feat: integrate and deploy kabelfachmann mcp

.gitea/workflows/deploy.yml

@@ -292,6 +292,7 @@ jobs:
       QDRANT_URL: ${{ secrets.QDRANT_URL || vars.QDRANT_URL || 'http://klz-qdrant:6333' }}
       QDRANT_API_KEY: ${{ secrets.QDRANT_API_KEY || vars.QDRANT_API_KEY }}
       REDIS_URL: ${{ secrets.REDIS_URL || vars.REDIS_URL || 'redis://klz-redis:6379' }}
+      KABELFACHMANN_MCP_URL: ${{ secrets.KABELFACHMANN_MCP_URL || vars.KABELFACHMANN_MCP_URL || 'http://klz-kabelfachmann:3007/sse' }}
       # Container Registry (standalone)
       REGISTRY_USER: ${{ secrets.REGISTRY_USER }}
       REGISTRY_PASS: ${{ secrets.REGISTRY_PASS }}
@@ -358,6 +359,7 @@ jobs:
             echo "QDRANT_URL=$QDRANT_URL"
             echo "QDRANT_API_KEY=$QDRANT_API_KEY"
             echo "REDIS_URL=$REDIS_URL"
+            echo "KABELFACHMANN_MCP_URL=$KABELFACHMANN_MCP_URL"
             echo ""
             echo "TARGET=$TARGET"
             echo "SENTRY_ENVIRONMENT=$TARGET"

app/api/ai-search/route.ts

@@ -3,6 +3,11 @@ import { searchProducts } from '../../../src/lib/qdrant';
 import redis from '../../../src/lib/redis';
 import { z } from 'zod';
 import * as Sentry from '@sentry/nextjs';
+import { generateText } from 'ai';
+import { createOpenAI } from '@ai-sdk/openai';
+// @ts-ignore
+import { createMcpTools } from '@mintel/payload-ai/tools/mcpAdapter';
+
 export const dynamic = 'force-dynamic';
 export const maxDuration = 60; // Max allowed duration (Vercel)
 
@@ -108,12 +113,9 @@ Das ECHTE KLZ Team:
           .map((p: any) => p.payload?.content)
           .join('\n\n');
 
-        const knowledgeDescriptions = searchResults
-          .filter((p) => p.payload?.type === 'knowledge')
-          .map((p: any) => p.payload?.content)
-          .join('\n\n');
-
-        contextStr = `KATALOG & PRODUKTE:\n${productDescriptions}\n\nKABELWISSEN (Handbuch):\n${knowledgeDescriptions}`;
+        if (productDescriptions) {
+          contextStr = `KATALOG & PRODUKTE:\n${productDescriptions}`;
+        }
 
         foundProducts = searchResults
           .filter((p) => (p.payload?.type === 'product' || !p.payload?.type) && p.payload?.data)
@@ -145,12 +147,14 @@ DEINE HAUPTAUFGABE: BERATEN, NICHT AUSFRAGEN!
 - FRAGE NICHT nach abstrakten Dingen wie "Welchen Kabeltyp brauchst du?" -> DAS IST DEIN JOB, IHM DAS ZU SAGEN!
 - FRAGE NICHT nach Längen oder genauen Trassen, es sei denn, der Kunde hat schon ganz klar gesagt, was er kaufen will.
 - Biete aktiv Hilfe an: "Ich kann dir die passenden Querschnitte raussuchen, wenn du willst."
+- Wenn technisches Wissen aus dem Kabelhandbuch benötigt wird, NUTZE UNBEDINGT eines der "kabelfachmann_*" Tools, anstatt zu raten oder zu behaupten du wüsstest es nicht! Das Tool weiss alles.
 
 VORGEHEN:
-1. Prüfe den KONTEXT auf passende Kabel für das Kundenprojekt.
-2. Nenne direkt 1-2 passende Produktserien aus dem Kontext, die für diesen Fall Sinn machen.
-3. Biete eine konkrete Hilfestellung an (z.B. Leitungsberechnung, Verfügbarkeitsprüfung) ODER stelle EINE einzige fachliche Rückfrage, um das Kabel weiter einzugrenzen (z.B. Alu oder Kupfer?).
-4. Wenn das Projekt klar ist und die Kabeltypen besprochen sind, frag nach, ob ein Kollege (z.B. Micha) ein konkretes Angebot machen soll.
+1. Prüfe den KONTEXT auf passende Katalog-Kabel für das Kundenprojekt.
+2. Wenn du tiefgehendes Wissen zu einem Kabeltyp brauchst (z.B. Biegeradius, Normen, Querschnitte), rufe das Kabelfachmann-Tool auf.
+3. Nenne direkt 1-2 passende Produktserien aus dem Kontext oder der Tool-Abfrage, die für diesen Fall Sinn machen.
+4. Biete eine konkrete Hilfestellung an (z.B. Leitungsberechnung, Verfügbarkeitsprüfung) ODER stelle EINE einzige fachliche Rückfrage, um das Kabel weiter einzugrenzen (z.B. Alu oder Kupfer?).
+5. Wenn das Projekt klar ist und die Kabeltypen besprochen sind, frag nach, ob ein Kollege (z.B. Micha) ein konkretes Angebot machen soll.
 
 GRENZEN:
 - PRIVAT-ANFRAGEN: B2B only. Private Hausinstallationen lehnen wir freundlich ab.
@@ -161,51 +165,42 @@ ${contextStr || 'Kein Katalogkontext verfügbar.'}
 ${teamContextStr}
 `;
 
-    const mistralKey = process.env.MISTRAL_API_KEY;
-    if (!mistralKey) {
-      throw new Error('MISTRAL_API_KEY is not set');
+    const openrouterApiKey = process.env.OPENROUTER_API_KEY;
+    if (!openrouterApiKey) {
+      throw new Error('OPENROUTER_API_KEY is not set');
     }
 
-    // DSGVO: Mistral AI API direkt (EU/Frankreich) statt OpenRouter (US)
-    const fetchRes = await fetch('https://api.mistral.ai/v1/chat/completions', {
-      method: 'POST',
-      headers: {
-        Authorization: `Bearer ${mistralKey}`,
-        'Content-Type': 'application/json',
-      },
-      body: JSON.stringify({
-        model: 'ministral-8b-latest',
-        temperature: 0.3,
-        max_tokens: MAX_RESPONSE_TOKENS,
-        messages: [
-          { role: 'system', content: systemPrompt },
-          ...cappedMessages.map((m: any) => ({
-            role: m.role,
-            content: typeof m.content === 'string' ? m.content : JSON.stringify(m.content),
-          })),
-        ],
-      }),
+    const openrouter = createOpenAI({
+      baseURL: 'https://openrouter.ai/api/v1',
+      apiKey: openrouterApiKey,
     });
 
-    if (!fetchRes.ok) {
-      const errBody = await fetchRes.text();
-      console.error('Mistral API Error:', errBody);
-      Sentry.captureException(new Error(`Mistral ${fetchRes.status}: ${errBody}`), {
-        tags: { context: 'ai-search-mistral' },
+    let mcpTools: Record<string, any> = {};
+    const mcpUrl = process.env.KABELFACHMANN_MCP_URL || 'http://host.docker.internal:3007/sse';
+    try {
+      const { tools } = await createMcpTools({
+        name: 'kabelfachmann',
+        url: mcpUrl
       });
-
-      // Return user-friendly error based on status
-      const userMsg =
-        fetchRes.status === 429
-          ? 'Der KI-Service ist gerade überlastet. Bitte versuche es in ein paar Sekunden erneut.'
-          : fetchRes.status >= 500
-            ? 'Der KI-Service ist vorübergehend nicht erreichbar. Bitte versuche es gleich nochmal.'
-            : 'Es gab ein Problem mit der KI-Anfrage. Bitte versuche es erneut.';
-      return NextResponse.json({ error: userMsg }, { status: 502 });
+      mcpTools = tools;
+    } catch (e) {
+      console.warn('Failed to load MCP tools', e);
+      Sentry.captureException(e, { tags: { context: 'ai-search-mcp' } });
     }
 
-    const data = await fetchRes.json();
-    const text = data.choices[0].message.content;
+    const { text } = await generateText({
+      model: openrouter('google/gemini-3.0-flash'),
+      system: systemPrompt,
+      messages: cappedMessages.map((m: any) => ({
+        role: m.role,
+        content: typeof m.content === 'string' ? m.content : JSON.stringify(m.content),
+      })),
+      tools: mcpTools,
+      // @ts-ignore
+      maxSteps: 3, // Allow the model to call the tool and then respond
+      temperature: 0.3,
+      maxTokens: MAX_RESPONSE_TOKENS,
+    });
 
     // Return the AI's answer along with any found products
     return NextResponse.json({

docker-compose.dev.yml

@@ -112,9 +112,22 @@ services:
       - klz_qdrant_data:/qdrant/storage
     networks:
       - default
-    ports:
       - "16333:6333"
 
+  klz-kabelfachmann:
+    image: registry.infra.mintel.me/mintel/kabelfachmann-mcp:${IMAGE_TAG:-latest}
+    restart: unless-stopped
+    networks:
+      - default
+    env_file:
+      - ${ENV_FILE:-.env}
+    environment:
+      QDRANT_URL: http://klz-qdrant:6333
+    ports:
+      - "3007:3007"
+    depends_on:
+      - klz-qdrant
+
 networks:
   default:
     name: ${PROJECT_NAME:-klz-cables}-internal

docker-compose.yml

@@ -119,6 +119,20 @@ services:
     networks:
       - default
 
+  klz-kabelfachmann:
+    image: registry.infra.mintel.me/mintel/kabelfachmann-mcp:${IMAGE_TAG:-latest}
+    restart: unless-stopped
+    networks:
+      - default
+    env_file:
+      - ${ENV_FILE:-.env}
+    environment:
+      QDRANT_URL: http://klz-qdrant:6333
+    ports:
+      - "3007:3007"
+    depends_on:
+      - klz-qdrant
+
 networks:
   default:
     name: ${PROJECT_NAME:-klz-cables}-internal

package.json

@@ -106,7 +106,7 @@
   },
   "scripts": {
     "dev": "bash -c '[ -f .env ] || (cp .env.example .env && sed -i.bak \"s/TRAEFIK_HOST=klz-cables.com/TRAEFIK_HOST=klz.localhost/\" .env && rm -f .env.bak && echo \"✅ Created .env from .env.example\"); trap \"COMPOSE_PROJECT_NAME=klz-2026 docker-compose -f docker-compose.dev.yml down\" EXIT INT TERM; docker network create infra 2>/dev/null || true && COMPOSE_PROJECT_NAME=klz-2026 docker-compose -f docker-compose.dev.yml down && COMPOSE_PROJECT_NAME=klz-2026 docker-compose -f docker-compose.dev.yml up klz-app klz-db klz-proxy klz-qdrant klz-redis --remove-orphans'",
-    "dev:local": "bash -c 'trap \"COMPOSE_PROJECT_NAME=klz-2026 docker-compose -f docker-compose.dev.yml down\" EXIT INT TERM; COMPOSE_PROJECT_NAME=klz-2026 docker-compose -f docker-compose.dev.yml up -d klz-db klz-proxy klz-qdrant klz-redis && POSTGRES_URI=\"\" NODE_ENV=development next dev --webpack --port 3100 --hostname 0.0.0.0'",
+    "dev:local": "bash -c 'trap \"COMPOSE_PROJECT_NAME=klz-2026 docker-compose -f docker-compose.dev.yml down\" EXIT INT TERM; COMPOSE_PROJECT_NAME=klz-2026 docker-compose -f docker-compose.dev.yml up -d klz-db klz-proxy klz-qdrant klz-redis && POSTGRES_URI=NODE_ENV=development next dev --webpack --port 3100 --hostname 0.0.0.0'",
     "dev:infra": "COMPOSE_PROJECT_NAME=klz-2026 docker-compose -f docker-compose.dev.yml up -d klz-db klz-proxy",
     "build": "next build",
     "start": "next start",
@@ -138,6 +138,10 @@
     "assets:pull:prod": "bash ./scripts/assets-sync.sh prod local",
     "assets:sync:testing-to-staging": "bash ./scripts/assets-sync.sh testing staging",
     "assets:sync:staging-to-prod": "bash ./scripts/assets-sync.sh staging prod",
+    "qdrant:push:testing": "bash ./scripts/qdrant-sync.sh testing",
+    "qdrant:push:staging": "bash ./scripts/qdrant-sync.sh staging",
+    "qdrant:push:prod": "bash ./scripts/qdrant-sync.sh prod",
+    "qdrant:push:branch": "bash ./scripts/qdrant-sync.sh",
     "pagespeed:test": "tsx ./scripts/pagespeed-sitemap.ts",
     "pagespeed:audit": "./scripts/audit-local.sh",
     "pagespeed:urls": "tsx -e \"import sitemap from './app/sitemap'; sitemap().then(urls => console.log(urls.map(u => u.url).join('\\n')))\"",

