Code
image_input_for_tool.py
from typing import Optional, Sequence
from agno.agent import Agent
from agno.db.postgres import PostgresDb
from agno.media import Image
from agno.models.openai import OpenAIResponses
from agno.tools.dalle import DalleTools
def analyze_images(images: Optional[Sequence[Image]] = None) -> str:
"""
Analyze all available images and provide detailed descriptions.
Args:
images: Images available to the tool (automatically injected)
Returns:
Analysis of all available images
"""
if not images:
return "No images available to analyze."
print(f"--> analyze_images received {len(images)} images")
analysis_results = []
for i, image in enumerate(images):
if image.url:
analysis_results.append(
f"Image {i + 1}: URL-based image at {image.url}"
)
elif image.content:
analysis_results.append(
f"Image {i + 1}: Content-based image ({len(image.content)} bytes)"
)
else:
analysis_results.append(f"Image {i + 1}: Unknown image format")
return f"Found {len(images)} images:\n" + "\n".join(analysis_results)
def count_images(images: Optional[Sequence[Image]] = None) -> str:
"""
Count the number of available images.
Args:
images: Images available to the tool (automatically injected)
Returns:
Count of available images
"""
if not images:
return "0 images available"
print(f"--> count_images received {len(images)} images")
return f"{len(images)} images available"
def create_sample_image_content() -> bytes:
"""Create a simple image-like content for demonstration."""
return b"FAKE_IMAGE_CONTENT_FOR_DEMO"
def main():
# Create an agent with both DALL-E and image analysis functions
agent = Agent(
model=OpenAIResponses(id="gpt-5.2"),
tools=[DalleTools(), analyze_images, count_images],
name="Joint Media Test Agent",
description="An agent that can generate and analyze images using joint media access.",
debug_mode=True,
add_history_to_context=True,
send_media_to_model=False,
db=PostgresDb(db_url="postgresql+psycopg://ai:ai@localhost:5532/ai"),
)
print("=== Joint Media Access Test ===\n")
# Test 1: Initial image upload and analysis
print("1. Testing initial image upload and analysis...")
sample_image = Image(id="test_image_1", content=create_sample_image_content())
response1 = agent.run(
input="I've uploaded an image. Please count how many images are available and analyze them.",
images=[sample_image],
)
print(f"Run 1 Response: {response1.content}")
print(f"--> Run 1 Images in response: {len(response1.input.images or [])}")
print("\n" + "=" * 50 + "\n")
# Test 2: DALL-E generation + analysis in same run
print("2. Testing DALL-E generation and immediate analysis...")
response2 = agent.run(input="Generate an image of a cute cat.")
print(f"Run 2 Response: {response2.content}")
print(f"--> Run 2 Images in response: {len(response2.images or [])}")
print("\n" + "=" * 50 + "\n")
# Test 3: Cross-run media persistence
print("3. Testing cross-run media persistence...")
response3 = agent.run(
input="Count how many images are available from all previous runs and analyze them."
)
print(f"Run 3 Response: {response3.content}")
print("\n" + "=" * 50 + "\n")
if __name__ == "__main__":
main()
Usage
1
Set up your virtual environment
uv venv --python 3.12
source .venv/bin/activate
uv venv --python 3.12
.venv\Scripts\activate
2
Export your OpenAI API key
export OPENAI_API_KEY="your_openai_api_key_here"
$Env:OPENAI_API_KEY="your_openai_api_key_here"
3
Set up PostgreSQL
# Start PostgreSQL with Docker
docker run -d \
--name postgres-ai \
-e POSTGRES_DB=ai \
-e POSTGRES_USER=ai \
-e POSTGRES_PASSWORD=ai \
-p 5532:5432 \
postgres:16
4
Install dependencies
uv pip install -U agno openai psycopg
5
Run Agent
python image_input_for_tool.py