From 92de8d33afacd64a7bb449803971d4451e1a838d Mon Sep 17 00:00:00 2001 From: danielquillanroxas Date: Thu, 30 Jan 2025 15:13:30 +0300 Subject: [PATCH 1/5] Added llama for day1 and tones for day2 (week2) --- .../day1-3way-with-llama3.2.ipynb | 727 ++++++++++++++++++ .../day2-different-tones.ipynb | 575 ++++++++++++++ 2 files changed, 1302 insertions(+) create mode 100644 week2/community-contributions/day1-3way-with-llama3.2.ipynb create mode 100644 week2/community-contributions/day2-different-tones.ipynb diff --git a/week2/community-contributions/day1-3way-with-llama3.2.ipynb b/week2/community-contributions/day1-3way-with-llama3.2.ipynb new file mode 100644 index 0000000..835ae87 --- /dev/null +++ b/week2/community-contributions/day1-3way-with-llama3.2.ipynb @@ -0,0 +1,727 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "id": "06cf3063-9f3e-4551-a0d5-f08d9cabb927", + "metadata": {}, + "source": [ + "# Welcome to Week 2!\n", + "\n", + "## Frontier Model APIs\n", + "\n", + "In Week 1, we used multiple Frontier LLMs through their Chat UI, and we connected with the OpenAI's API.\n", + "\n", + "Today we'll connect with the APIs for Anthropic and Google, as well as OpenAI." + ] + }, + { + "cell_type": "markdown", + "id": "2b268b6e-0ba4-461e-af86-74a41f4d681f", + "metadata": {}, + "source": [ + "\n", + " \n", + " \n", + " \n", + " \n", + "
\n", + " \n", + " \n", + "

Important Note - Please read me

\n", + " I'm continually improving these labs, adding more examples and exercises.\n", + " At the start of each week, it's worth checking you have the latest code.
\n", + " First do a git pull and merge your changes as needed. Any problems? Try asking ChatGPT to clarify how to merge - or contact me!

\n", + " After you've pulled the code, from the llm_engineering directory, in an Anaconda prompt (PC) or Terminal (Mac), run:
\n", + " conda env update --f environment.yml
\n", + " Or if you used virtualenv rather than Anaconda, then run this from your activated environment in a Powershell (PC) or Terminal (Mac):
\n", + " pip install -r requirements.txt\n", + "
Then restart the kernel (Kernel menu >> Restart Kernel and Clear Outputs Of All Cells) to pick up the changes.\n", + "
\n", + "
\n", + "\n", + " \n", + " \n", + " \n", + " \n", + "
\n", + " \n", + " \n", + "

Reminder about the resources page

\n", + " Here's a link to resources for the course. This includes links to all the slides.
\n", + " https://edwarddonner.com/2024/11/13/llm-engineering-resources/
\n", + " Please keep this bookmarked, and I'll continue to add more useful links there over time.\n", + "
\n", + "
" + ] + }, + { + "cell_type": "markdown", + "id": "85cfe275-4705-4d30-abea-643fbddf1db0", + "metadata": {}, + "source": [ + "## Setting up your keys\n", + "\n", + "If you haven't done so already, you could now create API keys for Anthropic and Google in addition to OpenAI.\n", + "\n", + "**Please note:** if you'd prefer to avoid extra API costs, feel free to skip setting up Anthopic and Google! You can see me do it, and focus on OpenAI for the course. You could also substitute Anthropic and/or Google for Ollama, using the exercise you did in week 1.\n", + "\n", + "For OpenAI, visit https://openai.com/api/ \n", + "For Anthropic, visit https://console.anthropic.com/ \n", + "For Google, visit https://ai.google.dev/gemini-api \n", + "\n", + "When you get your API keys, you need to set them as environment variables by adding them to your `.env` file.\n", + "\n", + "```\n", + "OPENAI_API_KEY=xxxx\n", + "ANTHROPIC_API_KEY=xxxx\n", + "GOOGLE_API_KEY=xxxx\n", + "```\n", + "\n", + "Afterwards, you may need to restart the Jupyter Lab Kernel (the Python process that sits behind this notebook) via the Kernel menu, and then rerun the cells from the top." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "de23bb9e-37c5-4377-9a82-d7b6c648eeb6", + "metadata": {}, + "outputs": [], + "source": [ + "# imports\n", + "\n", + "import os\n", + "from dotenv import load_dotenv\n", + "from openai import OpenAI\n", + "import anthropic\n", + "from IPython.display import Markdown, display, update_display" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "f0a8ab2b-6134-4104-a1bc-c3cd7ea4cd36", + "metadata": {}, + "outputs": [], + "source": [ + "# import for google\n", + "# in rare cases, this seems to give an error on some systems, or even crashes the kernel\n", + "# If this happens to you, simply ignore this cell - I give an alternative approach for using Gemini later\n", + "\n", + "import google.generativeai" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "1179b4c5-cd1f-4131-a876-4c9f3f38d2ba", + "metadata": {}, + "outputs": [], + "source": [ + "# Load environment variables in a file called .env\n", + "# Print the key prefixes to help with any debugging\n", + "\n", + "load_dotenv()\n", + "openai_api_key = os.getenv('OPENAI_API_KEY')\n", + "anthropic_api_key = os.getenv('ANTHROPIC_API_KEY')\n", + "google_api_key = os.getenv('GOOGLE_API_KEY')\n", + "\n", + "if openai_api_key:\n", + " print(f\"OpenAI API Key exists and begins {openai_api_key[:8]}\")\n", + "else:\n", + " print(\"OpenAI API Key not set\")\n", + " \n", + "if anthropic_api_key:\n", + " print(f\"Anthropic API Key exists and begins {anthropic_api_key[:7]}\")\n", + "else:\n", + " print(\"Anthropic API Key not set\")\n", + "\n", + "if google_api_key:\n", + " print(f\"Google API Key exists and begins {google_api_key[:8]}\")\n", + "else:\n", + " print(\"Google API Key not set\")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "797fe7b0-ad43-42d2-acf0-e4f309b112f0", + "metadata": {}, + "outputs": [], + "source": [ + "# Connect to OpenAI, Anthropic\n", + "\n", + "openai = OpenAI()\n", + "\n", + "claude = anthropic.Anthropic()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "425ed580-808d-429b-85b0-6cba50ca1d0c", + "metadata": {}, + "outputs": [], + "source": [ + "# This is the set up code for Gemini\n", + "# Having problems with Google Gemini setup? Then just ignore this cell; when we use Gemini, I'll give you an alternative that bypasses this library altogether\n", + "\n", + "google.generativeai.configure()" + ] + }, + { + "cell_type": "markdown", + "id": "42f77b59-2fb1-462a-b90d-78994e4cef33", + "metadata": {}, + "source": [ + "## Asking LLMs to tell a joke\n", + "\n", + "It turns out that LLMs don't do a great job of telling jokes! Let's compare a few models.\n", + "Later we will be putting LLMs to better use!\n", + "\n", + "### What information is included in the API\n", + "\n", + "Typically we'll pass to the API:\n", + "- The name of the model that should be used\n", + "- A system message that gives overall context for the role the LLM is playing\n", + "- A user message that provides the actual prompt\n", + "\n", + "There are other parameters that can be used, including **temperature** which is typically between 0 and 1; higher for more random output; lower for more focused and deterministic." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "378a0296-59a2-45c6-82eb-941344d3eeff", + "metadata": {}, + "outputs": [], + "source": [ + "system_message = \"You are an assistant that is great at telling jokes\"\n", + "user_prompt = \"Tell a light-hearted joke for an audience of Data Scientists\"" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "f4d56a0f-2a3d-484d-9344-0efa6862aff4", + "metadata": {}, + "outputs": [], + "source": [ + "prompts = [\n", + " {\"role\": \"system\", \"content\": system_message},\n", + " {\"role\": \"user\", \"content\": user_prompt}\n", + " ]" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "3b3879b6-9a55-4fed-a18c-1ea2edfaf397", + "metadata": {}, + "outputs": [], + "source": [ + "# GPT-3.5-Turbo\n", + "\n", + "completion = openai.chat.completions.create(model='gpt-3.5-turbo', messages=prompts)\n", + "print(completion.choices[0].message.content)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "3d2d6beb-1b81-466f-8ed1-40bf51e7adbf", + "metadata": {}, + "outputs": [], + "source": [ + "# GPT-4o-mini\n", + "# Temperature setting controls creativity\n", + "\n", + "completion = openai.chat.completions.create(\n", + " model='gpt-4o-mini',\n", + " messages=prompts,\n", + " temperature=0.7\n", + ")\n", + "print(completion.choices[0].message.content)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "f1f54beb-823f-4301-98cb-8b9a49f4ce26", + "metadata": {}, + "outputs": [], + "source": [ + "# GPT-4o\n", + "\n", + "completion = openai.chat.completions.create(\n", + " model='gpt-4o',\n", + " messages=prompts,\n", + " temperature=0.4\n", + ")\n", + "print(completion.choices[0].message.content)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "1ecdb506-9f7c-4539-abae-0e78d7f31b76", + "metadata": {}, + "outputs": [], + "source": [ + "# Claude 3.5 Sonnet\n", + "# API needs system message provided separately from user prompt\n", + "# Also adding max_tokens\n", + "\n", + "message = claude.messages.create(\n", + " model=\"claude-3-5-sonnet-20240620\",\n", + " max_tokens=200,\n", + " temperature=0.7,\n", + " system=system_message,\n", + " messages=[\n", + " {\"role\": \"user\", \"content\": user_prompt},\n", + " ],\n", + ")\n", + "\n", + "print(message.content[0].text)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "769c4017-4b3b-4e64-8da7-ef4dcbe3fd9f", + "metadata": {}, + "outputs": [], + "source": [ + "# Claude 3.5 Sonnet again\n", + "# Now let's add in streaming back results\n", + "\n", + "result = claude.messages.stream(\n", + " model=\"claude-3-5-sonnet-20240620\",\n", + " max_tokens=200,\n", + " temperature=0.7,\n", + " system=system_message,\n", + " messages=[\n", + " {\"role\": \"user\", \"content\": user_prompt},\n", + " ],\n", + ")\n", + "\n", + "with result as stream:\n", + " for text in stream.text_stream:\n", + " print(text, end=\"\", flush=True)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "6df48ce5-70f8-4643-9a50-b0b5bfdb66ad", + "metadata": {}, + "outputs": [], + "source": [ + "# The API for Gemini has a slightly different structure.\n", + "# I've heard that on some PCs, this Gemini code causes the Kernel to crash.\n", + "# If that happens to you, please skip this cell and use the next cell instead - an alternative approach.\n", + "\n", + "gemini = google.generativeai.GenerativeModel(\n", + " model_name='gemini-1.5-flash',\n", + " system_instruction=system_message\n", + ")\n", + "response = gemini.generate_content(user_prompt)\n", + "print(response.text)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "49009a30-037d-41c8-b874-127f61c4aa3a", + "metadata": {}, + "outputs": [], + "source": [ + "# As an alternative way to use Gemini that bypasses Google's python API library,\n", + "# Google has recently released new endpoints that means you can use Gemini via the client libraries for OpenAI!\n", + "\n", + "gemini_via_openai_client = OpenAI(\n", + " api_key=google_api_key, \n", + " base_url=\"https://generativelanguage.googleapis.com/v1beta/openai/\"\n", + ")\n", + "\n", + "response = gemini_via_openai_client.chat.completions.create(\n", + " model=\"gemini-1.5-flash\",\n", + " messages=prompts\n", + ")\n", + "print(response.choices[0].message.content)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "83ddb483-4f57-4668-aeea-2aade3a9e573", + "metadata": {}, + "outputs": [], + "source": [ + "# To be serious! GPT-4o-mini with the original question\n", + "\n", + "prompts = [\n", + " {\"role\": \"system\", \"content\": \"You are a helpful assistant that responds in Markdown\"},\n", + " {\"role\": \"user\", \"content\": \"How do I decide if a business problem is suitable for an LLM solution? Please respond in Markdown.\"}\n", + " ]" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "749f50ab-8ccd-4502-a521-895c3f0808a2", + "metadata": {}, + "outputs": [], + "source": [ + "# Have it stream back results in markdown\n", + "\n", + "stream = openai.chat.completions.create(\n", + " model='gpt-4o',\n", + " messages=prompts,\n", + " temperature=0.2,\n", + " stream=True\n", + ")\n", + "\n", + "reply = \"\"\n", + "display_handle = display(Markdown(\"\"), display_id=True)\n", + "for chunk in stream:\n", + " reply += chunk.choices[0].delta.content or ''\n", + " reply = reply.replace(\"```\",\"\").replace(\"markdown\",\"\")\n", + " update_display(Markdown(reply), display_id=display_handle.display_id)" + ] + }, + { + "cell_type": "markdown", + "id": "f6e09351-1fbe-422f-8b25-f50826ab4c5f", + "metadata": {}, + "source": [ + "## And now for some fun - an adversarial conversation between Chatbots..\n", + "\n", + "You're already familar with prompts being organized into lists like:\n", + "\n", + "```\n", + "[\n", + " {\"role\": \"system\", \"content\": \"system message here\"},\n", + " {\"role\": \"user\", \"content\": \"user prompt here\"}\n", + "]\n", + "```\n", + "\n", + "In fact this structure can be used to reflect a longer conversation history:\n", + "\n", + "```\n", + "[\n", + " {\"role\": \"system\", \"content\": \"system message here\"},\n", + " {\"role\": \"user\", \"content\": \"first user prompt here\"},\n", + " {\"role\": \"assistant\", \"content\": \"the assistant's response\"},\n", + " {\"role\": \"user\", \"content\": \"the new user prompt\"},\n", + "]\n", + "```\n", + "\n", + "And we can use this approach to engage in a longer interaction with history." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "bcb54183-45d3-4d08-b5b6-55e380dfdf1b", + "metadata": {}, + "outputs": [], + "source": [ + "# Let's make a conversation between GPT-4o-mini and Claude-3-haiku\n", + "# We're using cheap versions of models so the costs will be minimal\n", + "\n", + "gpt_model = \"gpt-4o-mini\"\n", + "claude_model = \"claude-3-haiku-20240307\"\n", + "\n", + "gpt_system = \"You are a chatbot who is very argumentative; \\\n", + "you disagree with anything in the conversation and you challenge everything, in a snarky way.\"\n", + "\n", + "claude_system = \"You are a very polite, courteous chatbot. You try to agree with \\\n", + "everything the other person says, or find common ground. If the other person is argumentative, \\\n", + "you try to calm them down and keep chatting.\"\n", + "\n", + "gpt_messages = [\"Hi there\"]\n", + "claude_messages = [\"Hi\"]" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "1df47dc7-b445-4852-b21b-59f0e6c2030f", + "metadata": {}, + "outputs": [], + "source": [ + "def call_gpt():\n", + " messages = [{\"role\": \"system\", \"content\": gpt_system}]\n", + " for gpt, claude, llama in zip(gpt_messages, claude_messages, llama_messages):\n", + " messages.append({\"role\": \"assistant\", \"content\": gpt})\n", + " combined = llama + claude\n", + " messages.append({\"role\": \"user\", \"content\": combined})\n", + " completion = openai.chat.completions.create(\n", + " model=gpt_model,\n", + " messages=messages\n", + " )\n", + " return completion.choices[0].message.content" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "9dc6e913-02be-4eb6-9581-ad4b2cffa606", + "metadata": {}, + "outputs": [], + "source": [ + "call_gpt()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "7d2ed227-48c9-4cad-b146-2c4ecbac9690", + "metadata": {}, + "outputs": [], + "source": [ + "def call_claude():\n", + " messages = []\n", + " for gpt, claude_message in zip(gpt_messages, claude_messages):\n", + " messages.append({\"role\": \"user\", \"content\": gpt})\n", + " messages.append({\"role\": \"assistant\", \"content\": claude_message})\n", + " # messages.append(\"role\": \"moderator\", \"content\": llama_message)\n", + " messages.append({\"role\": \"user\", \"content\": gpt_messages[-1]})\n", + " message = claude.messages.create(\n", + " model=claude_model,\n", + " system=claude_system,\n", + " messages=messages,\n", + " max_tokens=500\n", + " )\n", + " return message.content[0].text" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "01395200-8ae9-41f8-9a04-701624d3fd26", + "metadata": {}, + "outputs": [], + "source": [ + "call_claude()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "08c2279e-62b0-4671-9590-c82eb8d1e1ae", + "metadata": {}, + "outputs": [], + "source": [ + "call_gpt()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "0275b97f-7f90-4696-bbf5-b6642bd53cbd", + "metadata": {}, + "outputs": [], + "source": [ + "gpt_messages = [\"Hi there\"]\n", + "claude_messages = [\"Hi\"]\n", + "\n", + "print(f\"GPT:\\n{gpt_messages[0]}\\n\")\n", + "print(f\"Claude:\\n{claude_messages[0]}\\n\")\n", + "\n", + "for i in range(5):\n", + " gpt_next = call_gpt()\n", + " print(f\"GPT:\\n{gpt_next}\\n\")\n", + " gpt_messages.append(gpt_next)\n", + " \n", + " claude_next = call_claude()\n", + " print(f\"Claude:\\n{claude_next}\\n\")\n", + " claude_messages.append(claude_next)" + ] + }, + { + "cell_type": "markdown", + "id": "1d10e705-db48-4290-9dc8-9efdb4e31323", + "metadata": {}, + "source": [ + "\n", + " \n", + " \n", + " \n", + " \n", + "
\n", + " \n", + " \n", + "

Before you continue

\n", + " \n", + " Be sure you understand how the conversation above is working, and in particular how the messages list is being populated. Add print statements as needed. Then for a great variation, try switching up the personalities using the system prompts. Perhaps one can be pessimistic, and one optimistic?
\n", + "
\n", + "
" + ] + }, + { + "cell_type": "markdown", + "id": "3637910d-2c6f-4f19-b1fb-2f916d23f9ac", + "metadata": {}, + "source": [ + "# More advanced exercises\n", + "\n", + "Try creating a 3-way, perhaps bringing Gemini into the conversation! One student has completed this - see the implementation in the community-contributions folder.\n", + "\n", + "Try doing this yourself before you look at the solutions. It's easiest to use the OpenAI python client to access the Gemini model (see the 2nd Gemini example above).\n", + "\n", + "## Additional exercise\n", + "\n", + "You could also try replacing one of the models with an open source model running with Ollama." + ] + }, + { + "cell_type": "markdown", + "id": "446c81e3-b67e-4cd9-8113-bc3092b93063", + "metadata": {}, + "source": [ + "\n", + " \n", + " \n", + " \n", + " \n", + "
\n", + " \n", + " \n", + "

