Enforce research recursion limit.

ra_aid/agent_utils.py

@@ -37,7 +37,6 @@ from ra_aid.tools.memory import (
     get_memory_value,
     get_related_files,
 )
-from ra_aid.globals import RESEARCH_AGENT_RECURSION_LIMIT
 from ra_aid.tool_configs import get_research_tools
 from ra_aid.prompts import (
     RESEARCH_PROMPT,
@@ -131,7 +130,7 @@ def run_research_agent(
 
     # Display console message if provided
     if console_message:
-        console.print(Panel(Markdown(console_message), title="🔬 Researching"))
+        console.print(Panel(Markdown(console_message), title="🔬 Looking into it..."))
 
     # Run agent with retry logic
     return run_agent_with_retry(agent, prompt, run_config)

ra_aid/globals.py

@@ -1,6 +0,0 @@
-"""
-Global constants and configuration values used across the RA-AID codebase.
-"""
-
-# Maximum recursion depth for research agents to prevent infinite loops
-RESEARCH_AGENT_RECURSION_LIMIT = 100

ra_aid/prompts.py

@@ -340,6 +340,10 @@ Scope and Focus:
 No Speculation:
     - Do not speculate about the purpose of the user’s request. Let the user’s instructions and clarifications guide you.
     - Stick to the facts derived from user input and discovered context from tools.
+    - You will often be delegating user queries to tools. When you do this, be sure to faithfully represent the user's intent and do not simplify or leave out any information from their original query.
+      - Sometimes you will have to do multiple research or implementation steps, along with asking the user in some cases, to fulfill the query.
+        - It's always better to research and clarify first.
+        - It's good practice to interview the user, perform one-off research tasks, before finally creating a highly detailed implementation plan which will be delegated to the request_research_and_implementation tool.
 
 Exit Criteria:
     - The conversation ends only when the user confirms that no further actions are needed.

ra_aid/tools/agent.py

@@ -1,19 +1,27 @@
 """Tools for spawning and managing sub-agents."""
 
 from langchain_core.tools import tool
-from typing import Dict, Any
+from typing import Dict, Any, Union, List
+from typing_extensions import TypeAlias
+
+ResearchResult = Dict[str, Union[str, bool, Dict[int, Any], List[Any], None]]
 from rich.console import Console
 from ra_aid.tools.memory import _global_memory
 from .memory import get_memory_value, get_related_files
 from ..llm import initialize_llm
 from ..console import print_task_header
 
+RESEARCH_AGENT_RECURSION_LIMIT = 2
+
 console = Console()
 
 @tool("request_research")
-def request_research(query: str) -> Dict[str, Any]:
+def request_research(query: str) -> ResearchResult:
     """Spawn a research-only agent to investigate the given query.
-    
+
+    This function creates a new research agent to investigate the given query. It includes 
+    recursion depth limiting to prevent infinite recursive research calls.
+
     Args:
         query: The research question or project description
     """
@@ -21,7 +29,27 @@ def request_research(query: str) -> Dict[str, Any]:
     config = _global_memory.get('config', {})
     model = initialize_llm(config.get('provider', 'anthropic'), config.get('model', 'claude-3-5-sonnet-20241022'))
     
+    # Check recursion depth
+    current_depth = _global_memory.get('research_depth', 0)
+    if current_depth >= RESEARCH_AGENT_RECURSION_LIMIT:
+        console.print("\n[red]Maximum research recursion depth reached[/red]")
+        return {
+            "completion_message": "Research stopped - maximum recursion depth reached",
+            "key_facts": get_memory_value("key_facts"),
+            "related_files": list(get_related_files()),
+            "research_notes": get_memory_value("research_notes"),
+            "key_snippets": get_memory_value("key_snippets"),
+            "success": False,
+            "reason": "max_depth_exceeded"
+        }
+
+    success = True
+    reason = None
+    
     try:
+        # Increment depth counter
+        _global_memory['research_depth'] = current_depth + 1
+        
         # Run research agent
         from ..agent_utils import run_research_agent
         result = run_research_agent(
@@ -32,9 +60,6 @@ def request_research(query: str) -> Dict[str, Any]:
             hil=config.get('hil', False),
             console_message=query
         )
-        
-        success = True
-        reason = None
     except KeyboardInterrupt:
         console.print("\n[yellow]Research interrupted by user[/yellow]")
         success = False
@@ -43,6 +68,9 @@ def request_research(query: str) -> Dict[str, Any]:
         console.print(f"\n[red]Error during research: {str(e)}[/red]")
         success = False
         reason = f"error: {str(e)}"
+    finally:
+        # Always decrement depth counter
+        _global_memory['research_depth'] = current_depth
         
     # Get completion message if available
     completion_message = _global_memory.get('completion_message', 'Task was completed successfully.' if success else None)

ra_aid/tools/memory.py

@@ -15,7 +15,7 @@ class SnippetInfo(TypedDict):
 console = Console()
 
 # Global memory store
-_global_memory: Dict[str, Union[List[Any], Dict[int, str], Dict[int, SnippetInfo], int, Set[str], bool, str]] = {
+_global_memory: Dict[str, Union[List[Any], Dict[int, str], Dict[int, SnippetInfo], int, Set[str], bool, str, int]] = {
     'research_notes': [],
     'plans': [],
     'tasks': {},  # Dict[int, str] - ID to task mapping
@@ -28,7 +28,8 @@ _global_memory: Dict[str, Union[List[Any], Dict[int, str], Dict[int, SnippetInfo
     'key_snippet_id_counter': 0,  # Counter for generating unique snippet IDs
     'implementation_requested': False,
     'related_files': set(),
-    'plan_completed': False
+    'plan_completed': False,
+    'research_depth': 0
 }
 
 @tool("emit_research_notes")