✨ Add some AI magic to your Android apps! Check out these three exciting experiments in Android Studio:
🤖 Turning designs into UI code
🎨 Smart UI fixes with Gemini in AI Studio
🔊 Integrating Gemini prompts in your app
Read the blog post → https://goo.gle/3ZBUg4z
La mia domanda è: quanto è efficiente Gemini con la scrittura di codice avanzato scalabile? Perché i primi passi sono semplici, la corsa in montagna è un'altra cosa... che dite?
There are endless possibilities for how you can use Google AI Studio for your Android app, so we gathered 3 fun experiments for you to get started now! → https://goo.gle/3z8V4TM
Explore the potential with:
🖇️ Turning designs into UI code
💡 Smart UI fixes with Gemini
💧 Integrating Gemini prompts in your app
There are endless possibilities for how you can use Google AI Studio for your Android app, so we gathered 3 fun experiments for you to get started now! → https://goo.gle/3z8V4TM
Explore the potential with:
🖇️ Turning designs into UI code
💡 Smart UI fixes with Gemini
💧 Integrating Gemini prompts in your app
To display nicely formatted code snippets in your Streamlit app, use the st.code or st.markdown functions.
To learn more input functions and widgets, check out my course, ML Model Deployment with FastAPI and Streamlit, which also teaches you model deployment with FastAPI. https://lnkd.in/d3CThSF3
Embrace these fun and creative experiments to start using Google AI Studio for your Android app! → https://goo.gle/3z8V4TM
Explore:
🟩 Turning designs into UI code
🔶 Smart UI fixes with Gemini
🟣 Integrating Gemini prompts in your app
🔥 My MLKit Document Scanner project with Jetpack Compose 😎
Inspired by the official sample app from Google, the app ui allows you to customize the scanner options and experiment with it to see what works best for you.
Key features of the api:
🚀 Easy implementation.
📵 Works offline.
📸 No camera permission needed.
✂️ Crop, apply filters and remove shadows.
➕ And way more!
Check out the repository and let me know what you think!:
➡️ https://lnkd.in/debpyTNf ⬅️
For more information, check the official documentation from Google here: https://lnkd.in/dbS4-Ygz
If you find this helpful, don't forget to like and share!
#android#kotlin#jetpackcompose#mlkit#google
🚀Jetpack Compose — Chapter 5: Navigation in Compose🚀
Jetpack Compose provides a modern and intuitive way to build UI i Android. One essential aspect of building any Android app is handling
navigation between different screens. In Jetpack Compose, navigation is achieved using the Navigation component from the Jetpack Navigation Library, which offers a declarative way to move between screens.
Read Full Article 👇
https://lnkd.in/g9YRwpNc#jetpackcompose#jetpack#compose#jetpackcomposeUI#android#kotlin#androiddeveloper
The new GPT-4o realtime API for audio enables developers to build apps with speech-to-speech interactions. Learn how to build your own VoiceRAG app using the new model here: https://msft.it/6043m7BY7
Curious about integrating Claude 3 into your Bubble apps? I've got a step-by-step tutorial that walks you through the process. It's simpler than you might think!
Learn more 👉 https://lttr.ai/AUj4Z
As you embark on your Flutter development journey, you’ll encounter the need to manage environment-specific configurations, especially for sensitive data like API keys. Here, we’ll explore secure practices to effectively handle API keys in your Flutter app.
This time on my journey to make cool stuff, I attack a crucial, yet often overlooked, part of LLM app development: Evaluations & Benchmarking. Many dev teams rely on user feedback post deployment, or tinkering with their solution themselves before release, but that won’t continue to cut it. Even more frustrating is that general evaluations rarely correlate to how a model may perform in your own specific use case or work flow, what’s needed is hyper custom metrics for your specific application.
In my latest deep dive, I go over how I’ve set up my own custom evaluations, both hard coded tests and using more powerful LLMs to dynamically score and evaluate LLM app output, and how you can too, using LangChain's LangSmith. Check it out here: https://lnkd.in/evhtsMuz
La mia domanda è: quanto è efficiente Gemini con la scrittura di codice avanzato scalabile? Perché i primi passi sono semplici, la corsa in montagna è un'altra cosa... che dite?