00_core.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "efe78920",
   "metadata": {},
   "outputs": [],
   "source": [
    "#|default_exp core"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3d773712-12fe-440e-891f-36f59666dfde",
   "metadata": {},
   "source": [
    "# Cosette's source"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ff6f6471-8061-4fdd-85a1-25fdc27c5cf3",
   "metadata": {},
   "source": [
    "## Setup"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "033c76fd",
   "metadata": {},
   "outputs": [],
   "source": [
    "#| export\n",
    "from fastcore import imghdr\n",
    "from fastcore.utils import *\n",
    "from fastcore.meta import delegates\n",
    "\n",
    "import inspect, typing, mimetypes, base64, json, ast\n",
    "from collections import abc\n",
    "from random import choices\n",
    "from string import ascii_letters,digits\n",
    "\n",
    "from msglm import mk_msg_openai as mk_msg, mk_msgs_openai as mk_msgs\n",
    "\n",
    "from openai import types\n",
    "from openai import Completion,OpenAI,NOT_GIVEN,AzureOpenAI\n",
    "from openai.resources import chat\n",
    "from openai.resources.chat import Completions\n",
    "from openai.types.chat.chat_completion import ChatCompletion, ChatCompletionMessage\n",
    "from openai.types.completion_usage import CompletionUsage\n",
    "\n",
    "from toolslm.funccall import *\n",
    "\n",
    "try: from IPython import display\n",
    "except: display=None"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "13866a72",
   "metadata": {},
   "outputs": [],
   "source": [
    "#| hide\n",
    "from nbdev import show_doc\n",
    "from datetime import datetime\n",
    "from pprint import pprint"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "6459c998",
   "metadata": {},
   "outputs": [],
   "source": [
    "#| export\n",
    "_all_ = ['mk_msg', 'mk_msgs']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "f5fa6b92",
   "metadata": {},
   "outputs": [],
   "source": [
    "#| export\n",
    "empty = inspect.Parameter.empty"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "ae1e9290",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Available models as of 2025-02-06:\n",
      "\n",
      "babbage-002                   chatgpt-4o-latest             dall-e-2                      \n",
      "dall-e-3                      davinci-002                   ft:gpt-4o-2024-08-06:answerai \n",
      "ft:gpt-4o-2024-08-06:answerai ft:gpt-4o-2024-08-06:answerai ft:gpt-4o-mini-2024-07-18:ans \n",
      "ft:gpt-4o-mini-2024-07-18:ans gpt-3.5-turbo                 gpt-3.5-turbo-0125            \n",
      "gpt-3.5-turbo-1106            gpt-3.5-turbo-16k             gpt-3.5-turbo-instruct        \n",
      "gpt-3.5-turbo-instruct-0914   gpt-4                         gpt-4-0125-preview            \n",
      "gpt-4-1106-preview            gpt-4-turbo                   gpt-4-turbo-2024-04-09        \n",
      "gpt-4-turbo-preview           gpt-4o                        gpt-4o-2024-05-13             \n",
      "gpt-4o-2024-08-06             gpt-4o-2024-11-20             gpt-4o-audio-preview          \n",
      "gpt-4o-audio-preview-2024-10- gpt-4o-audio-preview-2024-12- gpt-4o-mini                   \n",
      "gpt-4o-mini-2024-07-18        gpt-4o-mini-audio-preview     gpt-4o-mini-audio-preview-202 \n",
      "gpt-4o-mini-realtime-preview  gpt-4o-mini-realtime-preview- gpt-4o-realtime-preview       \n",
      "gpt-4o-realtime-preview-2024- gpt-4o-realtime-preview-2024- o1                            \n",
      "o1-2024-12-17                 o1-mini                       o1-mini-2024-09-12            \n",
      "o1-preview                    o1-preview-2024-09-12         o3-mini                       \n",
      "o3-mini-2025-01-31            omni-moderation-2024-09-26    omni-moderation-latest        \n",
      "text-embedding-3-large        text-embedding-3-small        text-embedding-ada-002        \n",
      "tts-1                         tts-1-1106                    tts-1-hd                      \n",
      "tts-1-hd-1106                 whisper-1                     \n"
     ]
    }
   ],
   "source": [
    "def print_columns(items, cols=3, width=30):\n",
    "    for i in range(0, len(items), cols):\n",
    "        row = items[i:i+cols]\n",
    "        print(''.join(item[:width-1].ljust(width) for item in row))\n",
    "\n",
    "client = OpenAI()\n",
    "models = client.models.list()\n",
    "print(f\"Available models as of {datetime.now().strftime('%Y-%m-%d')}:\\n\")\n",
    "print_columns(sorted([m.id for m in models]))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a311e8d9",
   "metadata": {},
   "source": [
    "*NB* Since index into models is often hardcoded in consuming code, *always append newer entries to the end of the list* to avoid breaking code that consumes this library."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "0fff8869",
   "metadata": {},
   "outputs": [],
   "source": [
    "#| exports\n",
    "models = 'o1-preview', 'o1-mini', 'gpt-4o', 'gpt-4o-mini', 'gpt-4-turbo', 'gpt-4', 'gpt-4-32k', 'gpt-3.5-turbo', 'gpt-3.5-turbo-instruct', 'o1', 'o3-mini', 'chatgpt-4o-latest'"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "92dd0e86",
   "metadata": {},
   "source": [
    "`o1` should support images while `o1-preview`, `o1-mini`, `o3-mini` do not support images."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "87f69208",
   "metadata": {},
   "outputs": [],
   "source": [
    "#| exports\n",
    "text_only_models = 'o1-preview', 'o1-mini', 'o3-mini'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "36d965d5",
   "metadata": {},
   "outputs": [],
   "source": [
    "#| exports\n",
    "has_streaming_models = set(models) - set(('o1', 'o1-mini', 'o3-mini'))\n",
    "has_system_prompt_models = set(models) - set(('o1-mini', 'o3-mini'))\n",
    "has_temperature_models = set(models) - set(('o1', 'o1-mini', 'o3-mini'))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "dd26d5ed",
   "metadata": {},
   "outputs": [],
   "source": [
    "#| exports\n",
    "\n",
    "def can_stream(m): return m in has_streaming_models\n",
    "def can_set_system_prompt(m): return m in has_system_prompt_models\n",
    "def can_set_temperature(m): return m in has_temperature_models"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "5c4505c7",
   "metadata": {},
   "outputs": [],
   "source": [
    "assert can_stream(\"gpt-4o\")\n",
    "assert not can_stream(\"o1\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "dacf2bd2",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'gpt-4o'"
      ]
     },
     "execution_count": null,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model = models[2]\n",
    "model"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "71985a9c",
   "metadata": {},
   "source": [
    "For examples, we'll use GPT-4o."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "863d4d81",
   "metadata": {},
   "source": [
    "## OpenAI SDK"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "70b53a51",
   "metadata": {},
   "outputs": [],
   "source": [
    "cli = OpenAI().chat.completions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "6ec40731",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/markdown": [
       "Hello, Jeremy! How can I assist you today?\n",
       "\n",
       "<details>\n",
       "\n",
       "- id: chatcmpl-AxxDzLirSVOpB1Fa5YINYyvmVNJtj\n",
       "- choices: [Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='Hello, Jeremy! How can I assist you today?', refusal=None, role='assistant', audio=None, function_call=None, tool_calls=None))]\n",
       "- created: 1738852375\n",
       "- model: gpt-4o-2024-08-06\n",
       "- object: chat.completion\n",
       "- service_tier: default\n",
       "- system_fingerprint: fp_50cad350e4\n",
       "- usage: CompletionUsage(completion_tokens=12, prompt_tokens=9, total_tokens=21, completion_tokens_details=CompletionTokensDetails(accepted_prediction_tokens=0, audio_tokens=0, reasoning_tokens=0, rejected_prediction_tokens=0), prompt_tokens_details=PromptTokensDetails(audio_tokens=0, cached_tokens=0))\n",
       "\n",
       "</details>"
      ],
      "text/plain": [
       "ChatCompletion(id='chatcmpl-AxxDzLirSVOpB1Fa5YINYyvmVNJtj', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='Hello, Jeremy! How can I assist you today?', refusal=None, role='assistant', audio=None, function_call=None, tool_calls=None))], created=1738852375, model='gpt-4o-2024-08-06', object='chat.completion', service_tier='default', system_fingerprint='fp_50cad350e4', usage=In: 9; Out: 12; Total: 21)"
      ]
     },
     "execution_count": null,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "m = {'role': 'user', 'content': \"I'm Jeremy\"}\n",
    "r = cli.create(messages=[m], model=model, max_completion_tokens=100)\n",
    "r"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d6359e1a",
   "metadata": {},
   "source": [
    "### Formatting output"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "eba620ce",
   "metadata": {},
   "outputs": [],
   "source": [
    "#| exports\n",
    "def find_block(r:abc.Mapping, # The message to look in\n",
    "              ):\n",
    "    \"Find the message in `r`.\"\n",
    "    m = nested_idx(r, 'choices', 0)\n",
    "    if not m: return m\n",
    "    if hasattr(m, 'message'): return m.message\n",
    "    return m.delta"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "ae99799d",
   "metadata": {},
   "outputs": [],
   "source": [
    "#| exports\n",
    "def contents(r):\n",
    "    \"Helper to get the contents from response `r`.\"\n",
    "    blk = find_block(r)\n",
    "    if not blk: return r\n",
    "    if hasattr(blk, 'content'): return getattr(blk,'content')\n",
    "    return blk"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "6d5f2107",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'Hello, Jeremy! How can I assist you today?'"
      ]
     },
     "execution_count": null,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "contents(r)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "17924d0c",
   "metadata": {},
   "outputs": [],
   "source": [
    "#| exports\n",
    "@patch\n",
    "def _repr_markdown_(self:ChatCompletion):\n",
    "    det = '\\n- '.join(f'{k}: {v}' for k,v in dict(self).items())\n",
    "    res = contents(self)\n",
    "    if not res: return f\"- {det}\"\n",
    "    return f\"\"\"{contents(self)}\n",
    "\n",
    "<details>\n",
    "\n",
    "- {det}\n",
    "\n",
    "</details>\"\"\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "cfd85eeb",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/markdown": [
       "Hello, Jeremy! How can I assist you today?\n",
       "\n",
       "<details>\n",
       "\n",
       "- id: chatcmpl-AxxDzLirSVOpB1Fa5YINYyvmVNJtj\n",
       "- choices: [Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='Hello, Jeremy! How can I assist you today?', refusal=None, role='assistant', audio=None, function_call=None, tool_calls=None))]\n",
       "- created: 1738852375\n",
       "- model: gpt-4o-2024-08-06\n",
       "- object: chat.completion\n",
       "- service_tier: default\n",
       "- system_fingerprint: fp_50cad350e4\n",
       "- usage: CompletionUsage(completion_tokens=12, prompt_tokens=9, total_tokens=21, completion_tokens_details=CompletionTokensDetails(accepted_prediction_tokens=0, audio_tokens=0, reasoning_tokens=0, rejected_prediction_tokens=0), prompt_tokens_details=PromptTokensDetails(audio_tokens=0, cached_tokens=0))\n",
       "\n",
       "</details>"
      ],
      "text/plain": [
       "ChatCompletion(id='chatcmpl-AxxDzLirSVOpB1Fa5YINYyvmVNJtj', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='Hello, Jeremy! How can I assist you today?', refusal=None, role='assistant', audio=None, function_call=None, tool_calls=None))], created=1738852375, model='gpt-4o-2024-08-06', object='chat.completion', service_tier='default', system_fingerprint='fp_50cad350e4', usage=In: 9; Out: 12; Total: 21)"
      ]
     },
     "execution_count": null,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "r"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "10c7466f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "In: 9; Out: 12; Total: 21"
      ]
     },
     "execution_count": null,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "r.usage"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "b1a24f68",
   "metadata": {},
   "outputs": [],
   "source": [
    "#| exports\n",
    "def usage(inp=0, # Number of prompt tokens\n",
    "          out=0  # Number of completion tokens\n",
    "         ):\n",
    "    \"Slightly more concise version of `CompletionUsage`.\"\n",
    "    return CompletionUsage(prompt_tokens=inp, completion_tokens=out, total_tokens=inp+out)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "a7e52afd",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "In: 5; Out: 0; Total: 5"
      ]
     },
     "execution_count": null,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "usage(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "27468180",
   "metadata": {},
   "outputs": [],
   "source": [
    "#| exports\n",
    "@patch\n",
    "def __repr__(self:CompletionUsage): return f'In: {self.prompt_tokens}; Out: {self.completion_tokens}; Total: {self.total_tokens}'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "765ca615",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "In: 9; Out: 12; Total: 21"
      ]
     },
     "execution_count": null,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "r.usage"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "bec303ba",
   "metadata": {},
   "outputs": [],
   "source": [
    "#| exports\n",
    "@patch\n",
    "def __add__(self:CompletionUsage, b):\n",
    "    \"Add together each of `input_tokens` and `output_tokens`\"\n",
    "    return usage(self.prompt_tokens+b.prompt_tokens, self.completion_tokens+b.completion_tokens)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "bffb0b2e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "In: 18; Out: 24; Total: 42"
      ]
     },
     "execution_count": null,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "r.usage+r.usage"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "307caa69",
   "metadata": {},
   "outputs": [],
   "source": [
    "#| export\n",
    "def wrap_latex(text, md=True):\n",
    "    \"Replace OpenAI LaTeX codes with markdown-compatible ones\"\n",
    "    text = re.sub(r\"\\\\\\((.*?)\\\\\\)\", lambda o: f\"${o.group(1)}$\", text)\n",
    "    res = re.sub(r\"\\\\\\[(.*?)\\\\\\]\", lambda o: f\"$${o.group(1)}$$\", text, flags=re.DOTALL)\n",
    "    if md: res = display.Markdown(res)\n",
    "    return res"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "edd0a43f",
   "metadata": {},
   "source": [
    "### Creating messages"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "13954d58",
   "metadata": {},
   "source": [
    "Creating correctly formatted `dict`s from scratch every time isn't very handy, so we'll import a couple of helper functions from the `msglm` library.\n",
    "\n",
    "Let's use `mk_msg` to recreate our msg `{'role': 'user', 'content': \"I'm Jeremy\"}` from earlier."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "e79f7705",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/markdown": [
       "Hello, Jeremy! How can I assist you today?\n",
       "\n",
       "<details>\n",
       "\n",
       "- id: chatcmpl-AxxE1Vtsvd9GeFEY8Db18sZLLZBQc\n",
       "- choices: [Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='Hello, Jeremy! How can I assist you today?', refusal=None, role='assistant', audio=None, function_call=None, tool_calls=None))]\n",
       "- created: 1738852377\n",
       "- model: gpt-4o-2024-08-06\n",
       "- object: chat.completion\n",
       "- service_tier: default\n",
       "- system_fingerprint: fp_4691090a87\n",
       "- usage: CompletionUsage(completion_tokens=12, prompt_tokens=9, total_tokens=21, completion_tokens_details=CompletionTokensDetails(accepted_prediction_tokens=0, audio_tokens=0, reasoning_tokens=0, rejected_prediction_tokens=0), prompt_tokens_details=PromptTokensDetails(audio_tokens=0, cached_tokens=0))\n",
       "\n",
       "</details>"
      ],
      "text/plain": [
       "ChatCompletion(id='chatcmpl-AxxE1Vtsvd9GeFEY8Db18sZLLZBQc', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='Hello, Jeremy! How can I assist you today?', refusal=None, role='assistant', audio=None, function_call=None, tool_calls=None))], created=1738852377, model='gpt-4o-2024-08-06', object='chat.completion', service_tier='default', system_fingerprint='fp_4691090a87', usage=In: 9; Out: 12; Total: 21)"
      ]
     },
     "execution_count": null,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "prompt = \"I'm Jeremy\"\n",
    "m = mk_msg(prompt)\n",
    "r = cli.create(messages=[m], model=model, max_completion_tokens=100)\n",
    "r"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6c7b389b",
   "metadata": {},
   "source": [
    "We can pass more than just text messages to OpenAI. As we'll see later we can also pass images, SDK objects, etc. To handle these different data types we need to pass the type along with our content to OpenAI. \n",
    "\n",
    "Here's an example of a multimodal message containing text and images. \n",
    "\n",
    "```json\n",
    "{\n",
    "    'role': 'user', \n",
    "    'content': [\n",
    "        {'type': 'text', 'text': 'What is in the image?'},\n",
    "        {'type': 'image_url', 'image_url': {'url': f'data:{MEDIA_TYPE};base64,{IMG}'}}\n",
    "    ]\n",
    "}\n",
    "```\n",
    "\n",
    "`mk_msg` infers the type automatically and creates the appropriate data structure. "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7e33194f",
   "metadata": {},
   "source": [
    "LLMs, don't actually have state, but instead dialogs are created by passing back all previous prompts and responses every time. With OpenAI, they always alternate *user* and *assistant*. We'll use `mk_msgs` from `msglm` to make it easier to build up these dialog lists."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "7eef3715",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[{'role': 'user', 'content': \"I'm Jeremy\"},\n",
       " ChatCompletionMessage(content='Hello, Jeremy! How can I assist you today?', refusal=None, role='assistant', audio=None, function_call=None, tool_calls=None),\n",
       " {'role': 'user', 'content': 'I forgot my name. Can you remind me please?'}]"
      ]
     },
     "execution_count": null,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "msgs = mk_msgs([prompt, r, \"I forgot my name. Can you remind me please?\"]) \n",
    "msgs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "6c464f8b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/markdown": [
       "It sounds like you're having a bit of a memory lapse! You just mentioned that your name is Jeremy. If there's anything else you need help with, feel free to ask.\n",
       "\n",
       "<details>\n",
       "\n",
       "- id: chatcmpl-AxxE28BxbRMXrKAMxiNw0dHXT9h6r\n",
       "- choices: [Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content=\"It sounds like you're having a bit of a memory lapse! You just mentioned that your name is Jeremy. If there's anything else you need help with, feel free to ask.\", refusal=None, role='assistant', audio=None, function_call=None, tool_calls=None))]\n",
       "- created: 1738852378\n",
       "- model: gpt-4o-2024-08-06\n",
       "- object: chat.completion\n",
       "- service_tier: default\n",
       "- system_fingerprint: fp_4691090a87\n",
       "- usage: CompletionUsage(completion_tokens=36, prompt_tokens=39, total_tokens=75, completion_tokens_details=CompletionTokensDetails(accepted_prediction_tokens=0, audio_tokens=0, reasoning_tokens=0, rejected_prediction_tokens=0), prompt_tokens_details=PromptTokensDetails(audio_tokens=0, cached_tokens=0))\n",
       "\n",
       "</details>"
      ],
      "text/plain": [
       "ChatCompletion(id='chatcmpl-AxxE28BxbRMXrKAMxiNw0dHXT9h6r', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content=\"It sounds like you're having a bit of a memory lapse! You just mentioned that your name is Jeremy. If there's anything else you need help with, feel free to ask.\", refusal=None, role='assistant', audio=None, function_call=None, tool_calls=None))], created=1738852378, model='gpt-4o-2024-08-06', object='chat.completion', service_tier='default', system_fingerprint='fp_4691090a87', usage=In: 39; Out: 36; Total: 75)"
      ]
     },
     "execution_count": null,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cli.create(messages=msgs, model=model, max_completion_tokens=200)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "281f8a4d",
   "metadata": {},
   "source": [
    "## Client"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "3b873aaf",
   "metadata": {},
   "outputs": [],
   "source": [
    "#| exports\n",
    "class Client:\n",
    "    def __init__(self, model, cli=None):\n",
    "        \"Basic LLM messages client.\"\n",
    "        self.model,self.use = model,usage(0,0)\n",
    "        self.text_only = model in text_only_models\n",
