langchain: catch if there are only system messages in a prompt for anthropic

libs/partners/anthropic/langchain_anthropic/chat_models.py

@@ -281,7 +281,6 @@ 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":
@@ -409,6 +408,16 @@ 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 ValueError(message)
+    else:
+        raise
+
+
 class ChatAnthropic(BaseChatModel):
     """Anthropic chat models.
 
@@ -1093,23 +1102,26 @@ def _stream(
             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,
@@ -1124,23 +1136,26 @@ async def _astream(
             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()
@@ -1200,7 +1215,10 @@ def _generate(
             )
             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(
@@ -1216,7 +1234,10 @@ async def _agenerate(
             )
             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(