Upload merge_texts_and_scores.py

merge_texts_and_scores.py

@@ -0,0 +1,56 @@
+
+import json
+from pathlib import Path
+
+import pandas as pd
+
+
+def read_jsonl_into_df(
+    path_to_jsonl: Path,
+) -> pd.DataFrame:
+    """
+    Read a JSONL file into a pandas DataFrame.
+
+    Args:
+        path_to_jsonl (Path): Path to the JSONL file.
+
+    Returns:
+        pd.DataFrame: DataFrame containing the data from the JSONL file.
+    """
+    with open(path_to_jsonl, "r", encoding="utf-8") as f:
+        lines = [json.loads(line) for line in f if line.strip() if line != "\n"]
+    return pd.DataFrame(lines)
+
+
+def merge_texts_and_scores(
+    path_to_text_jsonl: Path,
+    path_to_scores_jsonl: Path,
+    path_to_output_jsonl: Path,
+) -> None:
+    """
+    Merge texts and scores from two JSONL files into a single JSONL file.
+
+    Args:
+        path_to_text_jsonl (Path): Path to the JSONL file containing texts.
+        path_to_scores_jsonl (Path): Path to the JSONL file containing scores.
+        path_to_output_jsonl (Path): Path to the output JSONL file.
+    """
+    texts_df = read_jsonl_into_df(path_to_text_jsonl)
+    scores_df = read_jsonl_into_df(path_to_scores_jsonl)
+    
+    # Merge the DataFrames on the "id" column
+    merged_df = pd.merge(texts_df, scores_df, on="id", how="inner")
+
+    # Write the merged DataFrame to the output JSONL file
+    with open(path_to_output_jsonl, "w", encoding="utf-8") as output_file:
+        for _, row in merged_df.iterrows():
+            output_file.write(json.dumps(row.to_dict()) + "\n")
+
+
+if __name__ == "__main__":
+    # Example usage
+    merge_texts_and_scores(
+        path_to_text_jsonl=Path("/path/to/fineweb_2_500k_both_deduplicated/mlt_Latn_sampled_500k.jsonl"),
+        path_to_scores_jsonl=Path("/path/to/annotations/adult_content/mlt_Latn_sampled_500k_gemma-3-27b-it_aggregated_scores_majority.jsonl"),
+        path_to_output_jsonl=Path("/path/to/output_dir/mlt_Latn_sampled_500k_gemma-3-27b-it_aggregated_scores_majority_merged.jsonl")
+    )