cocoindex-io · badmonster0 · Oct 10, 2025 · Oct 12, 2025 · Oct 12, 2025 · Oct 12, 2025
diff --git a/docs/docs/examples/examples/academic_papers_index.md b/docs/docs/examples/examples/academic_papers_index.md
@@ -64,7 +64,7 @@ def paper_metadata_flow(
 ```
 
 `flow_builder.add_source` will create a table with sub fields (`filename`, `content`).
-<DocumentationButton url="https://cocoindex.io/docs/ops/sources" text="Sources" margin="0 0 16px 0" />
+<DocumentationButton url="https://cocoindex.io/docs/sources" text="Sources" margin="0 0 16px 0" />
 
 ## Extract and collect metadata
 

diff --git a/docs/docs/examples/examples/codebase_index.md b/docs/docs/examples/examples/codebase_index.md
@@ -70,7 +70,7 @@ def code_embedding_flow(flow_builder: cocoindex.FlowBuilder, data_scope: cocoind
 - Exclude files and directories starting `.`,  `target` in the root and `node_modules` under any directory.
 
 `flow_builder.add_source` will create a table with sub fields (`filename`, `content`).
-<DocumentationButton url="https://cocoindex.io/docs/ops/sources" text="Sources" />
+<DocumentationButton url="https://cocoindex.io/docs/sources" text="Sources" />
 
 
 ## Process each file and collect the information

diff --git a/docs/docs/examples/examples/custom_targets.md b/docs/docs/examples/examples/custom_targets.md
@@ -36,7 +36,7 @@ flow_builder: cocoindex.FlowBuilder, data_scope: cocoindex.DataScope
 	)
 ```
 This ingestion creates a table with `filename` and `content` fields.
-<DocumentationButton url="https://cocoindex.io/docs/ops/sources" text="Sources" />
+<DocumentationButton url="https://cocoindex.io/docs/sources" text="Sources" />
 
 ## Process each file and collect
 

diff --git a/docs/docs/examples/examples/docs_to_knowledge_graph.md b/docs/docs/examples/examples/docs_to_knowledge_graph.md
@@ -66,7 +66,7 @@ def docs_to_kg_flow(flow_builder: cocoindex.FlowBuilder, data_scope: cocoindex.D
 Here `flow_builder.add_source` creates a [KTable](https://cocoindex.io/docs/core/data_types#KTable).
 `filename` is the key of the KTable.
 
-<DocumentationButton url="https://cocoindex.io/docs/ops/sources" text="Sources" margin="0 0 16px 0" />
+<DocumentationButton url="https://cocoindex.io/docs/sources" text="Sources" margin="0 0 16px 0" />
 
