Great to meet you @localmind9358 Here is the code repo You can follow along by copying pasting the code in the READMEs github.com/thaddavis/how-to-deploy-a-dockerized-fastapi-to-google-cloud-run/blob/part_4/part_1.md github.com/thaddavis/how-to-deploy-a-dockerized-fastapi-to-google-cloud-run/blob/part_4/part_2.md github.com/thaddavis/how-to-deploy-a-dockerized-fastapi-to-google-cloud-run/blob/part_4/part_3.md github.com/thaddavis/how-to-deploy-a-dockerized-fastapi-to-google-cloud-run/blob/part_4/part_4.md Is this what you were looking for?
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It depends on the details on your hobby project. Like A) how many services make up your hobby project... B) How much it gets used C) How many other "paid" services your Cloud Run services rely on etc. I find Cloud Run in general to be extremely cheap for simple projects (ie: 1 or 2 services that make up the application) If you are asking for a rough estimate of the Cloud Run costs for a simple application made up of 1-2 services I'd say you'll be paying between $1 to $20 per month BUT! It depends on the details of your application to know the exact amount. Could be lower or higher. Let me know how it goes The nice thing about Cloud run services is that they shut themselves down after not being used for a few minutes so they are very cost effective
I'm not an expert in VPN's but my understanding of them is that they change what your IP address looks like to the websites and APIs you visit on the internet... All the technique in this video is doing is measuring how similar each login is to your previous ones... So if your VPN always switches your IP address to the same one then it would get caught by this technique. But if you VPN is always switching up your IP this technique might catch it The IP address is 1 component that is being tracked for the similarity measurement... So if your other login characteristics (like device type & time of login) are the same the switching up the IP address might not affect the "similarity score" that much
Could you use namespaces to weigh web search results for providing answers to LLM queries? When you originally asked about the most recent GPTuesdays that you missed, could it have used a namespace you previously generated, to search the web to try to find out about the most recent GPTuesday?
Yes that would work too... An LLM agent can be given the capability to connect to a search engine like Google via an API Like this one for example: serpapi.com/ ChatGPT I think connects to Bing when answering many questions, etc. That could/would work but there still might be info that you don't want on the web or want more control over... That's where a vector db comes in ie: Think a company's internal documents etc.
This was exceptionally well done. I was captivated from start to finish. The pacing, storytelling, research, visuals, tutorials and explanations were perfect and appropriate. You have a real talent! Keep up the fantastic work! 🎉 I can't wait to see the next video in this series!
I find this to be a vague question Can you provide more details? I would recommend you test what you are trying out and let us know how it goes Learn by doing If you want to share the link to your GitHub with your code please do ; )
Great to meet you @kirillzlobin7135 ToC 00:00 - Intro 00:57 - Variation 1 (including the translations content in the React app) 04:24 - Variation 2 (loading translations content from an API via an endpoint)
I'm guessing your mean translating the paths in the URL ie: my-website.com/news for English visitors & my-website.com/nouvelles for French visitors? What react framework are you using? Next.js? If I understand you question correctly, then the way for accomplishing this depends on the framework or combination of technologies you are using : )
Hey! it is really great try on LLM, I am doing a final project, and want to use your github for reference, I didn't get chance to run your code, do you think this project is completed and I can run your github code just like the video you are showing?
Ladies and gentlemen, this video on "Coding an OpenAI integration with Python and Flask" is truly fantastic, believe me! It's a tremendous example of what can be achieved when brilliant minds come together. OpenAI is the best, and they're doing amazing things. In this video, the author COMMAND shows how to integrate OpenAI technology with Python and Flask, making things easier and more efficient. It's a beautiful thing. We need to stay at the forefront of technology, and this video demonstrates that we're leading the way. I want to thank COMMAND for this winner. It's a real winner, and I love winners. Thank you and God bless you all! 🇺🇸👍
