> ## 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.

# Image Agent with Memory

> Use an OpenAIResponses gpt-4o agent with WebSearchTools and add_history_to_context to answer a follow-up question about an image described in an earlier turn.

## Code

```python image_agent_with_memory.py theme={null}
from agno.agent import Agent
from agno.media import Image
from agno.models.openai import OpenAIResponses
from agno.tools.websearch import WebSearchTools

agent = Agent(
    model=OpenAIResponses(id="gpt-4o"),
    tools=[WebSearchTools()],
    markdown=True,
    add_history_to_context=True,
    num_history_runs=3,
)

agent.print_response(
    "Tell me about this image and give me the latest news about it.",
    images=[
        Image(
            url="https://upload.wikimedia.org/wikipedia/commons/0/0c/GoldenGateBridge-001.jpg"
        )
    ],
)

agent.print_response("Tell me where I can get more images?")

```

## Usage

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

**1. Set your API key**

```bash theme={null}
export OPENAI_API_KEY=xxx
```

**2. Install dependencies**

```bash theme={null}
uv pip install -U openai ddgs agno
```

**3. Run Agent**

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

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


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