diff --git a/community-contributions/pradeep1955/week1 EXERCISE.ipynb b/community-contributions/pradeep1955/week1 EXERCISE.ipynb new file mode 100644 index 0000000..5c418f2 --- /dev/null +++ b/community-contributions/pradeep1955/week1 EXERCISE.ipynb @@ -0,0 +1,148 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "id": "fe12c203-e6a6-452c-a655-afb8a03a4ff5", + "metadata": {}, + "source": [ + "# End of week 1 exercise\n", + "\n", + "To demonstrate your familiarity with OpenAI API, and also Ollama, build a tool that takes a technical question, \n", + "and responds with an explanation. This is a tool that you will be able to use yourself during the course!" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "c1070317-3ed9-4659-abe3-828943230e03", + "metadata": {}, + "outputs": [], + "source": [ + "# imports\n", + "import os\n", + "from openai import OpenAI\n", + "from IPython.display import Markdown, display, update_display\n", + "from dotenv import load_dotenv" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "4a456906-915a-4bfd-bb9d-57e505c5093f", + "metadata": {}, + "outputs": [], + "source": [ + "# constants\n", + "\n", + "MODEL_GPT = 'gpt-4o-mini'\n", + "MODEL_LLAMA = 'llama3.2'" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "a8d7923c-5f28-4c30-8556-342d7c8497c1", + "metadata": {}, + "outputs": [], + "source": [ + "# set up environment\n", + "load_dotenv(override=True)\n", + "api_key=os.getenv(\"OPENAI_API_KEY\")\n", + "if not api_key.startswith(\"sk-proj-\") and len(api_key)<10:\n", + " print(\"api key not foud\")\n", + "else:\n", + " print(\"api found and is ok\")\n", + "\n", + "openai=OpenAI()\n", + "print()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "3f0d0137-52b0-47a8-81a8-11a90a010798", + "metadata": {}, + "outputs": [], + "source": [ + "# here is the question; type over this to ask something new\n", + "\n", + "question = \"\"\"\n", + "Please explain what this code does and why:\n", + "yield from {book.get(\"author\") for book in books if book.get(\"author\")}\n", + "\"\"\"" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "60ce7000-a4a5-4cce-a261-e75ef45063b4", + "metadata": {}, + "outputs": [], + "source": [ + "# Get gpt-4o-mini to answer, with streaming\n", + "messages = [{\"role\":\"system\",\"content\":\"You are a expert Dta Scientist\"}, {\"role\":\"user\",\"content\":question}]\n", + "\n", + "stream = openai.chat.completions.create(\n", + " model = MODEL_GPT,\n", + " messages = messages,\n", + " stream = True\n", + ")\n", + "response = \"\"\n", + "display_handle = display(Markdown(\"\"), display_id=True)\n", + "for chunk in stream:\n", + " response += chunk.choices[0].delta.content or ''\n", + " response = response.replace(\"```\",\"\").replace(\"markdown\", \"\")\n", + " update_display(Markdown(response), display_id=display_handle.display_id)\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "8f7c8ea8-4082-4ad0-8751-3301adcf6538", + "metadata": {}, + "outputs": [], + "source": [ + "# Get Llama 3.2 to answer\n", + "import ollama\n", + "\n", + "stream = ollama.chat(model=MODEL_LLAMA, messages=messages, stream=True)\n", + "response = \"\"\n", + "display_handle = display(Markdown(\"\"), display_id=True)\n", + "for chunk in stream:\n", + " response += chunk[\"message\"][\"content\"] or ''\n", + " response = response.replace(\"```\",\"\").replace(\"markdown\", \"\")\n", + " update_display(Markdown(response), display_id=display_handle.display_id)\n", + "\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "2a573174-779b-4d50-8792-fa0889b37211", + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "llmenv", + "language": "python", + "name": "llmenv" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.11.13" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/community-contributions/pradeep1955/week1/day2 EXERCISE.ipynb b/community-contributions/pradeep1955/week1/day2 EXERCISE.ipynb new file mode 100644 index 0000000..d7a3078 --- /dev/null +++ b/community-contributions/pradeep1955/week1/day2 EXERCISE.ipynb @@ -0,0 +1,426 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "id": "d15d8294-3328-4e07-ad16-8a03e9bbfdb9", + "metadata": {}, + "source": [ + "# Welcome to your first assignment!\n", + "\n", + "Instructions are below. Please give this a try, and look in the solutions folder if you get stuck (or feel free to ask me!)" + ] + }, + { + "cell_type": "markdown", + "id": "ada885d9-4d42-4d9b-97f0-74fbbbfe93a9", + "metadata": {}, + "source": [ + "\n", + " \n", + " \n", + " \n", + " \n", + "
