Update link checker config (#22604) (#22710)

Author: ti-chi-bot

.github/workflows/link.yaml

@@ -19,10 +19,11 @@ jobs:
       - name: Check Links
         uses: lycheeverse/lychee-action@v1.6.1
         with:
-          # For parameter description, see https://github.com/lycheeverse/lychee#commandline-parameters
-          # Accept 429 for now due to github rate limit.
-          # See https://github.com/lycheeverse/lychee/issues/634
-          args: -E --exclude-mail -i -n -t 45 -- **/*.md *.md
+          # Don't fail as we want the workflow to continue and run 'Create Issue From File'
+          # Excluding releases paths as historic releases may have outdated links.
+          fail: false
+          failIfEmpty: false
+          args: --root-dir $(pwd) --cache --max-cache-age 8d -E -i -n -t 45 --exclude-path '^./releases/' --exclude-path '^./tidb-cloud/releases/' --exclude-path '^./resources/' .
           output: out.md
         env:
           GITHUB_TOKEN: ${{secrets.GITHUB_TOKEN}}

.lycheeignore

@@ -29,6 +29,7 @@ https://bugs\.mysql\.com/bug\.php.*
 https://www\.mysql\.com/products/.*
 https://help\.openai\.com/en/articles/.*
 https://platform\.openai\.com/docs/.*
+https://platform\.openai\.com/api-keys
 https://openai\.com/.*
 https://jwt\.io/
 https://typeorm\.io/.*
@@ -38,3 +39,9 @@ https://docs\.pingcap\.com/tidb/v6\.6/system-variables#tidb_pessimistic_txn_aggr
 https://docs\.pingcap\.com/tidb/v7\.6/system-variables#tidb_ddl_version-new-in-v760
 https://developers\.redhat\.com/blog/2021/01/05/building-red-hat-enterprise-linux-9-for-the-x86-64-v2-microarchitecture-level
 https://portal\.azure\.com/.*
+https://.*github.*/%7B%7B%7B%20.tidb_operator_version%20%7D%7D%7D
+https://.*github.*/%7B%7B%7B.tidb-operator-version%7D%7D%7D
+https://portal\.azure\.com/.*
+https://azuremarketplace\.microsoft\.com/.*
+https://one\.newrelic\.com/.*
+https://tidbcloud\.com/.*

tidb-cloud/tidb-cloud-glossary.md

@@ -71,7 +71,7 @@ For more information, see [Manage an endpoint](/tidb-cloud/data-service-manage-e
 
 Unlike [Vector Search](/ai/concepts/vector-search-overview.md), which focuses on semantic similarity, full-text search lets you retrieve documents for exact keywords. In Retrieval-Augmented Generation (RAG) scenarios, you can use full-text search together with vector search to improve the retrieval quality.
 
-For more information, see [Full-Text Search with SQL](https://docs.pingcap.com/developer/vector-search-full-text-search-sql) and [Full-Text Search with Python](https://docs.pingcap.com/developer/vector-search-full-text-search-python).
+For more information, see [Full-Text Search with SQL](/ai/guides/vector-search-full-text-search-sql.md) and [Full-Text Search with Python](/ai/guides/vector-search-full-text-search-python.md).
 
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