# ๐ฑ FarmaBuddy โ AI Powered Smart Farming Assistant
**CRS Artificial Intelligence โ Formative Assessment 2
**Course:** Generative A.I
**Team:** Jashith Rathod, Nishtha Shah, Naman Shreshtha
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## ๐ Project Overview
FarmaBuddy is a Generative AI-powered web application built using **Streamlit** and **Google Gemini 1.5 API**.
The system provides region-specific, actionable farming advice to farmers in:
- ๐ฎ๐ณ India
- ๐ฌ๐ญ Ghana
- ๐จ๐ฆ Canada
The assistant formats AI responses clearly and includes reasoning behind each recommendation to improve farmer trust and usability.
This project transforms the FA-1 storyboard into a fully functional and deployed AI application.
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## ๐ฏ Intended Learning Outcomes Achieved
- โ Format and refine outputs generated by Gemini for clarity and real-world usability
- โ Evaluate and optimize model outputs using prompt engineering
- โ Deploy a working AI web application using Streamlit Cloud
- โ Implement user interaction monitoring and feedback collection
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## ๐ Live Deployment Link
๐ **Streamlit App URL:**
xdymq9ydmjn9xnab2qrigi.streโฆ
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## ๐ Technologies Used
- Python
- Streamlit
- Google Gemini 1.5 API
- Pandas
- GitHub
- Streamlit Cloud
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## ๐ Project Structure
FarmaBuddy/
โ
โโโ app.py
โโโ requirements.txt
โโโ README.md
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## ๐ฆ requirements.txt
streamlit
google-generativeai
requests
pandas
matplotlib
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## ๐ง Step 4 โ Output Formatting & Reasoning
To ensure clarity and usefulness:
- Gemini outputs are structured into bullet points.
- Each recommendation includes a justification (โwhyโ explanation).
- Technical language is simplified.
- Advice is region-aware and crop-stage specific.
### ๐ Example Prompt Tested
**Input:**
โWhat to grow in Rajasthan in August?โ
**Formatted Output:**
- **Pearl Millet** โ Drought-resistant and thrives in arid soil.
- **Cluster Bean** โ Suitable for sandy soil with low irrigation.
- **Green Gram** โ Short crop cycle fits monsoon season.
Each suggestion i โฆ