{ "cells": [ { "cell_type": "code", "execution_count": 1, "id": "17d6b46e-8c81-49b6-b478-48826c091fc3", "metadata": {}, "outputs": [], "source": [ "import os\n", "from dotenv import load_dotenv, find_dotenv\n", "_ = load_dotenv(find_dotenv())\n", "openai_api_key = os.environ[\"OPENAI_API_KEY\"]" ] }, { "cell_type": "markdown", "id": "6d41f440-273f-4efd-86a5-b0ac05164db4", "metadata": {}, "source": [ "## GPT-4 128k Context Length\n", "* Changes RAG: Now you can load one book at a time." ] }, { "cell_type": "code", "execution_count": null, "id": "4243f9ff-47e0-497e-89bc-eaaa5c5840bc", "metadata": {}, "outputs": [], "source": [ "import openai\n", "\n", "with open(\"my_long_document.txt\") as f:\n", " book_text = f.read()\n", "\n", "response = openai.chat.completions.create(\n", " model=\"gpt-4-1106-preview\",\n", " messages=[\n", " {\n", " \"role\": \"user\",\n", " \"content\": book_text + \"My question about the document?\"\n", " }\n", " ]\n", ")\n", "\n", "print(response.choices[0].message.content)\n", "\n", "print(f\"\\nTotal tokens: {response.usage.total_tokens}\")" ] }, { "cell_type": "markdown", "id": "0e68a57f-7a74-4806-b5c7-469da070a4f6", "metadata": {}, "source": [ "## Multiple Function Calling" ] }, { "cell_type": "code", "execution_count": null, "id": "2ed961a2-48ec-4ee7-a03e-9e965d595cb3", "metadata": {}, "outputs": [], "source": [ "import openai\n", "\n", "messages = [\n", " {\n", " \"role\": \"user\",\n", " \"content\": input(\"Message: \")\n", " }\n", "]\n", "\n", "tools = [\n", " {\n", " \"type\": \"function\",\n", " \"function\": {\n", " \"name\": \"play_song\",\n", " \"description\": \"Play a song\",\n", " \"parameters\": {\n", " \"type\": \"object\",\n", " \"properties\": {\n", " \"song_name\": {\n", " \"type\": \"string\",\n", " \"description\": \"The name of the song to play\",\n", " },\n", " },\n", " \"required\": [\"song_name\"],\n", " },\n", " },\n", " },\n", " {\n", " \"type\": \"function\",\n", " \"function\": {\n", " \"name\": \"light_dimmer\",\n", " \"description\": \"Adjust the light dimmer from 0-100\",\n", " \"parameters\": {\n", " \"type\": \"object\",\n", " \"properties\": {\n", " \"brightness\": {\n", " \"type\": \"number\",\n", " \"description\": \"The brightness from 0-100\",\n", " },\n", " },\n", " \"required\": [\"brightness\"],\n", " },\n", " },\n", " },\n", " {\n", " \"type\": \"function\",\n", " \"function\": {\n", " \"name\": \"order_food\",\n", " \"description\": \"Order food from a restaurant\",\n", " \"parameters\": {\n", " \"type\": \"object\",\n", " \"properties\": {\n", " \"dish_name\": {\n", " \"type\": \"string\",\n", " \"description\": \"The name of the dish to order\",\n", " },\n", " \"count\": {\n", " \"type\": \"number\",\n", " \"description\": \"The number of dishes to order\",\n", " },\n", " },\n", " \"required\": [\"dish_name\", \"count\"],\n", " },\n", " },\n", " },\n", " {\n", " \"type\": \"function\",\n", " \"function\": {\n", " \"name\": \"send_sms\",\n", " \"description\": \"Send a text message to a contact\",\n", " \"parameters\": {\n", " \"type\": \"object\",\n", " \"properties\": {\n", " \"contact_name\": {\n", " \"type\": \"string\",\n", " \"description\": \"The name of the contact\",\n", " },\n", " \"message\": {\n", " \"type\": \"string\",\n", " \"description\": \"The text message content\",\n", " },\n", " },\n", " \"required\": [\"contact_name\", \"message\"],\n", " },\n", " },\n", " }\n", "]\n", "\n", "response = openai.chat.completions.create(\n", " #model=\"gpt-3.5-turbo-1106\",\n", " model=\"gpt-4-1106-preview\",\n", " messages=messages,\n", " tools=tools,\n", " tool_choice=\"auto\",\n", ")\n", "\n", "response_message = response.choices[0].message\n", "\n", "tool_calls = response_message.tool_calls\n", "\n", "messages.append(response_message)\n", "\n", "for tool_call in tool_calls:\n", " function_name = tool_call.function.name\n", " arguments = tool_call.function.arguments\n", " print(f\"Called '{function_name}' with args {arguments}\")\n" ] }, { "cell_type": "markdown", "id": "66761ae6-a4ae-4f2c-b35b-dd083bfcc821", "metadata": {}, "source": [ "## JSON Mode\n", "* Changes: the most popular Output Parser is not needed anymore." ] }, { "cell_type": "code", "execution_count": null, "id": "a91df214-5bb7-467e-aaef-12dd62851271", "metadata": {}, "outputs": [], "source": [ "import openai\n", "import json\n", "\n", "response = openai.chat.completions.create(\n", " model=\"gpt-3.5-turbo-1106\",\n", " messages=[\n", " {\n", " \"role\": \"system\",\n", " \"content\": \"You are a book suggester. Respond with a book title, description and category in JSON format.\"\n", " },\n", " {\n", " \"role\": \"user\",\n", " \"content\": \"I want to make lots of money\"\n", " }\n", " ],\n", " response_format={\"type\": \"json_object\"}\n", ")\n", "\n", "print(\n", " json.dumps(\n", " json.loads(\n", " response.choices[0].message.content\n", " ),\n", " indent=4\n", " )\n", ")" ] }, { "cell_type": "markdown", "id": "45e0ec55-0796-4a6d-a5de-38dd4fa18c76", "metadata": {}, "source": [ "## Reproducible Outputs (Seed Parameter)" ] }, { "cell_type": "code", "execution_count": null, "id": "3c9b444d-a9c7-4de3-b326-63efbbf6dd55", "metadata": {}, "outputs": [], "source": [ "import openai\n", "\n", "response = openai.chat.completions.create(\n", " model=\"gpt-3.5-turbo-1106\",\n", " seed=3453,\n", " messages=[\n", " {\n", " \"role\": \"user\",\n", " \"content\": \"Create a story about a boy and his dog. Give them names\"\n", " }\n", " ],\n", " max_tokens=256,\n", ")\n", "\n", "print(response.choices[0].message.content)\n" ] }, { "cell_type": "markdown", "id": "9278714a-98cc-4473-8a39-22c2eedde46a", "metadata": {}, "source": [ "## Assistants" ] }, { "cell_type": "code", "execution_count": null, "id": "5c87af25-c47d-4f65-a5ac-67c03785b94b", "metadata": {}, "outputs": [], "source": [ "import openai\n", "\n", "assistant = openai.beta.assistants.create(\n", " model=\"gpt-3.5-turbo-1106\",\n", " name=\"Riddlebot\",\n", " instructions=\"You answer all questions in riddles\",\n", ")\n", "\n", "print(f\"Assistant ID: {assistant.id}\")\n", "\n", "thread = openai.beta.threads.create(\n", " messages=[\n", " {\n", " \"role\": \"user\",\n", " \"content\": \"How do I get started with Python?\",\n", " }\n", " ]\n", ")\n", "\n", "print(f\"Thread ID: {thread.id}\")\n", "\n", "run = openai.beta.threads.runs.create(\n", " thread_id=thread.id,\n", " assistant_id=assistant.id,\n", ")\n", "\n", "print(f\"Run ID: {run.id}\")\n" ] }, { "cell_type": "markdown", "id": "bb34ee52-46f1-49b8-a1b4-d6282e80cd88", "metadata": {}, "source": [ "## RAG Assistant\n", "* Changes RAG: not necessary for simple cases.\n", "* RAG still necessary for complex and sophisticated cases." ] }, { "cell_type": "code", "execution_count": null, "id": "7d9b9f1f-8cd3-415a-a0ed-5ae1945e0729", "metadata": {}, "outputs": [], "source": [ "import openai\n", "\n", "file = openai.files.create(\n", " file=openai.file_from_path(\"file.pdf\"),\n", " purpose=\"assistants\",\n", ")\n", "\n", "assistant = openai.beta.assistants.create(\n", " model=\"gpt-3.5-turbo-1106\",\n", " file_ids=[\n", " file.id,\n", " ],\n", " tools=[\n", " {\"type\": \"retrieval\"},\n", " ]\n", ")\n", "\n", "thread = openai.beta.threads.create()\n", "\n", "print(f\"File ID: {file.id}\")\n", "print(f\"Assistant ID: {assistant.id}\")\n", "print(f\"Thread ID: {thread.id}\\n\")\n", "\n", "print(\"GPT: Hello! How can I assist you today?