openai-cookbook/examples/Function_calling_with_an_OpenAPI_spec.ipynb

{"cells":[{"attachments":{},"cell_type":"markdown","metadata":{"cell_id":"8317718bcd8b475e9b336514241d679e","deepnote_cell_type":"text-cell-h1","formattedRanges":[]},"source":["# Function-calling with an OpenAPI specification\n"]},{"attachments":{},"cell_type":"markdown","metadata":{"cell_id":"6f810c4e582c41a1bd3bdfc4263dee89","deepnote_cell_type":"text-cell-p","formattedRanges":[]},"source":["Much of the internet is powered by RESTful APIs. Giving GPT the ability to call them opens up a world of possibilities. This notebook demonstrates how GPTs can be used to intelligently call APIs. It leverages OpenAPI specifications and chained function calls.\n","\n","The [OpenAPI Specification (OAS)](https://swagger.io/specification/) is a universally accepted standard for describing the details of RESTful APIs in a format that machines can read and interpret. It enables both humans and computers to understand the capabilities of a service, and it can be leveraged to show GPT how to call APIs.\n","\n","This notebook is divided into two main sections:\n","\n","1. How to convert a sample OpenAPI specification into a list of function definitions for the chat completions API.\n","2. How to use the chat completions API to intelligently invoke these functions based on user instructions.\n","\n","We recommend familiariazing yourself with [function-calling](./How_to_call_functions_with_chat_models.ipynb) before proceding.\n"]},{"cell_type":"code","execution_count":1,"metadata":{"cell_id":"bf983b3e199d4ea6a2718e58a141bd88","deepnote_cell_type":"code","deepnote_to_be_reexecuted":false,"execution_millis":10617,"execution_start":1697419508239,"source_hash":"d6b9a6d3"},"outputs":[{"name":"stdout","output_type":"stream","text":["\u001b[33mDEPRECATION: textract 1.6.5 has a non-standard dependency specifier extract-msg<=0.29.*. pip 23.3 will enforce this behaviour change. A possible replacement is to upgrade to a newer version of textract or contact the author to suggest that they release a version with a conforming dependency specifiers. Discussion can be found at https://github.com/pypa/pip/issues/12063\u001b[0m\u001b[33m\n","\u001b[0m\n","\u001b[1m[\u001b[0m\u001b[34;49mnotice\u001b[0m\u001b[1;39;49m]\u001b[0m\u001b[39;49m A new release of pip is available: \u001b[0m\u001b[31;49m23.2.1\u001b[0m\u001b[39;49m -> \u001b[0m\u001b[32;49m23.3.1\u001b[0m\n","\u001b[1m[\u001b[0m\u001b[34;49mnotice\u001b[0m\u001b[1;39;49m]\u001b[0m\u001b[39;49m To update, run: \u001b[0m\u001b[32;49mpip install --upgrade pip\u001b[0m\n","\u001b[33mDEPRECATION: textract 1.6.5 has a non-standard dependency specifier extract-msg<=0.29.*. pip 23.3 will enforce this behaviour change. A possible replacement is to upgrade to a newer version of textract or contact the author to suggest that they release a version with a conforming dependency specifiers. Discussion can be found at https://github.com/pypa/pip/issues/12063\u001b[0m\u001b[33m\n","\u001b[0m\n","\u001b[1m[\u001b[0m\u001b[34;49mnotice\u001b[0m\u001b[1;39;49m]\u001b[0m\u001b[39;49m A new release of pip is available: \u001b[0m\u001b[31;49m23.2.1\u001b[0m\u001b[39;49m -> \u001b[0m\u001b[32;49m23.3.1\u001b[0m\n","\u001b[1m[\u001b[0m\u001b[34;49mnotice\u001b[0m\u001b[1;39;49m]\u001b[0m\u001b[39;49m To update, run: \u001b[0m\u001b[32;49mpip install --upgrade pip\u001b[0m\n"]}],"source":["!pip install -q jsonref # for resolving $ref's in the OpenAPI spec\n","!pip install -q openai"]},{"cell_type":"code","execution_count":7,"metadata":{"cell_id":"12fb12583cc74b7c842a1b4656b94f47","deepnote_cell_type":"code","deepnote_to_be_reexecuted":false,"execution_millis":10,"execution_start":1697419706563,"source_hash":"750280cb"},"outputs":[],"source":["import os\n","import json\n","import jsonref\n","from openai import OpenAI\n","import requests\n","from pprint import pp\n","\n","client = OpenAI(api_key=os.environ.get(\"OPENAI_API_KEY\", \"<your OpenAI API key if not set as env var>\"))"]},{"attachments":{},"cell_type":"markdown","metadata":{"cell_id":"76ae868e66b14cc48c9c447302ea268e","deepnote_cell_type":"text-cell-h2","formattedRan