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  {
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   "metadata": {},
   "source": [
    "# Exploring OpenAI V1 functionality\n",
    "\n",
    "On 11.06.23 OpenAI released a number of new features, and along with it bumped their Python SDK to 1.0.0. This notebook shows off the new features and how to use them with LangChain."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "ee897729-263a-4073-898f-bb4cf01ed829",
   "metadata": {},
   "outputs": [],
   "source": [
    "!pip install \"openai>=1\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "c3e067ce-7a43-47a7-bc89-41f1de4cf136",
   "metadata": {},
   "outputs": [],
   "source": [
    "from langchain.chat_models import ChatOpenAI\n",
    "from langchain.schema.messages import HumanMessage, SystemMessage"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "fa7e7e95-90a1-4f73-98fe-10c4b4e0951b",
   "metadata": {},
   "source": [
    "## [Vision](https://platform.openai.com/docs/guides/vision)\n",
    "\n",
    "OpenAI released multi-modal models, which can take a sequence of text and images as input."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "1c8c3965-d3c9-4186-b5f3-5e67855ef916",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "AIMessage(content='The image appears to be a diagram illustrating the architecture or components of a software system')"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "chat = ChatOpenAI(model=\"gpt-4-vision-preview\")\n",
    "chat.invoke(\n",
    "    [\n",
    "        HumanMessage(\n",
    "            content=[\n",
    "                {\"type\": \"text\", \"text\": \"What is this image showing\"},\n",
    "                {\n",
    "                    \"type\": \"image_url\",\n",
    "                    \"image_url\": {\n",
    "                        \"url\": \"https://python.langchain.com/assets/images/langchain_stack-da369071b058555da3d491a695651f15.jpg\",\n",
    "                        \"detail\": \"auto\",\n",
    "                    },\n",
    "                },\n",
    "            ]\n",
    "        )\n",
    "    ]\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "71c34763-d1e7-4b9a-a9d7-3e4cc0dfc2c4",
   "metadata": {},
   "source": [
    "## [JSON mode](https://platform.openai.com/docs/guides/text-generation/json-mode)\n",
    "\n",
    "Constrain the model to only generate valid JSON. Note that you must include a system message with instructions to use JSON for this mode to work.\n",
    "\n",
    "Only works with certain models. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "db6072c4-f3f3-415d-872b-71ea9f3c02bb",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{\n",
      "  \"companies\": [\n",
      "    {\n",
      "      \"name\": \"Google\",\n",
      "      \"origin\": \"USA\"\n",
      "    },\n",
      "    {\n",
      "      \"name\": \"Deepmind\",\n",
      "      \"origin\": \"UK\"\n",
      "    }\n",
      "  ]\n",
      "}\n"
     ]
    }
   ],
   "source": [
    "chat = ChatOpenAI(model=\"gpt-3.5-turbo-1106\").bind(\n",
    "    response_format={\"type\": \"json_object\"}\n",
    ")\n",
    "\n",
    "output = chat.invoke(\n",
    "    [\n",
    "        SystemMessage(\n",
    "            content=\"Extract the 'name' and 'origin' of any companies mentioned in the following statement. Return a JSON list.\"\n",
    "        ),\n",
    "        HumanMessage(\n",
    "            content=\"Google was founded in the USA, while Deepmind was founded in the UK\"\n",
    "        ),\n",
    "    ]\n",
    ")\n",
    "print(output.content)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "08e00ccf-b991-4249-846b-9500a0ccbfa0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'companies': [{'name': 'Google', 'origin': 'USA'},\n",
       "  {'name': 'Deepmind', 'origin': 'UK'}]}"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import json\n",
    "\n",
    "json.loads(output.content)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "aa9a94d9-4319-4ab7-a979-c475ce6b5f50",
   "metadata": {},
   "source": [
    "## [System fingerprint](https://platform.openai.com/docs/guides/text-generation/reproducible-outputs)\n",
    "\n",
    "OpenAI sometimes changes model configurations in a way that impacts outputs. Whenever this happens, the system_fingerprint associated with a generation will change."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "1281883c-bf8f-4665-89cd-4f33ccde69ab",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{'token_usage': {'completion_tokens': 43, 'prompt_tokens': 49, 'total_tokens': 92}, 'model_name': 'gpt-3.5-turbo-1106', 'system_fingerprint': 'fp_eeff13170a'}\n"
     ]
    }
   ],
   "source": [
    "chat = ChatOpenAI(model=\"gpt-3.5-turbo-1106\")\n",
    "output = chat.generate(\n",
    "    [\n",
    "        [\n",
    "            SystemMessage(\n",
    "                content=\"Extract the 'name' and 'origin' of any companies mentioned in the following statement. Return a JSON list.\"\n",
    "            ),\n",
    "            HumanMessage(\n",
    "                content=\"Google was founded in the USA, while Deepmind was founded in the UK\"\n",
    "            ),\n",
    "        ]\n",
    "    ]\n",
    ")\n",
    "print(output.llm_output)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "5c637ba1-322d-4fc9-b97e-3afa83dc4d72",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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