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Delete find strengths and weekness.ipynb

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- {
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- "cells": [
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- {
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- "cell_type": "code",
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- "execution_count": null,
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- "id": "8a4c74f3-8f39-4396-afc6-036cfede2649",
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- "metadata": {},
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- "outputs": [],
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- "source": [
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- "import os\n",
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- "import json\n",
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- "import openai\n",
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- "\n",
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- "# Initialize the OpenAI client\n",
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- "client = openai.OpenAI(api_key=\"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\")\n",
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- "\n",
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- "# Define the prompt for hotel review analysis\n",
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- "prompt = \"Analyzing hotel reviews to identify strengths and weaknesses. Please provide only the weaknesses and strengths.\\n\"\n",
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- "\n",
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- "# Define the base directory path\n",
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- "base_dir = r\"D:\\21761A4230\\preproced hotel data\"\n",
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- "\n",
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- "# Define the output file path\n",
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- "output_file = \"strengths_weaknesses.txt\"\n",
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- "\n",
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- "# Open the output file in append mode\n",
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- "with open(output_file, \"a\") as f_out:\n",
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- " # Iterate through each subdirectory (hotel) in the base directory\n",
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- " for hotel_dir in os.listdir(base_dir):\n",
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- " hotel_path = os.path.join(base_dir, hotel_dir)\n",
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- " \n",
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- " # Iterate through each cluster file in the hotel directory\n",
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- " for cluster_file in os.listdir(hotel_path):\n",
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- " if cluster_file.endswith(\".json\"):\n",
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- " cluster_path = os.path.join(hotel_path, cluster_file)\n",
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- " \n",
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- " # Load the keywords from the cluster file\n",
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- " with open(cluster_path, \"r\") as f:\n",
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- " cluster_data = json.load(f)\n",
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- " keywords = cluster_data[\"hotels\"]\n",
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- " \n",
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- " # Analyze the keywords using OpenAI\n",
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- " response = client.chat.completions.create(\n",
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- " model=\"gpt-3.5-turbo\",\n",
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- " messages=[\n",
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- " {\n",
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- " \"role\": \"user\",\n",
