chore(conductor): Mark track 'Simulation Fidelity Enhancement' as complete.

simulation/user_agent.py

@@ -4,9 +4,10 @@ from typing import Any, Callable
 import ai_client
 
 class UserSimAgent:
- def __init__(self, hook_client: Any, model: str = "gemini-2.5-flash-lite") -> None:
+ def __init__(self, hook_client: Any, model: str = "gemini-2.5-flash-lite", enable_delays: bool = True) -> None:
   self.hook_client = hook_client
   self.model = model
+  self.enable_delays = enable_delays
   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. "
@@ -14,26 +15,46 @@ class UserSimAgent:
    "Do not use markdown blocks for your main message unless you are providing code."
   )
 
+ def calculate_reading_delay(self, text: str) -> float:
+  word_count = len(text.split())
+  delay = (word_count / 200.0) * 60.0 * 0.5
+  return max(0.5, min(5.0, delay))
+
+ def wait_to_read(self, text: str) -> None:
+  if self.enable_delays:
+   delay = self.calculate_reading_delay(text)
+   time.sleep(delay)
+
+ def wait_to_think(self, probability: float = 0.2, min_delay: float = 2.0, max_delay: float = 5.0) -> None:
+  if self.enable_delays and random.random() < probability:
+   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 generate_response(self, conversation_history: list[dict]) -> str:
   """
-        Generates a human-like response based on the conversation history.
-        conversation_history: list of dicts with 'role' and 'content'
-        """
-  # Format history for ai_client
-  # ai_client expects md_content and user_message.
-  # It handles its own internal history.
-  # We want the 'User AI' to have context of what the 'Assistant AI' said.
-  # For now, let's just use the last message from Assistant as the prompt.
+  Generates a human-like response based on the conversation history.
+  conversation_history: list of dicts with 'role' and 'content'
+  """
   last_ai_msg = ""
   for entry in reversed(conversation_history):
    if entry.get('role') == 'AI':
     last_ai_msg = entry.get('content', '')
     break
-    # We need to set a custom system prompt for the User Simulator
   try:
    ai_client.set_custom_system_prompt(self.system_prompt)
-   # We'll use a blank md_content for now as the 'User' doesn't need to read its own files 
-   # via the same mechanism, but we could provide it if needed.
    response = ai_client.send(md_content="", user_message=last_ai_msg)
   finally:
    ai_client.set_custom_system_prompt("")
@@ -41,8 +62,9 @@ class UserSimAgent:
 
  def perform_action_with_delay(self, action_func: Callable, *args: Any, **kwargs: Any) -> Any:
   """
-        Executes an action with a human-like delay.
-        """
-  delay = random.uniform(0.5, 2.0)
-  time.sleep(delay)
+  Executes an action with a human-like delay if enabled.
+  """
+  if self.enable_delays:
+   delay = random.uniform(0.5, 2.0)
+   time.sleep(delay)
   return action_func(*args, **kwargs)

simulation/workflow_sim.py

@@ -59,10 +59,12 @@ class WorkflowSimulator:
   active_disc = self.client.get_value("active_discussion")
   print(f"[DEBUG] Current active discussion in GUI: {active_disc}")
   print(f"\n[USER]: {user_message}")
+  self.user_agent.simulate_typing(user_message)
   self.client.set_value("ai_input", user_message)
   self.client.click("btn_gen_send")
 
  def wait_for_ai_response(self, timeout: int = 60) -> dict | None:
+  self.user_agent.wait_to_think(probability=0.1)
   print("Waiting for AI response...", end="", flush=True)
   
   start_time = time.time()
@@ -120,6 +122,7 @@ class WorkflowSimulator:
    if is_complete:
     content = last_ai_entry.get('content', '')
     print(f"\n[AI]: {content[:100]}...")
+    self.user_agent.wait_to_read(content)
     return last_ai_entry
 
    if non_system_entries: