Upload root_scripts/make_val_parquet.py with huggingface_hub

root_scripts/make_val_parquet.py

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+
+import json, pandas as pd, os
+
+src = "/workspace/rl4phyx/RL4Phyx/SFT/sft_eval_footprint/inference_results_base.jsonl"
+with open(src) as f:
+    lines = [json.loads(l) for l in f if l.strip()]
+
+# Use absolute path for test images
+IMAGE_BASE = "/workspace/rl4phyx/RL4Phyx/MetaPhyX/test_images"
+
+rows = []
+for r in lines:
+    idx = r.get("index", 0)
+    cat = r.get("category", "unknown")
+    subfield = r.get("subfield", "")
+    gt_value = str(r.get("ground_truth_value", "")).strip()
+    question = r.get("question", "")
+    
+    prompt_text = f"Look at the image and answer the physics question.\n\n{question}\n\nPlease reason step by step and put your final answer (with units if applicable) in \\boxed{{}}."
+    
+    # Use absolute path for image
+    abs_image_path = os.path.join(IMAGE_BASE, f"{idx}.png")
+    
+    row = {
+        "data_source": "metaphyx_physics",
+        "prompt": [{"content": prompt_text, "role": "user"}],
+        "ability": "physics",
+        "reward_model": {"ground_truth": gt_value, "style": "rule"},
+        "extra_info": {
+            "category": cat,
+            "subfield": subfield,
+            "index": idx,
+            "image_path": abs_image_path,
+            "split": "test",
+        },
+    }
+    rows.append(row)
+
+df = pd.DataFrame(rows)
+
+out_path = "/workspace/rl4phyx/RL4Phyx/oneshot/validation_data/metaphyx_oe_1533.parquet"
+df.to_parquet(out_path, index=False)
+
+# Verify
+df2 = pd.read_parquet(out_path)
+print(f"Saved: {out_path}")
+print(f"Shape: {df2.shape}")
+# Check first image exists
+img0 = df2.iloc[0]["extra_info"]["image_path"]
+print(f"First image: {img0}")
+print(f"Exists: {os.path.exists(img0)}")
+# Check a few more
+for i in [0, 100, 500, 1000, 1532]:
+    ip = df2.iloc[i]["extra_info"]["image_path"]
+    print(f"  [{i}] {os.path.basename(ip)}: exists={os.path.exists(ip)}")