Problem D / I
GreenLeaf
- Verdict
- Accepted
- Stack
- Python · FastAPI · PostgreSQL
- Links
- GitHub repository ↗
Statement
GreenLeaf is a two-agent agentic advisory system built for smallholder farmers. A conversation agent works with the farmer to build a costed season plan, while a monitor agent runs on a schedule to re-check live weather forecasts and market conditions, adjusting committed plans automatically as conditions change. Every output is grounded in real data sources: a live weather API, a RAG knowledge base, crop disease detection, and market price data, so recommendations stay trustworthy rather than speculative.
Subtasks
- 01
Conversational Planning Agent
Builds a costed, personalized season plan for the farmer through natural conversation.
- 02
Autonomous Monitor Agent
Runs on a schedule to re-check live forecasts and market data, adjusting committed plans automatically.
- 03
Grounded Real-Data Outputs
Combines a live weather API, a RAG knowledge base, crop disease detection, and market price data for every recommendation.
- 04
LangGraph Orchestration
Multi-agent workflows coordinated with LangGraph for reliable, stateful agent behavior.
Constraints
-
Python
Versatile, readable programming language widely used for backend development, data science, automation, and machine learning.
-
FastAPI
High-performance Python web framework for building APIs with automatic validation and interactive documentation.
-
PostgreSQL
Advanced open-source relational database known for reliability, extensibility, and standards compliance.
Next problem E
SignOLight