Create security_team.py

playground/demos/security_team/security_team.py

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+import os
+from dotenv import load_dotenv
+from swarms.models import GPT4VisionAPI
+from swarms.structs import Agent
+import swarms.prompts.security_team as stsp
+
+# Load environment variables and initialize the Vision API
+load_dotenv()
+api_key = os.getenv("OPENAI_API_KEY")
+
+llm = GPT4VisionAPI(openai_api_key=api_key)
+
+# Image for analysis
+img = "bank_robbery.jpg"
+
+# Initialize agents with respective prompts for security tasks
+crowd_analysis_agent = Agent(
+    llm=llm,
+    sop=stsp.CROWD_ANALYSIS_AGENT_PROMPT,
+    max_loops=1,
+    multi_modal=True,
+)
+
+# Facial Recognition Agent is currently not operational
+# facial_recognition_agent = Agent(
+#     llm=llm,
+#     sop=stsp.FACIAL_RECOGNITION_AGENT_PROMPT,
+#     max_loops=1,
+#     multi_modal=True,
+# )
+
+weapon_detection_agent = Agent(
+    llm=llm,
+    sop=stsp.WEAPON_DETECTION_AGENT_PROMPT,
+    max_loops=1,
+    multi_modal=True,
+)
+
+surveillance_monitoring_agent = Agent(
+    llm=llm,
+    sop=stsp.SURVEILLANCE_MONITORING_AGENT_PROMPT,
+    max_loops=1,
+    multi_modal=True,
+)
+
+emergency_response_coordinator = Agent(
+    llm=llm,
+    sop=stsp.EMERGENCY_RESPONSE_COORDINATOR_PROMPT,
+    max_loops=1,
+    multi_modal=True,
+)
+
+# Run agents with respective tasks on the same image
+crowd_analysis = crowd_analysis_agent.run(
+    "Analyze the crowd dynamics in the scene", img
+)
+
+# Facial Recognition Agent is currently not operational
+# facial_recognition_analysis = facial_recognition_agent.run(
+#     "Identify any known individuals in the scene", img
+# )
+
+weapon_detection_analysis = weapon_detection_agent.run(
+    "Inspect the scene for any potential threats", img
+)
+
+surveillance_monitoring_analysis = surveillance_monitoring_agent.run(
+    "Monitor the overall scene for unusual activities", img
+)
+
+emergency_response_analysis = emergency_response_coordinator.run(
+    "Develop a response plan based on the scene analysis", img
+)
+
+# Process and output results for each task
+# Example output (uncomment to use):
+# print(f"Crowd Analysis: {crowd_analysis}")
+# print(f"Weapon Detection Analysis: {weapon_detection_analysis}")
+# print(f"Surveillance Monitoring Analysis: {surveillance_monitoring_analysis}")
+# print(f"Emergency Response Analysis: {emergency_response_analysis}")