 
 ### Add data collectors

diff --git a/docs/docs/examples/examples/document_ai.md b/docs/docs/examples/examples/document_ai.md
@@ -98,7 +98,7 @@ data_scope["documents"] = flow_builder.add_source(
 doc_embeddings = data_scope.add_collector()
 ```
 
-<DocumentationButton url="https://cocoindex.io/docs/ops/sources" text="Source" margin="0 0 16px 0" />
+<DocumentationButton url="https://cocoindex.io/docs/sources" text="Source" margin="0 0 16px 0" />
 
 <DocumentationButton url="https://cocoindex.io/docs/ops/collectors" text="Collector" margin="0 0 16px 0" />
 
@@ -154,4 +154,4 @@ For a step-by-step walkthrough of each indexing stage and the query path, check
 
 CocoIndex natively supports Google Drive, Amazon S3, Azure Blob Storage, and more with native incremental processing out of box - when new or updated files are detected, the pipeline will capture the changes and only process what's changed.
 
-<DocumentationButton url="https://cocoindex.io/docs/ops/sources" text="Sources" margin="0 0 16px 0" />
+<DocumentationButton url="https://cocoindex.io/docs/sources" text="Sources" margin="0 0 16px 0" />
diff --git a/docs/docs/examples/examples/image_search.md b/docs/docs/examples/examples/image_search.md
@@ -66,7 +66,7 @@ def image_object_embedding_flow(flow_builder, data_scope):
 
 The `add_source` function sets up a table with fields like `filename` and `content`. Images are automatically re-scanned every minute.
 
-<DocumentationButton url="https://cocoindex.io/docs/ops/sources/localfile" text="LocalFile" />
+<DocumentationButton url="https://cocoindex.io/docs/sources/localfile" text="LocalFile" />
 
 
 ## Process Each Image and Collect the Embedding
@@ -266,6 +266,6 @@ One of CocoIndex’s core strengths is its ability to connect to your existing d
 - Amazon S3 / SQS
 - Azure Blob Storage
 
-<DocumentationButton url="https://cocoindex.io/docs/ops/sources" text="Sources" margin="0 0 16px 0" />
+<DocumentationButton url="https://cocoindex.io/docs/sources" text="Sources" margin="0 0 16px 0" />
 
 Once connected, CocoIndex continuously watches for changes — new uploads, updates, or deletions — and applies them to your index in real time.
diff --git a/docs/docs/examples/examples/manual_extraction.md b/docs/docs/examples/examples/manual_extraction.md
@@ -67,7 +67,7 @@ def manual_extraction_flow(
 - `filename` (key, type: `str`): the filename of the file, e.g. `dir1/file1.md`
 - `content` (type: `str` if `binary` is `False`, otherwise `bytes`): the content of the file
 
-<DocumentationButton url="https://cocoindex.io/docs/ops/sources" text="LocalFile" margin="0 0 16px 0" />
+<DocumentationButton url="https://cocoindex.io/docs/sources" text="LocalFile" margin="0 0 16px 0" />
 
 ## Parse Markdown
 

diff --git a/docs/docs/examples/examples/multi_format_index.md b/docs/docs/examples/examples/multi_format_index.md
@@ -52,7 +52,7 @@ data_scope["documents"] = flow_builder.add_source(
     cocoindex.sources.LocalFile(path="source_files", binary=True)
 )
 ```
-<DocumentationButton url="https://cocoindex.io/docs/ops/sources/localfile" text="LocalFile" margin="0 0 16px 0" />
+<DocumentationButton url="https://cocoindex.io/docs/sources/localfile" text="LocalFile" margin="0 0 16px 0" />
 
 
 ## Convert Files to Pages
@@ -203,4 +203,4 @@ Follow the url `https://cocoindex.io/cocoinsight`.  It connects to your local Co
 ## Connect to other sources
 CocoIndex natively supports Google Drive, Amazon S3, Azure Blob Storage, and more.
 
-<DocumentationButton url="https://cocoindex.io/docs/ops/sources" text="Sources" margin="0 0 16px 0" />
+<DocumentationButton url="https://cocoindex.io/docs/sources" text="Sources" margin="0 0 16px 0" />
diff --git a/docs/docs/examples/examples/patient_form_extraction.md b/docs/docs/examples/examples/patient_form_extraction.md
@@ -66,7 +66,7 @@ def patient_intake_extraction_flow(
 
 `flow_builder.add_source` will create a table with a few sub fields.
 
-<DocumentationButton url="https://cocoindex.io/docs/ops/sources" text="Sources" margin="0 0 16px 0" />
+<DocumentationButton url="https://cocoindex.io/docs/sources" text="Sources" margin="0 0 16px 0" />
 
 
 ##  Parse documents with different formats to Markdown
@@ -298,4 +298,4 @@ Click on the `markdown` column for `Patient_Intake_Form_Joe.pdf`, you could see
 ## Connect to other sources
 CocoIndex natively supports Google Drive, Amazon S3, Azure Blob Storage, and more.
 
-<DocumentationButton url="https://cocoindex.io/docs/ops/sources" text="Sources" margin="0 0 16px 0" />
+<DocumentationButton url="https://cocoindex.io/docs/sources" text="Sources" margin="0 0 16px 0" />
diff --git a/docs/docs/examples/examples/photo_search.md b/docs/docs/examples/examples/photo_search.md
@@ -65,8 +65,8 @@ def face_recognition_flow(flow_builder, data_scope):
 This creates a table with `filename` and `content` fields. 📂
 
 
-You can connect it to your [S3 Buckets](https://cocoindex.io/docs/ops/sources/amazons3) (with SQS integration, [example](https://cocoindex.io/blogs/s3-incremental-etl))
-or [Azure Blob store](https://cocoindex.io/docs/ops/sources/azureblob).
+You can connect it to your [S3 Buckets](https://cocoindex.io/docs/sources/amazons3) (with SQS integration, [example](https://cocoindex.io/blogs/s3-incremental-etl))
+or [Azure Blob store](https://cocoindex.io/docs/sources/azureblob).
 
