TypeError: 'ellipsis' object is not iterable

[istvancsabakis]

Steps to Reproduce:

from langchain.chat_models import init_chat_model
from langchain_core.prompts import ChatPromptTemplate
from langchain_core.output_parsers.string import StrOutputParser

llm = init_chat_model(model="gemini-1.5-flash")
llm.invoke('...')

Expected Behavior:

Return an AIMessage

Actual Behavior (Error):

---------------------------------------------------------------------------
TypeError                                 Traceback (most recent call last)
Cell In[19], line 1
----> 1 llm.invoke('...')

File /venv/lib/python3.12/site-packages/langchain_core/language_models/chat_models.py:307, in BaseChatModel.invoke(self, input, config, stop, **kwargs)
    296 def invoke(
    297     self,
    298     input: LanguageModelInput,
   (...)    302     **kwargs: Any,
    303 ) -> BaseMessage:
    304     config = ensure_config(config)
    305     return cast(
    306         ChatGeneration,
--> 307         self.generate_prompt(
    308             [self._convert_input(input)],
    309             stop=stop,
    310             callbacks=config.get("callbacks"),
    311             tags=config.get("tags"),
    312             metadata=config.get("metadata"),
    313             run_name=config.get("run_name"),
    314             run_id=config.pop("run_id", None),
    315             **kwargs,
    316         ).generations[0][0],
    317     ).message

File /venv/lib/python3.12/site-packages/langchain_core/language_models/chat_models.py:843, in BaseChatModel.generate_prompt(self, prompts, stop, callbacks, **kwargs)
    835 def generate_prompt(
    836     self,
    837     prompts: list[PromptValue],
   (...)    840     **kwargs: Any,
    841 ) -> LLMResult:
    842     prompt_messages = [p.to_messages() for p in prompts]
--> 843     return self.generate(prompt_messages, stop=stop, callbacks=callbacks, **kwargs)

File /venv/lib/python3.12/site-packages/langchain_core/language_models/chat_models.py:683, in BaseChatModel.generate(self, messages, stop, callbacks, tags, metadata, run_name, run_id, **kwargs)
    680 for i, m in enumerate(messages):
    681     try:
    682         results.append(
--> 683             self._generate_with_cache(
    684                 m,
    685                 stop=stop,
    686                 run_manager=run_managers[i] if run_managers else None,
    687                 **kwargs,
    688             )
    689         )
    690     except BaseException as e:
    691         if run_managers:

File /venv/lib/python3.12/site-packages/langchain_core/language_models/chat_models.py:908, in BaseChatModel._generate_with_cache(self, messages, stop, run_manager, **kwargs)
    906 else:
    907     if inspect.signature(self._generate).parameters.get("run_manager"):
--> 908         result = self._generate(
    909             messages, stop=stop, run_manager=run_manager, **kwargs
    910         )
    911     else:
    912         result = self._generate(messages, stop=stop, **kwargs)

File /venv/lib/python3.12/site-packages/langchain_google_vertexai/chat_models.py:1286, in ChatVertexAI._generate(self, messages, stop, run_manager, stream, **kwargs)
   1284 if not self._is_gemini_model:
   1285     return self._generate_non_gemini(messages, stop=stop, **kwargs)
-> 1286 return self._generate_gemini(
   1287     messages=messages,
   1288     stop=stop,
   1289     run_manager=run_manager,
   1290     is_gemini=True,
   1291     **kwargs,
   1292 )

File /venv/lib/python3.12/site-packages/langchain_google_vertexai/chat_models.py:1521, in ChatVertexAI._generate_gemini(self, messages, stop, run_manager, **kwargs)
   1514 def _generate_gemini(
   1515     self,
   1516     messages: List[BaseMessage],
   (...)   1519     **kwargs: Any,
   1520 ) -> ChatResult:
-> 1521     request = self._prepare_request_gemini(messages=messages, stop=stop, **kwargs)
   1522     response = _completion_with_retry(
   1523         self.prediction_client.generate_content,
   1524         max_retries=self.max_retries,
   (...)   1527         **kwargs,
   1528     )
   1529     return self._gemini_response_to_chat_result(response)

File /venv/lib/python3.12/site-packages/langchain_google_vertexai/chat_models.py:1376, in ChatVertexAI._prepare_request_gemini(self, messages, stop, stream, tools, functions, tool_config, safety_settings, cached_content, tool_choice, logprobs, **kwargs)
   1361 def _prepare_request_gemini(
   1362     self,
   1363     messages: List[BaseMessage],
   (...)   1374     **kwargs,
   1375 ) -> Union[v1GenerateContentRequest, GenerateContentRequest]:
-> 1376     system_instruction, contents = _parse_chat_history_gemini(
   1377         messages,
   1378         self._image_bytes_loader_client,
   1379         perform_literal_eval_on_string_raw_content=self.perform_literal_eval_on_string_raw_content,
   1380     )
   1381     formatted_tools = self._tools_gemini(tools=tools, functions=functions)
   1382     if tool_config:

File /venv/lib/python3.12/site-packages/langchain_google_vertexai/chat_models.py:319, in _parse_chat_history_gemini(history, imageBytesLoader, convert_system_message_to_human, perform_literal_eval_on_string_raw_content)
    317 prev_ai_message = None
    318 role = "user"
--> 319 parts = _convert_to_parts(message)
    320 if system_parts is not None:
    321     parts = system_parts + parts

File /venv/lib/python3.12/site-packages/langchain_google_vertexai/chat_models.py:286, in _parse_chat_history_gemini.<locals>._convert_to_parts(message)
    284     raw_content = [raw_content]
    285 result = []
--> 286 for raw_part in raw_content:
    287     part = _convert_to_prompt(raw_part)
    288     if part:

TypeError: 'ellipsis' object is not iterable

Environment:

• LangChain Version: 0.3.20
• langchain-google-vertexai Version: 2.0.15
• Python Version: 3.12

[lkuligin]

could you provide your prompt that reproduces the error, please?

[istvancsabakis]

"..." as it's specified in example