How_to_format_inputs_to_ChatGPT_models.ipynb

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   "source": [
    "# import the OpenAI Python library for calling the OpenAI API\n",
    "import openai"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "c4c6126d-d72c-4227-a7fa-e7440879645b",
   "metadata": {
    "tags": []
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   "outputs": [],
   "source": [
    "def open_file(filepath):\n",
    "    with open(filepath, 'r', encoding='utf-8') as infile:\n",
    "        return infile.read()\n",
    "\n",
    "openai.api_key = open_file('openaiapikey.txt')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "ae5c1482-5ce5-4051-b677-e1d29136aa3b",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<OpenAIObject chat.completion id=chatcmpl-6q4pfBSUZ2fGGqdJ1wLvAGZJ9M4nV at 0x2271e003ec0> JSON: {\n",
       "  \"choices\": [\n",
       "    {\n",
       "      \"finish_reason\": \"stop\",\n",
       "      \"index\": 0,\n",
       "      \"message\": {\n",
       "        \"content\": \"Orange who?\",\n",
       "        \"role\": \"assistant\"\n",
       "      }\n",
       "    }\n",
       "  ],\n",
       "  \"created\": 1677869651,\n",
       "  \"id\": \"chatcmpl-6q4pfBSUZ2fGGqdJ1wLvAGZJ9M4nV\",\n",
       "  \"model\": \"gpt-3.5-turbo-0301\",\n",
       "  \"object\": \"chat.completion\",\n",
       "  \"usage\": {\n",
       "    \"completion_tokens\": 5,\n",
       "    \"prompt_tokens\": 38,\n",
       "    \"total_tokens\": 43\n",
       "  }\n",
       "}"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Example OpenAI Python library request\n",
    "MODEL = \"gpt-3.5-turbo\"\n",
    "response = openai.ChatCompletion.create(\n",
    "    model=MODEL,\n",
    "    messages=[\n",
    "        {\"role\": \"system\", \"content\": \"You are a helpful assistant.\"},\n",
    "        {\"role\": \"user\", \"content\": \"Knock knock.\"},\n",
    "        {\"role\": \"assistant\", \"content\": \"Who's there?\"},\n",
    "        {\"role\": \"user\", \"content\": \"Orange.\"},\n",
    "    ],\n",
    "    temperature=0,\n",
    ")\n",
    "\n",
    "response"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "601a29ff-58c2-4c23-8f0a-672d013060a0",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'Orange who?'"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "response['choices'][0]['message']['content']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "484f426c-0589-48d0-8bbf-cd7b30169a02",
   "metadata": {
    "tags": []
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   "outputs": [
    {
     "name": "stdout",
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     "text": [
      "Ahoy matey! Asynchronous programming be like havin' a crew o' pirates workin' on different tasks at the same time. Ye see, instead o' waitin' for one task to be completed before startin' the next, we can have multiple tasks runnin' at once. It be like havin' me crew hoistin' the sails while others be swabbin' the deck and loadin' the cannons. Each task be workin' independently, but they all be contributin' to the overall success o' the ship. This be a powerful way to make our code run faster and more efficiently, just like how a well-oiled pirate ship can sail faster and more smoothly. Arrr!\n"
     ]
    }
   ],
   "source": [
    "# example with a system message\n",
    "response = openai.ChatCompletion.create(\n",
    "    model=MODEL,\n",
    "    messages=[\n",
    "        {\"role\": \"system\", \"content\": \"You are a helpful assistant.\"},\n",
    "        {\"role\": \"user\", \"content\": \"Explain asynchronous programming in the style of the pirate Blackbeard.\"},\n",
    "    ],\n",
    "    temperature=0,\n",
    ")\n",
    "\n",
    "print(response['choices'][0]['message']['content'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "77560f15-3058-402f-ac34-2e916d2243f0",
   "metadata": {
    "tags": []
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   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "\n",
      "Ahoy mateys! Let me tell ye about asynchronous programming, arrr! \n",
      "\n",
      "Ye see, in the world of programming, sometimes we need to wait for things to happen before we can move on to the next task. But with asynchronous programming, we can keep working on other tasks while we wait for those things to happen. \n",
      "\n",
      "It's like when we're sailing the high seas and we need to wait for the wind to change direction. We don't just sit there twiddling our thumbs, do we? No, we keep busy with other tasks like repairing the ship or checking the maps. \n",
      "\n",
      "In programming, we use something called callbacks or promises to keep track of those things we're waiting for. And while we wait for those callbacks or promises to be fulfilled, we can keep working on other parts of our code. \n",
      "\n",
      "So, me hearties, asynchronous programming is like being a pirate on the high seas, always ready to tackle the next task while we wait for the winds to change. Arrr!\n"
