Create app.py

app.py

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+# main
+
+import gradio as gr
+import textstat
+import matplotlib.pyplot as plt
+
+def evaluate_text_details(text):
+    details = {
+        "Number of Sentences": textstat.sentence_count(text),
+        "Number of Words": textstat.lexicon_count(text, removepunct=True),
+        "Number of Syllables": textstat.syllable_count(text),
+        "Number of Characters": sum(len(word) for word in text.split()),
+        "Number of Complex Words": textstat.difficult_words(text),
+        "Percentage of Complex Words": round((textstat.difficult_words(text) / max(textstat.lexicon_count(text, removepunct=True), 1)) * 100, 3),
+        "Average Syllables per Word": round(textstat.syllable_count(text) / max(textstat.lexicon_count(text, removepunct=True), 1), 3),
+        "Average Words per Sentence": round(textstat.lexicon_count(text, removepunct=True) / max(textstat.sentence_count(text), 1),3),
+    }
+    
+    readability_scores = {
+        "Flesch Reading Ease": textstat.flesch_reading_ease(text),
+        "Flesch-Kincaid Grade Level": textstat.flesch_kincaid_grade(text),
+        "Gunning Fog Index": textstat.gunning_fog(text),
+        "Automated Readability Index (ARI)": textstat.automated_readability_index(text),
+        "SMOG Index": textstat.smog_index(text),
+        "Coleman-Liau Index": textstat.coleman_liau_index(text),
+        "Dale-Chall Readability Score": textstat.dale_chall_readability_score(text)
+    }
+
+    return details, readability_scores
+
+def plot_bar_chart(data, title, ylabel):
+    plt.figure(figsize=(6, 4))
+    plt.barh(list(data.keys()), list(data.values()), color='skyblue')
+    plt.xlabel(ylabel)
+    plt.title(title)
+    plt.grid(axis='x', linestyle='--', alpha=0.6)
+    plt.tight_layout()
+
+    plot_filename = f"{title.replace(' ', '_')}.png"
+    plt.savefig(plot_filename)
+    plt.close()
+    return plot_filename
+
+def analyze_text(text):
+    details, readability_scores = evaluate_text_details(text)
+    
+    stats_chart = plot_bar_chart(details, "Text Statistics", "Count")
+    readability_chart = plot_bar_chart(readability_scores, "Readability Scores", "Score")
+    
+    return details, readability_scores, stats_chart, readability_chart
+
+# Explanation text to be displayed above the input box
+explanation_text = """
+### Readability Score Descriptions:
+- **Flesch Reading Ease**: A higher score means the text is easier to read.
+- **Flesch-Kincaid Grade Level**: Indicates the US school grade required to understand the text.
+- **Gunning Fog Index**: Estimates the number of years of formal education needed.
+- **Automated Readability Index (ARI)**: Similar to Flesch-Kincaid but uses a different formula.
+- **SMOG Index**: Designed for healthcare and scientific texts.
+- **Coleman-Liau Index**: Uses character count instead of syllables.
+- **Dale-Chall Readability Score**: Considers familiar words to determine readability.
+"""
+
+# Sample text
+sample_text = """This is an example text. It is used to demonstrate how readability scores work.
+          The quick brown fox jumps over the lazy dog. Readability metrics help in understanding
+          how easy or difficult a text is to read."""
+
+# Create Gradio Blocks Interface
+with gr.Blocks(title="Text Readability Analyzer") as app:
+    gr.Markdown("## Text Readability Analyzer")
+
+    with gr.Row():
+        with gr.Column(scale=1):  # Left Panel (Input & Explanation)
+            gr.Markdown(explanation_text)
+            text_input = gr.Textbox(lines=5, placeholder="Enter your text here...")
+            gr.Markdown("### Example Text")
+            example_btn = gr.Button("Use Example Text")
+
+        with gr.Column(scale=1):  # Right Panel (Output Results)
+            text_details_output = gr.JSON(label="Text Details")
+            readability_scores_output = gr.JSON(label="Readability Scores")
+            stats_chart_output = gr.Image(label="Text Statistics Chart")
+            readability_chart_output = gr.Image(label="Readability Scores Chart")
+
+    
+    # Function to handle button click
+    def load_example():
+        return sample_text
+
+    example_btn.click(load_example, outputs=text_input)
+    
+    # Link input to function outputs
+    text_input.change(
+        analyze_text,
+        inputs=text_input,
+        outputs=[text_details_output, readability_scores_output, stats_chart_output, readability_chart_output]
+    )
+
+# Launch the app
+app.launch()