Fix CohereInvocationLayer _ensure_token_limit not returning resized (#4978)

prompt

haystack/nodes/prompt/invocation_layer/cohere.py

@@ -155,7 +155,7 @@ class CohereInvocationLayer(PromptModelInvocationLayer):
         **kwargs,
     ) -> requests.Response:
         """
-        Post data to the HF inference model. It takes in a prompt and returns a list of responses using a REST
+        Post data to the Cohere inference model. It takes in a prompt and returns a list of responses using a REST
         invocation.
         :param data: The data to be sent to the model.
         :param stream: Whether to stream the response.
@@ -192,19 +192,21 @@ class CohereInvocationLayer(PromptModelInvocationLayer):
         return response
 
     def _ensure_token_limit(self, prompt: Union[str, List[Dict[str, str]]]) -> Union[str, List[Dict[str, str]]]:
-        # the prompt for this model will be of the type str
+        if isinstance(prompt, List):
-        resize_info = self.prompt_handler(prompt)  # type: ignore
+            raise ValueError("Cohere invocation layer doesn't support a dictionary as prompt")
+
+        resize_info = self.prompt_handler(prompt)
         if resize_info["prompt_length"] != resize_info["new_prompt_length"]:
             logger.warning(
                 "The prompt has been truncated from %s tokens to %s tokens so that the prompt length and "
                 "answer length (%s tokens) fit within the max token limit (%s tokens). "
-                "Shorten the prompt to prevent it from being cut off",
+                "Reduce the length of the prompt to prevent it from being cut off.",
                 resize_info["prompt_length"],
                 max(0, resize_info["model_max_length"] - resize_info["max_length"]),  # type: ignore
                 resize_info["max_length"],
                 resize_info["model_max_length"],
             )
-        return prompt
+        return str(resize_info["resized_prompt"])
 
     @classmethod
     def supports(cls, model_name_or_path: str, **kwargs) -> bool:

test/prompt/invocation_layer/test_cohere.py

@@ -178,3 +178,42 @@ def test_supports():
 
     # doesn't support other models that have base substring only i.e. google/flan-t5-base
     assert not CohereInvocationLayer.supports("google/flan-t5-base")
+
+
+@pytest.mark.unit
+def test_ensure_token_limit_fails_if_called_with_list():
+    layer = CohereInvocationLayer(model_name_or_path="command", api_key="some_fake_key")
+    with pytest.raises(ValueError):
+        layer._ensure_token_limit(prompt=[])
+
+
+@pytest.mark.unit
+def test_ensure_token_limit_with_small_max_length(caplog):
+    layer = CohereInvocationLayer(model_name_or_path="command", api_key="some_fake_key", max_length=10)
+    res = layer._ensure_token_limit(prompt="Short prompt")
+
+    assert res == "Short prompt"
+    assert not caplog.records
+
+    res = layer._ensure_token_limit(prompt="This is a very very very very very much longer prompt")
+    assert res == "This is a very very very very very much longer prompt"
+    assert not caplog.records
+
+
+@pytest.mark.unit
+def test_ensure_token_limit_with_huge_max_length(caplog):
+    layer = CohereInvocationLayer(model_name_or_path="command", api_key="some_fake_key", max_length=4090)
+    res = layer._ensure_token_limit(prompt="Short prompt")
+
+    assert res == "Short prompt"
+    assert not caplog.records
+
+    res = layer._ensure_token_limit(prompt="This is a very very very very very much longer prompt")
+    assert res == "This is a very very very"
+    assert len(caplog.records) == 1
+    expected_message_log = (
+        "The prompt has been truncated from 11 tokens to 6 tokens so that the prompt length and "
+        "answer length (4090 tokens) fit within the max token limit (4096 tokens). "
+        "Reduce the length of the prompt to prevent it from being cut off."
+    )
+    assert caplog.records[0].message == expected_message_log