changes

2_gradio.ipynb

@@ -78,14 +78,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 25,
+   "execution_count": 55,
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Running on local URL:  http://127.0.0.1:7869\n",
+      "Running on local URL:  http://127.0.0.1:7894\n",
       "\n",
       "To create a public link, set `share=True` in `launch()`.\n"
      ]
@@ -93,7 +93,7 @@
     {
      "data": {
       "text/html": [
-       "<div><iframe src=\"http://127.0.0.1:7869/\" width=\"100%\" height=\"500\" allow=\"autoplay; camera; microphone; clipboard-read; clipboard-write;\" frameborder=\"0\" allowfullscreen></iframe></div>"
+       "<div><iframe src=\"http://127.0.0.1:7894/\" width=\"100%\" height=\"500\" allow=\"autoplay; camera; microphone; clipboard-read; clipboard-write;\" frameborder=\"0\" allowfullscreen></iframe></div>"
       ],
       "text/plain": [
        "<IPython.core.display.HTML object>"
@@ -106,16 +106,20 @@
      "data": {
       "text/plain": []
      },
-     "execution_count": 25,
+     "execution_count": 55,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "source": [
-    "with gr.Blocks() as demo:\n",
-    "    \n",
-    "    txt = gr.Textbox(value='A Christmas present🎄for my 5 years old Kid!!!', label='What are you looking for?')\n",
-    "    btn = gr.Button(value=\"Search Product\")\n",
+    "with gr.Blocks(theme=gr.themes.Soft(primary_hue='amber', secondary_hue='gray', neutral_hue='amber')) as demo:\n",
+    "    # gr.Markdown(\n",
+    "    # \"\"\"\n",
+    "    # Try our AI Product Recommendation DEMO!!!\n",
+    "    # \"\"\"\n",
+    "    # )\n",
+    "    txt = gr.Textbox(value='A Christmas present🎄for my 5 years old Kid!!!', label='Try our AI Product Recommendation DEMO!!!')\n",
+    "    btn = gr.Button(value=\"Search for Product\")\n",
     "    state = gr.Dataframe()\n",
     "    # btn.click(greet, inputs='text', outputs=['dataframe'])\n",
     "    btn.click(greet, [txt], [state])\n",

app.py

@@ -15,7 +15,7 @@ model = SentenceTransformer('all-mpnet-base-v2') #all-MiniLM-L6-v2 #all-mpnet-ba
 df = pd.read_parquet('df_encoded.parquet')
 
 #prepare model
-nbrs = NearestNeighbors(n_neighbors=5, algorithm='ball_tree').fit(df['text_vector_'].values.tolist())
+nbrs = NearestNeighbors(n_neighbors=4, algorithm='ball_tree').fit(df['text_vector_'].values.tolist())
 
 def search(df, query):
     product = model.encode(query).tolist()
@@ -34,8 +34,13 @@ def greet(text1):
     return search(df, text1)
 
 with gr.Blocks(theme=gr.themes.Soft(primary_hue='amber', secondary_hue='gray', neutral_hue='amber')) as demo:
+    gr.Markdown(
+    """
+    # Try our AI Product Recommendation DEMO!!!
+    """
+    )
     txt = gr.Textbox(value='A Christmas present🎄for my 5 years old Kid!!!', label='What are you looking for?')
-    btn = gr.Button(value="Search Product")
+    btn = gr.Button(value="Search for Product")
     state = gr.Dataframe()
     # btn.click(greet, inputs='text', outputs=['dataframe'])
     btn.click(greet, [txt], [state])