000
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```
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---
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## 🐞 **Error Handling**
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- **API Key Errors**: Ensure `.env` contains valid API keys.
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- **Invalid Input**: Returns 400 for missing URLs.
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- **Transcription Errors**: Returns detailed error messages.
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---
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## 📝 **License**
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MIT License.
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---
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## 👤 **Contributors**
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- **Aniket**
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---
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💬 **Feedback or contributions?** Open an issue or submit a pull request!
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Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
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