feat(ai): Implement AI agent contact form and fix local Qdrant network configs

apps/web/scripts/index-posts.ts

@@ -0,0 +1,127 @@
+/**
+ * Index all published blog posts into Qdrant for AI search.
+ *
+ * Usage: pnpm --filter @mintel/web run index:posts
+ */
+import { getPayload } from 'payload';
+import configPromise from '../payload.config';
+import { upsertPostVector } from '../src/lib/qdrant';
+
+function extractPlainText(node: any): string {
+    if (!node) return '';
+
+    // Handle text nodes
+    if (typeof node === 'string') return node;
+    if (node.text) return node.text;
+
+    // Handle arrays
+    if (Array.isArray(node)) {
+        return node.map(extractPlainText).join('');
+    }
+
+    // Handle node with children
+    if (node.children) {
+        const childText = node.children.map(extractPlainText).join('');
+
+        // Add line breaks for block-level elements
+        if (['paragraph', 'heading', 'listitem', 'quote'].includes(node.type)) {
+            return childText + '\n';
+        }
+        return childText;
+    }
+
+    // Lexical root
+    if (node.root) {
+        return extractPlainText(node.root);
+    }
+
+    return '';
+}
+
+async function run() {
+    console.log('🔍 Starting blog post indexing for AI search...');
+
+    let payload;
+    let retries = 5;
+    while (retries > 0) {
+        try {
+            console.log(`Connecting to database (URI: ${process.env.DATABASE_URI || 'default'})...`);
+            payload = await getPayload({ config: configPromise });
+            break;
+        } catch (e: any) {
+            if (
+                e.code === 'ECONNREFUSED' ||
+                e.code === 'ENOTFOUND' ||
+                e.message?.includes('ECONNREFUSED') ||
+                e.message?.includes('cannot connect to Postgres')
+            ) {
+                console.log(`Database not ready, retrying in 3s... (${retries} retries left)`);
+                retries--;
+                await new Promise((res) => setTimeout(res, 3000));
+            } else {
+                throw e;
+            }
+        }
+    }
+
+    if (!payload) {
+        throw new Error('Failed to connect to database after multiple retries.');
+    }
+
+    // Fetch all published posts
+    const result = await payload.find({
+        collection: 'posts',
+        limit: 1000,
+        where: {
+            _status: { equals: 'published' },
+        },
+    });
+
+    console.log(`Found ${result.docs.length} published posts to index.`);
+
+    let indexed = 0;
+    for (const post of result.docs) {
+        const plainContent = extractPlainText(post.content);
+
+        // Build searchable text: title + description + tags + content
+        const tags = (post.tags as any[])?.map((t: any) => t.tag).filter(Boolean).join(', ') || '';
+        const searchableText = [
+            `Titel: ${post.title}`,
+            `Beschreibung: ${post.description}`,
+            tags ? `Tags: ${tags}` : '',
+            `Inhalt: ${plainContent.substring(0, 2000)}`, // Limit content to avoid token overflow
+        ]
+            .filter(Boolean)
+            .join('\n\n');
+
+        // Upsert into Qdrant
+        await upsertPostVector(
+            post.id,
+            searchableText,
+            {
+                content: searchableText,
+                data: {
+                    id: post.id,
+                    title: post.title,
+                    slug: post.slug,
+                    description: post.description,
+                    tags,
+                },
+            },
+        );
+
+        indexed++;
+        console.log(`  ✅ [${indexed}/${result.docs.length}] ${post.title}`);
+
+        // Small delay to avoid rate limiting on the embedding API
+        await new Promise((res) => setTimeout(res, 200));
+    }
+
+    console.log(`\n🎉 Successfully indexed ${indexed} posts into Qdrant.`);
+    process.exit(0);
+}
+
+run().catch((e) => {
+    console.error('Indexing failed:', e);
+    process.exit(1);
+});