\n",
- " ![](\"../assets/important.jpg\") \n",
- " | \n",
- " \n",
- " Important Note - Please read me\n", - " I'm continually improving these labs, adding more examples and exercises.\n", - " At the start of each week, it's worth checking you have the latest code.\n", - " First do a git pull and merge your changes as needed. Check out the GitHub guide for instructions. Any problems? Try asking ChatGPT to clarify how to merge - or contact me! \n", - " \n", - " | \n",
- "
\n",
- " ![](\"../assets/resources.jpg\") \n",
- " | \n",
- " \n",
- " Reminder about the resources page\n", - " Here's a link to resources for the course. This includes links to all the slides.\n", - " https://edwarddonner.com/2024/11/13/llm-engineering-resources/ \n", - " Please keep this bookmarked, and I'll continue to add more useful links there over time.\n", - " \n", - " | \n",
- "
| \n",
- " \n",
- " | \n",
- " \n",
- " Any time you change your .env file\n", - " Remember to Save it! And also rerun load_dotenv(override=True)\n", - " \n", - " | \n",
- "
| \n",
- " \n",
- " | \n",
- " \n",
- " Before you continue\n", - " \n", - " Be sure you understand how the conversation above is working, and in particular how themessages list is being populated. Add print statements as needed. Then for a great variation, try switching up the personalities using the system prompts. Perhaps one can be pessimistic, and one optimistic?\n", - " \n", - " | \n",
- "
\n",
- " ![](\"../assets/business.jpg\") \n",
- " | \n",
- " \n",
- " Business relevance\n", - " This structure of a conversation, as a list of messages, is fundamental to the way we build conversational AI assistants and how they are able to keep the context during a conversation. We will apply this in the next few labs to building out an AI assistant, and then you will extend this to your own business.\n", - " | \n",
- "
| \n",
+ " \n",
+ " | \n",
+ " \n",
+ " Important Note - Please read me\n", + " I'm continually improving these labs, adding more examples and exercises.\n", + " At the start of each week, it's worth checking you have the latest code.\n", + " First do a git pull and merge your changes as needed. Check out the GitHub guide for instructions. Any problems? Try asking ChatGPT to clarify how to merge - or contact me! \n", + " \n", + " | \n",
+ "
| \n",
+ " \n",
+ " | \n",
+ " \n",
+ " Reminder about the resources page\n", + " Here's a link to resources for the course. This includes links to all the slides.\n", + " https://edwarddonner.com/2024/11/13/llm-engineering-resources/ \n", + " Please keep this bookmarked, and I'll continue to add more useful links there over time.\n", + " \n", + " | \n",
+ "
| \n",
+ " \n",
+ " | \n",
+ " \n",
+ " Any time you change your .env file\n", + " Remember to Save it! And also rerun load_dotenv(override=True)\n", + " \n", + " | \n",
+ "
| \n",
+ " \n",
+ " | \n",
+ " \n",
+ " Before you continue\n", + " \n", + " Be sure you understand how the conversation above is working, and in particular how themessages list is being populated. Add print statements as needed. Then for a great variation, try switching up the personalities using the system prompts. Perhaps one can be pessimistic, and one optimistic?\n", + " \n", + " | \n",
+ "
| \n",
+ " \n",
+ " | \n",
+ " \n",
+ " Business relevance\n", + " This structure of a conversation, as a list of messages, is fundamental to the way we build conversational AI assistants and how they are able to keep the context during a conversation. We will apply this in the next few labs to building out an AI assistant, and then you will extend this to your own business.\n", + " | \n",
+ "
| \n",
+ " \n",
+ " | \n",
+ " \n",
+ " Please read - important note\n", + " The way I collaborate with you may be different to other courses you've taken. I prefer not to type code while you watch. Rather, I execute Jupyter Labs, like this, and give you an intuition for what's going on. My suggestion is that you carefully execute this yourself, after watching the lecture. Add print statements to understand what's going on, and then come up with your own variations. If you have a Github account, use this to showcase your variations. Not only is this essential practice, but it demonstrates your skills to others, including perhaps future clients or employers...\n", + " | \n",
+ "
| \n",
+ " \n",
+ " | \n",
+ " \n",
+ " This code is a live resource - keep an eye out for my emails\n", + " I push updates to the code regularly. As people ask questions, I add more examples or improved commentary. As a result, you'll notice that the code below isn't identical to the videos. Everything from the videos is here; but I've also added better explanations and new models like DeepSeek. Consider this like an interactive book.\n", + " I try to send emails regularly with important updates related to the course. You can find this in the 'Announcements' section of Udemy in the left sidebar. You can also choose to receive my emails via your Notification Settings in Udemy. I'm respectful of your inbox and always try to add value with my emails!\n", + " \n", + " | \n",
+ "
| \n",
+ " \n",
+ " | \n",
+ " \n",
+ " Business value of these exercises\n", + " A final thought. While I've designed these notebooks to be educational, I've also tried to make them enjoyable. We'll do fun things like have LLMs tell jokes and argue with each other. But fundamentally, my goal is to teach skills you can apply in business. I'll explain business implications as we go, and it's worth keeping this in mind: as you build experience with models and techniques, think of ways you could put this into action at work today. Please do contact me if you'd like to discuss more or if you have ideas to bounce off me.\n", + " | \n",
+ "
| \n",
+ " \n",
+ " | \n",
+ " \n",
+ " Business applications\n", + " In this exercise, you experienced calling the Cloud API of a Frontier Model (a leading model at the frontier of AI) for the first time. We will be using APIs like OpenAI at many stages in the course, in addition to building our own LLMs.\n", + "\n", + "More specifically, we've applied this to Summarization - a classic Gen AI use case to make a summary. This can be applied to any business vertical - summarizing the news, summarizing financial performance, summarizing a resume in a cover letter - the applications are limitless. Consider how you could apply Summarization in your business, and try prototyping a solution.\n", + " | \n",
+ "
| \n",
+ " \n",
+ " | \n",
+ " \n",
+ " Before you continue - now try yourself\n", + " Use the cell below to make your own simple commercial example. Stick with the summarization use case for now. Here's an idea: write something that will take the contents of an email, and will suggest an appropriate short subject line for the email. That's the kind of feature that might be built into a commercial email tool.\n", + " | \n",
