{"passport":{"unfragile":{"@version":"1.0","version":"2026-05","artifact":{"id":"vercel-ai-chatbot","slug":"vercel-ai-chatbot","name":"Vercel AI Chatbot","type":"template","url":"https://github.com/vercel/ai-chatbot","page_url":"https://unfragile.ai/vercel-ai-chatbot","categories":["app-builders"],"tags":[],"pricing":{"model":"free","free":true,"starting_price":null},"status":"active","verified":false},"capabilities":[{"id":"vercel-ai-chatbot__cap_0","uri":"capability://tool.use.integration.multi.provider.ai.model.routing.with.streaming.responses","name":"multi-provider ai model routing with streaming responses","description":"Routes chat requests through Vercel AI Gateway to multiple LLM providers (OpenAI, Anthropic, Google, etc.) with automatic provider failover and streaming token-by-token responses back to the client. Uses the Vercel AI SDK's `generateText` and `streamText` APIs which abstract provider-specific APIs into a unified interface, with streaming handled via Server-Sent Events (SSE) from the `/api/chat` route.","intents":["I want to support multiple AI providers without rewriting provider-specific code","I need to switch between Claude, GPT-4, and Gemini based on cost or availability","I want streaming responses to appear in real-time without waiting for full completion"],"best_for":["teams building multi-model chatbot applications","developers wanting provider-agnostic AI integration","applications requiring cost optimization across LLM providers"],"limitations":["Vercel AI Gateway adds ~50-100ms latency per request for routing decisions","Provider-specific features (vision, function calling schemas) require adapter code","Streaming requires persistent HTTP connection; incompatible with some edge environments"],"requires":["Vercel AI SDK 6.0.37+","@ai-sdk/gateway 3.0.15+","API keys for at least one LLM provider (OpenAI, Anthropic, Google, etc.)","Node.js 18+ runtime"],"input_types":["text messages","conversation history (array of Message objects with role and content)","system prompts"],"output_types":["streaming text tokens","complete text response","structured tool call results"],"categories":["tool-use-integration","text-generation-language"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"vercel-ai-chatbot__cap_1","uri":"capability://text.generation.language.real.time.chat.streaming.with.client.side.state.synchronization","name":"real-time chat streaming with client-side state synchronization","description":"Implements bidirectional chat state management using the `useChat` hook from @ai-sdk/react, which maintains optimistic UI updates while streaming responses from the server. The hook automatically handles message queuing, loading states, and error recovery without manual state management, synchronizing client-side chat state with server-persisted messages via the `/api/chat` route.","intents":["I want the UI to show user messages immediately while waiting for AI response","I need to display streaming tokens as they arrive without blocking the UI","I want automatic error handling and retry logic for failed messages"],"best_for":["React developers building chat UIs","teams wanting zero-boilerplate chat state management","applications requiring responsive, low-latency chat experiences"],"limitations":["useChat hook is React-only; no Vue, Svelte, or vanilla JS support","Optimistic updates can diverge from server state if network errors occur mid-stream","No built-in conflict resolution for concurrent user edits to same message"],"requires":["React 18+ (hooks support)","@ai-sdk/react 3.0.39+","Next.js API route at `/api/chat` returning streaming responses"],"input_types":["user text input","file attachments (converted to base64 or URLs)","system context/prompts"],"output_types":["Message array with role/content/id","streaming text chunks","loading/error state flags"],"categories":["text-generation-language","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"vercel-ai-chatbot__cap_10","uri":"capability://data.processing.analysis.message.voting.and.feedback.collection","name":"message voting and feedback collection","description":"Allows users to upvote/downvote AI responses via the `/api/votes` endpoint, storing feedback in the database for model improvement and quality monitoring. Votes are associated with specific messages and can be used to identify problematic responses or train reward models. The UI includes thumbs-up/down buttons on each message.","intents":["I want to collect user feedback on AI response quality","I need to identify low-quality responses for retraining","I want to track which models produce better responses"],"best_for":["teams training reward models","applications needing quality metrics","developers building feedback loops for model improvement"],"limitations":["Votes are binary (up/down); no nuanced feedback","No automatic action on negative votes; requires manual review","Vote data is not anonymized; can be traced to users"],"requires":["Database table for storing votes","API endpoint to record votes","UI components for vote buttons"],"input_types":["message ID","vote direction (up/down)","user ID for attribution"],"output_types":["vote confirmation response","aggregated vote counts per message","feedback reports for