Merge branch 'agent_as_a_tool' into '0.4.0'

Agent as a tool

See merge request aliasrobotics/alias_research/cai!169

src/cai/sdk/agents/function_schema.py

@@ -36,7 +36,6 @@ class FuncSchema:
     strict_json_schema: bool = True
     """Whether the JSON schema is in strict mode. We **strongly** recommend setting this to True,
     as it increases the likelihood of correct JSON input."""
-
     def to_call_args(self, data: BaseModel) -> tuple[list[Any], dict[str, Any]]:
         """
         Converts validated data from the Pydantic model into (args, kwargs), suitable for calling
@@ -51,6 +50,10 @@ class FuncSchema:
             # If the function takes a RunContextWrapper and this is the first parameter, skip it.
             if self.takes_context and idx == 0:
                 continue
+                
+            # Skip parameters named 'ctf' or 'CTF'
+            if name.lower() == 'ctf':
+                continue
 
             value = getattr(data, name, None)
             if param.kind == param.VAR_POSITIONAL:

src/cai/sdk/agents/model_settings.py

@@ -43,6 +43,10 @@ class ModelSettings:
     store: bool | None = None
     """Whether to store the generated model response for later retrieval.
     Defaults to True if not provided."""
+    
+    agent_model: str | None = None
+    """The model from the Agent class. If set, this will override the model provided
+    to the OpenAIChatCompletionsModel during initialization."""
 
     def resolve(self, override: ModelSettings | None) -> ModelSettings:
         """Produce a new ModelSettings by overlaying any non-None values from the

src/cai/sdk/agents/models/openai_chatcompletions.py

@@ -1485,9 +1485,16 @@ class OpenAIChatCompletionsModel(Model):
         # Match the behavior of Responses where store is True when not given
         store = model_settings.store if model_settings.store is not None else True
 
+        # Check if we should use the agent's model instead of self.model
+        # This prioritizes the model from Agent when available
+        agent_model = None
+        if hasattr(model_settings, 'agent_model') and model_settings.agent_model:
+            agent_model = model_settings.agent_model
+            logger.debug(f"Using agent model: {agent_model} instead of {self.model}")
+        
         # Prepare kwargs for the API call
         kwargs = {
-            "model": self.model,
+            "model": agent_model if agent_model else self.model,
             "messages": converted_messages,
             "tools": converted_tools or NOT_GIVEN,
             "temperature": self._non_null_or_not_given(model_settings.temperature),
@@ -1505,7 +1512,7 @@ class OpenAIChatCompletionsModel(Model):
         }
 
         # Determine provider based on model string
-        model_str = str(self.model).lower()
+        model_str = str(kwargs["model"]).lower()
         
         # Provider-specific adjustments
         if "/" in model_str:

src/cai/sdk/agents/run.py

@@ -657,6 +657,13 @@ class Runner:
         model = cls._get_model(agent, run_config)
         model_settings = agent.model_settings.resolve(run_config.model_settings)
         model_settings = RunImpl.maybe_reset_tool_choice(agent, tool_use_tracker, model_settings)
+        
+        # Ensure agent model is set in model_settings for streaming mode
+        if not hasattr(model_settings, 'agent_model') or not model_settings.agent_model:
+            if isinstance(agent.model, str):
+                model_settings.agent_model = agent.model
+            elif isinstance(run_config.model, str):
+                model_settings.agent_model = run_config.model
 
         final_response: ModelResponse | None = None
 
@@ -941,6 +948,13 @@ class Runner:
         model_settings = agent.model_settings.resolve(run_config.model_settings)
         model_settings = RunImpl.maybe_reset_tool_choice(agent, tool_use_tracker, model_settings)
 
+        # Ensure agent model is set in model_settings
+        if not hasattr(model_settings, 'agent_model') or not model_settings.agent_model:
+            if isinstance(agent.model, str):
+                model_settings.agent_model = agent.model
+            elif isinstance(run_config.model, str):
+                model_settings.agent_model = run_config.model
+
         new_response = await model.get_response(
             system_instructions=system_prompt,
             input=input,
@@ -981,14 +995,21 @@ class Runner:
     @classmethod
     def _get_model(cls, agent: Agent[Any], run_config: RunConfig) -> Model:
         model = None
+        agent_model = None
         if isinstance(run_config.model, Model):
             model = run_config.model
         elif isinstance(run_config.model, str):
             model = run_config.model_provider.get_model(run_config.model)
+            agent_model = run_config.model
         elif isinstance(agent.model, Model):
             model = agent.model
         else:
             model = run_config.model_provider.get_model(agent.model)
+            agent_model = agent.model
+            
+        # Store the original agent model in model_settings for later use
+        if agent_model and hasattr(agent, 'model_settings'):
+            agent.model_settings.agent_model = agent_model
             
         # Set agent name if the model supports it (for CLI display)
         if hasattr(model, 'set_agent_name'):