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- " \"content\": f\"{prompt}Keywords: {keywords}\"\n",
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- " }\n",
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- " ],\n",
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- " temperature=1,\n",
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- " max_tokens=256,\n",
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- " top_p=1,\n",
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- " frequency_penalty=0,\n",
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- " presence_penalty=0\n",
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- " )\n",
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- " \n",
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- " # Write the hotel, cluster, keywords, and OpenAI response to the output file\n",
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- " f_out.write(f\"Hotel: {hotel_dir}, Cluster: {cluster_file}\\n\")\n",
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- " f_out.write(f\"Keywords: {keywords}\\n\")\n",
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- " f_out.write(f\"OpenAI Response:\\n{response.choices[0].message.content}\\n\\n\")\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": 16,
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- "id": "66dedbfb-7663-4a23-beec-16f400ae07f3",
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- "metadata": {},
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- "outputs": [
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- {
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- "ename": "RateLimitError",
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- "evalue": "Error code: 429 - {'error': {'message': 'You exceeded your current quota, please check your plan and billing details. For more information on this error, read the docs: https://platform.openai.com/docs/guides/error-codes/api-errors.', 'type': 'insufficient_quota', 'param': None, 'code': 'insufficient_quota'}}",
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- "output_type": "error",
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- "traceback": [
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- "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
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- "\u001b[1;31mRateLimitError\u001b[0m Traceback (most recent call last)",
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- "Cell \u001b[1;32mIn[16], line 31\u001b[0m\n\u001b[0;32m 28\u001b[0m keywords \u001b[38;5;241m=\u001b[39m cluster_data[\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mhotels\u001b[39m\u001b[38;5;124m\"\u001b[39m]\n\u001b[0;32m 30\u001b[0m \u001b[38;5;66;03m# Analyze the keywords using OpenAI\u001b[39;00m\n\u001b[1;32m---> 31\u001b[0m response \u001b[38;5;241m=\u001b[39m \u001b[43mclient\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mchat\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mcompletions\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mcreate\u001b[49m\u001b[43m(\u001b[49m\n\u001b[0;32m 32\u001b[0m \u001b[43m \u001b[49m\u001b[43mmodel\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mgpt-3.5-turbo\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m,\u001b[49m\n\u001b[0;32m 33\u001b[0m \u001b[43m \u001b[49m\u001b[43mmessages\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43m[\u001b[49m\n\u001b[0;32m 34\u001b[0m \u001b[43m \u001b[49m\u001b[43m{\u001b[49m\n\u001b[0;32m 35\u001b[0m \u001b[43m \u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mrole\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m:\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43muser\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m,\u001b[49m\n\u001b[0;32m 36\u001b[0m \u001b[43m \u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mcontent\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m:\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;124;43mf\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;132;43;01m{\u001b[39;49;00m\u001b[43mprompt\u001b[49m\u001b[38;5;132;43;01m}\u001b[39;49;00m\u001b[38;5;124;43mKeywords: \u001b[39;49m\u001b[38;5;132;43;01m{\u001b[39;49;00m\u001b[43mkeywords\u001b[49m\u001b[38;5;132;43;01m}\u001b[39;49;00m\u001b[38;5;124;43m\"\u001b[39;49m\n\u001b[0;32m 37\u001b[0m \u001b[43m \u001b[49m\u001b[43m}\u001b[49m\n\u001b[0;32m 38\u001b[0m \u001b[43m \u001b[49m\u001b[43m]\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m 39\u001b[0m \u001b[43m \u001b[49m\u001b[43mtemperature\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;241;43m1\u001b[39;49m\u001b[43m,\u001b[49m\n\u001b[0;32m 40\u001b[0m \u001b[43m \u001b[49m\u001b[43mmax_tokens\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;241;43m256\u001b[39;49m\u001b[43m,\u001b[49m\n\u001b[0;32m 41\u001b[0m \u001b[43m \u001b[49m\u001b[43mtop_p\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;241;43m1\u001b[39;49m\u001b[43m,\u001b[49m\n\u001b[0;32m 42\u001b[0m \u001b[43m \u001b[49m\u001b[43mfrequency_penalty\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;241;43m0\u001b[39;49m\u001b[43m,\u001b[49m\n\u001b[0;32m 43\u001b[0m \u001b[43m \u001b[49m\u001b[43mpresence_penalty\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;241;43m0\u001b[39;49m\n\u001b[0;32m 44\u001b[0m \u001b[43m\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m 46\u001b[0m \u001b[38;5;66;03m# Write the OpenAI response to the output file\u001b[39;00m\n\u001b[0;32m 47\u001b[0m \u001b[38;5;66;03m#f_out.write(f\"Cluster: {cluster_file}\\n\")\u001b[39;00m\n\u001b[0;32m 48\u001b[0m \u001b[38;5;66;03m#f_out.write(f\"Keywords: {keywords}\\n\")\u001b[39;00m\n\u001b[0;32m 49\u001b[0m f_out\u001b[38;5;241m.\u001b[39mwrite(\u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mOpenAI Response:\u001b[39m\u001b[38;5;130;01m\\n\u001b[39;00m\u001b[38;5;132;01m{\u001b[39;00mresponse\u001b[38;5;241m.\u001b[39mchoices[\u001b[38;5;241m0\u001b[39m]\u001b[38;5;241m.\u001b[39mmessage\u001b[38;5;241m.\u001b[39mcontent\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;130;01m\\n\u001b[39;00m\u001b[38;5;130;01m\\n\u001b[39;00m\u001b[38;5;124m\"\u001b[39m)\n",
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- "File \u001b[1;32mD:\\21761A4230\\venv\\Lib\\site-packages\\openai\\_utils\\_utils.py:275\u001b[0m, in \u001b[0;36mrequired_args.<locals>.inner.<locals>.wrapper\u001b[1;34m(*args, **kwargs)\u001b[0m\n\u001b[0;32m 273\u001b[0m msg \u001b[38;5;241m=\u001b[39m \u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mMissing required argument: \u001b[39m\u001b[38;5;132;01m{\u001b[39;00mquote(missing[\u001b[38;5;241m0\u001b[39m])\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m\"\u001b[39m\n\u001b[0;32m 274\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mTypeError\u001b[39;00m(msg)\n\u001b[1;32m--> 275\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mfunc\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n",
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- "File \u001b[1;32mD:\\21761A4230\\venv\\Lib\\site-packages\\openai\\resources\\chat\\completions.py:667\u001b[0m, in \u001b[0;36mCompletions.create\u001b[1;34m(self, messages, model, frequency_penalty, function_call, functions, logit_bias, logprobs, max_tokens, n, presence_penalty, response_format, seed, stop, stream, temperature, tool_choice, tools, top_logprobs, top_p, user, extra_headers, extra_query, extra_body, timeout)\u001b[0m\n\u001b[0;32m 615\u001b[0m \u001b[38;5;129m@required_args\u001b[39m([\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mmessages\u001b[39m\u001b[38;5;124m\"\u001b[39m, \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mmodel\u001b[39m\u001b[38;5;124m\"\u001b[39m], [\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mmessages\u001b[39m\u001b[38;5;124m\"\u001b[39m, \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mmodel\u001b[39m\u001b[38;5;124m\"\u001b[39m, \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mstream\u001b[39m\u001b[38;5;124m\"\u001b[39m])\n\u001b[0;32m 616\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mcreate\u001b[39m(\n\u001b[0;32m 617\u001b[0m \u001b[38;5;28mself\u001b[39m,\n\u001b[1;32m (...)\u001b[0m\n\u001b[0;32m 665\u001b[0m timeout: \u001b[38;5;28mfloat\u001b[39m \u001b[38;5;241m|\u001b[39m httpx\u001b[38;5;241m.