analysis"],"categories":["data-processing-analysis","safety-moderation"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"vercel-ai-chatbot__cap_11","uri":"capability://text.generation.language.shadcn.ui.component.library.with.tailwind.css.styling","name":"shadcn/ui component library with tailwind css styling","description":"Uses shadcn/ui (Radix UI primitives + Tailwind CSS) for all UI components, providing a consistent, accessible design system with dark mode support. Components are copied into the project (not npm-installed), allowing customization without forking. Tailwind configuration enables responsive design and theme customization via CSS variables.","intents":["I want a polished, accessible UI without building from scratch","I need dark mode support with minimal effort","I want to customize component styling to match my brand"],"best_for":["teams wanting production-ready UI quickly","developers comfortable with Tailwind CSS","applications requiring accessibility compliance"],"limitations":["shadcn/ui components are copied into project; updates require manual re-copying","Tailwind CSS increases bundle size by ~50KB (mitigated by PurgeCSS)","Component customization requires CSS knowledge; limited visual builder support"],"requires":["Tailwind CSS 3.0+","shadcn/ui CLI for component scaffolding","React 18+ for component compatibility"],"input_types":["component props (variant, size, disabled, etc.)","Tailwind class names for styling"],"output_types":["rendered HTML components","styled UI with dark mode support","accessible ARIA attributes"],"categories":["text-generation-language","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"vercel-ai-chatbot__cap_12","uri":"capability://code.generation.editing.typescript.type.safety.across.full.stack","name":"typescript type safety across full stack","description":"Enforces strict TypeScript typing from database schema (via Drizzle) through API routes to React components, catching type mismatches at compile time. Database types are automatically generated from Drizzle schema definitions, API responses are typed via Zod schemas, and React components use strict prop types. This eliminates entire classes of runtime errors.","intents":["I want to catch type errors before deployment","I need confidence that API contracts match client expectations","I want IDE autocomplete for database queries and API responses"],"best_for":["teams prioritizing code quality and maintainability","developers using TypeScript for the first time","applications with complex data models"],"limitations":["TypeScript compilation adds ~5-10s to build time","Type definitions can become verbose for complex nested structures","Runtime validation (Zod) adds overhead; not suitable for high-throughput APIs"],"requires":["TypeScript 5.0+","tsconfig.json with strict mode enabled","Drizzle ORM for database type generation","Zod for runtime schema validation"],"input_types":["TypeScript source files","Drizzle schema definitions","Zod schema definitions"],"output_types":["compiled JavaScript","type declaration files (.d.ts)","runtime validation errors"],"categories":["code-generation-editing","safety-moderation"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"vercel-ai-chatbot__cap_13","uri":"capability://automation.workflow.playwright.end.to.end.testing.framework","name":"playwright end-to-end testing framework","description":"Includes Playwright test suite for automated browser testing of chat flows, authentication, and UI interactions. Tests run in headless mode and can be executed in CI/CD pipelines. The test suite covers critical user journeys like sending messages, uploading files, and sharing conversations.","intents":["I want to automate testing of chat interactions","I need to verify authentication flows work correctly","I want to catch UI regressions before deployment"],"best_for":["teams with CI/CD pipelines","developers wanting automated regression testing","applications with complex user flows"],"limitations":["Playwright tests are slow (~5-10s per test); not suitable for TDD","Tests are brittle if UI selectors change frequently","No built-in visual regression testing; requires additional tools"],"requires":["@playwright/test package","playwright.config.ts configuration","CI/CD environment with browser support"],"input_types":["test specifications (user actions, assertions)","test data (credentials, chat messages)"],"output_types":["test results (pass/fail)","screenshots on failure","test reports for CI/CD"],"categories":["automation-workflow","safety-moderation"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"vercel-ai-chatbot__cap_2","uri":"capability://memory.knowledge.persistent.chat.history.with.postgresql.and.drizzle.orm","name":"persistent chat history with postgresql and drizzle orm","description":"Stores all chat messages, conversations, and metadata in PostgreSQL using Drizzle ORM for type-safe queries. The data layer abstracts database operations through query functions in `lib/db` that handle message insertion, retrieval, and conversation management. Messages are persisted server-side after streaming completes, enabling chat resumption and history browsing across sessions.","intents":["I want users to resume conversations after closing the browser","I need to query chat history for analytics or moderation","I want to support conversation forking and branching"],"best_for":["applications requiring persistent user data","teams using PostgreSQL as primary