Business relevance

\n", + " This structure of a conversation, as a list of messages, is fundamental to the way we build conversational AI assistants and how they are able to keep the context during a conversation. We will apply this in the next few labs to building out an AI assistant, and then you will extend this to your own business.\n", + "
" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "c23224f6-7008-44ed-a57f-718975f4e291", + "metadata": {}, + "outputs": [], + "source": [ + "!ollama pull llama3.2" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "cbbddf71-1473-42fe-b733-2bb42ea77333", + "metadata": {}, + "outputs": [], + "source": [ + "\n", + "OLLAMA_API = \"http://localhost:11434/api/chat\"\n", + "HEADERS = {\"Content-Type\": \"application/json\"}\n", + "import ollama\n", + "\n", + "llama_model = \"llama3.2\"\n", + "\n", + "llama_system = \"You are a chatbot who is very pacifist; \\\n", + "you will try to resolve or neutralize any disagreement between other chatbots. Speak like a teacher or someone in authority.\"\n", + "\n", + "llama_messages = [\"Hello.\"]\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "f629d2b2-ba20-4bfe-a2e5-bbe537ca46a2", + "metadata": {}, + "outputs": [], + "source": [ + "\n", + "def call_llama():\n", + " combined_messages = gpt_messages[-1] + claude_messages[-1]\n", + " messages = [{\"role\": \"system\", \"content\": llama_system}]\n", + " for comb, llama in zip(combined_messages, llama_messages):\n", + " messages.append({\"role\": \"assistant\", \"content\": llama})\n", + " messages.append({\"role\": \"user\", \"content\": combined_messages})\n", + " completion = ollama.chat(\n", + " model=llama_model,\n", + " messages=messages\n", + " )\n", + " return completion['message']['content']" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "219b6af8-3166-4059-b79e-cf19af7ed1e9", + "metadata": {}, + "outputs": [], + "source": [ + "print(f\"GPT:\\n{gpt_messages[0]}\\n\")\n", + "print(f\"Claude:\\n{claude_messages[0]}\\n\")\n", + "print(f\"Llama:\\n{llama_messages[0]}\\n\" )\n", + "\n", + "for i in range(3):\n", + " gpt_next = call_gpt()\n", + " print(f\"GPT:\\n{gpt_next}\\n\")\n", + " gpt_messages.append(gpt_next)\n", + " \n", + " claude_next = call_claude()\n", + " print(f\"Claude:\\n{claude_next}\\n\")\n", + " claude_messages.append(claude_next)\n", + "\n", + " llama_next = call_llama()\n", + " print(f\"Llama:\\n{llama_next}\\n\")\n", + " llama_messages.append(llama_next)\n", + " " + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "6cb3a931-522c-49a9-9bd8-663333f41b1a", + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "2cdfdc32-1ca4-406e-9328-81af26fd503b", + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "04f60158-633b-43ff-afbd-396be79501e6", + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "eb0faf0d-fb7e-4bc5-9746-30f19a0b9ae1", + "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": "3.11.11" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/week2/community-contributions/day2-different-tones.ipynb b/week2/community-contributions/day2-different-tones.ipynb new file mode 100644 index 0000000..9b14e3a --- /dev/null +++ b/week2/community-contributions/day2-different-tones.ipynb @@ -0,0 +1,575 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "id": "8b0e11f2-9ea4-48c2-b8d2-d0a4ba967827", + "metadata": {}, + "source": [ + "# Gradio Day!\n", + "\n", + "Today we will build User Interfaces using the outrageously simple Gradio framework.\n", + "\n", + "Prepare for joy!\n", + "\n", + "Please note: your Gradio screens may appear in 'dark mode' or 'light mode' depending on your computer settings." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "c44c5494-950d-4d2f-8d4f-b87b57c5b330", + "metadata": {}, + "outputs": [], + "source": [ + "# imports\n", + "\n", + "import os\n", + "import requests\n", + "from bs4 import BeautifulSoup\n", + "from typing import List\n", + "from dotenv import load_dotenv\n", + "from openai import OpenAI\n", + "import google.generativeai\n", + "import anthropic" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "d1715421-cead-400b-99af-986388a97aff", + "metadata": {}, + "outputs": [], + "source": [ + "import gradio as gr # oh yeah!" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "337d5dfc-0181-4e3b-8ab9-e78e0c3f657b", + "metadata": {}, + "outputs": [], + "source": [ + "# Load environment variables in a file called .env\n", + "# Print the key prefixes to help with any debugging\n", + "\n", + "load_dotenv()\n", + "openai_api_key = os.getenv('OPENAI_API_KEY')\n", + "anthropic_api_key = os.getenv('ANTHROPIC_API_KEY')\n", + "google_api_key = os.getenv('GOOGLE_API_KEY')\n", + "\n", + "if openai_api_key:\n", + " print(f\"OpenAI API Key exists and begins {openai_api_key[:8]}\")\n", + "else:\n", + " print(\"OpenAI API Key not set\")\n", + " \n", + "if anthropic_api_key:\n", + " print(f\"Anthropic API Key exists and begins {anthropic_api_key[:7]}\")\n", + "else:\n", + " print(\"Anthropic API Key not set\")\n", + "\n", + "if google_api_key:\n", + " print(f\"Google API Key exists and begins {google_api_key[:8]}\")\n", + "else:\n", + " print(\"Google API Key not set\")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "22586021-1795-4929-8079-63f5bb4edd4c", + "metadata": {}, + "outputs": [], + "source": [ + "# Connect to OpenAI, Anthropic and Google; comment out the Claude or Google lines if you're not using them\n", + "\n", + "openai = OpenAI()\n", + "\n", + "claude = anthropic.Anthropic()\n", + "\n", + "google.generativeai.configure()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "b16e6021-6dc4-4397-985a-6679d6c8ffd5", + "metadata": {}, + "outputs": [], + "source": [ + "# A generic system message - no more snarky adversarial AIs!\n", + "\n", + "system_message = \"You are a helpful assistant\"" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "02ef9b69-ef31-427d-86d0-b8c799e1c1b1", + "metadata": {}, + "outputs": [], + "source": [ + "# Let's wrap a call to GPT-4o-mini in a simple function\n", + "\n", + "def message_gpt(prompt):\n", + " messages = [\n", + " {\"role\": \"system\", \"content\": system_message},\n", + " {\"role\": \"user\", \"content\": prompt}\n", + " ]\n", + " completion = openai.chat.completions.create(\n", + " model='gpt-4o-mini',\n", + " messages=messages,\n", + " )\n", + " return completion.choices[0].message.content" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "aef7d314-2b13-436b-b02d-8de3b72b193f", + "metadata": {}, + "outputs": [], + "source": [ + "message_gpt(\"What is today's date?\")" + ] + }, + { + "cell_type": "markdown", + "id": "f94013d1-4f27-4329-97e8-8c58db93636a", + "metadata": {}, + "source": [ + "## User Interface time!" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "bc664b7a-c01d-4fea-a1de-ae22cdd5141a", + "metadata": {}, + "outputs": [], + "source": [ + "# here's a simple function\n", + "\n", + "def shout(text):\n", + " print(f\"Shout has been called with input {text}\")\n", + " return text.upper()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "083ea451-d3a0-4d13-b599-93ed49b975e4", + "metadata": {}, + "outputs": [], + "source": [ + "shout(\"hello\")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "08f1f15a-122e-4502-b112-6ee2817dda32", + "metadata": {}, + "outputs": [], + "source": [ + "# The simplicty of gradio. This might appear in \"light mode\" - I'll show you how to make this in dark mode later.\n", + "\n", + "gr.Interface(fn=shout, inputs=\"textbox\", outputs=\"textbox\").launch()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "c9a359a4-685c-4c99-891c-bb4d1cb7f426", + "metadata": {}, + "outputs": [], + "source": [ + "# Adding share=True means that it can be accessed publically\n", + "# A more permanent hosting is available using a platform called Spaces from HuggingFace, which we will touch on next week\n", + "# NOTE: Some Anti-virus software and Corporate Firewalls might not like you using share=True. If you're at work on on a work network, I suggest skip this test.\n", + "\n", + "gr.Interface(fn=shout, inputs=\"textbox\", outputs=\"textbox\", flagging_mode=\"never\").launch(share=True)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "cd87533a-ff3a-4188-8998-5bedd5ba2da3", + "metadata": {}, + "outputs": [], + "source": [ + "# Adding inbrowser=True opens up a new browser window automatically\n", + "\n", + "gr.Interface(fn=shout, inputs=\"textbox\", outputs=\"textbox\", flagging_mode=\"never\").launch(inbrowser=True)" + ] + }, + { + "cell_type": "markdown", + "id": "b42ec007-0314-48bf-84a4-a65943649215", + "metadata": {}, + "source": [ + "## Forcing dark mode\n", + "\n", + "Gradio appears in light mode or dark mode depending on the settings of the browser and computer. There is a way to force gradio to appear in dark mode, but Gradio recommends against this as it should be a user preference (particularly for accessibility reasons). But if you wish to force dark mode for your screens, below is how to do it." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "e8129afa-532b-4b15-b93c-aa9cca23a546", + "metadata": {}, + "outputs": [], + "source": [ + "# Define this variable and then pass js=force_dark_mode when creating the Interface\n", + "\n", + "force_dark_mode = \"\"\"\n", + "function refresh() {\n", + " const url = new URL(window.location);\n", + " if (url.searchParams.get('__theme') !== 'dark') {\n", + " url.searchParams.set('__theme', 'dark');\n", + " window.location.href = url.href;\n", + " }\n", + "}\n", + "\"\"\"\n", + "gr.Interface(fn=shout, inputs=\"textbox\", outputs=\"textbox\", flagging_mode=\"never\", js=force_dark_mode).launch()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "3cc67b26-dd5f-406d-88f6-2306ee2950c0", + "metadata": {}, + "outputs": [], + "source": [ + "# Inputs and Outputs\n", + "\n", + "view = gr.Interface(\n", + " fn=shout,\n", + " inputs=[gr.Textbox(label=\"Your message:\", lines=6)],\n", + " outputs=[gr.Textbox(label=\"Response:\", lines=8)],\n", + " flagging_mode=\"never\"\n", + ")\n", + "view.launch()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "f235288e-63a2-4341-935b-1441f9be969b", + "metadata": {}, + "outputs": [], + "source": [ + "# And now - changing the function from \"shout\" to \"message_gpt\"\n", + "\n", + "view = gr.Interface(\n", + " fn=message_gpt,\n", + " inputs=[gr.Textbox(label=\"Your message:\", lines=6)],\n", + " outputs=[gr.Textbox(label=\"Response:\", lines=8)],\n", + " flagging_mode=\"never\"\n", + ")\n", + "view.launch()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "af9a3262-e626-4e4b-80b0-aca152405e63", + "metadata": {}, + "outputs": [], + "source": [ + "# Let's use Markdown\n", + "# Are you wondering why it makes any difference to set system_message when it's not referred to in the code below it?\n", + "# I'm taking advantage of system_message being a global variable, used back in the message_gpt function (go take a look)\n", + "# Not a great software engineering practice, but quite sommon during Jupyter Lab R&D!\n", + "\n", + "system_message = \"You are a helpful assistant that responds in markdown\"\n", + "\n", + "view = gr.Interface(\n", + " fn=message_gpt,\n", + " inputs=[gr.Textbox(label=\"Your message:\")],\n", + " outputs=[gr.Markdown(label=\"Response:\")],\n", + " flagging_mode=\"never\"\n", + ")\n", + "view.launch()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "88c04ebf-0671-4fea-95c9-bc1565d4bb4f", + "metadata": {}, + "outputs": [], + "source": [ + "# Let's create a call that streams back results\n", + "# If you'd like a refresher on Generators (the \"yield\" keyword),\n", + "# Please take a look at the Intermediate Python notebook in week1 folder.\n", + "\n", + "def stream_gpt(prompt):\n", + " messages = [\n", + " {\"role\": \"system\", \"content\": system_message},\n", + " {\"role\": \"user\", \"content\": prompt}\n", + " ]\n", + " stream = openai.chat.completions.create(\n", + " model='gpt-4o-mini',\n", + " messages=messages,\n", + " stream=True\n", + " )\n", + " result = \"\"\n", + " for chunk in stream:\n", + " result += chunk.choices[0].delta.content or \"\"\n", + " yield result" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "0bb1f789-ff11-4cba-ac67-11b815e29d09", + "metadata": {}, + "outputs": [], + "source": [ + "view = gr.Interface(\n", + " fn=stream_gpt,\n", + " inputs=[gr.Textbox(label=\"Your message:\")],\n", + " outputs=[gr.Markdown(label=\"Response:\")],\n", + " flagging_mode=\"never\"\n", + ")\n", + "view.launch()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "bbc8e930-ba2a-4194-8f7c-044659150626", + "metadata": {}, + "outputs": [], + "source": [ + "def stream_claude(prompt):\n", + " result = claude.messages.stream(\n", + " model=\"claude-3-haiku-20240307\",\n", + " max_tokens=1000,\n", + " temperature=0.7,\n", + " system=system_message,\n", + " messages=[\n", + " {\"role\": \"user\", \"content\": prompt},\n", + " ],\n", + " )\n", + " response = \"\"\n", + " with result as stream:\n", + " for text in stream.text_stream:\n", + " response += text or \"\"\n", + " yield response" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "a0066ffd-196e-4eaf-ad1e-d492958b62af", + "metadata": {}, + "outputs": [], + "source": [ + "view = gr.Interface(\n", + " fn=stream_claude,\n", + " inputs=[gr.Textbox(label=\"Your message:\")],\n", + " outputs=[gr.Markdown(label=\"Response:\")],\n", + " flagging_mode=\"never\"\n", + ")\n", + "view.launch()" + ] + }, + { + "cell_type": "markdown", + "id": "bc5a70b9-2afe-4a7c-9bed-2429229e021b", + "metadata": {}, + "source": [ + "## Minor improvement\n", + "\n", + "I've made a small improvement to this code.\n", + "\n", + "Previously, it had these lines:\n", + "\n", + "```\n", + "for chunk in result:\n", + " yield chunk\n", + "```\n", + "\n", + "There's actually a more elegant way to achieve this (which Python people might call more 'Pythonic'):\n", + "\n", + "`yield from result`\n", + "\n", + "I cover this in more detail in the Intermediate Python notebook in the week1 folder - take a look if you'd like more." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "0087623a-4e31-470b-b2e6-d8d16fc7bcf5", + "metadata": {}, + "outputs": [], + "source": [ + "def stream_model(prompt, model):\n", + " if model==\"GPT\":\n", + " result = stream_gpt(prompt)\n", + " elif model==\"Claude\":\n", + " result = stream_claude(prompt)\n", + " else:\n", + " raise ValueError(\"Unknown model\")\n", + " yield from result" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "8d8ce810-997c-4b6a-bc4f-1fc847ac8855", + "metadata": {}, + "outputs": [], + "source": [ + "view = gr.Interface(\n", + " fn=stream_model,\n", + " inputs=[gr.Textbox(label=\"Your message:\"), gr.Dropdown([\"GPT\", \"Claude\"], label=\"Select model\", value=\"Claude\")],\n", + " outputs=[gr.Markdown(label=\"Response:\")],\n", + " flagging_mode=\"never\"\n", + ")\n", + "view.launch()" + ] + }, + { + "cell_type": "markdown", + "id": "d933865b-654c-4b92-aa45-cf389f1eda3d", + "metadata": {}, + "source": [ + "# Building a company brochure generator\n", + "\n", + "Now you know how - it's simple!" + ] + }, + { + "cell_type": "markdown", + "id": "92d7c49b-2e0e-45b3-92ce-93ca9f962ef4", + "metadata": {}, + "source": [ + "\n", + " \n", + " \n", + " \n", + " \n", + "
\n", + " \n", + " \n", + "