\u001b[39mTimeout \u001b[38;5;241m|\u001b[39m \u001b[38;5;28;01mNone\u001b[39;00m \u001b[38;5;241m|\u001b[39m NotGiven \u001b[38;5;241m=\u001b[39m NOT_GIVEN,\n\u001b[0;32m 666\u001b[0m ) \u001b[38;5;241m-\u001b[39m\u001b[38;5;241m>\u001b[39m ChatCompletion \u001b[38;5;241m|\u001b[39m Stream[ChatCompletionChunk]:\n\u001b[1;32m--> 667\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_post\u001b[49m\u001b[43m(\u001b[49m\n\u001b[0;32m 668\u001b[0m \u001b[43m \u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43m/chat/completions\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m,\u001b[49m\n\u001b[0;32m 669\u001b[0m \u001b[43m \u001b[49m\u001b[43mbody\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mmaybe_transform\u001b[49m\u001b[43m(\u001b[49m\n\u001b[0;32m 670\u001b[0m \u001b[43m \u001b[49m\u001b[43m{\u001b[49m\n\u001b[0;32m 671\u001b[0m \u001b[43m \u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mmessages\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m:\u001b[49m\u001b[43m \u001b[49m\u001b[43mmessages\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m 672\u001b[0m \u001b[43m \u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mmodel\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m:\u001b[49m\u001b[43m \u001b[49m\u001b[43mmodel\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m 673\u001b[0m \u001b[43m \u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mfrequency_penalty\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m:\u001b[49m\u001b[43m \u001b[49m\u001b[43mfrequency_penalty\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m 674\u001b[0m \u001b[43m \u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mfunction_call\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m:\u001b[49m\u001b[43m \u001b[49m\u001b[43mfunction_call\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m 675\u001b[0m \u001b[43m \u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mfunctions\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m:\u001b[49m\u001b[43m \u001b[49m\u001b[43mfunctions\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m 676\u001b[0m \u001b[43m \u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mlogit_bias\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m:\u001b[49m\u001b[43m \u001b[49m\u001b[43mlogit_bias\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m 677\u001b[0m \u001b[43m \u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mlogprobs\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m:\u001b[49m\u001b[43m \u001b[49m\u001b[43mlogprobs\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m 678\u001b[0m \u001b[43m \u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mmax_tokens\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m:\u001b[49m\u001b[43m \u001b[49m\u001b[43mmax_tokens\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m 679\u001b[0m \u001b[43m \u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mn\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m:\u001b[49m\u001b[43m \u001b[49m\u001b[43mn\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m 680\u001b[0m \u001b[43m \u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mpresence_penalty\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m:\u001b[49m\u001b[43m \u001b[49m\u001b[43mpresence_penalty\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m 681\u001b[0m \u001b[43m \u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mresponse_format\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m:\u001b[49m\u001b[43m \u001b[49m\u001b[43mresponse_format\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m 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80
- "File \u001b[1;32mD:\\21761A4230\\venv\\Lib\\site-packages\\openai\\_base_client.py:1213\u001b[0m, in \u001b[0;36mSyncAPIClient.post\u001b[1;34m(self, path, cast_to, body, options, files, stream, stream_cls)\u001b[0m\n\u001b[0;32m 1199\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mpost\u001b[39m(\n\u001b[0;32m 1200\u001b[0m \u001b[38;5;28mself\u001b[39m,\n\u001b[0;32m 1201\u001b[0m path: \u001b[38;5;28mstr\u001b[39m,\n\u001b[1;32m (...)\u001b[0m\n\u001b[0;32m 1208\u001b[0m stream_cls: \u001b[38;5;28mtype\u001b[39m[_StreamT] \u001b[38;5;241m|\u001b[39m \u001b[38;5;28;01mNone\u001b[39;00m \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mNone\u001b[39;00m,\n\u001b[0;32m 1209\u001b[0m ) \u001b[38;5;241m-\u001b[39m\u001b[38;5;241m>\u001b[39m ResponseT \u001b[38;5;241m|\u001b[39m _StreamT:\n\u001b[0;32m 1210\u001b[0m opts \u001b[38;5;241m=\u001b[39m FinalRequestOptions\u001b[38;5;241m.