    "        self.c = (cli or OpenAI()).chat.completions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "d01e9ccf",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "In: 0; Out: 0; Total: 0"
      ]
     },
     "execution_count": null,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "c = Client(model)\n",
    "c.use"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "be54737f",
   "metadata": {},
   "outputs": [],
   "source": [
    "#| exports\n",
    "@patch\n",
    "def _r(self:Client, r:ChatCompletion):\n",
    "    \"Store the result of the message and accrue total usage.\"\n",
    "    self.result = r\n",
    "    if getattr(r,'usage',None): self.use += r.usage\n",
    "    return r"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "0181f7b3",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "In: 9; Out: 12; Total: 21"
      ]
     },
     "execution_count": null,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "c._r(r)\n",
    "c.use"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "36029ed5",
   "metadata": {},
   "outputs": [],
   "source": [
    "#| export\n",
    "def get_stream(r):\n",
    "    for o in r:\n",
    "        o = contents(o)\n",
    "        if o and isinstance(o, str): yield(o)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "5fb96c43",
   "metadata": {},
   "outputs": [],
   "source": [
    "#| exports\n",
    "@patch\n",
    "@delegates(Completions.create)\n",
    "def __call__(self:Client,\n",
    "             msgs:list, # List of messages in the dialog\n",
    "             sp:str='', # System prompt\n",
    "             maxtok=4096, # Maximum tokens\n",
    "             stream:bool=False, # Stream response?\n",
    "             **kwargs):\n",
    "    \"Make a call to LLM.\"\n",
    "    if 'tools' in kwargs: assert not self.text_only, \"Tool use is not supported by the current model type.\"\n",
    "    if any(c['type'] == 'image_url' for msg in msgs if isinstance(msg, dict) and isinstance(msg.get('content'), list) for c in msg['content']): assert not self.text_only, \"Images are not supported by the current model type.\"\n",
    "    if stream: kwargs['stream_options'] = {\"include_usage\": True}\n",
    "    if sp and self.model in has_system_prompt_models:\n",
    "        msgs = [mk_msg(sp, 'system')] + list(msgs)\n",
    "\n",
    "    r = self.c.create(\n",
    "        model=self.model, messages=msgs, max_completion_tokens=maxtok, stream=stream, **kwargs)\n",
    "    if not stream: return self._r(r)\n",
    "    else: return get_stream(map(self._r, r))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "47195b07",
   "metadata": {},
   "outputs": [],
   "source": [
    "msgs = [mk_msg('Hi')]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "338a38e5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/markdown": [
       "Hello! How can I assist you today?\n",
       "\n",
       "<details>\n",
       "\n",
       "- id: chatcmpl-AxxE4eN6uGVZpCt4DqZpeqAfeVcVF\n",
       "- choices: [Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='Hello! How can I assist you today?', refusal=None, role='assistant', audio=None, function_call=None, tool_calls=None))]\n",
       "- created: 1738852380\n",
       "- model: gpt-4o-2024-08-06\n",
       "- object: chat.completion\n",
       "- service_tier: default\n",
       "- system_fingerprint: fp_4691090a87\n",
       "- usage: CompletionUsage(completion_tokens=10, prompt_tokens=8, total_tokens=18, completion_tokens_details=CompletionTokensDetails(accepted_prediction_tokens=0, audio_tokens=0, reasoning_tokens=0, rejected_prediction_tokens=0), prompt_tokens_details=PromptTokensDetails(audio_tokens=0, cached_tokens=0))\n",
       "\n",
       "</details>"
      ],
      "text/plain": [
       "ChatCompletion(id='chatcmpl-AxxE4eN6uGVZpCt4DqZpeqAfeVcVF', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='Hello! How can I assist you today?', refusal=None, role='assistant', audio=None, function_call=None, tool_calls=None))], created=1738852380, model='gpt-4o-2024-08-06', object='chat.completion', service_tier='default', system_fingerprint='fp_4691090a87', usage=In: 8; Out: 10; Total: 18)"
      ]
     },
     "execution_count": null,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "c(msgs)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "d7c3a5b6",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "In: 17; Out: 22; Total: 39"
      ]
     },
     "execution_count": null,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "c.use"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "13a92b57",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Hello! How can I assist you today?"
     ]
    }
   ],
   "source": [
    "for o in c(msgs, stream=True): print(o, end='')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "b1af093b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "In: 25; Out: 32; Total: 57"
      ]
     },
     "execution_count": null,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "c.use"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1a7cdbc6",
   "metadata": {},
   "source": [
    "## Tool use"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "046e8cc3",
   "metadata": {},
   "outputs": [],
   "source": [
    "def sums(\n",
    "    a:int,  # First thing to sum\n",
    "    b:int # Second thing to sum\n",
    ") -> int: # The sum of the inputs\n",
    "    \"Adds a + b.\"\n",
    "    print(f\"Finding the sum of {a} and {b}\")\n",
    "    return a + b"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "88420769",
   "metadata": {},
   "outputs": [],
   "source": [
    "#| export\n",
    "def mk_openai_func(f): \n",
    "    sc = get_schema(f, 'parameters')\n",
    "    sc['parameters'].pop('title', None)\n",
    "    return dict(type='function', function=sc)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "ff47e55f",
   "metadata": {},
   "outputs": [],
   "source": [
    "#| export\n",
    "def mk_tool_choice(f): return dict(type='function', function={'name':f})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "abcab8c7",
   "metadata": {},
   "outputs": [],
   "source": [
    "sysp = \"You are a helpful assistant. When using tools, be sure to pass all required parameters, at minimum.\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "567d958c",
   "metadata": {},
   "outputs": [],
   "source": [
    "a,b = 604542,6458932\n",
    "pr = f\"What is {a}+{b}?\"\n",
    "tools=[mk_openai_func(sums)]\n",
    "tool_choice=mk_tool_choice(\"sums\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "4cad8f11",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/markdown": [
       "- id: chatcmpl-AxxE60yQrAQborSaxvspHxWKbI1We\n",
       "- choices: [Choice(finish_reason='tool_calls', index=0, logprobs=None, message=ChatCompletionMessage(content=None, refusal=None, role='assistant', audio=None, function_call=None, tool_calls=[ChatCompletionMessageToolCall(id='call_gxbDrZ9AmIuSgvgQSoUCCp2N', function=Function(arguments='{\"a\":604542,\"b\":6458932}', name='sums'), type='function')]))]\n",
       "- created: 1738852382\n",
       "- model: gpt-4o-2024-08-06\n",
       "- object: chat.completion\n",
       "- service_tier: default\n",
       "- system_fingerprint: fp_50cad350e4\n",
       "- usage: CompletionUsage(completion_tokens=22, prompt_tokens=94, total_tokens=116, completion_tokens_details=CompletionTokensDetails(accepted_prediction_tokens=0, audio_tokens=0, reasoning_tokens=0, rejected_prediction_tokens=0), prompt_tokens_details=PromptTokensDetails(audio_tokens=0, cached_tokens=0))"
      ],
      "text/plain": [
       "ChatCompletion(id='chatcmpl-AxxE60yQrAQborSaxvspHxWKbI1We', choices=[Choice(finish_reason='tool_calls', index=0, logprobs=None, message=ChatCompletionMessage(content=None, refusal=None, role='assistant', audio=None, function_call=None, tool_calls=[ChatCompletionMessageToolCall(id='call_gxbDrZ9AmIuSgvgQSoUCCp2N', function=Function(arguments='{\"a\":604542,\"b\":6458932}', name='sums'), type='function')]))], created=1738852382, model='gpt-4o-2024-08-06', object='chat.completion', service_tier='default', system_fingerprint='fp_50cad350e4', usage=In: 94; Out: 22; Total: 116)"
      ]
     },
     "execution_count": null,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "msgs = [mk_msg(pr)]\n",
    "r = c(msgs, sp=sysp, tools=tools)\n",
    "r"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "c9394b2d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "ChatCompletionMessage(content=None, refusal=None, role='assistant', audio=None, function_call=None, tool_calls=[ChatCompletionMessageToolCall(id='call_gxbDrZ9AmIuSgvgQSoUCCp2N', function=Function(arguments='{\"a\":604542,\"b\":6458932}', name='sums'), type='function')])"
      ]
     },
     "execution_count": null,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "m = find_block(r)\n",
    "m"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "2a6488b7",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[ChatCompletionMessageToolCall(id='call_gxbDrZ9AmIuSgvgQSoUCCp2N', function=Function(arguments='{\"a\":604542,\"b\":6458932}', name='sums'), type='function')]"
      ]
     },
     "execution_count": null,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tc = m.tool_calls\n",
    "tc"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "d5fc3933",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Function(arguments='{\"a\":604542,\"b\":6458932}', name='sums')"
      ]
     },
     "execution_count": null,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "func = tc[0].function\n",
    "func"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "a3616cf0",
   "metadata": {},
   "outputs": [],
   "source": [
    "#| exports\n",
    "def call_func_openai(func:types.chat.chat_completion_message_tool_call.Function, ns:Optional[abc.Mapping]=None):\n",
    "    return call_func(func.name, ast.literal_eval(func.arguments), ns)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "b506ec11",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Finding the sum of 604542 and 6458932\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "7063474"
      ]
     },
     "execution_count": null,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ns = mk_ns(sums)\n",
    "res = call_func_openai(func, ns=ns)\n",
    "res"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "d475922d",
   "metadata": {},
   "outputs": [],
   "source": [
    "#| exports\n",
    "def mk_toolres(\n",
    "    r:abc.Mapping, # Tool use request response\n",
    "    ns:Optional[abc.Mapping]=None, # Namespace to search for tools\n",
    "    obj:Optional=None # Class to search for tools\n",
    "    ):\n",
    "    \"Create a `tool_result` message from response `r`.\"\n",
    "    r = mk_msg(r)\n",
    "    tcs = getattr(r, 'tool_calls', [])\n",
    "    res = [r]\n",
    "    if ns is None: ns = globals()\n",
    "    if obj is not None: ns = mk_ns(obj)\n",
    "    for tc in (tcs or []):\n",
    "        func = tc.function\n",
    "        cts = str(call_func_openai(func, ns=ns))\n",
    "        res.append(mk_msg(str(cts), 'tool', tool_call_id=tc.id, name=func.name))\n",
    "    return res"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "f13de1fc",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Finding the sum of 604542 and 6458932\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "[ChatCompletionMessage(content=None, refusal=None, role='assistant', audio=None, function_call=None, tool_calls=[ChatCompletionMessageToolCall(id='call_gxbDrZ9AmIuSgvgQSoUCCp2N', function=Function(arguments='{\"a\":604542,\"b\":6458932}', name='sums'), type='function')]),\n",
       " {'role': 'tool',\n",
       "  'content': '7063474',\n",
       "  'tool_call_id': 'call_gxbDrZ9AmIuSgvgQSoUCCp2N',\n",
       "  'name': 'sums'}]"
      ]
     },
     "execution_count": null,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tr = mk_toolres(r, ns=ns)\n",
    "tr"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "bcc83c48",
   "metadata": {},
   "outputs": [],
   "source": [
    "msgs += tr"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "eed99502",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/markdown": [
       "The sum of 604542 and 6458932 is 7,063,474.\n",
       "\n",
       "<details>\n",
       "\n",
       "- id: chatcmpl-AxxE77DTrlhWfU5FKcM2ZYwqhggUI\n",
       "- choices: [Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='The sum of 604542 and 6458932 is 7,063,474.', refusal=None, role='assistant', audio=None, function_call=None, tool_calls=None))]\n",
       "- created: 1738852383\n",
       "- model: gpt-4o-2024-08-06\n",
       "- object: chat.completion\n",
       "- service_tier: default\n",
       "- system_fingerprint: fp_4691090a87\n",
       "- usage: CompletionUsage(completion_tokens=21, prompt_tokens=126, total_tokens=147, completion_tokens_details=CompletionTokensDetails(accepted_prediction_tokens=0, audio_tokens=0, reasoning_tokens=0, rejected_prediction_tokens=0), prompt_tokens_details=PromptTokensDetails(audio_tokens=0, cached_tokens=0))\n",
       "\n",
       "</details>"
      ],
      "text/plain": [
       "ChatCompletion(id='chatcmpl-AxxE77DTrlhWfU5FKcM2ZYwqhggUI', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='The sum of 604542 and 6458932 is 7,063,474.', refusal=None, role='assistant', audio=None, function_call=None, tool_calls=None))], created=1738852383, model='gpt-4o-2024-08-06', object='chat.completion', service_tier='default', system_fingerprint='fp_4691090a87', usage=In: 126; Out: 21; Total: 147)"
      ]
     },
     "execution_count": null,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "res = c(msgs, sp=sysp, tools=tools)\n",
    "res"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "800a53a9",
   "metadata": {},
   "outputs": [],
   "source": [
    "class Dummy:\n",
    "    def sums(\n",
    "        self,\n",
    "        a:int,  # First thing to sum\n",
    "        b:int=1 # Second thing to sum\n",
    "    ) -> int: # The sum of the inputs\n",
    "        \"Adds a + b.\"\n",
    "        print(f\"Finding the sum of {a} and {b}\")\n",
    "        return a + b"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "7ff70d08",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/markdown": [
       "Hello Jeremy! What can I do for you today?\n",
       "\n",
       "<details>\n",
       "\n",
       "- id: chatcmpl-AxxEB3zopAfdLdTDAKxMN7U3JYoha\n",
       "- choices: [Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='Hello Jeremy! What can I do for you today?', refusal=None, role='assistant', audio=None, function_call=None, tool_calls=None))]\n",
       "- created: 1738852387\n",
       "- model: gpt-4o-2024-08-06\n",
       "- object: chat.completion\n",
       "- service_tier: default\n",
       "- system_fingerprint: fp_4691090a87\n",
       "- usage: CompletionUsage(completion_tokens=13, prompt_tokens=106, total_tokens=119, completion_tokens_details=CompletionTokensDetails(accepted_prediction_tokens=0, audio_tokens=0, reasoning_tokens=0, rejected_prediction_tokens=0), prompt_tokens_details=PromptTokensDetails(audio_tokens=0, cached_tokens=0))\n",
       "\n",
       "</details>"
      ],
      "text/plain": [
       "ChatCompletion(id='chatcmpl-AxxEB3zopAfdLdTDAKxMN7U3JYoha', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='Hello Jeremy! What can I do for you today?', refusal=None, role='assistant', audio=None, function_call=None, tool_calls=None))], created=1738852387, model='gpt-4o-2024-08-06', object='chat.completion', service_tier='default', system_fingerprint='fp_4691090a87', usage=In: 106; Out: 13; Total: 119)"
      ]
     },
     "execution_count": null,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tools = [mk_openai_func(Dummy.sums)]\n",
    "\n",
    "o = Dummy()\n",
    "msgs = mk_toolres(\"I'm Jeremy\")\n",
    "r = c(msgs, sp=sysp, tools=tools)\n",
    "msgs += mk_toolres(r, obj=o)\n",
    "res = c(msgs, sp=sysp, tools=tools)\n",
    "res"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "9e93b087",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[{'role': 'user', 'content': \"I'm Jeremy\"},\n",
       " ChatCompletionMessage(content='Hi Jeremy! How can I assist you today?', refusal=None, role='assistant', audio=None, function_call=None, tool_calls=None)]"
      ]
     },
     "execution_count": null,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "msgs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "b21e6290",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Finding the sum of 604542 and 6458932\n"
     ]
    },
    {
     "data": {
      "text/markdown": [
       "The result of \\( 604542 + 6458932 \\) is 7,063,474.\n",
       "\n",
       "<details>\n",
       "\n",
       "- id: chatcmpl-AxxEDgQUhxjSyQp9iaRmyVmAadi5q\n",
       "- choices: [Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='The result of \\\\( 604542 + 6458932 \\\\) is 7,063,474.', refusal=None, role='assistant', audio=None, function_call=None, tool_calls=None))]\n",
       "- created: 1738852389\n",
       "- model: gpt-4o-2024-08-06\n",
       "- object: chat.completion\n",
       "- service_tier: default\n",
       "- system_fingerprint: fp_50cad350e4\n",
       "- usage: CompletionUsage(completion_tokens=24, prompt_tokens=132, total_tokens=156, completion_tokens_details=CompletionTokensDetails(accepted_prediction_tokens=0, audio_tokens=0, reasoning_tokens=0, rejected_prediction_tokens=0), prompt_tokens_details=PromptTokensDetails(audio_tokens=0, cached_tokens=0))\n",
       "\n",
       "</details>"
      ],
      "text/plain": [
       "ChatCompletion(id='chatcmpl-AxxEDgQUhxjSyQp9iaRmyVmAadi5q', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='The result of \\\\( 604542 + 6458932 \\\\) is 7,063,474.', refusal=None, role='assistant', audio=None, function_call=None, tool_calls=None))], created=1738852389, model='gpt-4o-2024-08-06', object='chat.completion', service_tier='default', system_fingerprint='fp_50cad350e4', usage=In: 132; Out: 24; Total: 156)"
      ]
     },
     "execution_count": null,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tools = [mk_openai_func(Dummy.sums)]\n",
    "\n",
    "o = Dummy()\n",
    "msgs = mk_toolres(pr)\n",
    "r = c(msgs, sp=sysp, tools=tools)\n",
    "msgs += mk_toolres(r, obj=o)\n",
    "res = c(msgs, sp=sysp, tools=tools)\n",
    "res"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "c29b9b81",
   "metadata": {},
   "outputs": [],
   "source": [
    "#| exports\n",
    "\n",
    "def _mock_id(): return 'call_' + ''.join(choices(ascii_letters+digits, k=24))\n",
    "\n",
    "def mock_tooluse(name:str, # The name of the called function\n",
    "                 res,  # The result of calling the function\n",
    "                 **kwargs): # The arguments to the function\n",
    "    \"\"\n",
    "    id = _mock_id()\n",
    "    func = dict(arguments=json.dumps(kwargs), name=name)\n",
    "    tc = dict(id=id, function=func, type='function')\n",
    "    req = dict(content=None, role='assistant', tool_calls=[tc])\n",
    "    resp = mk_msg('' if res is None else str(res), 'tool', tool_call_id=id, name=name)\n",
    "    return [req,resp]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "785f693c",
   "metadata": {},
   "source": [
    "This function mocks the messages needed to implement tool use, for situations where you want to insert tool use messages into a dialog without actually calling into the model."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "9bcee006",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/markdown": [
       "The sum of 604542 and 6458932 is 7063474.\n",
       "\n",
       "<details>\n",
       "\n",
       "- id: chatcmpl-AxxEEgwmhB6rTQiEHNbmN6HdLGFDg\n",
       "- choices: [Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='The sum of 604542 and 6458932 is 7063474.', refusal=None, role='assistant', audio=None, function_call=None, tool_calls=None))]\n",
       "- created: 1738852390\n",
       "- model: gpt-4o-2024-08-06\n",
       "- object: chat.completion\n",
       "- service_tier: default\n",
       "- system_fingerprint: fp_7b6a074e04\n",
       "- usage: CompletionUsage(completion_tokens=19, prompt_tokens=111, total_tokens=130, completion_tokens_details=CompletionTokensDetails(accepted_prediction_tokens=0, audio_tokens=0, reasoning_tokens=0, rejected_prediction_tokens=0), prompt_tokens_details=PromptTokensDetails(audio_tokens=0, cached_tokens=0))\n",
       "\n",
       "</details>"
      ],
      "text/plain": [
       "ChatCompletion(id='chatcmpl-AxxEEgwmhB6rTQiEHNbmN6HdLGFDg', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='The sum of 604542 and 6458932 is 7063474.', refusal=None, role='assistant', audio=None, function_call=None, tool_calls=None))], created=1738852390, model='gpt-4o-2024-08-06', object='chat.completion', service_tier='default', system_fingerprint='fp_7b6a074e04', usage=In: 111; Out: 19; Total: 130)"
      ]
     },
     "execution_count": null,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tu = mock_tooluse(name='sums', res=7063474, a=604542, b=6458932)\n",
    "r = c([mk_msg(pr)]+tu, tools=tools)\n",
    "r"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1ffaa969",
   "metadata": {},
   "source": [
    "Structured outputs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "a3679879",
   "metadata": {},
   "outputs": [],
   "source": [
