AI features for your app

Normally, adding AI to an app means choosing a provider, managing API keys, setting up billing, securing credentials, and wiring model calls into your backend. Lovable’s built-in AI connector handles that setup for you, so you can add AI features to your app by describing what you want to build. These AI features run inside your app. They are separate from the Lovable agent that helps you build and edit your project. Some examples include:

• Summaries: automatically condense long text into clear takeaways.
• Chatbots and assistants: build conversational helpers into your app.
• Sentiment detection: understand user feedback at scale.
• Document Q&A: let users ask questions directly against your content.
• Creative generation: brainstorm ideas, draft copy, or expand concepts.
• Translation: serve users across languages.
• Image and document analysis: extract, summarize, and interpret key information from unstructured content.
• Workflow automation: handle repetitive or multi-step tasks inside your app.
• Semantic search and retrieval-augmented generation (RAG): search documents, knowledge bases, and content by meaning instead of exact keywords.
• Text-to-speech: turn text into spoken audio for voice narration, read-aloud, and audio-first experiences.
• Speech-to-text: transcribe voice notes, recordings, and meetings, and add voice input or dictation.

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Enabling the built-in AI connector

By default, the built-in AI connector is enabled for your workspace, and Lovable can add AI features to your app when requested. You can manage the built-in AI connector for your projects in Connectors → App connectors → Lovable AI → Manage permissions. Workspace admins can also disable the built-in AI connector entirely for the workspace from Connectors → App connectors → Lovable AI.

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Permission preferences

The default setting is Always allow, meaning the built-in AI connector can be used automatically in your projects. You can change your preference anytime from Connectors → App connectors → Lovable AI → Manage permissions. Choose between:

• Always allow: Lovable automatically performs the action without asking for review or approval.
• Ask each time: Lovable asks for your approval whenever the action is needed. For example, if you want to add a chatbot, you can:
  • Allow: enable the integration for the current project.
  • Deny: decline the integration for this request. You may be asked again later.
  • Adjust preferences: change the default behavior for future projects. This does not affect the current project.
• Never allow: Lovable blocks the action, informs you that AI is required, and instructs you to enable the built-in AI connector.

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How it works

Lovable sets up the AI infrastructure for you:

• API key: Lovable automatically generates and manages a LOVABLE_API_KEY for each project. You never need to create or provide it yourself. When a project is remixed, a fresh key is generated for the new project automatically.
• Backend calls: AI calls run through a secure backend edge function that Lovable creates for you. Calls are never made directly from the browser, which keeps your credentials and prompts server-side.
• Streaming: the built-in AI connector supports streaming responses with server-sent events (SSE). Lovable uses streaming by default for chatbot and assistant features, so responses appear token by token rather than all at once.

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Supported models for AI features in your app

When you ask Lovable to add or update an AI feature, you can name a supported model or describe what you want and let Lovable pick the right one. Each model links to its official source for technical details.

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Choosing a model

Not sure which to use? Describe what you want, and Lovable picks a model for you. This table shows where to start and when you might switch.

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Chat models

Chat models power conversational and text features: chatbots, assistants, summaries, document Q&A, translation, classification, and extraction. They range from fast, low-cost models for simple tasks to high-reasoning models for complex work. Ask Lovable to:

• Build a chatbot or in-app assistant.
• Summarize long text, documents, or transcripts.
• Answer questions from your own content.
• Classify, extract, or translate text.

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Image models

Image models generate and edit images from text prompts, uploaded images, or both. Use them for visual assets, product mockups, marketing imagery, and in-app image editing. Ask Lovable to:

• Generate images from a text description.
• Edit or restyle an uploaded image.
• Create product mockups or marketing visuals.
• Produce thumbnails or illustrations on demand.

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Embedding models

Embedding models turn content into a format that can be searched by meaning instead of exact keywords. Use them for semantic search, retrieval-augmented generation (RAG), FAQ bots, document search, and knowledge bases. Ask Lovable to:

• Build semantic search over uploaded documents.
• Create a FAQ bot that answers from your help content.
• Build a company knowledge base that finds relevant internal docs.