+ "
\n",
+ " ![](\"../../assets/resources.jpg\") \n",
+ " | \n",
+ " \n",
+ " Just before we get started --\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", + " | \n",
+ "
\n",
+ " ![](\"../../assets/business.jpg\") \n",
+ " | \n",
+ " \n",
+ " Business applications\n", + " In this exercise we extended the Day 1 code to make multiple LLM calls, and generate a document.\n", + "\n", + "This is perhaps the first example of Agentic AI design patterns, as we combined multiple calls to LLMs. This will feature more in Week 2, and then we will return to Agentic AI in a big way in Week 8 when we build a fully autonomous Agent solution.\n", + "\n", + "Generating content in this way is one of the very most common Use Cases. As with summarization, this can be applied to any business vertical. Write marketing content, generate a product tutorial from a spec, create personalized email content, and so much more. Explore how you can apply content generation to your business, and try making yourself a proof-of-concept prototype. See what other students have done in the community-contributions folder -- so many valuable projects -- it's wild!\n", + " | \n",
+ "
\n",
+ " ![](\"../../assets/important.jpg\") \n",
+ " | \n",
+ " \n",
+ " Before you move to Week 2 (which is tons of fun)\n", + " Please see the week1 EXERCISE notebook for your challenge for the end of week 1. This will give you some essential practice working with Frontier APIs, and prepare you well for Week 2.\n", + " | \n",
+ "
| \n",
+ " \n",
+ " | \n",
+ " \n",
+ " A reminder on 3 useful resources\n", + " 1. The resources for the course are available here.\n", + " 2. I'm on LinkedIn here and I love connecting with people taking the course! \n", + " 3. I'm trying out X/Twitter and I'm at @edwarddonner and hoping people will teach me how it's done.. \n", + " \n", + " | \n",
+ "
\n",
+ " ![](\"../../assets/thankyou.jpg\") \n",
+ " | \n",
+ " \n",
+ " Finally! I have a special request for you\n", + " \n", + " My editor tells me that it makes a MASSIVE difference when students rate this course on Udemy - it's one of the main ways that Udemy decides whether to show it to others. If you're able to take a minute to rate this, I'd be so very grateful! And regardless - always please reach out to me at ed@edwarddonner.com if I can help at any point.\n", + " \n", + " | \n",
+ "
| \n",
+ " \n",
+ " | \n",
+ " \n",
+ " Important Note - Please read me\n", + " I'm continually improving these labs, adding more examples and exercises.\n", + " At the start of each week, it's worth checking you have the latest code.\n", + " First do a git pull and merge your changes as needed. Check out the GitHub guide for instructions. Any problems? Try asking ChatGPT to clarify how to merge - or contact me! \n", + " \n", + " | \n",
+ "
| \n",
+ " \n",
+ " | \n",
+ " \n",
+ " Reminder about the resources page\n", + " Here's a link to resources for the course. This includes links to all the slides.\n", + " https://edwarddonner.com/2024/11/13/llm-engineering-resources/ \n", + " Please keep this bookmarked, and I'll continue to add more useful links there over time.\n", + " \n", + " | \n",
+ "
| \n",
+ " \n",
+ " | \n",
+ " \n",
+ " Any time you change your .env file\n", + " Remember to Save it! And also rerun load_dotenv(override=True)\n", + " \n", + " | \n",
+ "
| \n",
+ " \n",
+ " | \n",
+ " \n",
+ " Before you continue\n", + " \n", + " Be sure you understand how the conversation above is working, and in particular how themessages list is being populated. Add print statements as needed. Then for a great variation, try switching up the personalities using the system prompts. Perhaps one can be pessimistic, and one optimistic?\n", + " \n", + " | \n",
+ "
| \n",
+ " \n",
+ " | \n",
+ " \n",
+ " Business relevance\n", + " This structure of a conversation, as a list of messages, is fundamental to the way we build conversational AI assistants and how they are able to keep the context during a conversation. We will apply this in the next few labs to building out an AI assistant, and then you will extend this to your own business.\n", + " | \n",
+ "
| \n",
+ " \n",
+ " | \n",
+ " \n",
+ " NOTE: Using Gradio's Share tool\n", + " I'm about to show you a really cool way to share your Gradio UI with others. This deploys your gradio app as a demo on gradio's website, and then allows gradio to call the 'shout' function. This uses an advanced technology known as 'HTTP tunneling' (like ngrok for people who know it) which isn't allowed by many Antivirus programs and corporate environments. If you get an error, just skip the next cell.\n", + " \n", + " | \n",
+ "
| \n",
+ " \n",
+ " | \n",
+ " \n",
+ " Before you read the next few cells\n", + " \n", + " Try to do this yourself - go back to the company brochure in week1, day5 and add a Gradio UI to the end. Then come and look at the solution.\n", + " \n", + " | \n",
+ "
| \n",
+ " \n",
+ " | \n",
+ " \n",
+ " Gradio Resources\n", + " If you'd like to go deeper on Gradio, check out the amazing documentation - a wonderful rabbit hole.\n", + " https://www.gradio.app/guides/quickstart Gradio is primarily designed for Demos, Prototypes and MVPs, but I've also used it frequently to make internal apps for power users.\n", + " \n", + " | \n",
+ "
| \n",
+ " \n",
+ " | \n",
+ " \n",
+ " Business Applications\n", + " Conversational Assistants are of course a hugely common use case for Gen AI, and the latest frontier models are remarkably good at nuanced conversation. And Gradio makes it easy to have a user interface. Another crucial skill we covered is how to use prompting to provide context, information and examples.\n", + "\n", + "Consider how you could apply an AI Assistant to your business, and make yourself a prototype. Use the system prompt to give context on your business, and set the tone for the LLM.\n", + " | \n",
+ "
| \n",
+ " \n",
+ " | \n",
+ " \n",
+ " Business Applications\n", + " Hopefully this hardly needs to be stated! You now have the ability to give actions to your LLMs. This Airline Assistant can now do more than answer questions - it could interact with booking APIs to make bookings!\n", + " | \n",
+ "
| \n",
+ " \n",
+ " | \n",
+ " \n",
+ " I have a special request for you\n", + " \n", + " My editor tells me that it makes a HUGE difference when students rate this course on Udemy - it's one of the main ways that Udemy decides whether to show it to others. If you're able to take a minute to rate this, I'd be so very grateful! And regardless - always please reach out to me at ed@edwarddonner.com if I can help at any point.\n", + " \n", + " | \n",
+ "
No results.
\" if format == \"html\" else \"No results.\"\n", + " c, cur, p = max(rows, key=lambda x: x[2])\n", + " if format == \"html\":\n", + " trs = \"\".join(\n", + " f\"| Country (currency) | Estimated price |
|---|
Most expensive: {c} ({cur}) \u2014 {p:,.0f}
\"\n", + " )\n", + " lines = [\"| Country (currency) | Estimated price |\", \"|--------------------|----------------|\"]\n", + " for country, currency, price in rows:\n", + " lines.append(f\"| {country} ({currency}) | {price:,.0f} |\")\n", + " lines.append(\"\")\n", + " lines.append(f\"**Most expensive:** {c} ({cur}) \u2014 {p:,.0f}\")\n", + " return \"\\n\".join(lines)\n", + "\n", + "# Quick demo (optional: run on one product)\n", + "# demo_desc = \"50 kg bag of imported long-grain rice, wholesale or retail, urban West Africa.\"\n", + "# print(cross_country_table(demo_desc))" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Going further (Day 1\u20135 in the main repo)\n", + "\n", + "To go deeper into the full Week 6 curriculum (same repo, `week6/` folder):\n", + "\n", + "- **Day 1** \u2014 Curate data from [Amazon-Reviews-2023](https://huggingface.co/datasets/McAuley-Lab/Amazon-Reviews-2023), filter and sample, push to HuggingFace. Requires `pricer` package and `HF_TOKEN`.\n", + "- **Day 2** \u2014 Pre-process with an LLM (rewrite product text), Groq batch API, push processed dataset to Hub.\n", + "- **Day 3** \u2014 Compare baselines (random, constant, linear regression, Random Forest, XGBoost) using `pricer.evaluator.evaluate`.\n", + "- **Day 4** \u2014 Train a PyTorch neural network on bag-of-words; then compare frontier LLMs (GPT, Claude, Gemini, Grok) via LiteLLM.\n", + "- **Day 5** \u2014 Fine-tune a frontier model (e.g. GPT-4.1-nano) on (summary, price) pairs with the OpenAI fine-tuning API.\n", + "\n", + "This notebook stays **self-contained** (no `pricer`, no HuggingFace): we use CSV or the West Africa sample, a constant baseline, and an LLM predictor." + ], + "outputs": [], + "execution_count": null + }, + { + "cell_type": "markdown", + "id": "f36f28db-d59", + "metadata": {}, + "source": [ + "## Optional: Gradio UI\n", + "\n", + "Two tabs: (1) **Single price (XOF)** \u2014 one estimate in West African CFA franc for ECOWAS/UEMOA use. (2) **Cross-country (ECOWAS)** \u2014 same product in Ghana (GHS), Nigeria (NGN), C\u00f4te d'Ivoire (XOF)." + ], + "outputs": [], + "execution_count": null + }, + { + "cell_type": "code", + "execution_count": null, + "id": "41ebb883-ef7", + "metadata": {}, + "outputs": [], + "source": [ + "import gradio as gr\n", + "\n", + "def ui_predict(description: str) -> str:\n", + " if not description.strip():\n", + " return \"Enter a product description.\"\n", + " p = predict_price(description.strip())\n", + " return f\"Estimated price: {p:,.0f} XOF\"\n", + "\n", + "def ui_cross_country(description: str) -> str:\n", + " if not description.strip():\n", + " return \"Enter a product description to compare across ECOWAS countries.
