Resolve GraphChat pages (#1306)

* resolve graphchat pages

* resolve comment

Author: matea16

next.config.mjs

@@ -3395,8 +3395,11 @@ export default withNextra({
         destination: '/getting-started/install-memgraph/docker#troubleshooting',
         permanent: true
       },
-      
-      
+      {
+        source: '/ai-ecosystem/graphchat',
+        destination: '/ai-ecosystem#graphchat',
+        permanent: true
+      },
 
 
 

pages/ai-ecosystem.mdx

@@ -4,6 +4,7 @@ description: Explore key features, such as community detection, node embeddings,
 ---
 
 import { Callout } from 'nextra/components'
+import { Cards } from 'nextra/components'
 import {CommunityLinks} from '/components/social-card/CommunityLinks'
 
 # Memgraph's AI ecosystem
@@ -24,10 +25,11 @@ This section of Memgraph’s documentation is your guide to using Memgraph for A
   own GenAI application from scratch. Some of the libraries that support
   Memgraph include **Model Context Protocol (MCP)**, **LangChain**,
   **LlamaIndex**, **Cognee** and **Mem0**.
-- [GraphChat in Memgraph Lab](/ai-ecosystem/graphchat): Explore how natural
-  language querying (GraphChat) ties into the GraphRAG ecosystem, making complex
-  graphs accessible to everyone.
 - [Machine learning with Memgraph](/ai-ecosystem/machine-learning): Learn how
   Memgraph powers ML workflows with graph-powered insights.
+- [GraphChat in Memgraph Lab](/memgraph-lab/features/graphchat): Explore how
+  natural language querying (GraphChat) ties into the GraphRAG ecosystem, making
+  complex graphs accessible to everyone.
+
 
 <CommunityLinks/>

pages/ai-ecosystem/_meta.ts

@@ -1,6 +1,5 @@
 export default {
     "graph-rag": "GraphRAG",
     "integrations": "Integrations",
-    "graphchat": "GraphChat",
     "machine-learning": "Machine learning",
 }