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Update app.py
Browse filesworking for 1 url
app.py
CHANGED
@@ -118,20 +118,14 @@ def classify_website(url):
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urls = [url]
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print(urls)
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results_shop = main(urls)
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# Convert results to DataFrame
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df_result_train_more = pd.DataFrame(results_shop)
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print(df_result_train_more)
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text = df_result_train_more['text'][0]
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try:
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translated = GoogleTranslator(source='auto', target='en').translate(text[:4990])
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# except:
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# Prepare the input prompt for the model
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prompt = f"""Below is an instruction that describes a task, paired with an input that provides further context. Write a response that appropriately completes the request.
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### Instruction:
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@@ -161,38 +155,14 @@ Categorize the website into one of the 3 categories:
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logging.exception(e)
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return str(e)
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def classify_urls_from_csv(csv_file):
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# Read CSV file and extract URLs from the first column
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df = pd.read_csv(csv_file)
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df.iloc[:, 0] = df.iloc[:, 0].str.replace(';', '').str.strip()
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urls = df.iloc[:, 0].tolist()
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# Classify each URL and store the results
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predictions = []
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for url in urls:
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prediction = classify_website(url)
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predictions.append(prediction)
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# Add predictions as a new column in the dataframe
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df['Prediction'] = predictions
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# Save the results to a new CSV file
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output_file = "predictions.csv"
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df.to_csv(output_file, index=False)
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return output_file
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# Create a Gradio interface
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iface = gr.Interface(
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fn=
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inputs=
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outputs=
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title="Website Categorization",
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description="
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)
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# Launch the interface
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iface.launch()
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urls = [url]
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results_shop = main(urls)
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# Convert results to DataFrame
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df_result_train_more = pd.DataFrame(results_shop)
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text = df_result_train_more['text'][0]
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translated = GoogleTranslator(source='auto', target='en').translate(text[:4990])
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try:
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# Prepare the input prompt for the model
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prompt = f"""Below is an instruction that describes a task, paired with an input that provides further context. Write a response that appropriately completes the request.
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### Instruction:
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logging.exception(e)
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return str(e)
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# Create a Gradio interface
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iface = gr.Interface(
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fn=classify_website,
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inputs="text",
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outputs="text",
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title="Website Categorization",
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description="Categorize a website into one of the 3 categories: OTHER, NEWS/BLOG, or E-commerce."
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)
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# Launch the interface
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iface.launch()
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