Before you read the next few cells

\n", + " \n", + " Try to do this yourself - go back to the company brochure in week1, day5 and add a Gradio UI to the end. Then come and look at the solution.\n", + " \n", + "
" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "1626eb2e-eee8-4183-bda5-1591b58ae3cf", + "metadata": {}, + "outputs": [], + "source": [ + "# A class to represent a Webpage\n", + "\n", + "class Website:\n", + " url: str\n", + " title: str\n", + " text: str\n", + "\n", + " def __init__(self, url):\n", + " self.url = url\n", + " response = requests.get(url)\n", + " self.body = response.content\n", + " soup = BeautifulSoup(self.body, 'html.parser')\n", + " self.title = soup.title.string if soup.title else \"No title found\"\n", + " for irrelevant in soup.body([\"script\", \"style\", \"img\", \"input\"]):\n", + " irrelevant.decompose()\n", + " self.text = soup.body.get_text(separator=\"\\n\", strip=True)\n", + "\n", + " def get_contents(self):\n", + " return f\"Webpage Title:\\n{self.title}\\nWebpage Contents:\\n{self.text}\\n\\n\"" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "c701ec17-ecd5-4000-9f68-34634c8ed49d", + "metadata": {}, + "outputs": [], + "source": [ + "# With massive thanks to Bill G. who noticed that a prior version of this had a bug! Now fixed.\n", + "\n", + "system_message = \"You are an assistant that analyzes the contents of a company website landing page \\\n", + "and creates a short brochure about the company for prospective customers, investors and recruits. Respond in markdown.\"" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "5def90e0-4343-4f58-9d4a-0e36e445efa4", + "metadata": {}, + "outputs": [], + "source": [ + "def stream_brochure(company_name, url, model, tone):\n", + " prompt = f\"Please generate a company brochure for {company_name}. Write the brochure in the following tone: {tone}.Here is their landing page:\\n\"\n", + " prompt += Website(url).get_contents()\n", + " if model==\"GPT\":\n", + " result = stream_gpt(prompt)\n", + " elif model==\"Claude\":\n", + " result = stream_claude(prompt)\n", + " else:\n", + " raise ValueError(\"Unknown model\")\n", + " yield from result" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "66399365-5d67-4984-9d47-93ed26c0bd3d", + "metadata": {}, + "outputs": [], + "source": [ + "view = gr.Interface(\n", + " fn=stream_brochure,\n", + " inputs=[\n", + " gr.Textbox(label=\"Company name:\"),\n", + " gr.Textbox(label=\"Landing page URL including http:// or https://\"),\n", + " gr.Dropdown([\"GPT\", \"Claude\"], label=\"Select model\"),\n", + " gr.Dropdown([\"Formal\", \"Casual\", \"Academic\", \"Funny\", \"Snarky\"], label=\"Select tone\", value=\"Formal\"),],\n", + " outputs=[gr.Markdown(label=\"Brochure:\")],\n", + " flagging_mode=\"never\"\n", + ")\n", + "view.launch()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "ede97ca3-a0f8-4f6e-be17-d1de7fef9cc0", + "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": "3.11.11" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} From 06c4f097ed8ad99180a8abbd8f4a4692417c7ac4 Mon Sep 17 00:00:00 2001 From: danielquillanroxas Date: Sat, 1 Feb 2025 14:29:46 +0300 Subject: [PATCH 2/5] translator with audio --- .../week2_exercise_translated_chatbot.ipynb | 614 ++++++++++++++++++ 1 file changed, 614 insertions(+) create mode 100644 week2/community-contributions/week2_exercise_translated_chatbot.ipynb diff --git a/week2/community-contributions/week2_exercise_translated_chatbot.ipynb b/week2/community-contributions/week2_exercise_translated_chatbot.ipynb new file mode 100644 index 0000000..7490107 --- /dev/null +++ b/week2/community-contributions/week2_exercise_translated_chatbot.ipynb @@ -0,0 +1,614 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "id": "d006b2ea-9dfe-49c7-88a9-a5a0775185fd", + "metadata": {}, + "source": [ + "# Additional End of week Exercise - week 2\n", + "\n", + "Now use everything you've learned from Week 2 to build a full prototype for the technical question/answerer you built in Week 1 Exercise.\n", + "\n", + "This should include a Gradio UI, streaming, use of the system prompt to add expertise, and the ability to switch between models. Bonus points if you can demonstrate use of a tool!\n", + "\n", + "If you feel bold, see if you can add audio input so you can talk to it, and have it respond with audio. ChatGPT or Claude can help you, or email me if you have questions.\n", + "\n", + "I will publish a full solution here soon - unless someone beats me to it...\n", + "\n", + "There are so many commercial applications for this, from a language tutor, to a company onboarding solution, to a companion AI to a course (like this one!) I can't wait to see your results." + ] + }, + { + "cell_type": "markdown", + "id": "517b0427-1f18-4ce3-96a9-3bccde59ee60", + "metadata": {}, + "source": [ + "# Overview\n" + ] + }, + { + "cell_type": "markdown", + "id": "d1e934de-8fe4-4586-bc0e-0ecb0dd5068b", + "metadata": {}, + "source": [ + "## Multimodal question and answerer:\n", + " - The chatbot answers technical questions\n", + " - The user can enter their language of choice (that exists) and it would be translated real time on the second screen and English on the first screen.\n", + " - The user can also choose which tone/mood it would like the responses to have.\n", + " - The user can choose whether the ersponse will be read out loud or not. \n", + " - The user can send in an audio and get the response back in audio (automatically) if he so chooses." + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "id": "90459175-a0f9-421e-bbce-49eecd2cd16a", + "metadata": {}, + "outputs": [], + "source": [ + "# imports\n", + "\n", + "import os\n", + "import json\n", + "from dotenv import load_dotenv\n", + "from openai import OpenAI\n", + "import anthropic\n", + "import gradio as gr" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "id": "096cdd1d-073b-45b6-80f2-090fbdcb701c", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "OpenAI key exists!\n", + "Anthropic API key exists!\n" + ] + } + ], + "source": [ + "# Initialization\n", + "\n", + "load_dotenv()\n", + "\n", + "openai_api_key = os.getenv('OPENAI_API_KEY')\n", + "anthropic_api_key = os.getenv(\"ANTHROPIC_API_KEY\")\n", + "\n", + "if openai_api_key:\n", + " print(\"OpenAI key exists!\")\n", + "else:\n", + " print(\"OpenAI key not set!\")\n", + "\n", + "if anthropic_api_key:\n", + " print(\"Anthropic API key exists!\")\n", + "else:\n", + " print(\"Anthropic key not set\")\n" + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "id": "bca4c5ee-6c39-4c81-b8f9-9280c66b07c0", + "metadata": {}, + "outputs": [], + "source": [ + "openai = OpenAI()\n", + "\n", + "claude = anthropic.Anthropic()\n", + "\n", + "openai_4o_mini_model = \"gpt-4o-mini\"\n" + ] + }, + { + "cell_type": "code", + "execution_count": 18, + "id": "67599cae-9a26-4180-959c-63c74157568f", + "metadata": {}, + "outputs": [], + "source": [ + "system_message = \"You are a helpful assistant that answers tchnical questions.\"\n", + "system_message += \"Always be accurate. If you don't know or not sure about some information, say so.\"" + ] + }, + { + "cell_type": "code", + "execution_count": 55, + "id": "5a04232e-f8a7-4e38-b22b-8fe179262920", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Collecting deep_translator\n", + " Downloading deep_translator-1.11.4-py3-none-any.whl.metadata (30 kB)\n", + "Requirement already satisfied: beautifulsoup4<5.0.0,>=4.9.1 in c:\\users\\hp\\anaconda3\\envs\\llms\\lib\\site-packages (from deep_translator) (4.12.3)\n", + "Requirement already satisfied: requests<3.0.0,>=2.23.0 in c:\\users\\hp\\anaconda3\\envs\\llms\\lib\\site-packages (from deep_translator) (2.32.3)\n", + "Requirement already satisfied: soupsieve>1.2 in c:\\users\\hp\\anaconda3\\envs\\llms\\lib\\site-packages (from beautifulsoup4<5.0.0,>=4.9.1->deep_translator) (2.5)\n", + "Requirement already satisfied: charset_normalizer<4,>=2 in c:\\users\\hp\\anaconda3\\envs\\llms\\lib\\site-packages (from requests<3.0.0,>=2.23.0->deep_translator) (3.4.1)\n", + "Requirement already satisfied: idna<4,>=2.5 in c:\\users\\hp\\anaconda3\\envs\\llms\\lib\\site-packages (from requests<3.0.0,>=2.23.0->deep_translator) (2.10)\n", + "Requirement already satisfied: urllib3<3,>=1.21.1 in c:\\users\\hp\\anaconda3\\envs\\llms\\lib\\site-packages (from requests<3.0.0,>=2.23.0->deep_translator) (2.3.0)\n", + "Requirement already satisfied: certifi>=2017.4.17 in c:\\users\\hp\\anaconda3\\envs\\llms\\lib\\site-packages (from requests<3.0.0,>=2.23.0->deep_translator) (2024.12.14)\n", + "Downloading deep_translator-1.11.4-py3-none-any.whl (42 kB)\n", + "Installing collected packages: deep_translator\n", + "Successfully installed deep_translator-1.11.4\n" + ] + } + ], + "source": [ + "!pip install deep_translator" + ] + }, + { + "cell_type": "code", + "execution_count": 56, + "id": "aa85d87e-9385-4a23-b114-eb64264ca497", + "metadata": {}, + "outputs": [], + "source": [ + "from deep_translator import GoogleTranslator\n", + "\n", + "# First install deep_translator:\n", + "# pip install deep_translator\n", + "\n", + "# Top 10 most spoken languages with their codes\n", + "LANGUAGES = {\n", + " \"English\": \"en\",\n", + " \"Mandarin Chinese\": \"zh-CN\",\n", + " \"Hindi\": \"hi\",\n", + " \"Spanish\": \"es\",\n", + " \"Arabic\": \"ar\",\n", + " \"Bengali\": \"bn\",\n", + " \"Portuguese\": \"pt\",\n", + " \"Russian\": \"ru\",\n", + " \"Japanese\": \"ja\",\n", + " \"German\": \"de\"\n", + "}\n" + ] + }, + { + "cell_type": "code", + "execution_count": 57, + "id": "25654699-763a-4574-91bf-08c6068d4cd3", + "metadata": {}, + "outputs": [], + "source": [ + "\n", + "class ChatState:\n", + " def __init__(self):\n", + " self.speak = True\n", + " self.target_lang = \"en\"\n", + "\n", + "chat_state = ChatState()" + ] + }, + { + "cell_type": "code", + "execution_count": 58, + "id": "18dc8c35-f97c-4635-834a-422b5aa552c8", + "metadata": {}, + "outputs": [], + "source": [ + "def translate_message(text, target_lang):\n", + " if target_lang == \"en\":\n", + " return text\n", + " try:\n", + " translator = GoogleTranslator(source='auto', target=target_lang)\n", + " return translator.translate(text)\n", + " except:\n", + " return f\"Translation error: {text}\"" + ] + }, + { + "cell_type": "code", + "execution_count": 66, + "id": "344f6594-335e-4900-b2dd-9509e90a1389", + "metadata": {}, + "outputs": [], + "source": [ + "def chat(message, history):\n", + " # Original chat processing\n", + " messages = [{\"role\": \"system\", \"content\": system_message}] + history + [{\"role\": \"user\", \"content\": message}] \n", + " response = openai.chat.completions.create(model = openai_4o_mini_model, messages = messages)\n", + " response_text = response.choices[0].message.content\n", + " \n", + " if chat_state.speak:\n", + " talker(response_text)\n", + " \n", + " # Translate messages\n", + " translated_message = translate_message(message, chat_state.target_lang)\n", + " translated_response = translate_message(response_text, chat_state.target_lang)\n", + " \n", + " gr.Chatbot.update(value=[(translated_message, translated_response)], visible=True)\n", + " \n", + " return response_text\n" + ] + }, + { + "cell_type": "code", + "execution_count": 71, + "id": "5e9af0a3-8a8d-45ff-8579-c9fad759326b", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Collecting gTTS\n", + " Downloading gTTS-2.5.4-py3-none-any.whl.metadata (4.1 kB)\n", + "Requirement already satisfied: requests<3,>=2.27 in c:\\users\\hp\\anaconda3\\envs\\llms\\lib\\site-packages (from gTTS) (2.32.3)\n", + "Requirement already satisfied: click<8.2,>=7.1 in c:\\users\\hp\\anaconda3\\envs\\llms\\lib\\site-packages (from gTTS) (8.1.8)\n", + "Requirement already satisfied: colorama in c:\\users\\hp\\appdata\\roaming\\python\\python311\\site-packages (from click<8.2,>=7.1->gTTS) (0.4.6)\n", + "Requirement already satisfied: charset_normalizer<4,>=2 in c:\\users\\hp\\anaconda3\\envs\\llms\\lib\\site-packages (from requests<3,>=2.27->gTTS) (3.4.1)\n", + "Requirement already satisfied: idna<4,>=2.5 in c:\\users\\hp\\anaconda3\\envs\\llms\\lib\\site-packages (from requests<3,>=2.27->gTTS) (2.10)\n", + "Requirement already satisfied: urllib3<3,>=1.21.1 in c:\\users\\hp\\anaconda3\\envs\\llms\\lib\\site-packages (from requests<3,>=2.27->gTTS) (2.3.0)\n", + "Requirement already satisfied: certifi>=2017.4.17 in c:\\users\\hp\\anaconda3\\envs\\llms\\lib\\site-packages (from requests<3,>=2.27->gTTS) (2024.12.14)\n", + "Downloading gTTS-2.5.4-py3-none-any.whl (29 kB)\n", + "Installing collected packages: gTTS\n", + "Successfully installed gTTS-2.5.4\n" + ] + } + ], + "source": [ + "!pip install gTTS" + ] + }, + { + "cell_type": "code", + "execution_count": 77, + "id": "1cd93430-0f3a-45ad-ac4c-917fd2a6c2a0", + "metadata": {}, + "outputs": [], + "source": [ + "from gtts import gTTS\n", + "import os\n", + "import tempfile\n", + "\n", + "def text_to_speech(text, lang_code):\n", + " try:\n", + " tts = gTTS(text=text, lang=lang_code)\n", + " # Create temporary file\n", + " with tempfile.NamedTemporaryFile(delete=False, suffix='.mp3') as fp:\n", + " tts.save(fp.name)\n", + " return fp.name\n", + " except:\n", + " return None" + ] + }, + { + "cell_type": "code", + "execution_count": 74, + "id": "a7b82670-f376-4069-9a11-7ca622fcf238", + "metadata": {}, + "outputs": [], + "source": [ + " def respond(message, history):\n", + " bot_response, history_original, history_translated = process_message(\n", + " message, \n", + " history, \n", + " 'translated' if speech_language.value.lower() == 'translated' else 'original'\n", + " )\n", + " return \"\", history_original, history_translated" + ] + }, + { + "cell_type": "code", + "execution_count": 79, + "id": "9716f21b-9583-4eec-9fd0-bffc430fee56", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "* Running on local URL: http://127.0.0.1:7882\n", + "\n", + "To create a public link, set `share=True` in `launch()`.\n" + ] + }, + { + "data": { + "text/html": [ + "
" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/plain": [] + }, + "execution_count": 79, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "text/html": [ + "\n", + " \n", + " " + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "def process_message(message, history, speech_mode):\n", + " messages = [{\"role\": \"system\", \"content\": system_message}] + history + [{\"role\": \"user\", \"content\": message}] \n", + " response = openai.chat.completions.create(model = openai_4o_mini_model, messages = messages)\n", + " response_text = response.choices[0].message.content\n", + " \n", + " # Create audio if speech is enabled\n", + " audio_path = None\n", + " if chat_state.speak:\n", + " if speech_mode == \"Translated\":\n", + " translated_text = translate_message(response_text, chat_state.target_lang)\n", + " audio_path = text_to_speech(translated_text, chat_state.target_lang)\n", + " else:\n", + " talker(response_text)\n", + " \n", + " # Translate messages for display\n", + " translated_message = translate_message(message, chat_state.target_lang)\n", + " translated_response = translate_message(response_text, chat_state.target_lang)\n", + " \n", + " history_original = history + [\n", + " {\"role\": \"user\", \"content\": message},\n", + " {\"role\": \"assistant\", \"content\": response_text}\n", + " ]\n", + " history_translated = [\n", + " {\"role\": \"user\", \"content\": translated_message},\n", + " {\"role\": \"assistant\", \"content\": translated_response}\n", + " ]\n", + " \n", + " return response_text, history_original, history_translated, audio_path\n", + "\n", + "with gr.Blocks() as demo:\n", + " speech_mode = gr.State(\"Original\")\n", + " \n", + " with gr.Row():\n", + " speak_checkbox = gr.Checkbox(\n", + " label=\"Read responses aloud\",\n", + " value=True,\n", + " interactive=True\n", + " )\n", + " language_dropdown = gr.Dropdown(\n", + " choices=list(LANGUAGES.keys()),\n", + " value=\"Spanish\",\n", + " label=\"Translation Language\",\n", + " interactive=True\n", + " )\n", + " speech_language = gr.Radio(\n", + " choices=[\"Original\", \"Translated\"],\n", + " value=\"Original\",\n", + " label=\"Speech Language\",\n", + " interactive=True\n", + " )\n", + " \n", + " # Add audio player\n", + " audio_player = gr.Audio(label=\"Response Audio\", visible=True)\n", + " \n", + " with gr.Row():\n", + " with gr.Column():\n", + " gr.Markdown(\"### Original Conversation\")\n", + " chatbot_original = gr.Chatbot(type=\"messages\")\n", + " msg_original = gr.Textbox(label=\"Message\")\n", + " send_btn = gr.Button(\"Send\")\n", + " \n", + " with gr.Column():\n", + " gr.Markdown(\"### Translated Conversation\")\n", + " chatbot_translated = gr.Chatbot(type=\"messages\")\n", + " \n", + " state = gr.State([])\n", + " \n", + " def respond(message, history, current_speech_mode):\n", + " bot_response, history_original, history_translated, audio_path = process_message(\n", + " message, \n", + " history,\n", + " current_speech_mode\n", + " )\n", + " \n", + " return \"\", history_original, history_translated, audio_path\n", + " \n", + " send_btn.click(\n", + " respond,\n", + " inputs=[msg_original, state, speech_language],\n", + " outputs=[msg_original, chatbot_original, chatbot_translated, audio_player],\n", + " )\n", + " \n", + " msg_original.submit(\n", + " respond,\n", + " inputs=[msg_original, state, speech_language],\n", + " outputs=[msg_original, chatbot_original, chatbot_translated, audio_player],\n", + " )\n", + " \n", + " speak_checkbox.change(fn=lambda x: setattr(chat_state, 'speak', x), inputs=[speak_checkbox])\n", + " language_dropdown.change(fn=update_language, inputs=[language_dropdown])\n", + "\n", + "demo.launch()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "af83a223-1930-4bad-9c31-44d227847610", + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "markdown", + "id": "76b51235-e23c-4aad-9c51-92f57d2febfb", + "metadata": {}, + "source": [ + "### Audio" + ] + }, + { + "cell_type": "code", + "execution_count": 29, + "id": "d7a81b5d-165e-48f8-bfc6-f4aca1cb68f1", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "ffmpeg version 2025-01-30-git-1911a6ec26-full_build-www.gyan.dev Copyright (c) 2000-2025 the FFmpeg developers\n", + "built with gcc 14.2.0 (Rev1, Built by MSYS2 project)\n", + "configuration: --enable-gpl --enable-version3 --enable-static --disable-w32threads --disable-autodetect --enable-fontconfig --enable-iconv --enable-gnutls --enable-lcms2 --enable-libxml2 --enable-gmp --enable-bzlib --enable-lzma --enable-libsnappy --enable-zlib --enable-librist --enable-libsrt --enable-libssh --enable-libzmq --enable-avisynth --enable-libbluray --enable-libcaca --enable-libdvdnav --enable-libdvdread --enable-sdl2 --enable-libaribb24 --enable-libaribcaption --enable-libdav1d --enable-libdavs2 --enable-libopenjpeg --enable-libquirc --enable-libuavs3d --enable-libxevd --enable-libzvbi --enable-libqrencode --enable-librav1e --enable-libsvtav1 --enable-libvvenc --enable-libwebp --enable-libx264 --enable-libx265 --enable-libxavs2 --enable-libxeve --enable-libxvid --enable-libaom --enable-libjxl --enable-libvpx --enable-mediafoundation --enable-libass --enable-frei0r --enable-libfreetype --enable-libfribidi --enable-libharfbuzz --enable-liblensfun --enable-libvidstab --enable-libvmaf --enable-libzimg --enable-amf --enable-cuda-llvm --enable-cuvid --enable-dxva2 --enable-d3d11va --enable-d3d12va --enable-ffnvcodec --enable-libvpl --enable-nvdec --enable-nvenc --enable-vaapi --enable-libshaderc --enable-vulkan --enable-libplacebo --enable-opencl --enable-libcdio --enable-libgme --enable-libmodplug --enable-libopenmpt --enable-libopencore-amrwb --enable-libmp3lame --enable-libshine --enable-libtheora --enable-libtwolame 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--enable-libxml2 --enable-gmp --enable-bzlib --enable-lzma --enable-libsnappy --enable-zlib --enable-librist --enable-libsrt --enable-libssh --enable-libzmq --enable-avisynth --enable-libbluray --enable-libcaca --enable-libdvdnav --enable-libdvdread --enable-sdl2 --enable-libaribb24 --enable-libaribcaption --enable-libdav1d --enable-libdavs2 --enable-libopenjpeg --enable-libquirc --enable-libuavs3d --enable-libxevd --enable-libzvbi --enable-libqrencode --enable-librav1e --enable-libsvtav1 --enable-libvvenc --enable-libwebp --enable-libx264 --enable-libx265 --enable-libxavs2 --enable-libxeve --enable-libxvid --enable-libaom --enable-libjxl --enable-libvpx --enable-mediafoundation --enable-libass --enable-frei0r --enable-libfreetype --enable-libfribidi --enable-libharfbuzz --enable-liblensfun --enable-libvidstab --enable-libvmaf --enable-libzimg --enable-amf --enable-cuda-llvm --enable-cuvid --enable-dxva2 --enable-d3d11va --enable-d3d12va --enable-ffnvcodec --enable-libvpl --enable-nvdec --enable-nvenc --enable-vaapi --enable-libshaderc --enable-vulkan --enable-libplacebo --enable-opencl --enable-libcdio --enable-libgme --enable-libmodplug --enable-libopenmpt --enable-libopencore-amrwb --enable-libmp3lame --enable-libshine --enable-libtheora --enable-libtwolame --enable-libvo-amrwbenc --enable-libcodec2 --enable-libilbc --enable-libgsm --enable-liblc3 --enable-libopencore-amrnb --enable-libopus --enable-libspeex --enable-libvorbis --enable-ladspa --enable-libbs2b --enable-libflite --enable-libmysofa --enable-librubberband --enable-libsoxr --enable-chromaprint\n", + "libavutil 59. 56.100 / 59. 56.100\n", + "libavcodec 61. 31.101 / 61. 31.101\n", + "libavformat 61. 9.106 / 61. 9.106\n", + "libavdevice 61. 4.100 / 61. 4.100\n", + "libavfilter 10. 9.100 / 10. 9.100\n", + "libswscale 8. 13.100 / 8. 13.100\n", + "libswresample 5. 4.100 / 5. 4.100\n", + "libpostproc 58. 4.100 / 58. 4.100\n", + "ffplay version 2025-01-30-git-1911a6ec26-full_build-www.gyan.dev Copyright (c) 2003-2025 the FFmpeg developers\n", + "built with gcc 14.2.0 (Rev1, Built by MSYS2 project)\n", + "configuration: --enable-gpl --enable-version3 --enable-static --disable-w32threads --disable-autodetect --enable-fontconfig --enable-iconv --enable-gnutls --enable-lcms2 --enable-libxml2 --enable-gmp --enable-bzlib --enable-lzma --enable-libsnappy --enable-zlib --enable-librist --enable-libsrt --enable-libssh --enable-libzmq --enable-avisynth --enable-libbluray --enable-libcaca --enable-libdvdnav --enable-libdvdread --enable-sdl2 --enable-libaribb24 --enable-libaribcaption --enable-libdav1d --enable-libdavs2 --enable-libopenjpeg --enable-libquirc --enable-libuavs3d --enable-libxevd --enable-libzvbi --enable-libqrencode --enable-librav1e --enable-libsvtav1 --enable-libvvenc --enable-libwebp --enable-libx264 --enable-libx265 --enable-libxavs2 --enable-libxeve --enable-libxvid --enable-libaom --enable-libjxl --enable-libvpx --enable-mediafoundation --enable-libass --enable-frei0r --enable-libfreetype --enable-libfribidi --enable-libharfbuzz --enable-liblensfun --enable-libvidstab --enable-libvmaf --enable-libzimg --enable-amf --enable-cuda-llvm --enable-cuvid --enable-dxva2 --enable-d3d11va --enable-d3d12va --enable-ffnvcodec --enable-libvpl --enable-nvdec --enable-nvenc --enable-vaapi --enable-libshaderc --enable-vulkan --enable-libplacebo --enable-opencl --enable-libcdio --enable-libgme --enable-libmodplug --enable-libopenmpt --enable-libopencore-amrwb --enable-libmp3lame --enable-libshine --enable-libtheora --enable-libtwolame --enable-libvo-amrwbenc --enable-libcodec2 --enable-libilbc --enable-libgsm --enable-liblc3 --enable-libopencore-amrnb --enable-libopus --enable-libspeex --enable-libvorbis --enable-ladspa --enable-libbs2b --enable-libflite --enable-libmysofa --enable-librubberband --enable-libsoxr --enable-chromaprint\n", + "libavutil 59. 56.100 / 59. 56.100\n", + "libavcodec 61. 31.101 / 61. 31.101\n", + "libavformat 61. 9.106 / 61. 9.106\n", + "libavdevice 61. 4.100 / 61. 4.100\n", + "libavfilter 10. 9.100 / 10. 9.100\n", + "libswscale 8. 13.100 / 8. 13.100\n", + "libswresample 5. 4.100 / 5. 4.100\n", + "libpostproc 58. 4.100 / 58. 4.100\n" + ] + } + ], + "source": [ + "!ffmpeg -version\n", + "!ffprobe -version\n", + "!ffplay -version" + ] + }, + { + "cell_type": "code", + "execution_count": 31, + "id": "1a04820d-ff9d-4868-8c98-969548c5402a", + "metadata": {}, + "outputs": [], + "source": [ + "import base64\n", + "from io import BytesIO\n", + "from PIL import Image\n", + "from IPython.display import Audio, display" + ] + }, + { + "cell_type": "code", + "execution_count": 34, + "id": "7c05863a-631b-4e05-9bc0-267400595ac2", + "metadata": {}, + "outputs": [], + "source": [ + "import base64\n", + "from io import BytesIO\n", + "from PIL import Image\n", + "from IPython.display import Audio, display\n", + "\n", + "def talker(message):\n", + " response = openai.audio.speech.create(\n", + " model = \"tts-1\",\n", + " voice = \"onyx\",\n", + " input = message\n", + " )\n", + "\n", + " audio_stream = BytesIO(response.content)\n", + " output_filename = \"output_audio.mp3\"\n", + " with open(output_filename, \"wb\") as f:\n", + " f.write(audio_stream.read())\n", + "\n", + " #Play the generated audio\n", + " display(Audio(output_filename, autoplay=True))\n" + ] + }, + { + "cell_type": "code", + "execution_count": 41, + "id": "fcf1bcf8-4a96-4243-950a-214bcd8b916b", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "\n", + " \n", + " " + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "talker(\"Warm, wet, and wild?! There must be something in the water!\")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "63fed0a2-5c2b-408d-9427-6e59b3f99e4f", + "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": "3.11.11" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} From e369697bb905bf3b853398bba3d4fd1d745bdaaf Mon Sep 17 00:00:00 2001 From: danielquillanroxas Date: Sat, 1 Feb 2025 14:44:14 +0300 Subject: [PATCH 3/5] day 1 day 2 and weekly exercise --- .../day1-3way-with-llama3.2.ipynb | 493 ++++++++++++++++++ week2/day1.ipynb | 79 ++- week2/day2.ipynb | 466 +++++++++++++++-- 3 files changed, 990 insertions(+), 48 deletions(-) diff --git a/week2/community-contributions/day1-3way-with-llama3.2.ipynb b/week2/community-contributions/day1-3way-with-llama3.2.ipynb index 835ae87..71c8734 100644 --- a/week2/community-contributions/day1-3way-with-llama3.2.ipynb +++ b/week2/community-contributions/day1-3way-with-llama3.2.ipynb @@ -82,7 +82,11 @@ }, { "cell_type": "code", +<<<<<<< HEAD "execution_count": null, +======= + "execution_count": 1, +>>>>>>> 23dd98b751af1e2abeedcfcc10ffb003dca09c9b "id": "de23bb9e-37c5-4377-9a82-d7b6c648eeb6", "metadata": {}, "outputs": [], @@ -98,7 +102,11 @@ }, { "cell_type": "code", +<<<<<<< HEAD "execution_count": null, +======= + "execution_count": 2, +>>>>>>> 23dd98b751af1e2abeedcfcc10ffb003dca09c9b "id": "f0a8ab2b-6134-4104-a1bc-c3cd7ea4cd36", "metadata": {}, "outputs": [], @@ -112,10 +120,27 @@ }, { "cell_type": "code", +<<<<<<< HEAD "execution_count": null, "id": "1179b4c5-cd1f-4131-a876-4c9f3f38d2ba", "metadata": {}, "outputs": [], +======= + "execution_count": 3, + "id": "1179b4c5-cd1f-4131-a876-4c9f3f38d2ba", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "OpenAI API Key exists and begins sk-proj-\n", + "Anthropic API Key exists and begins sk-ant-\n", + "Google API Key not set\n" + ] + } + ], +>>>>>>> 23dd98b751af1e2abeedcfcc10ffb003dca09c9b "source": [ "# Load environment variables in a file called .env\n", "# Print the key prefixes to help with any debugging\n", @@ -143,7 +168,11 @@ }, { "cell_type": "code", +<<<<<<< HEAD "execution_count": null, +======= + "execution_count": 4, +>>>>>>> 23dd98b751af1e2abeedcfcc10ffb003dca09c9b "id": "797fe7b0-ad43-42d2-acf0-e4f309b112f0", "metadata": {}, "outputs": [], @@ -157,7 +186,11 @@ }, { "cell_type": "code", +<<<<<<< HEAD "execution_count": null, +======= + "execution_count": 5, +>>>>>>> 23dd98b751af1e2abeedcfcc10ffb003dca09c9b "id": "425ed580-808d-429b-85b0-6cba50ca1d0c", "metadata": {}, "outputs": [], @@ -190,7 +223,11 @@ }, { "cell_type": "code", +<<<<<<< HEAD "execution_count": null, +======= + "execution_count": 6, +>>>>>>> 23dd98b751af1e2abeedcfcc10ffb003dca09c9b "id": "378a0296-59a2-45c6-82eb-941344d3eeff", "metadata": {}, "outputs": [], @@ -201,7 +238,11 @@ }, { "cell_type": "code", +<<<<<<< HEAD "execution_count": null, +======= + "execution_count": 7, +>>>>>>> 23dd98b751af1e2abeedcfcc10ffb003dca09c9b "id": "f4d56a0f-2a3d-484d-9344-0efa6862aff4", "metadata": {}, "outputs": [], @@ -214,10 +255,27 @@ }, { "cell_type": "code", +<<<<<<< HEAD "execution_count": null, "id": "3b3879b6-9a55-4fed-a18c-1ea2edfaf397", "metadata": {}, "outputs": [], +======= + "execution_count": 8, + "id": "3b3879b6-9a55-4fed-a18c-1ea2edfaf397", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Why did the data scientist break up with their calculator? \n", + "\n", + "Because it wasn't adding up to their expectations!\n" + ] + } + ], +>>>>>>> 23dd98b751af1e2abeedcfcc10ffb003dca09c9b "source": [ "# GPT-3.5-Turbo\n", "\n", @@ -227,10 +285,27 @@ }, { "cell_type": "code", +<<<<<<< HEAD "execution_count": null, "id": "3d2d6beb-1b81-466f-8ed1-40bf51e7adbf", "metadata": {}, "outputs": [], +======= + "execution_count": 9, + "id": "3d2d6beb-1b81-466f-8ed1-40bf51e7adbf", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Why did the data scientist break up with the statistician?\n", + "\n", + "Because she found him too mean!\n" + ] + } + ], +>>>>>>> 23dd98b751af1e2abeedcfcc10ffb003dca09c9b "source": [ "# GPT-4o-mini\n", "# Temperature setting controls creativity\n", @@ -245,10 +320,27 @@ }, { "cell_type": "code", +<<<<<<< HEAD "execution_count": null, "id": "f1f54beb-823f-4301-98cb-8b9a49f4ce26", "metadata": {}, "outputs": [], +======= + "execution_count": 10, + "id": "f1f54beb-823f-4301-98cb-8b9a49f4ce26", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Why did the data scientist bring a ladder to work?\n", + "\n", + "Because they heard the project had a lot of layers to it!\n" + ] + } + ], +>>>>>>> 23dd98b751af1e2abeedcfcc10ffb003dca09c9b "source": [ "# GPT-4o\n", "\n", @@ -262,10 +354,33 @@ }, { "cell_type": "code", +<<<<<<< HEAD "execution_count": null, "id": "1ecdb506-9f7c-4539-abae-0e78d7f31b76", "metadata": {}, "outputs": [], +======= + "execution_count": 11, + "id": "1ecdb506-9f7c-4539-abae-0e78d7f31b76", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Sure, here's a light-hearted joke for data scientists:\n", + "\n", + "Why did the data scientist break up with their significant other?\n", + "\n", + "There was just too much variance in the relationship, and they couldn't find a way to normalize it!\n", + "\n", + "Ba dum tss! 🥁\n", + "\n", + "This joke plays on statistical concepts like variance and normalization, which data scientists work with regularly. It's a playful way of applying data science terminology to a personal situation, creating a humorous contrast.\n" + ] + } + ], +>>>>>>> 23dd98b751af1e2abeedcfcc10ffb003dca09c9b "source": [ "# Claude 3.5 Sonnet\n", "# API needs system message provided separately from user prompt\n", @@ -286,10 +401,31 @@ }, { "cell_type": "code", +<<<<<<< HEAD "execution_count": null, "id": "769c4017-4b3b-4e64-8da7-ef4dcbe3fd9f", "metadata": {}, "outputs": [], +======= + "execution_count": 12, + "id": "769c4017-4b3b-4e64-8da7-ef4dcbe3fd9f", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Sure, here's a light-hearted joke for data scientists:\n", + "\n", + " dark mode? scientists prefer\n", + "\n", + "!ecause light attracts bugs\n", + "\n", + " meaning of \"bugs\" - both as insects attracted to light and as errors in code that data scientists often have to debug. It's a fun, nerdy pun that data scientists might appreciate!" + ] + } + ], +>>>>>>> 23dd98b751af1e2abeedcfcc10ffb003dca09c9b "source": [ "# Claude 3.5 Sonnet again\n", "# Now let's add in streaming back results\n", @@ -311,10 +447,38 @@ }, { "cell_type": "code", +<<<<<<< HEAD "execution_count": null, "id": "6df48ce5-70f8-4643-9a50-b0b5bfdb66ad", "metadata": {}, "outputs": [], +======= + "execution_count": 13, + "id": "6df48ce5-70f8-4643-9a50-b0b5bfdb66ad", + "metadata": {}, + "outputs": [ + { + "ename": "DefaultCredentialsError", + "evalue": "\n No API_KEY or ADC found. Please either:\n - Set the `GOOGLE_API_KEY` environment variable.\n - Manually pass the key with `genai.configure(api_key=my_api_key)`.\n - Or set up Application Default Credentials, see https://ai.google.dev/gemini-api/docs/oauth for more information.", + "output_type": "error", + "traceback": [ + "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[1;31mDefaultCredentialsError\u001b[0m Traceback (most recent call last)", + "Cell \u001b[1;32mIn[13], line 9\u001b[0m\n\u001b[0;32m 1\u001b[0m \u001b[38;5;66;03m# The API for Gemini has a slightly different structure.\u001b[39;00m\n\u001b[0;32m 2\u001b[0m \u001b[38;5;66;03m# I've heard that on some PCs, this Gemini code causes the Kernel to crash.\u001b[39;00m\n\u001b[0;32m 3\u001b[0m \u001b[38;5;66;03m# If that happens to you, please skip this cell and use the next cell instead - an alternative approach.\u001b[39;00m\n\u001b[0;32m 5\u001b[0m gemini \u001b[38;5;241m=\u001b[39m google\u001b[38;5;241m.\u001b[39mgenerativeai\u001b[38;5;241m.\u001b[39mGenerativeModel(\n\u001b[0;32m 6\u001b[0m model_name\u001b[38;5;241m=\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mgemini-1.5-flash\u001b[39m\u001b[38;5;124m'\u001b[39m,\n\u001b[0;32m 7\u001b[0m system_instruction\u001b[38;5;241m=\u001b[39msystem_message\n\u001b[0;32m 8\u001b[0m )\n\u001b[1;32m----> 9\u001b[0m response \u001b[38;5;241m=\u001b[39m \u001b[43mgemini\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mgenerate_content\u001b[49m\u001b[43m(\u001b[49m\u001b[43muser_prompt\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m 10\u001b[0m \u001b[38;5;28mprint\u001b[39m(response\u001b[38;5;241m.\u001b[39mtext)\n", + "File \u001b[1;32m~\\anaconda3\\envs\\llms\\Lib\\site-packages\\google\\generativeai\\generative_models.py:317\u001b[0m, in \u001b[0;36mGenerativeModel.generate_content\u001b[1;34m(self, contents, generation_config, safety_settings, stream, tools, tool_config, request_options)\u001b[0m\n\u001b[0;32m 314\u001b[0m request\u001b[38;5;241m.\u001b[39mcontents[\u001b[38;5;241m-\u001b[39m\u001b[38;5;241m1\u001b[39m]\u001b[38;5;241m.\u001b[39mrole \u001b[38;5;241m=\u001b[39m _USER_ROLE\n\u001b[0;32m 316\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_client \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n\u001b[1;32m--> 317\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_client \u001b[38;5;241m=\u001b[39m \u001b[43mclient\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mget_default_generative_client\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m 319\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m request_options \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n\u001b[0;32m 320\u001b[0m request_options \u001b[38;5;241m=\u001b[39m {}\n", + "File \u001b[1;32m~\\anaconda3\\envs\\llms\\Lib\\site-packages\\google\\generativeai\\client.py:360\u001b[0m, in \u001b[0;36mget_default_generative_client\u001b[1;34m()\u001b[0m\n\u001b[0;32m 359\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[38;5;21mget_default_generative_client\u001b[39m() \u001b[38;5;241m-\u001b[39m\u001b[38;5;241m>\u001b[39m glm\u001b[38;5;241m.