Merge pull request #289017 from Daidihuang/2024_10-Monthly-broken-links-fix-franlanglois

2024_10 - Fix monthly broken links - franlanglois

Author: prmerger-automator[bot]

articles/azure-cache-for-redis/cache-overview-vector-similarity.md

@@ -76,7 +76,7 @@ Vector similarity search can be used in multiple applications. Some common use-c
 - **Document Retrieval**. Use the deeper semantic understanding of text provided by LLMs to provide a richer document search experience where traditional keyword-based search falls short. [Document Retrieval Example](https://github.com/RedisVentures/redis-arXiv-search)
 - **Product Recommendation**. Find similar products or services to recommend based on past user activities, like search history or previous purchases. [Product Recommendation Example](https://github.com/RedisVentures/LLM-Recommender)
 - **Visual Search**. Search for products that look similar to a picture taken by a user or a picture of another product. [Visual Search Example](https://github.com/RedisVentures/redis-product-search)
-- **Semantic Caching**. Reduce the cost and latency of LLMs by caching LLM completions. LLM queries are compared using vector similarity. If a new query is similar enough to a previously cached query, the cached query is returned. [Semantic Caching example using LangChain](https://python.langchain.com/docs/integrations/llms/llm_caching#redis-cache)
+- **Semantic Caching**. Reduce the cost and latency of LLMs by caching LLM completions. LLM queries are compared using vector similarity. If a new query is similar enough to a previously cached query, the cached query is returned. [Semantic Caching example using LangChain](https://python.langchain.com/docs/integrations/llm_caching/#redis-cache)
 - **LLM Conversation Memory**. Persist conversation history with an LLM as embeddings in a vector database. Your application can use vector search to pull relevant history or "memories" into the response from the LLM. [LLM Conversation Memory example](https://github.com/continuum-llms/chatgpt-memory)
 
 ## Why choose Azure Cache for Redis for storing and searching vectors?