datastore","developers wanting type-safe database queries in TypeScript"],"limitations":["Drizzle ORM adds ~10-20ms per query due to abstraction overhead","No built-in sharding; single PostgreSQL instance becomes bottleneck at >10k concurrent users","Message versioning requires manual implementation; no automatic diff tracking"],"requires":["PostgreSQL 12+ database (Neon Serverless recommended)","drizzle-orm 0.34.0+","postgres driver 3.4.4+","DATABASE_URL environment variable with connection string"],"input_types":["Message objects (role, content, createdAt)","Conversation metadata (title, visibility)","User IDs for access control"],"output_types":["Message arrays with full metadata","Conversation objects with message counts","Query results as typed TypeScript objects"],"categories":["memory-knowledge","data-processing-analysis"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"vercel-ai-chatbot__cap_3","uri":"capability://tool.use.integration.tool.function.calling.with.weather.data.and.document.generation","name":"tool/function calling with weather data and document generation","description":"Implements schema-based function calling where the AI model can invoke predefined tools (weather lookup, document creation, suggestion generation) by returning structured function calls. The `/api/chat` route defines tool schemas using Vercel AI SDK's `tool()` API, executes the tool server-side, and returns results back to the model for context-aware responses. Supports multi-turn tool use where the model can chain multiple tool calls.","intents":["I want the AI to fetch real-time weather data and incorporate it into responses","I need the AI to create and save documents/artifacts based on conversation context","I want the AI to generate suggestions and persist them to the database"],"best_for":["applications requiring AI-driven automation","teams building AI agents with external integrations","developers wanting structured AI outputs for downstream processing"],"limitations":["Tool schemas must be manually defined; no automatic schema generation from function signatures","Tool execution is synchronous; long-running tools (>5s) may timeout in serverless environments","No built-in tool result caching; repeated calls to same tool re-execute"],"requires":["Vercel AI SDK 6.0.37+ with tool() API","Tool implementations as async functions returning structured data","Model support for function calling (GPT-4, Claude 3+, Gemini Pro)"],"input_types":["tool schema definitions (name, description, parameters)","tool execution parameters (typed based on schema)","conversation context for tool decision-making"],"output_types":["tool call results (JSON-serializable objects)","model responses incorporating tool results","persisted artifacts/documents"],"categories":["tool-use-integration","planning-reasoning"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"vercel-ai-chatbot__cap_4","uri":"capability://image.visual.multimodal.input.with.file.attachments.and.base64.encoding","name":"multimodal input with file attachments and base64 encoding","description":"Accepts file uploads (images, documents) through the `MultimodalInput` component, converts them to base64 or URLs via Vercel Blob storage, and passes them to the AI model as multimodal context. The `/api/upload` route handles file storage, while the chat component embeds file references in message history for vision-capable models to process.","intents":["I want users to upload images for the AI to analyze","I need to support document uploads for content summarization","I want file attachments to persist in chat history"],"best_for":["applications requiring vision/document analysis","teams building document-centric chatbots","developers wanting simple file handling without S3 setup"],"limitations":["File size limited by serverless function timeout (typically 30s); large files (>100MB) may fail","Base64 encoding increases message size by 33%; impacts token usage and latency","Vision models have different image format support; no automatic format conversion"],"requires":["@vercel/blob 0.24.1+ for file storage","BLOB_READ_WRITE_TOKEN environment variable","Vision-capable model (GPT-4V, Claude 3 Vision, Gemini Pro Vision)"],"input_types":["image files (JPEG, PNG, WebP, GIF)","document files (PDF, text)","binary data via FormData"],"output_types":["file URLs in Vercel Blob storage","base64-encoded file content","multimodal message objects with file references"],"categories":["image-visual","data-processing-analysis"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"vercel-ai-chatbot__cap_5","uri":"capability://safety.moderation.nextauth.based.authentication.with.guest.and.registered.modes","name":"nextauth-based authentication with guest and registered modes","description":"Implements user authentication using NextAuth 5.0 with support for both guest (anonymous) and registered user flows. The middleware in `lib/auth.ts` protects routes, while login/registration pages handle credential-based auth. Guest users get temporary session IDs for chat history, while registered users have persistent accounts with email verification and password reset capabilities.","intents":["I want to allow users to chat without signing up","I need to support email/password registration with verification","I want to track user identity for analytics and moderation"],"best_for":["applications