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‎.ipynb_checkpoints/Simple Search engine-checkpoint.ipynb

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"4 5 They are distinguished by their “memory” as th..."
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"name": "stdout",
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"output_type": "stream",
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"text": [
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" 1 2 3 4 5 6 7 8 9 10 ... 587 \\\n",
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},
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{
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"cell_type": "code",
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"id": "929844ac",
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"metadata": {},
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"outputs": [
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"## <span style=\"font-family: Cambria;\">Step6: </span>"
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]
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},
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{
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"cell_type": "code",
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"id": "7f153c70",
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"Stored search input: \n",
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"\n",
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"\n",
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"\n",
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"Stored search input: \n",
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"\n",
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"\n",
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"\n",
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"Stored search input: \n",
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"\n",
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"\n",
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"\n",
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"Stored search input: \n",
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"\n",
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"\n",
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"\n"
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]
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}
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],
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"source": [
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"import tkinter as tk\n",
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"from tkinter import scrolledtext\n",
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"import pandas as pd\n",
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"\n",
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"def store_search_input():\n",
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" # Get the content of the ScrolledText widget\n",
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" search_query = result_text.get(1.0, tk.END)\n",
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" print(f\"Stored search input: {search_query}\")\n",
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"\n",
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" print( search_query)\n",
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"def perform_search():\n",
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" # Read the ranked output file\n",
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" ranked_df = pd.read_csv('ranked_output.csv')\n",
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"\n",
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" # Get the top 10 IDs\n",
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" top_ids = ranked_df['id'].head(10).tolist()\n",
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"\n",
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" # Read the output file\n",
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" output_df = pd.read_csv('output.csv', index_col='id')\n",
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"\n",
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" # Display the sentences corresponding to the top IDs\n",
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" result_text.delete(1.0, tk.END) # Clear the previous results\n",
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"\n",
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" for id in top_ids:\n",
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" if id in output_df.index:\n",
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" sentence = output_df.loc[id, 'sentence']\n",
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" result_text.insert(tk.END, f\"{id}: {sentence}\\n\")\n",
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" else:\n",
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" result_text.insert(tk.END, f\"{id}: Not found\\n\")\n",
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"\n",
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"# Create the main window\n",
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"root = tk.Tk()\n",
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"root.title(\"Search Engine\")\n",
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"\n",
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"# Create a StringVar to store the search input\n",
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"kiarash_string = tk.StringVar()\n",
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"\n",
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"search_entry = tk.Entry(root, width=40, textvariable=kiarash_string)\n",
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"search_entry.grid(row=0, column=0, padx=10, pady=10)\n",
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"\n",
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"# Button to store search input\n",
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"store_button = tk.Button(root, text=\"Store Input\", command=store_search_input)\n",
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"store_button.grid(row=0, column=1, padx=10, pady=10)\n",
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"\n",
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"# Button to perform search\n",
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"search_button = tk.Button(root, text=\"Perform Search\", command=perform_search)\n",
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"search_button.grid(row=0, column=2, padx=10, pady=10)\n",
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"\n",
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"result_text = scrolledtext.ScrolledText(root, width=50, height=10, wrap=tk.WORD)\n",
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"result_text.grid(row=1, column=0, columnspan=3, padx=10, pady=10)\n",
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"\n",
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"# Run the Tkinter event loop\n",
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"root.mainloop()\n"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "9ca873c7",
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"id": "e8732cc7",
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"metadata": {},
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"outputs": [],
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"source": []

‎Simple Search engine.ipynb

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"... ... ... ... ... ... ... ... ... ... ... ... ... \n",
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"decomposing 0 0 0 0 0 0 0 0 0 0 ... 0 \n",
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"(lstm) 0 0 0 0 0 0 0 0 0 0 ... 0 \n",
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"digital 0 0 0 0 0 0 0 0 0 0 ... 0 \n",
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"outputs": [

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