Add chat_template.argilla_chat support for DPO datasets (#3202)

* Add chat_template.argilla_chat support for DPO datasets

  Creates a new chat_template.argilla_chat prompt strategy for handling
  DPO datasets where chosen/rejected fields contain full conversations
  (messages + final response), following the pattern of chatml.argilla_chat
  and llama3.argilla_chat.

  - Add argilla_chat() function to chat_template.py
  - Add chat_template.argilla_chat to RLHF documentation
  - Add test coverage for argilla_chat with multiple tokenizers

  Dataset format:
  {
    "chosen": [
      {"role": "user", "content": "..."},
      {"role": "assistant", "content": "..."}
    ],
    "rejected": [
      {"role": "user", "content": "..."},
      {"role": "assistant", "content": "..."}
    ]
  }

* Fix chat_template.argilla_chat return value contract and add docstring

- Return (transform_fn, dataset_kwargs) tuple instead of bare transform_fn
- Add remove_columns specification for field_chosen and field_rejected
- Add comprehensive docstring with Args/Returns sections
- Update tests to unpack tuple return value

Addresses PR feedback to maintain consistency with chat_template.default()
and properly specify columns to remove after dataset transformation.

* Update tests/prompt_strategies/test_dpo_chat_templates.py

Co-authored-by: Wing Lian <[email protected]>

---------

Co-authored-by: Wing Lian <[email protected]>

Author: lhl

docs/rlhf.qmd

@@ -219,6 +219,21 @@ DPO supports the following types with the following dataset format:
 }
 ```
 
+#### chat_template.argilla_chat
+
+```json
+{
+    "chosen": [
+        {"role": "user", "content": "..."},
+        {"role": "assistant", "content": "..."}
+    ],
+    "rejected": [
+        {"role": "user", "content": "..."},
+        {"role": "assistant", "content": "..."}
+    ]
+}
+```
+
 #### chat_template.default
 
 ```yaml

src/axolotl/prompt_strategies/dpo/chat_template.py

@@ -120,3 +120,123 @@ def transform_fn(sample, tokenizer=None):
         return result
 
     return transform_fn, {"remove_columns": [field_messages]}
+
+
+def argilla_chat(cfg, dataset_idx=0, **kwargs):
+    """
+    DPO chat template strategy for argilla-style datasets.
+
+    For argilla-style datasets where chosen/rejected contain full conversations
+    instead of single response messages. Extracts the conversation history from
+    the chosen field and formats both chosen/rejected responses using the
+    configured chat template.
+
+    Args:
+        cfg: Configuration object containing chat_template and dataset settings
+        dataset_idx: Index of the dataset in the config (default: 0)
+        **kwargs: Additional keyword arguments (unused)
+
+    Returns:
+        tuple: (transform_fn, dataset_kwargs) where:
+            - transform_fn: Function to transform dataset samples
+            - dataset_kwargs: Dict with 'remove_columns' specifying columns to drop
+
+    Dataset format:
+        {
+            "chosen": [
+                {"role": "user", "content": "..."},
+                {"role": "assistant", "content": "..."}
+            ],
+            "rejected": [
+                {"role": "user", "content": "..."},
+                {"role": "assistant", "content": "..."}
+            ]
+        }
+    """
+    ds_cfg = cfg["datasets"][dataset_idx]
+    ds_cfg = handle_legacy_message_fields_logic(ds_cfg)
+
+    chat_template_choice, chat_template_jinja = extract_chat_template_args(
+        cfg=cfg, ds_cfg=ds_cfg
+    )
+    field_chosen = ds_cfg.get("field_chosen", "chosen")
+    field_rejected = ds_cfg.get("field_rejected", "rejected")
+    message_property_mappings = ds_cfg.get(
+        "message_property_mappings",
+        {
+            "role": "role",
+            "content": "content",
+        },
+    )
+    role_map_inv = ds_cfg.get(
+        "roles",
+        {
+            "user": ["user"],
+            "assistant": ["assistant"],
+            "system": ["system"],
+        },
+    )
+    role_map = {}
+    for target, sources in role_map_inv.items():
+        for source in sources:
+            role_map[source] = target
+
+    def transform_fn(sample, tokenizer=None):
+        chat_template_string = get_chat_template(
+            user_choice=chat_template_choice,
+            jinja_template=chat_template_jinja,
+            tokenizer=tokenizer,
+        )
+
+        chosen_raw = sample[field_chosen]
+        rejected_raw = sample[field_rejected]
+
+        # Extract messages (all but last) and responses (last message)
+        chosen_messages = [
+            {
+                "role": role_map[m[message_property_mappings["role"]]],
+                "content": m[message_property_mappings["content"]],
+            }
+            for m in chosen_raw[:-1]
+        ]
+        chosen_response = {
+            "role": role_map[chosen_raw[-1][message_property_mappings["role"]]],
+            "content": chosen_raw[-1][message_property_mappings["content"]],
+        }
+
+        rejected_response = {
+            "role": role_map[rejected_raw[-1][message_property_mappings["role"]]],
+            "content": rejected_raw[-1][message_property_mappings["content"]],
+        }
+
+        dummy_user_message = {"role": "user", "content": "[[dummy_message]]"}
+
+        result = {}
+        result["prompt"] = tokenizer.apply_chat_template(
+            chosen_messages,
+            add_generation_prompt=True,
+            chat_template=chat_template_string,
+            tokenize=False,
+        )
+
+        result["chosen"] = tokenizer.apply_chat_template(
+            [dummy_user_message, chosen_response],
+            add_generation_prompt=False,
+            chat_template=chat_template_string,
+            tokenize=False,
+        )
+        chosen_strip_index = result["chosen"].find(chosen_response["content"])
+        result["chosen"] = result["chosen"][chosen_strip_index:].rstrip()
+
+        result["rejected"] = tokenizer.apply_chat_template(
+            [dummy_user_message, rejected_response],
+            add_generation_prompt=False,
+            chat_template=chat_template_string,
+            tokenize=False,
+        )
+        rejected_strip_index = result["rejected"].find(rejected_response["content"])
+        result["rejected"] = result["rejected"][rejected_strip_index:].rstrip()
+
+        return result
+
+    return transform_fn, {"remove_columns": [field_chosen, field_rejected]}

