Service Tone Track

A Basic HTTP Server for Tracking Sentiment of Text Data.

Website: https://tone-track.uno

Cross-platform mobile application: Tone Track

Email: [email protected]

   

📖 Description

Service Tone Track is a heavyweight HTTP server designed to track the sentiment of text data.

Leveraging the power of the NLTK and Transformers libraries, this service provides a straightforward way to analyze the sentiment of any given text.

🌐 Features

• sentiment analysis service: Accurately determines the sentiment (positive, negative, neutral) of the input text.
• flutter app: A Mobile app that integrates with this service to provide sentiment analysis and handle user diary entries.
• slack app: The Slack App that integrates with this service to provide sentiment analysis for Slack messages.
• web interface: A simple web interface that allows users to interact with the sentiment analysis service.

Models supported only english language for now:

• VADER: A rule-based sentiment analysis tool that is specifically attuned to sentiments expressed in social media.
• BERT: A transformer model that is fine-tuned to perform sentiment analysis on text data.

Tone Track - A diary application that analyzes entries based on sentiment analysis, helping users track and understand their emotional states over time.

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🛠️ Installation instructions and running the server on your local machine

To install the required dependencies, run the following commands:

chmod +x ./generate_env.sh;
./generate_env.sh;
docker compose --file user-setup.yml up -d

When the server is up and running, you can access the API at localhost:80

Replace <YOUR API KEY FROM .env FILE volume> with the API key from the .env file in the root directory.

curl --location 'http://0:80/api/v1/sentiment-analysis' \
--header 'Content-Type: application/json' \
--header 'Authorization: <YOUR API KEY FROM .env FILE volume>' \
--data '{"text": "Your hard work is noticed, and it brings results!", "sentiment_type": "vader"}'

A successful response will look like this:

{"text":"Your hard work is noticed, and it brings results!","sentiment_result":"negative"}

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📩 Demo integration and running your Slack App on local machine

To integrate the Slack App with the service, you need to create a Slack App and install it on your workspace.

1. Create a new Slack App here and select from scratch.
2. Navigate to the OAuth & Permissions section and add the following scopes:

Bot Token Scopes:

• chat:write
• chat:write.public
• channels:read
• commands

User Token Scopes:

• channels:history

Install the app to your workspace by Install to Workspace button.

4. Add the following environment variables to the .env file in the root directory:

• SLACK_SIGNING_SECRET - your Slack App's signing secret from the Basic Information section.
• SLACK_BOT_OAUTH_TOKEN - your Slack App's bot token from the OAuth & Permissions section.

5. Run the following command to expose the local server to the internet:

Ngrok is required to expose the local server to the internet.

Required environment variable:

• NGROK_AUTHTOKEN - your Ngrok auth token from here

docker run --net=host -it -e NGROK_AUTHTOKEN=YOUR_NGROK_AUTH_TOKEN ngrok/ngrok:latest http 80

6. Navigate to the Interactivity & Shortcuts section of the Slack and add the following request URL:

Replace YOUR_NGROK_SUBDOMAIN with your Ngrok subdomain.

Example: https://0154-95-160-47-60.ngrok-free.app/api/v1/slack/interactions

https://YOUR_NGROK_SUBDOMAIN.ngrok-free.app/api/v1/slack/interactions

7. Navigate to the Enable Events section and add the following request URL:

Replace YOUR_NGROK_SUBDOMAIN with your Ngrok subdomain.

https://YOUR_NGROK_SUBDOMAIN.ngrok.io/api/v1/slack/events

Note: trouble with save button, look at the Slack Forum for more information.

8. Navigate to the Slash Commands section and create a new commands:

Replace YOUR_NGROK_SUBDOMAIN with your Ngrok subdomain.

I: Add | Update sentiment analysis message to channel

    - Command: /tt-add-message
    - Request URL: https://YOUR_NGROK_SUBDOMAIN.ngrok.io/api/v1/slack/commands
    - Short Description: Add | Update sentiment analysis message to channel

Replace YOUR_NGROK_SUBDOMAIN with your Ngrok subdomain.

II: Retrieve sentiment analysis message from channel

    - Command: /tt-read-message
    - Request URL: https://YOUR_NGROK_SUBDOMAIN.ngrok.io/api/v1/slack/commands
    - Short Description: Retrieve sentiment analysis message from channel

Well done! You have successfully integrated the Slack App with service.

You can now test the app by sending negative message in channel and bot identifies the sentiment and reply to you.

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📦 Deployment

Kubernetes

To deploy the service to Kubernetes cluster, you can use the Helm chart provided in the devops/helm directory.

For detailed instructions, refer to the Helm README.

Docker Compose (cloud instance)

Alternatively, if you are using Docker Compose, you can deploy the service using the user-setup.yml file provided in the root directory.

SSL certificate are required to configure the Slack App. You can generate them using this guide and modify user-setup.yml and nginx files.

Don't forget to update configuration settings by new URL in the Slack App settings after deployment.

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📄 License

This project is licensed under the Apache License - see the LICENSE file for details.

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