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BlocksReal-world Examples
AI Profile Enrichment Form
AI Profile Enrichment Form
Analyze user profiles with AI and provide personalized suggestions. Enriches data, suggests improvements, and offers career insights.
Use this when users fill out a sparse profile form and you want AI to stream in the missing fields for them to review before accepting.
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Problems solved
Technical challenges this implementation handles out of the box.
- Enrich sparse profile forms into fuller structured profiles
- Generate missing profile fields with generateObject
- Let users review AI enrichments before accepting them
Use cases
Products and workflows this pattern is designed to support.
- CRM lead enrichment forms
- User onboarding profile completion
- Directory listing intake forms
- Marketplace seller profile builders
Compare with
Similar patterns, and when each one is the better fit.
Data Analysis AgentUse this when users upload a CSV or JSON dataset and need an agent to find correlations, outliers, and trends, then chart them and export a report.
AI Wizard Brand StrategyUse this when you are building a brand discovery or marketing onboarding flow where AI interviews gate progress and end in a written strategy.
HIL Agentic Context BuilderUse this when an agent must interview a user and research the web to build a brand profile, stopping once a completion tool fires.
AI Form GeneratorUse this when you are prototyping forms, such as surveys or admin inputs, and want a validated Zod schema generated from a description.
Setup
Requirements, wiring steps, and what this pattern adds to your project.
Getting started
Pick how you want to pull this pattern in. Then wire env vars and routes the same way.
- 1
Download → Next.js app
Use Download → Next.js app in the preview toolbar. You get a zip scaffold (Pro downloads rewrite preview `/view/.../api/*` paths to `/api/*` automatically).
- 2
Extract the zip and install dependencies
Unzip the archive, then run `pnpm install` (or npm / yarn) in the project folder.
- 3
Fill .env.local
The download includes .env.local placeholders when needed. Add real values for: OPENAI_API_KEY.
- 4
Customize the agent and tool files
Adapt prompts, tools, and stop conditions in the generated project for your product.
- 5
Run the app and open the pattern route
Run `pnpm dev`, open the setup/checklist page if present, then navigate to the generated pattern route and verify responses.
Environment variables
OPENAI_API_KEYGet key
Capabilities
AI SDK APIs
streamObjectcreateStreamableValueProviders
OpenAI
External services
streamobjectopenai-chat
Files added
5 files
app/page.tsxapp/layout.tsxapp/actions.tsxlib/schema.tslib/rate-limit.ts
Dependencies
18 total
npm packages
11AISDK@hookform/resolvers@base-ui/reactUpstashclass-variance-authoritylucide-reactmotionNext.jsReactreact-hook-formZod
Registry components
badgebuttoncardforminputtextareatooltip
Critical files
2 files
app/actions.tsxCore AI pipeline: uses streamObject with OpenAI and createStreamableValue to stream structured profile enrichment (tags, category, skill level, career suggestions) back to the client in real-time.
lib/schema.tsDefines the enrichedProfileSchema (suggestedTags, categoryMatch, skillLevel, careerSuggestions) and the profileFormSchema for input validation. Essential for the streamObject pipeline.
Requirements
- Complexity
- Intermediate
- Setup time
- ~10 minutes
- Node
- 24+
- Memory
- 256MB
