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speech_to_speech/LLM/tool_call/function_tool.py

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+import textwrap
+
+from openai.types.realtime import RealtimeFunctionTool
+
+from speech_to_speech.LLM.tool_call.signature_from_schema import signature_from_schema
+
+
+class FunctionTool(RealtimeFunctionTool):
+    def to_code_prompt(self, include_args_doc: bool = True) -> str:
+        """Generate a code-style prompt string for this function tool.
+
+        Args:
+            include_args_doc: If True, include argument descriptions in the docstring.
+                ⚠️ This lets the model see each argument's purpose but significantly increases
+                token usage (e.g. 906 tokens without vs 3434 with for the default Reachy Mini
+                tool profile). Enable depending on the model's capabilities and context limit.
+        """
+        signature = signature_from_schema(self.parameters)
+
+        tool_doc = self.description or ""
+
+        if isinstance(self.parameters, dict) and include_args_doc:
+            props = self.parameters.get("properties", {})
+            if props:
+                arg_lines = []
+                for arg_name, arg_schema in props.items():
+                    desc = arg_schema.get("description", "") if isinstance(arg_schema, dict) else ""
+                    arg_lines.append(f"{arg_name}: {desc}")
+                args_doc = f"Args:\n{textwrap.indent(chr(10).join(arg_lines), '    ')}"
+                tool_doc += f"\n\n{args_doc}"
+
+        tool_doc = f'"""{tool_doc}\n"""'
+
+        return f"def {self.name}{signature}:\n{textwrap.indent(tool_doc, '    ')}"