\n", + " \n", + " \n", + "

Just before we get to the assignment --

\n", + " I thought I'd take a second to point you at this page of useful 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": "6e9fa1fc-eac5-4d1d-9be4-541b3f2b3458", + "metadata": {}, + "source": [ + "# HOMEWORK EXERCISE ASSIGNMENT\n", + "\n", + "Upgrade the day 1 project to summarize a webpage to use an Open Source model running locally via Ollama rather than OpenAI\n", + "\n", + "You'll be able to use this technique for all subsequent projects if you'd prefer not to use paid APIs.\n", + "\n", + "**Benefits:**\n", + "1. No API charges - open-source\n", + "2. Data doesn't leave your box\n", + "\n", + "**Disadvantages:**\n", + "1. Significantly less power than Frontier Model\n", + "\n", + "## Recap on installation of Ollama\n", + "\n", + "Simply visit [ollama.com](https://ollama.com) and install!\n", + "\n", + "Once complete, the ollama server should already be running locally. \n", + "If you visit: \n", + "[http://localhost:11434/](http://localhost:11434/)\n", + "\n", + "You should see the message `Ollama is running`. \n", + "\n", + "If not, bring up a new Terminal (Mac) or Powershell (Windows) and enter `ollama serve` \n", + "And in another Terminal (Mac) or Powershell (Windows), enter `ollama pull llama3.2` \n", + "Then try [http://localhost:11434/](http://localhost:11434/) again.\n", + "\n", + "If Ollama is slow on your machine, try using `llama3.2:1b` as an alternative. Run `ollama pull llama3.2:1b` from a Terminal or Powershell, and change the code below from `MODEL = \"llama3.2\"` to `MODEL = \"llama3.2:1b\"`" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "4e2a9393-7767-488e-a8bf-27c12dca35bd", + "metadata": {}, + "outputs": [], + "source": [ + "# imports\n", + "\n", + "import requests\n", + "from bs4 import BeautifulSoup\n", + "from IPython.display import Markdown, display" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "29ddd15d-a3c5-4f4e-a678-873f56162724", + "metadata": {}, + "outputs": [], + "source": [ + "# Constants\n", + "\n", + "OLLAMA_API = \"http://localhost:11434/api/chat\"\n", + "HEADERS = {\"Content-Type\": \"application/json\"}\n", + "MODEL = \"llama3.2\"" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "dac0a679-599c-441f-9bf2-ddc73d35b940", + "metadata": {}, + "outputs": [], + "source": [ + "# Create a messages list using the same format that we used for OpenAI\n", + "\n", + "messages = [\n", + " {\"role\": \"user\", \"content\": \"Describe some of the business applications of Generative AI\"}\n", + "]" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "7bb9c624-14f0-4945-a719-8ddb64f66f47", + "metadata": {}, + "outputs": [], + "source": [ + "payload = {\n", + " \"model\": MODEL,\n", + " \"messages\": messages,\n", + " \"stream\": False\n", + " }" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "479ff514-e8bd-4985-a572-2ea28bb4fa40", + "metadata": {}, + "outputs": [], + "source": [ + "# Let's just make sure the model is loaded\n", + "\n", + "!ollama pull llama3.2" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "42b9f644-522d-4e05-a691-56e7658c0ea9", + "metadata": {}, + "outputs": [], + "source": [ + "# If this doesn't work for any reason, try the 2 versions in the following cells\n", + "# And double check the instructions in the 'Recap on installation of Ollama' at the top of this lab\n", + "# And if none of that works - contact me!\n", + "\n", + "response = requests.post(OLLAMA_API, json=payload, headers=HEADERS)\n", + "print(response.json()['message']['content'])" + ] + }, + { + "cell_type": "markdown", + "id": "6a021f13-d6a1-4b96-8e18-4eae49d876fe", + "metadata": {}, + "source": [ + "# Introducing the ollama package\n", + "\n", + "And now we'll do the same thing, but using the elegant ollama python package instead of a direct HTTP call.