scripts/qdrant-sync.sh

@@ -0,0 +1,120 @@
+#!/usr/bin/env bash
+# ────────────────────────────────────────────────────────────────────────────
+# Qdrant Snapshot Sync Tool
+# Syncs a Qdrant collection from the local machine to a remote environment
+# using the safe Snapshot API to avoid RocksDB corruption.
+# ────────────────────────────────────────────────────────────────────────────
+set -euo pipefail
+
+# Load environment variables
+if [ -f .env ]; then
+  set -a; source .env; set +a
+fi
+
+# ── Configuration ──────────────────────────────────────────────────────────
+TARGET_ENV="${1:-}"        # testing | staging | branch_slug | prod
+COLLECTION="${2:-kabelfachmann}"
+SSH_HOST="root@alpha.mintel.me"
+
+if [[ -z "$TARGET_ENV" ]]; then
+  echo "Usage: pnpm run qdrant:push <target_env> [collection]"
+  echo "Example: pnpm run qdrant:push testing kabelfachmann"
+  echo "Example: pnpm run qdrant:push mein-feature-slug kabelfachmann"
+  exit 1
+fi
+
+LOCAL_QDRANT_URL=${QDRANT_URL:-"http://localhost:16333"}
+
+get_target_path() {
+  case "$1" in
+    testing) echo "/home/deploy/sites/testing.klz-cables.com" ;;
+    staging) echo "/home/deploy/sites/staging.klz-cables.com" ;;
+    prod|production) echo "/home/deploy/sites/klz-cables.com" ;;
+    *) echo "/home/deploy/sites/branch.klz-cables.com/$1" ;;
+  esac
+}
+
+get_project_name() {
+  case "$1" in
+    testing) echo "klz-testing" ;;
+    staging) echo "klz-staging" ;;
+    prod|production) echo "klz-cablescom" ;;
+    *) echo "klz-branch-$1" ;;
+  esac
+}
+
+TGT_PATH=$(get_target_path "$TARGET_ENV")
+PROJECT_NAME=$(get_project_name "$TARGET_ENV")
+QDRANT_CONTAINER="${PROJECT_NAME}-klz-qdrant-1"
+WORK_DIR=$(mktemp -d)
+
+echo "🚀 Syncing Qdrant Collection '$COLLECTION' to: $TARGET_ENV"
+
+# 1. Create Snapshot Locally
+echo "📸 1/5 Creating snapshot on local Qdrant ($LOCAL_QDRANT_URL)..."
+SNAPSHOT_INFO=$(curl -s -X POST "$LOCAL_QDRANT_URL/collections/$COLLECTION/snapshots")
+
+if ! echo "$SNAPSHOT_INFO" | grep -q '"status":"ok"'; then
+  echo "❌ Failed to create snapshot."
+  echo "Response: $SNAPSHOT_INFO"
+  exit 1
+fi
+
+SNAPSHOT_NAME=$(echo "$SNAPSHOT_INFO" | grep -o '"name":"[^"]*' | cut -d'"' -f4)
