Fuego 1.0.0: A Milestone in Stability and Enterprise Features

Complete Firestore Index Management

One of the most requested features is finally here: Fuego now offers complete Firestore index management directly from the application.

What you can do:

• View all your database indexes with detailed information
• Delete obsolete or unnecessary indexes
• Create missing indexes when your queries require them
• Compare indexes across different databases (perfect for keeping staging and production in sync)
• Synchronize indexes between environments by creating missing ones or removing unnecessary ones

This feature solves one of the biggest pain points in Firestore development: no more constant switching between your app and the Firebase console to manage indexes. Everything is now just a click away, with the ability to compare configurations across environments and ensure production and staging have the same indexes.

Real-world use case: During deployment of a new feature requiring complex queries, you can create the necessary indexes in staging, test them, and then quickly sync them to production with confidence that the configuration is identical.

Full Vector Data Support

With the explosion of AI and machine learning-based applications, vector data has become essential. Fuego 1.0.0 introduces full support for Firestore’s Vector data type, for both float32 and float64.

Available features:

• Visualization of vector fields in documents with clear formatting
• Export/Import of documents containing vectors
• Direct editing of vector values in the document editor
• findNearest queries for vector similarity searches
• Embedding creation through integrated AI providers

AI Providers for Vector Embeddings

This is probably the most innovative feature of 1.0.0: you can configure AI providers directly in Fuego to automatically generate vector embeddings.

Supported providers:

• Google: Gemini and Vertex AI Backends
• OpenAI: all embedding models
• Ollama: for local and privacy-first solutions
• OpenAI-compatible providers: any service implementing OpenAI APIs

Practical use cases:

1. Semantic search: Configure a provider, generate embeddings for your content, and use findNearest queries to implement intelligent search based on meaning rather than keywords.

2. Embedding migration: Want to change embedding models? With batch modifications, you can regenerate all existing vectors in your database using a new provider, making migration simple and fast.

3. Local testing: Use Ollama to test your implementation locally without API costs, then switch to a cloud provider in production.

findNearest Queries: Powerful Vector Search

findNearest queries allow you to search for similar documents based on vector distance. Fuego now fully supports this query type with an intuitive interface.

Specify your search vector (generated by your AI provider or entered manually), the desired number of results, and optionally a maximum distance filter. Fuego builds the optimal query and shows you results ordered by similarity.

Practical example: In an e-commerce app, you can implement “similar products” by loading a product’s embedding and using findNearest to find items with similar characteristics.

Quick Access to Emulators

For developers working locally with Firebase emulators, the “Emulators” menu now automatically lists all emulators found on your machine. One click and you’re connected, without manually entering hosts and ports.

Improvement of Existing Tools

We’ll continue to refine current features based on user feedback. The goal is to make every interaction with Firestore even smoother and more intuitive.

Keyboard Navigation and Shortcuts

We’re investing heavily in improving the experience for power users. More shortcuts, complete keyboard navigation, and a command palette to quickly access any feature without ever touching the mouse.

Linux Build

One of the most frequent requests: we’re working to officially bring Fuego to Linux, expanding availability to all major operating systems.

Signed Build for Windows

To eliminate Windows Defender warnings and ensure an even more secure installation, we’ll implement code signing for Windows builds.

Team Version

This is the most important upcoming feature: a team version of Fuego that will allow:

• Sharing configurations and connections among team members
• Managing centralized permissions and access
• Collaborating in real-time on queries and databases
• Audit logs of performed operations

Good news for current users: all existing plans will be able to automatically migrate to the new teams when the feature becomes available, maintaining all current benefits and adding collaborative capabilities.