1790 results found

1. Integrate the new Google agent development kit and Agent to Agent frameworks
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   0 comments  ·  Firebase Studio  ·  Delete…  ·  Admin →
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2. Firebase Should Work With Kotlin Multiplatform

   KMP is now getting stable and the Firebase should be able to be used in these projects

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   0 comments  ·  SDKs  ·  Edit…  ·  Delete…  ·  Admin →
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3. please attach a gpu any one it will really help in ding mml stuffs sir .
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4. not every developer prefers to use github

   I like to use my local machines for version control for security reason and with Project IDX there seem to be no security as you can look at my code.

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   0 comments  ·  Firebase Studio  ·  Delete…  ·  Admin →
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5. Mirror other phones

   I need know how to do this

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   0 comments  ·  Emulators  ·  Edit…  ·  Delete…  ·  Admin →
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6. Fix the delete button

   If by design than disregard. The delete button and requires you use lowercase when typing. It should include upper and lower as a correct response to delete an app.

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   0 comments  ·  Other  ·  Edit…  ·  Delete…  ·  Admin →
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7. Hybrid On Device Inference using Firebase AI Logic. Mobile please.

   Hybrid On Device Inference using Firebase AI Logic. Mobile please.

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   0 comments  ·  Firebase AI Logic  ·  Edit…  ·  Delete…  ·  Admin →
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8. google adk

   Feature Request: Seamless Firebase Studio to Vertex AI Agent Engine DeploymentHigh-Level Goal: To empower non developers, especially those with limited coding experience, to build, customize, and deploy sophisticated AI agents by creating a seamless, low-code integration between Firebase Studio and the Vertex AI Agent Engine with use of Google ADK.The Vision: The "Why"The future of productivity lies in specialized AI agents that can automate tasks and provide intelligent assistance. Platforms like Google AgentSpace and the upcoming Google Workspace Gemini Apps will be the ecosystems where these agents live.However, there is currently a gap between the easy-to-use prototyping environment of Firebase Studio and the powerful, production-grade deployment environment of Vertex AI Agent Engine. Bridging this gap will democratize AI agent development. It will enable a much broader audience of creators—including business analysts, designers, and citizen developers—to bring their ideas to life without getting stuck on complex infrastructure and deployment hurdles.By simplifying this workflow, Firebase Studio can become the definitive starting point for creating agents destined for Google's entire agent ecosystem.The Proposal: The "How"I propose enhancing Firebase Studio with the following integrated features, creating a guided, end-to-end experience for agent development and deployment.1. Native Google ADK (Agent Development Kit) Starting Templates:What: Offer a gallery of pre-built agent templates within Firebase Studio based on the Google ADK. These could range from a simple "Q&A Bot" to a more complex "Research Assistant."Why: This gives users a solid, best-practice foundation to build upon, removing the need to start from a blank slate and understand the ADK's boilerplate code.2. Integrated "Toolbox" for Agent Capabilities:What: A simple, visual interface or "toolbox" within Firebase Studio to add tools to an agent. This would include:Google Search: A one-click integration to give the agent the ability to search the web for real-time information.Database Connectors (Your "MCP Toolbox"): Simplified connectors for common databases (like Cloud SQL, Firestore, BigQuery, and even common external databases). The user would provide credentials and connection details through a simple form, and Firebase Studio would handle the code for connecting the agent to that data source.Why: Abstracting away the complexity of API calls and database clients.3. Simplified Vertex AI RAG Configuration:What: An intuitive, guided workflow for setting up Retrieval-Augmented Generation (RAG). A user could simply point to a Google Drive folder, a Cloud Storage bucket, or a website, and Firebase Studio would manage the process of indexing that content and making it available to the agent for contextually relevant answers.Why: RAG is incredibly powerful but setting up vector embeddings and data pipelines is a major hurdle for non-specialists. Automating this makes grounding agents in specific knowledge accessible to everyone.4. One-Click "Deploy to Vertex AI Agent Engine" Button:What: The cornerstone of this request. A button in the Firebase Studio interface that automates the process of packaging the agent, configuring the necessary resources, and deploying it as a scalable, secure endpoint on the Vertex AI Agent Engine.Why: This is the "magic step" that removes the most significant barrier for low-code developers. It transforms agent deployment from a complex DevOps task into a simple, final step in the creative process.Summary of BenefitsAccelerates Innovation: Drastically reduces the time and expertise needed to go from an idea to a deployed AI agent.Drives Adoption: Encourages wider adoption of Google's entire AI stack (Firebase Studio, ADK, Vertex AI).Populates the Ecosystem: Creates a pipeline of high-quality, specialized agents ready for Google AgentSpace and Workspace, creating a vibrant and useful ecosystem for all users.Empowers a New Class of Creators: Unlocks the potential of non-traditional developers to build and contribute valuable AI solutions.

