""" Example of knowledge graph node """ import os from scrapegraphai.models import OpenAI from scrapegraphai.nodes import KnowledgeGraphNode job_postings = { "Job Postings": { "Company A": [ { "title": "Software Engineer", "description": "Develop and maintain software applications.", "location": "New York, NY", "date_posted": "2024-05-01", "requirements": ["Python", "Django", "REST APIs"] }, { "title": "Data Scientist", "description": "Analyze and interpret complex data.", "location": "San Francisco, CA", "date_posted": "2024-05-05", "requirements": ["Python", "Machine Learning", "SQL"] } ], "Company B": [ { "title": "Project Manager", "description": "Manage software development projects.", "location": "Boston, MA", "date_posted": "2024-04-20", "requirements": ["Project Management", "Agile", "Scrum"] } ] } } # ************************************************ # Define the configuration for the graph # ************************************************ openai_key = os.getenv("OPENAI_APIKEY") graph_config = { "llm": { "api_key": openai_key, "model": "gpt-4o", "temperature": 0, }, "verbose": True, } # ************************************************ # Define the node # ************************************************ llm_model = OpenAI(graph_config["llm"]) robots_node = KnowledgeGraphNode( input="user_prompt & answer_dict", output=["is_scrapable"], node_config={"llm_model": llm_model} ) # ************************************************ # Test the node # ************************************************ state = { "user_prompt": "What are the job postings?", "answer_dict": job_postings } result = robots_node.execute(state) print(result)