I've been in awe of the ChatGPT phenomenon. It's not my first exposure to AI, I've been following along and implementing basic solutions in this area. I've done some basic python programming involving training and implementation of iterative learning. Conceptually I understand what is going on, but I find that ChatGPT has made this much more relevant and almost a commodity now. Everyone has the ability to "chat" and start to understand the power of AI - even if in this basic use case of large language exchange.
I think that the really cool thing about this is that we are all learning how to ask better questions. How we can use AI to assist us in our daily activities. I've used it to summarise and generate data. Awesome use cases there. I've used it for programming, it's helped me with python and groovy. I've asked it about the weather: using https://chat.openai.com/ of course.
If you have a good think about the response above, I think it explains a lot about what ChatGPT can do. It talks about it's training is only until Sept 21 - so it's not a prediction method for random events (like weather), sure it can tell you the average temperature for the month of May in Melbourne Australia - but it cannot tell you accurately what tomorrows weather is going to be - because it needs super current context.
Yes, there are some advanced toggles that will include "google results" with the model for these types of queries - but this information is just not part of a model.
Let's get JDE specific, so I'll try some other queries:
This is a pretty decent summary of the actions to perform. Incredible that the model has crawled over the JDE manuals to be able to create a response like this. Of course, we start to think that this is a good way of integrating help into JD Edwards - because all of the content it there. What if I want a little more, include program names:
Fairly generic again, some additional and decent information.
Right - we are starting to get a feel for what we might be able to do in JD Edwards. Let's get started.
We take this to the next level and create a composite page with the same chat interface.
Parametrized URL:
In this example I've preloaded the chat with context sensitive information from the native JD Edwards screen. I'm passing in the item and the description and a few other details to get ChatGPT to create context sensitive and relevant information - generate a purchase agreement.
You can see that it's fairly easy to create the query with context from the webpage and have ChatGPT do all of the hard work. Thanks - this is a really easy way of getting things done.
Purchase Agreement
This Purchase Agreement (the “Agreement”) is made and entered into as of this ____ day of ___________, 20___ (the “Effective Date”), by and between ___________________ (the “Buyer”) and ___________________ (the “Seller”).
WHEREAS, the Buyer desires to purchase, and the Seller desires to sell, the following item (the “Item”):
Mountain Bike, Red, Item Number 210
NOW, THEREFORE, in consideration of the mutual promises and covenants set forth herein, the parties agree as follows:
1. Purchase. The Buyer agrees to purchase the Item from the Seller for the purchase price of ___________ (the “Purchase Price”). The Purchase Price shall be paid in full on or before the Effective Date.
2. Delivery. The Seller agrees to deliver the Item to the Buyer on or before the Effective Date. The Seller shall be responsible for all costs associated with the delivery of the Item, including any applicable taxes.
3. Specifications. The Item shall have the following estimated weight and volume: ___________.
4. Warranty. The Seller warrants that the Item shall be free from defects in material and workmanship for a period of ___________ from the date of delivery.
5. Limitation of Liability. The Seller shall not be liable for any damages, losses, or liabilities arising out of the Item’s use, other than those expressly provided for in this Agreement.
6. Governing Law. This Agreement shall be governed by and construed in accordance with the laws of the ___________.
7. Severability. If any provision of this Agreement is held to be invalid or unenforceable, such provision shall be struck and the remaining provisions shall be enforced.
8. Entire Agreement. This Agreement constitutes the entire agreement between the parties and supersedes all prior and contemporaneous agreements, representations, and understandings between the parties.
9. Modification. This Agreement may not be modified or amended except in a writing signed by both parties.
10. Waiver. No waiver of any provision of this Agreement shall be deemed or shall constitute a waiver of any other provision, whether or not similar, nor shall any waiver constitute a continuing waiver. No waiver shall be binding unless executed in writing by the party making the waiver.
IN WITNESS WHEREOF, the parties have executed this Agreement as of the date first set forth above.
BUYER: ___________________
SELLER: ___________________
We may have the most simple orchestration in the world. I've created a connector and connection and then used this to call the chatGPT API's natively. I did this by fighting the security layer a little bit and using postman to get it all working in the "lab". I then created the MO functions, which now are very easy to use... So - two steps and I'm interacting with Chat GPT.
- iPhone 13 Pro Max Dimension: 160.8 mm x 78.1 mm x 7.65 mm
- Volume = 160.8 x 78.1 x 7.65 = 93,346.908 cubic millimeters
- Metric Cubic Volume = 93.35 cubic centimeters
Average Weight:
- iPhone 13 Pro Max Weight: 238 grams
Packing Instructions:
1. Secure the iPhone 13 Pro Max in its original packaging.
2. Place it in a sturdy cardboard box that is slightly larger than the phone's packaging.
3. Fill any empty spaces inside the box with bubble wrap or packing peanuts to prevent the phone from shifting.
4. Seal the box with high-quality packing tape.
5. Attach the shipping label to the box.
6. Deliver to the courier service for shipping.
Remember to handle the phone with care and make sure it is properly secured to prevent any damage during transit.
Note that this is a similar orchestration to last time. We needed an additional URL launcher - as JDE cannot store URL's greater than 256 chars, which was a little annoying. We create a copy of the object in Azure Blob Storage and serve it up through there.
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