Create urban_planning.py

playground/demos/urban_planning/urban_planning.py

@@ -0,0 +1,47 @@
+import os
+from dotenv import load_dotenv
+from swarms.models import OpenAIChat, GPT4VisionAPI
+from swarms.structs import Agent, SequentialWorkflow
+import swarms.prompts.urban_planning as upp
+
+# Load environment variables
+load_dotenv()
+api_key = os.getenv("OPENAI_API_KEY")
+stability_api_key = os.getenv("STABILITY_API_KEY")
+
+# Initialize language model
+llm = OpenAIChat(openai_api_key=api_key, temperature=0.5, max_tokens=3000)
+
+# Initialize Vision model
+vision_api = GPT4VisionAPI(api_key=api_key)
+
+# Initialize agents for urban planning tasks
+architecture_analysis_agent = Agent(llm=llm, max_loops=1, sop=upp.ARCHITECTURE_ANALYSIS_PROMPT)
+infrastructure_evaluation_agent = Agent(llm=llm, max_loops=1, sop=upp.INFRASTRUCTURE_EVALUATION_PROMPT)
+traffic_flow_analysis_agent = Agent(llm=llm, max_loops=1, sop=upp.TRAFFIC_FLOW_ANALYSIS_PROMPT)
+environmental_impact_assessment_agent = Agent(llm=llm, max_loops=1, sop=upp.ENVIRONMENTAL_IMPACT_ASSESSMENT_PROMPT)
+public_space_utilization_agent = Agent(llm=llm, max_loops=1, sop=upp.PUBLIC_SPACE_UTILIZATION_PROMPT)
+socioeconomic_impact_analysis_agent = Agent(llm=llm, max_loops=1, sop=upp.SOCIOECONOMIC_IMPACT_ANALYSIS_PROMPT)
+
+# Initialize the final planning agent
+final_plan_agent = Agent(llm=llm, max_loops=1, sop=upp.FINAL_URBAN_IMPROVEMENT_PLAN_PROMPT)
+
+# Create Sequential Workflow
+workflow = SequentialWorkflow(max_loops=1)
+
+# Add tasks to workflow with personalized prompts
+workflow.add(architecture_analysis_agent, "Architecture Analysis")
+workflow.add(infrastructure_evaluation_agent, "Infrastructure Evaluation")
+workflow.add(traffic_flow_analysis_agent, "Traffic Flow Analysis")
+workflow.add(environmental_impact_assessment_agent, "Environmental Impact Assessment")
+workflow.add(public_space_utilization_agent, "Public Space Utilization")
+workflow.add(socioeconomic_impact_analysis_agent, "Socioeconomic Impact Analysis")
+workflow.add(final_plan_agent, "Generate the final urban improvement plan based on all previous agent's findings")
+# Run the workflow for individual analysis tasks
+
+# Execute the workflow for the final planning
+workflow.run()
+
+# Output results for each task and the final plan
+for task in workflow.tasks:
+    print(f"Task Description: {task.description}\nResult: {task.result}\n")