github/langchain
1
0
Fork 0
mirror of https://github.com/hwchase17/langchain.git synced 2025-06-21 14:18:52 +00:00
Code Issues Packages Projects Releases Wiki Activity

anthropic: emit informative error message if there are only system messages in a prompt (#30822)

Browse Source 
**PR message**: Not sure if I put the check at the right spot, but I
thought throwing the error before the loop made sense to me.
**Description:** Checks if there are only system messages using
AnthropicChat model and throws an error if it's the case. Check Issue
for more details
**Issue:** #30764

---------

Co-authored-by: Chester Curme <chester.curme@gmail.com>
This commit is contained in:
mathislindner 2025-05-16 22:43:59 +02:00 committed by GitHub
parent eb25d7472d
commit e1af509966
No known key found for this signature in database
GPG Key ID: B5690EEEBB952194
1 changed files with 56 additions and 35 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

91
libs/partners/anthropic/langchain_anthropic/chat_models.py
View File

@ -282,7 +282,6 @@ def _format_messages(
"""
system: Union[str, list[dict], None] = None
formatted_messages: list[dict] = []
merged_messages = _merge_messages(messages)
for i, message in enumerate(merged_messages):
if message.type == "system":
@ -410,6 +409,16 @@ def _format_messages(
return system, formatted_messages
def _handle_anthropic_bad_request(e: anthropic.BadRequestError) -> None:
"""Handle Anthropic BadRequestError."""
if ("messages: at least one message is required") in e.message:
message = "Received only system message(s). "
warnings.warn(message)
raise e
else:
raise
class ChatAnthropic(BaseChatModel):
"""Anthropic chat models.
@ -1111,23 +1120,26 @@ class ChatAnthropic(BaseChatModel):
stream_usage = self.stream_usage
kwargs["stream"] = True
payload = self._get_request_payload(messages, stop=stop, **kwargs)
stream = self._client.messages.create(**payload)
coerce_content_to_string = (
not _tools_in_params(payload)
and not _documents_in_params(payload)
and not _thinking_in_params(payload)
)
for event in stream:
msg = _make_message_chunk_from_anthropic_event(
event,
stream_usage=stream_usage,
coerce_content_to_string=coerce_content_to_string,
try:
stream = self._client.messages.create(**payload)
coerce_content_to_string = (
not _tools_in_params(payload)
and not _documents_in_params(payload)
and not _thinking_in_params(payload)
)
if msg is not None:
chunk = ChatGenerationChunk(message=msg)
if run_manager and isinstance(msg.content, str):
run_manager.on_llm_new_token(msg.content, chunk=chunk)
yield chunk
for event in stream:
msg = _make_message_chunk_from_anthropic_event(
event,
stream_usage=stream_usage,
coerce_content_to_string=coerce_content_to_string,
)
if msg is not None:
chunk = ChatGenerationChunk(message=msg)
if run_manager and isinstance(msg.content, str):
run_manager.on_llm_new_token(msg.content, chunk=chunk)
yield chunk
except anthropic.BadRequestError as e:
_handle_anthropic_bad_request(e)
async def _astream(
self,
@ -1142,23 +1154,26 @@ class ChatAnthropic(BaseChatModel):
stream_usage = self.stream_usage
kwargs["stream"] = True
payload = self._get_request_payload(messages, stop=stop, **kwargs)
stream = await self._async_client.messages.create(**payload)
coerce_content_to_string = (
not _tools_in_params(payload)
and not _documents_in_params(payload)
and not _thinking_in_params(payload)
)
async for event in stream:
msg = _make_message_chunk_from_anthropic_event(
event,
stream_usage=stream_usage,
coerce_content_to_string=coerce_content_to_string,
try:
stream = await self._async_client.messages.create(**payload)
coerce_content_to_string = (
not _tools_in_params(payload)
and not _documents_in_params(payload)
and not _thinking_in_params(payload)
)
if msg is not None:
chunk = ChatGenerationChunk(message=msg)
if run_manager and isinstance(msg.content, str):
await run_manager.on_llm_new_token(msg.content, chunk=chunk)
yield chunk
async for event in stream:
msg = _make_message_chunk_from_anthropic_event(
event,
stream_usage=stream_usage,
coerce_content_to_string=coerce_content_to_string,
)
if msg is not None:
chunk = ChatGenerationChunk(message=msg)
if run_manager and isinstance(msg.content, str):
await run_manager.on_llm_new_token(msg.content, chunk=chunk)
yield chunk
except anthropic.BadRequestError as e:
_handle_anthropic_bad_request(e)
def _format_output(self, data: Any, **kwargs: Any) -> ChatResult:
data_dict = data.model_dump()
@ -1218,7 +1233,10 @@ class ChatAnthropic(BaseChatModel):
)
return generate_from_stream(stream_iter)
payload = self._get_request_payload(messages, stop=stop, **kwargs)
data = self._client.messages.create(**payload)
try:
data = self._client.messages.create(**payload)
except anthropic.BadRequestError as e:
_handle_anthropic_bad_request(e)
return self._format_output(data, **kwargs)
async def _agenerate(
@ -1234,7 +1252,10 @@ class ChatAnthropic(BaseChatModel):
)
return await agenerate_from_stream(stream_iter)
payload = self._get_request_payload(messages, stop=stop, **kwargs)
data = await self._async_client.messages.create(**payload)
try:
data = await self._async_client.messages.create(**payload)
except anthropic.BadRequestError as e:
_handle_anthropic_bad_request(e)
return self._format_output(data, **kwargs)
def _get_llm_for_structured_output_when_thinking_is_enabled(