Create a DIY text analysis app

app.py

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+import gradio as gr
+import numpy as np
+from textblob import TextBlob
+
+def analyze_text(text):
+    if not text:
+        return "Please enter some text to analyse.", 0, 0, 0
+
+    blob = TextBlob(text)
+
+    sentiment = blob.sentiment.polarity
+
+    word_count = len(split(text))
+    char_count = len(text)
+
+    avg_word_length = char_count / word_count
+
+    return {
+        "sentiment_score": round(sentiment, 2),
+        "word_count": word_count,
+        "char_count": char_count,
+        "avg_word_length": rount(avg_word_length, 2)
+    }
+
+with gr.Blocks() as demo:
+    gr.Markdown("# Text Analysis App")
+    gr.Markdown("Enter some text to analyze its sentiment and get basic statistics.")
+
+    with gr.Row():
+        text_input = gr.TextBox(
+            label = "Input Text",
+            placeholder = "Type your text here...",
+            lines = 5,
+        )
+
+    with gr.Row():
+        analyse_button = gr..Button("Analyze")
+
+    with gr.Row():
+        sentiment_output = gr.Number(label="Sentiment Score (-1 to 1)")
+        word_count_output = gr.Number(label="Word Count")
+        char_count_output = gr.Number("Character Count")
+        avg_length_output = gr.Number(label = "Average Word Length")
+
+    analyze_button.click(
+        fn=analyse_text,
+        inputs=text_input,
+        outputs=[
+            sentiment_output,
+            word_count_output,
+            char_count_output,
+            avg_length_output
+        ]
+    )
+
+if __name__ == '__main__':
+    demo.launch():

requirements.txt

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+textblob
+numpy