Add ChatModels wrapper for Cloudflare Workers AI (#27645)

Thank you for contributing to LangChain!

- [x] **PR title**: "community: chat models wrapper for Cloudflare
Workers AI"


- [x] **PR message**:
- **Description:** Add chat models wrapper for Cloudflare Workers AI.
Enables Langgraph intergration via ChatModel for tool usage, agentic
usage.


- [x] **Add tests and docs**: If you're adding a new integration, please
include
1. a test for the integration, preferably unit tests that do not rely on
network access,
2. an example notebook showing its use. It lives in
`docs/docs/integrations` directory.


- [x] **Lint and test**: Run `make format`, `make lint` and `make test`
from the root of the package(s) you've modified. See contribution
guidelines for more: https://python.langchain.com/docs/contributing/

Additional guidelines:
- Make sure optional dependencies are imported within a function.
- Please do not add dependencies to pyproject.toml files (even optional
ones) unless they are required for unit tests.
- Most PRs should not touch more than one package.
- Changes should be backwards compatible.
- If you are adding something to community, do not re-import it in
langchain.

If no one reviews your PR within a few days, please @-mention one of
baskaryan, efriis, eyurtsev, ccurme, vbarda, hwchase17.

---------

Co-authored-by: Erick Friis <erick@langchain.dev>
Co-authored-by: Chester Curme <chester.curme@gmail.com>

libs/community/tests/unit_tests/chat_models/test_cloudflare_workersai.py

@@ -0,0 +1,78 @@
+"""Test CloudflareWorkersAI Chat API wrapper."""
+
+from typing import Any, Dict, List, Type
+
+import pytest
+from langchain_core.language_models import BaseChatModel
+from langchain_core.messages import (
+    AIMessage,
+    BaseMessage,
+    HumanMessage,
+    SystemMessage,
+    ToolMessage,
+)
+from langchain_standard_tests.unit_tests import ChatModelUnitTests
+
+from langchain_community.chat_models.cloudflare_workersai import (
+    ChatCloudflareWorkersAI,
+    _convert_messages_to_cloudflare_messages,
+)
+
+
+class TestChatCloudflareWorkersAI(ChatModelUnitTests):
+    @property
+    def chat_model_class(self) -> Type[BaseChatModel]:
+        return ChatCloudflareWorkersAI
+
+    @property
+    def chat_model_params(self) -> dict:
+        return {
+            "account_id": "my_account_id",
+            "api_token": "my_api_token",
+            "model": "@hf/nousresearch/hermes-2-pro-mistral-7b",
+        }
+
+
+@pytest.mark.parametrize(
+    ("messages", "expected"),
+    [
+        # Test case with a single HumanMessage
+        (
+            [HumanMessage(content="Hello, AI!")],
+            [{"role": "user", "content": "Hello, AI!"}],
+        ),
+        # Test case with SystemMessage, HumanMessage, and AIMessage without tool calls
+        (
+            [
+                SystemMessage(content="System initialized."),
+                HumanMessage(content="Hello, AI!"),
+                AIMessage(content="Response from AI"),
+            ],
+            [
+                {"role": "system", "content": "System initialized."},
+                {"role": "user", "content": "Hello, AI!"},
+                {"role": "assistant", "content": "Response from AI"},
+            ],
+        ),
+        # Test case with ToolMessage and tool_call_id
+        (
+            [
+                ToolMessage(
+                    content="Tool message content", tool_call_id="tool_call_123"
+                ),
+            ],
+            [
+                {
+                    "role": "tool",
+                    "content": "Tool message content",
+                    "tool_call_id": "tool_call_123",
+                }
+            ],
+        ),
+    ],
+)
+def test_convert_messages_to_cloudflare_format(
+    messages: List[BaseMessage], expected: List[Dict[str, Any]]
+) -> None:
+    result = _convert_messages_to_cloudflare_messages(messages)
+    assert result == expected