Session Store

{conv:session_id}:messages     # JSON-encoded list of message dicts
{conv:session_id}:metadata     # JSON-encoded conversation metadata
conv:user:{user_id}:sessions   # sorted set of session_ids, score = timestamp

# pip install valkey
# For serverless or cluster-mode-enabled node-based clusters:
#   from valkey.cluster import ValkeyCluster
# For cluster-mode-disabled node-based clusters:
#   import valkey  (use valkey.Valkey)
import json
import time
import valkey

CONVERSATION_TTL = 30 * 24 * 60 * 60  # 30 days (adjust to your retention policy)

_client = None

def get_client():
    """Lazy client initialization. Never create connections at module level.

    For serverless or cluster-mode-enabled node-based clusters, use
    valkey.cluster.ValkeyCluster instead of valkey.Valkey.

import valkey
from strands import Agent
from strands_valkey_session_manager import ValkeySessionManager

_strands_client = None

def get_strands_client():
    """Lazy client initialization. Never create connections at module level.
    Uses ValkeyCluster for serverless (cluster-mode-enabled).
    For cluster-mode-disabled node-based clusters, use valkey.Valkey instead.
    """
    global _strands_client
    if _strands_client is None:
        _strands_client = valkey.ValkeyCluster(
            host="your-endpoint.serverless.use1.cache.amazonaws.com", port=6379, ssl=True,
            ssl_cert_reqs="required", decode_responses=True,  # in-VPC EKS with real cert verification
            # tunnel/dev alternative: ssl_cert_reqs="none" (skips cert verification; not for production)
        )
    return _strands_client

def create_agent(session_id: str = "user-42") -> Agent:
    client = get_strands_client()
    session_mgr = ValkeySessionManager(session_id=session_id, client=client)
    return Agent(system_prompt="You are a helpful assistant.", session_manager=session_mgr)

# Usage:
# agent = create_agent("user-42")
# response = agent("My name is Alex and I'm building a RAG pipeline.")