wanting frictionless onboarding","teams using NextAuth for authentication","developers building multi-tenant SaaS chatbots"],"limitations":["NextAuth 5.0 is beta; API may change before stable release","Guest sessions are ephemeral; no automatic cleanup of abandoned sessions","Email verification requires SMTP setup; no built-in email provider"],"requires":["next-auth 5.0.0-beta.25+","NEXTAUTH_SECRET environment variable","NEXTAUTH_URL matching deployment domain","Email provider credentials (SendGrid, Resend, etc.) for verification"],"input_types":["email and password credentials","OAuth provider tokens (if configured)","session cookies"],"output_types":["session objects with user ID and email","JWT tokens for API authentication","user entitlement/role information"],"categories":["safety-moderation","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"vercel-ai-chatbot__cap_6","uri":"capability://memory.knowledge.artifact.document.creation.and.versioning.system","name":"artifact/document creation and versioning system","description":"Allows the AI to create and update code snippets, documents, or other artifacts through tool calls, which are stored as separate entities with version history. The `Document and Artifact System` tracks changes via `document_versions` table, enabling users to view diffs and revert to previous versions. Artifacts are rendered in a side panel with syntax highlighting for code and rich editing for documents.","intents":["I want the AI to generate code that I can edit and iterate on","I need to track changes to AI-generated documents","I want to revert artifacts to previous versions"],"best_for":["applications generating code or documents","teams needing audit trails for AI-generated content","developers building collaborative editing features"],"limitations":["Version history is append-only; no automatic cleanup of old versions","Diff computation is client-side only; no server-side diff API","No concurrent editing support; last-write-wins conflict resolution"],"requires":["PostgreSQL with `documents` and `document_versions` tables","Drizzle ORM migrations for schema setup","React component library for artifact rendering"],"input_types":["artifact type (code, document, etc.)","artifact content (text, code)","version metadata (author, timestamp)"],"output_types":["artifact objects with version history","diff objects showing changes between versions","rendered artifact UI with syntax highlighting"],"categories":["memory-knowledge","code-generation-editing"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"vercel-ai-chatbot__cap_7","uri":"capability://safety.moderation.chat.visibility.and.sharing.controls.with.public.private.modes","name":"chat visibility and sharing controls with public/private modes","description":"Implements conversation-level access control where users can mark chats as private (only visible to owner) or public (shareable via URL). The database schema includes `visibility` column on conversations, and middleware enforces access checks before rendering chat content. Public chats generate shareable URLs that bypass authentication for read-only access.","intents":["I want to keep some conversations private","I need to share a specific conversation with others via URL","I want to prevent unauthorized access to sensitive conversations"],"best_for":["multi-user chatbot applications","teams needing conversation privacy controls","applications supporting content sharing"],"limitations":["No granular permissions; visibility is binary (private/public)","Public URLs are permanent; no automatic expiration","No audit logging of who accessed shared conversations"],"requires":["Database column for visibility status","Middleware to check user ownership before rendering","URL generation logic for public share links"],"input_types":["visibility setting (private/public)","user ID for ownership verification","chat ID for access control"],"output_types":["shareable URLs for public conversations","access denied responses for unauthorized requests","visibility metadata in conversation objects"],"categories":["safety-moderation","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"vercel-ai-chatbot__cap_8","uri":"capability://automation.workflow.resumable.streaming.with.redis.state.recovery","name":"resumable streaming with redis state recovery","description":"Stores in-flight streaming state in Redis to enable resumption if the connection drops mid-stream. When a user reconnects, the system retrieves the partial response from Redis and continues streaming from where it left off, rather than restarting the entire request. This is implemented via Redis keys keyed by chat ID and message ID.","intents":["I want streaming responses to survive network interruptions","I need to resume long-running AI responses without restarting","I want to minimize wasted tokens on failed requests"],"best_for":["applications with unreliable network conditions","teams supporting mobile users with spotty connectivity","applications with long-running AI responses (>30s)"],"limitations":["Redis adds ~5-10ms latency per state check","State recovery only works within same session; cross-device resumption not supported","Redis keys must be manually cleaned up; no automatic TTL expiration"],"requires":["redis 5.9.0+ client library","REDIS_URL environment variable with connection string","Redis instance with sufficient memory for concurrent streams"],"input_types":["chat ID and message ID for state key","partial streaming response data","connection status indicators"],"output_types":["recovered partial response from Redis","continuation token for resuming stream","updated message state"],"categories":["automation-workflow","memory-knowledge"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"vercel-ai-chatbot__cap_9","uri":"capability://safety.moderation.rate.limiting.and.entitlement.based.feature.access","name":"rate limiting and entitlement-based feature access","description":"Enforces per-user rate limits on API calls and gates premium features based on user entitlements (free vs paid tiers). Rate limiting is implemented via middleware that checks request counts against time windows, while entitlements are stored in the user object and checked before allowing access to premium models or tools.","intents":["I want to prevent abuse by limiting requests per user","I need to offer free and paid tiers with different feature access","I want to track usage for billing purposes"],"best_for":["SaaS applications with usage-based pricing","teams needing abuse prevention","applications supporting multiple subscription tiers"],"limitations":["Rate limiting is per-instance; distributed systems need Redis-backed counters","No built-in billing integration; requires manual entitlement management","Rate limit headers not standardized; clients must parse custom headers"],"requires":["Middleware implementation for rate limit checks","User entitlement data in session/database","Rate limit configuration (requests per minute, etc.)"],"input_types":["user ID for rate limit tracking","entitlement tier (free/pro/enterprise)","request metadata (model, tool used)"],"output_types":["429 Too Many Requests responses","403 Forbidden for unauthorized features","usage metrics for billing"],"categories":["safety-moderation","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"vercel-ai-chatbot__headline","uri":"capability://app.builders.ai.chatbot.template.for.rapid.development","name":"ai chatbot template for rapid development","description":"A full-featured AI chatbot template built with Next.js and Vercel AI SDK, designed for developers seeking to create production-ready chat applications with multi-provider support and real-time interactions.","intents":["best AI chatbot template","AI chatbot for Next.js","production-ready chatbot solution","full-stack chatbot development","AI chatbot with multi-provider support"],"best_for":["developers looking to build chat applications quickly"],"limitations":[],"requires":["Next.js knowledge","familiarity with Vercel AI SDK"],"input_types":["text","file uploads"],"output_types":["chat responses","chat history"],"categories":["app-builders"],"confidence":0.5,"matches":0,"success_rate":0}],"trust":{"score":55,"verified":false,"data_access_risk":"high","permissions":["Vercel AI SDK 6.0.37+","@ai-sdk/gateway 3.0.15+","API keys for at least one LLM provider (OpenAI, Anthropic, Google, etc.)","Node.js 18+ runtime","React 18+ (hooks support)","@ai-sdk/react 3.0.39+","Next.js API route at `/api/chat` returning streaming responses","Database table for storing votes","API endpoint to record votes","UI components for vote buttons"],"failure_modes":["Vercel AI Gateway adds ~50-100ms latency per request for routing decisions","Provider-specific features (vision, function calling schemas) require adapter code","Streaming requires persistent HTTP connection; incompatible with some edge environments","useChat hook is React-only; no Vue, Svelte, or vanilla JS support","Optimistic updates can diverge from server state if network errors occur mid-stream","No built-in conflict resolution for concurrent user edits to same message","Votes are binary (up/down); no nuanced feedback","No automatic action on negative votes; requires manual review","Vote data is not anonymized; can be traced to users","shadcn/ui components are copied into project; updates require manual re-copying","builder identity is not verified yet","no observed match outcomes yet"],"rank_breakdown":{"adoption":0.7,"quality":0.9,"ecosystem":0.39999999999999997,"match_graph":0.25,"freshness":0.52,"weights":{"adoption":0.25,"quality":0.25,"ecosystem":0.1,"match_graph":0.35,"freshness":0.05}},"observed_outcomes":{"matches":0,"success_rate":0,"avg_confidence":0,"top_intents":[],"last_matched_at":null},"maintenance":{"status":"active","updated_at":"2026-06-17T09:51:05.297Z","last_scraped_at":null,"last_commit":null},"community":{"stars":null,"forks":null,"weekly_downloads":null,"model_downloads":null,"model_likes":null}},"distribution":{"claim_url":"https://unfragile.ai/submit?claim=vercel-ai-chatbot","compare_url":"https://unfragile.ai/compare?artifact=vercel-ai-chatbot"}},"signature":"KNqh/3DN7xizFLHiOOpiUXLntMj5g0TEcPgNY5swuIX6Ob8Xv6vNqsBsohndvXxRQ5xW1xz7gM3zHvE3ey9+Cw==","signedAt":"2026-06-22T05:28:49.290Z","signedBy":"unfragile.ai","version":1},"_links":{"self":"https://unfragile.ai/api/v1/passport/vercel-ai-chatbot","artifact":"https://unfragile.ai/vercel-ai-chatbot","verify":"https://unfragile.ai/api/v1/verify?slug=vercel-ai-chatbot","publicKey":"https://unfragile.ai/api/v1/trust-passport-public-key","spec":"https://unfragile.ai/trust","schema":"https://unfragile.ai/schema.json","docs":"https://unfragile.ai/docs"}}