refactor: remove batch translation code

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

app.py

@@ -3,11 +3,8 @@ Translation interface using the MADLAD-400 3B model.
 Translates English text to 22 production-ready languages from the MADLAD-400 paper.
 """
 
-import csv
-import tempfile
 import warnings
 from functools import lru_cache
-from pathlib import Path
 
 import gradio as gr
 import spaces
@@ -83,93 +80,6 @@ def translate(
     return result
 
 
-def _parse_input_file(file_path: str) -> tuple[list[str], list[dict] | None]:
-    """Parse a .txt or .csv file into a list of texts to translate.
-
-    Returns (texts, original_data). original_data is None for .txt files,
-    or a list of row dicts for .csv files (used to preserve extra columns in output).
-    """
-    path = Path(file_path)
-    ext = path.suffix.lower()
-
-    if ext == ".txt":
-        texts = [line for line in path.read_text().splitlines() if line.strip()]
-        return texts, None
-
-    if ext == ".csv":
-        with open(path, newline="") as f:
-            reader = csv.DictReader(f)
-            if reader.fieldnames is None or "text" not in reader.fieldnames:
-                raise ValueError("CSV file must have a 'text' column.")
-            rows = list(reader)
-        texts = [row["text"] for row in rows]
-        return texts, rows
-
-    raise ValueError(f"Unsupported file type: {ext}. Use .txt or .csv.")
-
-
-def _write_output_file(translations: list[str], original_data: list[dict] | None, ext: str) -> str:
-    """Write translation results to a temp file and return its path."""
-    if ext == ".txt":
-        f = tempfile.NamedTemporaryFile(mode="w", suffix=".txt", delete=False)
-        f.write("\n".join(translations))
-        f.close()
-        return f.name
-
-    # CSV: append translation column to original data
-    f = tempfile.NamedTemporaryFile(mode="w", suffix=".csv", delete=False, newline="")
-    assert original_data is not None
-    fieldnames = list(original_data[0].keys()) + ["translation"]
-    writer = csv.DictWriter(f, fieldnames=fieldnames)
-    writer.writeheader()
-    for row, translation in zip(original_data, translations):
-        row["translation"] = translation
-        writer.writerow(row)
-    f.close()
-    return f.name
-
-
-def _build_table_data(texts: list[str], translations: list[str], original_data: list[dict] | None) -> dict:
-    """Build a dict with headers and data for gr.Dataframe display."""
-    if original_data is None:
-        return {"headers": ["source", "translation"], "data": [[t, tr] for t, tr in zip(texts, translations)]}
-    headers = list(original_data[0].keys()) + ["translation"]
-    data = [[row[k] for k in original_data[0].keys()] + [tr] for row, tr in zip(original_data, translations)]
-    return {"headers": headers, "data": data}
-
-
-@spaces.GPU
-def translate_batch(
-    file,
-    target_language_name: str,
-    max_new_tokens: int = 512,
-    num_beams: int = 1,
-    temperature: float = 1.0,
-    progress=gr.Progress(),
-) -> tuple[dict, str]:
-    if file is None:
-        raise gr.Error("Please upload a file first.")
-
-    file_path = file.name if hasattr(file, "name") else str(file)
-    ext = Path(file_path).suffix.lower()
-    texts, original_data = _parse_input_file(file_path)
-
-    if not texts:
-        raise gr.Error("File is empty or contains no text to translate.")
-
-    if num_beams > 1 and temperature != 1.0:
-        gr.Info("Temperature has no effect when beam search is enabled (num_beams > 1).")
-
-    translations = []
-    for i, text in enumerate(progress.tqdm(texts, desc="Translating")):
-        result = translate(text, target_language_name, max_new_tokens, num_beams, temperature)
-        translations.append(result)
-
-    output_path = _write_output_file(translations, original_data, ext)
-    table_data = _build_table_data(texts, translations, original_data)
-    return table_data, output_path
-
-
 def _build_demo() -> gr.Blocks:
     _, language_names = _build_language_mappings()
 
@@ -228,24 +138,6 @@ def _build_demo() -> gr.Blocks:
                         inputs=[input_text, target_language],
                     )
 
-                with gr.Tab("Batch"):
-                    with gr.Row():
-                        batch_input = gr.File(
-                            label="Upload file (.txt, one sentence per line, or .csv with 'text' column)",
-                            file_types=[".txt", ".csv"],
-                        )
-                        batch_output = gr.File(label="Download translations", interactive=False)
-
-                    batch_btn = gr.Button("Translate", variant="primary")
-
-                    batch_preview = gr.Dataframe(label="Preview", interactive=False)
-
-                    batch_btn.click(
-                        fn=translate_batch,
-                        inputs=[batch_input, target_language, max_new_tokens, num_beams, temperature],
-                        outputs=[batch_preview, batch_output],
-                    )
-
     return demo