filter bug solved

_test.ipynb

@@ -2,7 +2,7 @@
  "cells": [
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 49,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -46,53 +46,8 @@
     "    distances, indices = nbrs.kneighbors([product]) #input the vector of the reference object\n",
     "\n",
     "    #print out the description of every recommended product\n",
-    "    return df.iloc[list(indices)[0]][['name', 'raised', 'target', 'size', 'stage', 'country', 'source', 'description', 'tags']]"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 47,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "c:\\Users\\ardit\\AppData\\Local\\Programs\\Python\\Python39\\lib\\site-packages\\gradio\\deprecation.py:43: UserWarning: You have unused kwarg parameters in Radio, please remove them: {'multiselect': False}\n",
-      "  warnings.warn(\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Running on local URL:  http://127.0.0.1:7887\n",
-      "\n",
-      "To create a public link, set `share=True` in `launch()`.\n"
-     ]
-    },
-    {
-     "data": {
-      "text/html": [
-       "<div><iframe src=\"http://127.0.0.1:7887/\" width=\"100%\" height=\"500\" allow=\"autoplay; camera; microphone; clipboard-read; clipboard-write;\" frameborder=\"0\" allowfullscreen></iframe></div>"
-      ],
-      "text/plain": [
-       "<IPython.core.display.HTML object>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "text/plain": []
-     },
-     "execution_count": 47,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
+    "    return df.iloc[list(indices)[0]][['name', 'raised', 'target', 'size', 'stage', 'country', 'source', 'description', 'tags']]\n",
+    "\n",
     "def filter_df(df, column_name, filter_type, filter_value, minimum_acceptable_size=0):\n",
     "    if filter_type == '==':\n",
     "        df_filtered = df[df[column_name]==filter_value]\n",
@@ -106,8 +61,15 @@
     "    if df_filtered.size >= minimum_acceptable_size:\n",
     "        return df_filtered\n",
     "    else:\n",
-    "        return df\n",
-    "\n",
+    "        return df"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
     "#the first module becomes text1, the second module file1\n",
     "def greet(size, target, stage, query): \n",
     "    def raised_zero(x):\n",
@@ -118,20 +80,20 @@
     "    df_knn = search(df, query)\n",
     "    df_knn['raised'] = df_knn['raised'].apply(lambda x : raised_zero(x))\n",
     "\n",
-    "    df_size = filter_df(df_knn, 'size', '==', size, 1000)\n",
-    "    df_target = filter_df(df_size, 'target', 'contains', target, 20)\n",
-    "\n",
+    "    df_target = filter_df(df_knn, 'target', 'contains', target, 500)\n",
     "    if stage != 'ALL':\n",
-    "        df_stage = filter_df(df_target, 'stage', '==', stage.lower(), 10)\n",
+    "        df_stage = filter_df(df_target, 'stage', '==', stage.lower(), 40)\n",
     "    else:\n",
     "        #we bypass the filter\n",
     "        df_stage = df_target\n",
+    "\n",
+    "    df_size = filter_df(df_stage, 'size', '==', size, 20)\n",
     "    \n",
     "    # display(df_stage)\n",
     "    # df_raised = df_target[(df_target['raised'] >= raised) | (df_target['raised'] == 0)]\n",
     "\n",
     "    #we live the sorting for last\n",
-    "    return df_stage[0:100].sort_values('raised', ascending=False)\n",
+    "    return df_size[0:100] #.sort_values('raised', ascending=False)\n",
     "\n",
     "with gr.Blocks(theme=gr.themes.Soft(primary_hue='amber', secondary_hue='gray', neutral_hue='amber')) as demo:\n",
     "    gr.Markdown(\n",

app.py

@@ -1,6 +1,6 @@
 import os
-os.system('pip install openpyxl')
-os.system('pip install sentence-transformers')
+# os.system('pip install openpyxl')
+# os.system('pip install sentence-transformers')
 import pandas as pd
 import gradio as gr
 from sentence_transformers import SentenceTransformer
@@ -65,20 +65,20 @@ def greet(size, target, stage, query):
     df_knn = search(df, query)
     df_knn['raised'] = df_knn['raised'].apply(lambda x : raised_zero(x))
 
-    df_size = filter_df(df_knn, 'size', '==', size, 1000)
-    df_target = filter_df(df_size, 'target', 'contains', target, 20)
-
+    df_target = filter_df(df_knn, 'target', 'contains', target, 5000)
     if stage != 'ALL':
-        df_stage = filter_df(df_target, 'stage', '==', stage.lower(), 10)
+        df_stage = filter_df(df_target, 'stage', '==', stage.lower(), 40)
     else:
         #we bypass the filter
         df_stage = df_target
+
+    df_size = filter_df(df_stage, 'size', '==', size, 0)
     
     # display(df_stage)
     # df_raised = df_target[(df_target['raised'] >= raised) | (df_target['raised'] == 0)]
 
     #we live the sorting for last
-    return df_stage[0:100] #.sort_values('raised', ascending=False)
+    return df_size[0:100] #.sort_values('raised', ascending=False)
 
 with gr.Blocks(theme=gr.themes.Soft(primary_hue='amber', secondary_hue='gray', neutral_hue='amber')) as demo:
     gr.Markdown(