\u001b[39mconstruct(\n\u001b[0;32m 1211\u001b[0m method\u001b[38;5;241m=\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mpost\u001b[39m\u001b[38;5;124m\"\u001b[39m, url\u001b[38;5;241m=\u001b[39mpath, json_data\u001b[38;5;241m=\u001b[39mbody, files\u001b[38;5;241m=\u001b[39mto_httpx_files(files), \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39moptions\n\u001b[0;32m 1212\u001b[0m )\n\u001b[1;32m-> 1213\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m cast(ResponseT, \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mrequest\u001b[49m\u001b[43m(\u001b[49m\u001b[43mcast_to\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mopts\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mstream\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mstream\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mstream_cls\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mstream_cls\u001b[49m\u001b[43m)\u001b[49m)\n",
81
- "File \u001b[1;32mD:\\21761A4230\\venv\\Lib\\site-packages\\openai\\_base_client.py:902\u001b[0m, in \u001b[0;36mSyncAPIClient.request\u001b[1;34m(self, cast_to, options, remaining_retries, stream, stream_cls)\u001b[0m\n\u001b[0;32m 893\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mrequest\u001b[39m(\n\u001b[0;32m 894\u001b[0m \u001b[38;5;28mself\u001b[39m,\n\u001b[0;32m 895\u001b[0m cast_to: Type[ResponseT],\n\u001b[1;32m (...)\u001b[0m\n\u001b[0;32m 900\u001b[0m stream_cls: \u001b[38;5;28mtype\u001b[39m[_StreamT] \u001b[38;5;241m|\u001b[39m \u001b[38;5;28;01mNone\u001b[39;00m \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mNone\u001b[39;00m,\n\u001b[0;32m 901\u001b[0m ) \u001b[38;5;241m-\u001b[39m\u001b[38;5;241m>\u001b[39m ResponseT \u001b[38;5;241m|\u001b[39m _StreamT:\n\u001b[1;32m--> 902\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_request\u001b[49m\u001b[43m(\u001b[49m\n\u001b[0;32m 903\u001b[0m \u001b[43m \u001b[49m\u001b[43mcast_to\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mcast_to\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m 904\u001b[0m \u001b[43m \u001b[49m\u001b[43moptions\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43moptions\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m 905\u001b[0m \u001b[43m \u001b[49m\u001b[43mstream\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mstream\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m 906\u001b[0m \u001b[43m \u001b[49m\u001b[43mstream_cls\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mstream_cls\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m 907\u001b[0m \u001b[43m \u001b[49m\u001b[43mremaining_retries\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mremaining_retries\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m 908\u001b[0m \u001b[43m \u001b[49m\u001b[43m)\u001b[49m\n",
82
- "File \u001b[1;32mD:\\21761A4230\\venv\\Lib\\site-packages\\openai\\_base_client.py:978\u001b[0m, in \u001b[0;36mSyncAPIClient._request\u001b[1;34m(self, cast_to, options, remaining_retries, stream, stream_cls)\u001b[0m\n\u001b[0;32m 976\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m retries \u001b[38;5;241m>\u001b[39m \u001b[38;5;241m0\u001b[39m \u001b[38;5;129;01mand\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_should_retry(err\u001b[38;5;241m.\u001b[39mresponse):\n\u001b[0;32m 977\u001b[0m err\u001b[38;5;241m.\u001b[39mresponse\u001b[38;5;241m.