Text Recommendation

Inspiration

We've all experienced the struggle of finding the right words for a client email, starting a conversation with a colleague, or striking the perfect balance between formality and informality. Text Recommendation aims to alleviate this common communication challenge.

What it does

The app analyzes incoming texts and generates tailored responses based on sentiment and style preferences. Users can choose from multiple tone options or learn to create better replies. It also offers suggestions for starting conversations or emails in a desired tone and includes a tone translation feature to adjust text formality. By leveraging these recommendations, users can improve their communication skills effectively.

Target Audience The app is ideal for professionals, businesses, and individuals who need assistance in crafting clear, effective, and appropriately toned communication.

How we built it

We combined a robust tech stack, including Ruby on Rails , SambaNova , Bootstrap , StimulusJs , Llama3 , and render.com , to bring Text Recommendation to life.

Challenges we ran into

Maintaining consistency in AI-generated responses was a significant challenge. We plan to refine this through further model tuning.

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

• Enhance the visual design for a more intuitive user experience.
• Expanding query parameters for more versatile text recommendations.
• Optimizing the AI model to deliver more consistent and reliable responses.

Built With

• ajax
• bootstrap
• javascript
• llama3
• postgresql
• render
• ruby
• ruby-on-rails
• sambanova