ChatCompletion

hugging_face.ipynb

@@ -2,7 +2,7 @@
  "cells": [
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": 1,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -13,7 +13,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": 2,
    "metadata": {},
    "outputs": [
     {

prompt.ipynb

@@ -10,15 +10,108 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 2,
    "metadata": {},
    "outputs": [],
-   "source": []
+   "source": [
+    "from auth import API_KEY\n",
+    "import openai"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "openai.api_key = API_KEY"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def get_completion(prompt, model='gpt-3.5-turbo'):\n",
+    "    messages = [{'role':'user', 'content': prompt}]\n",
+    "    response = openai.ChatCompletion.create(\n",
+    "        model=model,\n",
+    "        messages = messages,\n",
+    "        temperature = 0, # this is the degree of randomness of the model's output\n",
+    "    )\n",
+    "    return response.choices[0].message['content']"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "text = f\"\"\"\n",
+    "You should express what you want a model to do by \\ \n",
+    "providing instructions that are as clear and \\ \n",
+    "specific as you can possibly make them. \\ \n",
+    "This will guide the model towards the desired output, \\ \n",
+    "and reduce the chances of receiving irrelevant \\ \n",
+    "or incorrect responses. Don't confuse writing a \\ \n",
+    "clear prompt with writing a short prompt. \\ \n",
+    "In many cases, longer prompts provide more clarity \\ \n",
+    "and context for the model, which can lead to \\ \n",
+    "more detailed and relevant outputs.\n",
+    "\"\"\""
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "prompt = f\"\"\"\n",
+    "Summarize the text delimited by triple backticks \\ \n",
+    "into a single sentence.\n",
+    "```{text}```\n",
+    "\"\"\""
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Clear and specific instructions should be provided to guide a model towards the desired output, and longer prompts can provide more clarity and context for the model, leading to more detailed and relevant outputs.\n"
+     ]
+    }
+   ],
+   "source": [
+    "response = get_completion(prompt)\n",
+    "print(response)"
+   ]
   }
  ],
  "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
   "language_info": {
-   "name": "python"
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.10.6"
   },
   "orig_nbformat": 4
  },