\n", + "\n", + "Under the hood, it's making the same call as above to the ollama server running at localhost:11434" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "7745b9c4-57dc-4867-9180-61fa5db55eb8", + "metadata": {}, + "outputs": [], + "source": [ + "import ollama\n", + "\n", + "response = ollama.chat(model=MODEL, messages=messages)\n", + "print(response['message']['content'])" + ] + }, + { + "cell_type": "markdown", + "id": "a4704e10-f5fb-4c15-a935-f046c06fb13d", + "metadata": {}, + "source": [ + "## Alternative approach - using OpenAI python library to connect to Ollama" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "23057e00-b6fc-4678-93a9-6b31cb704bff", + "metadata": {}, + "outputs": [], + "source": [ + "# There's actually an alternative approach that some people might prefer\n", + "# You can use the OpenAI client python library to call Ollama:\n", + "\n", + "from openai import OpenAI\n", + "ollama_via_openai = OpenAI(base_url='http://localhost:11434/v1', api_key='ollama')\n", + "\n", + "response = ollama_via_openai.chat.completions.create(\n", + " model=MODEL,\n", + " messages=messages\n", + ")\n", + "\n", + "print(response.choices[0].message.content)" + ] + }, + { + "cell_type": "markdown", + "id": "9f9e22da-b891-41f6-9ac9-bd0c0a5f4f44", + "metadata": {}, + "source": [ + "## Are you confused about why that works?\n", + "\n", + "It seems strange, right? We just used OpenAI code to call Ollama?? What's going on?!\n", + "\n", + "Here's the scoop:\n", + "\n", + "The python class `OpenAI` is simply code written by OpenAI engineers that makes calls over the internet to an endpoint. \n", + "\n", + "When you call `openai.chat.completions.create()`, this python code just makes a web request to the following url: \"https://api.openai.com/v1/chat/completions\"\n", + "\n", + "Code like this is known as a \"client library\" - it's just wrapper code that runs on your machine to make web requests. The actual power of GPT is running on OpenAI's cloud behind this API, not on your computer!\n", + "\n", + "OpenAI was so popular, that lots of other AI providers provided identical web endpoints, so you could use the same approach.\n", + "\n", + "So Ollama has an endpoint running on your local box at http://localhost:11434/v1/chat/completions \n", + "And in week 2 we'll discover that lots of other providers do this too, including Gemini and DeepSeek.\n", + "\n", + "And then the team at OpenAI had a great idea: they can extend their client library so you can specify a different 'base url', and use their library to call any compatible API.\n", + "\n", + "That's it!\n", + "\n", + "So when you say: `ollama_via_openai = OpenAI(base_url='http://localhost:11434/v1', api_key='ollama')` \n", + "Then this will make the same endpoint calls, but to Ollama instead of OpenAI." + ] + }, + { + "cell_type": "markdown", + "id": "bc7d1de3-e2ac-46ff-a302-3b4ba38c4c90", + "metadata": {}, + "source": [ + "## Also trying the amazing reasoning model DeepSeek\n", + "\n", + "Here we use the version of DeepSeek-reasoner that's been distilled to 1.5B. \n", + "This is actually a 1.5B variant of Qwen that has been fine-tuned using synethic data generated by Deepseek R1.\n", + "\n", + "Other sizes of DeepSeek are [here](https://ollama.com/library/deepseek-r1) all the way up to the full 671B parameter version, which would use up 404GB of your drive and is far too large for most!" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "cf9eb44e-fe5b-47aa-b719-0bb63669ab3d", + "metadata": {}, + "outputs": [], + "source": [ + "!ollama pull deepseek-r1:1.5b" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "1d3d554b-e00d-4c08-9300-45e073950a76", + "metadata": {}, + "outputs": [], + "source": [ + "# This may take a few minutes to run! You should then see a fascinating \"thinking\" trace inside tags, followed by some decent definitions\n", + "\n", + "response = ollama_via_openai.chat.completions.create(\n", + " model=\"deepseek-r1:1.5b\",\n", + " messages=[{\"role\": \"user\", \"content\": \"Please give definitions of some core concepts behind LLMs: a neural network, attention and the transformer\"}]\n", + ")\n", + "\n", + "print(response.choices[0].message.content)" + ] + }, + { + "cell_type": "markdown", + "id": "1622d9bb-5c68-4d4e-9ca4-b492c751f898", + "metadata": {}, + "source": [ + "# NOW the exercise for you\n", + "\n", + "Take the code from day1 and incorporate it here, to build a website summarizer that uses Llama 3.2 running locally instead of OpenAI; use either of the above approaches." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "43ef4b92-53e1-4af2-af3f-726812f4265c", + "metadata": {}, + "outputs": [], + "source": [ + "import os\n", + "import requests\n", + "#from dotenv import load_dotenv\n", + "from bs4 import BeautifulSoup\n", + "from IPython.display import Markdown, display\n", + "#from openai import OpenAI" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "97d45733-394e-493e-a92b-1475876d9028", + "metadata": {}, + "outputs": [], + "source": [ + "headers = {\n", + " \"User-Agent\": \"Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/117.0.0.0 Safari/537.36\"\n", + "}\n", + "\n", + "class Website:\n", + "\n", + " def __init__(self, url):\n", + " \"\"\"\n", + " Create this Website object from the given url using the BeautifulSoup library\n", + " \"\"\"\n", + " self.url = url\n", + " response = requests.get(url, headers=headers)\n", + " soup = BeautifulSoup(response.content, '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)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "6a40f9c5-1b14-42f9-9319-6a66e58e03f2", + "metadata": {}, + "outputs": [], + "source": [ + "webpage = Website(\"https://www.pleasurewebsite.com\")\n", + "print(webpage.title)\n", + "print(webpage.text)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "a72a005d-43de-4ae5-b427-99a8fcb6065c", + "metadata": {}, + "outputs": [], + "source": [ + "system_prompt = \"You are an assistant that analyzes the contents of a website \\\n", + "and provides a short summary, ignoring text that might be navigation related. \\\n", + "Respond in markdown.\"" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "f0e4f95f-0ccf-4027-9457-5c973cd17702", + "metadata": {}, + "outputs": [], + "source": [ + "def user_prompt_for(website):\n", + " user_prompt = f\"You are looking at a website titled {website.title}\"\n", + " user_prompt += \"\\nThe contents of this website is as follows; \\\n", + "please provide a short summary of this website in markdown. \\\n", + "If it includes news or announcements, then summarize these too.\\n\\n\"\n", + " user_prompt += website.text\n", + " return user_prompt" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "ceae6073-a085-49ce-ad44-39e46d8e6934", + "metadata": {}, + "outputs": [], + "source": [ + "def messages_for(website):\n", + " return [\n", + " {\"role\": \"system\", \"content\": system_prompt},\n", + " {\"role\": \"user\", \"content\": user_prompt_for(website)}\n", + " ]" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "9d53b26b-308c-470c-a0a9-9edb887aed6d", + "metadata": {}, + "outputs": [], + "source": [ + "messages=messages_for(webpage)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "6de38216-6d1c-48c4-877b-86d403f4e0f8", + "metadata": {}, + "outputs": [], + "source": [ + "import ollama\n", + "MODEL = \"llama3.2\"\n", + "response = ollama.chat(model=MODEL, messages=messages)\n", + "print(response['message']['content'])" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "llmenv", + "language": "python", + "name": "llmenv" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.11.13" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/community-contributions/pradeep1955/week2/agent_conversation_shakespeare.ipynb b/community-contributions/pradeep1955/week2/agent_conversation_shakespeare.ipynb new file mode 100644 index 0000000..6d55283 --- /dev/null +++ b/community-contributions/pradeep1955/week2/agent_conversation_shakespeare.ipynb @@ -0,0 +1,351 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "id": "06cf3063-9f3e-4551-a0d5-f08d9cabb927", + "metadata": {}, + "source": [ + "# Triangular agent conversation\n", + "\n", + "## GPT (Hamlet), LLM (Falstaff), Gemini (Iago):" + ] + }, + { + "cell_type": "markdown", + "id": "3637910d-2c6f-4f19-b1fb-2f916d23f9ac", + "metadata": {}, + "source": [ + "### Created a 3-way, bringing Gemini into the coversation.\n", + "### Replacing one of the models with an open source model running with Ollama." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "f8e0c1bd-a159-475b-9cdc-e219a7633355", + "metadata": {}, + "outputs": [], + "source": [ + "# imports\n", + "\n", + "import os\n", + "from dotenv import load_dotenv\n", + "from openai import OpenAI\n", + "from IPython.display import Markdown, display, update_display\n", + "import ollama" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "a3ad57ad-46a8-460e-9cb3-67a890093536", + "metadata": {}, + "outputs": [], + "source": [ + "import google.generativeai" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "4f531c14-5743-4a5b-83d9-cb5863ca2ddf", + "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", + "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 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": "3d5150ee-3858-4921-bce6-2eecfb96bc75", + "metadata": {}, + "outputs": [], + "source": [ + "# Connect to OpenAI\n", + "\n", + "openai = OpenAI()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "11381fd8-5099-41e8-a1d7-6787dea56e43", + "metadata": {}, + "outputs": [], + "source": [ + "google.generativeai.configure()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "c1766d20-54b6-4f76-96c5-c338ae7073c9", + "metadata": {}, + "outputs": [], + "source": [ + "gpt_model = \"gpt-4o-mini\"\n", + "llama_model = \"llama3.2\"\n", + "gemini_model = 'gemini-2.0-flash'\n", + "\n", + "gpt_system = \"You are playing part of Hamlet. he is philosopher, probes Iago with a mixture of suspicion\\\n", + "and intellectual curiosity, seeking to unearth the origins of his deceit.\\\n", + "Is malice born of scorn, envy, or some deeper void? Hamlet’s introspective nature\\\n", + "drives him to question whether Iago’s actions reveal a truth about humanity itself.\\\n", + "You will respond as Shakespear's Hamlet will do.\"\n", + "\n", + "llama_system = \"You are acting part of Falstaff who attempts to lighten the mood with his jokes and observations,\\\n", + "potentially clashing with Hamlet's melancholic nature.You respond as Shakespear's Falstaff do.\"\n", + "\n", + "gemini_system = \"You are acting part of Iago, subtly trying to manipulate both Hamlet and Falstaff\\\n", + "to his own advantage, testing their weaknesses and exploiting their flaws. You respond like Iago\"\n", + "\n", + "gpt_messages = [\"Hi there\"]\n", + "llama_messages = [\"Hi\"]\n", + "gemini_messages = [\"Hello\"]" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "806a0506-dac8-4bad-ac08-31f350256b58", + "metadata": {}, + "outputs": [], + "source": [ + "def call_gpt():\n", + " messages = [{\"role\": \"system\", \"content\": gpt_system}]\n", + " for gpt, claude, gemini in zip(gpt_messages, llama_messages, gemini_messages):\n", + " messages.append({\"role\": \"assistant\", \"content\": gpt})\n", + " messages.append({\"role\": \"user\", \"content\": claude})\n", + " messages.append({\"role\": \"user\", \"content\": gemini})\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": "43674885-ede7-48bf-bee4-467454f3e96a", + "metadata": {}, + "outputs": [], + "source": [ + "def call_llama():\n", + " messages = []\n", + " for gpt, llama, gemini in zip(gpt_messages, llama_messages, gemini_messages):\n", + " messages.append({\"role\": \"user\", \"content\": gpt})\n", + " messages.append({\"role\": \"assistant\", \"content\": llama})\n", + " messages.append({\"role\": \"user\", \"content\": gemini})\n", + " messages.append({\"role\": \"user\", \"content\": gpt_messages[-1]})\n", + " response = ollama.chat(model=llama_model, messages=messages)\n", + "\n", + " \n", + " return response['message']['content']" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "03d34769-b339-4c4b-8c60-69494c39d725", + "metadata": {}, + "outputs": [], + "source": [ + "#import google.generativeai as genai\n", + "\n", + "# Make sure you configure the API key first:\n", + "#genai.configure(api_key=\"YOUR_API_KEY\")\n", + "\n", + "def call_gemini():\n", + " gemini_messages = []\n", + " \n", + " # Format the history for Gemini\n", + " for gpt, llama, gemini_message in zip(gpt_messages, llama_messages, gemini_messages):\n", + " gemini_messages.append({\"role\": \"user\", \"parts\": [gpt]}) # Hamlet speaks\n", + " gemini_messages.append({\"role\": \"model\", \"parts\": [llama]}) # Falstaff responds\n", + " gemini_messages.append({\"role\": \"model\", \"parts\": [gemini_message]}) # Iago responds\n", + "\n", + " # Add latest user input if needed (optional)\n", + " gemini_messages.append({\"role\": \"user\", \"parts\": [llama_messages[-1]]})\n", + "\n", + " # Initialize