> ## Documentation Index
> Fetch the complete documentation index at: https://phidatainc-studio-tools-doc.mintlify.site/llms.txt
> Use this file to discover all available pages before exploring further.

# Knowledge

## Code

```python cookbook/11_models/ollama/knowledge.py theme={null}
from agno.agent import Agent
from agno.knowledge.embedder.ollama import OllamaEmbedder
from agno.knowledge.knowledge import Knowledge
from agno.models.ollama import Ollama
from agno.vectordb.pgvector import PgVector

db_url = "postgresql+psycopg://ai:ai@localhost:5532/ai"

knowledge = Knowledge(
    vector_db=PgVector(
        table_name="recipes",
        db_url=db_url,
        embedder=OllamaEmbedder(id="llama3.2", dimensions=3072),
    ),
)
# Add content to the knowledge
knowledge.insert(
    url="https://agno-public.s3.amazonaws.com/recipes/ThaiRecipes.pdf"
)

agent = Agent(model=Ollama(id="llama3.2"), knowledge=knowledge)
agent.print_response("How to make Thai curry?", markdown=True)

```

## Usage

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

  <Step title="Install Ollama">
    Follow the [Ollama installation guide](https://github.com/ollama/ollama?tab=readme-ov-file#macos) and run:

    ```bash theme={null}
    ollama pull llama3.2
    ```
  </Step>

  <Step title="Install dependencies">
    ```bash theme={null}
    uv pip install -U agno sqlalchemy pgvector pypdf openai ollama
    ```
  </Step>

  <Step title="Run Agent">
    ```bash theme={null}
    python cookbook/11_models/ollama/knowledge.py
    ```
  </Step>
</Steps>