Transform your decision-making journey into an exhilarating adventure responsibly with AIGuru – the Guru of All Creative Assistants!
Inspiration
In the domain of AI, decision-making is a crucial part. Many times, we need to choose between 2 different options, some examples are
- Shall I eat a burger or a pizza? 🍔 🍕
- Shall I go to the gym or play a game? 🏋️ ⚽️
- Shall I buy a car or a bike? 🚗 🏍️
- Shall I invest in stocks or mutual funds? 📉 💵
- Shall I go for a movie or a party? 🎬 🍾
and many more small and big decisions. The AIGuru 🤖 is such a tool that helps in making decisions by providing the best possible solution to a problem along with suited explanation. No matter how important or trivial the decision is, AIGuru 🤖 will help you make the best decision, responsibly.
Our Key Inspiration was also to utilize AWS Partyrock to implement a practical aspect of Responsible AI, for which we drew motivation from following research paper 📝
What it does
- AIGuru 🤖 analyses the User's Input, which usually are just 2 options to choose from, seperated by
; - Then it asks user to provide answer to follow-up questions ❓ that it generates, by understanding options, in a few words.
- User can answer as many questions as they want, in like a word or a phrase, and when they are done, they can ask AIGuruChat the same options. 💬
- AIGuruChat will then provide the best possible solution to the problem along with suited explanation 🤔, that it draws from answers and follow-up questions.
- Finally, AiGuruImageGenerator provides a visual representation of the decision made by AIGuruChat 🌄, to motivate user to take action.
- Moreover, AIGuruChat, can give you answers and explanations in multiple languages ⽂, as it is powered by Claude Model
How we built it
- We used AWS Partyrock to implement AIGuru, AIGuruChat and AIGuruImageGenerator 💻
- We used Claude Model to provide answers and explanations in multiple languages 🧠
- We used StableDiffusion XL for Image Generation 🌄
The benefit of AWS Partyrock are,
- It provides a no-code interface to deploy powerful AI models provided by AWS Bedrock and 3rd party model providers
- Give it the problem statement, and AWS Partyrock, provides necessary widgets and prompt boilerplates to start with
- It provides with necessary UI components to interact with AI models
- It also provides with a sharable Link to share and showcase project, thus making Generative AI, accessible to everyone
Challenges we ran into
- We had to learn how to use AWS Partyrock, as it was our first time using it 💻
- We had to tune models a bit (temperature & top-p), but thanks to AWS Partyrock, it was easy to do so 🛠️
- We had to write proper prompts, to get desired answers from AI models 💬
Accomplishments that we're proud of
- We are proud of the fact that we were able to implement a practical aspect of Responsible AI, by utilizing AWS Partyrock ⛑️
- We are proud of the fact that we were able to provide a tool that helps in making decisions by providing the best possible solution to a problem along with suited explanation ❓
- We are proud of the fact that we were able to provide a tool that can give you answers and explanations in multiple languages and generate visual representation of the decision made ⽂
- We are proud to do all this without writing a single line of code, thanks to AWS Partyrock 📜
What we learned
- We learned how to use AWS Partyrock 💻
- We learned about Responsible AI ⛑️
- We learned about Generative AI 👾
- We learned about AWS Bedrock and 3rd party model providers
What's next for AI Guru
- We plan to introduce more models to analyze answers to AIGuru follow-up questions, and cumulatively provide the best possible solution to the problem along with suited explanation
- We plan to introduce more language support to AIGuruChat
- Sometimes, AIGuruImageGenerator, changes visual representation based on AIGuruChat's language, we plan to fix that

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