alindor_task

Flask Application for sentiment analysis

This Flask application allows users to upload audio files, which are then processed to extract text using Deepgram's speech-to-text service. The extracted text undergoes sentiment analysis via OpenAI's API, providing insights into the emotional tone of the dialogue within the audio file. This document outlines how to set up, run, and deploy the application.

Prerequisites

Before you begin, ensure you have the following:

1. Python 3.8 or later installed on your machine.
2. Docker should be installed for containerization and deployment.
3. A Google Cloud account for deployment with Google Cloud Run.
4. OpenAI API key for sentiment analysis.
5. Deepgram API key for speech-to-text conversion.

Install requirements.txt file to create a python environment installed with the mentioned libraries, command to install the requirements.txt file - python -m pip install -r requirements.txt --no-cache-dir

Usage

1. Uploading Audio Files: Use the web interface to upload audio files. The application will process the files, perform speech-to-text conversion, and then analyze the sentiment of the extracted text.

2. API Endpoints: The application also provides REST API endpoints for uploading audio files and retrieving results programmatically. (Detail these endpoints based on your implementation.)

Local Setup

Step 1: Clone the Repository

1. git clone https://github.com/viper-108/alindor_task.git
2. cd alindor_task

Step 2: Install Dependencies

python -m pip install -r requirements.txt --no-cache-dir

Step 3: Set Environment Variables

OPENAI_API_KEY=your_openai_api_key_here DEEPGRAM_API_KEY=your_deepgram_api_key_here FLASK_SECRET_KEY=your_flask_secret_key_here

Step 4: Run the Application

flask run