\"\n", + " return cross_country_table(description, format=\"html\")\n", + "\n", + "with gr.Blocks(title=\"Week 6 \u2014 Price predictor (West Africa, ECOWAS)\") as app:\n", + " gr.Markdown(\"**West Africa price predictor (ECOWAS)** \u2014 default **XOF**. Single price (XOF) or cross-country (NGN, GHS, XOF).\")\n", + " with gr.Tabs():\n", + " with gr.Tab(\"Single price (XOF)\"):\n", + " inp1 = gr.Textbox(label=\"Product description\", lines=4)\n", + " out1 = gr.Textbox(label=\"Estimated price (XOF, West Africa)\")\n", + " gr.Button(\"Estimate\").click(fn=ui_predict, inputs=inp1, outputs=out1)\n", + " with gr.Tab(\"Cross-country (ECOWAS)\"):\n", + " inp2 = gr.Textbox(label=\"Product description\", lines=4)\n", + " out2 = gr.HTML(label=\"Price by country\")\n", + " gr.Button(\"Compare\").click(fn=ui_cross_country, inputs=inp2, outputs=out2)\n", + "app.launch()" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": ".venv", + "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": "3.13.3" + } + }, + "nbformat": 4, + "nbformat_minor": 4 +} \ No newline at end of file diff --git a/extras/community/prototype_signal.ipynb b/extras/community/prototype_signal.ipynb index 58da337b3..41fdadaf9 100644 --- a/extras/community/prototype_signal.ipynb +++ b/extras/community/prototype_signal.ipynb @@ -45,7 +45,7 @@ "BASE_URL = 'https://rest.coinapi.io/v1/ohlcv/'\n", "OLLAMA_URL = \"http://localhost:11434/v1\"\n", "\n", - "os.environ['OPENAI_API_KEY'] = os.getenv('OPENAI_API_KEY', 'your-key-if-not-using-env')\n", + "os.environ['OPENROUTER_API_KEY'] = os.getenv('OPENROUTER_API_KEY', 'your-key-if-not-using-env')\n", "# URL to fetch the OHLCV data\n" ] }, diff --git a/guides/03_git_and_github.ipynb b/guides/03_git_and_github.ipynb index a1a5ae9bc..fe80a83a7 100644 --- a/guides/03_git_and_github.ipynb +++ b/guides/03_git_and_github.ipynb @@ -1,90 +1,158 @@ { - "cells": [ - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# Git and Github" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "This guide is all about using source code control: Git and Github.\n", - "\n", - "By the end of this, you should be confident with every day code control processes, including fetching the latest code and submitting a PR to merge your own changes." - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Foundational briefing\n", - "\n", - "Here is Git and Github for a PC or Mac audience:\n", - "\n", - "https://chatgpt.com/share/68061486-08b8-8012-97bc-3264ad5ebcd4" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Pulling latest code\n", - "\n", - "I regularly add improvements to the course with new examples, exercises and materials.\n", - "\n", - "Here are instructions for how to bring in the latest - the easy way, and the rigorous way!\n", - "\n", - "https://chatgpt.com/share/6806178b-0700-8012-836f-7e87b2670b7b" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Contributing your changes to the repo to share your contributions with others\n", - "\n", - "I'd be so grateful to include your contributions. It adds value for all other students, and I love to see it myself! As an added benefit, you get recognition in Github as a contributor to the repo.\n", - "\n", - "Here's the overall steps involved in making a PR and the key instructions: \n", - "https://edwarddonner.com/pr \n", - "\n", - "Please check before submitting: \n", - "1. Your PR only contains changes in community-contributions (unless we've discussed it) \n", - "2. All notebook outputs are clear \n", - "3. Less than 2,000 lines of code in total, and not too many files \n", - "4. Don't include unnecessary test files, or overly wordy README or .env.example or emojis or other LLM artifacts!\n", - "\n", - "Thanks so much!\n", - "\n", - "Detailed steps here: \n", - "\n", - "https://chatgpt.com/share/6873c22b-2a1c-8012-bc9a-debdcf7c835b\n" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "vscode": { - "languageId": "plaintext" + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Git and Github" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "This guide is all about using source code control: Git and Github.\n", + "\n", + "By the end of this, you should be confident with every day code control processes, including fetching the latest code and submitting a PR to merge your own changes." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Foundational briefing\n", + "\n", + "Here is Git and Github for a PC or Mac audience:\n", + "\n", + "https://chatgpt.com/share/68061486-08b8-8012-97bc-3264ad5ebcd4" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Pulling latest code\n", + "\n", + "I regularly add improvements to the course with new examples, exercises and materials.\n", + "\n", + "Here are instructions for how to bring in the latest - the easy way, and the rigorous way!\n", + "\n", + "https://chatgpt.com/share/6806178b-0700-8012-836f-7e87b2670b7b" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "**Steps to pull the latest code** (run these in your terminal from the repo root):\n", + "\n", + "**Easy way** – merge upstream into your current branch:\n", + "```bash\n", + "git fetch upstream\n", + "git merge upstream/main\n", + "```\n", + "\n", + "**Rigorous way** – keep a clean history by rebasing your work on top of upstream:\n", + "```bash\n", + "git fetch upstream\n", + "git rebase upstream/main\n", + "```\n", + "(If you already pushed your branch, after rebase you may need `git push --force-with-lease`.)