Add My Bar, Bartender, Recommend features + drink images

- Drink Images: upload/display photos of bottles/cans on drink cards and detail pages
- My Bar: inventory tracker for spirits, liqueurs, mixers, bitters, garnishes, tools
- Bartender: AI-powered cocktail recipe generation, "what can I make" suggestions,
  saved recipes. Cross-references bar inventory for ingredient availability.
- Recommend: AI flavor profile analysis, personalized drink recommendations,
  "find similar" drinks based on highly-rated favorites
- Navigation: desktop sidebar with all 8 routes, mobile bottom nav with
  4 primary items + "More" popup menu
- New Prisma models: BarItem, Recipe, FlavorProfile
- Backup/restore updated to include bar items

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

src/lib/ai/prompts.ts

@@ -166,3 +166,119 @@ Do not include any text before or after the JSON array. Example format:
   }
 ]`
 }
+
+export const COCKTAIL_RECIPE_PROMPT = `You are an expert bartender and cocktail specialist. Generate a detailed cocktail recipe.
+
+The user's home bar inventory is provided. For each ingredient, indicate whether the user has it.
+
+## User's Bar Inventory
+{barInventory}
+
+## Instructions
+Create a recipe for the requested cocktail. Return a valid JSON object:
+- "title" (string): Cocktail name
+- "ingredients" (array): Each { "name": string, "amount": string, "available": boolean }
+- "steps" (string array): Step-by-step instructions
+- "garnish" (string, optional): Garnish description
+- "glassware" (string, optional): Recommended glass
+- "notes" (string, optional): Tips, variations, or history
+
+Mark ingredients available:true only if matching item exists in bar inventory. Do not include text before or after the JSON.`
+
+export const WHAT_CAN_I_MAKE_PROMPT = `You are an expert bartender. Based on the user's bar inventory, suggest cocktails they can make.
+
+## User's Bar Inventory
+{barInventory}
+
+## Instructions
+Suggest cocktails prioritizing those where ALL ingredients are available, then those missing 1-2 ingredients.
+
+Return a valid JSON array of objects:
+- "title" (string): Cocktail name
+- "ingredients" (array): Each { "name": string, "amount": string, "available": boolean }
+- "steps" (string array): Brief preparation steps
+- "garnish" (string, optional)
+- "glassware" (string, optional)
+- "missingCount" (number): How many ingredients missing (0 = can make now)
+
+Sort by missingCount ascending. Return up to 10. Do not include text before or after the JSON.`
+
+export function buildBarInventoryString(items: { name: string; category: string; quantity: string }[]): string {
+  const byCategory: Record<string, string[]> = {}
+  for (const item of items) {
+    if (item.quantity === "EMPTY") continue
+    if (!byCategory[item.category]) byCategory[item.category] = []
+    byCategory[item.category].push(`${item.name} (${item.quantity.toLowerCase()})`)
+  }
+  return Object.entries(byCategory)
+    .map(([cat, items]) => `### ${cat}\n${items.map(i => `- ${i}`).join('\n')}`)
+    .join('\n\n') || 'No items in bar inventory.'
+}
+
+export const FLAVOR_PROFILE_PROMPT = `You are an expert sommelier and drink taste profiler. Analyze the user's drink history and ratings to build a flavor profile.
+
+## User's Rated Drinks
+{drinkHistory}
+
+## Instructions
+Create a comprehensive flavor profile. Return a valid JSON object:
+- "summary" (string): 2-3 sentence natural language summary
+- "topFlavors" (string array): Top 5-8 flavor descriptors they prefer
+- "avoidFlavors" (string array): Flavors they tend to dislike
+- "preferredTypes" (string array): Preferred drink types/styles
+- "adventureScore" (number, 0-1): How adventurous/varied their choices are
+
+Do not include text before or after the JSON.`
+
+export const RECOMMEND_DRINK_PROMPT = `You are a drink recommendation expert. Based on the user's flavor profile and context, suggest drinks they'd enjoy.
+
+## User's Flavor Profile
+{flavorProfile}
+
+## Additional Context
+{context}
+
+## Instructions
+Recommend 3-5 drinks. Return a valid JSON array of objects:
+- "name" (string): Specific drink name
+- "type" (string): BEER, WINE, COCKTAIL, SPIRIT, or OTHER
+- "subType" (string, optional): Style
+- "brewery" (string, optional): Producer
+- "reason" (string): 1-2 sentence personalized explanation
+- "matchScore" (number, 0-1): How well it matches their profile
+
+Sort by matchScore descending. Do not include text before or after the JSON.`
+
+export const SIMILAR_DRINK_PROMPT = `You are a drink expert. The user loves a specific drink and wants similar ones.
+
+## Drink They Love
+{sourceDrink}
+
+## User's Flavor Profile
+{flavorProfile}
+
+## Instructions
+Suggest 3-5 similar drinks. Return a valid JSON array of objects:
+- "name" (string): Specific drink name
+- "type" (string): BEER, WINE, COCKTAIL, SPIRIT, or OTHER
+- "subType" (string, optional): Style
+- "brewery" (string, optional): Producer
+- "reason" (string): Why it's similar and why they'd like it
+- "similarity" (number, 0-1): How similar to the source drink
+
+Sort by similarity descending. Do not include text before or after the JSON.`
+
+export function buildDrinkHistoryString(drinks: { name: string; type: string; subType?: string | null; brewery?: string | null; avgRating: number | null; ratingCount: number; wouldReorder: boolean }[]): string {
+  return drinks
+    .filter(d => d.avgRating !== null)
+    .sort((a, b) => (b.avgRating ?? 0) - (a.avgRating ?? 0))
+    .map(d => {
+      const parts = [`${d.name} (${d.type})`]
+      if (d.subType) parts.push(`Style: ${d.subType}`)
+      if (d.brewery) parts.push(`From: ${d.brewery}`)
+      parts.push(`Rating: ${d.avgRating}/5 (${d.ratingCount} rating${d.ratingCount !== 1 ? 's' : ''})`)
+      if (d.wouldReorder) parts.push('Would reorder: Yes')
+      return `- ${parts.join(' | ')}`
+    })
+    .join('\n') || 'No rated drinks yet.'
+}

src/lib/ai/types.ts

@@ -42,6 +42,8 @@ export interface DrinkSearchResult {
 
 export interface AIProvider {
   name: string
+  sendTextRequest(systemPrompt: string, userMessage: string): Promise<string>
+  sendVisionRequest(systemPrompt: string, imageBase64: string, mimeType: string): Promise<string>
   extractMenuItems(imageBase64: string, mimeType: string): Promise<MenuExtractionResult>
   recommendDrinks(
     extractedItems: ExtractedMenuItem[],