\u001b[39mclose()\n\u001b[1;32m--> 978\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_retry_request\u001b[49m\u001b[43m(\u001b[49m\n\u001b[0;32m 979\u001b[0m \u001b[43m \u001b[49m\u001b[43moptions\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m 980\u001b[0m \u001b[43m \u001b[49m\u001b[43mcast_to\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m 981\u001b[0m \u001b[43m \u001b[49m\u001b[43mretries\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m 982\u001b[0m \u001b[43m \u001b[49m\u001b[43merr\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mresponse\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mheaders\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m 983\u001b[0m \u001b[43m \u001b[49m\u001b[43mstream\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mstream\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m 984\u001b[0m \u001b[43m \u001b[49m\u001b[43mstream_cls\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mstream_cls\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m 985\u001b[0m \u001b[43m \u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m 987\u001b[0m \u001b[38;5;66;03m# If the response is streamed then we need to explicitly read the response\u001b[39;00m\n\u001b[0;32m 988\u001b[0m \u001b[38;5;66;03m# to completion before attempting to access the response text.\u001b[39;00m\n\u001b[0;32m 989\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m err\u001b[38;5;241m.\u001b[39mresponse\u001b[38;5;241m.\u001b[39mis_closed:\n",
83
- "File \u001b[1;32mD:\\21761A4230\\venv\\Lib\\site-packages\\openai\\_base_client.py:1026\u001b[0m, in \u001b[0;36mSyncAPIClient._retry_request\u001b[1;34m(self, options, cast_to, remaining_retries, response_headers, stream, stream_cls)\u001b[0m\n\u001b[0;32m 1022\u001b[0m \u001b[38;5;66;03m# In a synchronous context we are blocking the entire thread. Up to the library user to run the client in a\u001b[39;00m\n\u001b[0;32m 1023\u001b[0m \u001b[38;5;66;03m# different thread if necessary.\u001b[39;00m\n\u001b[0;32m 1024\u001b[0m time\u001b[38;5;241m.\u001b[39msleep(timeout)\n\u001b[1;32m-> 1026\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_request\u001b[49m\u001b[43m(\u001b[49m\n\u001b[0;32m 1027\u001b[0m \u001b[43m \u001b[49m\u001b[43moptions\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43moptions\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m 1028\u001b[0m \u001b[43m \u001b[49m\u001b[43mcast_to\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mcast_to\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m 1029\u001b[0m \u001b[43m \u001b[49m\u001b[43mremaining_retries\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mremaining\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m 1030\u001b[0m \u001b[43m \u001b[49m\u001b[43mstream\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mstream\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m 1031\u001b[0m \u001b[43m \u001b[49m\u001b[43mstream_cls\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mstream_cls\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m 1032\u001b[0m \u001b[43m\u001b[49m\u001b[43m)\u001b[49m\n",
84
- "File \u001b[1;32mD:\\21761A4230\\venv\\Lib\\site-packages\\openai\\_base_client.py:978\u001b[0m, in \u001b[0;36mSyncAPIClient._request\u001b[1;34m(self, cast_to, options, remaining_retries, stream, stream_cls)\u001b[0m\n\u001b[0;32m 976\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m retries \u001b[38;5;241m>\u001b[39m \u001b[38;5;241m0\u001b[39m \u001b[38;5;129;01mand\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_should_retry(err\u001b[38;5;241m.\u001b[39mresponse):\n\u001b[0;32m 977\u001b[0m err\u001b[38;5;241m.\u001b[39mresponse\u001b[38;5;241m.\u001b[39mclose()\n\u001b[1;32m--> 978\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_retry_request\u001b[49m\u001b[43m(\u001b[49m\n\u001b[0;32m 979\u001b[0m \u001b[43m \u001b[49m\u001b[43moptions\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m 980\u001b[0m \u001b[43m \u001b[49m\u001b[43mcast_to\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m 981\u001b[0m \u001b[43m \u001b[49m\u001b[43mretries\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m 982\u001b[0m \u001b[43m \u001b[49m\u001b[43merr\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mresponse\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mheaders\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m 983\u001b[0m \u001b[43m \u001b[49m\u001b[43mstream\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mstream\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m 984\u001b[0m \u001b[43m \u001b[49m\u001b[43mstream_cls\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mstream_cls\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m 985\u001b[0m \u001b[43m \u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m 987\u001b[0m \u001b[38;5;66;03m# If the response is streamed then we need to explicitly read the response\u001b[39;00m\n\u001b[0;32m 988\u001b[0m \u001b[38;5;66;03m# to completion before attempting to access the response text.\u001b[39;00m\n\u001b[0;32m 989\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m err\u001b[38;5;241m.\u001b[39mresponse\u001b[38;5;241m.\u001b[39mis_closed:\n",
