{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "# !pip install sentence-transformers==2.0.0"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "c:\\Users\\ardit\\AppData\\Local\\Programs\\Python\\Python39\\lib\\site-packages\\torch\\onnx\\_internal\\_beartype.py:30: UserWarning: module 'beartype.roar' has no attribute 'BeartypeDecorHintPep585DeprecationWarning'\n",
      "  warnings.warn(f\"{e}\")\n"
     ]
    }
   ],
   "source": [
    "import pandas as pd\n",
    "from tqdm import tqdm\n",
    "from sentence_transformers import SentenceTransformer\n",
    "\n",
    "model = SentenceTransformer('all-mpnet-base-v2') #all-MiniLM-L6-v2 #all-mpnet-base-v2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.read_parquet('df_encoded.parquet')\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.neighbors import NearestNeighbors\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "\n",
    "from sentence_transformers import SentenceTransformer\n",
    "\n",
    "model = SentenceTransformer('all-mpnet-base-v2') #all-MiniLM-L6-v2 #all-mpnet-base-v2\n",
    "\n",
    "#prepare model\n",
    "# nbrs = NearestNeighbors(n_neighbors=8, algorithm='ball_tree').fit(df['text_vector_'].values.tolist())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>shortName</th>\n",
       "      <th>location</th>\n",
       "      <th>title</th>\n",
       "      <th>hourlyRate</th>\n",
       "      <th>avgFeedbackScore</th>\n",
       "      <th>description</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>3761</th>\n",
       "      <td>Steven F.</td>\n",
       "      <td>New York</td>\n",
       "      <td>Database Manger / Graphics / Social Media</td>\n",
       "      <td>35.0</td>\n",
       "      <td>4.939631</td>\n",
       "      <td>A highly skilled problem solver​ with over 10 ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>835</th>\n",
       "      <td>Jacquelyn N.</td>\n",
       "      <td>New York</td>\n",
       "      <td>Admin support specialist</td>\n",
       "      <td>12.0</td>\n",
       "      <td>4.920992</td>\n",
       "      <td>I am a Kansas City based Virtual Assistant. I ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2787</th>\n",
       "      <td>Mark H.</td>\n",
       "      <td>New York</td>\n",
       "      <td>WordPress Specialist - Development, Administra...</td>\n",
       "      <td>60.0</td>\n",
       "      <td>4.751762</td>\n",
       "      <td>Top Rated Plus | Specialize in WordPress | Inv...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3402</th>\n",
       "      <td>Carleton C.</td>\n",
       "      <td>New York</td>\n",
       "      <td>Expert freelancer with skills in Divi theme, C...</td>\n",
       "      <td>25.0</td>\n",
       "      <td>4.692159</td>\n",
       "      <td>For over 30 years, I have developed a wide ran...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1156</th>\n",
       "      <td>Andee F.</td>\n",
       "      <td>New York</td>\n",
       "      <td>Experienced Freelancer</td>\n",
       "      <td>15.0</td>\n",
       "      <td>4.645855</td>\n",
       "      <td>I have 8+ years of successfully providing admi...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1556</th>\n",
       "      <td>Laura O.</td>\n",
       "      <td>New York</td>\n",
       "      <td>Admin Expert with experience in Microsoft Suit...</td>\n",
       "      <td>30.0</td>\n",
       "      <td>4.620818</td>\n",
       "      <td>I have been passionate about my personal budge...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1002</th>\n",
       "      <td>Nicole H.</td>\n",
       "      <td>New York</td>\n",
       "      <td>Experienced admin support and customer support...</td>\n",
       "      <td>30.0</td>\n",
       "      <td>4.129972</td>\n",
       "      <td>I'm an experienced jack of all trades.  I have...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1626</th>\n",
       "      <td>Drew L.</td>\n",
       "      <td>New York</td>\n",
       "      <td>Front End Web Developer</td>\n",
       "      <td>50.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>Worked for agency with big name clients doing ...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         shortName  location  \\\n",
       "3761     Steven F.  New York   \n",
       "835   Jacquelyn N.  New York   \n",
       "2787       Mark H.  New York   \n",
       "3402   Carleton C.  New York   \n",
       "1156      Andee F.  New York   \n",
       "1556      Laura O.  New York   \n",
       "1002     Nicole H.  New York   \n",
       "1626       Drew L.  New York   \n",
       "\n",
       "                                                  title  hourlyRate  \\\n",
       "3761          Database Manger / Graphics / Social Media        35.0   \n",
       "835                            Admin support specialist        12.0   \n",
       "2787  WordPress Specialist - Development, Administra...        60.0   \n",
