agentmemory-python / examples /python /observe_and_recall.py
Yash030's picture
Initialize Hugging Face Space deployment for AgentMemory Python (clean without assets)
b2d9e47
"""Observation ingest + context rendering at a token budget.
Pattern: send hook-style observations during a coding session, then ask
agentmemory to render the most relevant context back at a fixed token budget.
Prerequisites:
pip install iii-sdk
npx -y @agentmemory/agentmemory
Run:
python examples/python/observe_and_recall.py
"""
from datetime import datetime, timezone
from iii import register_worker
SESSION_ID = "py-example-session-001"
PROJECT = "demo"
def now_iso() -> str:
return datetime.now(timezone.utc).isoformat()
def main() -> None:
iii = register_worker("ws://localhost:49134")
iii.connect()
observations = [
("PreToolUse", {"tool": "Bash", "command": "cargo test"}),
("PostToolUse", {"tool": "Bash", "exit_code": 0}),
("UserPromptSubmit", {"prompt": "refactor auth middleware to use HMAC"}),
]
for hook_type, data in observations:
iii.trigger(
{
"function_id": "mem::observe",
"payload": {
"hookType": hook_type,
"sessionId": SESSION_ID,
"project": PROJECT,
"cwd": "/home/user/service",
"timestamp": now_iso(),
"data": data,
},
}
)
context = iii.trigger(
{
"function_id": "mem::context",
"payload": {
"sessionId": SESSION_ID,
"project": PROJECT,
"budget": 2000,
},
}
)
print(f"Rendered context ({context.get('token_count', 0)} tokens):\n")
print(context.get("text", ""))
if __name__ == "__main__":
main()