set temperature param on all initialize_llm calls

ra_aid/__main__.py

@@ -368,6 +368,7 @@ def main():
             _global_memory["config"]["model"] = args.model
             _global_memory["config"]["expert_provider"] = args.expert_provider
             _global_memory["config"]["expert_model"] = args.expert_model
+            _global_memory["config"]["temperature"] = args.temperature
 
             # Create chat agent with appropriate tools
             chat_agent = create_agent(
@@ -437,6 +438,9 @@ def main():
         )
         _global_memory["config"]["research_model"] = args.research_model or args.model
 
+        # Store temperature in global config
+        _global_memory["config"]["temperature"] = args.temperature
+
         # Run research stage
         print_stage_header("Research Stage")
 

ra_aid/tools/agent.py

@@ -38,6 +38,7 @@ def request_research(query: str) -> ResearchResult:
     model = initialize_llm(
         config.get("provider", "anthropic"),
         config.get("model", "claude-3-5-sonnet-20241022"),
+        temperature=config.get("temperature"),
     )
 
     # Check recursion depth
@@ -120,6 +121,7 @@ def request_web_research(query: str) -> ResearchResult:
     model = initialize_llm(
         config.get("provider", "anthropic"),
         config.get("model", "claude-3-5-sonnet-20241022"),
+        temperature=config.get("temperature"),
     )
 
     success = True
@@ -188,6 +190,7 @@ def request_research_and_implementation(query: str) -> Dict[str, Any]:
     model = initialize_llm(
         config.get("provider", "anthropic"),
         config.get("model", "claude-3-5-sonnet-20241022"),
+        temperature=config.get("temperature"),
     )
 
     try:
@@ -258,6 +261,7 @@ def request_task_implementation(task_spec: str) -> Dict[str, Any]:
     model = initialize_llm(
         config.get("provider", "anthropic"),
         config.get("model", "claude-3-5-sonnet-20241022"),
+        temperature=config.get("temperature"),
     )
 
     # Get required parameters
@@ -334,6 +338,7 @@ def request_implementation(task_spec: str) -> Dict[str, Any]:
     model = initialize_llm(
         config.get("provider", "anthropic"),
         config.get("model", "claude-3-5-sonnet-20241022"),
+        temperature=config.get("temperature"),
     )
 
     try:

ra_aid/tools/programmer.py

@@ -118,8 +118,6 @@ def run_programming_task(
         # Log the programming task
         log_work_event(f"Executed programming task: {_truncate_for_log(instructions)}")
         
-        print(repr(result))
-        
         # Return structured output
         return {
             "output": truncate_output(result[0].decode()) if result[0] else "",