anthropic[patch]: support citations in streaming (#29591)

libs/partners/anthropic/langchain_anthropic/chat_models.py

@@ -718,7 +718,9 @@ class ChatAnthropic(BaseChatModel):
         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)
+        coerce_content_to_string = not _tools_in_params(
+            payload
+        ) and not _documents_in_params(payload)
         for event in stream:
             msg = _make_message_chunk_from_anthropic_event(
                 event,
@@ -745,7 +747,9 @@ class ChatAnthropic(BaseChatModel):
         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)
+        coerce_content_to_string = not _tools_in_params(
+            payload
+        ) and not _documents_in_params(payload)
         async for event in stream:
             msg = _make_message_chunk_from_anthropic_event(
                 event,
@@ -761,6 +765,16 @@ class ChatAnthropic(BaseChatModel):
     def _format_output(self, data: Any, **kwargs: Any) -> ChatResult:
         data_dict = data.model_dump()
         content = data_dict["content"]
+
+        # Remove citations if they are None - introduced in anthropic sdk 0.45
+        for block in content:
+            if (
+                isinstance(block, dict)
+                and "citations" in block
+                and block["citations"] is None
+            ):
+                block.pop("citations")
+
         llm_output = {
             k: v for k, v in data_dict.items() if k not in ("content", "role", "type")
         }
@@ -1254,6 +1268,19 @@ def _tools_in_params(params: dict) -> bool:
     )
 
 
+def _documents_in_params(params: dict) -> bool:
+    for message in params.get("messages", []):
+        if isinstance(message.get("content"), list):
+            for block in message["content"]:
+                if (
+                    isinstance(block, dict)
+                    and block.get("type") == "document"
+                    and block.get("citations", {}).get("enabled")
+                ):
+                    return True
+    return False
+
+
 class _AnthropicToolUse(TypedDict):
     type: Literal["tool_use"]
     name: str
@@ -1299,31 +1326,37 @@ def _make_message_chunk_from_anthropic_event(
     elif (
         event.type == "content_block_start"
         and event.content_block is not None
-        and event.content_block.type == "tool_use"
+        and event.content_block.type in ("tool_use", "document")
     ):
         if coerce_content_to_string:
             warnings.warn("Received unexpected tool content block.")
         content_block = event.content_block.model_dump()
         content_block["index"] = event.index
-        tool_call_chunk = create_tool_call_chunk(
+        if event.content_block.type == "tool_use":
-            index=event.index,
+            tool_call_chunk = create_tool_call_chunk(
-            id=event.content_block.id,
+                index=event.index,
-            name=event.content_block.name,
+                id=event.content_block.id,
-            args="",
+                name=event.content_block.name,
-        )
+                args="",
+            )
+            tool_call_chunks = [tool_call_chunk]
+        else:
+            tool_call_chunks = []
         message_chunk = AIMessageChunk(
             content=[content_block],
-            tool_call_chunks=[tool_call_chunk],  # type: ignore
+            tool_call_chunks=tool_call_chunks,  # type: ignore
         )
     elif event.type == "content_block_delta":
-        if event.delta.type == "text_delta":
+        if event.delta.type in ("text_delta", "citations_delta"):
-            if coerce_content_to_string:
+            if coerce_content_to_string and hasattr(event.delta, "text"):
                 text = event.delta.text
                 message_chunk = AIMessageChunk(content=text)
             else:
                 content_block = event.delta.model_dump()
                 content_block["index"] = event.index
                 content_block["type"] = "text"
+                if "citation" in content_block:
+                    content_block["citations"] = [content_block.pop("citation")]
                 message_chunk = AIMessageChunk(content=[content_block])
         elif event.delta.type == "input_json_delta":
             content_block = event.delta.model_dump()

libs/partners/anthropic/poetry.lock

@@ -1,4 +1,4 @@
-# This file is automatically @generated by Poetry 1.8.3 and should not be changed by hand.
+# This file is automatically @generated by Poetry 1.8.2 and should not be changed by hand.
 
 [[package]]
 name = "annotated-types"
@@ -544,7 +544,7 @@ url = "../../core"
 
 [[package]]
 name = "langchain-tests"
-version = "0.3.9"
+version = "0.3.10"
 description = "Standard tests for LangChain implementations"
 optional = false
 python-versions = ">=3.9,<4.0"
@@ -553,7 +553,7 @@ develop = true
 
 [package.dependencies]
 httpx = ">=0.25.0,<1"
-langchain-core = "^0.3.31"
+langchain-core = "^0.3.33"
 numpy = [
     {version = ">=1.24.0,<2.0.0", markers = "python_version < \"3.12\""},
     {version = ">=1.26.2,<3", markers = "python_version >= \"3.12\""},
@@ -1558,4 +1558,4 @@ cffi = ["cffi (>=1.11)"]
 [metadata]
 lock-version = "2.0"
 python-versions = ">=3.9,<4.0"
-content-hash = "311f60adde43535d7e5dc14d93167440a8fb838868d544ac1b89b0faac174efe"
+content-hash = "e92c081312cc5199ac660851355ac9bc59f0333a4a2e61375b5ecfaffe4725b7"

libs/partners/anthropic/pyproject.toml

@@ -21,7 +21,7 @@ plugins = ['pydantic.mypy']
 
 [tool.poetry.dependencies]
 python = ">=3.9,<4.0"
-anthropic = ">=0.41.0,<1"
+anthropic = ">=0.45.0,<1"
 langchain-core = "^0.3.33"
 pydantic = "^2.7.4"
 

libs/partners/anthropic/tests/integration_tests/test_chat_models.py

@@ -649,3 +649,12 @@ def test_citations() -> None:
     assert isinstance(response, AIMessage)
     assert isinstance(response.content, list)
     assert any("citations" in block for block in response.content)
+
+    # Test streaming
+    full: Optional[BaseMessageChunk] = None
+    for chunk in llm.stream(messages):
+        full = chunk if full is None else full + chunk
+    assert isinstance(full, AIMessageChunk)
+    assert isinstance(full.content, list)
+    assert any("citations" in block for block in full.content)
+    assert not any("citation" in block for block in full.content)