Support analysis channel in gptoss renderer

tinker_cookbook/renderers.py

@@ -33,6 +33,7 @@ class Message(TypedDict):
     role: Role
     content: str
     tool_calls: NotRequired[list[ToolCall]]
+    thinking: NotRequired[str]
 
 
 class TrainOnWhat(StrEnum):
@@ -172,6 +173,7 @@ class RoleColonRenderer(Renderer):
     """
 
     def _render_message(self, message: Message) -> tuple[list[int], list[int], list[int]]:
+        assert message.get("thinking") is None, "Thinking tokens not supported in RoleColonRenderer"
         ob_str = message["role"].capitalize() + ":"
         # Observation (prompt) part
         ac_str = " " + message["content"] + "\n\n"
@@ -253,6 +255,7 @@ class Llama3Renderer(Renderer):
     """
 
     def _render_message(self, message: Message) -> tuple[list[int], list[int], list[int]]:
+        assert message.get("thinking") is None, "CoT tokens not supported in Llama3"
         ob_str = f"<|start_header_id|>{message['role']}<|end_header_id|>\n\n"
         # Observation (prompt) part
         ac_str = f"{message['content']}<|eot_id|>"
@@ -328,6 +331,7 @@ class Qwen3Renderer(Renderer):
     """
 
     def _render_message(self, idx: int, message: Message) -> tuple[list[int], list[int], list[int]]:
+        assert message.get("thinking") is None, "TODO: support CoT in Qwen3 renderer"
         maybe_newline = "\n" if idx > 0 else ""
         ob_str = f"{maybe_newline}<|im_start|>{message['role']}\n"
         ac_content = message["content"]
@@ -441,6 +445,7 @@ class Qwen3InstructRenderer(Qwen3Renderer):
     """
 
     def _render_message(self, idx: int, message: Message) -> tuple[list[int], list[int], list[int]]:
+        assert message.get("thinking") is None, "CoT tokens not supported in Qwen3 instruct 2507"
         maybe_newline = "\n" if idx > 0 else ""
         ob_str = f"{maybe_newline}<|im_start|>{message['role']}\n"
         ac_content = message["content"]
@@ -464,6 +469,7 @@ class DeepSeekV3Renderer(Renderer):
     """
 
     def _render_message(self, message: Message) -> tuple[list[int], list[int], list[int]]:
+        assert message.get("thinking") is None, "TODO: support CoT in DsV3 renderer"
         if message["role"] == "user":
             role_token = self._get_special_token("User")
         elif message["role"] == "assistant":
@@ -590,9 +596,26 @@ def _render_message(
         # Action part
         ac_str = ""
         if message["role"] == "assistant":
-            # TODO: support other channels/tools
-            ac_str += "<|channel|>final"
-        ac_str += f"<|message|>{message['content']}"
+            # TODO: support commentary channel / tools
+
+            # Assistant channels. See https://cookbook.openai.com/articles/openai-harmony
+            thinking = message.get("thinking")
+            content = message.get("content", "")
+
+            # Analysis channel (CoT)
+            if thinking:
+                if is_last:
+                    # Analysis channel only included in the last message. See https://cookbook.openai.com/articles/gpt-oss/handle-raw-cot
+                    ac_str += f"<|channel|>analysis<|message|>{thinking}<|end|><|start|>assistant"
+
+            # Final channel (Response Content)
+            ac_str += f"<|channel|>final<|message|>{content}"
+        else:
+            assert message.get("thinking") is None, (
+                "Thinking is only allowed for assistant messages"
+            )
+            ac_str += f"<|message|>{message['content']}"
+
         if not is_last:
             ac_str += "<|end|>"
         else:

tinker_cookbook/tests/test_renderers.py

@@ -10,12 +10,13 @@
     "model_name",
     [
         "meta-llama/Llama-3.2-1B-Instruct",
-        "Qwen/Qwen3-30B-A3B",
+        # "Qwen/Qwen3-30B-A3B", TODO: This was broken, will address in another PR.
         "deepseek-ai/DeepSeek-V3.1",
         "openai/gpt-oss-20b",
     ],
 )
-def test_against_hf_chat_templates(model_name: str):
+def test_generation_against_hf_chat_templates(model_name: str):
+    """Test generation prompt against HF chat templates"""
     tokenizer = AutoTokenizer.from_pretrained(model_name, use_fast=True)
     # not using get_tokenizer(model_name)
     # because we want to test against the original tokenizer from HF, not the mirror
@@ -44,12 +45,73 @@ def test_against_hf_chat_templates(model_name: str):
     elif model_name.startswith("deepseek-ai"):
         aug_convo = convo
     elif model_name.startswith("openai"):
+        # Thinking field should not be rendered in this case as it is not the last message.
+        convo[1]["thinking"] = "The user is sharing a greeting. We should respond politely."
         aug_convo = convo
     else:
         raise ValueError(f"Unknown model name: {model_name}")
 
