feat: Implement data source management and analysis flow, allowing users to add and analyze websites for project opportunities.

app/api/opportunities/route.ts

@@ -1,44 +1,14 @@
 import { NextRequest, NextResponse } from 'next/server'
-import { isAuthenticatedNextjs } from "@convex-dev/auth/nextjs/server";
+import { convexAuthNextjsToken, isAuthenticatedNextjs } from "@convex-dev/auth/nextjs/server";
+import { fetchQuery } from "convex/nextjs";
+import { api } from "@/convex/_generated/api";
 import { z } from 'zod'
 import { generateSearchQueries, getDefaultPlatforms } from '@/lib/query-generator'
 import { executeSearches, scoreOpportunities } from '@/lib/search-executor'
 import type { EnhancedProductAnalysis, SearchConfig, PlatformConfig } from '@/lib/types'
 
 const searchSchema = z.object({
-  analysis: z.object({
-    productName: z.string(),
-    tagline: z.string(),
-    description: z.string(),
-    features: z.array(z.object({
-      name: z.string(),
-      description: z.string(),
-      benefits: z.array(z.string()),
-      useCases: z.array(z.string())
-    })),
-    problemsSolved: z.array(z.object({
-      problem: z.string(),
-      severity: z.enum(['high', 'medium', 'low']),
-      currentWorkarounds: z.array(z.string()),
-      emotionalImpact: z.string(),
-      searchTerms: z.array(z.string())
-    })),
-    keywords: z.array(z.object({
-      term: z.string(),
-      type: z.string(),
-      searchVolume: z.string(),
-      intent: z.string(),
-      funnel: z.string(),
-      emotionalIntensity: z.string()
-    })),
-    competitors: z.array(z.object({
-      name: z.string(),
-      differentiator: z.string(),
-      theirStrength: z.string(),
-      switchTrigger: z.string(),
-      theirWeakness: z.string()
-    }))
-  }),
+  projectId: z.string(),
   config: z.object({
     platforms: z.array(z.object({
       id: z.string(),
@@ -65,7 +35,23 @@ export async function POST(request: NextRequest) {
     }
 
     const body = await request.json()
-    const { analysis, config } = searchSchema.parse(body)
+    const { projectId, config } = searchSchema.parse(body)
+
+    const token = await convexAuthNextjsToken();
+    const searchContext = await fetchQuery(
+      api.projects.getSearchContext,
+      { projectId: projectId as any },
+      { token }
+    );
+
+    if (!searchContext.context) {
+      return NextResponse.json(
+        { error: 'No analysis available for selected sources.' },
+        { status: 400 }
+      );
+    }
+
+    const analysis = searchContext.context as EnhancedProductAnalysis
 
     console.log('🔍 Starting opportunity search...')
     console.log(`   Product: ${analysis.productName}`)
@@ -105,7 +91,8 @@ export async function POST(request: NextRequest) {
           platform: q.platform,
           strategy: q.strategy,
           priority: q.priority
-        }))
+        })),
+        missingSources: searchContext.missingSources ?? []
       }
     })