> For the complete documentation index, see [llms.txt](https://docs.projectbit.ca/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.projectbit.ca/documentation/knowledges/website-knowledge-base.md).

# Website Knowledge Base

The **WebsiteKnowledgeBase** reads websites, converts them into vector embeddings and loads them to a `vector_db`.

### [​](https://docs.phidata.com/knowledge/website#usage)Usage <a href="#usage" id="usage"></a>

We are using a local PgVector database for this example. [Make sure it’s running](https://docs.phidata.com/vectordb/pgvector)

```shell
pip install bs4
```

knowledge\_base.py

```python
from bitca.knowledge.website import WebsiteKnowledgeBase
from bitca.vectordb.pgvector import PgVector

knowledge_base = WebsiteKnowledgeBase(
    urls=["https://docs.bitcadata.com/introduction"],
    # Number of links to follow from the seed URLs
    max_links=10,
    # Table name: ai.website_documents
    vector_db=PgVector(
        table_name="website_documents",
        db_url="postgresql+psycopg://ai:ai@localhost:5532/ai",
    ),
)
```

Then use the `knowledge_base` with an `Agent`:

agent.py

```python
from bitca.agent import Agent
from knowledge_base import knowledge_base

agent = Agent(
    knowledge=knowledge_base,
    search_knowledge=True,
)
agent.knowledge.load(recreate=False)

agent.print_response("Ask me about something from the knowledge base")
```

### [​](https://docs.phidata.com/knowledge/website#params)Params <a href="#params" id="params"></a>

| Parameter           | Type               | Default             | Description                                                                                       |
| ------------------- | ------------------ | ------------------- | ------------------------------------------------------------------------------------------------- |
| `urls`              | `List[str]`        | -                   | URLs to read                                                                                      |
| `reader`            | `WebsiteReader`    | -                   | A `WebsiteReader` that reads the urls and converts them into `Documents` for the vector database. |
| `max_depth`         | `int`              | `3`                 | Maximum depth to crawl.                                                                           |
| `max_links`         | `int`              | `10`                | Number of links to crawl.                                                                         |
| `vector_db`         | `VectorDb`         | -                   | Vector Database for the Knowledge Base.                                                           |
| `num_documents`     | `int`              | `5`                 | Number of documents to return on search.                                                          |
| `optimize_on`       | `int`              | -                   | Number of documents to optimize the vector db on.                                                 |
| `chunking_strategy` | `ChunkingStrategy` | `FixedSizeChunking` | The chunking strategy to use.                                                                     |