changed filename gradio_app.py to app.py

app.py

@@ -0,0 +1,60 @@
+import gradio as gr
+import requests
+
+API_URL = "http://127.0.0.1:8000/api/predict"
+
+def analyze_text(text):
+    try:
+        response = requests.post(API_URL, json={"text": text})
+        if response.status_code == 200:
+            result = response.json()
+            sentiment = result.get("sentiment", "")
+            emotion = result.get("emotion", "")
+            return f"➡️ **Sentiment:** {sentiment}\n\n ➡️ **Emotion:** {emotion}"
+        else:
+            return f"API Error: {response.status_code}"
+    except Exception as e:
+        return f"Error connecting to API: {str(e)}"
+
+custom_css = """
+.gradio-container {
+    background: linear-gradient(135deg, #e9f1fc 0%, #fefefe 100%);
+    font-family: 'Segoe UI', Roboto, sans-serif;
+}
+h1 {
+    text-align: center !important;
+    font-size: 2.2rem !important;
+    color: #1f2937 !important;
+    font-weight: 600 !important;
+}
+textarea, .output_text {
+    font-size: 1.1rem !important;
+    line-height: 1.6 !important;
+}
+.output_text {
+    background: #f9fafb !important;
+    border-radius: 12px !important;
+    padding: 16px !important;
+    border: 1px solid #e5e7eb !important;
+}
+"""
+
+with gr.Blocks(css=custom_css, theme=gr.themes.Soft()) as demo:
+    gr.Markdown("# 💬 Emotion & Sentiment Analyzer")
+    gr.Markdown("### Type your text below to discover its emotional tone and sentiment ✨")
+
+    with gr.Row():
+        text_input = gr.Textbox(
+            label="Enter text here",
+            placeholder="e.g. I'm so excited to work on this project!",
+            lines=4,
+            scale=2
+        )
+    with gr.Row():
+        output_box = gr.Markdown(label="Results", elem_classes="output_text")
+
+    analyze_button = gr.Button("🔍 Analyze", variant="primary")
+
+    analyze_button.click(fn=analyze_text, inputs=text_input, outputs=output_box)
+
+demo.launch()