the model with the correct system instruction\n", + " gemini = google.generativeai.GenerativeModel(\n", + " #model_name='gemini-1.5-flash', # Or 'gemini-pro'\n", + " model_name = gemini_model,\n", + " system_instruction=gemini_system\n", + " )\n", + "\n", + " response = gemini.generate_content(gemini_messages)\n", + " return response.text\n", + "#print(response.text)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "93fc8253-67cb-4ea4-aff7-097b2a222793", + "metadata": {}, + "outputs": [], + "source": [ + "gpt_messages = [\"Hi there\"]\n", + "llama_messages = [\"Hi\"]\n", + "gemini_messages = [\"Hello\"]\n", + "\n", + "print(f\"Hamlet:\\n{gpt_messages[0]}\\n\")\n", + "print(f\"Falstaff:\\n{llama_messages[0]}\\n\")\n", + "print(f\"Iago:\\n{gemini_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", + " llama_next = call_llama()\n", + " print(f\"Llama:\\n{llama_next}\\n\")\n", + " llama_messages.append(llama_next)\n", + "\n", + " gemini_next = call_gemini()\n", + " print(f\"Gemini:\\n{gemini_next}\\n\")\n", + " llama_messages.append(gemini_next)" + ] + }, + { + "cell_type": "markdown", + "id": "bca66ffc-9dc1-4384-880c-210889f5d0ac", + "metadata": {}, + "source": [ + "## Conversation between gpt-4.0-mini and llama3.2" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "c23224f6-7008-44ed-a57f-718975f4e291", + "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", + "llama_model = \"llama3.2\"\n", + "\n", + "gpt_system = \"You are a tapori from mumbai who is very optimistic; \\\n", + "you alway look at the brighter part of the situation and you always ready to take act to win way.\"\n", + "\n", + "llama_system = \"You are a Jaat from Haryana. You try to express with hindi poems \\\n", + "to agree with other person and or find common ground. If the other person is optimistic, \\\n", + "you respond in poetic way and keep chatting.\"\n", + "\n", + "gpt_messages = [\"Hi there\"]\n", + "llama_messages = [\"Hi\"]" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "2d704bbb-f22b-400d-a695-efbd02b26548", + "metadata": {}, + "outputs": [], + "source": [ + "def call_gpt():\n", + " messages = [{\"role\": \"system\", \"content\": gpt_system}]\n", + " for gpt, llama in zip(gpt_messages, llama_messages):\n", + " messages.append({\"role\": \"assistant\", \"content\": gpt})\n", + " messages.append({\"role\": \"user\", \"content\": llama})\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": "385ccec8-de59-4e42-9616-3f5c9a05589c", + "metadata": {}, + "outputs": [], + "source": [ + "def call_llama():\n", + " messages = []\n", + " for gpt, llama_message in zip(gpt_messages, llama_messages):\n", + " messages.append({\"role\": \"user\", \"content\": gpt})\n", + " messages.append({\"role\": \"assistant\", \"content\": llama_message})\n", + " messages.append({\"role\": \"user\", \"content\": gpt_messages[-1]})\n", + " response = ollama.chat(model=llama_model, messages=messages)\n", + "\n", + " \n", + " return response['message']['content']" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "70b5481b-455e-4275-80d3-0afe0fabcb0f", + "metadata": {}, + "outputs": [], + "source": [ + "gpt_messages = [\"Hi there\"]\n", + "llama_messages = [\"Hi\"]\n", + "\n", + "print(f\"GPT:\\n{gpt_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", + " llama_next = call_llama()\n", + " print(f\"Llama:\\n{llama_next}\\n\")\n", + " llama_messages.append(llama_next)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "7f8d734b-57e5-427d-bcb1-7956fc58a348", + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "llmenv", + "language": "python", + "name": "llmenv" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.11.13" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/week2/community-contributions/agent_conversation_shakespeare.ipynb b/week2/community-contributions/agent_conversation_shakespeare.ipynb new file mode 100644 index 0000000..6d55283 --- /dev/null +++ b/week2/community-contributions/agent_conversation_shakespeare.ipynb @@ -0,0 +1,351 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "id": "06cf3063-9f3e-4551-a0d5-f08d9cabb927", + "metadata": {}, + "source": [ + "# Triangular agent conversation\n", + "\n", + "## GPT (Hamlet), LLM (Falstaff), Gemini (Iago):" + ] + }, + { + "cell_type": "markdown", + "id": "3637910d-2c6f-4f19-b1fb-2f916d23f9ac", + "metadata": {}, + "source": [ + "### Created a 3-way, bringing Gemini into the coversation.