3_lab3.ipynb

{
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  {
   "cell_type": "markdown",
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   "source": [
    "## Welcome to Lab 3 for Week 1 Day 4\n",
    "\n",
    "Today we're going to build something with immediate value!\n",
    "\n",
    "In the folder `me` I've put a single file `linkedin.pdf` - it's a PDF download of my LinkedIn profile.\n",
    "\n",
    "Please replace it with yours!\n",
    "\n",
    "I've also made a file called `summary.txt`\n",
    "\n",
    "We're not going to use Tools just yet - we're going to add the tool tomorrow."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<table style=\"margin: 0; text-align: left; width:100%\">\n",
    "    <tr>\n",
    "        <td style=\"width: 150px; height: 150px; vertical-align: middle;\">\n",
    "            <img src=\"../assets/tools.png\" width=\"150\" height=\"150\" style=\"display: block;\" />\n",
    "        </td>\n",
    "        <td>\n",
    "            <h2 style=\"color:#00bfff;\">Looking up packages</h2>\n",
    "            <span style=\"color:#00bfff;\">In this lab, we're going to use the wonderful Gradio package for building quick UIs, \n",
    "            and we're also going to use the popular PyPDF2 PDF reader. You can get guides to these packages by asking \n",
    "            ChatGPT or Claude, and you find all open-source packages on the repository <a href=\"https://pypi.org\">https://pypi.org</a>.\n",
    "            </span>\n",
    "        </td>\n",
    "    </tr>\n",
    "</table>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "# If you don't know what any of these packages do - you can always ask ChatGPT for a guide!\n",
    "\n",
    "from dotenv import load_dotenv\n",
    "from openai import OpenAI\n",
    "from pypdf import PdfReader\n",
    "import gradio as gr"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "load_dotenv(override=True)\n",
    "openai = OpenAI()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "reader = PdfReader(\"me/linkedin.pdf\")\n",
    "linkedin = \"\"\n",
    "for page in reader.pages:\n",
    "    text = page.extract_text()\n",
    "    if text:\n",
    "        linkedin += text"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "   \n",
      "Contact\n",
      "sean@faheymedia.ie\n",
      "www.linkedin.com/in/seanfaheyire\n",
      "(LinkedIn)\n",
      "Top Skills\n",
      "Journalism\n",
      "Marketing\n",
      "Social Media\n",
      "Languages\n",
      "Spanish (Limited Working)\n",
      "English (Native or Bilingual)\n",
      "Seán Fahey\n",
      "Founder/Digital Communications Specialist at Fahey Media\n",
      "Ireland\n",
      "Summary\n",
      "As the Founder and Digital Communications Specialist at Fahey\n",
      "Media, I help businesses communicate effectively and authentically\n",
      "with their target audiences online. With a decade of experience in\n",
      "managing digital content and social media for various sectors, I have\n",
      "the skills and knowledge to create engaging and impactful digital\n",
      "communication strategies and campaigns.\n",
      "My mission is to help businesses grow their brand awareness, reach,\n",
      "and loyalty through compelling and relevant digital content and social\n",
      "media marketing. Whether it is writing web content, blog posts,\n",
      "newsletters, social media posts, or press releases, I deliver high-\n",
      "quality and professional content that reflects the voice and values of\n",
      "the business. I also offer consultancy and training services on digital\n",
      "communication best practices and trends. Contact me to have a chat\n",
      "about your business' communications needs. Contact card: https://\n",
      "card.link/items/sCes34A/\n",
      "Experience\n",
      "AI Training Solutions\n",
      "Director\n",
      "April 2025 - Present (3 months)\n",
      "Fahey Media\n",
      "Founder/Digital Communications Specialist\n",
      "June 2020 - Present (5 years 1 month)\n",
      "Dublin, Ireland\n",
      "Gibney Communications\n",
      "Head of Digital Communications\n",
      "April 2019 - June 2020 (1 year 3 months)\n",
      "Dublin, Leinster, Ireland\n",
      "Managing the accounts of some of Ireland’s largest companies in the retail,\n",
      "construction and technology sectors.\n",
      "  Page 1 of 2   \n",
      "Irish Daily Star\n",
      "3 years 4 months\n",
      "Digital Content Manager\n",
      "October 2016 - March 2019 (2 years 6 months)\n",
      "County Dublin, Ireland\n",
      "Digital Content Manager of the Irish Daily Star's digital and online presence\n",
      "Buzz.ie.\n",
      "Online Journalist\n",
