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Author: badmonster0

docs/docs/examples/examples/product_recommendation.md

@@ -30,7 +30,7 @@ Product taxonomy is a way to organize product catalogs in a logical and hierarch
 
 ## Prerequisites
 *   [Install PostgreSQL](https://cocoindex.io/docs/getting_started/installation#-install-postgres). CocoIndex uses PostgreSQL internally for incremental processing.
-*   [Install Neo4j](https://cocoindex.io/docs/targets#Neo4j), a graph database.
+*   [Install Neo4j](https://cocoindex.io/docs/targets/neo4j), a graph database.
 *   -  [Configure your OpenAI API key](https://cocoindex.io/docs/ai/llm#openai). Create a `.env` file from `.env.example`, and fill `OPENAI_API_KEY`.
 
 Alternatively, we have native support for Gemini, Ollama, LiteLLM. You can choose your favorite LLM provider and work completely on-premises.

examples/docs_to_knowledge_graph/README.md

@@ -14,8 +14,7 @@ Please drop [Cocoindex on Github](https://github.com/cocoindex-io/cocoindex) a s
 
 ## Prerequisite
 *   [Install Postgres](https://cocoindex.io/docs/getting_started/installation#-install-postgres) if you don't have one.
-*   Install [Neo4j](https://cocoindex.io/docs/targets#neo4j-dev-instance) or [Kuzu](https://cocoindex.io/docs/targets#kuzu-dev-instance) if you don't have one.
-    *   The example uses Neo4j by default for now. If you want to use Kuzu, find out the "SELECT ONE GRAPH DATABASE TO USE" section and switch the active branch.
+*   Install [Neo4j](https://cocoindex.io/docs/targets/neo4j).
 *   Install / configure LLM API. In this example we use Ollama, which runs LLM model locally. You need to get it ready following [this guide](https://cocoindex.io/docs/ai/llm#ollama). Alternatively, you can also follow the comments in source code to switch to OpenAI, and [configure OpenAI API key](https://cocoindex.io/docs/ai/llm#openai) before running the example.
 
 ## Documentation
@@ -48,8 +47,6 @@ cocoindex update main
 After the knowledge graph is built, you can explore the knowledge graph.
 
 * If you're using Neo4j, you can open the explorer at [http://localhost:7474](http://localhost:7474), with username `neo4j` and password `cocoindex`.
-* If you're using Kuzu, you can start a Kuzu explorer locally. See [Kuzu dev instance](https://cocoindex.io/docs/targets#kuzu-dev-instance) for more details.
-
 You can run the following Cypher query to get all relationships:
 
 ```cypher

examples/product_recommendation/README.md

@@ -9,7 +9,7 @@ Please drop [CocoIndex on Github](https://github.com/cocoindex-io/cocoindex) a s
 
 ## Prerequisite
 *   [Install Postgres](https://cocoindex.io/docs/getting_started/installation#-install-postgres) 
-*   Install [Neo4j](https://cocoindex.io/docs/targets#neo4j-dev-instance)
+*   Install [Neo4j](https://cocoindex.io/docs/targets/neo4j)
 *   [Configure your OpenAI API key](https://cocoindex.io/docs/ai/llm#openai).
 
 ## Documentation

examples/text_embedding_qdrant/README.md

@@ -2,7 +2,7 @@
 
 [![GitHub](https://img.shields.io/github/stars/cocoindex-io/cocoindex?color=5B5BD6)](https://github.com/cocoindex-io/cocoindex)
 
-CocoIndex supports Qdrant natively - [documentation](https://cocoindex.io/docs/targets#qdrant). In this example, we will build index flow from text embedding from local markdown files, and query the index. We will use **Qdrant** as the vector database.
+CocoIndex supports Qdrant natively - [documentation](https://cocoindex.io/docs/targets/qdrant). In this example, we will build index flow from text embedding from local markdown files, and query the index. We will use **Qdrant** as the vector database.
 
 We appreciate a star ⭐ at [CocoIndex Github](https://github.com/cocoindex-io/cocoindex) if this is helpful.