Adjustments to get smaller agent models working better.

ra_aid/__main__.py

@@ -1,6 +1,7 @@
 import argparse
 import sys
 import uuid
+from datetime import datetime
 from rich.panel import Panel
 from rich.console import Console
 from langgraph.checkpoint.memory import MemorySaver
@@ -191,6 +192,10 @@ def main():
             # Get initial request from user
             initial_request = ask_human.invoke({"question": "What would you like help with?"})
 
+            # Get working directory and current date
+            working_directory = os.getcwd()
+            current_date = datetime.now().strftime("%Y-%m-%d")
+
             # Run chat agent with CHAT_PROMPT
             config = {
                 "configurable": {"thread_id": uuid.uuid4()},
@@ -219,7 +224,9 @@ def main():
             # Run chat agent and exit
             run_agent_with_retry(chat_agent, CHAT_PROMPT.format(
                     initial_request=initial_request,
-                    web_research_section=WEB_RESEARCH_PROMPT_SECTION_CHAT if web_research_enabled else ""
+                    web_research_section=WEB_RESEARCH_PROMPT_SECTION_CHAT if web_research_enabled else "",
+                    working_directory=working_directory,
+                    current_date=current_date
                 ), config)
             return
 

ra_aid/agent_utils.py

@@ -569,7 +569,12 @@ def run_agent_with_retry(agent, prompt: str, config: dict) -> Optional[str]:
                         logger.debug("Agent output: %s", chunk)
                         check_interrupt()
                         print_agent_output(chunk)
-                        if _global_memory['task_completed']:
+                        if _global_memory['plan_completed']:
+                            _global_memory['plan_completed'] = False
+                            _global_memory['task_completed'] = False
+                            _global_memory['completion_message'] = ''
+                            break
+                        if _global_memory['task_completed'] or _global_memory['plan_completed']:
                             _global_memory['task_completed'] = False
                             _global_memory['completion_message'] = ''
                             break

ra_aid/agents/ciayn_agent.py

@@ -91,6 +91,7 @@ Start by asking the user what they want.
 </agent instructions>
 
 You must carefully review the conversation history, which functions were called so far, returned results, etc., and make sure the very next function call you make makes sense in order to achieve the original goal.
+You must achieve the goal in as few steps possible, but no fewer.
 
 You must ONLY use ONE of the following functions (these are the ONLY functions that exist):
 

ra_aid/llm.py

@@ -39,6 +39,7 @@ def initialize_llm(provider: str, model_name: str) -> BaseChatModel:
         return ChatOpenAI(
             api_key=os.getenv("OPENAI_API_KEY"),
             base_url=os.getenv("OPENAI_API_BASE"),
+            temperature=0.3,
             model=model_name,
         )
     else:

ra_aid/prompts.py

@@ -557,7 +557,8 @@ NEVER ANNOUNCE WHAT YOU ARE DOING, JUST DO IT!
 """
 
 # New agentic chat prompt for interactive mode
-CHAT_PROMPT = """
+CHAT_PROMPT = """Working Directory: {working_directory}
+Current Date: {current_date}
 Agentic Chat Mode Instructions:
 
 Overview: