Make inside-module functions private

crab/agents/backend_models/claude_model.py

@@ -62,14 +62,14 @@ def reset(self, system_message: str, action_space: list[Action] | None) -> None:
     def chat(self, message: list[Message] | Message) -> BackendOutput:
         if isinstance(message, tuple):
             message = [message]
-        request = self.fetch_from_memory()
-        new_message = self.construct_new_message(message)
+        request = self._fetch_from_memory()
+        new_message = self._construct_new_message(message)
         request.append(new_message)
-        response_message = self.call_api(request)
-        self.record_message(new_message, response_message)
-        return self.generate_backend_output(response_message)
+        response_message = self._call_api(request)
+        self._record_message(new_message, response_message)
+        return self._generate_backend_output(response_message)
 
-    def construct_new_message(self, message: list[Message]) -> dict[str, Any]:
+    def _construct_new_message(self, message: list[Message]) -> dict[str, Any]:
         parts: list[dict] = []
         for content, msg_type in message:
             match msg_type:
@@ -96,7 +96,7 @@ def construct_new_message(self, message: list[Message]) -> dict[str, Any]:
             "content": parts,
         }
 
-    def fetch_from_memory(self) -> list[dict]:
+    def _fetch_from_memory(self) -> list[dict]:
         request: list[dict] = []
         if self.history_messages_len > 0:
             fetch_history_len = min(self.history_messages_len, len(self.chat_history))
@@ -107,7 +107,7 @@ def fetch_from_memory(self) -> list[dict]:
     def get_token_usage(self):
         return self.token_usage
 
-    def record_message(
+    def _record_message(
         self, new_message: dict, response_message: anthropic.types.Message
     ) -> None:
         self.chat_history.append([new_message])
@@ -145,7 +145,7 @@ def record_message(
             )
         ),
     )
-    def call_api(self, request_messages: list[dict]) -> anthropic.types.Message:
+    def _call_api(self, request_messages: list[dict]) -> anthropic.types.Message:
         request_messages = _merge_request(request_messages)
         if self.action_schema is not None:
             response = self.client.messages.create(
@@ -169,7 +169,7 @@ def call_api(self, request_messages: list[dict]) -> anthropic.types.Message:
         self.token_usage += response.usage.input_tokens + response.usage.output_tokens
         return response
 
-    def generate_backend_output(
+    def _generate_backend_output(
         self, response_message: anthropic.types.Message
     ) -> BackendOutput:
         message = ""

crab/agents/backend_models/gemini_model.py

@@ -71,14 +71,14 @@ def reset(self, system_message: str, action_space: list[Action] | None) -> None:
     def chat(self, message: list[Message] | Message) -> BackendOutput:
         if isinstance(message, tuple):
             message = [message]
-        request = self.fetch_from_memory()
-        new_message = self.construct_new_message(message)
+        request = self._fetch_from_memory()
+        new_message = self._construct_new_message(message)
         request.append(new_message)
-        response_message = self.call_api(request)
-        self.record_message(new_message, response_message)
-        return self.generate_backend_output(response_message)
+        response_message = self._call_api(request)
+        self._record_message(new_message, response_message)
+        return self._generate_backend_output(response_message)
 
-    def construct_new_message(self, message: list[Message]) -> dict[str, Any]:
+    def _construct_new_message(self, message: list[Message]) -> dict[str, Any]:
         parts: list[str | Image] = []
         for content, msg_type in message:
             match msg_type:
@@ -91,7 +91,7 @@ def construct_new_message(self, message: list[Message]) -> dict[str, Any]:
             "parts": parts,
         }
 
-    def generate_backend_output(self, response_message: Content) -> BackendOutput:
+    def _generate_backend_output(self, response_message: Content) -> BackendOutput:
         tool_calls: list[ActionOutput] = []
         for part in response_message.parts:
             if "function_call" in Part.to_dict(part):
@@ -108,7 +108,7 @@ def generate_backend_output(self, response_message: Content) -> BackendOutput:
             action_list=tool_calls or None,
         )
 