       "3402  Expert freelancer with skills in Divi theme, C...        25.0   \n",
       "1156                             Experienced Freelancer        15.0   \n",
       "1556  Admin Expert with experience in Microsoft Suit...        30.0   \n",
       "1002  Experienced admin support and customer support...        30.0   \n",
       "1626                            Front End Web Developer        50.0   \n",
       "\n",
       "      avgFeedbackScore                                        description  \n",
       "3761          4.939631  A highly skilled problem solver​ with over 10 ...  \n",
       "835           4.920992  I am a Kansas City based Virtual Assistant. I ...  \n",
       "2787          4.751762  Top Rated Plus | Specialize in WordPress | Inv...  \n",
       "3402          4.692159  For over 30 years, I have developed a wide ran...  \n",
       "1156          4.645855  I have 8+ years of successfully providing admi...  \n",
       "1556          4.620818  I have been passionate about my personal budge...  \n",
       "1002          4.129972  I'm an experienced jack of all trades.  I have...  \n",
       "1626          0.000000  Worked for agency with big name clients doing ...  "
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "def filter_df(df, column_name, filter_type, filter_value):\n",
    "    if filter_type == '==':\n",
    "        df_filtered = df[df[column_name]==filter_value]\n",
    "    elif filter_type == '<=':\n",
    "        df_filtered = df[df[column_name]<=filter_value]\n",
    "    return df_filtered\n",
    "\n",
    "def search(df, query):\n",
    "    product = model.encode(query).tolist()\n",
    "    # product = df.iloc[0]['text_vector_'] #use one of the products as sample\n",
    "\n",
    "    nbrs = NearestNeighbors(n_neighbors=8, algorithm='ball_tree').fit(df['text_vector_'].values.tolist())\n",
    "    distances, indices = nbrs.kneighbors([product]) #input the vector of the reference object\n",
    "\n",
    "    #print out the description of every recommended product\n",
    "    df_search = df.iloc[list(indices)[0]].drop(['skills', 'text_vector_'], axis=1).sort_values('avgFeedbackScore', ascending=False)\n",
    "\n",
    "    return df_search[['shortName', 'location', 'title', 'hourlyRate', 'avgFeedbackScore', 'description']]\n",
    "\n",
    "# search('I want to hire a person who does both backend and')\n",
    "\n",
    "df_location = filter_df(df, 'location', '==', 'New York')\n",
    "df_price = filter_df(df_location, 'hourlyRate', '<=', 80)\n",
    "search(df_price, 'I want to hire a person who does both backend and')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import gradio as gr\n",
    "import os\n",
    "\n",
    "#the first module becomes text1, the second module file1\n",
    "def greet(price, location, query):\n",
    "    # df1 = \n",
    "    df_location = filter_df(df, 'location', '==', location)\n",
    "    df_price = filter_df(df_location, 'hourlyRate', '<=', price)\n",
    "    df_search = search(df_price, query)\n",
    "    return df_search"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "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 Slider, please remove them: {'step_size': 5}\n",
      "  warnings.warn(\n",
      "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://127.0.0.1:7906\n",
      "\n",
      "To create a public link, set `share=True` in `launch()`.\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div><iframe src=\"http://127.0.0.1:7906/\" 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": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "with gr.Blocks(theme=gr.themes.Soft(primary_hue='amber', secondary_hue='gray', neutral_hue='amber')) as demo:\n",
    "    gr.Markdown(\n",
    "    \"\"\"\n",
    "    # Freelancer Upwork Search\n",
    "    \"\"\"\n",
    "    )\n",
    "    input1 = gr.Slider(20, 120, value=90, step_size=5, label=\"Max Hourly Rate\")\n",
    "    input2 = gr.Radio(['New York', 'Chicago', 'Washington'], multiselect=False, label='State', value='New York')\n",
    "    input3 = gr.Textbox(label='Query', value='I want to develop a mobile app')\n",
    "\n",
    "    btn = gr.Button(value=\"Search for Product\")\n",
    "    output = gr.Dataframe()\n",
    "    # btn.click(greet, inputs='text', outputs=['dataframe'])\n",
    "    btn.click(greet, [input1, input2, input3], [output])\n",
    "demo.launch(share=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# iface = gr.Interface(\n",
    "#     fn=greet,\n",
    "#     inputs=[\n",
    "#         gr.Slider(20, 120, value=20, step_size=5, label=\"Max Hourly Rate\"),\n",
    "#         gr.Radio(\n",
    "#             ['New York', 'Chicago', 'Washington'], multiselect=False, label='State', value='New York'\n",
    "#         ),\n",
    "#         gr.Textbox(label='Input', value='I want to develop a mobile app')\n",
    "#     ],\n",
    "#     outputs=[\"dataframe\"])\n",
    "# iface.launch(share=False)"
   ]
  }
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