langchain-ollama (partners): allow passing ChatMessage (with custom 'role') to ChatOllama

[rylativity]

**Description: currently, ChatOllama will raise a value error if a ChatMessage is passed to it, as described here. This PR enables passing a langchain ChatMessage with a custom 'role' attribute through the langchain ChatOllama class.
Issue: resolves #30122 (also related to PR #30147 and ollama-python issue ollama/ollama#8955)
Dependencies: no new dependencies

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[lemassykoi]

from my initial stack trace in 30122, I'm afraid that I will not be able to use create_react_agent to work with granite3.2
could you confirm ? thanks for your implication

[rylativity]

@lemassykoi you will have to explicitly use a ChatMessage instance for the "control/thinking" message like so:

from langchain_core.messages import ChatMessage

...

    messages = {
                "messages": [
                    ChatMessage(role="control", content="thinking"),
                    (
                        "user",
                        "explain catdog",
                    )
                ]
    }

Or, for example with more context:

from langchain_ollama import ChatOllama
from langchain_core.messages import ChatMessage
from langgraph.prebuilt import create_react_agent

llm = ChatOllama(
        base_url    = "http://localhost:11434",
        model       = "granite3.2",
        verbose     = True,
        disable_streaming = True,
    )
agent_supervisor = create_react_agent(
        model        = llm,
        tools        = [],
        name         = "ReAct_Agent_WIP",
        debug        = True
    )

messages = {
            "messages": [
                ChatMessage(role="control", content="thinking"),
                {
                   "role": "user",
                    "content": "explain options trading",
                }
            ]
}

for event in agent_supervisor.stream(
    input = messages,
    # config = config,
    stream_mode = "values",
    debug = True
):
    print(event)

For now, I'd recommend using a ChatMessage instance as described above. I'm looking into whether we can have it accept a dictionary message like this:

...

messages = {
            "messages": [
                {
                    "type": "chat",
                    "role": "control",
                    "content": "thinking"
                },
                {
                   "role": "user",
                    "content": "explain options trading",
                }
            ]
}

...

[rylativity]

In order to make this also work with dict type messages it would require fixing something in langchain-core - Right now there is an implicit assumption in the _convert_to_message function in langchain_core/messages/utils.py: that 'role' and 'type' values are interchangable in dict type messages (see https://github.com/langchain-ai/langchain/blob/master/libs/core/langchain_core/messages/utils.py#L325-L328), which I don't think is the desired or intended behavior. Handling this will require a deeper look at langchain-core to avoid breaking something else, but that issue already exists and is not something that's introduced by this PR.

@ccurme my suggestion would be to merge this PR, which allows using ChatMessage with custom 'role' attributes with ChatOllama and closes #30122. And I can open a separate discussion and/or issue regarding how to handle 'role' vs 'type' keys in dict type messages in langchain-core (described above).