Check for single prompt in __call__ method of the BaseLLM class (#4892)

# Ensuring that users pass a single prompt when calling a LLM 

- This PR adds a check to the `__call__` method of the `BaseLLM` class
to ensure that it is called with a single prompt
- Raises a `ValueError` if users try to call a LLM with a list of prompt
and instructs them to use the `generate` method instead

## Why this could be useful

I stumbled across this by accident. I accidentally called the OpenAI LLM
with a list of prompts instead of a single string and still got a
result:

```
>>> from langchain.llms import OpenAI
>>> llm = OpenAI()
>>> llm(["Tell a joke"]*2)
"\n\nQ: Why don't scientists trust atoms?\nA: Because they make up everything!"
```

It might be better to catch such a scenario preventing unnecessary costs
and irritation for the user.

## Proposed behaviour

```
>>> from langchain.llms import OpenAI
>>> llm = OpenAI()
>>> llm(["Tell a joke"]*2)
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "/Users/marcus/Projects/langchain/langchain/llms/base.py", line 291, in __call__
    raise ValueError(
ValueError: Argument `prompt` is expected to be a single string, not a list. If you want to run the LLM on multiple prompts, use `generate` instead.
```

langchain/llms/base.py

@@ -287,6 +287,12 @@ class BaseLLM(BaseLanguageModel, ABC):
         self, prompt: str, stop: Optional[List[str]] = None, callbacks: Callbacks = None
     ) -> str:
         """Check Cache and run the LLM on the given prompt and input."""
+        if not isinstance(prompt, str):
+            raise ValueError(
+                "Argument `prompt` is expected to be a string. Instead found "
+                f"{type(prompt)}. If you want to run the LLM on multiple prompts, use "
+                "`generate` instead."
+            )
         return (
             self.generate([prompt], stop=stop, callbacks=callbacks)
             .generations[0][0]