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"""
Batch Analysis Page for Vietnamese Sentiment Analysis
"""
import gradio as gr
import pandas as pd
from io import StringIO
def create_batch_analysis_page(app_instance):
"""Create the batch analysis tab"""
def analyze_batch(texts):
"""Analyze sentiment for multiple texts"""
if not texts or not any(text.strip() for text in texts):
return "❌ Please enter some texts to analyze."
if not app_instance.model_loaded:
return "❌ Model not loaded. Please refresh the page."
# Filter valid texts
valid_texts = [text.strip() for text in texts if text.strip()]
if len(valid_texts) > 10:
return "❌ Too many texts. Maximum 10 texts per batch for memory efficiency."
if not valid_texts:
return "❌ No valid texts provided."
try:
results, error_msg = app_instance.batch_predict(valid_texts)
if error_msg:
return error_msg
if not results:
return "❌ No results generated. Please try again."
# Create a summary table
df_data = []
for result in results:
sentiment_emoji = {
"Positive": "😊",
"Neutral": "😐",
"Negative": "😠"
}.get(result["sentiment"], "❓")
df_data.append({
"Text": result["text"][:100] + ("..." if len(result["text"]) > 100 else ""),
"Sentiment": f"{sentiment_emoji} {result['sentiment']}",
"Confidence": f"{result['confidence']:.2%}",
"Processing Time": f"{result['processing_time']:.3f}s"
})
df = pd.DataFrame(df_data)
# Create summary statistics
sentiment_counts = df["Sentiment"].value_counts()
avg_confidence = sum(r["confidence"] for r in results) / len(results)
total_time = sum(r["processing_time"] for r in results)
summary = f"""
## 📊 Batch Analysis Results
**Summary Statistics:**
- Total texts analyzed: {len(results)}
- Average confidence: {avg_confidence:.2%}
- Total processing time: {total_time:.3f}s
- Average time per text: {total_time/len(results):.3f}s
**Sentiment Distribution:**
{sentiment_counts.to_string()}
### Detailed Results:
"""
# Convert DataFrame to markdown
table_md = df.to_markdown(index=False)
return summary + "\n" + table_md
except Exception as e:
app_instance.cleanup_memory()
return f"❌ Error during batch analysis: {str(e)}"
def clear_batch():
"""Clear batch inputs"""
return ""
# Batch Analysis Tab
with gr.Tab("📊 Batch Analysis"):
gr.Markdown("### 📝 Memory-Efficient Batch Processing")
gr.Markdown("**Maximum batch size:** 10 texts (for memory efficiency)")
gr.Markdown("**Memory limit:** 8GB")
with gr.Row():
with gr.Column(scale=2):
batch_input = gr.Textbox(
label="Enter Multiple Texts (one per line)",
placeholder="Enter text 1...\nEnter text 2...\nEnter text 3...",
lines=10,
max_lines=15
)
with gr.Row():
batch_analyze_btn = gr.Button("📊 Analyze Batch", variant="primary")
batch_clear_btn = gr.Button("🗑️ Clear All", variant="secondary")
with gr.Column(scale=3):
batch_result_output = gr.Markdown(label="Batch Analysis Result")
# Connect events
batch_analyze_btn.click(
fn=analyze_batch,
inputs=[batch_input],
outputs=[batch_result_output]
)
batch_clear_btn.click(
fn=clear_batch,
outputs=[batch_input]
)
return batch_analyze_btn, batch_clear_btn, batch_input, batch_result_output |