    "#| exports\n",
    "@patch\n",
    "@delegates(Client.__call__)\n",
    "def structured(self:Client,\n",
    "               msgs: list, # Prompt\n",
    "               tools:Optional[list]=None, # List of tools to make available to OpenAI model\n",
    "               obj:Optional=None, # Class to search for tools\n",
    "               ns:Optional[abc.Mapping]=None, # Namespace to search for tools\n",
    "               **kwargs):\n",
    "    \"Return the value of all tool calls (generally used for structured outputs)\"\n",
    "    tools = listify(tools)\n",
    "    if ns is None: ns=mk_ns(*tools)\n",
    "    tools = [mk_openai_func(o) for o in tools]\n",
    "    if obj is not None: ns = mk_ns(obj)\n",
    "    res = self(msgs, tools=tools, tool_choice='required', **kwargs)\n",
    "    cts = getattr(res, 'choices', [])\n",
    "    tcs = [call_func_openai(t.function, ns=ns) for o in cts for t in (o.message.tool_calls or [])]\n",
    "    return tcs"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1648f208",
   "metadata": {},
   "source": [
    "OpenAI's API doesn't natively support response formats, so we introduce a `structured` method to handle tool calling for this purpose. In this setup, the tool's result is sent directly to the user without being passed back to the model."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "31f40c68",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Finding the sum of 604542 and 6458932\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "[7063474]"
      ]
     },
     "execution_count": null,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "c.structured(mk_msgs(pr), tools=[sums])"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4ea144b8",
   "metadata": {},
   "source": [
    "## Chat"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "a77d1edb",
   "metadata": {},
   "outputs": [],
   "source": [
    "#| exports\n",
    "class Chat:\n",
    "    def __init__(self,\n",
    "                 model:Optional[str]=None, # Model to use (leave empty if passing `cli`)\n",
    "                 cli:Optional[Client]=None, # Client to use (leave empty if passing `model`)\n",
    "                 sp='', # Optional system prompt\n",
    "                 tools:Optional[list]=None,  # List of tools to make available\n",
    "                 tool_choice:Optional[str]=None): # Forced tool choice\n",
    "        \"OpenAI chat client.\"\n",
    "        assert model or cli\n",
    "        self.c = (cli or Client(model))\n",
    "        self.h,self.sp,self.tools,self.tool_choice = [],sp,tools,tool_choice\n",
    "    \n",
    "    @property\n",
    "    def use(self): return self.c.use"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "04b837c5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(In: 0; Out: 0; Total: 0, [])"
      ]
     },
     "execution_count": null,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sp = \"Never mention what tools you use.\"\n",
    "chat = Chat(model, sp=sp)\n",
    "chat.c.use, chat.h"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "403539e1",
   "metadata": {},
   "outputs": [],
   "source": [
    "#| exports\n",
    "@patch\n",
    "@delegates(Completions.create)\n",
    "def __call__(self:Chat,\n",
    "             pr=None,  # Prompt / message\n",
    "             stream:bool=False, # Stream response?\n",
    "             **kwargs):\n",
    "    \"Add prompt `pr` to dialog and get a response\"\n",
    "    if isinstance(pr,str): pr = pr.strip()\n",
    "    if pr: self.h.append(mk_msg(pr))\n",
    "    if self.tools: kwargs['tools'] = [mk_openai_func(o) for o in self.tools]\n",
    "    if self.tool_choice: kwargs['tool_choice'] = mk_tool_choice(self.tool_choice)\n",
    "    res = self.c(self.h, sp=self.sp, stream=stream, **kwargs)\n",
    "    self.h += mk_toolres(res, ns=self.tools)\n",
    "    return res"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "40073f42",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/markdown": [
       "Your name is Jeremy. How can I help you today?\n",
       "\n",
       "<details>\n",
       "\n",
       "- id: chatcmpl-AxxEGWAHp292zs25lAzsUAW68RaQm\n",
       "- choices: [Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='Your name is Jeremy. How can I help you today?', refusal=None, role='assistant', audio=None, function_call=None, tool_calls=None))]\n",
       "- created: 1738852392\n",
       "- model: gpt-4o-2024-08-06\n",
       "- object: chat.completion\n",
       "- service_tier: default\n",
       "- system_fingerprint: fp_4691090a87\n",
       "- usage: CompletionUsage(completion_tokens=13, prompt_tokens=43, total_tokens=56, completion_tokens_details=CompletionTokensDetails(accepted_prediction_tokens=0, audio_tokens=0, reasoning_tokens=0, rejected_prediction_tokens=0), prompt_tokens_details=PromptTokensDetails(audio_tokens=0, cached_tokens=0))\n",
       "\n",
       "</details>"
      ],
      "text/plain": [
       "ChatCompletion(id='chatcmpl-AxxEGWAHp292zs25lAzsUAW68RaQm', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='Your name is Jeremy. How can I help you today?', refusal=None, role='assistant', audio=None, function_call=None, tool_calls=None))], created=1738852392, model='gpt-4o-2024-08-06', object='chat.completion', service_tier='default', system_fingerprint='fp_4691090a87', usage=In: 43; Out: 13; Total: 56)"
      ]
     },
     "execution_count": null,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "chat(\"I'm Jeremy\")\n",
    "chat(\"What's my name?\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "529104ec",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Hi Jeremy! How can I assist you today?"
     ]
    }
   ],
   "source": [
    "chat = Chat(model, sp=sp)\n",
    "for o in chat(\"I'm Jeremy\", stream=True):\n",
    "    o = contents(o)\n",
    "    if o and isinstance(o, str): print(o, end='')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3d78a53a",
   "metadata": {},
   "source": [
    "Check that the o1 reasoning model works and compare 4o default to o1 behavior."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "9d9828dc",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Correct Answer:\n",
      "1233 * 4297 = 5298201\n",
      "\n",
      "gpt-4o Answer:\n",
      "1233 multiplied by 4297 is 5,295,201.\n",
      "\n",
      "o-1 Answer:\n",
      "1233 × 4297 = 5,298,201.\n"
     ]
    }
   ],
   "source": [
    "chat = Chat(model, sp=sp)\n",
    "chat_o1 = Chat(\"o1\", sp=sp)\n",
    "problem = \"1233 * 4297\"\n",
    "print(f\"Correct Answer:\\n{problem} = {eval(problem)}\")\n",
    "\n",
    "print(\"\\ngpt-4o Answer:\")\n",
    "r = chat(f\"what is {problem}?\")\n",
    "print(contents(r))\n",
    "\n",
    "print(\"\\no-1 Answer:\")\n",
    "r = chat_o1(f\"what is {problem}?\")\n",
    "print(contents(r))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6b40892f",
   "metadata": {},
   "source": [
    "### Chat tool use"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "ee6535cf",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'What is 604542+6458932?'"
