perf(core): Optimize DAG engine, orchestrator loop, and simulations

simulation/user_agent.py

@@ -4,10 +4,11 @@ from typing import Any, Callable
 from src import ai_client
 
 class UserSimAgent:
- def __init__(self, hook_client: Any, model: str = "gemini-2.5-flash-lite", enable_delays: bool = True) -> None:
+ def __init__(self, hook_client: Any, model: str = "gemini-2.5-flash-lite", enable_delays: bool = True, batch_typing: bool = False) -> None:
   self.hook_client = hook_client
   self.model = model
   self.enable_delays = enable_delays
+  self.batch_typing = batch_typing
   self.system_prompt = (
    "You are a software engineer testing an AI coding assistant called 'Manual Slop'. "
    "You want to build a small Python project and verify the assistant's capabilities. "
@@ -30,18 +31,22 @@ class UserSimAgent:
    delay = random.uniform(min_delay, max_delay)
    time.sleep(delay)
 
- def simulate_typing(self, text: str, jitter_range: tuple[float, float] = (0.01, 0.05)) -> None:
-  if self.enable_delays:
-   # Simulate typing by sleeping after chunks or characters to balance speed and realism
-   if len(text) > 200:
-    for i in range(0, len(text), 10):
-     time.sleep(random.uniform(jitter_range[0] * 3, jitter_range[1] * 3))
-   elif len(text) > 50:
-    for i in range(0, len(text), 3):
-     time.sleep(random.uniform(jitter_range[0] * 1.5, jitter_range[1] * 1.5))
-   else:
-    for char in text:
-     time.sleep(random.uniform(jitter_range[0], jitter_range[1]))
+ def simulate_typing(self, text: str, jitter_range: tuple[float, float] = (0.01, 0.05), batch_typing: bool = False) -> None:
+  if not self.enable_delays:
+   return
+  if batch_typing or self.batch_typing:
+   time.sleep(0.01)
+   return
+  # Simulate typing by sleeping after chunks or characters to balance speed and realism
+  if len(text) > 200:
+   for i in range(0, len(text), 10):
+    time.sleep(random.uniform(jitter_range[0] * 3, jitter_range[1] * 3))
+  elif len(text) > 50:
+   for i in range(0, len(text), 3):
+    time.sleep(random.uniform(jitter_range[0] * 1.5, jitter_range[1] * 1.5))
+  else:
+   for char in text:
+    time.sleep(random.uniform(jitter_range[0], jitter_range[1]))
 
  def generate_response(self, conversation_history: list[dict]) -> str:
   """