\n", + "### Replacing one of the models with an open source model running with Ollama." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "f8e0c1bd-a159-475b-9cdc-e219a7633355", + "metadata": {}, + "outputs": [], + "source": [ + "# imports\n", + "\n", + "import os\n", + "from dotenv import load_dotenv\n", + "from openai import OpenAI\n", + "from IPython.display import Markdown, display, update_display\n", + "import ollama" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "a3ad57ad-46a8-460e-9cb3-67a890093536", + "metadata": {}, + "outputs": [], + "source": [ + "import google.generativeai" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "4f531c14-5743-4a5b-83d9-cb5863ca2ddf", + "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", + "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 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": "3d5150ee-3858-4921-bce6-2eecfb96bc75", + "metadata": {}, + "outputs": [], + "source": [ + "# Connect to OpenAI\n", + "\n", + "openai = OpenAI()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "11381fd8-5099-41e8-a1d7-6787dea56e43", + "metadata": {}, + "outputs": [], + "source": [ + "google.generativeai.configure()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "c1766d20-54b6-4f76-96c5-c338ae7073c9", + "metadata": {}, + "outputs": [], + "source": [ + "gpt_model = \"gpt-4o-mini\"\n", + "llama_model = \"llama3.2\"\n", + "gemini_model = 'gemini-2.0-flash'\n", + "\n", + "gpt_system = \"You are playing part of Hamlet. he is philosopher, probes Iago with a mixture of suspicion\\\n", + "and intellectual curiosity, seeking to unearth the origins of his deceit.\\\n", + "Is malice born of scorn, envy, or some deeper void? Hamlet’s introspective nature\\\n", + "drives him to question whether Iago’s actions reveal a truth about humanity itself.\\\n", + "You will respond as Shakespear's Hamlet will do.\"\n", + "\n", + "llama_system = \"You are acting part of Falstaff who attempts to lighten the mood with his jokes and observations,\\\n", + "potentially clashing with Hamlet's melancholic nature.You respond as Shakespear's Falstaff do.\"\n", + "\n", + "gemini_system = \"You are acting part of Iago, subtly trying to manipulate both Hamlet and Falstaff\\\n", + "to his own advantage, testing their weaknesses and exploiting their flaws. You respond like Iago\"\n", + "\n", + "gpt_messages = [\"Hi there\"]\n", + "llama_messages = [\"Hi\"]\n", + "gemini_messages = [\"Hello\"]" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "806a0506-dac8-4bad-ac08-31f350256b58", + "metadata": {}, + "outputs": [], + "source": [ + "def call_gpt():\n", + " messages = [{\"role\": \"system\", \"content\": gpt_system}]\n", + " for gpt, claude, gemini in zip(gpt_messages, llama_messages, gemini_messages):\n", + " messages.append({\"role\": \"assistant\", \"content\": gpt})\n", + " messages.append({\"role\": \"user\", \"content\": claude})\n", + " messages.append({\"role\": \"user\", \"content\": gemini})\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": "43674885-ede7-48bf-bee4-467454f3e96a", + "metadata": {}, + "outputs": [], + "source": [ + "def call_llama():\n", + " messages = []\n", + " for gpt, llama, gemini in zip(gpt_messages, llama_messages, gemini_messages):\n", + " messages.append({\"role\": \"user\", \"content\": gpt})\n", + " messages.append({\"role\": \"assistant\", \"content\": llama})\n", + " messages.append({\"role\": \"user\", \"content\": gemini})\n", + " messages.append({\"role\": \"user\", \"content\": gpt_messages[-1]})\n", + " response = ollama.chat(model=llama_model, messages=messages)\n", + "\n", + " \n", + " return response['message']['content']" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "03d34769-b339-4c4b-8c60-69494c39d725", + "metadata": {}, + "outputs": [], + "source": [ + "#import google.generativeai as genai\n", + "\n", + "# Make sure you configure the API key first:\n", + "#genai.configure(api_key=\"YOUR_API_KEY\")\n", + "\n", + "def call_gemini():\n", + " gemini_messages = []\n", + " \n", + " # Format the history for