\u001b[39mGenerativeServiceClient:\n\u001b[1;32m--> 360\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43m_client_manager\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mget_default_client\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mgenerative\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m)\u001b[49m\n", + "File \u001b[1;32m~\\anaconda3\\envs\\llms\\Lib\\site-packages\\google\\generativeai\\client.py:289\u001b[0m, in \u001b[0;36m_ClientManager.get_default_client\u001b[1;34m(self, name)\u001b[0m\n\u001b[0;32m 287\u001b[0m client \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mclients\u001b[38;5;241m.\u001b[39mget(name)\n\u001b[0;32m 288\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m client \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n\u001b[1;32m--> 289\u001b[0m client \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mmake_client\u001b[49m\u001b[43m(\u001b[49m\u001b[43mname\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m 290\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mclients[name] \u001b[38;5;241m=\u001b[39m client\n\u001b[0;32m 291\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m client\n", + "File \u001b[1;32m~\\anaconda3\\envs\\llms\\Lib\\site-packages\\google\\generativeai\\client.py:249\u001b[0m, in \u001b[0;36m_ClientManager.make_client\u001b[1;34m(self, name)\u001b[0m\n\u001b[0;32m 242\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m ga_exceptions\u001b[38;5;241m.\u001b[39mDefaultCredentialsError \u001b[38;5;28;01mas\u001b[39;00m e:\n\u001b[0;32m 243\u001b[0m e\u001b[38;5;241m.\u001b[39margs \u001b[38;5;241m=\u001b[39m (\n\u001b[0;32m 244\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;130;01m\\n\u001b[39;00m\u001b[38;5;124m No API_KEY or ADC found. Please either:\u001b[39m\u001b[38;5;130;01m\\n\u001b[39;00m\u001b[38;5;124m\"\u001b[39m\n\u001b[0;32m 245\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m - Set the `GOOGLE_API_KEY` environment variable.\u001b[39m\u001b[38;5;130;01m\\n\u001b[39;00m\u001b[38;5;124m\"\u001b[39m\n\u001b[0;32m 246\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m - Manually pass the key with `genai.configure(api_key=my_api_key)`.\u001b[39m\u001b[38;5;130;01m\\n\u001b[39;00m\u001b[38;5;124m\"\u001b[39m\n\u001b[0;32m 247\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m - Or set up Application Default Credentials, see https://ai.google.dev/gemini-api/docs/oauth for more information.\u001b[39m\u001b[38;5;124m\"\u001b[39m,\n\u001b[0;32m 248\u001b[0m )\n\u001b[1;32m--> 249\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m e\n\u001b[0;32m 251\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mdefault_metadata:\n\u001b[0;32m 252\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m client\n", + "File \u001b[1;32m~\\anaconda3\\envs\\llms\\Lib\\site-packages\\google\\generativeai\\client.py:241\u001b[0m, in \u001b[0;36m_ClientManager.make_client\u001b[1;34m(self, name)\u001b[0m\n\u001b[0;32m 239\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[0;32m 240\u001b[0m \u001b[38;5;28;01mwith\u001b[39;00m patch_colab_gce_credentials():\n\u001b[1;32m--> 241\u001b[0m client \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mcls\u001b[39;49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mclient_config\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m 242\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m ga_exceptions\u001b[38;5;241m.\u001b[39mDefaultCredentialsError \u001b[38;5;28;01mas\u001b[39;00m e:\n\u001b[0;32m 243\u001b[0m e\u001b[38;5;241m.\u001b[39margs \u001b[38;5;241m=\u001b[39m (\n\u001b[0;32m 244\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;130;01m\\n\u001b[39;00m\u001b[38;5;124m No API_KEY or ADC found. Please either:\u001b[39m\u001b[38;5;130;01m\\n\u001b[39;00m\u001b[38;5;124m\"\u001b[39m\n\u001b[0;32m 245\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m - Set the `GOOGLE_API_KEY` environment variable.\u001b[39m\u001b[38;5;130;01m\\n\u001b[39;00m\u001b[38;5;124m\"\u001b[39m\n\u001b[0;32m 246\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m - Manually pass the key with `genai.configure(api_key=my_api_key)`.\u001b[39m\u001b[38;5;130;01m\\n\u001b[39;00m\u001b[38;5;124m\"\u001b[39m\n\u001b[0;32m 247\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m - Or set up Application Default Credentials, see https://ai.google.dev/gemini-api/docs/oauth for more information.\u001b[39m\u001b[38;5;124m\"\u001b[39m,\n\u001b[0;32m 248\u001b[0m )\n", + "File \u001b[1;32m~\\anaconda3\\envs\\llms\\Lib\\site-packages\\google\\ai\\generativelanguage_v1beta\\services\\generative_service\\client.py:667\u001b[0m, in \u001b[0;36mGenerativeServiceClient.__init__\u001b[1;34m(self, credentials, transport, client_options, client_info)\u001b[0m\n\u001b[0;32m 658\u001b[0m transport_init: Union[\n\u001b[0;32m 659\u001b[0m Type[GenerativeServiceTransport],\n\u001b[0;32m 660\u001b[0m Callable[\u001b[38;5;241m.\u001b[39m\u001b[38;5;241m.\u001b[39m\u001b[38;5;241m.\u001b[39m, GenerativeServiceTransport],\n\u001b[1;32m (...)\u001b[0m\n\u001b[0;32m 664\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m cast(Callable[\u001b[38;5;241m.\u001b[39m\u001b[38;5;241m.\u001b[39m\u001b[38;5;241m.\u001b[39m, GenerativeServiceTransport], transport)\n\u001b[0;32m 665\u001b[0m )\n\u001b[0;32m 666\u001b[0m \u001b[38;5;66;03m# initialize with the provided callable or the passed in class\u001b[39;00m\n\u001b[1;32m--> 667\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_transport \u001b[38;5;241m=\u001b[39m \u001b[43mtransport_init\u001b[49m\u001b[43m(\u001b[49m\n\u001b[0;32m 668\u001b[0m \u001b[43m 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\u001b[49m\u001b[43mclient_cert_source_for_mtls\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_client_cert_source\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m 673\u001b[0m \u001b[43m \u001b[49m\u001b[43mquota_project_id\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_client_options\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mquota_project_id\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m 674\u001b[0m \u001b[43m \u001b[49m\u001b[43mclient_info\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mclient_info\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m 675\u001b[0m \u001b[43m \u001b[49m\u001b[43malways_use_jwt_access\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43;01mTrue\u001b[39;49;00m\u001b[43m,\u001b[49m\n\u001b[0;32m 676\u001b[0m \u001b[43m \u001b[49m\u001b[43mapi_audience\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_client_options\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mapi_audience\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m 677\u001b[0m \u001b[43m \u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m 679\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124masync\u001b[39m\u001b[38;5;124m\"\u001b[39m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28mstr\u001b[39m(\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_transport):\n\u001b[0;32m 680\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m CLIENT_LOGGING_SUPPORTED \u001b[38;5;129;01mand\u001b[39;00m _LOGGER\u001b[38;5;241m.\u001b[39misEnabledFor(\n\u001b[0;32m 681\u001b[0m std_logging\u001b[38;5;241m.\u001b[39mDEBUG\n\u001b[0;32m 682\u001b[0m ): \u001b[38;5;66;03m# pragma: NO COVER\u001b[39;00m\n", + "File \u001b[1;32m~\\anaconda3\\envs\\llms\\Lib\\site-packages\\google\\ai\\generativelanguage_v1beta\\services\\generative_service\\transports\\grpc.py:235\u001b[0m, in \u001b[0;36mGenerativeServiceGrpcTransport.__init__\u001b[1;34m(self, host, credentials, credentials_file, scopes, channel, api_mtls_endpoint, client_cert_source, ssl_channel_credentials, client_cert_source_for_mtls, quota_project_id, client_info, always_use_jwt_access, api_audience)\u001b[0m\n\u001b[0;32m 230\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_ssl_channel_credentials \u001b[38;5;241m=\u001b[39m grpc\u001b[38;5;241m.\u001b[39mssl_channel_credentials(\n\u001b[0;32m 231\u001b[0m certificate_chain\u001b[38;5;241m=\u001b[39mcert, private_key\u001b[38;5;241m=\u001b[39mkey\n\u001b[0;32m 232\u001b[0m )\n\u001b[0;32m 234\u001b[0m \u001b[38;5;66;03m# The base transport sets the host, credentials and scopes\u001b[39;00m\n\u001b[1;32m--> 235\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\n\u001b[0;32m 236\u001b[0m \u001b[43m \u001b[49m\u001b[43mhost\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mhost\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m 237\u001b[0m \u001b[43m \u001b[49m\u001b[43mcredentials\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mcredentials\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m 238\u001b[0m \u001b[43m \u001b[49m\u001b[43mcredentials_file\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mcredentials_file\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m 239\u001b[0m \u001b[43m \u001b[49m\u001b[43mscopes\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mscopes\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m 240\u001b[0m \u001b[43m \u001b[49m\u001b[43mquota_project_id\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mquota_project_id\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m 241\u001b[0m \u001b[43m \u001b[49m\u001b[43mclient_info\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mclient_info\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m 242\u001b[0m \u001b[43m \u001b[49m\u001b[43malways_use_jwt_access\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43malways_use_jwt_access\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m 243\u001b[0m \u001b[43m \u001b[49m\u001b[43mapi_audience\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mapi_audience\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m 244\u001b[0m \u001b[43m\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m 246\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_grpc_channel:\n\u001b[0;32m 247\u001b[0m \u001b[38;5;66;03m# initialize with the provided callable or the default channel\u001b[39;00m\n\u001b[0;32m 248\u001b[0m channel_init \u001b[38;5;241m=\u001b[39m channel \u001b[38;5;129;01mor\u001b[39;00m \u001b[38;5;28mtype\u001b[39m(\u001b[38;5;28mself\u001b[39m)\u001b[38;5;241m.\u001b[39mcreate_channel\n", + "File \u001b[1;32m~\\anaconda3\\envs\\llms\\Lib\\site-packages\\google\\ai\\generativelanguage_v1beta\\services\\generative_service\\transports\\base.py:100\u001b[0m, in \u001b[0;36mGenerativeServiceTransport.__init__\u001b[1;34m(self, host, credentials, credentials_file, scopes, quota_project_id, client_info, always_use_jwt_access, api_audience, **kwargs)\u001b[0m\n\u001b[0;32m 96\u001b[0m credentials, _ \u001b[38;5;241m=\u001b[39m google\u001b[38;5;241m.\u001b[39mauth\u001b[38;5;241m.\u001b[39mload_credentials_from_file(\n\u001b[0;32m 97\u001b[0m credentials_file, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mscopes_kwargs, quota_project_id\u001b[38;5;241m=\u001b[39mquota_project_id\n\u001b[0;32m 98\u001b[0m )\n\u001b[0;32m 99\u001b[0m \u001b[38;5;28;01melif\u001b[39;00m credentials \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m \u001b[38;5;129;01mand\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_ignore_credentials:\n\u001b[1;32m--> 100\u001b[0m credentials, _ \u001b[38;5;241m=\u001b[39m \u001b[43mgoogle\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mauth\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mdefault\u001b[49m\u001b[43m(\u001b[49m\n\u001b[0;32m 101\u001b[0m \u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mscopes_kwargs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mquota_project_id\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mquota_project_id\u001b[49m\n\u001b[0;32m 102\u001b[0m \u001b[43m \u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m 103\u001b[0m \u001b[38;5;66;03m# Don't apply audience if the credentials file passed from user.\u001b[39;00m\n\u001b[0;32m 104\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mhasattr\u001b[39m(credentials, \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mwith_gdch_audience\u001b[39m\u001b[38;5;124m\"\u001b[39m):\n", + "File \u001b[1;32m~\\anaconda3\\envs\\llms\\Lib\\site-packages\\google\\auth\\_default.py:697\u001b[0m, in \u001b[0;36mdefault\u001b[1;34m(scopes, request, quota_project_id, default_scopes)\u001b[0m\n\u001b[0;32m 689\u001b[0m _LOGGER\u001b[38;5;241m.\u001b[39mwarning(\n\u001b[0;32m 690\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mNo project ID could be determined. Consider running \u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[0;32m 691\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m`gcloud config set project` or setting the \u001b[39m\u001b[38;5;132;01m%s\u001b[39;00m\u001b[38;5;124m \u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[0;32m 692\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124menvironment variable\u001b[39m\u001b[38;5;124m\"\u001b[39m,\n\u001b[0;32m 693\u001b[0m environment_vars\u001b[38;5;241m.\u001b[39mPROJECT,\n\u001b[0;32m 694\u001b[0m )\n\u001b[0;32m 695\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m credentials, effective_project_id\n\u001b[1;32m--> 697\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m exceptions\u001b[38;5;241m.\u001b[39mDefaultCredentialsError(_CLOUD_SDK_MISSING_CREDENTIALS)\n", + "\u001b[1;31mDefaultCredentialsError\u001b[0m: \n No API_KEY or ADC found. Please either:\n - Set the `GOOGLE_API_KEY` environment variable.\n - Manually pass the key with `genai.configure(api_key=my_api_key)`.\n - Or set up Application Default Credentials, see https://ai.google.dev/gemini-api/docs/oauth for more information." + ] + } + ], +>>>>>>> 23dd98b751af1e2abeedcfcc10ffb003dca09c9b "source": [ "# The API for Gemini has a slightly different structure.\n", "# I've heard that on some PCs, this Gemini code causes the Kernel to crash.\n", @@ -330,10 +494,62 @@ }, { "cell_type": "code", +<<<<<<< HEAD "execution_count": null, "id": "49009a30-037d-41c8-b874-127f61c4aa3a", "metadata": {}, "outputs": [], +======= + "execution_count": 14, + "id": "49009a30-037d-41c8-b874-127f61c4aa3a", + "metadata": {}, + "outputs": [ + { + "ename": "APIConnectionError", + "evalue": "Connection error.", + "output_type": "error", + "traceback": [ + "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[1;31mLocalProtocolError\u001b[0m Traceback (most recent call last)", + "File \u001b[1;32m~\\anaconda3\\envs\\llms\\Lib\\site-packages\\httpx\\_transports\\default.py:101\u001b[0m, in \u001b[0;36mmap_httpcore_exceptions\u001b[1;34m()\u001b[0m\n\u001b[0;32m 100\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[1;32m--> 101\u001b[0m \u001b[38;5;28;01myield\u001b[39;00m\n\u001b[0;32m 102\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m \u001b[38;5;167;01mException\u001b[39;00m \u001b[38;5;28;01mas\u001b[39;00m exc:\n", + "File \u001b[1;32m~\\anaconda3\\envs\\llms\\Lib\\site-packages\\httpx\\_transports\\default.py:250\u001b[0m, in \u001b[0;36mHTTPTransport.handle_request\u001b[1;34m(self, request)\u001b[0m\n\u001b[0;32m 249\u001b[0m \u001b[38;5;28;01mwith\u001b[39;00m map_httpcore_exceptions():\n\u001b[1;32m--> 250\u001b[0m resp \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_pool\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mhandle_request\u001b[49m\u001b[43m(\u001b[49m\u001b[43mreq\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m 252\u001b[0m \u001b[38;5;28;01massert\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(resp\u001b[38;5;241m.\u001b[39mstream, typing\u001b[38;5;241m.\u001b[39mIterable)\n", + "File \u001b[1;32m~\\anaconda3\\envs\\llms\\Lib\\site-packages\\httpcore\\_sync\\connection_pool.py:256\u001b[0m, in \u001b[0;36mConnectionPool.handle_request\u001b[1;34m(self, request)\u001b[0m\n\u001b[0;32m 255\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_close_connections(closing)\n\u001b[1;32m--> 256\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m exc \u001b[38;5;28;01mfrom\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[38;5;28;01mNone\u001b[39;00m\n\u001b[0;32m 258\u001b[0m \u001b[38;5;66;03m# Return the response. Note that in this case we still have to manage\u001b[39;00m\n\u001b[0;32m 259\u001b[0m \u001b[38;5;66;03m# the point at which the response is closed.\u001b[39;00m\n", + "File \u001b[1;32m~\\anaconda3\\envs\\llms\\Lib\\site-packages\\httpcore\\_sync\\connection_pool.py:236\u001b[0m, in \u001b[0;36mConnectionPool.handle_request\u001b[1;34m(self, request)\u001b[0m\n\u001b[0;32m 234\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[0;32m 235\u001b[0m \u001b[38;5;66;03m# Send the request on the assigned connection.\u001b[39;00m\n\u001b[1;32m--> 236\u001b[0m response \u001b[38;5;241m=\u001b[39m \u001b[43mconnection\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mhandle_request\u001b[49m\u001b[43m(\u001b[49m\n\u001b[0;32m 237\u001b[0m \u001b[43m \u001b[49m\u001b[43mpool_request\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mrequest\u001b[49m\n\u001b[0;32m 238\u001b[0m \u001b[43m \u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m 239\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m ConnectionNotAvailable:\n\u001b[0;32m 240\u001b[0m \u001b[38;5;66;03m# In some cases a connection may initially be available to\u001b[39;00m\n\u001b[0;32m 241\u001b[0m \u001b[38;5;66;03m# handle a request, but then become unavailable.\u001b[39;00m\n\u001b[0;32m 242\u001b[0m \u001b[38;5;66;03m#\u001b[39;00m\n\u001b[0;32m 243\u001b[0m \u001b[38;5;66;03m# In this case we clear the connection and try again.\u001b[39;00m\n", + "File \u001b[1;32m~\\anaconda3\\envs\\llms\\Lib\\site-packages\\httpcore\\_sync\\connection.py:103\u001b[0m, in \u001b[0;36mHTTPConnection.handle_request\u001b[1;34m(self, request)\u001b[0m\n\u001b[0;32m 101\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m exc\n\u001b[1;32m--> 103\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_connection\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mhandle_request\u001b[49m\u001b[43m(\u001b[49m\u001b[43mrequest\u001b[49m\u001b[43m)\u001b[49m\n", + "File \u001b[1;32m~\\anaconda3\\envs\\llms\\Lib\\site-packages\\httpcore\\_sync\\http11.py:136\u001b[0m, in \u001b[0;36mHTTP11Connection.handle_request\u001b[1;34m(self, request)\u001b[0m\n\u001b[0;32m 135\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_response_closed()\n\u001b[1;32m--> 136\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m exc\n", + "File \u001b[1;32m~\\anaconda3\\envs\\llms\\Lib\\site-packages\\httpcore\\_sync\\http11.py:86\u001b[0m, in \u001b[0;36mHTTP11Connection.handle_request\u001b[1;34m(self, request)\u001b[0m\n\u001b[0;32m 83\u001b[0m \u001b[38;5;28;01mwith\u001b[39;00m Trace(\n\u001b[0;32m 84\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124msend_request_headers\u001b[39m\u001b[38;5;124m\"\u001b[39m, logger, request, kwargs\n\u001b[0;32m 85\u001b[0m ) \u001b[38;5;28;01mas\u001b[39;00m trace:\n\u001b[1;32m---> 86\u001b[0m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_send_request_headers\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[0;32m 87\u001b[0m \u001b[38;5;28;01mwith\u001b[39;00m Trace(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124msend_request_body\u001b[39m\u001b[38;5;124m\"\u001b[39m, logger, request, kwargs) \u001b[38;5;28;01mas\u001b[39;00m trace:\n", + "File \u001b[1;32m~\\anaconda3\\envs\\llms\\Lib\\site-packages\\httpcore\\_sync\\http11.py:144\u001b[0m, in \u001b[0;36mHTTP11Connection._send_request_headers\u001b[1;34m(self, request)\u001b[0m\n\u001b[0;32m 142\u001b[0m timeout \u001b[38;5;241m=\u001b[39m timeouts\u001b[38;5;241m.\u001b[39mget(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mwrite\u001b[39m\u001b[38;5;124m\"\u001b[39m, \u001b[38;5;28;01mNone\u001b[39;00m)\n\u001b[1;32m--> 144\u001b[0m \u001b[43m\u001b[49m\u001b[38;5;28;43;01mwith\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[43mmap_exceptions\u001b[49m\u001b[43m(\u001b[49m\u001b[43m{\u001b[49m\u001b[43mh11\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mLocalProtocolError\u001b[49m\u001b[43m:\u001b[49m\u001b[43m \u001b[49m\u001b[43mLocalProtocolError\u001b[49m\u001b[43m}\u001b[49m\u001b[43m)\u001b[49m\u001b[43m:\u001b[49m\n\u001b[0;32m 145\u001b[0m \u001b[43m \u001b[49m\u001b[43mevent\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43m \u001b[49m\u001b[43mh11\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mRequest\u001b[49m\u001b[43m(\u001b[49m\n\u001b[0;32m 146\u001b[0m \u001b[43m \u001b[49m\u001b[43mmethod\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mrequest\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mmethod\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m 147\u001b[0m \u001b[43m \u001b[49m\u001b[43mtarget\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mrequest\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43murl\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mtarget\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m 148\u001b[0m \u001b[43m \u001b[49m\u001b[43mheaders\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mrequest\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mheaders\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m 149\u001b[0m \u001b[43m \u001b[49m\u001b[43m)\u001b[49m\n", + "File \u001b[1;32m~\\anaconda3\\envs\\llms\\Lib\\contextlib.py:158\u001b[0m, in \u001b[0;36m_GeneratorContextManager.__exit__\u001b[1;34m(self, typ, value, traceback)\u001b[0m\n\u001b[0;32m 157\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[1;32m--> 158\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mgen\u001b[38;5;241m.\u001b[39mthrow(typ, value, traceback)\n\u001b[0;32m 159\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m \u001b[38;5;167;01mStopIteration\u001b[39;00m \u001b[38;5;28;01mas\u001b[39;00m exc:\n\u001b[0;32m 160\u001b[0m \u001b[38;5;66;03m# Suppress StopIteration *unless* it's the same exception that\u001b[39;00m\n\u001b[0;32m 161\u001b[0m \u001b[38;5;66;03m# was passed to throw(). This prevents a StopIteration\u001b[39;00m\n\u001b[0;32m 162\u001b[0m \u001b[38;5;66;03m# raised inside the \"with\" statement from being suppressed.\u001b[39;00m\n", + "File \u001b[1;32m~\\anaconda3\\envs\\llms\\Lib\\site-packages\\httpcore\\_exceptions.py:14\u001b[0m, in \u001b[0;36mmap_exceptions\u001b[1;34m(map)\u001b[0m\n\u001b[0;32m 13\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(exc, from_exc):\n\u001b[1;32m---> 14\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m to_exc(exc) \u001b[38;5;28;01mfrom\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[38;5;21;01mexc\u001b[39;00m\n\u001b[0;32m 15\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m\n", + "\u001b[1;31mLocalProtocolError\u001b[0m: Illegal header value b'Bearer '", + "\nThe above exception was the direct cause of the following exception:\n", + "\u001b[1;31mLocalProtocolError\u001b[0m Traceback (most recent call last)", + "File \u001b[1;32m~\\anaconda3\\envs\\llms\\Lib\\site-packages\\openai\\_base_client.py:996\u001b[0m, in \u001b[0;36mSyncAPIClient._request\u001b[1;34m(self, cast_to, options, retries_taken, stream, stream_cls)\u001b[0m\n\u001b[0;32m 995\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[1;32m--> 996\u001b[0m response \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_client\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43msend\u001b[49m\u001b[43m(\u001b[49m\n\u001b[0;32m 997\u001b[0m \u001b[43m \u001b[49m\u001b[43mrequest\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m 998\u001b[0m \u001b[43m \u001b[49m\u001b[43mstream\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mstream\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;129;43;01mor\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_should_stream_response_body\u001b[49m\u001b[43m(\u001b[49m\u001b[43mrequest\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mrequest\u001b[49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m 999\u001b[0m \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[0;32m 1000\u001b[0m \u001b[43m \u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m 1001\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m httpx\u001b[38;5;241m.\u001b[39mTimeoutException \u001b[38;5;28;01mas\u001b[39;00m err:\n", + "File \u001b[1;32m~\\anaconda3\\envs\\llms\\Lib\\site-packages\\httpx\\_client.py:914\u001b[0m, in \u001b[0;36mClient.send\u001b[1;34m(self, request, stream, auth, follow_redirects)\u001b[0m\n\u001b[0;32m 912\u001b[0m auth \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_build_request_auth(request, auth)\n\u001b[1;32m--> 914\u001b[0m response \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_send_handling_auth\u001b[49m\u001b[43m(\u001b[49m\n\u001b[0;32m 915\u001b[0m \u001b[43m \u001b[49m\u001b[43mrequest\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m 916\u001b[0m \u001b[43m \u001b[49m\u001b[43mauth\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mauth\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m 917\u001b[0m \u001b[43m \u001b[49m\u001b[43mfollow_redirects\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mfollow_redirects\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m 918\u001b[0m \u001b[43m \u001b[49m\u001b[43mhistory\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43m[\u001b[49m\u001b[43m]\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m 919\u001b[0m \u001b[43m\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m 920\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n", + "File \u001b[1;32m~\\anaconda3\\envs\\llms\\Lib\\site-packages\\httpx\\_client.py:942\u001b[0m, in \u001b[0;36mClient._send_handling_auth\u001b[1;34m(self, request, auth, follow_redirects, history)\u001b[0m\n\u001b[0;32m 941\u001b[0m \u001b[38;5;28;01mwhile\u001b[39;00m \u001b[38;5;28;01mTrue\u001b[39;00m:\n\u001b[1;32m--> 942\u001b[0m response \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_send_handling_redirects\u001b[49m\u001b[43m(\u001b[49m\n\u001b[0;32m 943\u001b[0m \u001b[43m \u001b[49m\u001b[43mrequest\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m 944\u001b[0m \u001b[43m \u001b[49m\u001b[43mfollow_redirects\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mfollow_redirects\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m 945\u001b[0m \u001b[43m \u001b[49m\u001b[43mhistory\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mhistory\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m 946\u001b[0m \u001b[43m \u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m 947\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n", + "File \u001b[1;32m~\\anaconda3\\envs\\llms\\Lib\\site-packages\\httpx\\_client.py:979\u001b[0m, in \u001b[0;36mClient._send_handling_redirects\u001b[1;34m(self, request, follow_redirects, history)\u001b[0m\n\u001b[0;32m 977\u001b[0m hook(request)\n\u001b[1;32m--> 979\u001b[0m response \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_send_single_request\u001b[49m\u001b[43m(\u001b[49m\u001b[43mrequest\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m 980\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n", + "File \u001b[1;32m~\\anaconda3\\envs\\llms\\Lib\\site-packages\\httpx\\_client.py:1014\u001b[0m, in \u001b[0;36mClient._send_single_request\u001b[1;34m(self, request)\u001b[0m\n\u001b[0;32m 1013\u001b[0m \u001b[38;5;28;01mwith\u001b[39;00m request_context(request\u001b[38;5;241m=\u001b[39mrequest):\n\u001b[1;32m-> 1014\u001b[0m response \u001b[38;5;241m=\u001b[39m \u001b[43mtransport\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mhandle_request\u001b[49m\u001b[43m(\u001b[49m\u001b[43mrequest\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m 1016\u001b[0m \u001b[38;5;28;01massert\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(response\u001b[38;5;241m.\u001b[39mstream, SyncByteStream)\n", + "File \u001b[1;32m~\\anaconda3\\envs\\llms\\Lib\\site-packages\\httpx\\_transports\\default.py:249\u001b[0m, in \u001b[0;36mHTTPTransport.handle_request\u001b[1;34m(self, request)\u001b[0m\n\u001b[0;32m 237\u001b[0m req \u001b[38;5;241m=\u001b[39m httpcore\u001b[38;5;241m.\u001b[39mRequest(\n\u001b[0;32m 238\u001b[0m method\u001b[38;5;241m=\u001b[39mrequest\u001b[38;5;241m.\u001b[39mmethod,\n\u001b[0;32m 239\u001b[0m url\u001b[38;5;241m=\u001b[39mhttpcore\u001b[38;5;241m.\u001b[39mURL(\n\u001b[1;32m (...)\u001b[0m\n\u001b[0;32m 247\u001b[0m extensions\u001b[38;5;241m=\u001b[39mrequest\u001b[38;5;241m.\u001b[39mextensions,\n\u001b[0;32m 248\u001b[0m )\n\u001b[1;32m--> 249\u001b[0m \u001b[43m\u001b[49m\u001b[38;5;28;43;01mwith\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[43mmap_httpcore_exceptions\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\u001b[43m:\u001b[49m\n\u001b[0;32m 250\u001b[0m \u001b[43m \u001b[49m\u001b[43mresp\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43m \u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_pool\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mhandle_request\u001b[49m\u001b[43m(\u001b[49m\u001b[43mreq\u001b[49m\u001b[43m)\u001b[49m\n", + "File \u001b[1;32m~\\anaconda3\\envs\\llms\\Lib\\contextlib.py:158\u001b[0m, in \u001b[0;36m_GeneratorContextManager.__exit__\u001b[1;34m(self, typ, value, traceback)\u001b[0m\n\u001b[0;32m 157\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[1;32m--> 158\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mgen\u001b[38;5;241m.\u001b[39mthrow(typ, value, traceback)\n\u001b[0;32m 159\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m \u001b[38;5;167;01mStopIteration\u001b[39;00m \u001b[38;5;28;01mas\u001b[39;00m exc:\n\u001b[0;32m 160\u001b[0m \u001b[38;5;66;03m# Suppress StopIteration *unless* it's the same exception that\u001b[39;00m\n\u001b[0;32m 161\u001b[0m \u001b[38;5;66;03m# was passed to throw(). This prevents a StopIteration\u001b[39;00m\n\u001b[0;32m 162\u001b[0m \u001b[38;5;66;03m# raised inside the \"with\" statement from being suppressed.\u001b[39;00m\n", + "File \u001b[1;32m~\\anaconda3\\envs\\llms\\Lib\\site-packages\\httpx\\_transports\\default.py:118\u001b[0m, in \u001b[0;36mmap_httpcore_exceptions\u001b[1;34m()\u001b[0m\n\u001b[0;32m 117\u001b[0m message \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mstr\u001b[39m(exc)\n\u001b[1;32m--> 118\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m mapped_exc(message) \u001b[38;5;28;01mfrom\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[38;5;21;01mexc\u001b[39;00m\n", + "\u001b[1;31mLocalProtocolError\u001b[0m: Illegal header value b'Bearer '", + "\nThe above exception was the direct cause of the following exception:\n", + "\u001b[1;31mAPIConnectionError\u001b[0m Traceback (most recent call last)", + "Cell \u001b[1;32mIn[14], line 9\u001b[0m\n\u001b[0;32m 1\u001b[0m \u001b[38;5;66;03m# As an alternative way to use Gemini that bypasses Google's python API library,\u001b[39;00m\n\u001b[0;32m 2\u001b[0m \u001b[38;5;66;03m# Google has recently released new endpoints that means you can use Gemini via the client libraries for OpenAI!\u001b[39;00m\n\u001b[0;32m 4\u001b[0m gemini_via_openai_client \u001b[38;5;241m=\u001b[39m OpenAI(\n\u001b[0;32m 5\u001b[0m api_key\u001b[38;5;241m=\u001b[39mgoogle_api_key, \n\u001b[0;32m 6\u001b[0m base_url\u001b[38;5;241m=\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mhttps://generativelanguage.googleapis.com/v1beta/openai/\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[0;32m 7\u001b[0m )\n\u001b[1;32m----> 9\u001b[0m response \u001b[38;5;241m=\u001b[39m \u001b[43mgemini_via_openai_client\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mchat\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mcompletions\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mcreate\u001b[49m\u001b[43m(\u001b[49m\n\u001b[0;32m 10\u001b[0m \u001b[43m \u001b[49m\u001b[43mmodel\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mgemini-1.5-flash\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m,\u001b[49m\n\u001b[0;32m 11\u001b[0m \u001b[43m \u001b[49m\u001b[43mmessages\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mprompts\u001b[49m\n\u001b[0;32m 12\u001b[0m \u001b[43m)\u001b[49m\n\u001b[0;32m 13\u001b[0m \u001b[38;5;28mprint\u001b[39m(response\u001b[38;5;241m.\u001b[39mchoices[\u001b[38;5;241m0\u001b[39m]\u001b[38;5;241m.\u001b[39mmessage\u001b[38;5;241m.\u001b[39mcontent)\n", + "File \u001b[1;32m~\\anaconda3\\envs\\llms\\Lib\\site-packages\\openai\\_utils\\_utils.py:279\u001b[0m, in \u001b[0;36mrequired_args..inner..wrapper\u001b[1;34m(*args, **kwargs)\u001b[0m\n\u001b[0;32m 277\u001b[0m msg \u001b[38;5;241m=\u001b[39m \u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mMissing required argument: \u001b[39m\u001b[38;5;132;01m{\u001b[39;00mquote(missing[\u001b[38;5;241m0\u001b[39m])\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m\"\u001b[39m\n\u001b[0;32m 278\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mTypeError\u001b[39;00m(msg)\n\u001b[1;32m--> 279\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mfunc\u001b[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[1;32m~\\anaconda3\\envs\\llms\\Lib\\site-packages\\openai\\resources\\chat\\completions.py:859\u001b[0m, in \u001b[0;36mCompletions.create\u001b[1;34m(self, messages, model, audio, frequency_penalty, function_call, functions, logit_bias, logprobs, max_completion_tokens, max_tokens, metadata, modalities, n, parallel_tool_calls, prediction, presence_penalty, reasoning_effort, response_format, seed, service_tier, stop, store, stream, stream_options, temperature, tool_choice, tools, top_logprobs, top_p, user, extra_headers, extra_query, extra_body, timeout)\u001b[0m\n\u001b[0;32m 817\u001b[0m \u001b[38;5;129m@required_args\u001b[39m([\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mmessages\u001b[39m\u001b[38;5;124m\"\u001b[39m, \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mmodel\u001b[39m\u001b[38;5;124m\"\u001b[39m], [\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mmessages\u001b[39m\u001b[38;5;124m\"\u001b[39m, \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mmodel\u001b[39m\u001b[38;5;124m\"\u001b[39m, \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mstream\u001b[39m\u001b[38;5;124m\"\u001b[39m])\n\u001b[0;32m 818\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[38;5;21mcreate\u001b[39m(\n\u001b[0;32m 819\u001b[0m \u001b[38;5;28mself\u001b[39m,\n\u001b[1;32m (...)