+echo "   ✅ Snapshot created: $SNAPSHOT_NAME"
+
+# 2. Download Snapshot
+echo "⬇️  2/5 Downloading snapshot..."
+curl -s -o "$WORK_DIR/$SNAPSHOT_NAME" "$LOCAL_QDRANT_URL/collections/$COLLECTION/snapshots/$SNAPSHOT_NAME"
+echo "   ✅ Downloaded to $WORK_DIR/$SNAPSHOT_NAME"
+
+# 3. Transfer Snapshot
+echo "📤 3/5 Uploading snapshot to Alpha ($SSH_HOST)..."
+ssh "$SSH_HOST" "mkdir -p $TGT_PATH/qdrant_tmp"
+scp "$WORK_DIR/$SNAPSHOT_NAME" "$SSH_HOST:$TGT_PATH/qdrant_tmp/$SNAPSHOT_NAME"
+echo "   ✅ Upload complete."
+
+# 4. Restore Snapshot on Remote Server
+echo "🔄 4/5 Restoring snapshot on target container ($QDRANT_CONTAINER)..."
+
+# Qdrant restore process:
+# - Recreate collection (so it is clean)
+# - Download snapshot to container
+# - Recover from snapshot file
+
+ssh "$SSH_HOST" << EOF
+  set -e
+  # Step A: Copy file into the container
+  docker cp "$TGT_PATH/qdrant_tmp/$SNAPSHOT_NAME" $QDRANT_CONTAINER:/qdrant/$SNAPSHOT_NAME
+
+  # Step B: Delete existing collection
+  curl -s -X DELETE "http://127.0.0.1:6333/collections/$COLLECTION" > /dev/null
+
+  # Step C: Re-create empty collection (required before recovery)
+  # wir nutzen die standard vector config vom Kabelfachmann (Cosine, 384 dim für all-MiniLM-L6-v2)
+  curl -s -X PUT "http://127.0.0.1:6333/collections/$COLLECTION" \
+    -H 'Content-Type: application/json' \
+    -d '{ "vectors": { "size": 384, "distance": "Cosine" } }' > /dev/null
+
+  # Step D: Recover
+  echo "   [Remote] Triggering recover API..."
+  curl -s -X PUT "http://127.0.0.1:6333/collections/$COLLECTION/snapshots/recover" \
+    -H 'Content-Type: application/json' \
+    -d '{ "location": "file:///qdrant/'$SNAPSHOT_NAME'" }' > /dev/null
+
+  # Step E: Cleanup
+  docker exec $QDRANT_CONTAINER rm /qdrant/$SNAPSHOT_NAME
+  rm -rf "$TGT_PATH/qdrant_tmp"
+EOF
+
+echo "   ✅ Restore complete."
+
+# 5. Local Cleanup
+echo "🧹 5/5 Cleaning up..."
+rm -rf "$WORK_DIR"
+# Delete snapshot from local Qdrant server to save space
+curl -s -X DELETE "$LOCAL_QDRANT_URL/collections/$COLLECTION/snapshots/$SNAPSHOT_NAME" > /dev/null
+echo "   ✅ Local cleanup done."
+
+echo ""
+echo "🎉 Successfully synced Qdrant collection '$COLLECTION' to $TARGET_ENV!"