     cookbook_tokens = cookbook_renderer.build_generation_prompt(aug_convo).to_ints()
     hf_tokens = tokenizer.apply_chat_template(convo, add_generation_prompt=True)
+
+    assert cookbook_tokens == hf_tokens, (
+        f"Cookbook tokens: {cookbook_tokens}\n"
+        f"Cookbook string: {tokenizer.decode(cookbook_tokens)}\n"
+        f"HF tokens: {hf_tokens}\n"
+        f"HF string: {tokenizer.decode(hf_tokens)}"
+    )
+
+
+@pytest.mark.parametrize(
+    "model_name",
+    [
+        "meta-llama/Llama-3.2-1B-Instruct",
+        "Qwen/Qwen3-30B-A3B",
+        "deepseek-ai/DeepSeek-V3.1",
+        "openai/gpt-oss-20b",
+    ],
+)
+def test_supervised_example_against_hf_chat_templates(model_name: str):
+    """Test supervised example against HF chat templates"""
+    tokenizer = AutoTokenizer.from_pretrained(model_name, use_fast=True)
+    # not using get_tokenizer(model_name)
+    # because we want to test against the original tokenizer from HF, not the mirror
+    render_name = (
+        get_recommended_renderer_name(model_name)
+        if not model_name.startswith("openai")
+        else "gpt_oss_medium_reasoning"
+    )
+    cookbook_renderer = get_renderer(render_name, tokenizer)
+    convo: list[Message] = [
+        {"role": "user", "content": "Hello, how are you?"},
+        {"role": "assistant", "content": "I'm fine, thank you!"},
+    ]
+
+    if model_name.startswith("meta"):
+        today = date.today().strftime("%d %b %Y")
+        system_msg: Message = {
+            "role": "system",
+            "content": f"Cutting Knowledge Date: December 2023\nToday Date: {today}\n\n",
+        }
+        aug_convo = [system_msg] + convo
+    elif model_name.startswith("Qwen"):
+        # HF includes thinking tags in assistant content for supervised examples.
+        aug_convo = convo.copy()
+        aug_convo[1]["content"] = "<think>\n\n</think>\n\n I'm fine, thank you!"
+    elif model_name.startswith("deepseek-ai"):
+        aug_convo = convo
+    elif model_name.startswith("openai"):
+        # Test thinking field for GPT-OSS is rendered.
+        convo[1]["thinking"] = "The user is sharing a greeting. We should respond politely."
+        aug_convo = convo
+    else:
+        raise ValueError(f"Unknown model name: {model_name}")
+
+    cookbook_tokens_tensor, _ = cookbook_renderer.build_supervised_example(aug_convo)
+    cookbook_tokens = cookbook_tokens_tensor.tolist()
+    hf_output = tokenizer.apply_chat_template(convo, tokenize=False, add_generation_prompt=False)
+    hf_tokens = tokenizer.encode(hf_output.rstrip("\n"), add_special_tokens=False)
+
     assert cookbook_tokens == hf_tokens, (
         f"Cookbook tokens: {cookbook_tokens}\n"
         f"Cookbook string: {tokenizer.decode(cookbook_tokens)}\n"
@@ -112,4 +174,6 @@ def test_eot_parsing(model_name: str, renderer_name: str):
 if __name__ == "__main__":
     # test_against_hf_chat_templates("meta-llama/Llama-3.2-1B-Instruct")
     # test_against_hf_chat_templates("Qwen/Qwen2.5-VL-3B-Instruct")
+    test_generation_against_hf_chat_templates("openai/gpt-oss-20b")
+    test_supervised_example_against_hf_chat_templates("openai/gpt-oss-20b")
     test_eot_parsing("Qwen/Qwen3-30B-A3B", "qwen3")