@ -9,7 +9,8 @@ I'm so happy you're joining me on this path. We'll be building immensely satisfy
### A note before you begin
I'm here to help you be most successful with your learning! If you hit any snafus, or if you have any ideas on how I can improve the course, please do reach out in the platform or by emailing me direct (ed@edwarddonner.com). It's always great to connect with people on LinkedIn to build up the community - you'll find me here:
https://www.linkedin.com/in/eddonner/
https://www.linkedin.com/in/eddonner/
And this is new to me, but I'm also trying out X/Twitter at [@edwarddonner](https://x.com/edwarddonner) - if you're on X, please show me how it's done 😂
Resources to accompany the course, including the slides and useful links, are here:
@ -77,9 +77,10 @@ You should see `(llms)` in your prompt, which indicates you've activated your ne
Press Win + R, type `cmd`, and press Enter
Run `python --version` to find out which python you're on. Ideally you'd be using a version of Python 3.11, so we're completely in sync.
If not, it's not a big deal, but we might need to come back to this later if you have compatibility issues.
You can download python here:
Run `python --version` to find out which python you're on.
Ideally you'd be using a version of Python 3.11, so we're completely in sync.
I believe Python 3.12 works also, but (as of Feb 2025) Python 3.13 does **not** yet work as several Data Science dependencies are not yet ready for Python 3.13.
If you need to install Python or install another version, you can download it here:
https://www.python.org/downloads/
2. Navigate to the "project root directory" by entering something like `cd C:\Users\YourUsername\Documents\Projects\llm_engineering` using the actual path to your llm_engineering project root directory. Do a `dir` and check you can see subdirectories for each week of the course.
@ -70,9 +70,10 @@ You should see `(llms)` in your prompt, which indicates you've activated your ne
1. **Open a new Terminal** (Applications > Utilities > Terminal)
Run `python --version` to find out which python you're on. Ideally you'd be using a version of Python 3.11, so we're completely in sync.
If not, it's not a big deal, but we might need to come back to this later if you have compatibility issues.
You can download python here:
Run `python --version` to find out which python you're on.
Ideally you'd be using a version of Python 3.11, so we're completely in sync.
I believe Python 3.12 works also, but (as of Feb 2025) Python 3.13 does **not** yet work as several Data Science dependencies are not yet ready for Python 3.13.
If you need to install Python or install another version, you can download it here:
https://www.python.org/downloads/
2. Navigate to the "project root directory" using `cd ~/Documents/Projects/llm_engineering` (replace this path with the actual path to the llm_engineering directory, your locally cloned version of the repo). Do `ls` and check you can see subdirectories for each week of the course.
"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",
"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/Twitter at [@edwarddonner](https://x.com/edwarddonner) - if you're on X, please show me how it's done 😂 \n",
"\n",
"## More troubleshooting\n",
"\n",
@ -53,7 +54,19 @@
" </td>\n",
" <td>\n",
" <h2 style=\"color:#900;\">Please read - important note</h2>\n",
" <span style=\"color:#900;\">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 do this with me, either at the same time, or (perhaps better) right afterwards. 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...</span>\n",
" <span style=\"color:#900;\">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, <b>after</b> 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...</span>\n",
" <h2 style=\"color:#f71;\">Treat these labs as a resource</h2>\n",
" <span style=\"color:#f71;\">I push updates to the code regularly. When people ask questions or have problems, I incorporate it in the code, adding 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 in addition, I've added more steps and better explanations. Consider these labs like an interactive book that accompany the lectures.\n",
" </span>\n",
" </td>\n",
" </tr>\n",
"</table>\n",
@ -146,6 +159,21 @@
"# If it STILL doesn't work (horrors!) then please see the Troubleshooting notebook in this folder for full instructions"
"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.</span>\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!</span>\n",
" <h2 style=\"color:#f71;\">A reminder on 2 useful resources</h2>\n",
" <h2 style=\"color:#f71;\">A reminder on 3 useful resources</h2>\n",
" <span style=\"color:#f71;\">1. The resources for the course are available <a href=\"https://edwarddonner.com/2024/11/13/llm-engineering-resources/\">here.</a><br/>\n",
" 2. I'm on LinkedIn <a href=\"https://www.linkedin.com/in/eddonner/\">here</a> and I love connecting with people taking the course!\n",
" 2. I'm on LinkedIn <a href=\"https://www.linkedin.com/in/eddonner/\">here</a> and I love connecting with people taking the course!<br/>\n",
" 3. I'm trying out X/Twitter and I'm at <a href=\"https://x.com/edwarddonner\">@edwarddonner<a> and hoping people will teach me how it's done.. \n",
" print(\"If in doubt, close down all jupyter lab, and follow Part 5 in the SETUP-PC or SETUP-mac guide.\")"
]
},
{
"cell_type": "markdown",
"id": "45e2cc99-b7d3-48bd-b27c-910206c4171a",
"metadata": {},
"source": [
"# Step 1.1\n",
"\n",
"## It's time to check that the environment is good and dependencies are installed\n",
"\n",
"And now, this next cell should run with no output - no import errors. \n",
"\n",
"Import errors might indicate that you started jupyter lab without your environment activated? See SETUP Part 5. \n",
"\n",
"Or you might need to restart your Kernel and Jupyter Lab. \n",
"\n",
"Or it's possible that something is wrong with Anaconda. \n",
"If so, here are some recovery instructions: \n",
"First, close everything down and restart your computer. \n",
"Then in an Anaconda Prompt (PC) or Terminal (Mac), from an activated environment, with **(llms)** showing in the prompt, from the llm_engineering directory, run this: \n",
" <h2 style=\"color:#f71;\">Additional resource: more sophisticated planning agent</h2>\n",
" <span style=\"color:#f71;\">The Planning Agent that we use in the next cell is simply a python script that calls the other Agents; frankly that's all we require for this project. But if you're intrigued to see a more Autonomous version in which we give the Planning Agent tools and allow it to decide which Agents to call, see my implementation of <a href=\"https://github.com/ed-donner/agentic/blob/main/workshop/agents/autonomous_planning_agent.py\">AutonomousPlanningAgent</a> in my related repo, <a href=\"https://github.com/ed-donner/agentic\">Agentic</a>. This is an example with multiple tools that dynamically decides which function to call.\n",
" <h2 style=\"color:#090;\">CONGRATULATIONS AND THANK YOU!!!</h2>\n",
" <span style=\"color:#090;\">\n",
" It's so fabulous that you've made it to the end! My heartiest congratulations. Please stay in touch! I'm <a href=\"https://www.linkedin.com/in/eddonner/\">here on LinkedIn</a> if we're not already connected. And my editor would be cross with me if I didn't mention one more time: 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. <br/><br/>Thanks once again for working all the way through the course, and I'm excited to hear all about your career as an LLM Engineer.\n",
" It's so fabulous that you've made it to the end! My heartiest congratulations. Please stay in touch! I'm <a href=\"https://www.linkedin.com/in/eddonner/\">here on LinkedIn</a> if we're not already connected and I'm on X at <a href=\"https://x.com/edwarddonner\">@edwarddonner</a>. And my editor would be cross with me if I didn't mention one more time: 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. <br/><br/>Massive thanks again for putting up with me for 8 weeks and getting all the way to the final cell! I'm excited to hear all about your career as an LLM Engineer. <b>You could not have picked a better time to be in this field.</b>\n",