85
- "File \u001b[1;32mD:\\21761A4230\\venv\\Lib\\site-packages\\openai\\_base_client.py:1026\u001b[0m, in \u001b[0;36mSyncAPIClient._retry_request\u001b[1;34m(self, options, cast_to, remaining_retries, response_headers, stream, stream_cls)\u001b[0m\n\u001b[0;32m 1022\u001b[0m \u001b[38;5;66;03m# In a synchronous context we are blocking the entire thread. Up to the library user to run the client in a\u001b[39;00m\n\u001b[0;32m 1023\u001b[0m \u001b[38;5;66;03m# different thread if necessary.\u001b[39;00m\n\u001b[0;32m 1024\u001b[0m time\u001b[38;5;241m.\u001b[39msleep(timeout)\n\u001b[1;32m-> 1026\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_request\u001b[49m\u001b[43m(\u001b[49m\n\u001b[0;32m 1027\u001b[0m \u001b[43m \u001b[49m\u001b[43moptions\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43moptions\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m 1028\u001b[0m \u001b[43m \u001b[49m\u001b[43mcast_to\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mcast_to\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m 1029\u001b[0m \u001b[43m \u001b[49m\u001b[43mremaining_retries\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mremaining\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m 1030\u001b[0m \u001b[43m \u001b[49m\u001b[43mstream\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mstream\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m 1031\u001b[0m \u001b[43m \u001b[49m\u001b[43mstream_cls\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mstream_cls\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m 1032\u001b[0m \u001b[43m\u001b[49m\u001b[43m)\u001b[49m\n",
86
- "File \u001b[1;32mD:\\21761A4230\\venv\\Lib\\site-packages\\openai\\_base_client.py:993\u001b[0m, in \u001b[0;36mSyncAPIClient._request\u001b[1;34m(self, cast_to, options, remaining_retries, stream, stream_cls)\u001b[0m\n\u001b[0;32m 990\u001b[0m err\u001b[38;5;241m.\u001b[39mresponse\u001b[38;5;241m.\u001b[39mread()\n\u001b[0;32m 992\u001b[0m log\u001b[38;5;241m.\u001b[39mdebug(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mRe-raising status error\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n\u001b[1;32m--> 993\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_make_status_error_from_response(err\u001b[38;5;241m.\u001b[39mresponse) \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m\n\u001b[0;32m 995\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_process_response(\n\u001b[0;32m 996\u001b[0m cast_to\u001b[38;5;241m=\u001b[39mcast_to,\n\u001b[0;32m 997\u001b[0m options\u001b[38;5;241m=\u001b[39moptions,\n\u001b[1;32m (...)\u001b[0m\n\u001b[0;32m 1000\u001b[0m stream_cls\u001b[38;5;241m=\u001b[39mstream_cls,\n\u001b[0;32m 1001\u001b[0m )\n",
87
- "\u001b[1;31mRateLimitError\u001b[0m: Error code: 429 - {'error': {'message': 'You exceeded your current quota, please check your plan and billing details. For more information on this error, read the docs: https://platform.openai.com/docs/guides/error-codes/api-errors.', 'type': 'insufficient_quota', 'param': None, 'code': 'insufficient_quota'}}"
88
- ]
89
- }
90
- ],
91
- "source": [
92
- "import os\n",
93
- "import json\n",
94
- "import openai\n",
95
- "\n",
96
- "# Initialize the OpenAI client\n",
97
- "client = openai.OpenAI(api_key=\"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\")\n",
98
- "\n",
99
- "# Define the prompt for hotel review analysis\n",
100
- "prompt = \"Analyzing hotel reviews to identify strengths and weaknesses. Please provide only the weaknesses and strengths.only 3 or 4\\n\"\n",
101
- "\n",
102
- "# Define the base directory path\n",
103
- "base_dir = r\"D:\\21761A4230\\preproced hotel data\"\n",
104
- "\n",
105
- "# Iterate through each subdirectory (hotel) in the base directory\n",
106
- "for hotel_dir in os.listdir(base_dir):\n",
107
- " hotel_path = os.path.join(base_dir, hotel_dir)\n",
108
