chore(mma): Implement visual simulation for Epic planning and fix UI refresh

ai_client.py

@@ -1614,17 +1614,23 @@ def run_tier4_analysis(stderr: str) -> str:
   return f"[QA ANALYSIS FAILED] {e}"
   # ------------------------------------------------------------------ unified send
 
+import json
+from typing import Any, Callable, Optional, List
+
+# Assuming _model, _system_prompt, _provider, _send_lock are module-level variables
+# and the _send_xxx functions are also defined at module level.
+
 def send(
- md_content: str,
- user_message: str,
- base_dir: str = ".",
- file_items: list[dict[str, Any]] | None = None,
- discussion_history: str = "",
- stream: bool = False,
- pre_tool_callback: Optional[Callable[[str], bool]] = None,
- qa_callback: Optional[Callable[[str], str]] = None,
+    md_content: str,
+    user_message: str,
+    base_dir: str = ".",
+    file_items: list[dict[str, Any]] | None = None,
+    discussion_history: str = "",
+    stream: bool = False,
+    pre_tool_callback: Optional[Callable[[str], bool]] = None,
+    qa_callback: Optional[Callable[[str], str]] = None,
 ) -> str:
- """
+    """
     Send a message to the active provider.
 
     md_content         : aggregated markdown string (for Gemini: stable content only,
@@ -1639,16 +1645,72 @@ def send(
     pre_tool_callback  : Optional callback (payload: str) -> bool called before tool execution
     qa_callback        : Optional callback (stderr: str) -> str called for Tier 4 error analysis
     """
- with _send_lock:
-  if _provider == "gemini":
-   return _send_gemini(md_content, user_message, base_dir, file_items, discussion_history, pre_tool_callback, qa_callback)
-  elif _provider == "gemini_cli":
-   return _send_gemini_cli(md_content, user_message, base_dir, file_items, discussion_history, pre_tool_callback, qa_callback)
-  elif _provider == "anthropic":
-   return _send_anthropic(md_content, user_message, base_dir, file_items, discussion_history, pre_tool_callback, qa_callback)
-  elif _provider == "deepseek":
-   return _send_deepseek(md_content, user_message, base_dir, file_items, discussion_history, stream=stream, pre_tool_callback=pre_tool_callback, qa_callback=qa_callback)
-  raise ValueError(f"unknown provider: {_provider}")
+    # --- START MOCK LOGIC ---
+    # Assuming _model, _custom_system_prompt, and _system_prompt are module-level variables.
+    # If _model is not 'mock', proceed to original provider logic.
+    if _model == 'mock':
+        mock_response_content = None
+        # Use _custom_system_prompt for keyword detection
+        current_system_prompt = _custom_system_prompt # Assuming _custom_system_prompt is accessible and defined
+
+        if 'tier1_epic_init' in current_system_prompt:
+            mock_response_content = [
+                {
+                    "id": "mock-track-1",
+                    "type": "epic",
+                    "module": "conductor",
+                    "persona": "Tier 1 Orchestrator",
+                    "severity": "high",
+                    "goal": "Initialize a new track.",
+                    "acceptance_criteria": "Track created successfully with required fields."
+                },
+                {
+                    "id": "mock-track-2",
+                    "type": "epic",
+                    "module": "conductor",
+                    "persona": "Tier 1 Orchestrator",
+                    "severity": "medium",
+                    "goal": "Initialize another track.",
+                    "acceptance_criteria": "Second track created successfully."
+                }
+            ]
+        elif 'tier2_sprint_planning' in current_system_prompt:
+            mock_response_content = [
+                {
+                    "id": "mock-ticket-1",
+                    "type": "story",
+                    "goal": "Implement feature X.",
+                    "target_file": "src/feature_x.py",
+                    "depends_on": [],
+                    "context_requirements": ["requirements.txt", "main.py"]
+                },
+                {
+                    "id": "mock-ticket-2",
+                    "type": "bug",
+                    "goal": "Fix bug Y.",
+                    "target_file": "src/bug_y.py",
+                    "depends_on": ["mock-ticket-1"],
+                    "context_requirements": ["tests/test_bug_y.py"]
+                }
+            ]
+        else:
+            mock_response_content = "Mock AI Response"
+        
+        # The function is typed to return 'str', so we return a JSON string.
+        # Ensure 'json' is imported at the module level.
+        return json.dumps(mock_response_content)
+    # --- END MOCK LOGIC ---
+
+    with _send_lock:
+        if _provider == "gemini":
+            return _send_gemini(md_content, user_message, base_dir, file_items, discussion_history, pre_tool_callback, qa_callback)
+        elif _provider == "gemini_cli":
+            return _send_gemini_cli(md_content, user_message, base_dir, file_items, discussion_history, pre_tool_callback, qa_callback)
+        elif _provider == "anthropic":
+            return _send_anthropic(md_content, user_message, base_dir, file_items, discussion_history, pre_tool_callback, qa_callback)
+        elif _provider == "deepseek":
+            return _send_deepseek(md_content, user_message, base_dir, file_items, discussion_history, stream=stream, pre_tool_callback=pre_tool_callback, qa_callback=qa_callback)
+        raise ValueError(f"unknown provider: {_provider}")
 
 def get_history_bleed_stats(md_content: str | None = None) -> dict[str, Any]:
  """