This project is a production-ready AI agent built for the Meta OpenEnv Hackathon. The agent competes in a 3-round coding challenge against an OpenAI GPT-4o-mini judge, receiving Python coding tasks and submitting solutions for evaluation.
Agent: inference.py
The core agent logic lives entirely in inference.py. It runs a 3-round loop that:
Calls the local OpenEnv server's /reset endpoint to fetch a new coding task
Sends the task to a powerful LLM to generate a Python solution
Submits the solution back to the /step endpoint and retrieves the score
API Payload Compatibility
The agent uses the exact payload format required by the Meta OpenEnv REST API:
{"action": {"answer": "<agent_answer>"}}
This nested structure matches the server's strict Pydantic model validation, completely preventing 422 Unprocessable Entity errors that arise from incorrect top-level keys or flat payload formats.
Model: Qwen/Qwen2.5-72B-Instruct
The agent uses Qwen/Qwen2.5-72B-Instruct via the Hugging Face Router API (https://router.huggingface.co/v1), accessed through an OpenAI-compatible client.
Key reasons for this choice:
The HF Router endpoint is the current active inference gateway — the legacy api-inference.huggingface.co/v1 endpoint has been deprecated and returns 410 Gone errors