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Text-to-speech models

Text-to-speech models turn text into natural-sounding spoken audio, so your app can read content aloud, narrate generated text, or talk back. Describe the voice feature you want, and Lovable wires up the backend and picks the right settings. Speech streams as it is generated by default, so playback can begin before the full clip is ready, and you can describe the tone or pacing you want in plain language (for example, “speak slowly and warmly”). Ask Lovable to:

• Add a “read aloud” button that speaks an article or summary.
• Narrate AI-generated stories, lessons, or briefings.
• Turn a book or document into an audiobook.
• Build a voice assistant that responds with spoken audio.

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Speech-to-text models

Speech-to-text models turn spoken audio into text, so people can talk to your app instead of typing and your app can work with what they said. Upload a voice note, call recording, or meeting audio, and the app transcribes it. Transcription streams as it is produced by default; because these features run in real time, very long recordings may time out, so transcribe long audio in segments. Ask Lovable to:

• Build a meeting assistant that turns a recording into notes and action items.
• Add voice input or dictation so users can speak instead of type.
• Transcribe and search voice memos.
• Caption or subtitle uploaded audio.

Combine text-to-speech and speech-to-text to build apps people can have a real back-and-forth with, such as voice assistants, two-way translators, and hands-free helpers.

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Monitor AI usage and activity

Every project has an AI activity dashboard under Cloud → AI that shows what your app’s AI features cost and how they are performing. Use it to track spend, spot failed requests, and inspect individual AI calls. Choose a time range to summarize recent AI activity. Three cards show:

• Total cost: the credits your app’s AI requests used in the selected range.
• Success rate: the percentage of requests that completed successfully.
• Avg. Duration: the average time a request took, in milliseconds.

How far back you can view activity depends on your plan: Free workspaces can view the last 24 hours, and paid plans can view the last 90 days.

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AI activity

Below the summary, AI activity lists recent AI requests, newest first. Each entry shows its status, a title taken from the request, when it ran, the model used, the input and output tokens, the credits it cost, and how long it took. When an AI action takes several steps, they appear together as a single run so you can see the cost of each step. Lovable always records this summary information for every AI request, so the dashboard and activity list work whether or not request details are captured.

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Capture request details

To inspect the full content of a request, turn on Capture request details from Cloud → AI. When it is on, Lovable stores the redacted request and response payloads, so you can open a request in the activity list and see what was sent and returned. Secrets are removed before storage, and captured details are kept for 90 days. The default depends on your plan:

• Free and Pro: capture is on by default.
• Business and Enterprise: capture is off by default, and you can turn it on per project.

Project editors can change this setting anytime per project. When capture is off, the dashboard and activity list still work from summary data; you just cannot open a request to see its payload.

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Usage and pricing

AI gateway usage is measured when AI features inside your deployed app make model calls. These requests are separate from the Lovable agent that helps you plan, build, and edit your project. AI gateway usage uses credits. Credit usage depends on the model used and the amount of work performed, such as text tokens, generated images, audio processing, call volume, or other provider-reported usage. AI gateway usage rates are based on the underlying provider model costs. To estimate relative model costs, refer to the official provider pricing sources linked from the supported model list. On Free plans, AI gateway usage draws from the monthly AI grant first. After that, it draws from general credits where available. To review AI gateway usage, go to Settings → Plans & credit usage → Usage details and select Run credits. For more information about AI gateway costs, monthly AI grants, top-ups, auto top-up, alerts, and usage tracking, see Credits and usage.

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Cancelled requests

If your app cancels an in-flight AI request, some usage may still be counted. The built-in AI connector waits briefly for the provider to finish and report final usage before closing the connection. Provider behavior on cancelled requests varies, so some usage may still be billed even if the app closes the connection before the response finishes.

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Workspace rate limits

To ensure reliable performance and fair access for all users, the built-in AI connector applies rate limits per workspace. These limits help maintain system stability, prevent abuse, control costs, and provide a consistent experience for everyone. If your app’s requests exceed the allowed rate, the server returns a 429 Too Many Requests status code and the request will not be processed. If your workspace runs out of credits, the server returns a 402 Payment Required status code. You can restore access by adding credits or enabling auto top-up in Settings → Plans & credit usage. For more information, see Credits and usage. Rate limits are more restrictive for free users, while paid plans include higher thresholds and greater flexibility.

• Free plan users: upgrade anytime to increase your limits.
• Paid plan users: contact Lovable Support if you need additional capacity.

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FAQ