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import polars as pl |
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import sys |
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import json |
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from tqdm import tqdm |
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labelmap = {"E": 1.0, "S": 0.1, "C": 0.01, "I": 0.0} |
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split = sys.argv[3] |
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products = ( |
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pl.read_parquet(sys.argv[1]) |
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.filter((pl.col("product_locale") == "us")) |
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.with_columns( |
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pl.concat_str( |
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[ |
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pl.col("product_title"), |
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pl.col("product_description"), |
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pl.col("product_bullet_point"), |
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pl.col("product_brand"), |
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pl.col("product_color"), |
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], |
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separator=" ", |
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ignore_nulls=True, |
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).alias("text") |
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) |
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.select(pl.col("product_id", "text")) |
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) |
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examples = ( |
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pl.read_parquet(sys.argv[2]) |
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.filter( |
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(pl.col("product_locale") == "us") |
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& (pl.col("small_version") == 1) |
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& (pl.col("split") == split) |
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) |
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.with_columns( |
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pl.col("esci_label").replace(labelmap).alias("score").cast(pl.Float64) |
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) |
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.select(pl.col("query_id", "query", "product_id", "score")) |
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) |
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merged = examples.join(products, on="product_id", how="left") |
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print(merged) |
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result = merged.group_by("query_id").agg( |
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pl.first("query"), pl.col("text"), pl.col("score") |
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) |
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def save_json(df: pl.DataFrame, path: str): |
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with open(path, "w") as f: |
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for row in tqdm(result.to_dicts(), desc=f"saving {path}"): |
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query = row["query"] |
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pos = [] |
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neg = [] |
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negscore = [] |
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for doc, score in zip(row["text"], row["score"]): |
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if score == 1.0: |
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pos.append(doc) |
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else: |
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neg.append(doc) |
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negscore.append(score) |
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for p in pos: |
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line = json.dumps( |
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{"query": query, "pos": p, "neg": neg, "negscore": negscore} |
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) |
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f.write(line + "\n") |
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save_json(result, f"{split}.jsonl") |
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