OpenAI Fires Back at DeepSeek With a New Reasoning Model: o3-mini (n8n AI Agent)

Key Takeaways

so let's go ahead and throw a query at this travel agent and we will see what we get we're asking for it to plan a 5-day trip to Paris with a budget of $2,000 so let's see it's hitting the openai reasoning model right now first of all it's hitting the resort so it just grab Resort information it's going back to open ai's model to see what to do next it's going to hit either the flights database or the activities database to continue planning this itenerary for us it needs to gather all the information um like I said to structure that itinerary um human readly so now we've got flights information we've got activities information and finally right now it's formatting that into HTML structure and then it's going to hit the send itenerary Gmail tool in order to actually send that out to us and then we'll be able to take a look at what it what it did okay there we go so we just saw it hit the send itenerary Gmail tool now it finished up we'll see what it said back to us looks like you received the itenerary email please check your inbox for the detailed 5day trip to Paris so let's go ahead and check that out in our Gmail all right as you can see we just got this email back the subject is your 5-day Paris trip I tenary with a budget of $2,000 so that's great it keeps that into account when it's going through and reasoning how to make this itinerary so we've got our travel and flight details we're flying Air France we've got our routes and we've got the departure and return time and we have our price then we have accommodation for a comfortable centrally located stay we recommend a budget friendly hotel such as Hotel IIs Paris um or similar so we've got that information 600 700 bucks and then we have a day-by-day itinerary remember we asked for a 5-day trip so it planned out 5 days um we have different activities here morning afternoon evening um we have even different options down here it gives us option A and option b stuff like that and then it's going to give us a summary at the end of here's the flight here's the accommodation here's your expenses um and it's pretty much keeping everything about $2,000 like we asked for in the beginning and as you can see um it's a really nicely formatted itinerary for us so yesterday open AI just released 03 mini which is their newest most cost-efficient reasoning model to date it seems like this may have been a direct response to all the models that deeps has been releasing lately that have completely took the World by storm and made everyone sell their shares of Nvidia anyways what's really cool about 03 is that it's their first small reasoning model that supports highly requested developer features including function calling structured outputs and developer messages making it production ready right out of the gate this model is super fast and powerful and optimized for stem reasoning as you can see it's outperforming 01 in math in PhD level science questions in um competition code all this kind of stuff I'll leave the link to this open aai release um information Down Below in the description if you want to check it out for yourself but we don't want to spend too much time here what we want to do is we want to get into nadn plug it into an agent with different tools and see how it works so that's exactly what we're going to be doing here today as you can see I built out a travel agent it's accessing these three different databases in Pine Cone that have information on Resorts information on flights and then information about different activities to do based on where you are and um finally it's going to take all that information and then put it into an HTML formatted email and then send out that itinerary based on the user input of course which in here we're just chat chatting with a trigger with an nadn so we played around with deep see we've seen that it's been really really cool but when you try to hook up tools to an agent it's not really supported for that so it'll be really cool to see how o03 mini performs when we give it access to these four different tools and it also has that aspect of reasoning through and creating hopefully a really really nicely structured itinerary based on all the information it's going to get from these databases and what the we ask for up front so of course step one is to connect our AI agent to open ai's new model which is 03 so if we wanted to click on this chat model and we go down to open AI chat model what see here is that let me just fix the credential because that wasn't my open a credential but anyways what we'll see here is that we don't have 03 mini yet so this is just because it's so new um we may get a preview out here or something soon it literally just released yesterday um and so if you're watching this video later it will probably be here but for now we have a really easy solution which is um we can just connect to open router which thanks to the update that also happened yesterday or the day before um we have the native open a open router chat model now so this is really cool all you have to do is go to open router you will click up in the top right after you make an account go to Keys create a new key copy that into your credential section right here when you go to create a new credential paste that key in there and then you'll have all the models to choose from and as you can see right here we have open AI 03 mini what's also really cool about open router is that once you are using different models you can click on activity and you can see which ones you're using you can see how much they're costing you all that kind of stuff so as you can see I've been playing around with open AI 03 mini it's been about 007 per input and output um so it's definitely not too expensive so you saw a demo in the beginning of this video Let's really quickly break down what's actually going on within this workflow and um and then we'll do one more test at the end so what we've got here like I said is three different pine cone databases so if you were really wanting to build out a travel agent you'd probably want to hook it up to different apis that can go scrape for Resorts go scrape for flights go scrape for activities for the say this video I just want to throw something together quick and the purpose is still the same of can 03 reason through the prompt reason through its system message and understand how to hit tools and how to pull information back and clearly it does because it hits all these three tools formats the information into HTML email and then sends it off with the other tool so it's doing four Total Tool calls here so as far as the databases go like I said they're on Pine Cone there are three different Nam spaces this Nam space is Resorts this Nam space is flights and then the last one of course is activities and if we switch over to my pine cone real quick you can see I've got activities flights and Resorts so that's how we hooked up these three different databases to this agent and if you want to replicate this experiment in your own an instance you can download this workflow for free as well as this workflow that I used to push the documents into pine cone all you have to do is join my free school Community once you join all you'll have to do is click on the post associated with this specific video you can click into the Json file and download it once you have that file all you have to do is click on the top right three dots in your nadn click import from file and then once you choose that Json it'll open up right here for you and if you're looking to take your learning with nadn and a automations a little bit