\n", + "\n", + "Make sure `upstream` points at the course repo. If not:\n", + "```bash\n", + "git remote add upstream https://github.com/ed-donner/llm_engineering.git\n", + "```" + ] + }, + { + "cell_type": "code", + "metadata": {}, + "source": [ + "# Quick check: list remotes and current branch (run from repo root, e.g. in Terminal: cd /path/to/llm_engineering)\n", + "import subprocess\n", + "try:\n", + " print(subprocess.check_output([\"git\", \"remote\", \"-v\"], text=True))\n", + " print(\"Current branch:\", subprocess.check_output([\"git\", \"branch\", \"--show-current\"], text=True).strip())\n", + "except Exception as e:\n", + " print(\"Run from repo root in Terminal: git remote -v && git branch --show-current. Error:\", e)" + ], + "execution_count": null, + "outputs": [] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Contributing your changes to the repo to share your contributions with others\n", + "\n", + "I'd be so grateful to include your contributions. It adds value for all other students, and I love to see it myself! As an added benefit, you get recognition in Github as a contributor to the repo.\n", + "\n", + "Here's the overall steps involved in making a PR and the key instructions: \n", + "https://edwarddonner.com/pr \n", + "\n", + "Please check before submitting: \n", + "1. Your PR only contains changes in community-contributions (unless we've discussed it) \n", + "2. All notebook outputs are clear \n", + "3. Less than 2,000 lines of code in total, and not too many files \n", + "4. Don't include unnecessary test files, or overly wordy README or .env.example or emojis or other LLM artifacts!\n", + "\n", + "Thanks so much!\n", + "\n", + "Detailed steps here: \n", + "\n", + "https://chatgpt.com/share/6873c22b-2a1c-8012-bc9a-debdcf7c835b\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "**PR workflow – quick steps**\n", + "\n", + "1. **Fork** the repo on GitHub (if you haven’t already) and clone your fork.\n", + "2. **Create a branch** for your contribution:\n", + " ```bash\n", + " git checkout -b my-contribution\n", + " ```\n", + "3. **Make changes** (only in `community-contributions/` unless agreed otherwise).\n", + "4. **Commit and push** to your fork:\n", + " ```bash\n", + " git add community-contributions/your-project/\n", + " git commit -m \"Add: short description of your contribution\"\n", + " git push origin my-contribution\n", + " ```\n", + "5. **Open a Pull Request** on GitHub from your branch to `ed-donner/llm_engineering` main.\n", + "\n", + "**Before you submit – checklist**\n", + "\n", + "- [ ] Changes are only in `community-contributions/` (unless we’ve agreed otherwise).\n", + "- [ ] Notebook outputs are clear.\n", + "- [ ] Total change is under 2,000 lines and not too many files.\n", + "- [ ] No unnecessary test files, long READMEs, `.env.example`, emojis, or other LLM clutter." + ] + }, + { + "cell_type": "markdown", + "metadata": { + "vscode": { + "languageId": "plaintext" + } + }, + "source": [ + "### If you'd like to become a Git pro\n", + "\n", + "If you want to go deep on using Git, here is a brilliant guide. Read this and you will know much more than me!\n", + "\n", + "https://beej.us/guide/bggit/\n" + ] + } + ], + "metadata": { + "language_info": { + "name": "python" } - }, - "source": [ - "### If you'd like to become a Git pro\n", - "\n", - "If you want to go deep on using Git, here is a brilliant guide. Read this and you will know much more than me!\n", - "\n", - "https://beej.us/guide/bggit/\n" - ] - } - ], - "metadata": { - "language_info": { - "name": "python" - } - }, - "nbformat": 4, - "nbformat_minor": 2 -} + }, + "nbformat": 4, + "nbformat_minor": 2 +} \ No newline at end of file diff --git a/guides/09_ai_apis_and_ollama.ipynb b/guides/09_ai_apis_and_ollama.ipynb index e0b3c782e..b65fe52c4 100644 --- a/guides/09_ai_apis_and_ollama.ipynb +++ b/guides/09_ai_apis_and_ollama.ipynb @@ -357,7 +357,7 @@ " \n", "# Create OpenAI client using Azure OpenAI\n", "openai_client = AsyncAzureOpenAI(\n", - " api_key=os.getenv(\"AZURE_OPENAI_API_KEY\"),\n", + " api_key=os.getenv(\"AZURE_OPENROUTER_API_KEY\"),\n", " api_version=os.getenv(\"AZURE_OPENAI_API_VERSION\"),\n", " azure_endpoint=os.getenv(\"AZURE_OPENAI_ENDPOINT\"),\n", " azure_deployment=os.getenv(\"AZURE_OPENAI_DEPLOYMENT\")\n", diff --git a/pyproject.toml b/pyproject.toml index 3758ea461..e5243801c 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -51,3 +51,8 @@ dependencies = [ "groq>=0.33.0", "xgboost>=3.1.1", ] + +[tool.setuptools] +packages = [] +# Repo is notebooks + community contributions; no single Python package to install. +# Install deps via: uv sync OR pip install -r requirements.txt diff --git a/render.yaml b/render.yaml new file mode 100644 index 000000000..77bf92904 --- /dev/null +++ b/render.yaml @@ -0,0 +1,22 @@ +# Deploy Reputation_Radar to Render (https://render.com) +# 1. Push this repo to GitHub +# 2. Render Dashboard → New → Blueprint → connect this repo +# 3. Add OPENROUTER_API_KEY (and optional Reddit/Trustpilot keys) in Environment +# 4. Deploy + +services: + - type: web + name: reputation-radar + runtime: python + rootDir: community-contributions/Reputation_Radar + buildCommand: pip install -r requirements.txt + startCommand: streamlit run app.py --server.port=$PORT --server.address=0.0.0.0 + envVars: + - key: OPENROUTER_API_KEY + sync: false + - key: REDDIT_CLIENT_ID + sync: false + - key: REDDIT_CLIENT_SECRET + sync: false + - key: REDDIT_USER_AGENT + sync: false diff --git a/scripts/install_deps.sh b/scripts/install_deps.sh new file mode 100644 index 000000000..af9f05dcd --- /dev/null +++ b/scripts/install_deps.sh @@ -0,0 +1,25 @@ +#!