AI chat & AI code completion in files & input block improvements

AI chat: your data thinking partner

While our AI has always been excellent at executing tasks, we recognize that sometimes you need a thinking partner rather than a doer. That's why we're introducing a dedicated AI chat interface for more exploratory conversations about your data challenges. Check out our quick video below to see it in action!

Located in the bottom right corner of your projects, this new chat window creates a space where you can freely brainstorm ideas, discuss analytical approaches, and explore potential solutions before committing to code. It's perfect for those moments when you're still formulating your thoughts or need guidance on the best way forward.

The chat interface is fully integrated with your project environment - it understands your data, notebooks, and overall context. Ask it how to tackle a specific analysis problem, request suggestions for improving your notebooks, or explore different methodological approaches, all through natural conversation.

We've also enhanced it with comprehensive knowledge about Deepnote itself. Need help finding a feature or understanding how something works? The AI can quickly answer your Deepnote-related questions, saving you a trip to the documentation and keeping you focused on your work.

This new chat interface is just the first step in our effort to create a unified and more powerful AI agent experience in Deepnote. We don't want to spoil surprises, but here's a tiny sneak peek: what if the AI could turn your messy exploration into a structured, executable data story with a single prompt? That's all we'll say for now - watch this space!

AI code completion: now in the file editor

We've brought our popular AI code completion to the file editor! Now you can enjoy intelligent code suggestions while editing Python scripts, including Streamlit apps.

This enhancement gives you the same great experience you're used to in notebooks. The completions are lightning-fast as you type and contextually aware - understanding your project files and integrations to provide relevant suggestions. It's particularly handy when building Streamlit apps that connect to data - code for accessing your files and setting up data connections will be automatically suggested.

Working on scripts outside of notebooks just got a whole lot smoother. Whether you're building a Streamlit application or maintaining utility files, our AI assistant is ready to help speed up your coding.

Input block improvements

We've shipped several upgrades to our interactive inputs based on your requests! These improvements give you more flexibility when building data apps.

First, we're introducing a new date range input block. Now you can select both start and end dates from a single widget instead of managing them separately. We've also added relative date options like "last 7 days" or "last month," making it easier for your stakeholders to navigate dashboards.

You can now define specific default values for your input blocks too. Simply go to the block settings and set a default value. When someone opens your app in 'run app from scratch' mode, they'll see these defaults right away, giving you better control over their initial experience.

We've also added support for empty states in select inputs. Previously, you always needed to have a value selected in dropdown menus. Now you can enable the 'allow empty values' setting, letting users remove all selections when needed. This is particularly useful for workflows that start from a blank state or for removing filters. Remember: if you enable empty selection, make sure your code or SQL can handle None values.