Integrate Zep for Persistent Agent Memory

Enhance your Google ADK agent with persistent memory using Zep. Configure Zep to store agent conversation history, past routing decisions, and user preferences. The agent should consult its Zep memory when making new routing decisions, learning from previous interactions to optimize performance and cost over time. Provide the Python code for initializing Zep and integrating it into an agent's context retrieval process. ```python
from zep_python import ZepClient
from zep_python.memory import Memory # Initialize Zep client
zep_client = ZepClient("http://localhost:8000") # Replace with your Zep server URL # Example of integrating Zep memory into an agent function
def agent_with_memory(prompt: str, user_id: str) -> str: session_id = f"user-{user_id}" # Retrieve memory for the session memory = zep_client.get_memory(session_id) # Use memory for context in routing decisions # For instance, if user prefers 'fast' over 'cheap' based on past interactions # After decision, add current interaction to memory # zep_client.add_messages(session_id, [{'role': 'human', 'content': prompt}, {'role': 'ai', 'content': 'response'}]) return "Decision based on memory and current prompt"
```