/usr/bin/env bash +# Install all dependencies for llm_engineering. +# Run from repo root: bash scripts/install_deps.sh + +set -e +cd "$(dirname "$0")/.." + +echo "=== Installing dependencies for llm_engineering ===" + +if command -v uv &>/dev/null; then + echo "Using uv..." + uv self update 2>/dev/null || true + uv sync + echo "Done. Use: uv run python ... or uv run jupyter lab" + exit 0 +fi + +echo "uv not found. Using pip + venv..." +if [[ ! -d .venv ]]; then + python3 -m venv .venv +fi +source .venv/bin/activate +pip install --upgrade pip +pip install -r requirements.txt +echo "Done. Activate with: source .venv/bin/activate" diff --git a/setup/SETUP-PC.md b/setup/SETUP-PC.md index c1d2ee988..ac1c37c78 100644 --- a/setup/SETUP-PC.md +++ b/setup/SETUP-PC.md @@ -164,7 +164,7 @@ When you have these keys, please create a new file called `.env` in your project 2. In the Notepad, type this, replacing xxxx with your API key (starting `sk-proj-`). ``` -OPENAI_API_KEY=xxxx +OPENROUTER_API_KEY=xxxx ``` If you have other keys, you can add them too, or come back to this in future weeks: diff --git a/setup/SETUP-linux.md b/setup/SETUP-linux.md index 00424ccae..1a9303ef2 100644 --- a/setup/SETUP-linux.md +++ b/setup/SETUP-linux.md @@ -176,7 +176,7 @@ nano .env 4. Then type your API keys into nano, replacing xxxx with your API key (starting `sk-proj-`). ``` -OPENAI_API_KEY=xxxx +OPENROUTER_API_KEY=xxxx ``` If you have other keys, you can add them too, or come back to this in future weeks: diff --git a/setup/SETUP-mac.md b/setup/SETUP-mac.md index 3d0932acd..4a41dec2d 100644 --- a/setup/SETUP-mac.md +++ b/setup/SETUP-mac.md @@ -152,7 +152,7 @@ nano .env 4. Then type your API keys into nano, replacing xxxx with your API key (starting `sk-proj-`). ``` -OPENAI_API_KEY=xxxx +OPENROUTER_API_KEY=xxxx ``` If you have other keys, you can add them too, or come back to this in future weeks: diff --git a/setup/SETUP-new.md b/setup/SETUP-new.md index 5b78566c5..1394469cb 100644 --- a/setup/SETUP-new.md +++ b/setup/SETUP-new.md @@ -180,11 +180,11 @@ If you're wondering why I rant about this: I get many, many frustrated people co Select the file on the left. You should see an empty blank file on the right. And type this into the contents of the file in the right: -`OPENAI_API_KEY=` +`OPENROUTER_API_KEY=` And then press paste! You should now see something like this: -`OPENAI_API_KEY=sk-proj-lots-and-lots-of-digits` +`OPENROUTER_API_KEY=sk-proj-lots-and-lots-of-digits` But obviously with your actual key there, not the words "sk-proj-lots-and-lots-of-digits".. diff --git a/setup/diagnostics.py b/setup/diagnostics.py index 716e5441e..044aa1207 100644 --- a/setup/diagnostics.py +++ b/setup/diagnostics.py @@ -182,11 +182,11 @@ def _step4_check_env_file(self): self.log(f".env file exists at: {env_path}") try: with open(env_path, 'r') as f: - has_api_key = any(line.strip().startswith('OPENAI_API_KEY=') for line in f) + has_api_key = any(line.strip().startswith('OPENROUTER_API_KEY=') for line in f) if has_api_key: - self.log("OPENAI_API_KEY found in .env file") + self.log("OPENROUTER_API_KEY found in .env file") else: - self._log_warning("OPENAI_API_KEY not found in .env file") + self._log_warning("OPENROUTER_API_KEY not found in .env file") except Exception as e: self._log_error(f"Cannot read .env file: {e}") else: @@ -358,16 +358,16 @@ def _step8_environment_variables(self): for path in sys.path: self.log(f" - {path}") - # Check OPENAI_API_KEY + # Check OPENROUTER_API_KEY from dotenv import load_dotenv load_dotenv() - api_key = os.environ.get('OPENAI_API_KEY') + api_key = os.environ.get('OPENROUTER_API_KEY') if api_key: - self.log("OPENAI_API_KEY is set after calling load_dotenv()") + self.log("OPENROUTER_API_KEY is set after calling load_dotenv()") if not api_key.startswith('sk-proj-') or len(api_key)<12: - self._log_warning("OPENAI_API_KEY format looks incorrect after calling load_dotenv()") + self._log_warning("OPENROUTER_API_KEY format looks incorrect after calling load_dotenv()") else: - self._log_warning("OPENAI_API_KEY environment variable is not set after calling load_dotenv()") + self._log_warning("OPENROUTER_API_KEY environment variable is not set after calling load_dotenv()") except Exception as e: self._log_error(f"Environment variables check failed: {e}") diff --git a/setup/troubleshooting.ipynb b/setup/troubleshooting.ipynb index 8c2d5146a..a82eb09d3 100644 --- a/setup/troubleshooting.ipynb +++ b/setup/troubleshooting.ipynb @@ -227,7 +227,7 @@ "Is it possible that `.env` is actually called `.env.txt`? In Windows, you may need to change a setting in the File Explorer to ensure that file extensions are showing (\"Show file extensions\" set to \"On\"). You should also see file extensions if you type `dir` in the `llm_engineering` directory.\n", "\n", "Nasty gotchas to watch out for: \n", - "- In the .env file, there should be no space between the equals sign and the key. Like: `OPENAI_API_KEY=sk-proj-...`\n", + "- In the .env file, there should be no space between the equals sign and the key. Like: `OPENROUTER_API_KEY=sk-proj-...`\n", "- If you copied and pasted your API key from another application, make sure that it didn't replace hyphens in your key with long dashes \n", "\n", "Note that the `.env` file won't show up in your Jupyter Lab file browser, because Jupyter hides files that start with a dot for your security; they're considered hidden files. If you need to change the name, you'll need to use a command terminal or File Explorer (PC) / Finder Window (Mac). Ask ChatGPT if that's giving you problems, or email me!\n", @@ -256,18 +256,18 @@ " with env_path.open(\"r\") as env_file:\n", " contents = env_file.readlines()\n", "\n", - " key_exists = any(line.startswith(\"OPENAI_API_KEY=\") for line in contents)\n", - " good_key = any(line.startswith(\"OPENAI_API_KEY=sk-proj-\") for line in contents)\n", + " key_exists = any(line.startswith(\"OPENROUTER_API_KEY=\") for line in contents)\n", + " good_key = any(line.startswith(\"OPENROUTER_API_KEY=sk-proj-\") for line in contents)\n", " classic_problem = any(\"OPEN_\" in line for line in contents)\n", " \n", " if key_exists and good_key:\n", - " print(\"SUCCESS! OPENAI_API_KEY found and it has the right prefix\")\n", + " print(\"SUCCESS! OPENROUTER_API_KEY found and it has the right prefix\")\n", " elif key_exists:\n", - " print(\"Found an OPENAI_API_KEY although it didn't have the expected prefix sk-proj- \\nPlease double check your key in the file..