> ## Documentation Index
> Fetch the complete documentation index at: https://docs.mindsdb.com/llms.txt
> Use this file to discover all available pages before exploring further.
# How Knowledge Bases Work
A knowledge base is an advanced AI-table that organizes information based on semantic meaning rather than simple keyword matching. It integrates embedding models, reranking models, and vector stores to enable context-aware data retrieval.
By performing semantic reasoning across multiple data points, a knowledge base delivers deeper insights and more accurate responses, making it a powerful tool for intelligent data access.
Before diving into the syntax, here is a quick walkthrough showing how knowledge bases work in MindsDB.
We start by creating a knowledge base and inserting data. Next we can run semantic search queries with metadata filtering.
Use the `CREATE KNOWLEDGE_BASE` command to create a knowledge base, specifying all its components.
```sql theme={null}
CREATE KNOWLEDGE_BASE my_kb
USING
embedding_model = {
"provider": "openai",
"model_name" : "text-embedding-3-large",
"api_key": "sk-abc123"
},
reranking_model = {
"provider": "openai",
"model_name": "gpt-4o",
"api_key": "sk-abc123"
},
metadata_columns = ['product'],
content_columns = ['notes'],
id_column = 'order_id';
```
In this example, we use a simple dataset containing customer notes for product orders which will be inserted into the knowledge base.
```sql theme={null}
+----------+-----------------------+------------------------+
| order_id | product | notes |
+----------+-----------------------+------------------------+
| A1B | Wireless Mouse | Request color: black |
| 3XZ | Bluetooth Speaker | Gift wrap requested |
| Q7P | Aluminum Laptop Stand | Prefer aluminum finish |
+----------+-----------------------+------------------------+
```
Use the `INSERT INTO` command to ingest data into the knowledge base.
```sql theme={null}
INSERT INTO my_kb
SELECT order_id, product, notes
FROM sample_data.orders;
```
Query the knowledge base using semantic search.
```sql theme={null}
SELECT *
FROM my_kb
WHERE content = 'color preference'
```
This query returns:
```sql theme={null}
+-----+----------------------+-------------------------+-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+-----------------------+--------------------+--------------------+
| id | chunk_id | chunk_content | metadata | product | distance | relevance |
+-----+----------------------+-------------------------+-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+-----------------------+--------------------+--------------------+
| A1B | A1B_notes:1of1:0to20 | Request color: black | {"chunk_index":0,"content_column":"notes","end_char":20,"original_doc_id":"A1B_notes","original_row_id":"A1B","product":"Wireless Mouse","source":"TextChunkingPreprocessor","start_char":0} | Wireless Mouse | 0.5743341242061104 | 0.5093188026135379 |
| Q7P | Q7P_notes:1of1:0to22 | Prefer aluminum finish | {"chunk_index":0,"content_column":"notes","end_char":22,"original_doc_id":"Q7P_notes","original_row_id":"Q7P","product":"Aluminum Laptop Stand","source":"TextChunkingPreprocessor","start_char":0} | Aluminum Laptop Stand | 0.7744703514692067 | 0.2502580835880018 |
| 3XZ | 3XZ_notes:1of1:0to19 | Gift wrap requested | {"chunk_index":0,"content_column":"notes","end_char":19,"original_doc_id":"3XZ_notes","original_row_id":"3XZ","product":"Bluetooth Speaker","source":"TextChunkingPreprocessor","start_char":0} | Bluetooth Speaker | 0.8010851611432231 | 0.2500003885558766 |
+-----+----------------------+-------------------------+-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+-----------------------+--------------------+--------------------+
```
Query the knowledge base using semantic search and define the `relevance` parameter to receive only the best matching data for your use case.
```sql theme={null}
SELECT *
FROM my_kb
WHERE content = 'color'
AND relevance >= 0.2502;
```
This query returns:
```sql theme={null}
+-----+----------------------+-------------------------+-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+-----------------------+--------------------+--------------------+
| id | chunk_id | chunk_content | metadata | product | distance | relevance |
+-----+----------------------+-------------------------+-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+-----------------------+--------------------+--------------------+
| A1B | A1B_notes:1of1:0to20 | Request color: black | {"chunk_index":0,"content_column":"notes","end_char":20,"original_doc_id":"A1B_notes","original_row_id":"A1B","product":"Wireless Mouse","source":"TextChunkingPreprocessor","start_char":0} | Wireless Mouse | 0.5743341242061104 | 0.5093188026135379 |
| Q7P | Q7P_notes:1of1:0to22 | Prefer aluminum finish | {"chunk_index":0,"content_column":"notes","end_char":22,"original_doc_id":"Q7P_notes","original_row_id":"Q7P","product":"Aluminum Laptop Stand","source":"TextChunkingPreprocessor","start_char":0} | Aluminum Laptop Stand | 0.7744703514692067 | 0.2502580835880018 |
+-----+----------------------+-------------------------+-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+-----------------------+--------------------+--------------------+
```
Add metadata filtering to focus your search.
```sql theme={null}
SELECT *
FROM my_kb
WHERE product = 'Wireless Mouse'
AND content = 'color'
AND relevance >= 0.2502;
```
This query returns:
```sql theme={null}
+-----+----------------------+------------------------+----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+----------------+--------------------+-------------------+
| id | chunk_id | chunk_content | metadata | product | distance | relevance |
+-----+----------------------+------------------------+----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+----------------+--------------------+-------------------+
| A1B | A1B_notes:1of1:0to20 | Request color: black | {"chunk_index":0,"content_column":"notes","end_char":20,"original_doc_id":"A1B_notes","original_row_id":"A1B","product":"Wireless Mouse","source":"TextChunkingPreprocessor","start_char":0} | Wireless Mouse | 0.5743341242061104 | 0.504396172197583 |
+-----+----------------------+------------------------+----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+----------------+--------------------+-------------------+
```
The following sections explain the syntax and other features of knowledge bases.