- " output_file = os.path.join(hotel_path, f\"{hotel_dir}_strengths_weaknesses.txt\")\n",
109
- " \n",
110
- " with open(output_file, \"a\") as f_out:\n",
111
- " # Iterate through each cluster file in the hotel directory\n",
112
- " for cluster_file in os.listdir(hotel_path):\n",
113
- " if cluster_file.endswith(\".json\"):\n",
114
- " cluster_path = os.path.join(hotel_path, cluster_file)\n",
115
- " \n",
116
- " # Load the keywords from the cluster file\n",
117
- " with open(cluster_path, \"r\") as f:\n",
118
- " cluster_data = json.load(f)\n",
119
- " keywords = cluster_data[\"hotels\"]\n",
120
- " \n",
121
- " # Analyze the keywords using OpenAI\n",
122
- " response = client.chat.completions.create(\n",
123
- " model=\"gpt-3.5-turbo\",\n",
124
- " messages=[\n",
125
- " {\n",
126
- " \"role\": \"user\",\n",
127
- " \"content\": f\"{prompt}Keywords: {keywords}\"\n",
128
- " }\n",
129
- " ],\n",
130
- " temperature=1,\n",
131
- " max_tokens=256,\n",
132
- " top_p=1,\n",
133
- " frequency_penalty=0,\n",
134
- " presence_penalty=0\n",
135
- " )\n",
136
- " \n",
137
- " # Write the OpenAI response to the output file\n",
138
- " #f_out.write(f\"Cluster: {cluster_file}\\n\")\n",
139
- " #f_out.write(f\"Keywords: {keywords}\\n\")\n",
140
- " f_out.write(f\"OpenAI Response:\\n{response.choices[0].message.content}\\n\\n\")\n"
141
- ]
142
- },
143
- {
144
- "cell_type": "code",
145
- "execution_count": null,
146
- "id": "3559bfb9-0e04-4269-993f-4408380fad70",
147
- "metadata": {},
148
- "outputs": [],
149
- "source": [
150
- "import os\n",
151
- "import openai\n",
152
- "import csv\n",
153
- "\n",
154
- "# Initialize the OpenAI client\n",
155
- "client = openai.OpenAI(api_key=\"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\")\n",
156
- "\n",
157
- "# Define the function to process the text files\n",
158
- "def process_text_files(base_dir):\n",
159
- " prompt = \"Identify the 8 best strengths and 8 best weaknesses from the given text:\\n\"\n",
160
- " \n",
161
- " for hotel_dir in os.listdir(base_dir):\n",
162
- " hotel_path = os.path.join(base_dir, hotel_dir)\n",
163
- " output_file = os.path.join(hotel_path, f\"{hotel_dir}_strengths_weaknesses.txt\")\n",
164
- " \n",
165
- " with open(output_file, \"r\") as f_in:\n",
166
- " content = f_in.read()\n",
167
- " \n",
168
- " # Request OpenAI to provide the CSV file with the 8 best weaknesses and 8 best strengths\n",
169
- " response = client.completions.create(\n",
170
- " model=\"text-davinci-003\",\n",
171
- " prompt=f\"{prompt}Text: {content}\",\n",
172
- " max_tokens=256,\n",
173
- " n=1,\n",
174
- " stop=None\n",
175
- " )\n",
176
- " \n",
177
- " # Save the CSV file\n",
178
- " csv_output_file = os.path.join(hotel_path, f\"{hotel_dir}_strengths_weaknesses.csv\")\n",
179
- " with open(csv_output_file, \"w\", newline=\"\") as f_out:\n",
180
- " writer = csv.writer(f_out)\n",
181
- " writer.writerow([\"Strengths\", \"Weaknesses\"])\n",
182
- " for choice in response[\"choices\"][0][\"text\"].split(\"\\n\")[:16]: # Split the response into strengths and weaknesses\n",
183
- " writer.writerow([\"\", choice.strip()])\n",
184
- "\n",
185
- "# Process the text files in the base directory\n",
186
- "base_dir = r\"D:\\21761A4230\\preproced hotel data\"\n",
187
- "process_text_files(base_dir)\n"
188
- ]
189
- },
190
- {
191
- "cell_type": "code",
192
- "execution_count": null,
193
- "id": "3c8c8d20-5694-4eaa-9752-b950c23b6daa",
194
- "metadata": {},
195
- "outputs": [],
196
- "source": [
197
- "!streamlit run s.py\n"
198
- ]
199
- },
200
- {
201
- "cell_type": "code",
202
- "execution_count": null,
203
- "id": "4a660091-94be-4186-bb19-9965be6b2207",
204
- "metadata": {},
205
- "outputs": [],
206
- "source": []
207
- }
208
- ],
209
- "metadata": {
210
- "kernelspec": {
211
- "display_name": "Python 3 (ipykernel)",
212
- "language": "python",
213
- "name": "python3"
214
- },
215
- "language_info": {
216
- "codemirror_mode": {
217
- "name": "ipython",
218
- "version": 3
219
- },
220
- "file_extension": ".py",
221
- "mimetype": "text/x-python",
222
- "name": "python",
223
- "nbconvert_exporter": "python",
224
- "pygments_lexer": "ipython3",
225
- "version": "3.11.9"
226
- }
227
- },
228
- "nbformat": 4,
229
- "nbformat_minor": 5
230
- }