> ## Documentation Index
> Fetch the complete documentation index at: https://docs-v1.agno.com/llms.txt
> Use this file to discover all available pages before exploring further.

# Document Knowledge Base

## Code

```python theme={null}
from agno.agent import Agent
from agno.document.base import Document
from agno.knowledge.document import DocumentKnowledgeBase
from agno.vectordb.pgvector import PgVector

fun_facts = """
- Earth is the third planet from the Sun and the only known astronomical object to support life.
- Approximately 71% of Earth's surface is covered by water, with the Pacific Ocean being the largest.
- The Earth's atmosphere is composed mainly of nitrogen (78%) and oxygen (21%), with traces of other gases.
- Earth rotates on its axis once every 24 hours, leading to the cycle of day and night.
- The planet has one natural satellite, the Moon, which influences tides and stabilizes Earth's axial tilt.
- Earth's tectonic plates are constantly shifting, leading to geological activities like earthquakes and volcanic eruptions.
- The highest point on Earth is Mount Everest, standing at 8,848 meters (29,029 feet) above sea level.
- The deepest part of the ocean is the Mariana Trench, reaching depths of over 11,000 meters (36,000 feet).
- Earth has a diverse range of ecosystems, from rainforests and deserts to coral reefs and tundras.
- The planet's magnetic field protects life by deflecting harmful solar radiation and cosmic rays.
"""

# Load documents from the data/docs directory
documents = [Document(content=fun_facts)]

# Database connection URL
db_url = "postgresql+psycopg://ai:ai@localhost:5532/ai"

# Create a knowledge base with the loaded documents
knowledge_base = DocumentKnowledgeBase(
    documents=documents,
    vector_db=PgVector(
        table_name="documents",
        db_url=db_url,
    ),
)

# Load the knowledge base
knowledge_base.load(recreate=False)

# Create an agent with the knowledge base
agent = Agent(
    knowledge=knowledge_base,
)

# Ask the agent about the knowledge base
agent.print_response(
    "Ask me about something from the knowledge base about earth", markdown=True
)
```

## Usage

<Steps>
  <Snippet file="create-venv-step.mdx" />

  <Step title="Install libraries">
    ```bash theme={null}
    pip install -U sqlalchemy 'psycopg[binary]' pgvector agno
    ```
  </Step>

  <Step title="Run PgVector">
    ```bash theme={null}
    docker run -d \
      -e POSTGRES_DB=ai \
      -e POSTGRES_USER=ai \
      -e POSTGRES_PASSWORD=ai \
      -e PGDATA=/var/lib/postgresql/data/pgdata \
      -v pgvolume:/var/lib/postgresql/data \
      -p 5532:5432 \
      --name pgvector \
      agnohq/pgvector:16
    ```
  </Step>

  <Step title="Run Agent">
    <CodeGroup>
      ```bash Mac theme={null}
      python cookbook/agent_concepts/knowledge/doc_kb.py
      ```

      ```bash Windows theme={null}
      python cookbook/agent_concepts/knowledge/doc_kb.py
      ```
    </CodeGroup>
  </Step>
</Steps>