feat(main.py): import models_params and set default temperature for models that support it to improve user experience

fix(ciayn_agent.py): update fallback tool error messages to use FallbackToolExecutionError for better error handling
fix(config.py): remove unnecessary blank line to maintain code style consistency
fix(fallback_handler.py): raise FallbackToolExecutionError for better error clarity when tools are not found
fix(llm.py): set default temperature to 0.7 and notify user when not provided for models that support it
test(test_llm.py): update tests to check for default temperature behavior and improve error messages for unsupported providers

ra_aid/__main__.py

@@ -8,6 +8,7 @@ from langgraph.checkpoint.memory import MemorySaver
 from rich.console import Console
 from rich.panel import Panel
 from rich.text import Text
+from ra_aid.models_params import models_params
 
 from ra_aid import print_error, print_stage_header
 from ra_aid.__version__ import __version__
@@ -23,10 +24,12 @@ from ra_aid.config import (
     DEFAULT_RECURSION_LIMIT,
     VALID_PROVIDERS,
 )
+from ra_aid.console.output import cpm
 from ra_aid.dependencies import check_dependencies
 from ra_aid.env import validate_environment
 from ra_aid.llm import initialize_llm
 from ra_aid.logging_config import get_logger, setup_logging
+from ra_aid.models_params import DEFAULT_TEMPERATURE
 from ra_aid.project_info import format_project_info, get_project_info
 from ra_aid.prompts import CHAT_PROMPT, WEB_RESEARCH_PROMPT_SECTION_CHAT
 from ra_aid.tool_configs import get_chat_tools
@@ -309,7 +312,6 @@ def main():
         logger.debug("Environment validation successful")
 
         # Validate model configuration early
-        from ra_aid.models_params import models_params
 
         model_config = models_params.get(args.provider, {}).get(args.model or "", {})
         supports_temperature = model_config.get(
@@ -321,10 +323,10 @@ def main():
         if supports_temperature and args.temperature is None:
             args.temperature = model_config.get("default_temperature")
             if args.temperature is None:
-                print_error(
+                cpm(
-                    f"Temperature must be provided for model {args.model} which supports temperature"
+                    f"This model supports temperature argument but none was given. Setting default temperature to {DEFAULT_TEMPERATURE}."
                 )
-                sys.exit(1)
+                args.temperature = DEFAULT_TEMPERATURE
             logger.debug(
                 f"Using default temperature {args.temperature} for model {args.model}"
             )

ra_aid/agents/ciayn_agent.py

@@ -143,8 +143,6 @@ class CiaynAgent:
             if code.endswith("```"):
                 code = code[:-3].strip()
 
-            # logger.debug(f"_execute_tool: stripped code: {code}")
-
             # if the eval fails, try to extract it via a model call
             if validate_function_call_pattern(code):
                 functions_list = "\n\n".join(self.available_functions)
@@ -176,8 +174,8 @@ class CiaynAgent:
         msg = f"Fallback tool handler has triggered after consecutive failed tool calls reached {DEFAULT_MAX_TOOL_FAILURES} failures.\n"
         # Passing the fallback raw invocation may confuse our llm, as invocation methods may differ.
         # msg += f"<fallback llm raw invocation>{fallback_response[0]}</fallback llm raw invocation>\n"
-        msg += f"<fallback tool name>{e.tool_name}</fallback tool name>"
+        msg += f"<fallback tool name>{e.tool_name}</fallback tool name>\n"
-        msg += f"<fallback tool call result>{fallback_response[1]}</fallback tool call result>"
+        msg += f"<fallback tool call result>\n{fallback_response[1]}\n</fallback tool call result>\n"
         return msg
 
     def _create_agent_chunk(self, content: str) -> Dict[str, Any]:

ra_aid/config.py

@@ -6,6 +6,7 @@ DEFAULT_MAX_TOOL_FAILURES = 3
 FALLBACK_TOOL_MODEL_LIMIT = 5
 RETRY_FALLBACK_COUNT = 3
 
+
 VALID_PROVIDERS = [
     "anthropic",
     "openai",

ra_aid/fallback_handler.py

@@ -349,7 +349,7 @@ class FallbackHandler:
         ):
             return self.current_tool_to_bind.invoke(arguments)
         else:
-            raise Exception(f"Tool '{name}' not found in available tools.")
+            raise FallbackToolExecutionError(f"Tool '{name}' not found in available tools.")
 
     def base_message_to_tool_call_dict(self, response: BaseMessage):
         """
@@ -365,7 +365,7 @@ class FallbackHandler:
         tool_calls = self.get_tool_calls(response)
 
         if not tool_calls:
-            raise Exception(
+            raise FallbackToolExecutionError(
                 f"Could not extract tool_call_dict from response: {response}"
             )
 

ra_aid/llm.py

@@ -9,6 +9,7 @@ from langchain_openai import ChatOpenAI
 from openai import OpenAI
 
 from ra_aid.chat_models.deepseek_chat import ChatDeepseekReasoner
+from ra_aid.console.output import cpm
 from ra_aid.logging_config import get_logger
 
 from .models_params import models_params
@@ -228,8 +229,9 @@ def create_llm_client(
         temp_kwargs = {"temperature": 0} if supports_temperature else {}
     elif supports_temperature:
         if temperature is None:
-            raise ValueError(
+            temperature = 0.7
-                f"Temperature must be provided for model {model_name} which supports temperature"
+            cpm(
+                "This model supports temperature argument but none was given. Setting default temperature to 0.7."
             )
         temp_kwargs = {"temperature": temperature}
     else:

tests/ra_aid/test_llm.py

@@ -237,7 +237,7 @@ def test_initialize_openai_compatible(clean_env, mock_openai):
 
 def test_initialize_unsupported_provider(clean_env):
     """Test initialization with unsupported provider raises ValueError"""
-    with pytest.raises(ValueError, match=r"Unsupported provider: unknown"):
+    with pytest.raises(ValueError, match=r"Missing required environment variable for provider: unknown"):
         initialize_llm("unknown", "model")
 
 
@@ -259,15 +259,33 @@ def test_temperature_defaults(clean_env, mock_openai, mock_anthropic, mock_gemin
         max_retries=5,
     )
 
-    # Test error when no temperature provided for models that support it
+    # Test default temperature when none is provided for models that support it
-    with pytest.raises(ValueError, match="Temperature must be provided for model"):
+    initialize_llm("openai", "test-model")
-        initialize_llm("openai", "test-model")
+    mock_openai.assert_called_with(
+        api_key="test-key",
+        model="test-model",
+        temperature=0.7,
+        timeout=180,
+        max_retries=5,
+    )
 
-    with pytest.raises(ValueError, match="Temperature must be provided for model"):
+    initialize_llm("anthropic", "test-model")
-        initialize_llm("anthropic", "test-model")
+    mock_anthropic.assert_called_with(
+        api_key="test-key",
+        model_name="test-model",
+        temperature=0.7,
+        timeout=180,
+        max_retries=5,
+    )
 
-    with pytest.raises(ValueError, match="Temperature must be provided for model"):
+    initialize_llm("gemini", "test-model")
-        initialize_llm("gemini", "test-model")
+    mock_gemini.assert_called_with(
+        api_key="test-key",
+        model="test-model",
+        temperature=0.7,
+        timeout=180,
+        max_retries=5,
+    )
 
     # Test expert models don't require temperature
     initialize_expert_llm("openai", "o1")