tests/prompt_strategies/test_dpo_chat_templates.py

@@ -8,7 +8,7 @@
 from datasets import Dataset
 from transformers import AutoTokenizer
 
-from axolotl.prompt_strategies.dpo.chat_template import default
+from axolotl.prompt_strategies.dpo.chat_template import argilla_chat, default
 from axolotl.utils.dict import DictDefault
 
 from tests.hf_offline_utils import enable_hf_offline
@@ -78,6 +78,36 @@ def fixture_custom_assistant_dataset():
     )
 
 
+@pytest.fixture(name="argilla_chat_dataset")
+def fixture_argilla_chat_dataset():
+    return Dataset.from_list(
+        [
+            {
+                "chosen": [
+                    {
+                        "role": "user",
+                        "content": "hello",
+                    },
+                    {
+                        "role": "assistant",
+                        "content": "goodbye",
+                    },
+                ],
+                "rejected": [
+                    {
+                        "role": "user",
+                        "content": "hello",
+                    },
+                    {
+                        "role": "assistant",
+                        "content": "party on",
+                    },
+                ],
+            }
+        ]
+    )
+
+
 @pytest.fixture(name="phi3_tokenizer")
 @enable_hf_offline
 def fixture_phi3_tokenizer():
@@ -216,5 +246,51 @@ def test_gemma_defaults(self, gemma_tokenizer, assistant_dataset):
         assert result["rejected"] == "party on<end_of_turn>"
 
 
+class TestArgillaChatDPOChatTemplate:
+    """
+    Test class for argilla_chat style datasets (chosen/rejected contain full conversations).
+    """
+
+    def test_llama3_argilla_chat(self, llama3_tokenizer, argilla_chat_dataset):
+        transform_fn, _ = argilla_chat(
+            DictDefault(
+                {
+                    "chat_template": "llama3",
+                    "datasets": [
+                        {
+                            "type": "chat_template.argilla_chat",
+                        }
+                    ],
+                }
+            )
+        )
+        result = transform_fn(argilla_chat_dataset[0], tokenizer=llama3_tokenizer)
+        assert result["prompt"] == (
+            "<|begin_of_text|>"
+            + "<|start_header_id|>user<|end_header_id|>\n\nhello<|eot_id|>"
+            + "<|start_header_id|>assistant<|end_header_id|>\n\n"
+        )
+        assert result["chosen"] == "goodbye<|eot_id|>"
+        assert result["rejected"] == "party on<|eot_id|>"
+
+    def test_phi3_argilla_chat(self, phi3_tokenizer, argilla_chat_dataset):
+        transform_fn, _ = argilla_chat(
+            DictDefault(
+                {
+                    "chat_template": "tokenizer_default",
+                    "datasets": [
+                        {
+                            "type": "chat_template.argilla_chat",
+                        }
+                    ],
+                }
+            )
+        )
+        result = transform_fn(argilla_chat_dataset[0], tokenizer=phi3_tokenizer)
+        assert result["prompt"] == "<|user|>\nhello<|end|>\n" + "<|assistant|>\n"
+        assert result["chosen"] == "goodbye<|end|>"
+        assert result["rejected"] == "party on<|end|>"
+
+
 if __name__ == "__main__":
     unittest.main()