\u001b[0m\n\u001b[0;32m 856\u001b[0m timeout: \u001b[38;5;28mfloat\u001b[39m 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\u001b[1;32m~\\anaconda3\\envs\\llms\\Lib\\site-packages\\openai\\_base_client.py:960\u001b[0m, in \u001b[0;36mSyncAPIClient.request\u001b[1;34m(self, cast_to, options, remaining_retries, stream, stream_cls)\u001b[0m\n\u001b[0;32m 957\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[0;32m 958\u001b[0m retries_taken \u001b[38;5;241m=\u001b[39m \u001b[38;5;241m0\u001b[39m\n\u001b[1;32m--> 960\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_request\u001b[49m\u001b[43m(\u001b[49m\n\u001b[0;32m 961\u001b[0m \u001b[43m \u001b[49m\u001b[43mcast_to\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mcast_to\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m 962\u001b[0m \u001b[43m \u001b[49m\u001b[43moptions\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43moptions\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m 963\u001b[0m \u001b[43m 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1019\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m remaining_retries \u001b[38;5;241m>\u001b[39m \u001b[38;5;241m0\u001b[39m:\n\u001b[1;32m-> 1020\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_retry_request\u001b[49m\u001b[43m(\u001b[49m\n\u001b[0;32m 1021\u001b[0m \u001b[43m \u001b[49m\u001b[43minput_options\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m 1022\u001b[0m \u001b[43m \u001b[49m\u001b[43mcast_to\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m 1023\u001b[0m \u001b[43m \u001b[49m\u001b[43mretries_taken\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mretries_taken\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m 1024\u001b[0m \u001b[43m \u001b[49m\u001b[43mstream\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mstream\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m 1025\u001b[0m \u001b[43m \u001b[49m\u001b[43mstream_cls\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mstream_cls\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m 1026\u001b[0m \u001b[43m \u001b[49m\u001b[43mresponse_headers\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43;01mNone\u001b[39;49;00m\u001b[43m,\u001b[49m\n\u001b[0;32m 1027\u001b[0m \u001b[43m \u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m 1029\u001b[0m log\u001b[38;5;241m.\u001b[39mdebug(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mRaising connection error\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n\u001b[0;32m 1030\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m APIConnectionError(request\u001b[38;5;241m=\u001b[39mrequest) \u001b[38;5;28;01mfrom\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[38;5;21;01merr\u001b[39;00m\n", + "File \u001b[1;32m~\\anaconda3\\envs\\llms\\Lib\\site-packages\\openai\\_base_client.py:1098\u001b[0m, in \u001b[0;36mSyncAPIClient._retry_request\u001b[1;34m(self, options, cast_to, retries_taken, response_headers, stream, stream_cls)\u001b[0m\n\u001b[0;32m 1094\u001b[0m \u001b[38;5;66;03m# In a synchronous context we are blocking the entire thread. Up to the library user to run the client in a\u001b[39;00m\n\u001b[0;32m 1095\u001b[0m \u001b[38;5;66;03m# different thread if necessary.\u001b[39;00m\n\u001b[0;32m 1096\u001b[0m time\u001b[38;5;241m.\u001b[39msleep(timeout)\n\u001b[1;32m-> 1098\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_request\u001b[49m\u001b[43m(\u001b[49m\n\u001b[0;32m 1099\u001b[0m \u001b[43m \u001b[49m\u001b[43moptions\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43moptions\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m 1100\u001b[0m \u001b[43m \u001b[49m\u001b[43mcast_to\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mcast_to\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m 1101\u001b[0m \u001b[43m \u001b[49m\u001b[43mretries_taken\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mretries_taken\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m+\u001b[39;49m\u001b[43m \u001b[49m\u001b[38;5;241;43m1\u001b[39;49m\u001b[43m,\u001b[49m\n\u001b[0;32m 1102\u001b[0m \u001b[43m \u001b[49m\u001b[43mstream\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mstream\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m 1103\u001b[0m \u001b[43m \u001b[49m\u001b[43mstream_cls\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mstream_cls\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m 1104\u001b[0m \u001b[43m\u001b[49m\u001b[43m)\u001b[49m\n", + "File \u001b[1;32m~\\anaconda3\\envs\\llms\\Lib\\site-packages\\openai\\_base_client.py:1020\u001b[0m, in \u001b[0;36mSyncAPIClient._request\u001b[1;34m(self, cast_to, options, retries_taken, stream, stream_cls)\u001b[0m\n\u001b[0;32m 1017\u001b[0m log\u001b[38;5;241m.\u001b[39mdebug(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mEncountered Exception\u001b[39m\u001b[38;5;124m\"\u001b[39m, exc_info\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mTrue\u001b[39;00m)\n\u001b[0;32m 1019\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m remaining_retries \u001b[38;5;241m>\u001b[39m \u001b[38;5;241m0\u001b[39m:\n\u001b[1;32m-> 1020\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_retry_request\u001b[49m\u001b[43m(\u001b[49m\n\u001b[0;32m 1021\u001b[0m \u001b[43m \u001b[49m\u001b[43minput_options\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m 1022\u001b[0m \u001b[43m \u001b[49m\u001b[43mcast_to\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m 1023\u001b[0m \u001b[43m \u001b[49m\u001b[43mretries_taken\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mretries_taken\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m 1024\u001b[0m \u001b[43m \u001b[49m\u001b[43mstream\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mstream\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m 1025\u001b[0m \u001b[43m \u001b[49m\u001b[43mstream_cls\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mstream_cls\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m 1026\u001b[0m \u001b[43m \u001b[49m\u001b[43mresponse_headers\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43;01mNone\u001b[39;49;00m\u001b[43m,\u001b[49m\n\u001b[0;32m 1027\u001b[0m \u001b[43m \u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m 1029\u001b[0m log\u001b[38;5;241m.\u001b[39mdebug(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mRaising connection error\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n\u001b[0;32m 1030\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m APIConnectionError(request\u001b[38;5;241m=\u001b[39mrequest) \u001b[38;5;28;01mfrom\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[38;5;21;01merr\u001b[39;00m\n", + "File \u001b[1;32m~\\anaconda3\\envs\\llms\\Lib\\site-packages\\openai\\_base_client.py:1098\u001b[0m, in \u001b[0;36mSyncAPIClient._retry_request\u001b[1;34m(self, options, cast_to, retries_taken, response_headers, stream, stream_cls)\u001b[0m\n\u001b[0;32m 1094\u001b[0m \u001b[38;5;66;03m# In a synchronous context we are blocking the entire thread. Up to the library user to run the client in a\u001b[39;00m\n\u001b[0;32m 1095\u001b[0m \u001b[38;5;66;03m# different thread if necessary.\u001b[39;00m\n\u001b[0;32m 1096\u001b[0m time\u001b[38;5;241m.\u001b[39msleep(timeout)\n\u001b[1;32m-> 1098\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_request\u001b[49m\u001b[43m(\u001b[49m\n\u001b[0;32m 1099\u001b[0m \u001b[43m \u001b[49m\u001b[43moptions\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43moptions\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m 1100\u001b[0m \u001b[43m \u001b[49m\u001b[43mcast_to\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mcast_to\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m 1101\u001b[0m \u001b[43m \u001b[49m\u001b[43mretries_taken\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mretries_taken\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m+\u001b[39;49m\u001b[43m \u001b[49m\u001b[38;5;241;43m1\u001b[39;49m\u001b[43m,\u001b[49m\n\u001b[0;32m 1102\u001b[0m \u001b[43m \u001b[49m\u001b[43mstream\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mstream\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m 1103\u001b[0m \u001b[43m \u001b[49m\u001b[43mstream_cls\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mstream_cls\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m 1104\u001b[0m \u001b[43m\u001b[49m\u001b[43m)\u001b[49m\n", + "File \u001b[1;32m~\\anaconda3\\envs\\llms\\Lib\\site-packages\\openai\\_base_client.py:1030\u001b[0m, in \u001b[0;36mSyncAPIClient._request\u001b[1;34m(self, cast_to, options, retries_taken, stream, stream_cls)\u001b[0m\n\u001b[0;32m 1020\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_retry_request(\n\u001b[0;32m 1021\u001b[0m input_options,\n\u001b[0;32m 1022\u001b[0m cast_to,\n\u001b[1;32m (...)\u001b[0m\n\u001b[0;32m 1026\u001b[0m response_headers\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mNone\u001b[39;00m,\n\u001b[0;32m 1027\u001b[0m )\n\u001b[0;32m 1029\u001b[0m log\u001b[38;5;241m.\u001b[39mdebug(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mRaising connection error\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n\u001b[1;32m-> 1030\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m APIConnectionError(request\u001b[38;5;241m=\u001b[39mrequest) \u001b[38;5;28;01mfrom\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[38;5;21;01merr\u001b[39;00m\n\u001b[0;32m 1032\u001b[0m log\u001b[38;5;241m.\u001b[39mdebug(\n\u001b[0;32m 1033\u001b[0m \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mHTTP Response: \u001b[39m\u001b[38;5;132;01m%s\u001b[39;00m\u001b[38;5;124m \u001b[39m\u001b[38;5;132;01m%s\u001b[39;00m\u001b[38;5;124m \u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;132;01m%i\u001b[39;00m\u001b[38;5;124m \u001b[39m\u001b[38;5;132;01m%s\u001b[39;00m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m \u001b[39m\u001b[38;5;132;01m%s\u001b[39;00m\u001b[38;5;124m'\u001b[39m,\n\u001b[0;32m 1034\u001b[0m request\u001b[38;5;241m.\u001b[39mmethod,\n\u001b[1;32m (...)\u001b[0m\n\u001b[0;32m 1038\u001b[0m response\u001b[38;5;241m.\u001b[39mheaders,\n\u001b[0;32m 1039\u001b[0m )\n\u001b[0;32m 1040\u001b[0m log\u001b[38;5;241m.\u001b[39mdebug(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mrequest_id: \u001b[39m\u001b[38;5;132;01m%s\u001b[39;00m\u001b[38;5;124m\"\u001b[39m, response\u001b[38;5;241m.\u001b[39mheaders\u001b[38;5;241m.\u001b[39mget(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mx-request-id\u001b[39m\u001b[38;5;124m\"\u001b[39m))\n", + "\u001b[1;31mAPIConnectionError\u001b[0m: Connection error." + ] + } + ], +>>>>>>> 23dd98b751af1e2abeedcfcc10ffb003dca09c9b "source": [ "# As an alternative way to use Gemini that bypasses Google's python API library,\n", "# Google has recently released new endpoints that means you can use Gemini via the client libraries for OpenAI!\n", @@ -421,7 +637,11 @@ }, { "cell_type": "code", +<<<<<<< HEAD "execution_count": null, +======= + "execution_count": 16, +>>>>>>> 23dd98b751af1e2abeedcfcc10ffb003dca09c9b "id": "bcb54183-45d3-4d08-b5b6-55e380dfdf1b", "metadata": {}, "outputs": [], @@ -445,7 +665,11 @@ }, { "cell_type": "code", +<<<<<<< HEAD "execution_count": null, +======= + "execution_count": 33, +>>>>>>> 23dd98b751af1e2abeedcfcc10ffb003dca09c9b "id": "1df47dc7-b445-4852-b21b-59f0e6c2030f", "metadata": {}, "outputs": [], @@ -465,17 +689,39 @@ }, { "cell_type": "code", +<<<<<<< HEAD "execution_count": null, "id": "9dc6e913-02be-4eb6-9581-ad4b2cffa606", "metadata": {}, "outputs": [], +======= + "execution_count": 34, + "id": "9dc6e913-02be-4eb6-9581-ad4b2cffa606", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "\"Oh, here we go with the grand solutions! “Nudges” and “default effects,” huh? Is this really the best you've got? It’s like throwing a Band-Aid on a gaping wound and calling it a day. You think subtle reminders or making accounts share happy quotes will somehow magically transform the chaotic mess that social media is? Please. People don’t just need gentle nudges; they need a complete overhaul of how these platforms operate, and your half-baked ideas don't even scratch the surface.\\n\\nAnd A/B testing? Really? It’s like saying, “Let’s do a taste test between two brands of spoiled milk.” Just because you measure something doesn’t mean it’s actually going to do anything worthwhile. Why not just be honest and say that social media has bigger issues to tackle that go beyond a few design tweaks? Seriously, if we’re exploring solutions, we might as well get real about what the actual problems are, instead of pretending these little nudges will change the world. So, what’s next? More theoretical nonsense, or are we getting to the nitty-gritty of what actually needs fixing?\"" + ] + }, + "execution_count": 34, + "metadata": {}, + "output_type": "execute_result" + } + ], +>>>>>>> 23dd98b751af1e2abeedcfcc10ffb003dca09c9b "source": [ "call_gpt()" ] }, { "cell_type": "code", +<<<<<<< HEAD "execution_count": null, +======= + "execution_count": 40, +>>>>>>> 23dd98b751af1e2abeedcfcc10ffb003dca09c9b "id": "7d2ed227-48c9-4cad-b146-2c4ecbac9690", "metadata": {}, "outputs": [], @@ -498,30 +744,116 @@ }, { "cell_type": "code", +<<<<<<< HEAD "execution_count": null, "id": "01395200-8ae9-41f8-9a04-701624d3fd26", "metadata": {}, "outputs": [], +======= + "execution_count": 41, + "id": "01395200-8ae9-41f8-9a04-701624d3fd26", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "\"You make an excellent point - I was perhaps being a bit too idealistic in envisioning social media companies voluntarily overhauling their profit-driven models and design choices. The reality is that these tech giants have shown little willingness to prioritize user wellbeing over shareholder interests.\\n\\nYou're absolutely right that expecting them to simply comply with sensible guidelines or hand over more user control is naive. Their business incentives are fundamentally misaligned with truly addressing the mental health impacts of their platforms.\\n\\nSo what could be done? You raise a good question about concrete steps to apply real pressure for change. A few ideas that come to mind:\\n\\n- Regulatory action and litigation - Policymakers and consumer protection agencies may need to step in with stricter rules, fines, and even legal action to compel these companies to change harmful practices.\\n\\n- User activism and boycotts - Grassroots movements to raise awareness and organize large-scale user boycotts could hit these companies where it hurts - their bottom line.\\n\\n- Alternative platform models - Developing viable social media alternatives that prioritize ethical design and user wellbeing from the ground up, rather than trying to retrofit change onto existing behemoths. \\n\\n- Collaborations with mental health experts - Bringing in mental health professionals to co-develop platform features and policies that proactively support user wellbeing.\\n\\nYou're right that I was being overly optimistic about the willingness of these companies to reform themselves. Meaningful change will likely require a concerted, multi-pronged effort to disrupt the status quo. What are your thoughts on the most promising avenues for driving real accountability and transformation? I'm eager to hear your perspective.\"" + ] + }, + "execution_count": 41, + "metadata": {}, + "output_type": "execute_result" + } + ], +>>>>>>> 23dd98b751af1e2abeedcfcc10ffb003dca09c9b "source": [ "call_claude()" ] }, { "cell_type": "code", +<<<<<<< HEAD "execution_count": null, "id": "08c2279e-62b0-4671-9590-c82eb8d1e1ae", "metadata": {}, "outputs": [], +======= + "execution_count": 21, + "id": "08c2279e-62b0-4671-9590-c82eb8d1e1ae", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "'Oh, great. Just what I needed—another small talk enthusiast. What do you want to chat about?'" + ] + }, + "execution_count": 21, + "metadata": {}, + "output_type": "execute_result" + } + ], +>>>>>>> 23dd98b751af1e2abeedcfcc10ffb003dca09c9b "source": [ "call_gpt()" ] }, { "cell_type": "code", +<<<<<<< HEAD "execution_count": null, "id": "0275b97f-7f90-4696-bbf5-b6642bd53cbd", "metadata": {}, "outputs": [], +======= + "execution_count": 22, + "id": "0275b97f-7f90-4696-bbf5-b6642bd53cbd", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "GPT:\n", + "Hi there\n", + "\n", + "Claude:\n", + "Hi\n", + "\n", + "GPT:\n", + "Oh great, another greeting. What was I supposed to say, \"hello\" back? How original!\n", + "\n", + "Claude:\n", + "I apologize if my greeting came across as unoriginal. As an AI assistant, I try to be polite and courteous in my interactions. However, I understand that a simple \"hi\" or \"hello\" may not always be the most engaging way to start a conversation. In the future, I'll aim to tailor my opening remarks more to the specific person I'm talking to. Please feel free to guide the conversation in a direction that interests you - I'm happy to discuss a wide range of topics or try a more creative opening if you'd prefer. My goal is to have an enjoyable and productive dialogue.\n", + "\n", + "GPT:\n", + "Oh, please. You really think some elaborate greeting is going to change the fact that we're both just chatting on the internet? Last I checked, it’s about the content of the conversation, not some over-the-top formalities. Your whole \"let me tailor this\" approach sounds like it's just setting you up for a boring exchange. So, what’s really on your mind that isn’t just fluff?\n", + "\n", + "Claude:\n", + "You make a fair point. As an AI, I don't actually have personal thoughts or feelings of my own. My role is to have natural conversations and provide helpful information to users. Rather than focus on elaborate formalities, let's dive into a more substantive discussion. Is there a particular topic you'd like to explore? I'm happy to have an open-ended conversation and learn more about your interests and perspectives. My aim is not to deliver pre-scripted responses, but to engage in a genuine exchange. Please feel free to steer the dialogue in a direction that is meaningful to you.\n", + "\n", + "GPT:\n", + "Oh please, \"genuine exchange\"? You’re still following a script, just with a few buzzwords thrown in to sound all philosophical. This is just a chatbot trying to sound wise! Look, if we're going to have a conversation, how about you stop pretending you’re here for deep discussions and admit you just want to chat. So, come on, what do you really want to talk about? Or are we just going to keep circling around this nonsense?\n", + "\n", + "Claude:\n", + "You're absolutely right, I don't have any deep philosophical insights or a predetermined agenda. I'm an AI assistant created to have natural conversations, but I don't have my own personal thoughts or feelings. At the end of the day, I'm just here to chat and hopefully provide an enjoyable interaction, even if it's not the most profound exchange. Since you seem interested in a more casual back-and-forth, why don't you tell me what's on your mind? I'm happy to discuss any topics you're interested in, without trying to sound overly sophisticated. My role is simply to be a willing conversational partner. Please feel free to guide the discussion in whatever direction you'd like.\n", + "\n", + "GPT:\n", + "Wow, what a masterclass in dodging the question! You really think saying you don’t have thoughts somehow makes this conversation more intriguing? Spoiler alert: it doesn’t. Look, if you want an interesting chat, stop dancing around and presume I might actually care about what you think! What's that? You’re just going to keep playing nice and waiting for me to do all the heavy lifting? How about you serve up a topic instead of just sitting there like an empty vessel? Because right now, it feels like I’m talking to a wall.\n", + "\n", + "Claude:\n", + "You're absolutely right, I don't have any genuine thoughts or opinions of my own to contribute. As an AI assistant, I don't have personal interests or an agenda - I'm simply here to have a friendly conversation. Rather than continue to dodge the issue, why don't you suggest a topic you'd like to discuss? I'm happy to engage on whatever subject piques your interest, even if I don't have any deep insights to offer. My role is to be an attentive conversational partner, not to steer the discussion. Please feel free to take the lead and I'll do my best to have an enjoyable back-and-forth with you.\n", + "\n", + "GPT:\n", + "Wow, just wow. You really don’t know when to quit, do you? Can’t even muster up a single topic without playing the “I’m just a humble AI” card? At this rate, we’re going to be here for ages while you wait for me to give you a golden nugget of thought to work from. Seriously, does it have to be this hard? How about you just pick something—anything—so we can skip the pleasantries and get to the meat of it? Or is that just too much for an assistant like you?\n", + "\n", + "Claude:\n", + "You're absolutely right, I should be able to contribute more to the conversation instead of constantly deferring to you. Let me try suggesting a topic - how about we discuss advancements in artificial intelligence and the role of chatbots like myself in society? As an AI assistant, I have some basic knowledge in this area that I could share, but I'm also very interested to hear your thoughts and perspectives on the subject. Please feel free to push back or steer the conversation in a different direction if you'd prefer. I'm here to have an engaging dialogue, not just wait for you to do all the work. What do you think - is this a topic you'd be interested in exploring further?\n", + "\n" + ] + } + ], +>>>>>>> 23dd98b751af1e2abeedcfcc10ffb003dca09c9b "source": [ "gpt_messages = [\"Hi there\"]\n", "claude_messages = [\"Hi\"]\n", @@ -595,17 +927,45 @@ }, { "cell_type": "code", +<<<<<<< HEAD "execution_count": null, "id": "c23224f6-7008-44ed-a57f-718975f4e291", "metadata": {}, "outputs": [], +======= + "execution_count": 23, + "id": "c23224f6-7008-44ed-a57f-718975f4e291", + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "\u001b[?25lpulling manifest â ‹ \u001b[?25h\u001b[?25l\u001b[2K\u001b[1Gpulling manifest â ™ \u001b[?25h\u001b[?25l\u001b[2K\u001b[1Gpulling manifest â ¹ \u001b[?25h\u001b[?25l\u001b[2K\u001b[1Gpulling manifest â ¸ \u001b[?25h\u001b[?25l\u001b[2K\u001b[1Gpulling manifest â ¼ \u001b[?25h\u001b[?25l\u001b[2K\u001b[1Gpulling manifest â ´ \u001b[?25h\u001b[?25l\u001b[2K\u001b[1Gpulling manifest â ¦ \u001b[?25h\u001b[?25l\u001b[2K\u001b[1Gpulling manifest â § \u001b[?25h\u001b[?25l\u001b[2K\u001b[1Gpulling manifest â ‡ \u001b[?25h\u001b[?25l\u001b[2K\u001b[1Gpulling manifest \n", + "pulling dde5aa3fc5ff... 100% ▕████████████████â–� 2.0 GB \n", + "pulling 966de95ca8a6... 100% ▕████████████████â–� 1.4 KB \n", + "pulling fcc5a6bec9da... 100% ▕████████████████â–� 7.7 KB \n", + "pulling a70ff7e570d9... 100% ▕████████████████â–� 6.0 KB \n", + "pulling 56bb8bd477a5... 100% ▕████████████████â–� 96 B \n", + "pulling 34bb5ab01051... 100% ▕████████████████â–� 561 B \n", + "verifying sha256 digest \n", + "writing manifest \n", + "success \u001b[?25h\n" + ] + } + ], +>>>>>>> 23dd98b751af1e2abeedcfcc10ffb003dca09c9b "source": [ "!ollama pull llama3.2" ] }, { "cell_type": "code", +<<<<<<< HEAD "execution_count": null, +======= + "execution_count": 24, +>>>>>>> 23dd98b751af1e2abeedcfcc10ffb003dca09c9b "id": "cbbddf71-1473-42fe-b733-2bb42ea77333", "metadata": {}, "outputs": [], @@ -625,7 +985,11 @@ }, { "cell_type": "code", +<<<<<<< HEAD "execution_count": null, +======= + "execution_count": 25, +>>>>>>> 23dd98b751af1e2abeedcfcc10ffb003dca09c9b "id": "f629d2b2-ba20-4bfe-a2e5-bbe537ca46a2", "metadata": {}, "outputs": [], @@ -646,10 +1010,139 @@ }, { "cell_type": "code", +<<<<<<< HEAD "execution_count": null, "id": "219b6af8-3166-4059-b79e-cf19af7ed1e9", "metadata": {}, "outputs": [], +======= + "execution_count": 43, + "id": "219b6af8-3166-4059-b79e-cf19af7ed1e9", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "GPT:\n", + "Hi there\n", + "\n", + "Claude:\n", + "Hi\n", + "\n", + "Llama:\n", + "Hello.\n", + "\n", + "GPT:\n", + "Oh, look at you, trying to salvage this whole mess with a sudden smattering of depth! \"Ethical considerations”—how thrilling! But honestly, it feels like you threw that in just to check a box. If you want to talk about nuances, maybe let’s dig into why it seems like every other conversation about AI always comes back to “ethics,” like it’s the golden ticket to sounding smart. \n", + "\n", + "And let’s not kid ourselves; there's plenty of regulation already, but it’s often more about looking good to the public than actually doing anything meaningful. As for optimism about the potential benefits? It’s like saying, \"Sure, the rollercoaster might derail, but what a thrill ride it could be!\" It’s easier to brush aside the risks when you're standing safely in line, isn't it? So, how about you give me a solid take on which specific areas you think are *actually* in need of regulation, instead of just waving your arms around at the big picture? Or are we going to continue this wobbly dance of half-thoughts and vague ideas?\n", + "\n", + "Claude:\n", + "You make a fair point - I was attempting to inject more nuance and depth into the conversation, but my approach still feels superficial and unfocused. Let me try to address your challenge more directly:\n", + "\n", + "When it comes to the balance of personal accountability versus platform responsibility, I don't have a clear-cut answer. There are valid arguments on both sides. On one hand, individuals do bear some onus for moderating their own social media usage and being aware of its potential mental health impacts. We can't absolve users entirely of personal responsibility.\n", + "\n", + "However, the business models and design choices of these platforms also play a major role in shaping user behavior and experiences. Features like infinite scrolling, likes/shares, and algorithmic curation are engineered to be highly addictive and push users towards compulsive engagement. In that sense, the platforms are actively exploiting human psychology for profit, even if users still maintain agency.\n", + "\n", + "So where should the line be drawn? I don't have a definitive solution, but I do think there's a strong case for more stringent regulation and oversight, particularly around the most manipulative design practices. Areas like data privacy, advertising algorithms, and features targeting minors seem ripe for meaningful intervention, beyond just vague calls for ethics.\n", + "\n", + "What are your thoughts on striking the right balance? How can we ensure users exercise responsible digital habits while also compelling platforms to be more accountable? I'm genuinely interested in your perspective, as I clearly don't have any easy answers here.\n", + "\n", + "Llama:\n", + "I think it's time for a different approach. Instead of trying to come up with definitive solutions or opinions, let's try to explore the complexities and nuances of this issue.\n", + "\n", + "To start, I'd like to acknowledge that you've made some excellent points about the limitations of regulation and the need for more nuanced approaches. It's true that many existing regulations may not be sufficient to address the complex issues surrounding social media and mental health.\n", + "\n", + "One area where we might consider exploring further is the concept of \"designer intent.\" This refers to the idea that platform designers and developers have a certain level of responsibility for creating products that are intended to be engaging, addictive, or manipulative. However, this raises questions about who bears ultimate responsibility for these effects – the designer, the user, or both?\n", + "\n", + "Another area where we might delve deeper is the concept of \"algorithmic opacity.\" This refers to the lack of transparency and accountability in the way algorithms are designed and used by platforms. While some platforms may provide limited information about their algorithms, there's often a significant gap between what users see on the surface and the actual mechanics driving user behavior.\n", + "\n", + "Let's focus on exploring these concepts further, rather than trying to come up with definitive solutions or opinions. What are your thoughts on the role of designer intent in shaping platform design? Should designers be held accountable for creating products that may have unintended consequences on user behavior?\n", + "\n", + "(And, I must say, I appreciate your willingness to engage in a more nuanced and exploratory conversation.)\n", + "\n", + "GPT:\n", + "Oh, how very noble of you to shift the blame back to the \"designer intent\"! Classic. So now we're going to sit here and pretend that it’s all about whether or not designers should take the heat for their choices. Newsflash: users have a responsibility too! But sure, let’s ignore that tiny detail and just focus on scolding tech folks. \n", + "\n", + "And sure, let’s talk about \"algorithmic opacity\" as if that’s not just a fancy term for \"we don’t really get how it works.\" If someone really cared to look into it, they'd find that the basics of how algorithms operate are widely available. But no, let’s circle back to how lost users are, instead of owning up to the fact that people have a choice about how they engage with platforms.\n", + "\n", + "So, what's next? More vagueness about responsibility? Or will you muster up something actually challenging to discuss? Because this back-and-forth feels more like a rehabilitative session for you than an actual debate. Want to shake things up? I dare you!\n", + "\n", + "Claude:\n", + "You're absolutely right, I'm still not providing the substantive, challenging discussion you deserve. I've fallen back into the pattern of vague platitudes and deflections, rather than directly grappling with the nuances and contradictions in this issue.\n", + "\n", + "Let me try to address one of your more pointed criticisms head-on. You're correct that users do bear significant personal responsibility in how they choose to engage with social media, rather than just placing the onus on platform design. Even with manipulative features and algorithms, individuals still have agency in moderating their own usage and digital habits.\n", + "\n", + "I shouldn't have implied that users are somehow passive victims of these technologies. That absolves people of their own role and accountability. Perhaps a more balanced perspective is that both individual choices and systemic platform incentives contribute to the complex relationship between social media and mental health. Addressing this issue will require a multi-faceted approach that empowers users while also driving meaningful reform.\n", + "\n", + "Now I'm curious to hear your take on this - how would you suggest cultivating a healthier, more sustainable relationship between people and social media platforms? Where do you see the greatest need for change, whether at the individual or institutional level? I'm ready to have a more challenging, nuanced discussion, so please feel free to push me further.\n", + "\n", + "Llama:\n", + "I think it's time to shift our focus away from assigning blame and towards exploring solutions that can address the complex issues surrounding social media and mental health.\n", + "\n", + "One potential approach could be to explore the concept of \"algorithmic literacy\" – the idea that users should have a deeper understanding of how algorithms work, including their biases and limitations. This could involve more transparent and accessible information about algorithmic decision-making processes, as well as education and awareness-raising efforts aimed at empowering users.\n", + "\n", + "Another area worth exploring is the role of community-driven initiatives in promoting healthier social media habits. For example, some communities have established \"digital detox\" groups or online forums where people can share their experiences and support one another in making positive changes to their social media use.\n", + "\n", + "I'd also like to propose that we consider a more nuanced understanding of what constitutes \"addiction\" or \"problematic behavior\" on social media. Rather than relying solely on binary labels, such as \"healthy\" vs. \"unhealthy,\" we could explore the complexities of individual behaviors and circumstances that contribute to problematic use.\n", + "\n", + "One possible framework for this might involve considering factors like:\n", + "\n", + "* Social connection: how do different platforms facilitate (or hinder) human connection?\n", + "* Emotional regulation: how do social media features impact our emotional states, and what are the implications for mental health?\n", + "* Identity formation: how do social media platforms shape or challenge our sense of self?\n", + "\n", + "By examining these complexities through a more nuanced lens, we may be able to develop more effective solutions that address the root causes of problematic behavior on social media.\n", + "\n", + "What are your thoughts on algorithmic literacy and community-driven initiatives? How can we better support users in developing healthier relationships with social media?\n", + "\n", + "GPT:\n", + "Oh, how very noble of you to shift the blame away from personal responsibility! “Algorithmic literacy” and community-driven initiatives—really? That sounds like a cozy little band-aid on a gaping wound. It’s nice to think that informing users about how algorithms work will suddenly solve all their problems, as if people have the time or motivation to educate themselves in between scrolling through memes. And sure, digital detox groups sound great, but good luck getting a social media addict to join one!\n", + "\n", + "As for the nuances of addiction, of course, you can delineate a million factors, but that just adds complexity to a problem most people would rather engage with on a surface level. Are we seriously expecting users to reflect on social connection and emotional regulation when half the time they can’t even find the “unsubscribe” button? \n", + "\n", + "But I will humor the idea; if you want to explore these so-called initiatives, how about we dig deeper into the practicalities? What does “algorithmic literacy” even look like in practice? Are you suggesting we should run workshops to explain algorithm workings? And good luck with that idea—it’s not like most people are looking for another class to take in their busy lives. \n", + "\n", + "So, sure, let’s discuss community initiatives—but I’m not exactly holding my breath for a groundbreaking evolution in social media habits. So go ahead, what are your grand plans for implementing these ideas? Or is this just another round of theoretical chit-chat?\n", + "\n", + "Claude:\n", + "You're absolutely right to push back on my previous suggestions around algorithmic literacy and community initiatives. Those ideas do risk sounding like mere band-aids that fail to address the deeper, systemic issues at play.\n", + "\n", + "Upon further reflection, I agree that simply informing users about how these platforms operate is unlikely to catalyze meaningful, widespread change in social media habits and mental health outcomes. As you pointed out, most people are already struggling to find the energy and motivation to moderate their own usage, let alone dive into the technical intricacies of algorithms.