Add request_implementation tool.

ra_aid/tool_configs.py

@@ -3,14 +3,13 @@ from ra_aid.tools import (
     ask_expert, ask_human, run_shell_command, run_programming_task,
     emit_research_notes, emit_plan, emit_related_files, emit_task,
     emit_expert_context, emit_key_facts, delete_key_facts,
-    emit_key_snippets, delete_key_snippets, delete_tasks,
-    request_implementation, read_file_tool,
+    emit_key_snippets, delete_key_snippets, delete_tasks, read_file_tool,
     fuzzy_find_project_files, ripgrep_search, list_directory_tree,
     swap_task_order, monorepo_detected, existing_project_detected, ui_detected,
     task_completed, plan_implementation_completed
 )
 from ra_aid.tools.memory import one_shot_completed
-from ra_aid.tools.agent import request_research, request_research_and_implementation, request_task_implementation
+from ra_aid.tools.agent import request_research, request_implementation, request_research_and_implementation, request_task_implementation
 
 # Read-only tools that don't modify system state
 def get_read_only_tools(human_interaction: bool = False) -> list:

ra_aid/tools/agent.py

@@ -167,3 +167,49 @@ def request_task_implementation(task_spec: str) -> Dict[str, Any]:
         "success": success,
         "reason": reason
     }
+
+@tool("request_implementation")
+def request_implementation(task_spec: str) -> Dict[str, Any]:
+    """Spawn a planning agent to create an implementation plan for the given task.
+    
+    Args:
+        task_spec: The task specification to plan implementation for
+        
+    Returns:
+        Dict containing:
+        - facts: Current key facts
+        - files: Related files
+        - success: Whether completed or interrupted
+        - reason: Reason for failure, if any
+    """
+    # Initialize model from config
+    config = _global_memory.get('config', {})
+    model = initialize_llm(config.get('provider', 'anthropic'), config.get('model', 'claude-3-5-sonnet-20241022'))
+    
+    try:
+        # Run planning agent
+        from ..agent_utils import run_planning_agent
+        result = run_planning_agent(
+            task_spec,
+            model,
+            expert_enabled=True,
+            hil=_global_memory.get('config', {}).get('hil', False)
+        )
+        
+        success = True
+        reason = None
+    except KeyboardInterrupt:
+        console.print("\n[yellow]Planning interrupted by user[/yellow]")
+        success = False
+        reason = "cancelled_by_user"
+    except Exception as e:
+        console.print(f"\n[red]Error during planning: {str(e)}[/red]")
+        success = False
+        reason = f"error: {str(e)}"
+        
+    return {
+        "facts": get_memory_value("key_facts"),
+        "files": list(get_related_files()),
+        "success": success,
+        "reason": reason
+    }