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

# PDF Agent with Storage

Create an Agent that can

* Read PDFs and store them in a knowledge base
* Store the runs in PostgreSQL to provide long-term memory across sessions

```python theme={null}
import typer
from typing import Optional, List
from phi.agent import Agent
from phi.storage.agent.postgres import PgAgentStorage
from phi.knowledge.pdf import PDFUrlKnowledgeBase
from phi.vectordb.pgvector import PgVector, SearchType

db_url = "postgresql+psycopg://ai:ai@localhost:5532/ai"
knowledge_base = PDFUrlKnowledgeBase(
    urls=["https://phi-public.s3.amazonaws.com/recipes/ThaiRecipes.pdf"],
    vector_db=PgVector(table_name="recipes", db_url=db_url, search_type=SearchType.hybrid),
)
# Load the knowledge base: Comment out after first run
knowledge_base.load(upsert=True)

storage = PgAgentStorage(table_name="pdf_agent", db_url=db_url)


def pdf_agent(new: bool = False, user: str = "user"):
    session_id: Optional[str] = None

    if not new:
        existing_sessions: List[str] = storage.get_all_session_ids(user)
        if len(existing_sessions) > 0:
            session_id = existing_sessions[0]

    agent = Agent(
        session_id=session_id,
        user_id=user,
        knowledge=knowledge_base,
        storage=storage,
        # Show tool calls in the response
        show_tool_calls=True,
        # Enable the agent to read the chat history
        read_chat_history=True,
    )
    if session_id is None:
        session_id = agent.session_id
        print(f"Started Session: {session_id}\n")
    else:
        print(f"Continuing Session: {session_id}\n")

    # Runs the agent as a cli app
    agent.cli_app(markdown=True)


if __name__ == "__main__":
    typer.run(pdf_agent)

```

## Usage

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

  <Snippet file="run-pgvector-step.mdx" />

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

  <Step title="Run the agent">
    <CodeGroup>
      ```bash Mac theme={null}
      python cookbook/agents/pdf_agent.py
      ```

      ```bash Windows theme={null}
      python cookbook/agents/pdf_agent.py
      ```
    </CodeGroup>

    Now the agent continues across sessions. Ask a question:

    ```
    How do I make pad thai?
    ```

    Then message `bye` to exit, start the app again and ask:

    ```
    What was my last message?
    ```
  </Step>

  <Step title="Start a new run">
    Run the `agent_with_storage.py` file with the `--new` flag to start a new run.

    ```bash theme={null}
    python agent_with_storage.py --new
    ```
  </Step>

  <Step title="Stop PgVector">
    ```bash theme={null}
    phi stop cookbook/rag/resources.py -y
    ```
  </Step>
</Steps>

## Information

* Read about [Agent Storage](/agents/storage)