\")\n", + " print(\"Found an OPENROUTER_API_KEY although it didn't have the expected prefix sk-proj- \\nPlease double check your key in the file..\")\n", " elif classic_problem:\n", - " print(\"Didn't find an OPENAI_API_KEY, but I notice that 'OPEN_' appears - do you have a typo like OPEN_API_KEY instead of OPENAI_API_KEY?\")\n", + " print(\"Didn't find an OPENROUTER_API_KEY, but I notice that 'OPEN_' appears - do you have a typo like OPEN_API_KEY instead of OPENROUTER_API_KEY?\")\n", " else:\n", - " print(\"Didn't find an OPENAI_API_KEY in the .env file\")\n", + " print(\"Didn't find an OPENROUTER_API_KEY in the .env file\")\n", "else:\n", " print(\".env file not found in the llm_engineering directory. It needs to have exactly the name: .env\")\n", " \n", @@ -315,7 +315,7 @@ "else:\n", " try:\n", " with env_path.open(mode='w', encoding='utf-8') as env_file:\n", - " env_file.write(f\"OPENAI_API_KEY={make_me_a_file_with_this_key}\")\n", + " env_file.write(f\"OPENROUTER_API_KEY={make_me_a_file_with_this_key}\")\n", " print(f\"Successfully created the .env file at {env_path}\")\n", " if not make_me_a_file_with_this_key.startswith(\"sk-proj-\"):\n", " print(f\"The key that you provided started with '{make_me_a_file_with_this_key[:8]}' which is different to sk-proj- is that what you intended?\")\n", @@ -348,7 +348,7 @@ "from dotenv import load_dotenv\n", "load_dotenv(override=True)\n", "\n", - "api_key = os.getenv(\"OPENAI_API_KEY\")\n", + "api_key = os.getenv(\"OPENROUTER_API_KEY\")\n", "\n", "if not api_key:\n", " print(\"No API key was found - please try Kernel menu >> Restart Kernel And Clear Outputs of All Cells\")\n", @@ -418,7 +418,7 @@ "from dotenv import load_dotenv\n", "load_dotenv(override=True)\n", "\n", - "my_api_key = os.getenv(\"OPENAI_API_KEY\")\n", + "my_api_key = os.getenv(\"OPENROUTER_API_KEY\")\n", "\n", "print(f\"Using API key --> {my_api_key} <--\")\n", "\n", diff --git a/week1/day1.ipynb b/week1/day1.ipynb index 1727352a5..557ebf95b 100644 --- a/week1/day1.ipynb +++ b/week1/day1.ipynb @@ -1,570 +1,796 @@ { - "cells": [ - { - "cell_type": "markdown", - "id": "d15d8294-3328-4e07-ad16-8a03e9bbfdb9", - "metadata": {}, - "source": [ - "# YOUR FIRST LAB\n", - "### Please read this section. This is valuable to get you prepared, even if it's a long read -- it's important stuff.\n", - "\n", - "### Also, be sure to read [README.md](../README.md)! More info about the updated videos in the README and [top of the course resources in purple](https://edwarddonner.com/2024/11/13/llm-engineering-resources/)\n", - "\n", - "## Your first Frontier LLM Project\n", - "\n", - "By the end of this course, you will have built an autonomous Agentic AI solution with 7 agents that collaborate to solve a business problem. All in good time! We will start with something smaller...\n", - "\n", - "Our goal is to code a new kind of Web Browser. Give it a URL, and it will respond with a summary. The Reader's Digest of the internet!!\n", - "\n", - "Before starting, you should have completed the setup linked in the README.\n", - "\n", - "### If you're new to working in \"Notebooks\" (also known as Labs or Jupyter Lab)\n", - "\n", - "Welcome to the wonderful world of Data Science experimentation! Simply click in each \"cell\" with code in it, such as the cell immediately below this text, and hit Shift+Return to execute that cell. Be sure to run every cell, starting at the top, in order.\n", - "\n", - "Please look in the [Guides folder](../guides/01_intro.ipynb) for all the guides.\n", - "\n", - "## I am here to help\n", - "\n", - "If you have any problems at all, please do reach out. \n", - "I'm available through the platform, or at ed@edwarddonner.com, or at https://www.linkedin.com/in/eddonner/ if you'd like to connect (and I love connecting!) \n", - "And this is new to me, but I'm also trying out X at [@edwarddonner](https://x.com/edwarddonner) - if you're on X, please show me how it's done 😂 \n", - "\n", - "## More troubleshooting\n", - "\n", - "Please see the [troubleshooting](../setup/troubleshooting.ipynb) notebook in the setup folder to diagnose and fix common problems. At the very end of it is a diagnostics script with some useful debug info.\n", - "\n", - "## If this is old hat!\n", - "\n", - "If you're already comfortable with today's material, please hang in there; you can move swiftly through the first few labs - we will get much more in depth as the weeks progress. Ultimately we will fine-tune our own LLM to compete with OpenAI!\n", - "\n", - "| \n",
- " \n",
- " | \n",
- " \n",
- " Please read - important note\n", - " The way I collaborate with you may be different to other courses you've taken. I prefer not to type code while you watch. Rather, I execute Jupyter Labs, like this, and give you an intuition for what's going on. My suggestion is that you carefully execute this yourself, after watching the lecture. Add print statements to understand what's going on, and then come up with your own variations. If you have a Github account, use this to showcase your variations. Not only is this essential practice, but it demonstrates your skills to others, including perhaps future clients or employers...\n", - " | \n",
- "
| \n",
- " \n",
- " | \n",
- " \n",
