Update app.py

app.py

@@ -69,14 +69,48 @@ def analisi_finanziaria(query, k=3):
     result = pipe(final_prompt)[0]['generated_text']
     return result
     
+import gradio as gr
+
+# Examples from your thesis
+examples = [
+    "Elon Musk created a new political party",
+    "Trump imposes tariffs",
+    "Tesla announces a new affordable electric vehicle model",
+    "Nvidia releases new GPU technology",
+    "Apple launches Apple TV+ subscription service"
+]
+
+description_md = """
+# GRPO Financial Analyst
+
+This tool analyzes financial events using a retrieval-augmented **language model**.
+
+**How it works:**
+- The model leverages historical events and news to provide predictions.
+- For each input, similar past events are retrieved to give context.
+- The output includes:
+  - **Chosen Stocks**: stocks likely impacted
+  - **Prediction**: expected price change (Up, Down, Neutral)
+  - **Explanation**: brief reasoning based on historical context
+
+**Example use cases:**
+- Market reactions to political events
+- Corporate announcements and earnings reports
+- Technological product launches
+
+Click an example below to quickly test the model.
+"""
+
+# Create Gradio interface
 iface = gr.Interface(
-    fn=analisi_finanziaria,
-    inputs=gr.Textbox(label="Enter event"),
+    fn=analisi_finanziaria,  # your actual function
+    inputs=gr.Textbox(label="Enter financial event", placeholder="Type an event here..."),
     outputs=gr.Textbox(label="Prediction"),
     title="GRPO Financial Analyst",
-    description="Enter a financial event, the GRPO model will analyze historical context and provide a prediction."
+    description=description_md,
+    examples=[[e] for e in examples],
+    allow_flagging="never"
 )
 
-
 iface.launch()