Update app.py

app.py

@@ -1,98 +1,62 @@
 import gradio as gr
 import pandas as pd
-import requests
 from io import BytesIO
 
-def convert_hf_dataset(input_file, file_url):
-    """
-    This function accepts either an uploaded file or a Hugging Face dataset URL.
-    It automatically determines the file type (CSV or Parquet) based on the file extension,
-    converts the file to the opposite format, and returns the converted file along with a preview
-    of the top 10 rows.
-    """
-    df = None
-    source = None
-    converted_format = None
-    output_file = None
-
-    # If no file is provided via upload and URL is empty, raise an error.
-    if input_file is None and (file_url is None or file_url.strip() == ""):
-        raise ValueError("Please provide an uploaded file or a Hugging Face dataset URL.")
-
-    if input_file is not None:
-        # Process the uploaded file.
-        source = input_file.name
-        file_extension = source.lower().split('.')[-1]
-        file_bytes = input_file.read()  # read the file content
-
-        if file_extension == "csv":
-            df = pd.read_csv(BytesIO(file_bytes))
-            converted_format = "Parquet"
-            output_file = "output.parquet"
-        elif file_extension == "parquet":
-            df = pd.read_parquet(BytesIO(file_bytes))
-            converted_format = "CSV"
-            output_file = "output.csv"
-        else:
-            raise ValueError("Uploaded file must have a .csv or .parquet extension.")
-    else:
-        # Process the URL input.
-        file_url = file_url.strip()
-        if "huggingface.co" not in file_url:
-            raise ValueError("Please provide a URL from Hugging Face datasets.")
-        if not file_url.lower().startswith(("http://", "https://")):
-            file_url = "https://" + file_url
+def convert_file(input_file, conversion_type):
+    # Check if a file was uploaded
+    if input_file is None:
+        raise ValueError("Please upload a file.")
 
-        source = file_url.split('/')[-1]
-        response = requests.get(file_url)
-        response.raise_for_status()
-        content = response.content
+    file_name = input_file.name
+    file_extension = file_name.lower().split('.')[-1]
+    file_bytes = input_file.read()
 
-        if file_url.lower().endswith(".csv"):
-            df = pd.read_csv(BytesIO(content))
-            converted_format = "Parquet"
-            output_file = "output.parquet"
-        elif file_url.lower().endswith(".parquet"):
-            df = pd.read_parquet(BytesIO(content))
-            converted_format = "CSV"
-            output_file = "output.csv"
-        else:
-            raise ValueError("The URL must point to a .csv or .parquet file.")
+    df = None
+    output_file = None
+    converted_format = None
 
-    # Convert the file: if CSV, convert to Parquet; if Parquet, convert to CSV.
-    if converted_format == "Parquet":
+    # Conversion: CSV to Parquet
+    if conversion_type == "CSV to Parquet":
+        if file_extension != "csv":
+            raise ValueError("For CSV to Parquet conversion, please upload a CSV file.")
+        df = pd.read_csv(BytesIO(file_bytes))
+        output_file = "output.parquet"
         df.to_parquet(output_file, index=False)
-    else:
+        converted_format = "Parquet"
+    # Conversion: Parquet to CSV
+    elif conversion_type == "Parquet to CSV":
+        if file_extension != "parquet":
+            raise ValueError("For Parquet to CSV conversion, please upload a Parquet file.")
+        df = pd.read_parquet(BytesIO(file_bytes))
+        output_file = "output.csv"
         df.to_csv(output_file, index=False)
+        converted_format = "CSV"
+    else:
+        raise ValueError("Invalid conversion type selected.")
 
-    # Create a preview (top 10 rows) of the DataFrame.
+    # Generate a preview of the top 10 rows
     preview = df.head(10).to_string(index=False)
     info_message = (
-        f"Input file: {source}\n"
+        f"Input file: {file_name}\n"
         f"Converted file format: {converted_format}\n\n"
         f"Preview (Top 10 Rows):\n{preview}"
     )
-
     return output_file, info_message
 
 demo = gr.Interface(
-    fn=convert_hf_dataset,
+    fn=convert_file,
     inputs=[
-        gr.File(label="Uploaded File (Optional)"),
-        gr.Textbox(
-            label="Hugging Face Dataset URL (Optional)",
-            placeholder="e.g., huggingface.co/datasets/username/dataset/filename.csv"
-        )
+        gr.File(label="Upload CSV or Parquet File"),
+        gr.Radio(choices=["CSV to Parquet", "Parquet to CSV"], label="Conversion Type")
     ],
     outputs=[
         gr.File(label="Converted File"),
         gr.Textbox(label="Preview (Top 10 Rows)", lines=15)
     ],
-    title="Hugging Face CSV <-> Parquet Converter",
+    title="CSV <-> Parquet Converter",
     description=(
-        "Upload a file or enter the URL of a Hugging Face dataset file. "
-        "The app automatically detects the file type (.csv or .parquet), converts it to the opposite format, "
-        "and displays a preview of the top 10 rows."
+        "Upload a CSV or Parquet file and select the conversion type. "
+        "The app converts the file to the opposite format and displays a preview of the top 10 rows."
     )
 )