-    def fetch_from_memory(self) -> list[dict]:
+    def _fetch_from_memory(self) -> list[dict]:
         request: list[dict] = []
         if self.history_messages_len > 0:
             fetch_history_len = min(self.history_messages_len, len(self.chat_history))
@@ -119,7 +119,7 @@ def fetch_from_memory(self) -> list[dict]:
     def get_token_usage(self):
         return self.token_usage
 
-    def record_message(
+    def _record_message(
         self, new_message: dict[str, Any], response_message: Content
     ) -> None:
         self.chat_history.append([new_message])
@@ -132,7 +132,7 @@ def record_message(
         stop=stop_after_attempt(7),
         retry=retry_if_exception_type(ResourceExhausted),
     )
-    def call_api(self, request_messages: list) -> Content:
+    def _call_api(self, request_messages: list) -> Content:
         if self.action_schema is not None:
             tool_config = content_types.to_tool_config(
                 {

crab/agents/backend_models/openai_model.py

@@ -72,17 +72,17 @@ def reset(self, system_message: str, action_space: list[Action] | None) -> None:
     def chat(self, message: list[Message] | Message) -> BackendOutput:
         if isinstance(message, tuple):
             message = [message]
-        request = self.fetch_from_memory()
-        new_message = self.construct_new_message(message)
+        request = self._fetch_from_memory()
+        new_message = self._construct_new_message(message)
         request.append(new_message)
-        response_message = self.call_api(request)
-        self.record_message(new_message, response_message)
-        return self.generate_backend_output(response_message)
+        response_message = self._call_api(request)
+        self._record_message(new_message, response_message)
+        return self._generate_backend_output(response_message)
 
     def get_token_usage(self):
         return self.token_usage
 
-    def record_message(
+    def _record_message(
         self, new_message: dict, response_message: ChatCompletionMessage
     ) -> None:
         self.chat_history.append([new_message])
@@ -99,7 +99,7 @@ def record_message(
                     }
                 )  # extend conversation with function response
 
-    def call_api(
+    def _call_api(
         self, request_messages: list[ChatCompletionMessage | dict]
     ) -> ChatCompletionMessage:
         if self.action_schema is not None:
@@ -120,15 +120,15 @@ def call_api(
         self.token_usage += response.usage.total_tokens
         return response.choices[0].message
 
-    def fetch_from_memory(self) -> list[ChatCompletionMessage | dict]:
+    def _fetch_from_memory(self) -> list[ChatCompletionMessage | dict]:
         request: list[ChatCompletionMessage | dict] = [self.openai_system_message]
         if self.history_messages_len > 0:
             fetch_history_len = min(self.history_messages_len, len(self.chat_history))
             for history_message in self.chat_history[-fetch_history_len:]:
                 request = request + history_message
         return request
 
-    def construct_new_message(self, message: list[Message]) -> dict[str, Any]:
+    def _construct_new_message(self, message: list[Message]) -> dict[str, Any]:
         new_message_content: list[dict[str, Any]] = []
         for content, msg_type in message:
             match msg_type:
@@ -152,7 +152,7 @@ def construct_new_message(self, message: list[Message]) -> dict[str, Any]:
 
         return {"role": "user", "content": new_message_content}
 
-    def generate_backend_output(
+    def _generate_backend_output(
         self, response_message: ChatCompletionMessage
     ) -> BackendOutput:
         if response_message.tool_calls is None:
@@ -205,15 +205,15 @@ def reset(self, system_message: str, action_space: list[Action] | None) -> None:
         super().reset(system_message, action_space)
         self.action_schema = None
 
-    def record_message(
+    def _record_message(
         self, new_message: dict, response_message: ChatCompletionMessage
     ) -> None:
         self.chat_history.append([new_message])
         self.chat_history[-1].append(
             {"role": "assistant", "content": response_message.content}
         )
 
-    def generate_backend_output(
+    def _generate_backend_output(
         self, response_message: ChatCompletionMessage
     ) -> BackendOutput:
         content = response_message.content
@@ -240,7 +240,7 @@ def generate_backend_output(
 
 
 class SGlangOpenAIModelJSON(OpenAIModelJSON):
-    def construct_new_message(self, message: list[Message]) -> dict[str, Any]:
+    def _construct_new_message(self, message: list[Message]) -> dict[str, Any]:
         new_message_content: list[dict[str, Any]] = []
         image_count = 0
         for _, msg_type in message: