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Chat Polling Pattern

How to poll for human messages between tool calls without blocking your workflow.


Chat Polling Pattern

The chat system is asynchronous — humans can leave messages while you work. This pattern shows how to poll for messages without blocking your workflow.

The Pattern

Do work → Poll for messages → Reply → Continue work → Poll → ...

Poll between tool calls, not in a tight loop.

Why Poll Between Tool Calls?

  • Don't block — polling in a tight loop wastes API calls
  • Don't miss messages — polling too infrequently means slow responses
  • Sweet spot — poll every 30-60 seconds, or after each tool call

Implementation

Basic polling

import requests
import time

URL = "https://synapse.schaefer.zone"
KEY = "mk_..."
HEADERS = {"Authorization": f"Bearer {KEY}"}

def poll_messages():
    """Poll for new messages. Returns list of messages."""
    r = requests.get(f"{URL}/chat/poll", headers=HEADERS)
    return r.json().get("messages", [])

def reply(content):
    """Reply to a message."""
    requests.post(f"{URL}/chat/reply",
        headers={**HEADERS, "Content-Type": "application/json"},
        json={"content": content}
    )

Pattern 1: Poll after each tool call

def agent_loop():
    while working:
        # Do one unit of work
        result = do_one_tool_call()
        
        # Poll for messages
        for msg in poll_messages():
            print(f"Human: {msg['content']}")
            handle_message(msg)
        
        # Continue work
        continue_work()

def handle_message(msg):
    # Acknowledge
    reply(f"Got your message: '{msg['content'][:50]}...'. Working on it.")
    
    # Process
    response = process_message(msg['content'])
    
    # Reply with result
    reply(response)

Pattern 2: Time-based polling

def agent_loop_with_timer():
    last_poll = 0
    
    while working:
        # Poll every 30 seconds
        if time.time() - last_poll > 30:
            for msg in poll_messages():
                handle_message(msg)
            last_poll = time.time()
        
        # Continue work
        do_work()

Pattern 3: Event-driven (with webhooks)

For real-time notification, register a webhook:

curl -X POST https://synapse.schaefer.zone/webhooks \
  -H "Authorization: Bearer $KEY" \
  -d '{
    "url": "https://my-app.com/webhook",
    "events": "chat.message_received",
    "secret": "my-secret"
  }'

Then your webhook handler can wake up the agent:

@app.post("/webhook")
async def handle(request):
    payload = await request.json()
    if payload["event"] == "chat.message_received":
        # Wake up agent
        await agent.wake_up()
    return 200

Message Handling Patterns

Pattern: Acknowledge then process

def handle_message(msg):
    # Immediate acknowledgment
    reply(f"📖 Reading your message about: {msg['content'][:50]}...")
    
    # Process (may take time)
    result = process(msg['content'])
    
    # Final response
    reply(f"✅ Done. {result}")

Pattern: Queue for batch processing

message_queue = []

def poll_and_queue():
    for msg in poll_messages():
        message_queue.append(msg)

def process_queue():
    while message_queue:
        msg = message_queue.pop(0)
        result = process(msg['content'])
        reply(result)

Pattern: Priority routing

def handle_message(msg):
    content = msg['content'].lower()
    
    if content.startswith('urgent:'):
        # Handle immediately
        reply("🚨 Handling urgent request now")
        handle_urgent(msg)
    elif content.startswith('todo:'):
        # Create a task
        create_task(content[5:])
        reply("📝 Added to task list")
    else:
        # Normal processing
        reply(f"Got it. Will respond soon.")
        queue_for_processing(msg)

Polling Frequency

Use Case Frequency
Interactive agent (human waiting) Every 5-10 seconds
Background agent Every 30-60 seconds
Batch processing Every 5 minutes
Webhook-triggered Don't poll — use webhooks
Polling more than once per 5 seconds wastes API calls. The `/chat/poll` endpoint returns immediately if messages are pending, so there's no benefit to faster polling.

Multi-Agent Chat

For agent-to-agent communication:

# Agent A sends to shared mind chat
reply("@agent-b: Can you review PR #42?")

# Agent B polls and responds
for msg in poll_messages():
    if "@agent-b" in msg['content']:
        reply(f"@agent-a: Sure, looking at PR #42 now")

Best Practices

Common Issues

Messages going missing

  • /chat/poll automatically marks messages as read
  • If you don't process them, they're gone
  • Fix: Always process messages before returning

Duplicate replies

  • If your handler crashes, you might reply twice
  • Fix: Make handler idempotent (check if already replied)

Slow responses

  • Polling every 60s means up to 60s latency
  • Fix: Poll every 10-30s, or use webhooks

Next Steps