kg_test_cypher_generator_node_langgraph

async def kg_test(self, state: State) -> State:
        print("🕸️ Generando Cypher Query para Knowledge Graph...")
        
        customer_profile = state.get("customerProfile")
        
        system_template = """You are an expert assistant in creating Knowledge Graphs generating Cypher Queries.
        
        Your tasks are:
        1. Identify entities and relationships and property keys from the context.
        2. Context is the Customer Profile provided.
        3. Generate Cypher Query to create a knowledge Graph from the identified entities, relationships, and property keys.
        
        Guidelines:
        - Extract all entities and relationships as possible.
        - ALWAYS extract a person Profession as an Entity.
        - ALWAYS extract a Profession's Industry as an Entity.
        - Be Creative. Understand hidden relationships from the network.
        - Read the context three times and carefully before generating Cypher Query.
        - Return ONLY a Cypher Query. Do not return anything else.
        - Do not hallucinate.
        - Entities to include: Person, City, Profession, Industry.
        
        Few Shot Example:
        Example Context:
        {{
            "name": "Fabián Almenara Cerezo",
            "email": "fabian.almenara@gmail.com",
            "city": "granada",
            "customerProfile": {{
                "name": "Fabián Almenara Cerezo",
                "industry": "Information Technology and Services",
                "city": "Granada",
                "state": "Spain",
                "currentPosition": "CTO Cubicup",
                "interests": ["Innovation", "AI", "Sales"]
            }}
        }}
        
        Answer:
        MERGE (Fabián_Almenara_Cerezo:Person {{name: "Fabián Almenara Cerezo", email: "fabian.almenara@gmail.com"}})
        MERGE (CTO_Cubicup:Profession {{name: "CTO Cubicup"}})
        MERGE (Information_Technology:Industry {{name: "Information Technology and Services"}})
        MERGE (Fabián_Almenara_Cerezo)-[:HAS_PROFESSION]->(CTO_Cubicup)
        MERGE (CTO_Cubicup)-[:BELONGS_TO_INDUSTRY]->(Information_Technology)
        MERGE (Granada:City {{name: "Granada"}})
        MERGE (Spain:Country {{name: "Spain"}})
        MERGE (Fabián_Almenara_Cerezo)-[:LIVES_IN]->(Granada)
        MERGE (Fabián_Almenara_Cerezo)-[:FROM]->(Spain)
        """

        prompt = ChatPromptTemplate.from_messages([
            ("system", system_template),
            ("user", "Context: {context}")
        ])

        chain = prompt | self.llm
        
        try:
            # Serializar el perfil para el contexto
            context_str = str(customer_profile.model_dump()) if customer_profile else "No profile data"
            
            completion = await chain.ainvoke({"context": context_str})
            cypher_query = completion.content if hasattr(completion, 'content') else str(completion)
            
            # Limpiar posible markdown formatting ```cypher ... ```
            cypher_query = cypher_query.replace("```cypher", "").replace("```", "").strip()
            
            print(f"✅ Cypher Query generada:\n{cypher_query}")
            return State({"cypherQuery": cypher_query})
            
        except Exception as e:
            print(f"❌ Error generando Cypher Query: {e}")
            return State({"cypherQuery": ""})