Update app.py

app.py

@@ -97,15 +97,15 @@ def retrieve_documents(query: str, top_k: int = 5):
             return pd.DataFrame(), "No results found."
 
         df = pd.DataFrame(results)
-        status = f"✅ Retrieved top {len(results)} documents."
+        status = f"Retrieved {len(results)} results"
         return df, status
 
     except Exception as e:
-        return pd.DataFrame(), f"⚠️ Error: {str(e)}"
+        return pd.DataFrame(), f"Error: {str(e)}"
 
 
 # =========================
-# Gradio Interface (VERTICAL)
+# Gradio Interface (SIMPLE & ELEGANT)
 # =========================
 SAMPLE_QUERIES = [
     "takhne me dard",
@@ -114,85 +114,93 @@ SAMPLE_QUERIES = [
     "vayiru vali",
     "छाती में दर्द",
     "talenovu",
-    "వాంతులు"
-    "ಕಾಮಲೆ", # jaundice
-    "பேசுவது சிரமம்", # Dysphasia 
-    "Peshab Kartaana Jalan", # Scalding pain on urination
+    "వాంతులు",
+    "ಕಾಮಲೆ",
+    "பேசுவது சிரமம்",
+    "Peshab Kartaana Jalan",
     "Kurunnal",
     "sunn hua",
     "moochithinaral",
     "মাথাব্যথা"
 ]
 
-with gr.Blocks(title="Parrotlet-e Retrieval", theme=gr.themes.Soft()) as demo:
+# Custom CSS for elegant styling
+custom_css = """
+.gradio-container {
+    max-width: 900px !important;
+    margin: auto !important;
+}
+footer {
+    display: none !important;
+}
+"""
 
-    # ---- Header ----
-    gr.Markdown(
-        """
-        <h1 style='text-align:center; color:#2b4162;'>🦜 Parrotlet-e Retrieval</h1>
-        <p style='text-align:center; font-size:16px; color:#555;'>
-        Multilingual Medical Embedding Search powered by <b>EkaCare's Parrotlet-e</b> model
-        </p>
-        <hr>
-        """,
-    )
+with gr.Blocks(title="Parrotlet-e", theme=gr.themes.Soft(), css=custom_css) as demo:
 
-    # ---- Model Description ----
     gr.Markdown(
         """
-        ### 🧠 Model Description
-        **Parrotlet-e: Indic Medical Entity Embedding Model**  
-        A multilingual embedding model designed to represent Indian medical terminology across multiple scripts and languages.
-
-        - 🔗 **Model on Hugging Face:** [ekacare/parrotlet-e](https://huggingface.co/ekacare/parrotlet-e)  
-        - 📊 **Benchmarked on:** [Eka-IndicMTEB](https://huggingface.co/datasets/ekacare/Eka-IndicMTEB)  
-        - 📰 Read more on our [blog](https://info.eka.care/services/introducing-parrotlet-e-and-eka-indicmteb-bridging-indias-multilingual-healthcare-gap)
-
-        ---
+        # Parrotlet-e
+        Multilingual medical term search across Indian languages
         """,
+        elem_classes="header"
     )
 
-    # ---- Input Section ----
-    with gr.Group():
-        query_input = gr.Textbox(
-            label="Enter a medical term (not sentences in any language)",
-            placeholder="Type your query here...",
-            lines=1,
-        )
-
-        examples = gr.Examples(
-            examples=SAMPLE_QUERIES,
-            inputs=query_input,
-            label="💡 Example Queries"
-        )
+    query_input = gr.Textbox(
+        label="Search medical term",
+        placeholder="Enter a medical term in any language...",
+        lines=1,
+        scale=4
+    )
 
-        top_k_input = gr.Number(
-            label="Number of results (K)",
+    with gr.Row():
+        top_k_input = gr.Slider(
+            label="Results",
+            minimum=1,
+            maximum=20,
             value=5,
-            precision=0,
-            interactive=True
+            step=1,
+            scale=1
         )
+        search_btn = gr.Button("Search", variant="primary", scale=1)
+
+    gr.Examples(
+        examples=SAMPLE_QUERIES,
+        inputs=query_input,
+        label="Try these examples"
+    )
 
-        search_btn = gr.Button("🔍 retrieve", variant="primary")
+    results_output = gr.Dataframe(
+        headers=["Rank", "Score", "Term", "ID"],
+        datatype=["number", "str", "str", "str"],
+        interactive=False,
+        wrap=True,
+        label="Results"
+    )
+    
+    # status_box = gr.Textbox(label="", interactive=False, show_label=False)
 
-    # ---- Output Section ----
-    with gr.Group():
-        results_output = gr.Dataframe(
-            headers=["Rank", "Score", "Term", "ID"],
-            datatype=["number", "str", "str", "str"],
-            interactive=False,
-            wrap=True,
-            label="📄 Search Results"
-        )
-        status_box = gr.Textbox(label="Status", interactive=False)
+    gr.Markdown(
+        """
+        ---
+        Model: [ekacare/parrotlet-e](https://huggingface.co/ekacare/parrotlet-e) | 
+        Benchmark: [Eka-IndicMTEB](https://huggingface.co/datasets/ekacare/Eka-IndicMTEB) | 
+        [Learn more](https://info.eka.care/services/introducing-parrotlet-e-and-eka-indicmteb-bridging-indias-multilingual-healthcare-gap)
+        """,
+        elem_classes="footer-links"
+    )
 
-    # ---- Function Binding ----
     search_btn.click(
         fn=retrieve_documents,
         inputs=[query_input, top_k_input],
         outputs=[results_output, status_box],
     )
 
+    query_input.submit(
+        fn=retrieve_documents,
+        inputs=[query_input, top_k_input],
+        outputs=[results_output],
+    )
+
 
 if __name__ == "__main__":
-    demo.launch(server_name="0.0.0.0", server_port=7860)
+    demo.launch(server_name="0.0.0.0", server_port=7860)