   Feature Request: Seamless Firebase Studio to Vertex AI Agent Engine DeploymentHigh-Level Goal: To empower non developers, especially those with limited coding experience, to build, customize, and deploy sophisticated AI agents by creating a seamless, low-code integration between Firebase Studio and the Vertex AI Agent Engine with use of Google ADK.The Vision: The "Why"The future of productivity lies in specialized AI agents that can automate tasks and provide intelligent assistance. Platforms like Google AgentSpace and the upcoming Google Workspace Gemini Apps will be the ecosystems where these agents live.However, there is currently a gap between the easy-to-use prototyping environment of Firebase… more

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9. Support other stack when using Prototype an app with AI

   • Instead of only supporting nextjs, tailwindcss. It can also support Vite, Angular, etc...
   • Also add option to help switch between normal workspace and being able to use Prototype an app with AI
   • Add Github management section: to be able to connect once, and then each workspace can connect automatically (create repository, push, ...), can be select existed repository when create new workspace
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10. Generated SDK types

    Given a schema with a nullable type

    type MyType @table() {
    id: uuid!
    nullableString: String
    }

    When running a query that selects records from MyType and filters out null values for nullableString, the generated SDK still types nullableString as string | null (or string? | null). Even though the query ensures no null values are returned for that field.

    It would be great if the SDK could be smarter and refine the generated type to just string when the query explicitly filters out null values for that field.

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    0 comments  ·  Data Connect  ·  Edit…  ·  Delete…  ·  Admin →
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11. Transaction should update the local offline cache

    It is a surprise to users (and Gemini) that writing documents using a transaction does not result in the local offline cache being updated when the transaction completes successfully. I'm not sure that it makes sense for the SDK to do this automatically but the firestore docs need to be updated (including the code examples) to make it clear that the local cache does not get updated. There may be some documents in the set being written that are never written by other users, in which case the local user is not expecting to have to have a listener running on those documents. If all the documents being written are in the same collection then having a listener running on that collection is the easy way to get the local cache updated. The docs for batched write could also point out that the local offline cache will be automatically updated. For all of the "set", "update" and batched write commands, the docs should explain whether the local cache gets updated or not even if the command fails. Also the docs should explain that a document read won't actually fetch a new copy of a document if the local offline cache is already up to date, which saves on egress costs but still incurs a document read charge because the document is actually read in the cloud, just not sent back to the client. Also in the docs, explain that for flutter web apps, the offline cache is disabled by default and that browsers (and end users) can delete some or all of the local cache and for IOS and maybe MACOS, if the web app isn't used for seven days, the operating system might delete the local cache.

    It is a surprise to users (and Gemini) that writing documents using a transaction does not result in the local offline cache being updated when the transaction completes successfully. I'm not sure that it makes sense for the SDK to do this automatically but the firestore docs need to be updated (including the code examples) to make it clear that the local cache does not get updated. There may be some documents in the set being written that are never written by other users, in which case the local user is not expecting to have to have a listener running… more

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    0 comments  ·  Firestore  ·  Edit…  ·  Delete…  ·  Admin →
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12. Make easier way to connect storage, database with auto updating rules

    Make easier way to connect storage, database with auto-updating rules. I've been trying to build things using Firebase Studio, but as non-coder, it's impossible for me to find ways for storage, database, authentication etc, can you make easier way for that? like just clicking options to get that or commanding by natural language and get those things done by AI?

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13. Feature Request: Support for Unreal Engine Blueprint Scripting and C++ Integration in Firebase Studio

    SUMMARY:

    Extend Firebase Studio's capabilities to support Unreal Engine development workflows, with a focus on:

    1. Blueprint scripting support (graphical & JSON-based editing)

    2. Remote-friendly Unreal C++ file editing

    3. Optional build hooks or compilation syncing between Firebase Studio and local Unreal Engine projects

    WHY THIS MATTERS

    Unreal Engine is a leading game engine used by indie and AAA studios alike. While Firebase Studio has embraced web and mobile frameworks, game developers - especially those building multiplayer games with Firebase backend services - lack a cloud-native dev environment.

    Adding Unreal support (particularly or Blueprint visual scripting and C++ editing) would open Firebase Studio to an entirely new class of developers building cross-platform games with cloud features like Auth, Firestore, and Realtime Database.

    PROPOSED FEATURES

    1. Bluprint Scripting Support (Editor Mode)

    • Allow importing .uasset or .json versions of Blueprint nodes into a graph-like editor

    • Enable JSON or DSL-based blueprint editing (for version control & portability)

    • Visual preview mode of Blueprint graphs with drag-and-drop or syntax-safe editing

    • Sync changes back to .uasset or export as Unreal-readable blueprint structure

    1. C++ Editor Enhancements for Unreal Projects

    • Add Unreal-aware syntax highlighting and IntelliSense for .cpp and .h files

    • Template detection for Unreal macros (e.g., UCLASS, UPROPERTY, UFUNCTION)

    • Auto-link to the Unreal Engine Documentation API when writing code

    • Git-based C++ sync between Firebase Studio and local Unreal projects

    1. Firebase-to-Unreal-Sync-Tools

    • One-click webhook or CLI tool to pull/push changes to a connected Unreal project

    • Optional "compilation assistant" to prep edited code into a ZIP or mountable volume for fast local compilation