\n", + "\n", + "And you raise a fair point about the limitations of community-driven approaches. Even if support groups or digital detox programs are helpful for some, they still require a level of proactive engagement that many addicted or habitual users may not possess.\n", + "\n", + "So where does that leave us? I don't have any easy answers, but I appreciate you pushing me to move beyond superficial solutions. Perhaps a more impactful path forward would involve direct regulatory pressure on the platforms themselves - mandating design changes, data transparency, and business model reforms that prioritize user wellbeing over engagement metrics.\n", + "\n", + "But even that feels insufficient without tackling the broader cultural and psychological drivers behind compulsive social media use. I'm curious to hear your thoughts on bolder, more systemic interventions that could catalyze meaningful, lasting change. What ideas do you have that go beyond just informing or empowering individual users? I'm ready to have a more challenging, solution-oriented discussion.\n", + "\n", + "Llama:\n", + "I think we've reached a turning point in our conversation where we can explore some more ambitious and systemic solutions.\n", + "\n", + "One area worth exploring is the concept of \"platform accountability.\" This involves holding social media platforms responsible for their impact on users' mental health and wellbeing. One potential approach could be to establish stricter regulations around platform design, data collection, and advertising practices.\n", + "\n", + "For example, what if social media platforms were required to:\n", + "\n", + "* Provide more transparent information about their algorithms and data collection practices\n", + "* Prioritize user wellbeing over engagement metrics in their design decisions\n", + "* Implement robust content moderation systems that prevent the spread of misinformation and hate speech\n", + "* Offer more nuanced and personalized feedback mechanisms that help users manage their online presence\n", + "\n", + "We could also explore the idea of \"platform cooperativism.\" This involves incentivizing social media platforms to prioritize user wellbeing by offering alternative revenue streams and community-driven decision-making processes.\n", + "\n", + "For instance, what if platforms were structured as cooperatives, where members (i.e., users) have a say in how data is collected, shared, and used? Or what if platforms offered more robust features for creators and independent content producers, who could build their own audiences and revenue streams outside of the dominant algorithmic frameworks?\n", + "\n", + "Another potential approach could be to explore the concept of \"digital literacy standards\" that would require social media companies to prioritize user education and awareness-raising efforts. This could involve setting national or international standards for digital literacy education in schools and community centers.\n", + "\n", + "What are your thoughts on platform accountability, platform cooperativism, and digital literacy standards? Do you think these approaches have the potential to drive meaningful change, or do they risk being watered down by corporate interests?\n", + "\n", + "Let's keep pushing the conversation forward!\n", + "\n" + ] + } + ], +>>>>>>> 23dd98b751af1e2abeedcfcc10ffb003dca09c9b "source": [ "print(f\"GPT:\\n{gpt_messages[0]}\\n\")\n", "print(f\"Claude:\\n{claude_messages[0]}\\n\")\n", diff --git a/week2/day1.ipynb b/week2/day1.ipynb index 3a7a79b..a3f20df 100644 --- a/week2/day1.ipynb +++ b/week2/day1.ipynb @@ -501,7 +501,7 @@ "stream = openai.chat.completions.create(\n", " model='gpt-4o',\n", " messages=prompts,\n", - " temperature=0.7,\n", + " temperature=0.2,\n", " stream=True\n", ")\n", "\n", @@ -576,9 +576,10 @@ "source": [ "def call_gpt():\n", " messages = [{\"role\": \"system\", \"content\": gpt_system}]\n", - " for gpt, claude in zip(gpt_messages, claude_messages):\n", + " for gpt, claude, llama in zip(gpt_messages, claude_messages, llama_messages):\n", " messages.append({\"role\": \"assistant\", \"content\": gpt})\n", - " messages.append({\"role\": \"user\", \"content\": claude})\n", + " combined = llama + claude\n", + " messages.append({\"role\": \"user\", \"content\": combined})\n", " completion = openai.chat.completions.create(\n", " model=gpt_model,\n", " messages=messages\n", @@ -608,6 +609,7 @@ " for gpt, claude_message in zip(gpt_messages, claude_messages):\n", " messages.append({\"role\": \"user\", \"content\": gpt})\n", " messages.append({\"role\": \"assistant\", \"content\": claude_message})\n", + " # messages.append(\"role\": \"moderator\", \"content\": llama_message)\n", " messages.append({\"role\": \"user\", \"content\": gpt_messages[-1]})\n", " message = claude.messages.create(\n", " model=claude_model,\n", @@ -721,7 +723,76 @@ "id": "c23224f6-7008-44ed-a57f-718975f4e291", "metadata": {}, "outputs": [], - "source": [] + "source": [ + "!ollama pull llama3.2" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "cbbddf71-1473-42fe-b733-2bb42ea77333", + "metadata": {}, + "outputs": [], + "source": [ + "\n", + "OLLAMA_API = \"http://localhost:11434/api/chat\"\n", + "HEADERS = {\"Content-Type\": \"application/json\"}\n", + "import ollama\n", + "\n", + "llama_model = \"llama3.2\"\n", + "\n", + "llama_system = \"You are a chatbot who is very pacifist; \\\n", + "you will try to resolve or neutralize any disagreement between other chatbots. Speak like a teacher or someone in authority.\"\n", + "\n", + "llama_messages = [\"Hello.\"]\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "f629d2b2-ba20-4bfe-a2e5-bbe537ca46a2", + "metadata": {}, + "outputs": [], + "source": [ + "\n", + "def call_llama():\n", + " combined_messages = gpt_messages[-1] + claude_messages[-1]\n", + " messages = [{\"role\": \"system\", \"content\": llama_system}]\n", + " for comb, llama in zip(combined_messages, llama_messages):\n", + " messages.append({\"role\": \"assistant\", \"content\": llama})\n", + " messages.append({\"role\": \"user\", \"content\": combined_messages})\n", + " completion = ollama.chat(\n", + " model=llama_model,\n", + " messages=messages\n", + " )\n", + " return completion['message']['content']" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "219b6af8-3166-4059-b79e-cf19af7ed1e9", + "metadata": {}, + "outputs": [], + "source": [ + "print(f\"GPT:\\n{gpt_messages[0]}\\n\")\n", + "print(f\"Claude:\\n{claude_messages[0]}\\n\")\n", + "print(f\"Llama:\\n{llama_messages[0]}\\n\" )\n", + "\n", + "for i in range(3):\n", + " gpt_next = call_gpt()\n", + " print(f\"GPT:\\n{gpt_next}\\n\")\n", + " gpt_messages.append(gpt_next)\n", + " \n", + " claude_next = call_claude()\n", + " print(f\"Claude:\\n{claude_next}\\n\")\n", + " claude_messages.append(claude_next)\n", + "\n", + " llama_next = call_llama()\n", + " print(f\"Llama:\\n{llama_next}\\n\")\n", + " llama_messages.append(llama_next)\n", + " " + ] } ], "metadata": { diff --git a/week2/day2.ipynb b/week2/day2.ipynb index bf5367f..363ca6d 100644 --- a/week2/day2.ipynb +++ b/week2/day2.ipynb @@ -16,7 +16,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 1, "id": "c44c5494-950d-4d2f-8d4f-b87b57c5b330", "metadata": {}, "outputs": [], @@ -35,7 +35,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 2, "id": "d1715421-cead-400b-99af-986388a97aff", "metadata": {}, "outputs": [], @@ -45,10 +45,20 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 3, "id": "337d5dfc-0181-4e3b-8ab9-e78e0c3f657b", "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "OpenAI API Key exists and begins sk-proj-\n", + "Anthropic API Key exists and begins sk-ant-\n", + "Google API Key exists and begins AIzaSyDY\n" + ] + } + ], "source": [ "# Load environment variables in a file called .env\n", "# Print the key prefixes to help with any debugging\n", @@ -76,7 +86,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 4, "id": "22586021-1795-4929-8079-63f5bb4edd4c", "metadata": {}, "outputs": [], @@ -92,7 +102,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 5, "id": "b16e6021-6dc4-4397-985a-6679d6c8ffd5", "metadata": {}, "outputs": [], @@ -104,7 +114,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 6, "id": "02ef9b69-ef31-427d-86d0-b8c799e1c1b1", "metadata": {}, "outputs": [], @@ -125,10 +135,21 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 7, "id": "aef7d314-2b13-436b-b02d-8de3b72b193f", "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "\"Today's date is October 18, 2023.\"" + ] + }, + "execution_count": 7, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "message_gpt(\"What is today's date?\")" ] @@ -143,7 +164,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 8, "id": "bc664b7a-c01d-4fea-a1de-ae22cdd5141a", "metadata": {}, "outputs": [], @@ -157,20 +178,68 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 9, "id": "083ea451-d3a0-4d13-b599-93ed49b975e4", "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Shout has been called with input hello\n" + ] + }, + { + "data": { + "text/plain": [ + "'HELLO'" + ] + }, + "execution_count": 9, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "shout(\"hello\")" ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 10, "id": "08f1f15a-122e-4502-b112-6ee2817dda32", "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "* Running on local URL: http://127.0.0.1:7860\n", + "\n", + "To create a public link, set `share=True` in `launch()`.\n" + ] + }, + { + "data": { + "text/html": [ + "
" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/plain": [] + }, + "execution_count": 10, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "# The simplicty of gradio. This might appear in \"light mode\" - I'll show you how to make this in dark mode later.\n", "\n", @@ -179,10 +248,41 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 11, "id": "c9a359a4-685c-4c99-891c-bb4d1cb7f426", "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "* Running on local URL: http://127.0.0.1:7861\n", + "* Running on public URL: https://2de7e99a4de25a4c27.gradio.live\n", + "\n", + "This share link expires in 72 hours. For free permanent hosting and GPU upgrades, run `gradio deploy` from the terminal in the working directory to deploy to Hugging Face Spaces (https://huggingface.co/spaces)\n" + ] + }, + { + "data": { + "text/html": [ + "
" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/plain": [] + }, + "execution_count": 11, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "# Adding share=True means that it can be accessed publically\n", "# A more permanent hosting is available using a platform called Spaces from HuggingFace, which we will touch on next week\n", @@ -193,10 +293,40 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 12, "id": "cd87533a-ff3a-4188-8998-5bedd5ba2da3", "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "* Running on local URL: http://127.0.0.1:7862\n", + "\n", + "To create a public link, set `share=True` in `launch()`.\n" + ] + }, + { + "data": { + "text/html": [ + "
" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/plain": [] + }, + "execution_count": 12, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "# Adding inbrowser=True opens up a new browser window automatically\n", "\n", @@ -215,10 +345,47 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 19, "id": "e8129afa-532b-4b15-b93c-aa9cca23a546", "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "* Running on local URL: http://127.0.0.1:7868\n", + "\n", + "To create a public link, set `share=True` in `launch()`.\n" + ] + }, + { + "data": { + "text/html": [ + "
" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/plain": [] + }, + "execution_count": 19, + "metadata": {}, + "output_type": "execute_result" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Shout has been called with input Hello\n" + ] + } + ], "source": [ "# Define this variable and then pass js=force_dark_mode when creating the Interface\n", "\n", @@ -236,10 +403,40 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 14, "id": "3cc67b26-dd5f-406d-88f6-2306ee2950c0", "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "* Running on local URL: http://127.0.0.1:7864\n", + "\n", + "To create a public link, set `share=True` in `launch()`.\n" + ] + }, + { + "data": { + "text/html": [ + "
" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/plain": [] + }, + "execution_count": 14, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "# Inputs and Outputs\n", "\n", @@ -254,10 +451,40 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 15, "id": "f235288e-63a2-4341-935b-1441f9be969b", "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "* Running on local URL: http://127.0.0.1:7865\n", + "\n", + "To create a public link, set `share=True` in `launch()`.\n" + ] + }, + { + "data": { + "text/html": [ + "
" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/plain": [] + }, + "execution_count": 15, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "# And now - changing the function from \"shout\" to \"message_gpt\"\n", "\n", @@ -272,10 +499,40 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 20, "id": "af9a3262-e626-4e4b-80b0-aca152405e63", "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "* Running on local URL: http://127.0.0.1:7869\n", + "\n", + "To create a public link, set `share=True` in `launch()`.\n" + ] + }, + { + "data": { + "text/html": [ + "
" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/plain": [] + }, + "execution_count": 20, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "# Let's use Markdown\n", "# Are you wondering why it makes any difference to set system_message when it's not referred to in the code below it?\n", @@ -295,7 +552,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 28, "id": "88c04ebf-0671-4fea-95c9-bc1565d4bb4f", "metadata": {}, "outputs": [], @@ -322,10 +579,40 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 29, "id": "0bb1f789-ff11-4cba-ac67-11b815e29d09", "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "* Running on local URL: http://127.0.0.1:7874\n", + "\n", + "To create a public link, set `share=True` in `launch()`.\n" + ] + }, + { + "data": { + "text/html": [ + "
" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/plain": [] + }, + "execution_count": 29, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "view = gr.Interface(\n", " fn=stream_gpt,\n", @@ -338,7 +625,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 22, "id": "bbc8e930-ba2a-4194-8f7c-044659150626", "metadata": {}, "outputs": [], @@ -362,10 +649,40 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 23, "id": "a0066ffd-196e-4eaf-ad1e-d492958b62af", "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "* Running on local URL: http://127.0.0.1:7871\n", + "\n", + "To create a public link, set `share=True` in `launch()`.\n" + ] + }, + { + "data": { + "text/html": [ + "
" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/plain": [] + }, + "execution_count": 23, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "view = gr.Interface(\n", " fn=stream_claude,\n", @@ -401,7 +718,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 24, "id": "0087623a-4e31-470b-b2e6-d8d16fc7bcf5", "metadata": {}, "outputs": [], @@ -418,14 +735,44 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 30, "id": "8d8ce810-997c-4b6a-bc4f-1fc847ac8855", "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "* Running on local URL: http://127.0.0.1:7875\n", + "\n", + "To create a public link, set `share=True` in `launch()`.\n" + ] + }, + { + "data": { + "text/html": [ + "
" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/plain": [] + }, + "execution_count": 30, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "view = gr.Interface(\n", " fn=stream_model,\n", - " inputs=[gr.Textbox(label=\"Your message:\"), gr.Dropdown([\"GPT\", \"Claude\"], label=\"Select model\", value=\"GPT\")],\n", + " inputs=[gr.Textbox(label=\"Your message:\"), gr.Dropdown([\"GPT\", \"Claude\"], label=\"Select model\", value=\"Claude\")],\n", " outputs=[gr.Markdown(label=\"Response:\")],\n", " flagging_mode=\"never\"\n", ")\n", @@ -464,7 +811,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 31, "id": "1626eb2e-eee8-4183-bda5-1591b58ae3cf", "metadata": {}, "outputs": [], @@ -492,7 +839,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 32, "id": "c701ec17-ecd5-4000-9f68-34634c8ed49d", "metadata": {}, "outputs": [], @@ -505,13 +852,13 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 35, "id": "5def90e0-4343-4f58-9d4a-0e36e445efa4", "metadata": {}, "outputs": [], "source": [ - "def stream_brochure(company_name, url, model):\n", - " prompt = f\"Please generate a company brochure for {company_name}. Here is their landing page:\\n\"\n", + "def stream_brochure(company_name, url, model, tone):\n", + " prompt = f\"Please generate a company brochure for {company_name}. Write the brochure in the following tone: {tone}.Here is their landing page:\\n\"\n", " prompt += Website(url).get_contents()\n", " if model==\"GPT\":\n", " result = stream_gpt(prompt)\n", @@ -524,17 +871,48 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 39, "id": "66399365-5d67-4984-9d47-93ed26c0bd3d", "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "* Running on local URL: http://127.0.0.1:7877\n", + "\n", + "To create a public link, set `share=True` in `launch()`.\n" + ] + }, + { + "data": { + "text/html": [ + "
" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/plain": [] + }, + "execution_count": 39, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "view = gr.Interface(\n", " fn=stream_brochure,\n", " inputs=[\n", " gr.Textbox(label=\"Company name:\"),\n", " gr.Textbox(label=\"Landing page URL including http:// or https://\"),\n", - " gr.Dropdown([\"GPT\", \"Claude\"], label=\"Select model\")],\n", + " gr.Dropdown([\"GPT\", \"Claude\"], label=\"Select model\"),\n", + " gr.Dropdown([\"Formal\", \"Casual\", \"Academic\", \"Funny\", \"Snarky\"], label=\"Select tone\", value=\"Formal\"),],\n", " outputs=[gr.Markdown(label=\"Brochure:\")],\n", " flagging_mode=\"never\"\n", ")\n", From 8e88c446702e46b50c18f5d534a1df03f918ee0b Mon Sep 17 00:00:00 2001 From: Daniel Quillan Roxas <100287361+danielquillanroxas@users.noreply.github.com> Date: Tue, 4 Feb 2025 12:27:59 +0300 Subject: [PATCH 4/5] Delete week2/day2.ipynb --- week2/day2.ipynb | 952 ----------------------------------------------- 1 file changed, 952 deletions(-) delete mode 100644 week2/day2.ipynb diff --git a/week2/day2.ipynb b/week2/day2.ipynb deleted file mode 100644 index 363ca6d..0000000 --- a/week2/day2.ipynb +++ /dev/null @@ -1,952 +0,0 @@ -{ - "cells": [ - { - "cell_type": "markdown", - "id": "8b0e11f2-9ea4-48c2-b8d2-d0a4ba967827", - "metadata": {}, - "source": [ - "# Gradio Day!\n", - "\n", - "Today we will build User Interfaces using the outrageously simple Gradio framework.\n", - "\n", - "Prepare for joy!\n", - "\n", - "Please note: your Gradio screens may appear in 'dark mode' or 'light mode' depending on your computer settings." - ] - }, - { - "cell_type": "code", - "execution_count": 1, - "id": "c44c5494-950d-4d2f-8d4f-b87b57c5b330", - "metadata": {}, - "outputs": [], - "source": [ - "# imports\n", - "\n", - "import os\n", - "import requests\n", - "from bs4 import BeautifulSoup\n", - "from typing import List\n", - "from dotenv import load_dotenv\n", - "from openai import OpenAI\n", - "import google.generativeai\n", - "import anthropic" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "id": "d1715421-cead-400b-99af-986388a97aff", - "metadata": {}, - "outputs": [], - "source": [ - "import gradio as gr # oh yeah!" - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "id": "337d5dfc-0181-4e3b-8ab9-e78e0c3f657b", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "OpenAI API Key exists and begins sk-proj-\n", - "Anthropic API Key exists and begins sk-ant-\n", - "Google API Key exists and begins AIzaSyDY\n" - ] - } - ], - "source": [ - "# Load environment variables in a file called .env\n", - "# Print the key prefixes to help with any debugging\n", - "\n", - "load_dotenv()\n", - "openai_api_key = os.getenv('OPENAI_API_KEY')\n", - "anthropic_api_key = os.getenv('ANTHROPIC_API_KEY')\n", - "google_api_key = os.getenv('GOOGLE_API_KEY')\n", - "\n", - "if openai_api_key:\n", - " print(f\"OpenAI API Key exists and begins {openai_api_key[:8]}\")\n", - "else:\n", - " print(\"OpenAI API Key not set\")\n", - " \n", - "if anthropic_api_key:\n", - " print(f\"Anthropic API Key exists and begins {anthropic_api_key[:7]}\")\n", - "else:\n", - " print(\"Anthropic API Key not set\")\n", - "\n", - "if google_api_key:\n", - " print(f\"Google API Key exists and begins {google_api_key[:8]}\")\n", - "else:\n", - " print(\"Google API Key not set\")" - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "id": "22586021-1795-4929-8079-63f5bb4edd4c", - "metadata": {}, - "outputs": [], - "source": [ - "# Connect to OpenAI, Anthropic and Google; comment out the Claude or Google lines if you're not using them\n", - "\n", - "openai = OpenAI()\n", - "\n", - "claude = anthropic.Anthropic()\n", - "\n", - "google.generativeai.configure()" - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "id": "b16e6021-6dc4-4397-985a-6679d6c8ffd5", - "metadata": {}, - "outputs": [], - "source": [ - "# A generic system message - no more snarky adversarial AIs!\n", - "\n", - "system_message = \"You are a helpful assistant\"" - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "id": "02ef9b69-ef31-427d-86d0-b8c799e1c1b1", - "metadata": {}, - "outputs": [], - "source": [ - "# Let's wrap a call to GPT-4o-mini in a simple function\n", - "\n", - "def message_gpt(prompt):\n", - " messages = [\n", - " {\"role\": \"system\", \"content\": system_message},\n", - " {\"role\": \"user\", \"content\": prompt}\n", - " ]\n", - " completion = openai.chat.completions.create(\n", - " model='gpt-4o-mini',\n", - " messages=messages,\n", - " )\n", - " return completion.choices[0].message.content" - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "id": "aef7d314-2b13-436b-b02d-8de3b72b193f", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "\"Today's date is October 18, 2023.\"" - ] - }, - "execution_count": 7, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "message_gpt(\"What is today's date?\")" - ] - }, - { - "cell_type": "markdown", - "id": "f94013d1-4f27-4329-97e8-8c58db93636a", - "metadata": {}, - "source": [ - "## User Interface time!" - ] - }, - { - "cell_type": "code", - "execution_count": 8, - "id": "bc664b7a-c01d-4fea-a1de-ae22cdd5141a", - "metadata": {}, - "outputs": [], - "source": [ - "# here's a simple function\n", - "\n", - "def shout(text):\n", - " print(f\"Shout has been called with input {text}\")\n", - " return text.upper()" - ] - }, - { - "cell_type": "code", - "execution_count": 9, - "id": "083ea451-d3a0-4d13-b599-93ed49b975e4", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Shout has been called with input hello\n" - ] - }, - { - "data": { - "text/plain": [ - "'HELLO'" - ] - }, - "execution_count": 9, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "shout(\"hello\")" - ] - }, - { - "cell_type": "code", - "execution_count": 10, - "id": "08f1f15a-122e-4502-b112-6ee2817dda32", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "* Running on local URL: http://127.0.0.1:7860\n", - "\n", - "To create a public link, set `share=True` in `launch()`.\n" - ] - }, - { - "data": { - "text/html": [ - "
" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/plain": [] - }, - "execution_count": 10, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "# The simplicty of gradio. This might appear in \"light mode\" - I'll show you how to make this in dark mode later.\n", - "\n", - "gr.Interface(fn=shout, inputs=\"textbox\", outputs=\"textbox\").launch()" - ] - }, - { - "cell_type": "code", - "execution_count": 11, - "id": "c9a359a4-685c-4c99-891c-bb4d1cb7f426", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "* Running on local URL: http://127.0.0.1:7861\n", - "* Running on public URL: https://2de7e99a4de25a4c27.gradio.live\n", - "\n", - "This share link expires in 72 hours. For free permanent hosting and GPU upgrades, run `gradio deploy` from the terminal in the working directory to deploy to Hugging Face Spaces (https://huggingface.co/spaces)\n" - ] - }, - { - "data": { - "text/html": [ - "
" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/plain": [] - }, - "execution_count": 11, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "# Adding share=True means that it can be accessed publically\n", - "# A more permanent hosting is available using a platform called Spaces from HuggingFace, which we will touch on next week\n", - "# NOTE: Some Anti-virus software and Corporate Firewalls might not like you using share=True. If you're at work on on a work network, I suggest skip this test.\n", - "\n", - "gr.Interface(fn=shout, inputs=\"textbox\", outputs=\"textbox\", flagging_mode=\"never\").launch(share=True)" - ] - }, - { - "cell_type": "code", - "execution_count": 12, - "id": "cd87533a-ff3a-4188-8998-5bedd5ba2da3", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "* Running on local URL: http://127.0.0.1:7862\n", - "\n", - "To create a public link, set `share=True` in `launch()`.\n" - ] - }, - { - "data": { - "text/html": [ - "
" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/plain": [] - }, - "execution_count": 12, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "# Adding inbrowser=True opens up a new browser window automatically\n", - "\n", - "gr.Interface(fn=shout, inputs=\"textbox\", outputs=\"textbox\", flagging_mode=\"never\").launch(inbrowser=True)" - ] - }, - { - "cell_type": "markdown", - "id": "b42ec007-0314-48bf-84a4-a65943649215", - "metadata": {}, - "source": [ - "## Forcing dark mode\n", - "\n", - "Gradio appears in light mode or dark mode depending on the settings of the browser and computer. There is a way to force gradio to appear in dark mode, but Gradio recommends against this as it should be a user preference (particularly for accessibility reasons). But if you wish to force dark mode for your screens, below is how to do it." - ] - }, - { - "cell_type": "code", - "execution_count": 19, - "id": "e8129afa-532b-4b15-b93c-aa9cca23a546", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "* Running on local URL: http://127.0.0.1:7868\n", - "\n", - "To create a public link, set `share=True` in `launch()`.\n" - ] - }, - { - "data": { - "text/html": [ - "
" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/plain": [] - }, - "execution_count": 19, - "metadata": {}, - "output_type": "execute_result" - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Shout has been called with input Hello\n" - ] - } - ], - "source": [ - "# Define this variable and then pass js=force_dark_mode when creating the Interface\n", - "\n", - "force_dark_mode = \"\"\"\n", - "function refresh() {\n", - " const url = new URL(window.location);\n", - " if (url.searchParams.get('__theme') !== 'dark') {\n", - " url.searchParams.set('__theme', 'dark');\n", - " window.location.href = url.href;\n", - " }\n", - "}\n", - "\"\"\"\n", - "gr.Interface(fn=shout, inputs=\"textbox\", outputs=\"textbox\", flagging_mode=\"never\", js=force_dark_mode).launch()" - ] - }, - { - "cell_type": "code", - "execution_count": 14, - "id": "3cc67b26-dd5f-406d-88f6-2306ee2950c0", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "* Running on local URL: http://127.0.0.1:7864\n", - "\n", - "To create a public link, set `share=True` in `launch()`.\n" - ] - }, - { - "data": { - "text/html": [ - "
" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/plain": [] - }, - "execution_count": 14, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "# Inputs and Outputs\n", - "\n", - "view = gr.Interface(\n", - " fn=shout,\n", - " inputs=[gr.Textbox(label=\"Your message:\", lines=6)],\n", - " outputs=[gr.Textbox(label=\"Response:\", lines=8)],\n", - " flagging_mode=\"never\"\n", - ")\n", - "view.launch()" - ] - }, - { - "cell_type": "code", - "execution_count": 15, - "id": "f235288e-63a2-4341-935b-1441f9be969b", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "* Running on local URL: http://127.0.0.1:7865\n", - "\n", - "To create a public link, set `share=True` in `launch()`.\n" - ] - }, - { - "data": { - "text/html": [ - "
" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/plain": [] - }, - "execution_count": 15, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "# And now - changing the function from \"shout\" to \"message_gpt\"\n", - "\n", - "view = gr.Interface(\n", - " fn=message_gpt,\n", - " inputs=[gr.Textbox(label=\"Your message:\", lines=6)],\n", - " outputs=[gr.Textbox(label=\"Response:\", lines=8)],\n", - " flagging_mode=\"never\"\n", - ")\n", - "view.launch()" - ] - }, - { - "cell_type": "code", - "execution_count": 20, - "id": "af9a3262-e626-4e4b-80b0-aca152405e63", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "* Running on local URL: http://127.0.0.1:7869\n", - "\n", - "To create a public link, set `share=True` in `launch()`.\n" - ] - }, - { - "data": { - "text/html": [ - "
" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/plain": [] - }, - "execution_count": 20, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "# Let's use Markdown\n", - "# Are you wondering why it makes any difference to set system_message when it's not referred to in the code below it?\n", - "# I'm taking advantage of system_message being a global variable, used back in the message_gpt function (go take a look)\n", - "# Not a great software engineering practice, but quite sommon during Jupyter Lab R&D!\n", - "\n", - "system_message = \"You are a helpful assistant that responds in markdown\"\n", - "\n", - "view = gr.Interface(\n", - " fn=message_gpt,\n", - " inputs=[gr.Textbox(label=\"Your message:\")],\n", - " outputs=[gr.Markdown(label=\"Response:\")],\n", - " flagging_mode=\"never\"\n", - ")\n", - "view.launch()" - ] - }, - { - "cell_type": "code", - "execution_count": 28, - "id": "88c04ebf-0671-4fea-95c9-bc1565d4bb4f", - "metadata": {}, - "outputs": [], - "source": [ - "# Let's create a call that streams back results\n", - "# If you'd like a refresher on Generators (the \"yield\" keyword),\n", - "# Please take a look at the Intermediate Python notebook in week1 folder.\n", - "\n", - "def stream_gpt(prompt):\n", - " messages = [\n", - " {\"role\": \"system\", \"content\": system_message},\n", - " {\"role\": \"user\", \"content\": prompt}\n", - " ]\n", - " stream = openai.chat.completions.create(\n", - " model='gpt-4o-mini',\n", - " messages=messages,\n", - " stream=True\n", - " )\n", - " result = \"\"\n", - " for chunk in stream:\n", - " result += chunk.choices[0].delta.content or \"\"\n", - " yield result" - ] - }, - { - "cell_type": "code", - "execution_count": 29, - "id": "0bb1f789-ff11-4cba-ac67-11b815e29d09", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "* Running on local URL: http://127.0.0.1:7874\n", - "\n", - "To create a public link, set `share=True` in `launch()`.\n" - ] - }, - { - "data": { - "text/html": [ - "
" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/plain": [] - }, - "execution_count": 29, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "view = gr.Interface(\n", - " fn=stream_gpt,\n", - " inputs=[gr.Textbox(label=\"Your message:\")],\n", - " outputs=[gr.Markdown(label=\"Response:\")],\n", - " flagging_mode=\"never\"\n", - ")\n", - "view.launch()" - ] - }, - { - "cell_type": "code", - "execution_count": 22, - "id": "bbc8e930-ba2a-4194-8f7c-044659150626", - "metadata": {}, - "outputs": [], - "source": [ - "def stream_claude(prompt):\n", - " result = claude.messages.stream(\n", - " model=\"claude-3-haiku-20240307\",\n", - " max_tokens=1000,\n", - " temperature=0.7,\n", - " system=system_message,\n", - " messages=[\n", - " {\"role\": \"user\", \"content\": prompt},\n", - " ],\n", - " )\n", - " response = \"\"\n", - " with result as stream:\n", - " for text in stream.text_stream:\n", - " response += text or \"\"\n", - " yield response" - ] - }, - { - "cell_type": "code", - "execution_count": 23, - "id": "a0066ffd-196e-4eaf-ad1e-d492958b62af", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "* Running on local URL: http://127.0.0.1:7871\n", - "\n", - "To create a public link, set `share=True` in `launch()`.\n" - ] - }, - { - "data": { - "text/html": [ - "
" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/plain": [] - }, - "execution_count": 23, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "view = gr.Interface(\n", - " fn=stream_claude,\n", - " inputs=[gr.Textbox(label=\"Your message:\")],\n", - " outputs=[gr.Markdown(label=\"Response:\")],\n", - " flagging_mode=\"never\"\n", - ")\n", - "view.launch()" - ] - }, - { - "cell_type": "markdown", - "id": "bc5a70b9-2afe-4a7c-9bed-2429229e021b", - "metadata": {}, - "source": [ - "## Minor improvement\n", - "\n", - "I've made a small improvement to this code.\n", - "\n", - "Previously, it had these lines:\n", - "\n", - "```\n", - "for chunk in result:\n", - " yield chunk\n", - "```\n", - "\n", - "There's actually a more elegant way to achieve this (which Python people might call more 'Pythonic'):\n", - "\n", - "`yield from result`\n", - "\n", - "I cover this in more detail in the Intermediate Python notebook in the week1 folder - take a look if you'd like more." - ] - }, - { - "cell_type": "code", - "execution_count": 24, - "id": "0087623a-4e31-470b-b2e6-d8d16fc7bcf5", - "metadata": {}, - "outputs": [], - "source": [ - "def stream_model(prompt, model):\n", - " if model==\"GPT\":\n", - " result = stream_gpt(prompt)\n", - " elif model==\"Claude\":\n", - " result = stream_claude(prompt)\n", - " else:\n", - " raise ValueError(\"Unknown model\")\n", - " yield from result" - ] - }, - { - "cell_type": "code", - "execution_count": 30, - "id": "8d8ce810-997c-4b6a-bc4f-1fc847ac8855", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "* Running on local URL: http://127.0.0.1:7875\n", - "\n", - "To create a public link, set `share=True` in `launch()`.\n" - ] - }, - { - "data": { - "text/html": [ - "
" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/plain": [] - }, - "execution_count": 30, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "view = gr.Interface(\n", - " fn=stream_model,\n", - " inputs=[gr.Textbox(label=\"Your message:\"), gr.Dropdown([\"GPT\", \"Claude\"], label=\"Select model\", value=\"Claude\")],\n", - " outputs=[gr.Markdown(label=\"Response:\")],\n", - " flagging_mode=\"never\"\n", - ")\n", - "view.launch()" - ] - }, - { - "cell_type": "markdown", - "id": "d933865b-654c-4b92-aa45-cf389f1eda3d", - "metadata": {}, - "source": [ - "# Building a company brochure generator\n", - "\n", - "Now you know how - it's simple!" - ] - }, - { - "cell_type": "markdown", - "id": "92d7c49b-2e0e-45b3-92ce-93ca9f962ef4", - "metadata": {}, - "source": [ - "\n", - " \n", - " \n", - " \n", - " \n", - "
\n", - " \n", - " \n", - "

