How to add an adapter

from agno.agent import Agent as agnoAgent
from agno.media import Image as agnoImage
from agno.models.openai import OpenAIChat
from agno.tools.duckduckgo import DuckDuckGoTools

agent = agnoAgent(
    model=OpenAIChat(id="gpt-4.1-nano"),
    tools=[DuckDuckGoTools()],
    markdown=True,
)

response = agent.run(
    "Tell me about this image and give me the latest news about it.",
    images=[
        agnoImage(
            url="https://upload.wikimedia.org/wikipedia/commons/0/0c/GoldenGateBridge-001.jpg"
        )
    ],
    stream=False  # No streaming
)
response.content

from IPython.display import Markdown
Markdown(response.content)

img = agnoImage(url="https://upload.wikimedia.org/wikipedia/commons/0/0c/GoldenGateBridge-001.jpg")
type(img)

dir(img)

img.model_fields.keys()

print("URL:", img.url)
print("Filepath:", img.filepath)
print("Content:", img.content)
print("Format:", img.format)
print("Detail:", img.detail)
print("ID:", img.id)

from agno.media import Image as AgnoImage
import base64

# Method 1: Create with URL
print("=== Method 1: URL ===")
img_url = AgnoImage(url="https://upload.wikimedia.org/wikipedia/commons/0/0c/GoldenGateBridge-001.jpg")
print("URL Image:", img_url)
print("Has URL:", bool(img_url.url))

# Method 2: Create with raw bytes content
print("\n=== Method 2: Raw Bytes ===")
# Let's create a tiny 1x1 pixel PNG for testing
sample_base64 = "iVBORw0KGgoAAAANSUhEUgAAAAEAAAABCAYAAAAfFcSJAAAADUlEQVR42mP8/5+hHgAHggJ/PchI7wAAAABJRU5ErkJggg=="
content_bytes = base64.b64decode(sample_base64)
img_content = AgnoImage(content=content_bytes)
print("Content Image:", img_content)
print("Has content:", bool(img_content.content))

# Method 3: What about data URLs? (base64 encoded images with data: prefix)
print("\n=== Method 3: Data URL ===")
data_url = f"data:image/png;base64,{sample_base64}"
img_data_url = AgnoImage(url=data_url)
print("Data URL Image:", img_data_url)
print("URL field contains:", img_data_url.url[:50] + "..." if len(img_data_url.url) > 50 else img_data_url.url)

from attachments import Attachments

sample_attachments = Attachments("https://upload.wikimedia.org/wikipedia/commons/0/0c/GoldenGateBridge-001.jpg")

sample_attachment = sample_attachments.attachments[0]  # Get the first (and only) attachment
sample_attachment

# Let's examine what the attachment contains
print("Text content length:", len(sample_attachment.text))

print("Number of images:", len(sample_attachment.images))

print("Text preview:", sample_attachment.text[:200] + "..." if len(sample_attachment.text) > 200 else sample_attachment.text)

from IPython.display import HTML
HTML(f"<img src='{sample_attachment.images[0]}'>")

# Now let's look at how the image is stored
if sample_attachment.images:
    img_data = sample_attachment.images[0]
    print("Image data type:", type(img_data))
    print("Image data length:", len(img_data))
    print("Starts with 'data:image/':", img_data.startswith('data:image/'))
    print("First 50 characters:", img_data[:50])

# Take the image data from Attachments
img_data = sample_attachment.images[0]

# Create an agno Image with it
agno_img = AgnoImage(url=img_data)
print("Agno Image created successfully:", agno_img)
print("Image URL field (first 100 chars):", agno_img.url[:100] + "...")

att = Attachments("https://upload.wikimedia.org/wikipedia/commons/0/0c/GoldenGateBridge-001.jpg",
                  "https://upload.wikimedia.org/wikipedia/commons/2/2c/Llama_willu.jpg")
att

len(att.images)

print(att.text)

from IPython.display import HTML
HTML(f"<img src='{att.images[0]}' height='200'><img src='{att.images[1]}' height='200'>")

[AgnoImage(url=img) for img in att.images]

from agno.agent import Agent as AgnoAgent
from agno.models.openai import OpenAIChat

# Create a simple agent to examine its interface
agent = AgnoAgent(
    model=OpenAIChat(id="gpt-4o-mini"),
    markdown=True,
)

# Let's see what parameters agent.run accepts
import inspect
sig = inspect.signature(agent.run)
print("agent.run() parameters:")
for param_name, param in sig.parameters.items():
    print(f"  {param_name}: {param.annotation if param.annotation != inspect.Parameter.empty else 'Any'}")

agent = AgnoAgent(
    model=OpenAIChat(id="gpt-4.1-nano"),
    markdown=True,
)
att = Attachments("https://upload.wikimedia.org/wikipedia/commons/0/0c/GoldenGateBridge-001.jpg",
                  "https://upload.wikimedia.org/wikipedia/commons/2/2c/Llama_willu.jpg")
res = agent.run(
    message="What do you see in this image?",
    images=[AgnoImage(url=img) for img in att.images],
    stream=False
)
res.content

res = agent.run(
    message=f"Name the 2 things in the 2 images and tell me about the image metadata: {att.text}",
    images=[AgnoImage(url=img) for img in att.images],
    stream=False
)
res.content

prompt = f"Name the 2 things in the 2 images and tell me about the image metadata:"
images = [AgnoImage(url=img) for img in att.images]

params = {
    "message": f"{prompt} {att.text}",
    "images": images,
}
res = res = agent.run(**params)
res.content

def convert_attachments_to_agno(attachment, prompt=""):
    """Convert Attachments to agno Image objects."""
    images = [AgnoImage(url=img) for img in attachment.images]
    return {
        "message": f"{prompt} {attachment.text}",
        "images": images,
    }

params = convert_attachments_to_agno(att, "What do you see in this image?")
res = agent.run(**params)
res.content

from attachments.adapt import adapter
from attachments import Attachment, AttachmentCollection
from typing import Union, Dict, Any
@adapter
def custom_agno(input_obj: Union[Attachment, AttachmentCollection], prompt: str = "") -> Dict[str, Any]:
    return convert_attachments_to_agno(input_obj, prompt)

att = Attachments("https://upload.wikimedia.org/wikipedia/commons/0/0c/GoldenGateBridge-001.jpg",
                  "https://upload.wikimedia.org/wikipedia/commons/2/2c/Llama_willu.jpg")

res = agent.run(**att.custom_agno("What do you see in this image?"))
res.content

att = Attachments("https://upload.wikimedia.org/wikipedia/commons/f/f0/Strange_stories_%28microform%29_%28IA_cihm_05072%29.pdf[1-4]")
res = agent.run(**att.custom_agno("Summarize this document"))

Markdown(res.content)

from IPython.display import HTML
HTML(f"<img src='{att.images[0]}'>")

from agno.agent import Agent
from agno.models.openai import OpenAIChat
from agno.tools.duckduckgo import DuckDuckGoTools
from attachments import Attachments

agent = agnoAgent(
    model=OpenAIChat(id="gpt-4.1-nano"),
    tools=[DuckDuckGoTools()],
    markdown=True,
)

response = agent.run(
    **Attachments("https://upload.wikimedia.org/wikipedia/commons/0/0c/GoldenGateBridge-001.jpg").
             agno("Tell me about this image and give me the latest news about it."))

print(response.content)