update_annotations.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import dotenv\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "ename": "OpenAIError",
     "evalue": "The api_key client option must be set either by passing api_key to the client or by setting the OPENAI_API_KEY environment variable",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mOpenAIError\u001b[0m                               Traceback (most recent call last)",
      "Cell \u001b[0;32mIn[1], line 3\u001b[0m\n\u001b[1;32m      1\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mguidance\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m models, gen, user, assistant\n\u001b[0;32m----> 3\u001b[0m gpt \u001b[38;5;241m=\u001b[39m \u001b[43mmodels\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mOpenAI\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mgpt-3.5-turbo\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m)\u001b[49m\n\u001b[1;32m      5\u001b[0m \u001b[38;5;28;01mwith\u001b[39;00m user():\n\u001b[1;32m      6\u001b[0m     lm \u001b[38;5;241m=\u001b[39m gpt \u001b[38;5;241m+\u001b[39m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mWhat is the capital of France?\u001b[39m\u001b[38;5;124m\"\u001b[39m\n",
      "File \u001b[0;32m~/micromamba/envs/guidance/lib/python3.11/site-packages/guidance/models/_openai.py:80\u001b[0m, in \u001b[0;36mOpenAI.__init__\u001b[0;34m(self, model, tokenizer, echo, caching, api_key, temperature, top_p, max_streaming_tokens, **kwargs)\u001b[0m\n\u001b[1;32m     78\u001b[0m     \u001b[38;5;66;03m# convert to any found subclass\u001b[39;00m\n\u001b[1;32m     79\u001b[0m     \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m\u001b[38;5;18m__class__\u001b[39m \u001b[38;5;241m=\u001b[39m found_subclass\n\u001b[0;32m---> 80\u001b[0m     \u001b[43mfound_subclass\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[38;5;21;43m__init__\u001b[39;49m\u001b[43m(\u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mmodel\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mtokenizer\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mtokenizer\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mecho\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mecho\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mcaching\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mcaching\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mapi_key\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mapi_key\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mtemperature\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mtemperature\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mmax_streaming_tokens\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mmax_streaming_tokens\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m     81\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;66;03m# we return since we just ran init above and don't need to run again\u001b[39;00m\n\u001b[1;32m     83\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mclient \u001b[38;5;241m=\u001b[39m openai_package\u001b[38;5;241m.\u001b[39mOpenAI(api_key\u001b[38;5;241m=\u001b[39mapi_key, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs)\n",
      "File \u001b[0;32m~/micromamba/envs/guidance/lib/python3.11/site-packages/guidance/models/_openai.py:234\u001b[0m, in \u001b[0;36mOpenAIChat.__init__\u001b[0;34m(self, *args, **kwargs)\u001b[0m\n\u001b[1;32m    233\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21m__init__\u001b[39m(\u001b[38;5;28mself\u001b[39m, \u001b[38;5;241m*\u001b[39margs, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs):\n\u001b[0;32m--> 234\u001b[0m     \u001b[38;5;28;43msuper\u001b[39;49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[38;5;21;43m__init__\u001b[39;49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n",
      "File \u001b[0;32m~/micromamba/envs/guidance/lib/python3.11/site-packages/guidance/models/_openai.py:83\u001b[0m, in \u001b[0;36mOpenAI.__init__\u001b[0;34m(self, model, tokenizer, echo, caching, api_key, temperature, top_p, max_streaming_tokens, **kwargs)\u001b[0m\n\u001b[1;32m     80\u001b[0m     found_subclass\u001b[38;5;241m.\u001b[39m\u001b[38;5;21m__init__\u001b[39m(\u001b[38;5;28mself\u001b[39m, model, tokenizer\u001b[38;5;241m=\u001b[39mtokenizer, echo\u001b[38;5;241m=\u001b[39mecho, caching\u001b[38;5;241m=\u001b[39mcaching, api_key\u001b[38;5;241m=\u001b[39mapi_key, temperature\u001b[38;5;241m=\u001b[39mtemperature, max_streaming_tokens\u001b[38;5;241m=\u001b[39mmax_streaming_tokens, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs)\n\u001b[1;32m     81\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;66;03m# we return since we just ran init above and don't need to run again\u001b[39;00m\n\u001b[0;32m---> 83\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mclient \u001b[38;5;241m=\u001b[39m \u001b[43mopenai_package\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mOpenAI\u001b[49m\u001b[43m(\u001b[49m\u001b[43mapi_key\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mapi_key\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m     84\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mmodel_name \u001b[38;5;241m=\u001b[39m model\n\u001b[1;32m     85\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mtop_p \u001b[38;5;241m=\u001b[39m top_p\n",
      "File \u001b[0;32m~/micromamba/envs/guidance/lib/python3.11/site-packages/openai/_client.py:98\u001b[0m, in \u001b[0;36mOpenAI.__init__\u001b[0;34m(self, api_key, organization, base_url, timeout, max_retries, default_headers, default_query, http_client, _strict_response_validation)\u001b[0m\n\u001b[1;32m     96\u001b[0m     api_key \u001b[38;5;241m=\u001b[39m os\u001b[38;5;241m.\u001b[39menviron\u001b[38;5;241m.\u001b[39mget(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mOPENAI_API_KEY\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n\u001b[1;32m     97\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m api_key \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n\u001b[0;32m---> 98\u001b[0m     \u001b[38;5;28;01mraise\u001b[39;00m OpenAIError(\n\u001b[1;32m     99\u001b[0m         \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mThe api_key client option must be set either by passing api_key to the client or by setting the OPENAI_API_KEY environment variable\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m    100\u001b[0m     )\n\u001b[1;32m    101\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mapi_key \u001b[38;5;241m=\u001b[39m api_key\n\u001b[1;32m    103\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m organization \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n",
      "\u001b[0;31mOpenAIError\u001b[0m: The api_key client option must be set either by passing api_key to the client or by setting the OPENAI_API_KEY environment variable"
     ]
    }
   ],
   "source": [
    "from guidance import models, gen, user, assistant\n",
    "\n",
    "gpt = models.OpenAI(\"gpt-3.5-turbo\")\n",
    "\n",
    "with user():\n",
    "    lm = gpt + \"What is the capital of France?\"\n",
    "\n",
    "with assistant():\n",
    "    lm += gen(\"capital\")\n",
    "\n",
    "with user():\n",
    "    lm += \"What is one short surprising fact about it?\"\n",
    "\n",
    "with assistant():\n",
    "    lm += gen(\"fact\")"
   ]
  }
 ],
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