> ## Documentation Index
> Fetch the complete documentation index at: https://agno-v2.mintlify.site/llms.txt
> Use this file to discover all available pages before exploring further.

# Storage and Memory

> Combine PgVector knowledge, Postgres memory, session summaries, and web search on Gemini.

```python storage_and_memory.py theme={null}
"""Run `pip install ddgs pgvector google.genai` to install dependencies."""

from agno.agent import Agent
from agno.db.postgres.postgres import PostgresDb
from agno.knowledge import PDFUrlKnowledgeBase
from agno.models.google import Gemini
from agno.tools.websearch import WebSearchTools
from agno.vectordb.pgvector import PgVector

# ---------------------------------------------------------------------------
# Create Agent
# ---------------------------------------------------------------------------

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

knowledge_base = PDFUrlKnowledgeBase(
    urls=["https://agno-public.s3.amazonaws.com/recipes/ThaiRecipes.pdf"],
    vector_db=PgVector(table_name="recipes", db_url=db_url),
)
knowledge_base.load(recreate=True)  # Comment out after first run

agent = Agent(
    model=Gemini(id="gemini-3.7-flash"),
    tools=[WebSearchTools()],
    knowledge=knowledge_base,
    # Store the memories and summary in a database
    db=PostgresDb(db_url=db_url, memory_table="agent_memory"),
    update_memory_on_run=True,
    enable_session_summaries=True,
    # This setting adds a tool to search the knowledge base for information
    search_knowledge=True,
    # This setting adds a tool to get chat history
    read_chat_history=True,
    # Add the previous chat history to the messages sent to the Model.
    add_history_to_context=True,
    # This setting adds 6 previous messages from chat history to the messages sent to the LLM
    num_history_runs=6,
    markdown=True,
)
agent.print_response("Whats is the latest AI news?")

# ---------------------------------------------------------------------------
# Run Agent
# ---------------------------------------------------------------------------

if __name__ == "__main__":
    pass
```

## Run the Example

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

**1. Install dependencies**

```bash theme={null}
uv pip install -U agno "psycopg[binary]" ddgs google-genai openai pgvector pypdf sqlalchemy
```

**2. Export your API keys**

```bash Mac/Linux theme={null}
export GOOGLE_API_KEY="your_google_api_key_here"
export OPENAI_API_KEY="your_openai_api_key_here"
```

```bash Windows theme={null}
$Env:GOOGLE_API_KEY="your_google_api_key_here"
$Env:OPENAI_API_KEY="your_openai_api_key_here"
```

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

**3. Run the example**

Save the code above as `storage_and_memory.py`, then run:

```bash theme={null}
python storage_and_memory.py
```

Full source: [cookbook/90\_models/google/gemini/storage\_and\_memory.py](https://github.com/agno-agi/agno/blob/v3.0.4/cookbook/90_models/google/gemini/storage_and_memory.py)


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