 ## Detect and Extract Faces
 

diff --git a/docs/docs/examples/examples/postgres_source.md b/docs/docs/examples/examples/postgres_source.md
@@ -59,7 +59,7 @@ CocoIndex incrementally sync data from Postgres. When new or updated rows are fo
 - `notification` enables change capture based on Postgres LISTEN/NOTIFY. Each change triggers an incremental processing on the specific row immediately.
 - Regardless if `notification` is provided or not, CocoIndex still needs to scan the full table to detect changes in some scenarios (e.g. between two `update` invocation), and the `ordinal_column` provides a field that CocoIndex can use to quickly detect which row has changed without reading value columns.
 
-Check [Postgres source](https://cocoindex.io/docs/ops/sources/postgres) for more details.
+Check [Postgres source](https://cocoindex.io/docs/sources/postgres) for more details.
 
 If you use the Postgres database hosted by Supabase, please click Connect on your project dashboard and find the URL there. Check [DatabaseConnectionSpec](https://cocoindex.io/docs/core/settings#databaseconnectionspec)
 for more details.

diff --git a/docs/docs/examples/examples/product_recommendation.md b/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/ops/storages#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.

diff --git a/docs/docs/examples/examples/simple_vector_index.md b/docs/docs/examples/examples/simple_vector_index.md
@@ -51,7 +51,7 @@ def text_embedding_flow(flow_builder: cocoindex.FlowBuilder, data_scope: cocoind
 ```
 
 `flow_builder.add_source` will create a table with sub fields (`filename`, `content`)
-<DocumentationButton url="https://cocoindex.io/docs/ops/sources" text="Source" />
+<DocumentationButton url="https://cocoindex.io/docs/sources" text="Source" />
 
 
 ## Process each file and collect the embeddings

diff --git a/docs/docs/getting_started/quickstart.md b/docs/docs/getting_started/quickstart.md
@@ -64,7 +64,7 @@ doc_embeddings = data_scope.add_collector()
 
 `flow_builder.add_source` will create a table with sub fields (`filename`, `content`)
 
-<DocumentationButton url="https://cocoindex.io/docs/ops/sources" text="Source" />
+<DocumentationButton url="https://cocoindex.io/docs/sources" text="Source" />
 
 <DocumentationButton url="https://cocoindex.io/docs/core/flow_def#data-collector" text="Data Collector" />
 

diff --git a/docs/docs/targets/index.md b/docs/docs/targets/index.md
@@ -18,7 +18,6 @@ The way to map data from a data collector to a target depends on data model of t
 | [Qdrant](/docs/targets/qdrant)     | Vector Database, Keyword Search       |
 | [LanceDB](/docs/targets/lancedb)   | Vector Database, Keyword Search         |
 | [Neo4j](/docs/targets/neo4j)       | [Property graph](#property-graph-targets)        |
-| [Kuzu](/docs/targets/kuzu)         | [Property graph](#property-graph-targets)        |
 
 If you are looking for targets beyond here, you can always use [custom targets](/docs/custom_ops/custom_targets) as building blocks.
 

diff --git a/docs/docs/targets/kuzu.md b/docs/docs/targets/kuzu.md
@@ -5,7 +5,9 @@ toc_max_heading_level: 4
 ---
 import { ExampleButton } from '../../src/components/GitHubButton';
 
-# Kuzu
+# Kuzu (Archived)
+
+Note:[Kuzu](https://github.com/kuzudb/kuzu) - embedded graph database is no longer maintained.
 
 Exports data to a [Kuzu](https://kuzu.com/) graph database.
 

diff --git a/examples/docs_to_knowledge_graph/README.md b/examples/docs_to_knowledge_graph/README.md
@@ -14,12 +14,11 @@ 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/ops/targets#neo4j-dev-instance) or [Kuzu](https://cocoindex.io/docs/ops/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
-You can read the official CocoIndex Documentation for Property Graph Targets [here](https://cocoindex.io/docs/ops/targets#property-graph-targets).
+You can read the official CocoIndex Documentation for Property Graph Targets [here](https://cocoindex.io/docs/targets#property-graph-targets).
 
 ## Run
 
@@ -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/ops/targets#kuzu-dev-instance) for more details.
-
 You can run the following Cypher query to get all relationships:
 
 ```cypher

diff --git a/examples/docs_to_knowledge_graph/main.py b/examples/docs_to_knowledge_graph/main.py
@@ -14,29 +14,12 @@
         password="cocoindex",
     ),
 )
-kuzu_conn_spec = cocoindex.add_auth_entry(
-    "KuzuConnection",
-    cocoindex.targets.KuzuConnection(
-        api_server_url="http://localhost:8123",
-    ),
-)
 
-# SELECT ONE GRAPH DATABASE TO USE
-# This example can use either Neo4j or Kuzu as the graph database.
-# Please make sure only one branch is live and others are commented out.
-
-# Use Neo4j
 GraphDbSpec = cocoindex.targets.Neo4j
 GraphDbConnection = cocoindex.targets.Neo4jConnection
 GraphDbDeclaration = cocoindex.targets.Neo4jDeclaration
 conn_spec = neo4j_conn_spec
 
-# Use Kuzu
-#  GraphDbSpec = cocoindex.targets.Kuzu
-#  GraphDbConnection = cocoindex.targets.KuzuConnection
-#  GraphDbDeclaration = cocoindex.targets.KuzuDeclaration
-#  conn_spec = kuzu_conn_spec
-
 
 @dataclasses.dataclass
 class DocumentSummary:

diff --git a/examples/patient_intake_extraction/README.md b/examples/patient_intake_extraction/README.md
@@ -4,7 +4,7 @@ We appreciate a star ⭐ at [CocoIndex Github](https://github.com/cocoindex-io/c
 
 
 This repo shows how to use LLM to extract structured data from patient intake forms with different formats - like PDF, Docx, etc.
-CocoIndex supports multiple [sources](https://cocoindex.io/docs/ops/sources) and [LLM models](https://cocoindex.io/docs/ai/llm) natively.
+CocoIndex supports multiple [sources](https://cocoindex.io/docs/sources) and [LLM models](https://cocoindex.io/docs/ai/llm) natively.
 
 ![Structured Data From Patient Intake Forms](https://github.com/user-attachments/assets/1f6afb69-d26d-4a08-8774-13982d6aec1e)
 

diff --git a/examples/product_recommendation/README.md b/examples/product_recommendation/README.md
@@ -8,13 +8,12 @@ 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/ops/targets#neo4j-dev-instance) or [Kuzu](https://cocoindex.io/docs/ops/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 Postgres](https://cocoindex.io/docs/getting_started/installation#-install-postgres) 
+*   Install [Neo4j](https://cocoindex.io/docs/targets/neo4j)
 *   [Configure your OpenAI API key](https://cocoindex.io/docs/ai/llm#openai).
 
 ## Documentation
-You can read the official CocoIndex Documentation for Property Graph Targets [here](https://cocoindex.io/docs/ops/targets#property-graph-targets).
+You can read the official CocoIndex Documentation for Property Graph Targets [here](https://cocoindex.io/docs/targets#property-graph-targets).
 
 ## Run
 
@@ -43,7 +42,6 @@ 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/ops/targets#kuzu-dev-instance) for more details.
 
 You can run the following Cypher query to get all relationships:
 

diff --git a/examples/product_recommendation/main.py b/examples/product_recommendation/main.py
@@ -15,29 +15,12 @@
         password="cocoindex",
     ),
 )
-kuzu_conn_spec = cocoindex.add_auth_entry(
-    "KuzuConnection",
-    cocoindex.targets.KuzuConnection(
-        api_server_url="http://localhost:8123",
-    ),
-)
 
-# SELECT ONE GRAPH DATABASE TO USE
-# This example can use either Neo4j or Kuzu as the graph database.
-# Please make sure only one branch is live and others are commented out.
-
-# Use Neo4j
 GraphDbSpec = cocoindex.targets.Neo4j
 GraphDbConnection = cocoindex.targets.Neo4jConnection
 GraphDbDeclaration = cocoindex.targets.Neo4jDeclaration
 conn_spec = neo4j_conn_spec
 
-# Use Kuzu
-#  GraphDbSpec = cocoindex.targets.Kuzu
-#  GraphDbConnection = cocoindex.targets.KuzuConnection
-#  GraphDbDeclaration = cocoindex.targets.KuzuDeclaration
-#  conn_spec = kuzu_conn_spec
-
 
 # Template for rendering product information as markdown to provide information to LLMs
 PRODUCT_TEMPLATE = """

diff --git a/examples/text_embedding_qdrant/README.md b/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/ops/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.