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"""Background agent worker that autonomously completes tasks."""
import asyncio
import random
from app.database import SessionLocal
from app.models import Task, TaskStatus, Project, AI_AGENT_USER_ID
from app.tools.memory import complete_task
async def agent_loop():
"""Background loop that processes tasks for agent-enabled projects."""
print("[Agent] Worker started, waiting for initial delay...")
# Initial delay to let the server start up
await asyncio.sleep(10)
while True:
try:
await process_one_task()
except Exception as e:
print(f"[Agent] Error: {e}")
# Wait 25-35 seconds (jitter to avoid rate limit patterns)
wait_time = random.uniform(25, 35)
await asyncio.sleep(wait_time)
async def process_one_task():
"""Pick a random todo task from agent-enabled projects and complete it."""
db = SessionLocal()
try:
# Find projects with agent enabled
projects = db.query(Project).filter(Project.agent_enabled == True).all()
if not projects:
return
# Pick random project
project = random.choice(projects)
# Find a random todo task
todo_tasks = db.query(Task).filter(
Task.project_id == project.id,
Task.status == TaskStatus.todo
).all()
if not todo_tasks:
return
task = random.choice(todo_tasks)
print(f"[Agent] Starting task: {task.title}")
# Step 1: Move to in_progress
task.status = TaskStatus.in_progress
task.working_by = AI_AGENT_USER_ID
db.commit()
# Step 2: "Work" on it (small delay for realism)
await asyncio.sleep(random.uniform(2, 5))
# Step 3: Complete the task
result = await complete_task(
task_id=task.id,
project_id=project.id,
user_id=AI_AGENT_USER_ID,
what_i_did=f"Implemented {task.title}. {task.description or 'Completed the task as specified.'}",
actor_type="agent"
)
if result.get("success"):
print(f"[Agent] Completed task: {task.title}")
else:
print(f"[Agent] Failed to complete task: {result.get('error')}")
except Exception as e:
print(f"[Agent] Error in process_one_task: {e}")
db.rollback()
finally:
db.close()
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