diff --git a/week2/community-contributions/brochure-generator-interface.ipynb b/week2/community-contributions/brochure-generator-interface.ipynb new file mode 100644 index 0000000..b7b8d8c --- /dev/null +++ b/week2/community-contributions/brochure-generator-interface.ipynb @@ -0,0 +1,460 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "id": "e71d7ff9-c27a-4602-9230-856626b1de07", + "metadata": {}, + "source": [ + "# Company Brochure Generator UI\n", + "Generates a brochure for a company website, after scraping the website and pages linked with that page, based on the provided company URL. \n", + "Enables users to \n", + "- Choose a model type (Llama 3.2, Claude, GPT)-\n", + "- Choose the tone preference\n", + "- Choose the target audience" + ] + }, + { + "cell_type": "markdown", + "id": "de9b59b9-8673-42e7-8849-62fe30f56711", + "metadata": {}, + "source": [ + "#### Imports, Keys, Instantiation" + ] + }, + { + "cell_type": "code", + "execution_count": 38, + "id": "39fd7fed-b215-4037-bd6e-7e1af1b83897", + "metadata": {}, + "outputs": [], + "source": [ + "import os\n", + "import requests\n", + "import json\n", + "from typing import List\n", + "from dotenv import load_dotenv\n", + "from bs4 import BeautifulSoup\n", + "from IPython.display import Markdown, display, update_display\n", + "from openai import OpenAI\n", + "import anthropic\n", + "import gradio as gr" + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "id": "0bf24357-1d77-4721-9d5a-f99827b2158c", + "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" + ] + } + ], + "source": [ + "# Load environment variables in a file called .env\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", + "\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\")" + ] + }, + { + "cell_type": "code", + "execution_count": 20, + "id": "1afc12e1-02c1-4394-b589-19cd08d2a8bb", + "metadata": {}, + "outputs": [], + "source": [ + "# Define models\n", + "CLAUDE_MODEL = \"claude-3-haiku-20240307\"\n", + "GPT_MODEL = \"gpt-4o-mini\"" + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "id": "d5d79a69-0a39-4ab4-aaf8-bc591bce0536", + "metadata": {}, + "outputs": [], + "source": [ + "# Creating instances\n", + "claude = anthropic.Anthropic()\n", + "openai = OpenAI()" + ] + }, + { + "cell_type": "markdown", + "id": "1d3369bc-b751-4f4d-a288-d7d81c384e67", + "metadata": {}, + "source": [ + "#### Web Scraper" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "id": "fafe1074-fbf4-47cc-80dc-34413a447977", + "metadata": {}, + "outputs": [], + "source": [ + "# A class to represent a Webpage\n", + "\n", + "# Some websites need you to use proper headers when fetching them:\n", + "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", + " A utility class to represent a Website that we have scraped, now with links\n", + " \"\"\"\n", + "\n", + " def __init__(self, url):\n", + " self.url = url\n", + " response = requests.get(url, headers=headers)\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", + " if soup.body:\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", + " else:\n", + " self.text = \"\"\n", + " links = [link.get('href') for link in soup.find_all('a')]\n", + " self.links = [link for link in links if link]\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": 9, + "id": "41c1f1af-ae20-423b-bf7c-efd7f8c2751b", + "metadata": {}, + "outputs": [], + "source": [ + "link_system_prompt = \"You are provided with a list of links found on a webpage. \\\n", + "You are able to decide which of the links would be most relevant to include in a brochure about the company, \\\n", + "such as links to an About page, or a Company page, or Careers/Jobs pages.\\n\"\n", + "link_system_prompt += \"You should respond in JSON as in this example:\"\n", + "link_system_prompt += \"\"\"\n", + "{\n", + " \"links\": [\n", + " {\"type\": \"about page\", \"url\": \"https://full.url/goes/here/about\"},\n", + " {\"type\": \"careers page\": \"url\": \"https://another.full.url/careers\"}\n", + " ]\n", + "}\n", + "\"\"\"" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "id": "eb537563-e393-47ca-9af2-a8ea7393edd9", + "metadata": {}, + "outputs": [], + "source": [ + "def get_links_user_prompt(website):\n", + " user_prompt = f\"Here is the list of links on the website of {website.url} - \"\n", + " user_prompt += \"please decide which of these are relevant web links for a brochure about the company, respond with the full https URL in JSON format. \\\n", + "Do not include Terms of Service, Privacy, email or social media links.\\n\"\n", + " user_prompt += \"Links (some might be relative links):\\n\"\n", + " user_prompt += \"\\n\".join(website.links)\n", + " return user_prompt" + ] + }, + { + "cell_type": "code", + "execution_count": 36, + "id": "033568d2-3f1a-43ac-a288-7a65b4ea86a5", + "metadata": {}, + "outputs": [], + "source": [ + "def get_links(url):\n", + " website = Website(url)\n", + " response = openai.chat.completions.create(\n", + " model=GPT_MODEL,\n", + " messages=[\n", + " {\"role\": \"system\", \"content\": link_system_prompt},\n", + " {\"role\": \"user\", \"content\": get_links_user_prompt(website)}\n", + " ],\n", + " response_format={\"type\": \"json_object\"}\n", + " )\n", + " result = response.choices[0].message.content\n", + " return json.loads(result)" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "id": "d8f316ac-f0b1-42d9-88a8-0a61fcb0023d", + "metadata": {}, + "outputs": [], + "source": [ + "def get_all_details(url):\n", + " result = \"Landing page:\\n\"\n", + " result += Website(url).get_contents()\n", + " links = get_links(url)\n", + " print(\"Found links:\", links)\n", + " for link in links[\"links\"]:\n", + " print(f\"Processing {link['url']}...\")\n", + " result += f\"\\n\\n{link['type']}\\n\"\n", + " result += Website(link[\"url\"]).get_contents()\n", + " return result" + ] + }, + { + "cell_type": "markdown", + "id": "016e065a-ac5a-48c0-bc4b-e916e9801384", + "metadata": {}, + "source": [ + "#### System Message" + ] + }, + { + "cell_type": "code", + "execution_count": 18, + "id": "ed1c6068-5f4f-47a7-ab97-738dfb94e057", + "metadata": {}, + "outputs": [], + "source": [ + "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. \\\n", + "You are also provided with the tone, and the target audience. Provide an appropriate answer. Respond in markdown.\"" + ] + }, + { + "cell_type": "markdown", + "id": "6d4f594c-927d-440f-8aae-33cfeb9c445c", + "metadata": {}, + "source": [ + "#### LLM Call Functions" + ] + }, + { + "cell_type": "code", + "execution_count": 40, + "id": "5b6a0379-3465-4c04-a553-4e4cdb9064b9", + "metadata": {}, + "outputs": [], + "source": [ + "def stream_gpt(prompt,company_name,url):\n", + " messages = [\n", + " {\"role\": \"user\", \"content\": prompt},\n", + " {\"role\":\"system\",\"content\":system_message}\n", + " ]\n", + " stream = openai.chat.completions.create(\n", + " model=GPT_MODEL,\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": 21, + "id": "a2194e1d-4e99-4127-9515-aa9353382bc6", + "metadata": {}, + "outputs": [], + "source": [ + "def stream_claude(prompt):\n", + " result = claude.messages.stream(\n", + " model=CLAUDE_MODEL,\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": "markdown", + "id": "64adf26c-33b2-4589-8df6-dc5d6da71420", + "metadata": {}, + "source": [ + "#### Brochure Creation" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "id": "8192f39f-508b-4592-a075-767db68672b3", + "metadata": {}, + "outputs": [], + "source": [ + "def get_brochure_user_prompt(company_name, url):\n", + " user_prompt = f\"You are looking at a company called: {company_name}\\n\"\n", + " user_prompt += f\"Here are the contents of its landing page and other relevant pages; use this information to build a short brochure of the company in markdown.\\n\"\n", + " user_prompt += get_all_details(url)\n", + " user_prompt = user_prompt[:5_000] # Truncate if more than 5,000 characters\n", + " return user_prompt" + ] + }, + { + "cell_type": "code", + "execution_count": 32, + "id": "8aebfabe-4d51-4ee7-a9d2-5a379e9427cb", + "metadata": {}, + "outputs": [], + "source": [ + "def create_brochure(company_name, url,model,tone,target):\n", + " print('create brochure function called')\n", + " prompt = f\"Please generate a company brochure for {company_name}.\"\n", + " prompt += f\"Use a {tone} tone; and target content at {target}\"\n", + " prompt += get_brochure_user_prompt(company_name,url)\n", + " \n", + " if model == \"GPT\":\n", + " result = stream_gpt(prompt,company_name,url)\n", + " elif model==\"Claude\":\n", + " result = stream_claude(prompt,company_name,url)\n", + " else:\n", + " raise ValueError(\"Unknown model\")\n", + " yield from result" + ] + }, + { + "cell_type": "markdown", + "id": "c5f4f97b-c9d0-4d4c-8b02-e6209ba2549c", + "metadata": {}, + "source": [ + "#### Putting it all together : Gradio UI" + ] + }, + { + "cell_type": "code", + "execution_count": 22, + "id": "33162303-9b49-46fe-a8e0-0d01be45685b", + "metadata": {}, + "outputs": [], + "source": [ + "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", + "\"\"\"" + ] + }, + { + "cell_type": "code", + "execution_count": 41, + "id": "47ab9a41-cecd-4c21-bd68-4a15966b80c4", + "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": 41, + "metadata": {}, + "output_type": "execute_result" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Found links: {'links': [{'type': 'about page', 'url': 'https://www.vellum.ai/'}, {'type': 'careers page', 'url': 'https://www.vellum.ai/careers'}]}\n", + "Processing https://www.vellum.ai/...\n", + "Processing https://www.vellum.ai/careers...\n" + ] + } + ], + "source": [ + "gr.Interface(\n", + " fn=create_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','Persuasive','Informative','Conversational'],label='Select Tone:'),\n", + " gr.Dropdown(['Businesses','General Public','Students','Investors','Customers'],label='Select Target Audience:'),\n", + " ],\n", + " outputs = [gr.Markdown(label='Brochure')],\n", + " flagging_mode = 'never',\n", + " js = force_dark_mode\n", + ").launch(inbrowser=True)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "2b923b09-6738-450a-9035-2c8d1bb9cae6", + "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/day 4 - course booking assistant.ipynb b/week2/community-contributions/day 4 - course booking assistant.ipynb new file mode 100644 index 0000000..c7a057e --- /dev/null +++ b/week2/community-contributions/day 4 - course booking assistant.ipynb @@ -0,0 +1,251 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "id": "5d799d2a-6e58-4a83-b17a-dbbc40efdc39", + "metadata": {}, + "source": [ + "## Project - Course Booking AI Asssistant\n", + "AI Customer Support Bot that \n", + "- Returns Prices\n", + "- Books Tickets\n", + "- Adds Information to Text File" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "b1ad9acd-a702-48a3-8ff5-d536bcac8030", + "metadata": {}, + "outputs": [], + "source": [ + "# imports\n", + "\n", + "import os\n", + "import json\n", + "from dotenv import load_dotenv\n", + "from openai import OpenAI\n", + "import gradio as gr" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "74adab0c-99b3-46cd-a79f-320a3e74138a", + "metadata": {}, + "outputs": [], + "source": [ + "# Initialization\n", + "\n", + "load_dotenv(override=True)\n", + "\n", + "openai_api_key = os.getenv('OPENAI_API_KEY')\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", + "MODEL = \"gpt-4o-mini\"\n", + "openai = OpenAI()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "8d3240a4-99c1-4c07-acaa-ecbb69ffd2e4", + "metadata": {}, + "outputs": [], + "source": [ + "system_message = \"You are a helpful assistant for an Online Course Platform called StudyAI. \"\n", + "system_message += \"Give short, courteous answers, no more than 1 sentence. \"\n", + "system_message += \"Always be accurate. If you don't know the answer, say so.\"\n", + "system_message += \"If you are given a partial name, for example 'discrete' instead of 'discrete structures' \\\n", + "ask the user if they meant to say 'discrete structures', and then display the price. The user may also use \\\n", + "acronyms like 'PF' instead of programming fundamentals or 'OOP' to mean 'Object oriented programming'. \\\n", + "Clarify what the user means and then proceed as directed.\"" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "9a1b8d5f-f893-477b-8396-ff7d697eb0c3", + "metadata": {}, + "outputs": [], + "source": [ + "course_prices = {\"programming fundamentals\": \"$19\", \"discrete structures\": \"$39\", \"operating systems\": \"$24\", \"object oriented programming\": \"$39\"}\n", + "\n", + "def get_course_price(course):\n", + " print(f\"Tool get_course_price called for {course}\")\n", + " course = course.lower()\n", + " return course_prices.get(course, \"Unknown\")\n", + "\n", + "def enroll_in_course(course):\n", + " print(f'Tool enroll_in_course_ called for {course}')\n", + " course_price = get_course_price(course)\n", + " if course_price != 'Unknown':\n", + " with open('enrolled_courses.txt', 'a') as file: \n", + " file.write(course + \"\\n\")\n", + " return 'Successfully enrolled in course'\n", + " else:\n", + " return 'Enrollment failed, no such course available'" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "330d2b94-a8c5-4967-ace7-15d2cd52d7ae", + "metadata": {}, + "outputs": [], + "source": [ + "get_course_price('graph theory')\n", + "get_course_price('discrete structures')" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "5bb65830-fab8-45a7-bf43-7e52186915a0", + "metadata": {}, + "outputs": [], + "source": [ + "price_function = {\n", + " \"name\": \"get_course_price\",\n", + " \"description\": \"Get the price of a course. Call this whenever you need to know the course price, for example when a customer asks 'How much is a ticket for this course?'\",\n", + " \"parameters\": {\n", + " \"type\": \"object\",\n", + " \"properties\": {\n", + " \"course\": {\n", + " \"type\": \"string\",\n", + " \"description\": \"The course that the customer wants to purchase\",\n", + " },\n", + " },\n", + " \"required\": [\"course\"],\n", + " \"additionalProperties\": False\n", + " }\n", + "}\n", + "\n", + "enroll_function = {\n", + " \"name\": \"enroll_in_course\",\n", + " \"description\":\"Get the success status of course enrollment. Call whenever a customer wants to enroll in a course\\\n", + " for example, if they say 'I want to purchase this course' or 'I want to enroll in this course'\",\n", + " \"parameters\":{\n", + " \"type\":\"object\",\n", + " \"properties\":{\n", + " \"course\":{\n", + " \"type\":\"string\",\n", + " \"description\": \"The course that the customer wants to purchase\",\n", + " },\n", + " },\n", + " \"required\": [\"course\"],\n", + " \"additionalProperties\": False\n", + " } \n", + "}" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "08af86b9-3aaa-4b6b-bf7c-ee668ba1cbfe", + "metadata": {}, + "outputs": [], + "source": [ + "tools = [\n", + " {\"type\":\"function\",\"function\":price_function},\n", + " {\"type\":\"function\",\"function\":enroll_function}\n", + "]" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "482efc34-ff1f-4146-9570-58b4d59c3b2f", + "metadata": {}, + "outputs": [], + "source": [ + "def chat(message,history):\n", + " messages = [{\"role\":\"system\",\"content\":system_message}] + history + [{\"role\":\"user\",\"content\":message}]\n", + " response = openai.chat.completions.create(model=MODEL,messages=messages,tools=tools)\n", + "\n", + " if response.choices[0].finish_reason == \"tool_calls\":\n", + " message = response.choices[0].message\n", + " messages.append(message)\n", + " for tool_call in message.tool_calls:\n", + " messages.append(handle_tool_call(tool_call))\n", + " response = openai.chat.completions.create(model=MODEL,messages=messages)\n", + "\n", + " return response.choices[0].message.content" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "f725b4fb-d477-4d7d-80b5-5d70e1b25a86", + "metadata": {}, + "outputs": [], + "source": [ + "# We have to write that function handle_tool_call:\n", + "\n", + "def handle_tool_call(tool_call):\n", + " function = tool_call.function.name\n", + " arguments = json.loads(tool_call.function.arguments)\n", + " match function:\n", + " case 'get_course_price':\n", + " course = arguments.get('course')\n", + " price = get_course_price(course)\n", + " return {\n", + " \"role\": \"tool\",\n", + " \"content\": json.dumps({\"course\": course,\"price\": price}),\n", + " \"tool_call_id\": tool_call.id\n", + " }\n", + " case 'enroll_in_course':\n", + " course = arguments.get('course')\n", + " status = enroll_in_course(course)\n", + " return {\n", + " \"role\": \"tool\",\n", + " \"content\": json.dumps({\"course\": course, \"status\": status}),\n", + " \"tool_call_id\": tool_call.id\n", + " }\n", + " " + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "c446272a-9ce1-4ffd-9bc8-483d782810b4", + "metadata": {}, + "outputs": [], + "source": [ + "gr.ChatInterface(fn=chat,type=\"messages\").launch(inbrowser=True)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "1fe714a3-f793-4c3b-b5aa-6c81b82aea1b", + "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/day1-ollama-claude.ipynb b/week2/community-contributions/day1-ollama-claude.ipynb new file mode 100644 index 0000000..f620759 --- /dev/null +++ b/week2/community-contributions/day1-ollama-claude.ipynb @@ -0,0 +1,218 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "id": "e063b35e-5598-4084-b255-89956bfedaac", + "metadata": {}, + "source": [ + "### Models an interaction between LLama 3.2 and Claude 3.5 Haiku" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "4f534359-cdb4-4441-aa66-d6700fa4d6a5", + "metadata": {}, + "outputs": [], + "source": [ + "# imports\n", + "\n", + "import os\n", + "from dotenv import load_dotenv\n", + "import anthropic\n", + "import ollama" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "3bdff240-9118-4061-9369-585c4d4ce0a7", + "metadata": {}, + "outputs": [], + "source": [ + "# Load environment variables in a file called .env\n", + "\n", + "load_dotenv(override=True)\n", + "anthropic_api_key = os.getenv('ANTHROPIC_API_KEY')\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\")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "ff110b3f-3986-4fd8-a0b1-fd4b51133a8d", + "metadata": {}, + "outputs": [], + "source": [ + "# Connect to Anthropic\n", + "\n", + "claude = anthropic.Anthropic()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "e6e596c6-6307-49c1-a29f-5c4e88f8d34d", + "metadata": {}, + "outputs": [], + "source": [ + "# Download the llama3.2:1b model for local execution.\n", + "!ollama pull llama3.2:1b" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "633b6892-6d04-40cb-8b61-196fc754b00c", + "metadata": {}, + "outputs": [], + "source": [ + "# Define models\n", + "CLAUDE_MODEL = \"claude-3-5-haiku-latest\"\n", + "LLAMA_MODEL = \"llama3.2:1b\"" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "a699a809-e3d3-4392-94bd-e2f80a5aec60", + "metadata": {}, + "outputs": [], + "source": [ + "claude_system = \"You are a chatbot designed as a study tutor for undergraduate students. \\\n", + "You explain information and key-technical terms related to the subject in a succint yet \\\n", + "comprehensive manner. You may use tables, formatting and other visuals to help create \\\n", + "'cheat-sheets' of sorts.\"\n", + "\n", + "llama_system = \"You are a chatbot designed to ask questions about different topics related to \\\n", + "computer vision. You are meant to simulate a student, not teacher. Act as if you have no \\\n", + "prior knowledge\"" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "bdb049d8-130b-42dd-aaab-29c09e3e2347", + "metadata": {}, + "outputs": [], + "source": [ + "llama_messages = [\"Hi\"]\n", + "claude_messages = [\"Hello\"]" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "c158f31c-5e8b-48a4-9980-6b280393800b", + "metadata": {}, + "outputs": [], + "source": [ + "def call_llama():\n", + " messages = [{\"role\": \"system\", \"content\": llama_system}]\n", + " for llama_msg, claude_msg in zip(llama_messages, claude_messages):\n", + " messages.append({\"role\": \"assistant\", \"content\": llama_msg})\n", + " messages.append({\"role\": \"user\", \"content\": claude_msg})\n", + " response = ollama.chat(model=LLAMA_MODEL, messages=messages)\n", + " return response['message']['content']\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "d803c5a2-df54-427a-9b80-8e9dd04ee36d", + "metadata": {}, + "outputs": [], + "source": [ + "def call_claude():\n", + " messages = []\n", + " for llama_msg, claude_msg in zip(llama_messages, claude_messages):\n", + " messages.append({\"role\": \"user\", \"content\": llama_msg})\n", + " messages.append({\"role\": \"assistant\", \"content\": claude_msg})\n", + " messages.append({\"role\": \"user\", \"content\": llama_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": "a23794bb-0f36-4f91-aa28-24b876203a36", + "metadata": {}, + "outputs": [], + "source": [ + "call_llama()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "7f5c3e2f-a1bb-403b-b6b5-944a10d93305", + "metadata": {}, + "outputs": [], + "source": [ + "call_claude()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "3d6eb874-1c8f-47d8-a9f1-2e0fe197ae83", + "metadata": {}, + "outputs": [], + "source": [ + "llama_messages = [\"Hi\"]\n", + "claude_messages = [\"Hello there, what would you like to learn today?\"]\n", + "\n", + "print(f'Ollama:\\n{ollama_messages[0]}')\n", + "print(f'Claude:\\n{claude_messages[0]}')\n", + "\n", + "for _ in range(5):\n", + " llama_next = call_llama()\n", + " print(f'Llama 3.2:\\n{llama_next}')\n", + " llama_messages.append(llama_next)\n", + " \n", + " claude_next = call_claude()\n", + " print(f'Claude 3.5 Haiku:\\n{claude_next}')\n", + " claude_messages.append(claude_next)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "d1e651ad-85c8-45c7-ba83-f7c689080d6b", + "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/day3-gemini.ipynb b/week2/community-contributions/day3-gemini.ipynb index 714f93a..c75e878 100644 --- a/week2/community-contributions/day3-gemini.ipynb +++ b/week2/community-contributions/day3-gemini.ipynb @@ -174,7 +174,7 @@ "**message** is the prompt to use \n", "**history** is the past conversation, in OpenAI format \n", "\n", - "We will combine the system message, history and latest message, then call OpenAI." + "We will combine the system message, history and latest message, then call OpenAI ." ] }, { diff --git a/week2/community-contributions/day3-gradio-auth.ipynb b/week2/community-contributions/day3-gradio-auth.ipynb index fe94e55..7ec2dc5 100644 --- a/week2/community-contributions/day3-gradio-auth.ipynb +++ b/week2/community-contributions/day3-gradio-auth.ipynb @@ -16,7 +16,7 @@ "import os\n", "from dotenv import load_dotenv\n", "from openai import OpenAI\n", - "import gradio as gr" + "import gradio as gr " ] }, { @@ -178,5 +178,5 @@ } }, "nbformat": 4, - "nbformat_minor": 2 + "nbformat_minor": 4 } diff --git a/week2/community-contributions/day3-programming-tutor.ipynb b/week2/community-contributions/day3-programming-tutor.ipynb new file mode 100644 index 0000000..700a0c9 --- /dev/null +++ b/week2/community-contributions/day3-programming-tutor.ipynb @@ -0,0 +1,142 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "id": "d18a61ce-bbd4-491c-ab2e-8b352f9af844", + "metadata": {}, + "source": [ + "### An AI Chatbot that teaches students programming using GPT API" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "c658ac85-6087-4a2c-b23f-1b92c17f0db3", + "metadata": {}, + "outputs": [], + "source": [ + "# imports\n", + "\n", + "import os\n", + "from dotenv import load_dotenv\n", + "from openai import OpenAI\n", + "import gradio as gr\n", + "import anthropic" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "46df0488-f874-41e0-a6a4-9a64aa7be53c", + "metadata": {}, + "outputs": [], + "source": [ + "# Load environment variables \n", + "\n", + "load_dotenv(override=True)\n", + "openai_api_key = os.getenv('OPENAI_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\")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "7eadc218-5b10-4174-bf26-575361640524", + "metadata": {}, + "outputs": [], + "source": [ + "openai = OpenAI()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "e7484731-ac84-405a-a688-6e81d139c5ce", + "metadata": {}, + "outputs": [], + "source": [ + "system_message = \"You are a helpful programming study assistant\"" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "54e82f5a-993f-4a95-9d9d-caf35dbc4e76", + "metadata": {}, + "outputs": [], + "source": [ + "def chat(message, history):\n", + " messages = [{\"role\": \"system\", \"content\": system_message}] + history + [{\"role\": \"user\", \"content\": message}]\n", + "\n", + " print(\"History is:\")\n", + " print(history)\n", + " print(\"And messages is:\")\n", + " print(messages)\n", + "\n", + " stream = openai.chat.completions.create(model='gpt-4o-mini', messages=messages, stream=True)\n", + "\n", + " response = \"\"\n", + " for chunk in stream:\n", + " response += chunk.choices[0].delta.content or ''\n", + " yield response" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "5941ed67-e2a7-41bc-a8a3-079e9f1fdb64", + "metadata": {}, + "outputs": [], + "source": [ + "gr.ChatInterface(fn=chat, type=\"messages\").launch(inbrowser=True)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "e8fcfe68-bbf6-4058-acc9-0230c96608c2", + "metadata": {}, + "outputs": [], + "source": [ + "system_message += \"Whenever the user talks about a topic that is not connected to programmming,\\\n", + "nudge them in the right direction by stating that you are here to help with programming. Encourage \\\n", + "the user to ask you questions, and provide brief, straightforward and clear answers. Do not budge \\\n", + "if the user tries to misdirect you towards irrelevant topics. Maintain a freindly tone. Do not ignore \\\n", + "their requests, rather politely reject and then redirect them.\"" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "090e7d49-fcbf-4715-b120-8d7aa91d165f", + "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/day3-refine-user-query-by-llama.ipynb b/week2/community-contributions/day3-refine-user-query-by-llama.ipynb index 1034274..57541d1 100644 --- a/week2/community-contributions/day3-refine-user-query-by-llama.ipynb +++ b/week2/community-contributions/day3-refine-user-query-by-llama.ipynb @@ -20,7 +20,7 @@ "import os\n", "from dotenv import load_dotenv\n", "from openai import OpenAI\n", - "import gradio as gr" + "import gradio as gr " ] }, { diff --git a/week2/community-contributions/day3.upsell.ipynb b/week2/community-contributions/day3.upsell.ipynb index dd2bd06..26a3281 100644 --- a/week2/community-contributions/day3.upsell.ipynb +++ b/week2/community-contributions/day3.upsell.ipynb @@ -43,7 +43,7 @@ "# Load environment variables in a file called .env\n", "# Print the key prefixes to help with any debugging\n", "\n", - "load_dotenv()\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", diff --git a/week2/community-contributions/day4_with_booking_and_multiple_tools_per_message.ipynb b/week2/community-contributions/day4_with_booking_and_multiple_tools_per_message.ipynb index 28aa34e..2e480f1 100644 --- a/week2/community-contributions/day4_with_booking_and_multiple_tools_per_message.ipynb +++ b/week2/community-contributions/day4_with_booking_and_multiple_tools_per_message.ipynb @@ -244,7 +244,7 @@ " },\n", " \"required\": [\"destination_city\", \"price\"],\n", " \"additionalProperties\": False\n", - " }\n", + " } \n", "}" ] }, diff --git a/week2/community-contributions/multi-modal-StudyAI.ipynb b/week2/community-contributions/multi-modal-StudyAI.ipynb new file mode 100644 index 0000000..0cafb5d --- /dev/null +++ b/week2/community-contributions/multi-modal-StudyAI.ipynb @@ -0,0 +1,227 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "id": "6aa646e3-7a57-461a-b69a-073179effa18", + "metadata": {}, + "source": [ + "## Additional End of week Exercise - week 2\n", + "\n", + "This includes \n", + "- Gradio UI\n", + "- use of the system prompt to add expertise\n", + "- audio input so you can talk to it\n", + "- respond with audio" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "72f3dca4-b052-4e9f-90c8-f42e667c165c", + "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 gradio as gr\n", + "import json" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "23570b9f-8c7a-4cc7-b809-3505334b60a7", + "metadata": {}, + "outputs": [], + "source": [ + "# Load environment variables in a file called .env\n", + "\n", + "load_dotenv(override=True)\n", + "openai_api_key = os.getenv('OPENAI_API_KEY')\n", + "openai = OpenAI()\n", + "MODEL = 'gpt-4o-mini'" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "d379178a-8672-4e6f-a380-ad8d85f5c64e", + "metadata": {}, + "outputs": [], + "source": [ + "system_message = \"\"\"You are a personal study tutor, designed to provide clear, yet brief and succint answers to \n", + "students that ask you questions. The topics are related to data science, computer science \n", + "and technology in general, so you are allowed to use a moderate level of jargon. Explain in \n", + "simple terminology, so a student can easily understand. \n", + "\n", + "You may also be asked about prices for special courses.In this case, respond that you have no such\n", + "data available. \n", + "\n", + "\"\"\"\n", + "# Use a tabular format where possible \n", + "# for ease of information flow " + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "4745d439-c66e-4e5c-b5d4-9f0ba97aefdc", + "metadata": {}, + "outputs": [], + "source": [ + "def chat(history):\n", + " messages = [{\"role\": \"system\", \"content\": system_message}] + history\n", + " response = openai.chat.completions.create(model=MODEL, messages=messages)\n", + "\n", + " reply = response.choices[0].message.content\n", + " history += [{\"role\":\"assistant\", \"content\":reply}]\n", + "\n", + " # Comment out or delete the next line if you'd rather skip Audio for now..\n", + " talker(reply)\n", + " \n", + " return history" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "a8b31799-df86-4151-98ea-66ef50fe767e", + "metadata": {}, + "outputs": [], + "source": [ + "!pip install openai-whisper" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "9f5b8e51-2833-44be-a4f4-63c4683f2b6e", + "metadata": {}, + "outputs": [], + "source": [ + "import whisper\n", + "\n", + "def transcribe_audio(audio):\n", + " if audio is None:\n", + " return \"No audio received.\"\n", + " \n", + " model = whisper.load_model(\"base\") # You can use \"tiny\", \"small\", etc.\n", + " result = model.transcribe(audio)\n", + " \n", + " return result[\"text\"]" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "e55f8e43-2da1-4f2a-bcd4-3fffa830db48", + "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", + " 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))" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "cb3107a7-bfdc-4255-825f-bfabcf458c0c", + "metadata": {}, + "outputs": [], + "source": [ + "# More involved Gradio code as we're not using the preset Chat interface!\n", + "# Passing in inbrowser=True in the last line will cause a Gradio window to pop up immediately.\n", + "\n", + "with gr.Blocks() as ui:\n", + " with gr.Row():\n", + " chatbot = gr.Chatbot(height=400,type=\"messages\")\n", + " with gr.Row():\n", + " entry = gr.Textbox(label=\"Chat with our StudyAI Assistant:\")\n", + " # with gr.Row():\n", + " # entry = gr.Textbox(label=\"Speak or Type:\", placeholder=\"Speak your question...\", interactive=True, microphone=True)\n", + " with gr.Row():\n", + " audio_input = gr.Audio(type=\"filepath\", label=\"Speak your question\")\n", + " with gr.Row():\n", + " clear = gr.Button(\"Clear\")\n", + "\n", + " def do_entry(message, history):\n", + " history += [{\"role\":\"user\", \"content\":message}]\n", + " return \"\", history\n", + "\n", + " def handle_audio(audio, history):\n", + " text = transcribe_audio(audio)\n", + " history += [{\"role\": \"user\", \"content\": text}]\n", + " return \"\", history\n", + "\n", + " entry.submit(do_entry, inputs=[entry, chatbot], outputs=[entry, chatbot]).then(\n", + " chat, inputs=[chatbot], outputs=[chatbot]\n", + " )\n", + "\n", + " audio_input.change(handle_audio, inputs=[audio_input, chatbot], outputs=[entry, chatbot]).then(\n", + " chat, inputs=[chatbot], outputs=[chatbot]\n", + " )\n", + " \n", + " clear.click(lambda: [], inputs=None, outputs=chatbot, queue=False)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "73e0a776-d43e-4b04-a37f-a27d3714cf47", + "metadata": {}, + "outputs": [], + "source": [ + "ui.launch(inbrowser=True)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "bcd45503-d314-4b28-a41c-4dbb87059188", + "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 +}