Scaler-Hackathon / openenv.yaml
jeevank0
Final Submission
bd57080
environment:
name: farmrl-phase1
version: 0.1.0
description: Minimal FarmRL OpenEnv implementation for Round-1 Phase-1.
api:
reset: POST /reset
step: POST /step
state: GET /state
defaults:
API_BASE_URL: https://api.openai.com/v1
MODEL_NAME: gpt-4o-mini
TASK_NAME: farm-yield-optimization
BENCHMARK: farmrl
PORT: 7860
observation_schema:
type: object
required:
- soil_moisture
- soil_ph
- temperature
- rainfall
- crop_stage
- day
properties:
soil_moisture:
type: number
minimum: 0
maximum: 100
soil_ph:
type: number
minimum: 4
maximum: 9
temperature:
type: number
rainfall:
type: number
minimum: 0
crop_stage:
type: integer
minimum: 0
day:
type: integer
minimum: 0
action_schema:
type: object
required:
- water
- fertilizer
- pesticide
properties:
water:
type: number
minimum: 0
maximum: 50
fertilizer:
type: number
minimum: 0
maximum: 20
pesticide:
type: number
minimum: 0
maximum: 10
reward_schema:
type: number
description: yield_score + sustainability_bonus - resource_penalty
tasks:
- id: task_easy_yield
difficulty: easy
description: Maximize agronomic yield performance using normalized total reward.
- id: task_medium_chemical_efficiency
difficulty: medium
description: Minimize total fertilizer and pesticide while maintaining productivity.
- id: task_hard_sustainability_balance
difficulty: hard
description: Optimize the long-term yield-to-chemical-use balance ratio.