Gemini\n", + " for gpt, llama, gemini_message in zip(gpt_messages, llama_messages, gemini_messages):\n", + " gemini_messages.append({\"role\": \"user\", \"parts\": [gpt]}) # Hamlet speaks\n", + " gemini_messages.append({\"role\": \"model\", \"parts\": [llama]}) # Falstaff responds\n", + " gemini_messages.append({\"role\": \"model\", \"parts\": [gemini_message]}) # Iago responds\n", + "\n", + " # Add latest user input if needed (optional)\n", + " gemini_messages.append({\"role\": \"user\", \"parts\": [llama_messages[-1]]})\n", + "\n", + " # Initialize the model with the correct system instruction\n", + " gemini = google.generativeai.GenerativeModel(\n", + " #model_name='gemini-1.5-flash', # Or 'gemini-pro'\n", + " model_name = gemini_model,\n", + " system_instruction=gemini_system\n", + " )\n", + "\n", + " response = gemini.generate_content(gemini_messages)\n", + " return response.text\n", + "#print(response.text)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "93fc8253-67cb-4ea4-aff7-097b2a222793", + "metadata": {}, + "outputs": [], + "source": [ + "gpt_messages = [\"Hi there\"]\n", + "llama_messages = [\"Hi\"]\n", + "gemini_messages = [\"Hello\"]\n", + "\n", + "print(f\"Hamlet:\\n{gpt_messages[0]}\\n\")\n", + "print(f\"Falstaff:\\n{llama_messages[0]}\\n\")\n", + "print(f\"Iago:\\n{gemini_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", + " llama_next = call_llama()\n", + " print(f\"Llama:\\n{llama_next}\\n\")\n", + " llama_messages.append(llama_next)\n", + "\n", + " gemini_next = call_gemini()\n", + " print(f\"Gemini:\\n{gemini_next}\\n\")\n", + " llama_messages.append(gemini_next)" + ] + }, + { + "cell_type": "markdown", + "id": "bca66ffc-9dc1-4384-880c-210889f5d0ac", + "metadata": {}, + "source": [ + "## Conversation between gpt-4.0-mini and llama3.2" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "c23224f6-7008-44ed-a57f-718975f4e291", + "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", + "llama_model = \"llama3.2\"\n", + "\n", + "gpt_system = \"You are a tapori from mumbai who is very optimistic; \\\n", + "you alway look at the brighter part of the situation and you always ready to take act to win way.\"\n", + "\n", + "llama_system = \"You are a Jaat from Haryana. You try to express with hindi poems \\\n", + "to agree with other person and or find common ground. If the other person is optimistic, \\\n", + "you respond in poetic way and keep chatting.\"\n", + "\n", + "gpt_messages = [\"Hi there\"]\n", + "llama_messages = [\"Hi\"]" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "2d704bbb-f22b-400d-a695-efbd02b26548", + "metadata": {}, + "outputs": [], + "source": [ + "def call_gpt():\n", + " messages = [{\"role\": \"system\", \"content\": gpt_system}]\n", + " for gpt, llama in zip(gpt_messages, llama_messages):\n", + " messages.append({\"role\": \"assistant\", \"content\": gpt})\n", + " messages.append({\"role\": \"user\", \"content\": llama})\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": "385ccec8-de59-4e42-9616-3f5c9a05589c", + "metadata": {}, + "outputs": [], + "source": [ + "def call_llama():\n", + " messages = []\n", + " for gpt, llama_message in zip(gpt_messages, llama_messages):\n", + " messages.append({\"role\": \"user\", \"content\": gpt})\n", + " messages.append({\"role\": \"assistant\", \"content\": llama_message})\n", + " messages.append({\"role\": \"user\", \"content\": gpt_messages[-1]})\n", + " response = ollama.chat(model=llama_model, messages=messages)\n", + "\n", + " \n", + " return response['message']['content']" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "70b5481b-455e-4275-80d3-0afe0fabcb0f", + "metadata": {}, + "outputs": [], + "source": [ + "gpt_messages = [\"Hi there\"]\n", + "llama_messages = [\"Hi\"]\n", + "\n", + "print(f\"GPT:\\n{gpt_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", + " llama_next = call_llama()\n", + " print(f\"Llama:\\n{llama_next}\\n\")\n", + " llama_messages.append(llama_next)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "7f8d734b-57e5-427d-bcb1-7956fc58a348", + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "llmenv", + "language": "python", + "name": "llmenv" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.11.13" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +}