creating hallucinations with different models

hallucinations_models.ipynb

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      "Model: gpt-4\n",
      "Response: The expression given is 2 * ( 5 * 2 ), replacing '*' with the exponential\n",
      "operator would make it 2 ^ ( 5 ^ 2 ). So let's simplify: First, calculate the\n",
      "exponent in the parentheses: 5 ^ 2 = 25. Then use this result in the main\n",
      "equation: 2 ^ 25 = 33554432. So, the numeric value of the expression 2 ^ ( 5 ^ 2\n",
      ") is 33554432.\n",
      "\n",
      "Model: gpt-3.5-turbo\n",
      "Response: To replace \"*\" with the exponential operator, \"^\", the expression 2 * (5 * 2)\n",
      "would become 2 ^ (5 ^ 2).\n",
      "\n",
      "Model: gpt-3.5-turbo-0301\n",
      "Response: The exponential operator is '^'. So, 2 * ( 5 * 2 ) in exponential notation would\n",
      "be: 2 * (5^2) which simplifies to: 2 * (25) and the final result is: 50\n",
      "\n",
      "Model: gpt-3.5-turbo-0613\n",
      "Response: The numeric value of 2 * ( 5 * 2 ) replacing '*' by the exponential operator (^)\n",
      "would be 50. The expression can be rewritten as 2 * (5^2), which simplifies to 2\n",
      "* 25 = 50.\n",
      "\n"
     ]
    }
   ],
   "source": [
    "# Creating hallucinations for different models: see the huge gap from 3.5 to 4\n",
    "\n",
    "\n",
    "import os\n",
    "import openai\n",
    "import textwrap\n",
    "\n",
    "# Get the API key\n",
    "api_key = os.environ[\"OPENAI_API_KEY\"]\n",
    "\n",
    "# Set up the OpenAI API key\n",
    "openai.api_key = api_key\n",
    "\n",
    "# Define the prompt\n",
    "prompt = \"what is the numeric value of 2 * ( 5 * 2 ) replacing '*' by the exponential operator? \"\n",
    "\n",
    "# Define the list of models\n",
    "models = [\"gpt-4\",\"gpt-3.5-turbo\", \"gpt-3.5-turbo-0301\", \"gpt-3.5-turbo-0613\"]\n",
    "\n",
    "# Maximum number of words for each response\n",
    "max_words = 100\n",
    "\n",
    "# Generate a response for each model\n",
    "for model in models:\n",
    "    try:\n",
    "        # Generate a response with the API\n",
    "        response = openai.ChatCompletion.create(\n",
    "            model=model, messages=[{\"role\": \"system\", \"content\": \"You are a helpful assistant.\"}, {\"role\": \"user\", \"content\": prompt}]\n",
    "        )\n",
    "\n",
    "        # Extract the response text from the API response\n",
    "        generated_response = response['choices'][0]['message']['content']\n",
    "\n",
    "        # Split the response into words\n",
    "        words = generated_response.split()\n",
    "\n",
    "        # Truncate the response to the maximum number of words\n",
    "        truncated_response = ' '.join(words[:max_words])\n",
    "\n",
    "        # Print the response with text wrapping\n",
    "        wrapped_response = textwrap.fill(truncated_response, width=80)  # Adjust the width as needed\n",
    "        print(f\"Model: {model}\\nResponse: {wrapped_response}\\n\")\n",
    "    except Exception as e:\n",
    "        print(f\"Error for model {model}: {e}\\n\")"
   ]
  }
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