Project Name: Text Recommendation
DevPost Project Link: Text Recommendation | Devpost
Project Website : Text Recommendation | on render
Project Test Note : Please note that due to certain limitations, the initial page load may take up to 50 seconds, and the system can handle a maximum of 30 requests per minute.
Project Repo : text-recommendation | Github
Project Video : Text Recommendation | Youtube
Project Images :
Project Goal : The primary goal of the Text Recommendation app is to address the common challenge of finding the right words in various communication scenarios, whether it’s for crafting a client email, initiating a chat with a colleague, or maintaining an appropriate tone. By providing AI-driven, style-specific suggestions, the app aims to reduce the anxiety and uncertainty around written communication, enabling users to convey their messages confidently and effectively. Additionally, it allows users to learn from the recommendations, enhancing their communication skills.
Project Details:
Overview
Text Recommendation is an app designed to help users craft professional and effective communication by providing tailored text suggestions based on sentiment analysis. It offers options in different styles (business formal, casual) and includes tones translation capabilities, enabling users to learn from the recommendations to improve their communication skills.
Features
- Sentiment Analysis: Analyzes incoming text to understand tone and context and generates reply suggestions in different styles (formal, casual, etc.) to suit various communication scenarios.
- Initiation Suggestions: Offers suggestions for initiating a chat or email with a chosen recipient (Client, Superior, etc.), based on the selected tone.
- Tone Translation: Translates the tone of the text, helping users adjust their message to be more formal or casual as needed.
- Learning Component: Enables users to improve communication skills by learning from the recommended replies.
Technology Stack
The project is built using Ruby on Rails, Bootstrap, StimulusJs, SambaNova, and hosted on render.com.
Functionality
The app evaluates incoming texts and generates suitable responses based on sentiment and style preferences. Users receive multiple suggestions for different tones, or they can learn to craft better responses. The app also provides initiation suggestions, helping users start a chat or email with a chosen recipient in the desired tone. Additionally, it includes a tone translation feature, allowing users to adjust the formality of their text as needed.
Target Audience
The app is ideal for professionals, businesses, and individuals who need assistance in crafting clear, effective, and appropriately toned communication.
Accomplishments that we’re proud of
We’re proud to have developed a robust working prototype and successfully integrated the SambaNova Cloud with the Llama 3 model. This achievement highlights our ability to harness cutting-edge AI technologies, paving the way for advanced text recommendation features and seamless performance.
What’s Next for Text Recommendation
- Expanding query parameters to provide more versatile and tailored text recommendations, accommodating various communication scenarios.
- Optimizing the AI model to enhance consistency and reliability in generating responses, ensuring more accurate and effective suggestions.
- Enhance the visual design for a more intuitive user experience.