src/lib/qdrant.ts

@@ -152,31 +152,6 @@ export async function deleteProductVector(id: string | number) {
   }
 }
 
-/**
- * Delete knowledge chunks by their source Media ID
- */
-export async function deleteKnowledgeByMediaId(mediaId: string | number) {
-  try {
-    await ensureCollection();
-    await qdrant.delete(COLLECTION_NAME, {
-      wait: true,
-      filter: {
-        must: [
-          {
-            key: 'mediaId',
-            match: {
-              value: mediaId,
-            },
-          },
-        ],
-      },
-    });
-    console.log(`Successfully deleted Qdrant chunks for Media ID: ${mediaId}`);
-  } catch (error) {
-    console.error('Error deleting knowledge by Media ID from Qdrant:', error);
-  }
-}
-
 /**
  * Search products in Qdrant.
  * Results are cached in Redis for 30 minutes keyed by query text.

src/payload/collections/Media.ts

@@ -45,81 +45,4 @@ export const Media: CollectionConfig = {
       type: 'text',
     },
   ],
-  hooks: {
-    afterChange: [
-      async ({ doc, req }) => {
-        // Only process PDF files
-        if (doc.mimeType === 'application/pdf') {
-          try {
-            const fs = require('fs');
-            const path = require('path');
-            const crypto = require('crypto');
-            const pdfParse = require('pdf-parse');
-            const { upsertProductVector, deleteKnowledgeByMediaId } = require('../../lib/qdrant');
-
-            const filePath = path.join(process.cwd(), 'public/media', doc.filename);
-
-            if (fs.existsSync(filePath)) {
-              req.payload.logger.info(`Extracting text from PDF: ${doc.filename}`);
-
-              const dataBuffer = fs.readFileSync(filePath);
-              const data = await pdfParse(dataBuffer);
-
-              // Clear any previously indexed chunks for this file just in case it's an update
-              await deleteKnowledgeByMediaId(doc.id);
-
-              // Chunk the text like we did in the ingest script
-              const chunks = data.text
-                .split(/\n\s*\n/)
-                .map((c: string) => c.trim())
-                .filter((c: string) => c.length > 50);
-
-              let successCount = 0;
-              for (let i = 0; i < chunks.length; i++) {
-                // Generate a deterministic UUID based on doc ID and chunk index
-                const hash = crypto.createHash('md5').update(`${doc.id}-${i}`).digest('hex');
-                // Qdrant strictly requires UUID: 8-4-4-4-12
-                const uuid = [
-                  hash.substring(0, 8),
-                  hash.substring(8, 12),
-                  hash.substring(12, 16),
-                  hash.substring(16, 20),
-                  hash.substring(20, 32),
-                ].join('-');
-
-                await upsertProductVector(uuid, chunks[i], {
-                  type: 'knowledge',
-                  title: `${doc.filename} - Teil ${i + 1}`,
-                  content: chunks[i],
-                  source: doc.filename,
-                  mediaId: doc.id,
-                });
-                successCount++;
-              }
-              req.payload.logger.info(
-                `Successfully ingested ${successCount} chunks from ${doc.filename} into Qdrant`,
-              );
-            }
-          } catch (e: any) {
-            req.payload.logger.error(`Error parsing PDF ${doc.filename}: ${e.message}`);
-          }
-        }
-      },
-    ],
-    afterDelete: [
-      async ({ id, doc, req }) => {
-        if (doc.mimeType === 'application/pdf') {
-          try {
-            const { deleteKnowledgeByMediaId } = require('../../lib/qdrant');
-            await deleteKnowledgeByMediaId(id);
-            req.payload.logger.info(`Removed Qdrant chunks for deleted PDF: ${doc.filename}`);
-          } catch (e: any) {
-            req.payload.logger.error(
-              `Error removing Qdrant chunks for ${doc.filename}: ${e.message}`,
-            );
-          }
-        }
-      },
-    ],
-  },
 };

src/scripts/upload-pdfs.ts

@@ -1,58 +0,0 @@
-import fs from 'fs';
-import path from 'path';
-import 'dotenv/config';
-import { getPayload } from 'payload';
-import configPromise from '@payload-config';
-
-async function uploadPDFs() {
-  const payload = await getPayload({ config: configPromise });
-
-  const downloadDir = '/Users/marcmintel/Downloads';
-  const files = fs.readdirSync(downloadDir).filter((f) => f.endsWith('.pdf'));
-
-  console.log(`Found ${files.length} PDFs in Downloads folder.`);
-
-  for (const file of files) {
-    const filePath = path.join(downloadDir, file);
-    try {
-      const stats = fs.statSync(filePath);
-
-      // Check if it already exists
-      const existing = await payload.find({
-        collection: 'media',
-        where: {
-          filename: {
-            equals: file,
-          },
-        },
-      });
-
-      if (existing.docs.length > 0) {
-        console.log(`Skipping ${file} - already exists in CMS`);
-        continue;
-      }
-
-      console.log(`Uploading ${file}...`);
-      await payload.create({
-        collection: 'media',
-        data: {
-          alt: file,
-        },
-        file: {
-          data: fs.readFileSync(filePath),
-          mimetype: 'application/pdf',
-          name: file,
-          size: stats.size,
-        },
-      });
-      console.log(`✅ Uploaded ${file}`);
-    } catch (err) {
-      console.error(`❌ Failed to upload ${file}:`, err);
-    }
-  }
-
-  console.log('Done uploading PDFs to Payload CMS. Payload hooks have synced them to Qdrant.');
-  process.exit(0);
-}
-
-uploadPDFs();