Datasets:
Download code/sec4_3_improvements/coding_agents/coding_agent_eval.sh from afs07fda89sdfas90/data: direct link, hf CLI and curl.
- Browser
- Download file 1.14 kB
-
https://huggingface.co/datasets/afs07fda89sdfas90/data/resolve/main/code/sec4_3_improvements/coding_agents/coding_agent_eval.sh
- Command line
-
hf download hf://datasets/afs07fda89sdfas90/data/code/sec4_3_improvements/coding_agents/coding_agent_eval.sh
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curl -L -o coding_agent_eval.sh https://huggingface.co/datasets/afs07fda89sdfas90/data/resolve/main/code/sec4_3_improvements/coding_agents/coding_agent_eval.sh
1.14 kB
| # Codex (GPT-5.4) as a full agentic harness on the direct images. | |
| # Requires OPENAI_API_KEY in the environment. | |
| : "${OPENAI_API_KEY:?Set OPENAI_API_KEY before running}" | |
| # Run from the repo root (data and result paths are root-relative) | |
| cd "$(dirname "$0")/../.." | |
| for img in data/combined_output/*_occluded.png; do | |
| id=$(basename "$img" _occluded.png) | |
| # Skip if already evaluated | |
| if [ -f "data/eval_results_coding_agent/${id}.json" ]; then | |
| echo "Skipping $id (already done)" | |
| continue | |
| fi | |
| is_physical=$(python3 -c " | |
| import json | |
| with open('data/combined_output/annotations.json') as f: | |
| entries = json.load(f) | |
| entry = next((e for e in entries if e['id'] == '$id'), None) | |
| print(entry.get('physical', False) if entry else False) | |
| ") | |
| if [ "$is_physical" = "True" ]; then | |
| codex exec --model gpt-5.4 --full-auto --sandbox workspace-write --ephemeral \ | |
| "Look at the image at $img. What is the primary object that is completely occluded in this image? Be as specific as you can. Write your answer to data/eval_results_coding_agent/${id}.json as {\"id\": \"$id\", \"response\": \"<your answer>\"}." | |
| fi | |
| done |