    • Realtime sync with Firebase Functions for features like:
      ~ Cloud-hosted leaderboards
      ~ Multiplayer state sync
      ~ Analytics logging from Blueprints

    IMPACT

    • Opens Firebase Studio to game developers, not just app and web devs

    • Empowers Unreal developers to integrate Firebase easily (especially indie teams)

    • Encourages cloud-first workflow in Unreal without heavy DevOps setup

    • Enables lightweight prototyping from anywhere - even on low-end devices

    IDEAL USERS

    • Solo devs and indie teams using Firebase + Unreal

    • Students learning game dev in the cloud

    • Studios needing remote editing tools for collaborative Unreal work

    • Developers building cross-platform games with mobile + Firebase + Unreal

    FINAL THOUGHT

    By adding support for Blueprint scripting and better Unreal C++ integration, Firebase Studio can become the first truly cloud-native IDE for game developers, unlocking fast integrations, remove collaboration, and Firebase-powered game features - all without needing a heavy local setup.

    SUMMARY:

    Extend Firebase Studio's capabilities to support Unreal Engine development workflows, with a focus on:

    1. Blueprint scripting support (graphical & JSON-based editing)

    2. Remote-friendly Unreal C++ file editing

    3. Optional build hooks or compilation syncing between Firebase Studio and local Unreal Engine projects

    WHY THIS MATTERS

    Unreal Engine is a leading game engine used by indie and AAA studios alike. While Firebase Studio has embraced web and mobile frameworks, game developers - especially those building multiplayer games with Firebase backend services - lack a cloud-native dev environment.

    Adding Unreal support (particularly or Blueprint visual scripting and C++ editing) would open Firebase Studio… more

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14. Seamless integration with FIREBASE console features

    Enable developers to type or say things like:

    "Create a new Firebase project called EventManager. Add a Firestore collection named events with fields title, description, date. Enable Firebase Authentication with email/password. Generate a basic frontend form and deploy it using Firebase Hosting."

    And the Firebase Studio would:

    ✅ Automatically create the Firebase project (if permissions allow)

    ✅ Enable necessary products (Firestore, Authentication, Hosting, etc.)

    ✅ Create Firestore collections and initial schema definitions

    ✅ Setup authentication methods

    ✅ Preconfigure environment and allow instant deployment

    ✅ Visually reflect changes in Firebase Studio UI (without manual clicking around)

    🧩 Why This Is Needed
    Firebase Studio currently requires developers to:

    Manually create projects

    Enable Firestore/Auth individually

    Copy project IDs, API keys, and configure SDKs

    Manually define collections by pushing data

    This is tedious and repetitive, especially for rapid prototyping or junior developers.

    ✅ Benefits
    🕒 Saves time by automating boilerplate setup

    🧠 Makes Firebase beginner-friendly and more accessible

    ⚡️ Accelerates MVP and hackathon development

    🧩 Encourages deeper adoption of Firebase ecosystem

    🛠️ Reduces copy-paste errors in API key and project config

    ✨ Optional Advanced Features
    🌐 Natural language to Firestore Security Rules

    “Only allow users to read and write their own documents in the orders collection.”

    🔒 Natural language-based Auth rules and triggers

    📊 Automatically set up Realtime Analytics and Crashlytics

    💬 Preconfigured Cloud Functions using Gemini prompts

    Integrating Gemini AI into Firebase Studio for natural language project and schema setup would revolutionize the developer experience — turning Firebase into a true low-code, high-speed platform for modern FULLSTACK app development.

    Enable developers to type or say things like:

    "Create a new Firebase project called EventManager. Add a Firestore collection named events with fields title, description, date. Enable Firebase Authentication with email/password. Generate a basic frontend form and deploy it using Firebase Hosting."

    And the Firebase Studio would:

    ✅ Automatically create the Firebase project (if permissions allow)

    ✅ Enable necessary products (Firestore, Authentication, Hosting, etc.)

    ✅ Create Firestore collections and initial schema definitions

    ✅ Setup authentication methods

    ✅ Preconfigure environment and allow instant deployment

    ✅ Visually reflect changes in Firebase Studio UI (without manual clicking around)

    🧩 Why This Is Needed… more

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15. Snake app

    To exit this game

    1 vote

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16. Online transactions
    3 votes

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17. Firebase studio AI Prototyper erase .env

    Firebase studio AI Prototyper does not erase the whole .env if it edits it, OR it NEVER touches the .env and maybe writes to a .env.example. I have experienced this so many times after specifically telling the AI to NEVER TOUCH THE .ENV or adding it to the top of the blueprint.md...

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18. draw an app to make it a reality

    It would be really revolutionary if you could draw an app to create everything about it.

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19. Support for Django

    Along with python support please add Django and Flask project templates.

    51 votes

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    7 comments  ·  Firebase Studio  ·  Delete…  ·  Admin →
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20. SDK for .NET Maui to send Push Notifications

    An SDK to integrate push notifications in .NET Maui Apps

    3 votes

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    0 comments  ·  Cloud Messaging  ·  Delete…  ·  Admin →
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