DOC: Explain how to continue the conversation with OllamaFunctions
Labels: name: auto:bug, name: auto:documentation, name: area: models

### Issue with current documentation:

https://python.langchain.com/docs/integrations/chat/ollama_functions

Ollama functions page shows how to start a conversation where the llm calls a function.
But it stops there. 

How do we keep the conversation going? (i.e. I should give the llm the answer to the function call, and then it should give a text reply with his explanation of the weather in Paris, right?)

Here's what I tried

```
>>> from langchain_experimental.llms.ollama_functions import OllamaFunctions
>>> from langchain.schema import HumanMessage, FunctionMessage
>>> import json
>>> model = OllamaFunctions(model="mistral")
>>> model = model.bind(
...     functions=[
...         {
...             "name": "get_current_weather",
...             "description": "Get the current weather in a given location",
...             "parameters": {
...                 "type": "object",
...                 "properties": {
...                     "location": {
...                         "type": "string",
...                         "description": "The city and state, " "e.g. San Francisco, CA",
...                     },
...                     "unit": {
...                         "type": "string",
...                         "enum": ["celsius", "fahrenheit"],
...                     },
...                 },
...                 "required": ["location"],
...             },
...         }
...     ],
...     function_call={"name": "get_current_weather"},
... )
>>>
>>> messages = [HumanMessage(content="how is the weather in Paris?")]
>>> aim = model.invoke(messages)
>>> aim
AIMessage(content='', additional_kwargs={'function_call': {'name': 'get_current_weather', 'arguments': '{"location": "Paris, FR", "unit": "celsius"}'}})
>>> messages.append(aim)
>>> fm = FunctionMessage(name='get_current_weather', content=json.dumps({'temperature': '25 celsius'}))
>>> messages.append(fm)
>>> aim = model.invoke(messages)
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "/Users/tony/.pyenv/versions/functionary/lib/python3.11/site-packages/langchain_core/runnables/base.py", line 2871, in invoke
    return self.bound.invoke(
           ^^^^^^^^^^^^^^^^^^
  File "/Users/tony/.pyenv/versions/functionary/lib/python3.11/site-packages/langchain_core/language_models/chat_models.py", line 160, in invoke
    self.generate_prompt(
  File "/Users/tony/.pyenv/versions/functionary/lib/python3.11/site-packages/langchain_core/language_models/chat_models.py", line 491, in generate_prompt
    return self.generate(prompt_messages, stop=stop, callbacks=callbacks, **kwargs)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/Users/tony/.pyenv/versions/functionary/lib/python3.11/site-packages/langchain_core/language_models/chat_models.py", line 378, in generate
    raise e
  File "/Users/tony/.pyenv/versions/functionary/lib/python3.11/site-packages/langchain_core/language_models/chat_models.py", line 368, in generate
    self._generate_with_cache(
  File "/Users/tony/.pyenv/versions/functionary/lib/python3.11/site-packages/langchain_core/language_models/chat_models.py", line 524, in _generate_with_cache
    return self._generate(
           ^^^^^^^^^^^^^^^
  File "/Users/tony/.pyenv/versions/functionary/lib/python3.11/site-packages/langchain_experimental/llms/ollama_functions.py", line 90, in _generate
    response_message = self.llm.predict_messages(
                       ^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/Users/tony/.pyenv/versions/functionary/lib/python3.11/site-packages/langchain_core/language_models/chat_models.py", line 685, in predict_messages
    return self(messages, stop=_stop, **kwargs)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/Users/tony/.pyenv/versions/functionary/lib/python3.11/site-packages/langchain_core/language_models/chat_models.py", line 632, in __call__
    generation = self.generate(
                 ^^^^^^^^^^^^^^
  File "/Users/tony/.pyenv/versions/functionary/lib/python3.11/site-packages/langchain_core/language_models/chat_models.py", line 378, in generate
    raise e
  File "/Users/tony/.pyenv/versions/functionary/lib/python3.11/site-packages/langchain_core/language_models/chat_models.py", line 368, in generate
    self._generate_with_cache(
  File "/Users/tony/.pyenv/versions/functionary/lib/python3.11/site-packages/langchain_core/language_models/chat_models.py", line 524, in _generate_with_cache
    return self._generate(
           ^^^^^^^^^^^^^^^
  File "/Users/tony/.pyenv/versions/functionary/lib/python3.11/site-packages/langchain/chat_models/ollama.py", line 97, in _generate
    prompt = self._format_messages_as_text(messages)
             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/Users/tony/.pyenv/versions/functionary/lib/python3.11/site-packages/langchain/chat_models/ollama.py", line 70, in _format_messages_as_text
    [self._format_message_as_text(message) for message in messages]
  File "/Users/tony/.pyenv/versions/functionary/lib/python3.11/site-packages/langchain/chat_models/ollama.py", line 70, in <listcomp>
    [self._format_message_as_text(message) for message in messages]
     ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/Users/tony/.pyenv/versions/functionary/lib/python3.11/site-packages/langchain/chat_models/ollama.py", line 65, in _format_message_as_text
    raise ValueError(f"Got unknown type {message}")
ValueError: Got unknown type content='{"temperature": "25 celsius"}' name='get_current_weather'
>>>
```

### Idea or request for content:

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