Fix issue: WorkspaceTaskSubType.BROKEN_LINK

Author: hyperlint-ai[bot]

src/content/docs/reference-architecture/diagrams/ai/ai-rag.mdx

@@ -45,10 +45,10 @@ In the context of Retrieval-Augmented Generation (RAG), knowledge seeding involv
 2. **Embedding generation**: Generate embedding vectors by calling [Workers AI](/workers-ai/) [text embedding models](/workers-ai/models/) for the incoming query.
 3. **Vector search**: Query [Vectorize](/vectorize/) using the vector representation of the query to retrieve related vectors.
 4. **Document lookup**: Retrieve related documents from [D1](/d1/) based on search results from [Vectorize](/vectorize/).
-5. **Text generation**: Pass both the original query and the retrieved documents as context to [Workers AI](/workers-ai/) [text generation models](/workers-ai/models/#text-generation) to generate a response.
+5. **Text generation**: Pass both the original query and the retrieved documents as context to [Workers AI](/workers-ai/) [text generation models](/workers-ai/models/) to generate a response.
 
 ## Related resources
 
 - [Tutorial: Build a RAG AI](/workers-ai/tutorials/build-a-retrieval-augmented-generation-ai/)
 - [Workers AI: Text embedding models](/workers-ai/models/)
-- [Workers AI: Text generation models](/workers-ai/models/#text-generation)
+- [Workers AI: Text generation models](/workers-ai/models/)