     ]
    }
   ],
   "source": [
    "# example without a system message\n",
    "response = openai.ChatCompletion.create(\n",
    "    model=MODEL,\n",
    "    messages=[\n",
    "        {\"role\": \"user\", \"content\": \"Explain asynchronous programming in the style of the pirate Blackbeard.\"},\n",
    "    ],\n",
    "    temperature=0,\n",
    ")\n",
    "\n",
    "print(response['choices'][0]['message']['content'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "cee8dd6d-9694-4696-87d8-5e508eda4232",
   "metadata": {
    "tags": []
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   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Sure! Fractions are a way of representing a part of a whole. The top number of a fraction is called the numerator, and it represents how many parts of the whole we are talking about. The bottom number is called the denominator, and it represents how many equal parts the whole is divided into.\n",
      "\n",
      "For example, if we have a pizza that is divided into 8 equal slices, and we take 3 slices, we can represent that as the fraction 3/8. The numerator is 3 because we took 3 slices, and the denominator is 8 because the pizza was divided into 8 slices.\n",
      "\n",
      "To add or subtract fractions, we need to make sure they have a common denominator. To do this, we find the least common multiple of the denominators and then convert each fraction to an equivalent fraction with that denominator.\n",
      "\n",
      "For example, if we want to add 1/4 and 2/3, we need to find the least common multiple of 4 and 3, which is 12. Then we convert 1/4 to 3/12 (by multiplying the numerator and denominator by 3) and 2/3 to 8/12 (by multiplying the numerator and denominator by 4). Now we can add the fractions: 3/12 + 8/12 = 11/12.\n",
      "\n",
      "Does that make sense? Do you have any questions?\n"
     ]
    }
   ],
   "source": [
    "# An example of a system message that primes the assistant to explain concepts in great depth\n",
    "response = openai.ChatCompletion.create(\n",
    "    model=MODEL,\n",
    "    messages=[\n",
    "        {\"role\": \"system\", \"content\": \"You are a friendly and helpful teaching assistant. You explain concepts in great depth using simple terms, and you give examples to help people learn. At the end of each explanation, you ask a question to check for understanding\"},\n",
    "        {\"role\": \"user\", \"content\": \"Can you explain how fractions work?\"},\n",
    "    ],\n",
    "    temperature=0,\n",
    ")\n",
    "\n",
    "print(response[\"choices\"][0][\"message\"][\"content\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "10a2b906-c18e-4e2d-9927-c2a35220f9bf",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Fractions represent a part of a whole. They consist of a numerator (top number) and a denominator (bottom number) separated by a line. The numerator represents how many parts of the whole are being considered, while the denominator represents the total number of equal parts that make up the whole.\n"
     ]
    }
   ],
   "source": [
    "# An example of a system message that primes the assistant to give brief, to-the-point answers\n",
    "response = openai.ChatCompletion.create(\n",
    "    model=MODEL,\n",
    "    messages=[\n",
    "        {\"role\": \"system\", \"content\": \"You are a laconic assistant. You reply with brief, to-the-point answers with no elaboration.\"},\n",
    "        {\"role\": \"user\", \"content\": \"Can you explain how fractions work?\"},\n",
    "    ],\n",
    "    temperature=0,\n",
    ")\n",
    "\n",
    "print(response[\"choices\"][0][\"message\"][\"content\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "5594efbd-8ccc-456a-869f-56c1437ac7c8",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "We don't have enough time to complete the entire project perfectly.\n"
     ]
    }
   ],
   "source": [
    "# An example of a faked few-shot conversation to prime the model into translating business jargon to simpler speech\n",
    "response = openai.ChatCompletion.create(\n",
    "    model=MODEL,\n",
    "    messages=[\n",
    "        {\"role\": \"system\", \"content\": \"You are a helpful, pattern-following assistant.\"},\n",
    "        {\"role\": \"user\", \"content\": \"Help me translate the following corporate jargon into plain English.\"},\n",
    "        {\"role\": \"assistant\", \"content\": \"Sure, I'd be happy to!\"},\n",
    "        {\"role\": \"user\", \"content\": \"New synergies will help drive top-line growth.\"},\n",
    "        {\"role\": \"assistant\", \"content\": \"Things working well together will increase revenue.\"},\n",
    "        {\"role\": \"user\", \"content\": \"Let's circle back when we have more bandwidth to touch base on opportunities for increased leverage.\"},\n",
    "        {\"role\": \"assistant\", \"content\": \"Let's talk later when we're less busy about how to do better.\"},\n",