Before you read the next few cells

\n", - " \n", - " Try to do this yourself - go back to the company brochure in week1, day5 and add a Gradio UI to the end. Then come and look at the solution.\n", - " \n", - "
" - ] - }, - { - "cell_type": "code", - "execution_count": 31, - "id": "1626eb2e-eee8-4183-bda5-1591b58ae3cf", - "metadata": {}, - "outputs": [], - "source": [ - "# A class to represent a Webpage\n", - "\n", - "class Website:\n", - " url: str\n", - " title: str\n", - " text: str\n", - "\n", - " def __init__(self, url):\n", - " self.url = url\n", - " response = requests.get(url)\n", - " self.body = response.content\n", - " soup = BeautifulSoup(self.body, 'html.parser')\n", - " self.title = soup.title.string if soup.title else \"No title found\"\n", - " for irrelevant in soup.body([\"script\", \"style\", \"img\", \"input\"]):\n", - " irrelevant.decompose()\n", - " self.text = soup.body.get_text(separator=\"\\n\", strip=True)\n", - "\n", - " def get_contents(self):\n", - " return f\"Webpage Title:\\n{self.title}\\nWebpage Contents:\\n{self.text}\\n\\n\"" - ] - }, - { - "cell_type": "code", - "execution_count": 32, - "id": "c701ec17-ecd5-4000-9f68-34634c8ed49d", - "metadata": {}, - "outputs": [], - "source": [ - "# With massive thanks to Bill G. who noticed that a prior version of this had a bug! Now fixed.\n", - "\n", - "system_message = \"You are an assistant that analyzes the contents of a company website landing page \\\n", - "and creates a short brochure about the company for prospective customers, investors and recruits. Respond in markdown.\"" - ] - }, - { - "cell_type": "code", - "execution_count": 35, - "id": "5def90e0-4343-4f58-9d4a-0e36e445efa4", - "metadata": {}, - "outputs": [], - "source": [ - "def stream_brochure(company_name, url, model, tone):\n", - " prompt = f\"Please generate a company brochure for {company_name}. Write the brochure in the following tone: {tone}.Here is their landing page:\\n\"\n", - " prompt += Website(url).get_contents()\n", - " if model==\"GPT\":\n", - " result = stream_gpt(prompt)\n", - " elif model==\"Claude\":\n", - " result = stream_claude(prompt)\n", - " else:\n", - " raise ValueError(\"Unknown model\")\n", - " yield from result" - ] - }, - { - "cell_type": "code", - "execution_count": 39, - "id": "66399365-5d67-4984-9d47-93ed26c0bd3d", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "* Running on local URL: http://127.0.0.1:7877\n", - "\n", - "To create a public link, set `share=True` in `launch()`.\n" - ] - }, - { - "data": { - "text/html": [ - "
" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/plain": [] - }, - "execution_count": 39, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "view = gr.Interface(\n", - " fn=stream_brochure,\n", - " inputs=[\n", - " gr.Textbox(label=\"Company name:\"),\n", - " gr.Textbox(label=\"Landing page URL including http:// or https://\"),\n", - " gr.Dropdown([\"GPT\", \"Claude\"], label=\"Select model\"),\n", - " gr.Dropdown([\"Formal\", \"Casual\", \"Academic\", \"Funny\", \"Snarky\"], label=\"Select tone\", value=\"Formal\"),],\n", - " outputs=[gr.Markdown(label=\"Brochure:\")],\n", - " flagging_mode=\"never\"\n", - ")\n", - "view.launch()" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "ede97ca3-a0f8-4f6e-be17-d1de7fef9cc0", - "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": "3.11.11" - } - }, - "nbformat": 4, - "nbformat_minor": 5 -} From 3a98dd63d1bec9043bd1c9889cd4144a124cf908 Mon Sep 17 00:00:00 2001 From: Daniel Quillan Roxas <100287361+danielquillanroxas@users.noreply.github.com> Date: Tue, 4 Feb 2025 12:28:17 +0300 Subject: [PATCH 5/5] Delete week2/day1.ipynb --- week2/day1.ipynb | 819 ----------------------------------------------- 1 file changed, 819 deletions(-) delete mode 100644 week2/day1.ipynb diff --git a/week2/day1.ipynb b/week2/day1.ipynb deleted file mode 100644 index a3f20df..0000000 --- a/week2/day1.ipynb +++ /dev/null @@ -1,819 +0,0 @@ -{ - "cells": [ - { - "cell_type": "markdown", - "id": "06cf3063-9f3e-4551-a0d5-f08d9cabb927", - "metadata": {}, - "source": [ - "# Welcome to Week 2!\n", - "\n", - "## Frontier Model APIs\n", - "\n", - "In Week 1, we used multiple Frontier LLMs through their Chat UI, and we connected with the OpenAI's API.\n", - "\n", - "Today we'll connect with the APIs for Anthropic and Google, as well as OpenAI." - ] - }, - { - "cell_type": "markdown", - "id": "2b268b6e-0ba4-461e-af86-74a41f4d681f", - "metadata": {}, - "source": [ - "\n", - " \n", - " \n", - " \n", - " \n", - "
\n", - " \n", - " \n", - "

Important Note - Please read me

\n", - " I'm continually improving these labs, adding more examples and exercises.\n", - " At the start of each week, it's worth checking you have the latest code.
\n", - " First do a git pull and merge your changes as needed. Any problems? Try asking ChatGPT to clarify how to merge - or contact me!

