added custom_tools support for OpenAI adapters

src/pipecat/adapters/schemas/tools_schema.py

@@ -21,10 +21,12 @@ class AdapterType(Enum):
     """Supported adapter types for custom tools.
 
     Parameters:
-        GEMINI: Google Gemini adapter - currently the only service supporting custom tools.
+        GEMINI: Google Gemini adapter.
+        OPENAI: OpenAI adapter (Chat Completions and Responses API).
     """
 
-    GEMINI = "gemini"  # that is the only service where we are able to add custom tools for now
+    GEMINI = "gemini"
+    OPENAI = "openai"
 
 
 class ToolsSchema:

src/pipecat/adapters/services/open_ai_adapter.py

@@ -17,7 +17,7 @@ from openai.types.chat import (
 )
 
 from pipecat.adapters.base_llm_adapter import BaseLLMAdapter
-from pipecat.adapters.schemas.tools_schema import ToolsSchema
+from pipecat.adapters.schemas.tools_schema import AdapterType, ToolsSchema
 from pipecat.processors.aggregators.llm_context import (
     LLMContext,
     LLMContextMessage,
@@ -96,7 +96,7 @@ class OpenAILLMAdapter(BaseLLMAdapter[OpenAILLMInvocationParams]):
             "tool_choice": context.tool_choice,
         }
 
-    def to_provider_tools_format(self, tools_schema: ToolsSchema) -> List[ChatCompletionToolParam]:
+    def to_provider_tools_format(self, tools_schema: ToolsSchema) -> List[Any]:
         """Convert function schemas to OpenAI's function-calling format.
 
         Args:
@@ -107,10 +107,14 @@ class OpenAILLMAdapter(BaseLLMAdapter[OpenAILLMInvocationParams]):
             with ChatCompletion API.
         """
         functions_schema = tools_schema.standard_tools
-        return [
+        formatted_standard_tools = [
             ChatCompletionToolParam(type="function", function=func.to_default_dict())
             for func in functions_schema
         ]
+        custom_openai_tools = []
+        if tools_schema.custom_tools:
+            custom_openai_tools = tools_schema.custom_tools.get(AdapterType.OPENAI, [])
+        return formatted_standard_tools + custom_openai_tools
 
     def get_messages_for_logging(self, context: LLMContext) -> List[Dict[str, Any]]:
         """Get messages from a universal LLM context in a format ready for logging about OpenAI.

src/pipecat/adapters/services/open_ai_realtime_adapter.py

@@ -15,7 +15,7 @@ from loguru import logger
 
 from pipecat.adapters.base_llm_adapter import BaseLLMAdapter
 from pipecat.adapters.schemas.function_schema import FunctionSchema
-from pipecat.adapters.schemas.tools_schema import ToolsSchema
+from pipecat.adapters.schemas.tools_schema import AdapterType, ToolsSchema
 from pipecat.processors.aggregators.llm_context import LLMContext, LLMContextMessage
 from pipecat.services.openai.realtime import events
 
@@ -236,4 +236,10 @@ class OpenAIRealtimeLLMAdapter(BaseLLMAdapter):
             List of function definitions in OpenAI Realtime format.
         """
         functions_schema = tools_schema.standard_tools
-        return [self._to_openai_realtime_function_format(func) for func in functions_schema]
+        formatted_standard_tools = [
+            self._to_openai_realtime_function_format(func) for func in functions_schema
+        ]
+        custom_openai_tools = []
+        if tools_schema.custom_tools:
+            custom_openai_tools = tools_schema.custom_tools.get(AdapterType.OPENAI, [])
+        return formatted_standard_tools + custom_openai_tools

src/pipecat/adapters/services/open_ai_responses_adapter.py

@@ -13,7 +13,7 @@ from openai._types import NotGiven as OpenAINotGiven
 from openai.types.responses import FunctionToolParam, ResponseInputItemParam
 
 from pipecat.adapters.base_llm_adapter import BaseLLMAdapter
-from pipecat.adapters.schemas.tools_schema import ToolsSchema
+from pipecat.adapters.schemas.tools_schema import AdapterType, ToolsSchema
 from pipecat.processors.aggregators.llm_context import (
     LLMContext,
     LLMContextMessage,
@@ -106,7 +106,7 @@ class OpenAIResponsesLLMAdapter(BaseLLMAdapter[OpenAIResponsesLLMInvocationParam
 
         return params
 
-    def to_provider_tools_format(self, tools_schema: ToolsSchema) -> List[FunctionToolParam]:
+    def to_provider_tools_format(self, tools_schema: ToolsSchema) -> List[Any]:
         """Convert function schemas to Responses API function tool format.
 
         Args:
@@ -128,7 +128,10 @@ class OpenAIResponsesLLMAdapter(BaseLLMAdapter[OpenAIResponsesLLMInvocationParam
             if "description" in d:
                 tool["description"] = d["description"]
             result.append(tool)
-        return result
+        custom_openai_tools = []
+        if tools_schema.custom_tools:
+            custom_openai_tools = tools_schema.custom_tools.get(AdapterType.OPENAI, [])
+        return result + custom_openai_tools
 
     def get_messages_for_logging(self, context: LLMContext) -> List[Dict[str, Any]]:
         """Get messages from context in a format ready for logging.