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Initialize AutoGen Image Audit Agents

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Linked challenge: Multi-Agent Image Integrity Audit for Antibody Validation

Format
Code-aware
Lines
15
Sections
6
Linked challenge
Multi-Agent Image Integrity Audit for Antibody Validation

Prompt source

Original prompt text with formatting preserved for inspection.

15 lines
6 sections
No variables
0 checklist items
import autogen
from autogen import AssistantAgent, UserProxyAgent

config_list = [{'model': 'gpt-4o', 'api_key': '<YOUR_API_KEY>'}]

llm_config = {'config_list': config_list, 'temperature': 0}

vision_analyst = AssistantAgent(
    name='VisionAnalyst',
    llm_config=llm_config,
    system_message='You analyze image feature matrices for copy-move splicing anomalies.'
)

audit_manager = UserProxyAgent(
    name='AuditManager',
    human_input_mode='NEVER',
    code_execution_config={'use_docker': False}
)

# Implement interaction loop to inspect figure data

Adaptation plan

Keep the source stable, then change the prompt in a predictable order so the next run is easier to evaluate.

Keep stable

Hold the task contract and output shape stable so generated implementations remain comparable.

Tune next

Update libraries, interfaces, and environment assumptions to match the stack you actually run.

Verify after

Test failure handling, edge cases, and any code paths that depend on hidden context or secrets.