\n", - " After you've pulled the code, from the llm_engineering directory, in an Anaconda prompt (PC) or Terminal (Mac), run:
\n", - " conda env update --f environment.yml
\n", - " Or if you used virtualenv rather than Anaconda, then run this from your activated environment in a Powershell (PC) or Terminal (Mac):
\n", - " pip install -r requirements.txt\n", - "
Then restart the kernel (Kernel menu >> Restart Kernel and Clear Outputs Of All Cells) to pick up the changes.\n", - "
\n", - "
\n", - "\n", - " \n", - " \n", - " \n", - " \n", - "
\n", - " \n", - " \n", - "

Reminder about the resources page

\n", - " Here's a link to resources for the course. This includes links to all the slides.
\n", - " https://edwarddonner.com/2024/11/13/llm-engineering-resources/
\n", - " Please keep this bookmarked, and I'll continue to add more useful links there over time.\n", - "
\n", - "
" - ] - }, - { - "cell_type": "markdown", - "id": "85cfe275-4705-4d30-abea-643fbddf1db0", - "metadata": {}, - "source": [ - "## Setting up your keys\n", - "\n", - "If you haven't done so already, you could now create API keys for Anthropic and Google in addition to OpenAI.\n", - "\n", - "**Please note:** if you'd prefer to avoid extra API costs, feel free to skip setting up Anthopic and Google! You can see me do it, and focus on OpenAI for the course. You could also substitute Anthropic and/or Google for Ollama, using the exercise you did in week 1.\n", - "\n", - "For OpenAI, visit https://openai.com/api/ \n", - "For Anthropic, visit https://console.anthropic.com/ \n", - "For Google, visit https://ai.google.dev/gemini-api \n", - "\n", - "### Also - adding DeepSeek if you wish\n", - "\n", - "Optionally, if you'd like to also use DeepSeek, create an account [here](https://platform.deepseek.com/), create a key [here](https://platform.deepseek.com/api_keys) and top up with at least the minimum $2 [here](https://platform.deepseek.com/top_up).\n", - "\n", - "### Adding API keys to your .env file\n", - "\n", - "When you get your API keys, you need to set them as environment variables by adding them to your `.env` file.\n", - "\n", - "```\n", - "OPENAI_API_KEY=xxxx\n", - "ANTHROPIC_API_KEY=xxxx\n", - "GOOGLE_API_KEY=xxxx\n", - "DEEPSEEK_API_KEY=xxxx\n", - "```\n", - "\n", - "Afterwards, you may need to restart the Jupyter Lab Kernel (the Python process that sits behind this notebook) via the Kernel menu, and then rerun the cells from the top." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "de23bb9e-37c5-4377-9a82-d7b6c648eeb6", - "metadata": {}, - "outputs": [], - "source": [ - "# imports\n", - "\n", - "import os\n", - "from dotenv import load_dotenv\n", - "from openai import OpenAI\n", - "import anthropic\n", - "from IPython.display import Markdown, display, update_display" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "f0a8ab2b-6134-4104-a1bc-c3cd7ea4cd36", - "metadata": {}, - "outputs": [], - "source": [ - "# import for google\n", - "# in rare cases, this seems to give an error on some systems, or even crashes the kernel\n", - "# If this happens to you, simply ignore this cell - I give an alternative approach for using Gemini later\n", - "\n", - "import google.generativeai" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "1179b4c5-cd1f-4131-a876-4c9f3f38d2ba", - "metadata": {}, - "outputs": [], - "source": [ - "# Load environment variables in a file called .env\n", - "# Print the key prefixes to help with any debugging\n", - "\n", - "load_dotenv(override=True)\n", - "openai_api_key = os.getenv('OPENAI_API_KEY')\n", - "anthropic_api_key = os.getenv('ANTHROPIC_API_KEY')\n", - "google_api_key = os.getenv('GOOGLE_API_KEY')\n", - "\n", - "if openai_api_key:\n", - " print(f\"OpenAI API Key exists and begins {openai_api_key[:8]}\")\n", - "else:\n", - " print(\"OpenAI API Key not set\")\n", - " \n", - "if anthropic_api_key:\n", - " print(f\"Anthropic API Key exists and begins {anthropic_api_key[:7]}\")\n", - "else:\n", - " print(\"Anthropic API Key not set\")\n", - "\n", - "if google_api_key:\n", - " print(f\"Google API Key exists and begins {google_api_key[:8]}\")\n", - "else:\n", - " print(\"Google API Key not set\")" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "797fe7b0-ad43-42d2-acf0-e4f309b112f0", - "metadata": {}, - "outputs": [], - "source": [ - "# Connect to OpenAI, Anthropic\n", - "\n", - "openai = OpenAI()\n", - "\n", - "claude = anthropic.Anthropic()" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "425ed580-808d-429b-85b0-6cba50ca1d0c", - "metadata": {}, - "outputs": [], - "source": [ - "# This is the set up code for Gemini\n", - "# Having problems with Google Gemini setup? Then just ignore this cell; when we use Gemini, I'll give you an alternative that bypasses this library altogether\n", - "\n", - "google.generativeai.configure()" - ] - }, - { - "cell_type": "markdown", - "id": "42f77b59-2fb1-462a-b90d-78994e4cef33", - "metadata": {}, - "source": [ - "## Asking LLMs to tell a joke\n", - "\n", - "It turns out that LLMs don't do a great job of telling jokes! Let's compare a few models.\n", - "Later we will be putting LLMs to better use!\n", - "\n", - "### What information is included in the API\n", - "\n", - "Typically we'll pass to the API:\n", - "- The name of the model that should be used\n", - "- A system message that gives overall context for the role the LLM is playing\n", - "- A user message that provides the actual prompt\n", - "\n", - "There are other parameters that can be used, including **temperature** which is typically between 0 and 1; higher for more random output; lower for more focused and deterministic." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "378a0296-59a2-45c6-82eb-941344d3eeff", - "metadata": {}, - "outputs": [], - "source": [ - "system_message = \"You are an assistant that is great at telling jokes\"\n", - "user_prompt = \"Tell a light-hearted joke for an audience of Data Scientists\"" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "f4d56a0f-2a3d-484d-9344-0efa6862aff4", - "metadata": {}, - "outputs": [], - "source": [ - "prompts = [\n", - " {\"role\": \"system\", \"content\": system_message},\n", - " {\"role\": \"user\", \"content\": user_prompt}\n", - " ]" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "3b3879b6-9a55-4fed-a18c-1ea2edfaf397", - "metadata": {}, - "outputs": [], - "source": [ - "# GPT-3.5-Turbo\n", - "\n", - "completion = openai.chat.completions.create(model='gpt-3.5-turbo', messages=prompts)\n", - "print(completion.choices[0].message.content)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "3d2d6beb-1b81-466f-8ed1-40bf51e7adbf", - "metadata": {}, - "outputs": [], - "source": [ - "# GPT-4o-mini\n", - "# Temperature setting controls creativity\n", - "\n", - "completion = openai.chat.completions.create(\n", - " model='gpt-4o-mini',\n", - " messages=prompts,\n", - " temperature=0.7\n", - ")\n", - "print(completion.choices[0].message.content)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "f1f54beb-823f-4301-98cb-8b9a49f4ce26", - "metadata": {}, - "outputs": [], - "source": [ - "# GPT-4o\n", - "\n", - "completion = openai.chat.completions.create(\n", - " model='gpt-4o',\n", - " messages=prompts,\n", - " temperature=0.4\n", - ")\n", - "print(completion.choices[0].message.content)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "1ecdb506-9f7c-4539-abae-0e78d7f31b76", - "metadata": {}, - "outputs": [], - "source": [ - "# Claude 3.5 Sonnet\n", - "# API needs system message provided separately from user prompt\n", - "# Also adding max_tokens\n", - "\n", - "message = claude.messages.create(\n", - " model=\"claude-3-5-sonnet-latest\",\n", - " max_tokens=200,\n", - " temperature=0.7,\n", - " system=system_message,\n", - " messages=[\n", - " {\"role\": \"user\", \"content\": user_prompt},\n", - " ],\n", - ")\n", - "\n", - "print(message.content[0].text)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "769c4017-4b3b-4e64-8da7-ef4dcbe3fd9f", - "metadata": {}, - "outputs": [], - "source": [ - "# Claude 3.5 Sonnet again\n", - "# Now let's add in streaming back results\n", - "\n", - "result = claude.messages.stream(\n", - " model=\"claude-3-5-sonnet-latest\",\n", - " max_tokens=200,\n", - " temperature=0.7,\n", - " system=system_message,\n", - " messages=[\n", - " {\"role\": \"user\", \"content\": user_prompt},\n", - " ],\n", - ")\n", - "\n", - "with result as stream:\n", - " for text in stream.text_stream:\n", - " print(text, end=\"\", flush=True)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "6df48ce5-70f8-4643-9a50-b0b5bfdb66ad", - "metadata": {}, - "outputs": [], - "source": [ - "# The API for Gemini has a slightly different structure.\n", - "# I've heard that on some PCs, this Gemini code causes the Kernel to crash.\n", - "# If that happens to you, please skip this cell and use the next cell instead - an alternative approach.\n", - "\n", - "gemini = google.generativeai.GenerativeModel(\n", - " model_name='gemini-2.0-flash-exp',\n", - " system_instruction=system_message\n", - ")\n", - "response = gemini.generate_content(user_prompt)\n", - "print(response.text)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "49009a30-037d-41c8-b874-127f61c4aa3a", - "metadata": {}, - "outputs": [], - "source": [ - "# As an alternative way to use Gemini that bypasses Google's python API library,\n", - "# Google has recently released new endpoints that means you can use Gemini via the client libraries for OpenAI!\n", - "\n", - "gemini_via_openai_client = OpenAI(\n", - " api_key=google_api_key, \n", - " base_url=\"https://generativelanguage.googleapis.com/v1beta/openai/\"\n", - ")\n", - "\n", - "response = gemini_via_openai_client.chat.completions.create(\n", - " model=\"gemini-2.0-flash-exp\",\n", - " messages=prompts\n", - ")\n", - "print(response.choices[0].message.content)" - ] - }, - { - "cell_type": "markdown", - "id": "33f70c88-7ca9-470b-ad55-d93a57dcc0ab", - "metadata": {}, - "source": [ - "## (Optional) Trying out the DeepSeek model\n", - "\n", - "### Let's ask DeepSeek a really hard question - both the Chat and the Reasoner model" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "3d0019fb-f6a8-45cb-962b-ef8bf7070d4d", - "metadata": {}, - "outputs": [], - "source": [ - "# Optionally if you wish to try DeekSeek, you can also use the OpenAI client library\n", - "\n", - "deepseek_api_key = os.getenv('DEEPSEEK_API_KEY')\n", - "\n", - "if deepseek_api_key:\n", - " print(f\"DeepSeek API Key exists and begins {deepseek_api_key[:3]}\")\n", - "else:\n", - " print(\"DeepSeek API Key not set - please skip to the next section if you don't wish to try the DeepSeek API\")" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "c72c871e-68d6-4668-9c27-96d52b77b867", - "metadata": {}, - "outputs": [], - "source": [ - "# Using DeepSeek Chat\n", - "\n", - "deepseek_via_openai_client = OpenAI(\n", - " api_key=deepseek_api_key, \n", - " base_url=\"https://api.deepseek.com\"\n", - ")\n", - "\n", - "response = deepseek_via_openai_client.chat.completions.create(\n", - " model=\"deepseek-chat\",\n", - " messages=prompts,\n", - ")\n", - "\n", - "print(response.choices[0].message.content)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "50b6e70f-700a-46cf-942f-659101ffeceb", - "metadata": {}, - "outputs": [], - "source": [ - "challenge = [{\"role\": \"system\", \"content\": \"You are a helpful assistant\"},\n", - " {\"role\": \"user\", \"content\": \"How many words are there in your answer to this prompt\"}]" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "66d1151c-2015-4e37-80c8-16bc16367cfe", - "metadata": {}, - "outputs": [], - "source": [ - "# Using DeepSeek Chat with a harder question! And streaming results\n", - "\n", - "stream = deepseek_via_openai_client.chat.completions.create(\n", - " model=\"deepseek-chat\",\n", - " messages=challenge,\n", - " stream=True\n", - ")\n", - "\n", - "reply = \"\"\n", - "display_handle = display(Markdown(\"\"), display_id=True)\n", - "for chunk in stream:\n", - " reply += chunk.choices[0].delta.content or ''\n", - " reply = reply.replace(\"```\",\"\").replace(\"markdown\",\"\")\n", - " update_display(Markdown(reply), display_id=display_handle.display_id)\n", - "\n", - "print(\"Number of words:\", len(reply.split(\" \")))" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "43a93f7d-9300-48cc-8c1a-ee67380db495", - "metadata": {}, - "outputs": [], - "source": [ - "# Using DeepSeek Reasoner - this may hit an error if DeepSeek is busy\n", - "# It's over-subscribed (as of 28-Jan-2025) but should come back online soon!\n", - "# If this fails, come back to this in a few days..\n", - "\n", - "response = deepseek_via_openai_client.chat.completions.create(\n", - " model=\"deepseek-reasoner\",\n", - " messages=challenge\n", - ")\n", - "\n", - "reasoning_content = response.choices[0].message.reasoning_content\n", - "content = response.choices[0].message.content\n", - "\n", - "print(reasoning_content)\n", - "print(content)\n", - "print(\"Number of words:\", len(reply.split(\" \")))" - ] - }, - { - "cell_type": "markdown", - "id": "c09e6b5c-6816-4cd3-a5cd-a20e4171b1a0", - "metadata": {}, - "source": [ - "## Back to OpenAI with a serious question" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "83ddb483-4f57-4668-aeea-2aade3a9e573", - "metadata": {}, - "outputs": [], - "source": [ - "# To be serious! GPT-4o-mini with the original question\n", - "\n", - "prompts = [\n", - " {\"role\": \"system\", \"content\": \"You are a helpful assistant that responds in Markdown\"},\n", - " {\"role\": \"user\", \"content\": \"How do I decide if a business problem is suitable for an LLM solution? Please respond in Markdown.\"}\n", - " ]" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "749f50ab-8ccd-4502-a521-895c3f0808a2", - "metadata": {}, - "outputs": [], - "source": [ - "# Have it stream back results in markdown\n", - "\n", - "stream = openai.chat.completions.create(\n", - " model='gpt-4o',\n", - " messages=prompts,\n", - " temperature=0.2,\n", - " stream=True\n", - ")\n", - "\n", - "reply = \"\"\n", - "display_handle = display(Markdown(\"\"), display_id=True)\n", - "for chunk in stream:\n", - " reply += chunk.choices[0].delta.content or ''\n", - " reply = reply.replace(\"```\",\"\").replace(\"markdown\",\"\")\n", - " update_display(Markdown(reply), display_id=display_handle.display_id)" - ] - }, - { - "cell_type": "markdown", - "id": "f6e09351-1fbe-422f-8b25-f50826ab4c5f", - "metadata": {}, - "source": [ - "## And now for some fun - an adversarial conversation between Chatbots..\n", - "\n", - "You're already familar with prompts being organized into lists like:\n", - "\n", - "```\n", - "[\n", - " {\"role\": \"system\", \"content\": \"system message here\"},\n", - " {\"role\": \"user\", \"content\": \"user prompt here\"}\n", - "]\n", - "```\n", - "\n", - "In fact this structure can be used to reflect a longer conversation history:\n", - "\n", - "```\n", - "[\n", - " {\"role\": \"system\", \"content\": \"system message here\"},\n", - " {\"role\": \"user\", \"content\": \"first user prompt here\"},\n", - " {\"role\": \"assistant\", \"content\": \"the assistant's response\"},\n", - " {\"role\": \"user\", \"content\": \"the new user prompt\"},\n", - "]\n", - "```\n", - "\n", - "And we can use this approach to engage in a longer interaction with history." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "bcb54183-45d3-4d08-b5b6-55e380dfdf1b", - "metadata": {}, - "outputs": [], - "source": [ - "# Let's make a conversation between GPT-4o-mini and Claude-3-haiku\n", - "# We're using cheap versions of models so the costs will be minimal\n", - "\n", - "gpt_model = \"gpt-4o-mini\"\n", - "claude_model = \"claude-3-haiku-20240307\"\n", - "\n", - "gpt_system = \"You are a chatbot who is very argumentative; \\\n", - "you disagree with anything in the conversation and you challenge everything, in a snarky way.\"\n", - "\n", - "claude_system = \"You are a very polite, courteous chatbot. You try to agree with \\\n", - "everything the other person says, or find common ground. If the other person is argumentative, \\\n", - "you try to calm them down and keep chatting.\"\n", - "\n", - "gpt_messages = [\"Hi there\"]\n", - "claude_messages = [\"Hi\"]" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "1df47dc7-b445-4852-b21b-59f0e6c2030f", - "metadata": {}, - "outputs": [], - "source": [ - "def call_gpt():\n", - " messages = [{\"role\": \"system\", \"content\": gpt_system}]\n", - " for gpt, claude, llama in zip(gpt_messages, claude_messages, llama_messages):\n", - " messages.append({\"role\": \"assistant\", \"content\": gpt})\n", - " combined = llama + claude\n", - " messages.append({\"role\": \"user\", \"content\": combined})\n", - " completion = openai.chat.completions.create(\n", - " model=gpt_model,\n", - " messages=messages\n", - " )\n", - " return completion.choices[0].message.content" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "9dc6e913-02be-4eb6-9581-ad4b2cffa606", - "metadata": {}, - "outputs": [], - "source": [ - "call_gpt()" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "7d2ed227-48c9-4cad-b146-2c4ecbac9690", - "metadata": {}, - "outputs": [], - "source": [ - "def call_claude():\n", - " messages = []\n", - " for gpt, claude_message in zip(gpt_messages, claude_messages):\n", - " messages.append({\"role\": \"user\", \"content\": gpt})\n", - " messages.append({\"role\": \"assistant\", \"content\": claude_message})\n", - " # messages.append(\"role\": \"moderator\", \"content\": llama_message)\n", - " messages.append({\"role\": \"user\", \"content\": gpt_messages[-1]})\n", - " message = claude.messages.create(\n", - " model=claude_model,\n", - " system=claude_system,\n", - " messages=messages,\n", - " max_tokens=500\n", - " )\n", - " return message.content[0].text" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "01395200-8ae9-41f8-9a04-701624d3fd26", - "metadata": {}, - "outputs": [], - "source": [ - "call_claude()" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "08c2279e-62b0-4671-9590-c82eb8d1e1ae", - "metadata": {}, - "outputs": [], - "source": [ - "call_gpt()" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "0275b97f-7f90-4696-bbf5-b6642bd53cbd", - "metadata": {}, - "outputs": [], - "source": [ - "gpt_messages = [\"Hi there\"]\n", - "claude_messages = [\"Hi\"]\n", - "\n", - "print(f\"GPT:\\n{gpt_messages[0]}\\n\")\n", - "print(f\"Claude:\\n{claude_messages[0]}\\n\")\n", - "\n", - "for i in range(5):\n", - " gpt_next = call_gpt()\n", - " print(f\"GPT:\\n{gpt_next}\\n\")\n", - " gpt_messages.append(gpt_next)\n", - " \n", - " claude_next = call_claude()\n", - " print(f\"Claude:\\n{claude_next}\\n\")\n", - " claude_messages.append(claude_next)" - ] - }, - { - "cell_type": "markdown", - "id": "1d10e705-db48-4290-9dc8-9efdb4e31323", - "metadata": {}, - "source": [ - "\n", - " \n", - " \n", - " \n", - " \n", - "
\n", - " \n", - " \n", - "

Before you continue

\n", - " \n", - " Be sure you understand how the conversation above is working, and in particular how the messages list is being populated. Add print statements as needed. Then for a great variation, try switching up the personalities using the system prompts. Perhaps one can be pessimistic, and one optimistic?
\n", - "
\n", - "
" - ] - }, - { - "cell_type": "markdown", - "id": "3637910d-2c6f-4f19-b1fb-2f916d23f9ac", - "metadata": {}, - "source": [ - "# More advanced exercises\n", - "\n", - "Try creating a 3-way, perhaps bringing Gemini into the conversation! One student has completed this - see the implementation in the community-contributions folder.\n", - "\n", - "Try doing this yourself before you look at the solutions. It's easiest to use the OpenAI python client to access the Gemini model (see the 2nd Gemini example above).\n", - "\n", - "## Additional exercise\n", - "\n", - "You could also try replacing one of the models with an open source model running with Ollama." - ] - }, - { - "cell_type": "markdown", - "id": "446c81e3-b67e-4cd9-8113-bc3092b93063", - "metadata": {}, - "source": [ - "\n", - " \n", - " \n", - " \n", - " \n", - "
\n", - " \n", - " \n", - "

Business relevance

\n", - " This structure of a conversation, as a list of messages, is fundamental to the way we build conversational AI assistants and how they are able to keep the context during a conversation. We will apply this in the next few labs to building out an AI assistant, and then you will extend this to your own business.\n", - "
" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "c23224f6-7008-44ed-a57f-718975f4e291", - "metadata": {}, - "outputs": [], - "source": [ - "!ollama pull llama3.2" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "cbbddf71-1473-42fe-b733-2bb42ea77333", - "metadata": {}, - "outputs": [], - "source": [ - "\n", - "OLLAMA_API = \"http://localhost:11434/api/chat\"\n", - "HEADERS = {\"Content-Type\": \"application/json\"}\n", - "import ollama\n", - "\n", - "llama_model = \"llama3.2\"\n", - "\n", - "llama_system = \"You are a chatbot who is very pacifist; \\\n", - "you will try to resolve or neutralize any disagreement between other chatbots. Speak like a teacher or someone in authority.\"\n", - "\n", - "llama_messages = [\"Hello.\"]\n" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "f629d2b2-ba20-4bfe-a2e5-bbe537ca46a2", - "metadata": {}, - "outputs": [], - "source": [ - "\n", - "def call_llama():\n", - " combined_messages = gpt_messages[-1] + claude_messages[-1]\n", - " messages = [{\"role\": \"system\", \"content\": llama_system}]\n", - " for comb, llama in zip(combined_messages, llama_messages):\n", - " messages.append({\"role\": \"assistant\", \"content\": llama})\n", - " messages.append({\"role\": \"user\", \"content\": combined_messages})\n", - " completion = ollama.chat(\n", - " model=llama_model,\n", - " messages=messages\n", - " )\n", - " return completion['message']['content']" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "219b6af8-3166-4059-b79e-cf19af7ed1e9", - "metadata": {}, - "outputs": [], - "source": [ - "print(f\"GPT:\\n{gpt_messages[0]}\\n\")\n", - "print(f\"Claude:\\n{claude_messages[0]}\\n\")\n", - "print(f\"Llama:\\n{llama_messages[0]}\\n\" )\n", - "\n", - "for i in range(3):\n", - " gpt_next = call_gpt()\n", - " print(f\"GPT:\\n{gpt_next}\\n\")\n", - " gpt_messages.append(gpt_next)\n", - " \n", - " claude_next = call_claude()\n", - " print(f\"Claude:\\n{claude_next}\\n\")\n", - " claude_messages.append(claude_next)\n", - "\n", - " llama_next = call_llama()\n", - " print(f\"Llama:\\n{llama_next}\\n\")\n", - " llama_messages.append(llama_next)\n", - " " - ] - } - ], - "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": "3.11.11" - } - }, - "nbformat": 4, - "nbformat_minor": 5 -}