      ]
     },
     "execution_count": null,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pr = f\"What is {a}+{b}?\"\n",
    "pr"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "797741c5",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Finding the sum of 604542 and 6458932\n"
     ]
    },
    {
     "data": {
      "text/markdown": [
       "- id: chatcmpl-AxxENmOGgDLJf76uw6zAa04gp3ttA\n",
       "- choices: [Choice(finish_reason='tool_calls', index=0, logprobs=None, message=ChatCompletionMessage(content=None, refusal=None, role='assistant', audio=None, function_call=None, tool_calls=[ChatCompletionMessageToolCall(id='call_H906YFMeZg2yDdiWKoBbtvw6', function=Function(arguments='{\"a\":604542,\"b\":6458932}', name='sums'), type='function')]))]\n",
       "- created: 1738852399\n",
       "- model: gpt-4o-2024-08-06\n",
       "- object: chat.completion\n",
       "- service_tier: default\n",
       "- system_fingerprint: fp_4691090a87\n",
       "- usage: CompletionUsage(completion_tokens=22, prompt_tokens=80, total_tokens=102, completion_tokens_details=CompletionTokensDetails(accepted_prediction_tokens=0, audio_tokens=0, reasoning_tokens=0, rejected_prediction_tokens=0), prompt_tokens_details=PromptTokensDetails(audio_tokens=0, cached_tokens=0))"
      ],
      "text/plain": [
       "ChatCompletion(id='chatcmpl-AxxENmOGgDLJf76uw6zAa04gp3ttA', choices=[Choice(finish_reason='tool_calls', index=0, logprobs=None, message=ChatCompletionMessage(content=None, refusal=None, role='assistant', audio=None, function_call=None, tool_calls=[ChatCompletionMessageToolCall(id='call_H906YFMeZg2yDdiWKoBbtvw6', function=Function(arguments='{\"a\":604542,\"b\":6458932}', name='sums'), type='function')]))], created=1738852399, model='gpt-4o-2024-08-06', object='chat.completion', service_tier='default', system_fingerprint='fp_4691090a87', usage=In: 80; Out: 22; Total: 102)"
      ]
     },
     "execution_count": null,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "chat = Chat(model, sp=sp, tools=[sums])\n",
    "r = chat(pr)\n",
    "r"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "0979c832",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/markdown": [
       "The sum of 604542 and 6458932 is 7063474.\n",
       "\n",
       "<details>\n",
       "\n",
       "- id: chatcmpl-AxxEOmWmCSUxAVslLnDwNIA1Qlpcx\n",
       "- choices: [Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='The sum of 604542 and 6458932 is 7063474.', refusal=None, role='assistant', audio=None, function_call=None, tool_calls=None))]\n",
       "- created: 1738852400\n",
       "- model: gpt-4o-2024-08-06\n",
       "- object: chat.completion\n",
       "- service_tier: default\n",
       "- system_fingerprint: fp_4691090a87\n",
       "- usage: CompletionUsage(completion_tokens=19, prompt_tokens=112, total_tokens=131, completion_tokens_details=CompletionTokensDetails(accepted_prediction_tokens=0, audio_tokens=0, reasoning_tokens=0, rejected_prediction_tokens=0), prompt_tokens_details=PromptTokensDetails(audio_tokens=0, cached_tokens=0))\n",
       "\n",
       "</details>"
      ],
      "text/plain": [
       "ChatCompletion(id='chatcmpl-AxxEOmWmCSUxAVslLnDwNIA1Qlpcx', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='The sum of 604542 and 6458932 is 7063474.', refusal=None, role='assistant', audio=None, function_call=None, tool_calls=None))], created=1738852400, model='gpt-4o-2024-08-06', object='chat.completion', service_tier='default', system_fingerprint='fp_4691090a87', usage=In: 112; Out: 19; Total: 131)"
      ]
     },
     "execution_count": null,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "chat()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "df1dd4c3",
   "metadata": {},
   "source": [
    "## Images"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cf741dbc",
   "metadata": {},
   "source": [
    "As everyone knows, when testing image APIs you have to use a cute puppy."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "5d35d564",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/jpeg": 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",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "execution_count": null,
     "metadata": {
      "image/jpeg": {
       "width": 200
      }
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Image is Cute_dog.jpg from Wikimedia\n",
    "fn = Path('samples/puppy.jpg')\n",
    "display.Image(filename=fn, width=200)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "d120d8fb",
   "metadata": {},
   "outputs": [],
   "source": [
    "img = fn.read_bytes()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8a18ee71",
   "metadata": {},
   "source": [
    "OpenAI expects an image message to have the following structure\n",
    "\n",
    "```js\n",
    "{\n",
    "  \"type\": \"image_url\",\n",
    "  \"image_url\": {\n",
    "    \"url\": f\"data:{MEDIA_TYPE};base64,{IMG}\"\n",
    "  }\n",
    "}\n",
    "```\n",
    "`msglm` automatically detects if a message is an image, encodes it, and generates the data structure above.\n",
    "All we need to do is a create a list containing our image and a query and then pass it to `mk_msg`.\n",
    "\n",
    "Let's try it out..."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "0c0eed5d",
   "metadata": {},
   "outputs": [],
   "source": [
    "q = \"In brief, what color flowers are in this image?\"\n",
    "msg = [mk_msg(img), mk_msg(q)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "2295c2d3",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/markdown": [
       "The flowers in the image are purple.\n",
       "\n",
       "<details>\n",
       "\n",
       "- id: chatcmpl-AxxEQLbPnVVEmTjyVmmU5TWTIddeW\n",
       "- choices: [Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='The flowers in the image are purple.', refusal=None, role='assistant', audio=None, function_call=None, tool_calls=None))]\n",
       "- created: 1738852402\n",
       "- model: gpt-4o-2024-08-06\n",
       "- object: chat.completion\n",
       "- service_tier: default\n",
       "- system_fingerprint: fp_4691090a87\n",
       "- usage: CompletionUsage(completion_tokens=9, prompt_tokens=458, total_tokens=467, completion_tokens_details=CompletionTokensDetails(accepted_prediction_tokens=0, audio_tokens=0, reasoning_tokens=0, rejected_prediction_tokens=0), prompt_tokens_details=PromptTokensDetails(audio_tokens=0, cached_tokens=0))\n",
       "\n",
       "</details>"
      ],
      "text/plain": [
       "ChatCompletion(id='chatcmpl-AxxEQLbPnVVEmTjyVmmU5TWTIddeW', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='The flowers in the image are purple.', refusal=None, role='assistant', audio=None, function_call=None, tool_calls=None))], created=1738852402, model='gpt-4o-2024-08-06', object='chat.completion', service_tier='default', system_fingerprint='fp_4691090a87', usage=In: 458; Out: 9; Total: 467)"
      ]
     },
     "execution_count": null,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "c = Chat(model)\n",
    "c([img, q])"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7dc18d6c",
   "metadata": {},
   "source": [
    "# Third Party Providers"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "acf7626b",
   "metadata": {},
   "source": [
    "## Azure OpenAI Service"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "80455a73",
   "metadata": {},
   "outputs": [],
   "source": [
    "#| export\n",
    "models_azure = ('gpt-4o', 'gpt-4-32k', 'gpt4-1106-preview', 'gpt-35-turbo', 'gpt-35-turbo-16k')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4e056a52",
   "metadata": {},
   "source": [
    "Example Azure usage:\n",
    "```\n",
    "azure_endpoint = AzureOpenAI(\n",
    "  azure_endpoint = os.getenv(\"AZURE_OPENAI_ENDPOINT\"), \n",
    "  api_key=os.getenv(\"AZURE_OPENAI_API_KEY\"),  \n",
    "  api_version=\"2024-08-01-preview\"\n",
    ")\n",
    "\n",
    "client = Client(models_azure[0], azure_endpoint)\n",
    "chat = Chat(cli=client)\n",
    "chat(\"I'm Faisal\")\n",
    "```"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "94ec4289",
   "metadata": {},
   "source": [
    "## Export -"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "1e9ee5c1",
   "metadata": {},
   "outputs": [],
   "source": [
    "#|hide\n",
    "#|eval: false\n",
    "from nbdev.doclinks import nbdev_export\n",
    "nbdev_export()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "207f9715",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "python3",
   "language": "python",
   "name": "python3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}