\")\n", "\n", "while True:\n", " message = input(\"You: \")\n", " print()\n", "\n", " openai.beta.threads.messages.create(\n", " thread_id=thread.id,\n", " role=\"user\",\n", " content=message,\n", " )\n", "\n", " run = openai.beta.threads.runs.create(\n", " thread_id=thread.id,\n", " assistant_id=assistant.id,\n", " )\n", "\n", " while True:\n", " run = openai.beta.threads.runs.retrieve(\n", " run_id=run.id,\n", " thread_id=thread.id,\n", " )\n", "\n", " if run.status not in [\"queued\", \"in_progress\", \"cancelling\"]:\n", " break\n", "\n", " messages = openai.beta.threads.messages.list(\n", " thread_id=thread.id,\n", " limit=1,\n", " )\n", " print(\"GPT: \" + messages.data[0].content[0].text.value)\n" ] }, { "cell_type": "markdown", "id": "572a0506-0eae-46d8-a2a8-4ea093da8359", "metadata": {}, "source": [ "## Multi-modality: Vision" ] }, { "cell_type": "code", "execution_count": null, "id": "242d2c68-2fa0-4a38-948d-6e985fe7e940", "metadata": {}, "outputs": [], "source": [ "import openai\n", "import base64\n", "\n", "def encode_image(image_path):\n", " with open(image_path, \"rb\") as f:\n", " return base64.b64encode(f.read()).decode()\n", "\n", "base64_image = encode_image(\"test.jpg\")\n", "\n", "response = openai.chat.completions.create(\n", " model=\"gpt-4-vision-preview\",\n", " messages=[\n", " {\n", " \"role\": \"user\",\n", " \"content\": [\n", " {\n", " \"type\": \"text\",\n", " \"text\": \"What's in this image?\",\n", " },\n", " {\n", " \"type\": \"image_url\",\n", " \"image_url\": f\"data:image/jpeg;base64,{base64_image}\",\n", " }\n", " ]\n", " }\n", " ]\n", ")\n", "\n", "print(response.choices[0].message.content)\n" ] }, { "cell_type": "markdown", "id": "4c2ca626-13d4-45f3-8189-1172ea814fa0", "metadata": {}, "source": [ "## Multi-modality: Audio (TextSpeech)" ] }, { "cell_type": "code", "execution_count": null, "id": "69ba8815-e5b5-4987-968f-76dd4945da6f", "metadata": {}, "outputs": [], "source": [ "import playsound\n", "import openai\n", "import json\n", "import os\n", "\n", "def play_with_voice(voice, speech):\n", " audio = openai.audio.speech.create(\n", " input=speech,\n", " model=\"tts-1\",\n", " voice=voice,\n", " )\n", "\n", " audio.stream_to_file(\"audio.mp3\")\n", " playsound.playsound(\"audio.mp3\")\n", " os.remove(\"audio.mp3\")\n", "\n", "def mark_speaks(speech):\n", " play_with_voice(\"echo\", speech)\n", "\n", "def lisa_speaks(speech):\n", " play_with_voice(\"nova\", speech)\n", "\n", "response = openai.chat.completions.create(\n", " model=\"gpt-3.5-turbo-1106\",\n", " messages=[\n", " {\n", " \"role\": \"system\",\n", " \"content\": \"You are a conversation generator. Generate the full conversation using function calls. Call the speech functions 5 times for both Mark and Lisa\",\n", " },\n", " {\n", " \"role\": \"user\",\n", " \"content\": \"Create a conversation between Lisa and Mark. They're talking about Rust vs C++\"\n", " }\n", " ],\n", " tools=[\n", " {\n", " \"type\": \"function\",\n", " \"function\": {\n", " \"name\": \"mark_speaks\",\n", " \"parameters\": {\n", " \"type\": \"object\",\n", " \"properties\": {\n", " \"speech\": {\n", " \"type\": \"string\"\n", " }\n", " }\n", " }\n", " }\n", " },\n", " {\n", " \"type\": \"function\",\n", " \"function\": {\n", " \"name\": \"lisa_speaks\",\n", " \"parameters\": {\n", " \"type\": \"object\",\n", " \"properties\": {\n", " \"speech\": {\n", " \"type\": \"string\"\n", " }\n", " }\n", " }\n", " }\n", " }\n", " ]\n", ")\n", "\n", "for tool_call in response.choices[0].message.tool_calls:\n", " function_name = tool_call.function.name\n", " arguments = json.loads(tool_call.function.arguments)\n", "\n", " print(function_name + \": \" + arguments[\"speech\"])\n", "\n", " if function_name in [\"mark_speaks\", \"lisa_speaks\"]:\n", " globals()[function_name](**arguments)\n" ] }, { "cell_type": "code", "execution_count": null, "id": "610bdbaf-2d42-4faa-b5e3-acdbe7167c9a", "metadata": {}, "outputs": [], "source": [] } ], "metadata": { "kernelspec": { "display_name": "Python 3 (ipykernel)", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.11.4" } }, "nbformat": 4, "nbformat_minor": 5 }