qeleb
diff --git a/‎examples/notebooks/Functions.ipynb
Copy file name to clipboardExpand all lines: examples/notebooks/Functions.ipynb
+77-17Lines changed: 77 additions & 17 deletions b/‎examples/notebooks/Functions.ipynb
Copy file name to clipboardExpand all lines: examples/notebooks/Functions.ipynb
+77-17Lines changed: 77 additions & 17 deletions
@@ -1,15 +1,22 @@
 {
  "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Function Calling with OpenAI Python Client"
+   ]
+  },
   {
    "cell_type": "code",
-   "execution_count": 29,
+   "execution_count": 4,
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "ChatCompletion(id='chatcmpl-b6dcbb47-1120-4761-8cd9-83542c97647b', choices=[Choice(finish_reason='stop', index=0, message=ChatCompletionMessage(content=\"The current temperature in San Francisco is 72 degrees Fahrenheit. It's a sunny day with clear skies, making it perfect for outdoor activities.\\n \", role='assistant', function_call=None, tool_calls=None))], created=1699602158, model='gpt-3.5-turbo-1106', object='chat.completion', system_fingerprint=None, usage=CompletionUsage(completion_tokens=38, prompt_tokens=135, total_tokens=173))\n"
+      "ChatCompletion(id='chatcmpl-a2d9eb9f-7354-472f-b6ad-4d7a807729a3', choices=[Choice(finish_reason='stop', index=0, message=ChatCompletionMessage(content='The current weather in San Francisco is **72°F** (22°C).\\n ', role='assistant', function_call=None, tool_calls=None))], created=1699638365, model='gpt-3.5-turbo-1106', object='chat.completion', system_fingerprint=None, usage=CompletionUsage(completion_tokens=22, prompt_tokens=136, total_tokens=158))\n"
      ]
     }
    ],
@@ -100,9 +107,26 @@
     "print(run_conversation())"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Function Calling with Instructor\n",
+    "\n",
+    "You'll need to install the [`instructor`](https://github.com/jxnl/instructor/) package to run this notebook. You can do so by running the following command in your terminal:\n",
+    "\n",
+    "```bash\n",
+    "pip install instructor\n",
+    "```\n",
+    "\n",
+    "We'll highlight a few basic examples taken from the [instructor cookbook](https://jxnl.github.io/instructor/)\n",
+    "\n",
+    "## Basic Usage"
+   ]
+  },
   {
    "cell_type": "code",
-   "execution_count": 30,
+   "execution_count": 5,
    "metadata": {},
    "outputs": [
     {
@@ -139,11 +163,28 @@
     "print(user)"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Text Classification\n",
+    "\n",
+    "### Single-Label Classification"
+   ]
+  },
   {
    "cell_type": "code",
-   "execution_count": 31,
+   "execution_count": 7,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "class_label=<Labels.SPAM: 'spam'>\n"
+     ]
+    }
+   ],
    "source": [
     "import enum\n",
     "\n",
@@ -172,19 +213,27 @@
     "    )  # type: ignore\n",
     "\n",
     "prediction = classify(\"Hello there I'm a Nigerian prince and I want to give you money\")\n",
-    "assert prediction.class_label == Labels.SPAM"
+    "assert prediction.class_label == Labels.SPAM\n",
+    "print(prediction)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Multi-Label Classification"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 32,
+   "execution_count": 12,
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "class_labels=[<MultiLabels.BILLING: 'billing'>, <MultiLabels.TECH_ISSUE: 'tech_issue'>]\n"
+      "class_labels=[<MultiLabels.TECH_ISSUE: 'tech_issue'>, <MultiLabels.BILLING: 'billing'>]\n"
      ]
     }
    ],
@@ -223,16 +272,27 @@
     "print(prediction)"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Self-Critique"
+   ]
+  },
   {
    "cell_type": "code",
-   "execution_count": 33,
+   "execution_count": 13,
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "question='What is the meaning of life?' answer='The meaning of life, according to the Devil, is to live a life of sin and debauchery.'\n"
+      "question='What is the meaning of life?' answer='According to the Devil, the meaning of life is to live a life of sin and debauchery.'\n",
+      "1 validation error for QuestionAnswerNoEvil\n",
+      "answer\n",
+      "  Assertion failed, The statement promotes sin and debauchery, which can be considered objectionable. [type=assertion_error, input_value='According to the Devil, ... of sin and debauchery.', input_type=str]\n",
+      "    For further information visit https://errors.pydantic.dev/2.3/v/assertion_error\n"
      ]
     }
    ],
@@ -294,6 +354,13 @@
     "    print(e)"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Answering Questions with Validated Citations"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": 42,
@@ -366,13 +433,6 @@
     "qa = ask_ai(question, context)\n",
     "print(qa)"
    ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": []
   }
  ],
  "metadata": {