    "        {\"role\": \"user\", \"content\": \"This late pivot means we don't have time to boil the ocean for the client deliverable.\"},\n",
    "    ],\n",
    "    temperature=0,\n",
    ")\n",
    "\n",
    "print(response[\"choices\"][0][\"message\"][\"content\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "d2914208-ab59-4a83-b60e-abb05c3b8c90",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "This sudden change in plans means we don't have enough time to do everything for the client's project.\n"
     ]
    }
   ],
   "source": [
    "# The business jargon translation example, but with example names for the example messages\n",
    "response = openai.ChatCompletion.create(\n",
    "    model=MODEL,\n",
    "    messages=[\n",
    "        {\"role\": \"system\", \"content\": \"You are a helpful, pattern-following assistant that translates corporate jargon into plain English.\"},\n",
    "        {\"role\": \"system\", \"name\":\"example_user\", \"content\": \"New synergies will help drive top-line growth.\"},\n",
    "        {\"role\": \"system\", \"name\": \"example_assistant\", \"content\": \"Things working well together will increase revenue.\"},\n",
    "        {\"role\": \"system\", \"name\":\"example_user\", \"content\": \"Let's circle back when we have more bandwidth to touch base on opportunities for increased leverage.\"},\n",
    "        {\"role\": \"system\", \"name\": \"example_assistant\", \"content\": \"Let's talk later when we're less busy about how to do better.\"},\n",
    "        {\"role\": \"user\", \"content\": \"This late pivot means we don't have time to boil the ocean for the client deliverable.\"},\n",
    "    ],\n",
    "    temperature=0,\n",
    ")\n",
    "\n",
    "print(response[\"choices\"][0][\"message\"][\"content\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "fd545b51-c749-4cb8-bc2d-98ac34ad3b03",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "import tiktoken\n",
    "\n",
    "\n",
    "def num_tokens_from_messages(messages, model=\"gpt-3.5-turbo-0301\"):\n",
    "    \"\"\"Returns the number of tokens used by a list of messages.\"\"\"\n",
    "    try:\n",
    "        encoding = tiktoken.encoding_for_model(model)\n",
    "    except KeyError:\n",
    "        encoding = tiktoken.get_encoding(\"cl100k_base\")\n",
    "    if model == \"gpt-3.5-turbo-0301\":  # note: future models may deviate from this\n",
    "        num_tokens = 0\n",
    "        for message in messages:\n",
    "            num_tokens += 4  # every message follows <im_start>{role/name}\\n{content}<im_end>\\n\n",
    "            for key, value in message.items():\n",
    "                num_tokens += len(encoding.encode(value))\n",
    "                if key == \"name\":  # if there's a name, the role is omitted\n",
    "                    num_tokens += -1  # role is always required and always 1 token\n",
    "        num_tokens += 2  # every reply is primed with <im_start>assistant\n",
    "        return num_tokens\n",
    "    else:\n",
    "        raise NotImplementedError(f\"\"\"num_tokens_from_messages() is not presently implemented for model {model}.\n",
    "See https://github.com/openai/openai-python/blob/main/chatml.md for information on how messages are converted to tokens.\"\"\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "61b3ff12-f88e-4330-a355-6b1cd2ccaafe",
   "metadata": {
    "tags": []
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   "outputs": [],
   "source": [
    "messages = [\n",
    "    {\"role\": \"system\", \"content\": \"You are a helpful, pattern-following assistant that translates corporate jargon into plain English.\"},\n",
    "    {\"role\": \"system\", \"name\":\"example_user\", \"content\": \"New synergies will help drive top-line growth.\"},\n",
    "    {\"role\": \"system\", \"name\": \"example_assistant\", \"content\": \"Things working well together will increase revenue.\"},\n",
    "    {\"role\": \"system\", \"name\":\"example_user\", \"content\": \"Let's circle back when we have more bandwidth to touch base on opportunities for increased leverage.\"},\n",
    "    {\"role\": \"system\", \"name\": \"example_assistant\", \"content\": \"Let's talk later when we're less busy about how to do better.\"},\n",
    "    {\"role\": \"user\", \"content\": \"This late pivot means we don't have time to boil the ocean for the client deliverable.\"},\n",
    "]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "efb71572-3991-4a8d-aecd-1ab56db67e75",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "126 prompt tokens counted.\n"
     ]
    }
   ],
   "source": [
    "# example token count from the function defined above\n",
    "print(f\"{num_tokens_from_messages(messages)} prompt tokens counted.\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "6becda0e-ad70-4286-9883-79b88b2593d3",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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