farther you're looking for more hands-on experience feel free to check out my paid Community the link for that will also be down in the description as you can see we've got a great community of members who are learning nadn and also sharing their resources and their challenges that they're facing we've got a great classroom section as well with different Deep dive topics and these resources are always being updated and then finally we've got a calendar with five live calls per week which is super exciting we've got three Tech supports one coffee chat one weekly Q&A and as you can see in February we've already got three guest speakers planned which is really really exciting and hopefully we have multiple guest speakers every month so I'd love to see you guys in these calls let's get back back to the video all right so that's what the database looks like that's where it's getting its information and then the last thing it needs to do is actually send out the email so right now I just put my email it's going to be fixed so every time I activate this agent it's going to send an email to this address rather than being able to dynamically put that in if you want it to do dynamically you could do that super easily by making this an expression and then you utilize the from AI function that we're using in the the subject and the message parameters and just put in from Ai and then the key would be like an email address or recipient or something like that anyways obviously we're sending a message Mage and we wanted to do HTML this time rather than text because we could just get it formatted a little better a little more human readable for us and then finally we just turned off the append naden attribution so that at the bottom of the email it doesn't say that this was generated by naden so let's take a quick look at the prompt and then we'll send off another example and see what type of itenerary we get back so I got this prompt by using my AI agent prompt architect that gives us markdown formatted prompts as you can see I told it what the agent's going to do and then after it gave me an initial one I was able to say perfect now I want to add another tool called send itinerary so it's able to have that memory and work with us and then we could copy and paste this prompt straight into our AI agent with the markdown because that's super important for us to be able to understand as well as um saying like you know this is your overview this is your context these are instructions anyways so we told that you have access to four tools Resorts is for information about Resorts flights activities send itenerary um at the end you have to send the itenerary in a HTML format what we wanted to do is give it instructions because when I first started doing this it wasn't calling the tools or sometimes it was just calling one or the other so what we said is always call all three data retrieval tools before providing any response so use all three of the tools and then based on the retrieved information create a detailed itinerary that includes stuff like recommended Resorts flights a day-by-day breakdown of activities and then once the itenerary is logical well paced align with the Traveler's preferences based on what they say up front at the beginning then you can format that final itenerary and HTML format and send that off to the send itenerary Gmail tool so um very simple prompt here we get gave it a few examples and then we told it sort of how to structure your HTML and then just gave it standard operating procedures and final notes so I know I went through that quick if you want to take a little more in-depth look at the prompt go ahead and download this workflow The Prompt will be in there and you'll be able to sort of break down what's going on okay cool so we broke down what's going on within this workflow one thing I want to mention before we do one final test is that this may not be the optimal way to structure a travel agent because this kind of stuff is happening sequentially rather than variably so what I mean by that is the agent has autonomous decision here to use the different tools but in this case every single time we want it to check Resorts check flights check activities and then send a message so if I was really trying to build this out to be sort of a production ready agent what I would do is build it linearly sequentially rather than having this be like a parent type tooling uh multi-tool agent um anyways so what we would do is maybe have like a an agent that originally takes the query and then gets Resort information then passes it off to another another agent to get flight information and activity information then finally a send email tool um just because having that linear flow may cut down on sort of like errors and hallucination with data transfer and Tool calling okay so now we've got that out of the way let's send off one more query to end this one off so what we're saying here is I need a week-long vacation in Sydney Australia recommend flights a hotel with a pool and some activities so it just hit the resorts tool now it's going to go back to the model it's thinking about what to do next it should be understanding that it needs to hit flights so it can get flight information and then finally needs to get activities so it can recommend activities of course so it just hit flights um now it's going to activities and then it's going to pull that all back right now it's creating that HTML formatted itinerary going to send that off to our Gmail and then we'll take a look at what we got okay so here's what we got as you can see it actually formatted a little bit differently from the demo in the demo we got those horizontal bars which I really liked so maybe we can go back and try to refix that prompting but here we have our weeklong Sydney vacation itinerary um as you can see the HTML looks really good we've got sort of like headers and sub headers that kind of stuff we have our flight details which is a little bit over a week so maybe that's just because that's the only flight they had in the database um hotel accommodations we asked for a pool looks like this one has a refreshing pool and top-notch amenities and then we have 7 Days planned which are um arrival and relaxation landmarks Harbor Bridge Bondi Beach um cultural immersion adventure and nature and then Leisure and Department preparation also this one didn't sign off the same way the other one did where it was like best regards your travel team or whatever so there's a little bit of variability here like I said the prompt I made really quickly with that um prompt gbt generator which you can get in my free school Community as well but as you can see um we just spun something up really really quick like I said this took me probably 5 to 10 minutes to set up um I used chbt to just create me some fake example data for the resorts the flights and the activities but the purpose of this video was to show you how to connect to open ai's new 03 Mini model that's their reasoning model more cost effective um you can do that through open router you can check on your usage up there and the new native node thanks to the new 1.77 update makes that super super quick and easy but um yeah as you can see the tool calling works pretty well the reasoning is clearly pretty well pretty good as far as how it's able to plan out an itenerary based on given information and then it was able to format something pretty nice for us as well in an email so that's all I've got for you guys today as always really appreciate you making it to the end hope this one was helpful if it was please give it a like definitely helps me out a lot and I will see you guys in the next one