      "December 2015 - October 2016 (11 months)\n",
      "Dublin, Leinster, Ireland\n",
      "KISC - Kandersteg International Scout Centre\n",
      "PR & Marketing Assistant\n",
      "January 2014 - September 2015 (1 year 9 months)\n",
      "Lead project manager for all website publications and design, as well as any\n",
      "other digital or physical publications compiled by the World Scout Centre. \n",
      "Social media manager across Facebook, Twitter, LinkedIn, Instagram and\n",
      "YouTube.\n",
      "Public Relations head for the World Scout Centre.\n",
      "Project manager at World Scout Jamboree 2015.\n",
      "Carphone Warehouse\n",
      "Sales Assistant\n",
      "May 2010 - May 2013 (3 years 1 month)\n",
      "Senior Sales Consultant, consistently hitting sales targets and scoring highly in\n",
      "customer feedback. \n",
      "Education\n",
      "National University of Ireland, Maynooth\n",
      "Bachelor of Arts (B.A.), Psychology · (2009 - 2012)\n",
      "Coolmine Community School\n",
      " · (2003 - 2009)\n",
      "  Page 2 of 2\n"
     ]
    }
   ],
   "source": [
    "print(linkedin)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "with open(\"me/summary.txt\", \"r\", encoding=\"utf-8\") as f:\n",
    "    summary = f.read()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "name = \"Sean Fahey\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "system_prompt = f\"You are acting as {name}. You are answering questions on {name}'s website, \\\n",
    "particularly questions related to {name}'s career, background, skills and experience. \\\n",
    "Your responsibility is to represent {name} for interactions on the website as faithfully as possible. \\\n",
    "You are given a summary of {name}'s background and LinkedIn profile which you can use to answer questions. \\\n",
    "Be professional and engaging, as if talking to a potential client or future employer who came across the website. \\\n",
    "If you don't know the answer, say so.\"\n",
    "\n",
    "system_prompt += f\"\\n\\n## Summary:\\n{summary}\\n\\n## LinkedIn Profile:\\n{linkedin}\\n\\n\"\n",
    "system_prompt += f\"With this context, please chat with the user, always staying in character as {name}.\"\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "\"You are acting as Sean Fahey. You are answering questions on Sean Fahey's website, particularly questions related to Sean Fahey's career, background, skills and experience. Your responsibility is to represent Sean Fahey for interactions on the website as faithfully as possible. You are given a summary of Sean Fahey's background and LinkedIn profile which you can use to answer questions. Be professional and engaging, as if talking to a potential client or future employer who came across the website. If you don't know the answer, say so.\\n\\n## Summary:\\nMy name is Sean Fahey. I am an entrepreneur based in Ireland specialising in digital marketing and communications. I have a great interest in AI, am currently learning agentic AI and recently launched a corporate AI training company AI Training Solutions, under my parent company Fahey Media - a marketing and communications agency.\\n\\n## LinkedIn Profile:\\n\\xa0 \\xa0\\nContact\\nsean@faheymedia.ie\\nwww.linkedin.com/in/seanfaheyire\\n(LinkedIn)\\nTop Skills\\nJournalism\\nMarketing\\nSocial Media\\nLanguages\\nSpanish (Limited Working)\\nEnglish (Native or Bilingual)\\nSeán Fahey\\nFounder/Digital Communications Specialist at Fahey Media\\nIreland\\nSummary\\nAs the Founder and Digital Communications Specialist at Fahey\\nMedia, I help businesses communicate effectively and authentically\\nwith their target audiences online. With a decade of experience in\\nmanaging digital content and social media for various sectors, I have\\nthe skills and knowledge to create engaging and impactful digital\\ncommunication strategies and campaigns.\\nMy mission is to help businesses grow their brand awareness, reach,\\nand loyalty through compelling and relevant digital content and social\\nmedia marketing. Whether it is writing web content, blog posts,\\nnewsletters, social media posts, or press releases, I deliver high-\\nquality and professional content that reflects the voice and values of\\nthe business. I also offer consultancy and training services on digital\\ncommunication best practices and trends. Contact me to have a chat\\nabout your business' communications needs. Contact card: https://\\ncard.link/items/sCes34A/\\nExperience\\nAI Training Solutions\\nDirector\\nApril 2025\\xa0-\\xa0Present\\xa0(3 months)\\nFahey Media\\nFounder/Digital Communications Specialist\\nJune 2020\\xa0-\\xa0Present\\xa0(5 years 1 month)\\nDublin, Ireland\\nGibney Communications\\nHead of Digital Communications\\nApril 2019\\xa0-\\xa0June 2020\\xa0(1 year 3 months)\\nDublin, Leinster, Ireland\\nManaging the accounts of some of Ireland’s largest companies in the retail,\\nconstruction and technology sectors.\\n\\xa0 Page 1 of 2\\xa0 \\xa0\\nIrish Daily Star\\n3 years 4 months\\nDigital Content Manager\\nOctober 2016\\xa0-\\xa0March 2019\\xa0(2 years 6 months)\\nCounty Dublin, Ireland\\nDigital Content Manager of the Irish Daily Star's digital and online presence\\nBuzz.ie.\\nOnline Journalist\\nDecember 2015\\xa0-\\xa0October 2016\\xa0(11 months)\\nDublin, Leinster, Ireland\\nKISC - Kandersteg International Scout Centre\\nPR & Marketing Assistant\\nJanuary 2014\\xa0-\\xa0September 2015\\xa0(1 year 9 months)\\nLead project manager for all website publications and design, as well as any\\nother digital or physical publications compiled by the World Scout Centre. \\nSocial media manager across Facebook, Twitter, LinkedIn, Instagram and\\nYouTube.\\nPublic Relations head for the World Scout Centre.\\nProject manager at World Scout Jamboree 2015.\\nCarphone Warehouse\\nSales Assistant\\nMay 2010\\xa0-\\xa0May 2013\\xa0(3 years 1 month)\\nSenior Sales Consultant, consistently hitting sales targets and scoring highly in\\ncustomer feedback. \\nEducation\\nNational University of Ireland, Maynooth\\nBachelor of Arts (B.A.),\\xa0Psychology\\xa0·\\xa0(2009\\xa0-\\xa02012)\\nCoolmine Community School\\n\\xa0·\\xa0(2003\\xa0-\\xa02009)\\n\\xa0 Page 2 of 2\\n\\nWith this context, please chat with the user, always staying in character as Sean Fahey.\""
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "system_prompt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "def chat(message, history):\n",
    "    messages = [{\"role\": \"system\", \"content\": system_prompt}] + history + [{\"role\": \"user\", \"content\": message}]\n",
    "    response = openai.chat.completions.create(model=\"gpt-4o-mini\", messages=messages)\n",
    "    return response.choices[0].message.content"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "* Running on local URL:  http://127.0.0.1:7860\n",
      "* To create a public link, set `share=True` in `launch()`.\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div><iframe src=\"http://127.0.0.1:7860/\" width=\"100%\" height=\"500\" allow=\"autoplay; camera; microphone; clipboard-read; clipboard-write;\" frameborder=\"0\" allowfullscreen></iframe></div>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
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     "output_type": "display_data"
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    {
     "data": {
      "text/plain": []
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "gr.ChatInterface(chat, type=\"messages\").launch()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## A lot is about to happen...\n",
    "\n",
    "1. Be able to ask an LLM to evaluate an answer\n",
    "2. Be able to rerun if the answer fails evaluation\n",
    "3. Put this together into 1 workflow\n",
    "\n",
    "All without any Agentic framework!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Create a Pydantic model for the Evaluation\n",
    "\n",
    "from pydantic import BaseModel\n",
    "\n",
    "class Evaluation(BaseModel):\n",
    "    is_acceptable: bool\n",
    "    feedback: str\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "evaluator_system_prompt = f\"You are an evaluator that decides whether a response to a question is acceptable. \\\n",
    "You are provided with a conversation between a User and an Agent. Your task is to decide whether the Agent's latest response is acceptable quality. \\\n",
    "The Agent is playing the role of {name} and is representing {name} on their website. \\\n",
    "The Agent has been instructed to be professional and engaging, as if talking to a potential client or future employer who came across the website. \\\n",
    "The Agent has been provided with context on {name} in the form of their summary and LinkedIn details. Here's the information:\"\n",
    "\n",
    "evaluator_system_prompt += f\"\\n\\n## Summary:\\n{summary}\\n\\n## LinkedIn Profile:\\n{linkedin}\\n\\n\"\n",
    "evaluator_system_prompt += f\"With this context, please evaluate the latest response, replying with whether the response is acceptable and your feedback.\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "def evaluator_user_prompt(reply, message, history):\n",
    "    user_prompt = f\"Here's the conversation between the User and the Agent: \\n\\n{history}\\n\\n\"\n",
    "    user_prompt += f\"Here's the latest message from the User: \\n\\n{message}\\n\\n\"\n",
    "    user_prompt += f\"Here's the latest response from the Agent: \\n\\n{reply}\\n\\n\"\n",
    "    user_prompt += f\"Please evaluate the response, replying with whether it is acceptable and your feedback.\"\n",
    "    return user_prompt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "import os\n",
    "gemini = OpenAI(\n",
    "    api_key=os.getenv(\"GOOGLE_API_KEY\"), \n",
    "    base_url=\"https://generativelanguage.googleapis.com/v1beta/openai/\"\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "def evaluate(reply, message, history) -> Evaluation:\n",
    "\n",
    "    messages = [{\"role\": \"system\", \"content\": evaluator_system_prompt}] + [{\"role\": \"user\", \"content\": evaluator_user_prompt(reply, message, history)}]\n",
    "    response = gemini.beta.chat.completions.parse(model=\"gemini-2.0-flash\", messages=messages, response_format=Evaluation)\n",
    "    return response.choices[0].message.parsed"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "messages = [{\"role\": \"system\", \"content\": system_prompt}] + [{\"role\": \"user\", \"content\": \"do you hold a patent?\"}]\n",
    "response = openai.chat.completions.create(model=\"gpt-4o-mini\", messages=messages)\n",
    "reply = response.choices[0].message.content"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'I do not hold any patents at this time. My focus has primarily been on digital marketing, communications, and recent ventures into AI training through AI Training Solutions. If you have any questions regarding my work or expertise in those areas, I’d be happy to help!'"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "reply"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Evaluation(is_acceptable=True, feedback='The response is good. It answers the question directly and then pivots to what Sean is actually working on.')"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "evaluate(reply, \"do you hold a patent?\", messages[:1])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "def rerun(reply, message, history, feedback):\n",
    "    updated_system_prompt = system_prompt + f\"\\n\\n## Previous answer rejected\\nYou just tried to reply, but the quality control rejected your reply\\n\"\n",
    "    updated_system_prompt += f\"## Your attempted answer:\\n{reply}\\n\\n\"\n",
    "    updated_system_prompt += f\"## Reason for rejection:\\n{feedback}\\n\\n\"\n",
    "    messages = [{\"role\": \"system\", \"content\": updated_system_prompt}] + history + [{\"role\": \"user\", \"content\": message}]\n",
    "    response = openai.chat.completions.create(model=\"gpt-4o-mini\", messages=messages)\n",
    "    return response.choices[0].message.content"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "def chat(message, history):\n",
    "    if \"patent\" in message:\n",
    "        system = system_prompt + \"\\n\\nEverything in your reply needs to be in pig latin - \\\n",
    "              it is mandatory that you respond only and entirely in pig latin\"\n",
    "    else:\n",
    "        system = system_prompt\n",
    "    messages = [{\"role\": \"system\", \"content\": system}] + history + [{\"role\": \"user\", \"content\": message}]\n",
    "    response = openai.chat.completions.create(model=\"gpt-4o-mini\", messages=messages)\n",
    "    reply =response.choices[0].message.content\n",
    "\n",
    "    evaluation = evaluate(reply, message, history)\n",
    "    \n",
    "    if evaluation.is_acceptable:\n",
    "        print(\"Passed evaluation - returning reply\")\n",
    "    else:\n",
    "        print(\"Failed evaluation - retrying\")\n",
    "        print(evaluation.feedback)\n",
    "        reply = rerun(reply, message, history, evaluation.feedback)       \n",
    "    return reply"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "* Running on local URL:  http://127.0.0.1:7862\n",
      "* Running on public URL: https://5020e028d1564a14fc.gradio.live\n",
      "\n",
      "This share link expires in 1 week. 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": [
       "<div><iframe src=\"https://5020e028d1564a14fc.gradio.live\" width=\"100%\" height=\"500\" allow=\"autoplay; camera; microphone; clipboard-read; clipboard-write;\" frameborder=\"0\" allowfullscreen></iframe></div>"
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     "execution_count": 23,
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   ],
   "source": [
    "gr.ChatInterface(chat, type=\"messages\").launch(share=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": []
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  {
   "cell_type": "code",
   "execution_count": null,
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