- " This code is a live resource - keep an eye out for my emails\n", - " I push updates to the code regularly. As people ask questions, I add more examples or improved commentary. As a result, you'll notice that the code below isn't identical to the videos. Everything from the videos is here; but I've also added better explanations and new models like DeepSeek. Consider this like an interactive book.\n", - " I try to send emails regularly with important updates related to the course. You can find this in the 'Announcements' section of Udemy in the left sidebar. You can also choose to receive my emails via your Notification Settings in Udemy. I'm respectful of your inbox and always try to add value with my emails!\n", - " \n", - " | \n",
- "
| \n",
- " \n",
- " | \n",
- " \n",
- " Business value of these exercises\n", - " A final thought. While I've designed these notebooks to be educational, I've also tried to make them enjoyable. We'll do fun things like have LLMs tell jokes and argue with each other. But fundamentally, my goal is to teach skills you can apply in business. I'll explain business implications as we go, and it's worth keeping this in mind: as you build experience with models and techniques, think of ways you could put this into action at work today. Please do contact me if you'd like to discuss more or if you have ideas to bounce off me.\n", - " | \n",
- "
| \n",
+ " \n",
+ " | \n",
+ " \n",
+ " Please read - important note\n", + " The way I collaborate with you may be different to other courses you've taken. I prefer not to type code while you watch. Rather, I execute Jupyter Labs, like this, and give you an intuition for what's going on. My suggestion is that you carefully execute this yourself, after watching the lecture. Add print statements to understand what's going on, and then come up with your own variations. If you have a Github account, use this to showcase your variations. Not only is this essential practice, but it demonstrates your skills to others, including perhaps future clients or employers...\n", + " | \n",
+ "
| \n",
+ " \n",
+ " | \n",
+ " \n",
+ " This code is a live resource - keep an eye out for my emails\n", + " I push updates to the code regularly. As people ask questions, I add more examples or improved commentary. As a result, you'll notice that the code below isn't identical to the videos. Everything from the videos is here; but I've also added better explanations and new models like DeepSeek. Consider this like an interactive book.\n", + " I try to send emails regularly with important updates related to the course. You can find this in the 'Announcements' section of Udemy in the left sidebar. You can also choose to receive my emails via your Notification Settings in Udemy. I'm respectful of your inbox and always try to add value with my emails!\n", + " \n", + " | \n",
+ "
| \n",
+ " \n",
+ " | \n",
+ " \n",
+ " Business value of these exercises\n", + " A final thought. While I've designed these notebooks to be educational, I've also tried to make them enjoyable. We'll do fun things like have LLMs tell jokes and argue with each other. But fundamentally, my goal is to teach skills you can apply in business. I'll explain business implications as we go, and it's worth keeping this in mind: as you build experience with models and techniques, think of ways you could put this into action at work today. Please do contact me if you'd like to discuss more or if you have ideas to bounce off me.\n", + " | \n",
+ "
| \n",
+ " \n",
+ " | \n",
+ " \n",
+ " Business applications\n", + " In this exercise, you experienced calling the Cloud API of a Frontier Model (a leading model at the frontier of AI) for the first time. We will be using APIs like OpenAI at many stages in the course, in addition to building our own LLMs.\n", + "\n", + "More specifically, we've applied this to Summarization - a classic Gen AI use case to make a summary. This can be applied to any business vertical - summarizing the news, summarizing financial performance, summarizing a resume in a cover letter - the applications are limitless. Consider how you could apply Summarization in your business, and try prototyping a solution.\n", + " | \n",
+ "
| \n",
+ " \n",
+ " | \n",
+ " \n",
+ " Before you continue - now try yourself\n", + " Use the cell below to make your own simple commercial example. Stick with the summarization use case for now. Here's an idea: write something that will take the contents of an email, and will suggest an appropriate short subject line for the email. That's the kind of feature that might be built into a commercial email tool.\n", + " | \n",
+ "
| \n",
- " \n",
- " | \n",
- " \n",
- " Business applications\n", - " In this exercise, you experienced calling the Cloud API of a Frontier Model (a leading model at the frontier of AI) for the first time. We will be using APIs like OpenAI at many stages in the course, in addition to building our own LLMs.\n", - "\n", - "More specifically, we've applied this to Summarization - a classic Gen AI use case to make a summary. This can be applied to any business vertical - summarizing the news, summarizing financial performance, summarizing a resume in a cover letter - the applications are limitless. Consider how you could apply Summarization in your business, and try prototyping a solution.\n", - " | \n",
- "
| \n",
- " \n",
- " | \n",
- " \n",
- " Before you continue - now try yourself\n", - " Use the cell below to make your own simple commercial example. Stick with the summarization use case for now. Here's an idea: write something that will take the contents of an email, and will suggest an appropriate short subject line for the email. That's the kind of feature that might be built into a commercial email tool.\n", - " | \n",
- "