anthropic[patch]: always return content blocks if citations are generated (#29398)

We currently return string (and therefore no content blocks / citations)
if the response is of the form
```
[
    {"text": "a claim", "citations": [...]},
]
```

There are other cases where we do return citations as-is:
```
[
    {"text": "a claim", "citations": [...]},
    {"text": "some other text"},
    {"text": "another claim", "citations": [...]},
]
```
Here we update to return content blocks including citations in the first
case as well.

libs/partners/anthropic/langchain_anthropic/chat_models.py

@@ -764,7 +764,11 @@ class ChatAnthropic(BaseChatModel):
         llm_output = {
             k: v for k, v in data_dict.items() if k not in ("content", "role", "type")
         }
-        if len(content) == 1 and content[0]["type"] == "text":
+        if (
+            len(content) == 1
+            and content[0]["type"] == "text"
+            and "citations" not in content[0]
+        ):
             msg = AIMessage(content=content[0]["text"])
         elif any(block["type"] == "tool_use" for block in content):
             tool_calls = extract_tool_calls(content)

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

@@ -622,3 +622,30 @@ def test_pdf_document_input() -> None:
     assert isinstance(result, AIMessage)
     assert isinstance(result.content, str)
     assert len(result.content) > 0
+
+
+def test_citations() -> None:
+    llm = ChatAnthropic(model="claude-3-5-haiku-latest")
+    messages = [
+        {
+            "role": "user",
+            "content": [
+                {
+                    "type": "document",
+                    "source": {
+                        "type": "content",
+                        "content": [
+                            {"type": "text", "text": "The grass is green"},
+                            {"type": "text", "text": "The sky is blue"},
+                        ],
+                    },
+                    "citations": {"enabled": True},
+                },
+                {"type": "text", "text": "What color is the grass and sky?"},
+            ],
+        }
+    ]
+    response = llm.invoke(messages)
+    assert isinstance(response, AIMessage)
+    assert isinstance(response.content, list)
+    assert any("citations" in block for block in response.content)