DSPy Gemma Weirdness

adapter_repro.py

import dspy
from pydantic import BaseModel

model = "lm_studio/gemma-3-27b-it"
lm = dspy.LM(model, api_key='')
dspy.configure(lm=lm)

class Sentence(BaseModel):
    sentence: str
    index: str

class SplitSentences(dspy.Signature):
    input: str = dspy.InputField()
    output: list[Sentence] = dspy.OutputField()

math = dspy.Predict(SplitSentences)

print(f"model = {model}")
print(math(input="This is sentence one. This is sentence two. This is sentence three."))

base.py

# dspy/adapters/base.py
class Adapter:
  ...
 def __call__(
        self,
        lm: "LM",
        lm_kwargs: dict[str, Any],
        signature: Type[Signature],
        demos: list[dict[str, Any]],
        inputs: dict[str, Any],
    ) -> list[dict[str, Any]]:
        # Monkey patched print calls to get above logs. 
        inputs = self.format(signature, demos, inputs)
        print(f"inputs: {inputs}")
        outputs = lm(messages=inputs, **lm_kwargs)
        print(f"outputs: {outputs}")
        return self._call_post_process(outputs, signature)

logs

model = lm_studio/gemma-3-27b-it
inputs: [{'role': 'system', 'content': 'Your input fields are:\n1. `input` (str)\nYour output fields are:\n1. `output` (list[Sentence])\nAll interactions will be structured in the following way, with the appropriate values filled in.\n\n[[ ## input ## ]]\n{input}\n\n[[ ## output ## ]]\n{output}        # note: the value you produce must adhere to the JSON schema: {"type": "array", "$defs": {"Sentence": {"type": "object", "properties": {"index": {"type": "string", "title": "Index"}, "sentence": {"type": "string", "title": "Sentence"}}, "required": ["sentence", "index"], "title": "Sentence"}}, "items": {"$ref": "#/$defs/Sentence"}}\n\n[[ ## completed ## ]]\nIn adhering to this structure, your objective is: \n        Given the fields `input`, produce the fields `output`.'}, {'role': 'user', 'content': '[[ ## input ## ]]\nThis is sentence one. This is sentence two. This is sentence three.\n\nRespond with the corresponding output fields, starting with the field `[[ ## output ## ]]` (must be formatted as a valid Python list[Sentence]), and then ending with the marker for `[[ ## completed ## ]]`.'}]
outputs: ['```json\n[\n  {\n    "index": "1",\n    "sentence": "This is sentence one."\n  },\n  {\n    "index": "2",\n    "sentence": "This is sentence two."\n  },\n  {\n    "index": "3",\n    "sentence": "This is sentence three."\n  }\n]\n```']