Update index.py

index.py

@@ -1,24 +1,75 @@
 import transformers
 from flask import Flask, request, jsonify
 from transformers import RobertaTokenizerFast, TFRobertaForSequenceClassification, pipeline
+import gradio as gr
+import pandas as pd
+import numpy as np
+import matplotlib.pyplot as plt
+import io
+from io import BytesIO  # Import BytesIO for image generation
 
-app = Flask(__name__)
-
-# Load model and tokenizer once at app startup
+# Load model and tokenizer
 tokenizer = RobertaTokenizerFast.from_pretrained("arpanghoshal/EmoRoBERTa")
 model = TFRobertaForSequenceClassification.from_pretrained("arpanghoshal/EmoROBERTa")
 emotion = pipeline("sentiment-analysis", model="arpanghoshal/EmoROBERTa")
 
-@app.route("/analyze_sentiment", methods=["POST"])
-def analyze_sentiment():
-    data = request.get_json()
-    phrase = data.get("phrase")
+def analyze_csv(file):
+    try:
+        # Print file content for debugging
+        file_content = file.read()
+        print("File content:", file_content)
+
+        # Reset file position to the beginning
+        file.seek(0)
+
+        # Read the CSV file into a DataFrame
+        df = pd.read_csv(io.BytesIO(file_content))``
+        print("DataFrame shape:", df.shape)  # Print DataFrame shape for debugging
+        print("DataFrame columns:", df.columns)  # Print DataFrame columns for debugging
+
+        # Check if the DataFrame is empty
+        if df.empty:
+            return "Empty file. Please upload a CSV file with data.", None
+
+        # Check if the expected column "phrase" is present in the DataFrame
+        if "phrase" not in df.columns:
+            return "Column 'phrase' not found in the CSV file. Please check the file format.", None
+
+        phrases = df["phrase"]
+
+        # Analyze sentiment for each phrase
+        emotion_labels = emotion(phrases)
+
+        # Create summary statistics
+        summary_df = pd.DataFrame(emotion_labels).describe()
+
+        # Create a bar chart of emotion distribution
+        plt.figure()
+        emotion_counts = emotion_labels.get("labels").value_counts()
+        emotion_counts.plot(kind="bar")
+        plt.title("Emotion Distribution")
+        plt.xlabel("Emotion")
+        plt.ylabel("Count")
+
+        # Generate PNG image of the chart
+        chart_img = BytesIO()
+        plt.savefig(chart_img, format="png")
+        chart_img.seek(0)
+
+        return summary_df.to_json(), chart_img.read()
+
+    except Exception as e:
+        error_message = f"Error processing the CSV file: {str(e)}"
+        print(error_message)  # Print the error message for debugging
+        return error_message, None
+
 
-    if phrase:
-        emotion_labels = emotion(phrase)
-        return jsonify({"emotion_labels": emotion_labels})
-    else:
-        return jsonify({"error": "Missing phrase"}), 400
+iface = gr.Interface(
+    fn=analyze_csv,
+    inputs=[gr.File(label="Upload CSV File")],
+    outputs=["dataframe", "image"],
+    title="Emotion Analyzer with CSV",
+    description="Analyzes sentiment and creates charts/tables from a CSV file.",
+)
 
-if __name__ == "__main__":
-    app.run(debug=True)  # Set debug=False in production
+iface.launch()