Add llm-mac installation option

convokit/forecaster/__init__.py

@@ -24,7 +24,7 @@
         or "datasets" in str(e)
     ):
         raise ImportError(
-            "TransformerDecoderModel requires ML dependencies. Run 'pip install convokit[llm]' to install them."
+            "TransformerDecoderModel requires ML dependencies. Run 'pip install convokit[llm]' to install them (or 'pip install convokit[llm-mac]' if you are on macOS)."
         ) from e
     else:
         raise
@@ -39,7 +39,7 @@
         or "datasets" in str(e)
     ):
         raise ImportError(
-            "TransformerEncoderModel requires ML dependencies. Run 'pip install convokit[llm]' to install them."
+            "TransformerEncoderModel requires ML dependencies. Run 'pip install convokit[llm]' to install them (or 'pip install convokit[llm-mac]' if you are on macOS)."
         ) from e
     else:
         raise

convokit/pivotal_framework/__init__.py

@@ -12,7 +12,7 @@
         or "transformers" in str(e)
     ):
         raise ImportError(
-            "Pivotal framework requires ML dependencies. Run 'pip install convokit[llm]' to install them."
+            "Pivotal framework requires ML dependencies. Run 'pip install convokit[llm]' to install them (or 'pip install convokit[llm-mac]' if you are on macOS)."
         ) from e
     else:
         raise

convokit/redirection/__init__.py

@@ -3,7 +3,7 @@
 except (ImportError, ModuleNotFoundError) as e:
     if "torch" in str(e) or "not currently installed" in str(e):
         raise ImportError(
-            "Redirection module requires ML dependencies. Run 'pip install convokit[llm]' to install them."
+            "Redirection module requires ML dependencies. Run 'pip install convokit[llm]' to install them (or 'pip install convokit[llm-mac]' if you are on macOS)."
         ) from e
     else:
         raise
@@ -13,7 +13,7 @@
 except (ImportError, ModuleNotFoundError) as e:
     if "not currently installed" in str(e):
         raise ImportError(
-            "LikelihoodModel requires ML dependencies. Run 'pip install convokit[llm]' to install them."
+            "LikelihoodModel requires ML dependencies. Run 'pip install convokit[llm]' to install them (or 'pip install convokit[llm-mac]' if you are on macOS)."
         ) from e
     else:
         raise

convokit/utterance_likelihood/__init__.py

@@ -3,7 +3,7 @@
 except (ImportError, ModuleNotFoundError) as e:
     if "torch" in str(e) or "datasets" in str(e) or "not currently installed" in str(e):
         raise ImportError(
-            "UtteranceLikelihood requires ML dependencies. Run 'pip install convokit[llm]' to install them."
+            "UtteranceLikelihood requires ML dependencies. Run 'pip install convokit[llm]' to install them (or 'pip install convokit[llm-mac]' if you are on macOS)."
         ) from e
     else:
         raise

convokit/utterance_simulator/__init__.py

@@ -16,7 +16,7 @@
         or "datasets" in str(e)
     ):
         raise ImportError(
-            "UnslothUtteranceSimulatorModel requires ML dependencies. Run 'pip install convokit[llm]' to install them."
+            "UnslothUtteranceSimulatorModel requires ML dependencies. Run 'pip install convokit[llm]' to install them (or 'pip install convokit[llm-mac]' if you are on macOS)."
         ) from e
     else:
         raise

docs/source/pivotal.rst

@@ -1,6 +1,6 @@
 Pivotal Moment Measure
 ====================================
-Please note: this transformer requires installing convokit with the optional LLM packages via `pip install convokit[llm]`
+Please note: this transformer requires installing convokit with the optional LLM packages via `pip install convokit[llm]` (or `pip install convokit[llm-mac]` if you are on macOS)
 
 The `PivotalMomentMeasure` transformer identifies pivotal moments in conversations 
 as described in this `paper <http://www.cs.cornell.edu/~cristian/Pivotal_Moments.html>`_. 

docs/source/redirectionAndUtteranceLikelihood.rst

@@ -1,6 +1,6 @@
 Redirection and Utterance Likelihood
 ====================================
-Please note: this transformer requires installing convokit with the optional LLM packages via `pip install convokit[llm]`
+Please note: this transformer requires installing convokit with the optional LLM packages via `pip install convokit[llm]` (or `pip install convokit[llm-mac]` if you are on macOS)
 
 The `Redirection` transformer measures the extent to which utterances 
 redirect the flow of the conversation, 

docs/source/transformerdecodermodel.rst

@@ -1,6 +1,6 @@
 Transformer Decoder-based Forecasting Model
 ===========================================
-Please note: this transformer requires installing convokit with the optional LLM packages via `pip install convokit[llm]`
+Please note: this transformer requires installing convokit with the optional LLM packages via `pip install convokit[llm]` (or `pip install convokit[llm-mac]` if you are on macOS)
 
 A ConvoKit Forecaster-adherent implementation of conversational forecasting model based on Transformer Decoder Model (e.g. LlaMA, Gemma, GPT).
 This class is first used in the paper "Conversations Gone Awry, But Then? Evaluating Conversational Forecasting Models" (Tran et al., 2025).

docs/source/transformerencodermodel.rst

@@ -1,6 +1,6 @@
 Transformer Encoder-based Forecasting Model
 ===========================================
-Please note: this transformer requires installing convokit with the optional LLM packages via `pip install convokit[llm]`.
+Please note: this transformer requires installing convokit with the optional LLM packages via `pip install convokit[llm]` (or `pip install convokit[llm-mac]` if you are on macOS).
 
 A ConvoKit Forecaster-adherent implementation of conversational forecasting model based on Transformer Encoder Model (e.g. BERT, RoBERTa, SpanBERT, DeBERTa).
 This class is first used in the paper "Conversations Gone Awry, But Then? Evaluating Conversational Forecasting Models"(Tran et al., 2025).

setup.py

@@ -99,6 +99,17 @@
             "tensorflow>=2.18.0",
             "tf-keras>=2.17.0,<3.0.0",
         ],
+        "llm-mac": [
+            "torch>=2.0.0",
+            "accelerate",
+            "peft",
+            "bitsandbytes",
+            "transformers",
+            "unsloth[apple-silicon]",  # https://github.com/yhsung/unsloth/blob/c2a368b26f5febd9dd4cd39cabc73da67c1f1eb1/APPLE_SILICON.md
+            "mlx>=0.20.0",
+            "trl>=0.12.2",
+            "tensorflow>=2.13.0",
+        ],
     },
     classifiers=[
         "Programming Language :: Python",