Update app.py

app.py

@@ -6,6 +6,7 @@ import os
 
 import gradio as gr
 from huggingface_hub import CommitScheduler
+from transformers import pipeline
 
 # Setup the directory for saving data
 JSON_DATASET_DIR = Path("feedback_dataset")
@@ -23,22 +24,43 @@ scheduler = CommitScheduler(
     token=os.getenv('hf_write')
 )
 
+# Initialize Sentiment Analysis Pipeline
+sentiment_pipeline = pipeline("sentiment-analysis")
+
+# Function to analyze sentiment
+def analyze_sentiment(user_input: str):
+    result = sentiment_pipeline(user_input)[0]
+    sentiment = result['label']
+    confidence = result['score']
+    return sentiment, confidence
+
 # Function to save data
-def save_feedback(name: str, feedback: str) -> None:
+def save_feedback(user_input: str, sentiment: str, confidence: float) -> None:
     with scheduler.lock:
         with JSON_DATASET_PATH.open("a") as f:
             json.dump(
-                {"name": name, "feedback": feedback, "datetime": datetime.now().isoformat()}, f
+                {
+                    "review": user_input,
+                    "sentiment": sentiment,
+                    "confidence": confidence,
+                    "datetime": datetime.now().isoformat(),
+                },
+                f,
             )
             f.write("\n")
     scheduler.push_to_hub(commit_message="Add new feedback")
 
 # Gradio Interface
+def handle_feedback(user_input):
+    sentiment, confidence = analyze_sentiment(user_input)
+    save_feedback(user_input, sentiment, confidence)
+    return f"Sentiment: {sentiment}, Confidence: {confidence:.2f}"
+
 with gr.Blocks() as demo:
     with gr.Row():
-        name_input = gr.Textbox(label="Name")
-        feedback_input = gr.Textbox(label="Feedback")
-    submit_button = gr.Button("Submit")
-    submit_button.click(fn=save_feedback, inputs=[name_input, feedback_input], outputs=None)
+        user_input = gr.Textbox(label="Enter Your Review", placeholder="Type your review here...")
+        output = gr.Textbox(label="Analysis Result", interactive=False)
+    submit_button = gr.Button("Analyze and Save")
+    submit_button.click(fn=handle_feedback, inputs=user_input, outputs=output)
 
 demo.launch()