During testing I found any other approach would always inevitably make stuff up.
Not trying to disparage this work. I think it's great that you can build such a thing so quickly. But I wouldn't rely on the info these LLM's provide.
For anyone else that is interested in this question: I've tried a whole bunch of the TTS services and found that Microsoft and AWS are the best of the standard providers IMHO and these are services that tend to have startup credits available so I use a mix of these two - I try to never rely on just one provider. I've met with the Eleven Labs folks and some of their demo's of the V2 stuff that's coming are really amazing but latency and pricing might rule them out as an option for the time being.
I used it to plan a summer European trip to 17 cities and didn't notice any hallucinations for what must have been 20 hours of back and forth creating itineraries, day trips, etc.
Did not use it as my only source of info, still watched some videos by Rick Steeves and Wolter's World, but it far and away was the most efficient part of the planning process for me.
Well for itineraries, given that its training data gets cut off at some point, I’d also be worried about it recommending places that are no longer open.
Note that I’m building an app for customers and attempting to build a brand that can be trusted - whereas in your case gpt 4 is probably ideal given you know it’s caveats and can check the important stuff.
Also, they literally just demoed something similar as this project as part of their recent keynote on new openai stuff. The demo featured focused on their new assistant api.
I've actually grilled chat gpt a bit on geographic information on a few occasions. It's not perfect but surprisingly good. It obviously extracts a lot of that from things like wikipedia.
You can actually ask it to answer in geojson format, paste it in geojson.io and end up with a usable map. It seems to know about a lot of landmarks; including coordinates. For smaller venues, the coordinates are not super accurate.
You can also ask it to provide geojson for the boundingbox of a city or area. I even asked it to pretend to be an in car navigation system and provide me with directions to an address. It half succeeded in listing correct streets but messing up right and left. With the latest chatgpt it just asks bing.
GitHub: https://github.com/widgetti/wanderlust App: https://huggingface.co/spaces/solara-dev/wanderlust X: https://twitter.com/maartenbreddels/status/17223244907077020... Solara: https://github.com/widgetti/solara/
We (Ploomber) have been working with the team to help their community easily deploy applications in our cloud platform: https://docs.cloud.ploomber.io/en/latest/apps/solara.html
Is it much more of a project for tools used by one or two end users? How have you found it?
https://github.com/widgetti/wanderlust/blob/master/wanderlus...
...though I still can't figure out what "the OpenAPI Wanderlust app" does after reading every line!
chat, search, upload images, get flight info. still developing. It's free. Enjoy
Not a criticism of this repo, but presentation is important in order to attract potential users.
because it's not like human travel agents don't exist today, just like human drivers exist today. Does having an AI book the tickets for you meaningfully change the things for you, the customer?
I am finding myself reaching for GPT4 more often to spin up POC apps.
You could fine-tune a coding assistant on your library and good quality example apps with documentation ... and that might take the ease of churning out new demos and apps to the next level?
I ask it to write it in small chuncks but in the same context. I sometimes have to remind it to refer back to decisions we made earlier.
* Solara will not continuously re-execute your script as Streamlit does.
* Solara will re-execute components instead, only what needs to. * State in Solara is separate from the UI components, unlike streamlit, where they are strongly linked.
* State can be on the application level (global) for simplicity or on the component level (local) for creating reusable components.
* Solara should not block the render loop. Long-running functions should be executed in a thread using use_thread.
I can totally understand not being great for smaller landmarks... it could be the case too that it could trigger a call to an external service for things it doesn't have high confidence about.
Of course it does. You don't think replacing humans in the full service travel industry wouldn't drive down costs and upgrade capabilities and experience could be a thing?
I want my ai to have as little financial incentive for itself and only maximize my needs. I'd pay for THAT.
In the end, you'll end up with Booking.com with extra steps:
"Perfect, ugh123! I've got just the hotel for you! It's the Marriott Grand Paradise, our top partner hotel. It is only 45 miles away from the specific address you requested and just barely $150 over budget per night, but they have a 4.9 rating, and with their Top Partner status, you earn 10 BookiePoints by booking there. Hurry, 33 people have booked a room there in the last hour! Do you confirm? Whoops, one more booking just now, only one room left! Do you want to save yours now?"