Glm4

generate/__init__.py

@@ -29,6 +29,7 @@
     OpenAIImageGenerationParameters,
     QianfanImageGeneration,
     QianfanImageGenerationParameters,
+    ZhipuImageGeneration,
 )
 from generate.text_to_speech import (
     MinimaxProSpeech,
@@ -82,6 +83,7 @@
     'BaiduImageGenerationParameters',
     'QianfanImageGeneration',
     'QianfanImageGenerationParameters',
+    'ZhipuImageGeneration',
     'function',
     'load_chat_model',
     'load_speech_model',

generate/access_token_manager.py

@@ -7,15 +7,15 @@ class AccessTokenManager(ABC):
     _token: Optional[str] = None
     _token_expires_at: datetime
 
-    def __init__(self, token_refresh_days: int = 1) -> None:
+    def __init__(self, token_refresh_seconds: int = 24 * 60 * 60) -> None:
         self._token = None
-        self.token_refresh_days = token_refresh_days
+        self.token_refresh_seconds = token_refresh_seconds
 
     @property
     def token(self) -> str:
         if self._token is None:
             self._token = self._get_token()
-            self._token_expires_at = datetime.now() + timedelta(days=self.token_refresh_days)
+            self._token_expires_at = datetime.now() + timedelta(seconds=self.token_refresh_seconds)
         else:
             self._maybe_refresh_token()
         return self._token
@@ -27,4 +27,4 @@ def _get_token(self) -> str:
     def _maybe_refresh_token(self) -> None:
         if self._token_expires_at < datetime.now():
             self._token = self._get_token()
-            self._token_expires_at = datetime.now() + timedelta(days=self.token_refresh_days)
+            self._token_expires_at = datetime.now() + timedelta(seconds=self.token_refresh_seconds)

generate/chat_completion/message/core.py

@@ -59,7 +59,7 @@ class FunctionCall(BaseModel):
 
 class ToolCall(BaseModel):
     id: str  # noqa: A003
-    type: Literal['function'] = 'function'  # noqa: A003
+    type: str = 'function'
     function: FunctionCall
 
 

generate/chat_completion/model_output.py

@@ -8,7 +8,7 @@
 from generate.model import ModelOutput
 
 
-class ChatCompletionOutput(ModelOutput, AssistantMessage):
+class ChatCompletionOutput(ModelOutput):
     message: AssistantMessage
     finish_reason: Optional[str] = None
 

generate/chat_completion/models/openai.py

@@ -210,7 +210,7 @@ def calculate_cost(model_name: str, input_tokens: int, output_tokens: int) -> fl
     return None
 
 
-def convert_openai_message_to_generate_message(message: dict[str, Any]) -> AssistantMessage:
+def _convert_to_assistant_message(message: dict[str, Any]) -> AssistantMessage:
     if function_call_dict := message.get('function_call'):
         function_call = FunctionCall(
             name=function_call_dict.get('name') or '',
@@ -236,7 +236,7 @@ def convert_openai_message_to_generate_message(message: dict[str, Any]) -> Assis
 
 
 def parse_openai_model_reponse(response: ResponseValue) -> ChatCompletionOutput:
-    message = convert_openai_message_to_generate_message(response['choices'][0]['message'])
+    message = _convert_to_assistant_message(response['choices'][0]['message'])
     extra = {'usage': response['usage']}
     if system_fingerprint := response.get('system_fingerprint'):
         extra['system_fingerprint'] = system_fingerprint
@@ -263,11 +263,11 @@ def process(self, response: ResponseValue) -> ChatCompletionStreamOutput | None:
         delta_dict = response['choices'][0]['delta']
 
         if self.message is None:
-            self.message = self.process_initial_message(delta_dict)
-            if self.message is None:
-                return None
-        else:
-            self.update_existing_message(delta_dict)
+            if self._is_contains_content(delta_dict):
+                self.message = self.process_initial_message(delta_dict)
+            return None
+
+        self.update_existing_message(delta_dict)
         extra = self.extract_extra_info(response)
         cost = cost = self.calculate_response_cost(response)
         finish_reason = self.determine_finish_reason(response)
@@ -282,14 +282,15 @@ def process(self, response: ResponseValue) -> ChatCompletionStreamOutput | None:
             stream=Stream(delta=delta_dict.get('content') or '', control=stream_control),
         )
 
-    def process_initial_message(self, delta_dict: dict[str, Any]) -> AssistantMessage | None:
-        if (
+    def _is_contains_content(self, delta_dict: dict[str, Any]) -> bool:
+        return not (
             delta_dict.get('content') is None
             and delta_dict.get('tool_calls') is None
             and delta_dict.get('function_call') is None
-        ):
-            return None
-        return convert_openai_message_to_generate_message(delta_dict)
+        )
+
+    def process_initial_message(self, delta_dict: dict[str, Any]) -> AssistantMessage:
+        return _convert_to_assistant_message(delta_dict)
 
     def update_existing_message(self, delta_dict: dict[str, Any]) -> None:
         if not delta_dict:
@@ -302,7 +303,7 @@ def update_existing_message(self, delta_dict: dict[str, Any]) -> None:
         if delta_dict.get('tool_calls'):
             index = delta_dict['tool_calls'][0]['index']
             if index >= len(self.message.tool_calls or []):
-                new_tool_calls_message = convert_openai_message_to_generate_message(delta_dict).tool_calls
+                new_tool_calls_message = _convert_to_assistant_message(delta_dict).tool_calls
                 assert new_tool_calls_message is not None
                 if self.message.tool_calls is None:
                     self.message.tool_calls = []