multimodal.py

from praisonaiagents import Agent, Task, AgentTeam

# Create Vision Analysis Agent
vision_agent = Agent(
    name="VisionAnalyst",
    role="Computer Vision Specialist",
    goal="Analyze images and videos to extract meaningful information",
    backstory="""You are an expert in computer vision and image analysis.
    You excel at describing images, detecting objects, and understanding visual content.""",
    llm="gpt-4o-mini",
    reflection=False
)

# 1. Task with Image URL
task1 = Task(
    name="analyze_landmark",
    description="Describe this famous landmark and its architectural features.",
    expected_output="Detailed description of the landmark's architecture and significance",
    agent=vision_agent,
    images=["https://upload.wikimedia.org/wikipedia/commons/b/bf/Krakow_-_Kosciol_Mariacki.jpg"]
)

# 2. Task with Local Image File
task2 = Task(
    name="analyze_local_image",
    description="What objects can you see in this image? Describe their arrangement.",
    expected_output="Detailed description of objects and their spatial relationships",
    agent=vision_agent,
    images=["image.jpg"] 
)

# 3. Task with Video File
task3 = Task(
    name="analyze_video",
    description="""Watch this video and provide:
    1. A summary of the main events
    2. Key objects and people visible
    3. Any text or important information shown
    4. The overall context and setting""",
    expected_output="Comprehensive analysis of the video content",
    agent=vision_agent,
    images=["video.mp4"]  
)

# Create Agents instance
agents = AgentTeam(
    agents=[vision_agent],
    tasks=[task1, task2, task3],
    process="sequential"
)

# Run all tasks
result = agents.start()

# Print results
for task_id, task_result in result["task_results"].items():
    print(f"\nTask {task_id} Result:")
    print(task_result.raw)