ENVOApp

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  This is our dashboard for environment chatbot

Inspiration

The growing need for accessible and practical environmental information, coupled with the desire to empower individuals to make informed, sustainable choices in their daily lives, inspired the creation of ENVOApp. We wanted to bridge the gap between complex environmental issues and actionable steps anyone can take.

What it does

ENVOApp empowers users to embrace a more sustainable lifestyle by offering:

• ** Interactive Quiz:** Tests and expands environmental knowledge.
• ** Eco-Friendly Alternatives:** Provides curated, practical alternatives to common items.
• ** AI-Powered EcoBot:** Answers user questions about sustainability.

How we built it

ENVOApp was built using:

• Streamlit: For rapid prototyping and interactive web interface.
• Google Gemini API: (or other LLM provider) For natural language understanding in the EcoBot.
• Python: For application logic and data processing.

Challenges we ran into

• Balancing AI Accuracy and Scope: Ensuring EcoBot provided accurate and helpful responses while covering a broad range of topics.
• Designing an Engaging User Experience: Creating a user interface that is both informative and fun to interact with.
• Rate Limit Issues: Handling of the rate limit on Google's Gemini API calls.
• Discovering Correct Model Names: Determining which model to call to allow for API access

Accomplishments that we're proud of

• Developing a functional and user-friendly application that integrates diverse environmental information into a single platform.
• Successfully implementing the AI-powered EcoBot feature.
• Creating a well-structured and engaging quiz to motivate users in their environmental journey.

What we learned

• The power of prompt engineering in eliciting quality responses from LLMs.
• The importance of user-centered design in creating effective educational tools.
• The challenges and rewards of integrating complex AI models into a web application.

What's next for ENVOApp

• Expanding the Knowledge Base: Adding more eco-alternatives, sustainability tips, and information to the EcoBot's data.
• Personalized Recommendations: Implementing a system to provide customized suggestions based on user quiz results and interests.
• Community Features: Adding a forum or social component to allow users to connect and share their sustainability journeys.
• Carbon Footprint Tracking: Integrating a tool to allow users to estimate and track their environmental impact.

Built With

• api
• gemini
• llm
• python
• streamlit