Fixed TypeError: generate_step() got an unexpected keyword argument from 'formatter' in MLXPipeline

libs/community/langchain_community/llms/mlx_pipeline.py

@@ -1,7 +1,7 @@
 from __future__ import annotations
 
 import logging
 from typing import Any, Callable, Iterator, List, Mapping, Optional
 
 from langchain_core.callbacks import CallbackManagerForLLMRun
 from langchain_core.language_models.llms import LLM
@@ -156,7 +156,6 @@
         temp: float = pipeline_kwargs.get("temp", 0.0)
         max_tokens: int = pipeline_kwargs.get("max_tokens", 100)
         verbose: bool = pipeline_kwargs.get("verbose", False)
-        formatter: Optional[Callable] = pipeline_kwargs.get("formatter", None)
         repetition_penalty: Optional[float] = pipeline_kwargs.get(
             "repetition_penalty", None
         )
@@ -178,7 +177,6 @@
             prompt=prompt,
             max_tokens=max_tokens,
             verbose=verbose,
-            formatter=formatter,
             sampler=sampler,
             logits_processors=logits_processors,
         )

libs/community/tests/unit_tests/llms/test_mlx_pipeline_no_formatter_kwarg.py

@@ -0,0 +1,31 @@
+from langchain_community.llms.mlx_pipeline import MLXPipeline
+from langchain_core.prompts import PromptTemplate
+
+def test_mlx_pipeline_no_formatter_kwarg():
+    """Mimicking example code listed on https://python.langchain.com/docs/integrations/llms/mlx_pipelines/
+
+    To showcase issue with `formatter` keyword which is being passed to mlx-lm
+    generate function
+    """
+    pipe = MLXPipeline.from_model_id(
+         "mlx-community/quantized-gemma-2b-it"
+     )
+
+    assert pipe, "Model not loaded"
+
+    template = """Question: {question}
+
+    Answer: Let's think step by step."""
+
+    prompt = PromptTemplate.from_template(template)
+
+    chain = prompt | pipe
+
+    question = "What is electroencephalography?"
+
+    answer = chain.invoke({"question": question})
+
+    assert answer, "Answer was not generated"
+
+
+