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vLLM: Move from guided_options_request to structured_outputs #1805

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vLLM: Move from guided_options_request to structured_outputs #1805

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54e9592
vLLM: Move from guided_options_request to structured_outputs
suryabdev Oct 10, 2025
461235a
Pin vLLM version to >= 0.10.2
suryabdev Oct 10, 2025
cf4f9e2
make style
suryabdev Oct 11, 2025
2ed70fa
Merge branch 'main' into fix-1794
suryabdev Oct 16, 2025
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2 changes: 1 addition & 1 deletion pyproject.toml
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Original file line number Diff line number Diff line change
Expand Up @@ -81,7 +81,7 @@ vision = [
"selenium",
]
vllm = [
"vllm",
"vllm>=0.10.2",
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We could add some version control logic like the following

json_schema = response_format["json_schema"]["schema"]
if parse(vllm.__version__) >= parse("0.10.2"):
    from vllm.outputs import StructuredOutputsParams
    if response_format:
        structured_outputs = StructuredOutputsParams(json=json_schema)
else:
    if response_format:       
        guided_options_request = {"guided_json": json_schema}

But I think that adds unnecessary complexity. Might be simpler to just force the version to be >= 0.10.2

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@suryabdev suryabdev Oct 10, 2025 •
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Tested with vLLM 0.10.0, With the new code it will break
image

"torch"
]
all = [
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5 changes: 3 additions & 2 deletions src/smolagents/models.py
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Original file line number Diff line number Diff line change
Expand Up @@ -623,6 +623,7 @@ def generate(
**kwargs,
) -> ChatMessage:
from vllm import SamplingParams # type: ignore
from vllm.sampling_params import StructuredOutputsParams # type: ignore

completion_kwargs = self._prepare_completion_kwargs(
messages=messages,
Expand All @@ -632,7 +633,7 @@ def generate(
**kwargs,
)
# Override the OpenAI schema for VLLM compatibility
guided_options_request = {"guided_json": response_format["json_schema"]["schema"]} if response_format else None
structured_outputs = StructuredOutputsParams(json=response_format["json_schema"]["schema"]) if response_format else None
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@qjflores suggested a fix when he opened the issue,

# Convert old guided_options_request format to new structured_outputs
    structured_outputs_params = None
    if response_format:
        if "json_schema" in response_format:
            # Extract the JSON schema from the response_format
            json_schema = response_format["json_schema"]["schema"]
            structured_outputs_params = StructuredOutputsParams(json=json_schema)
        elif "choice" in response_format:
            # Handle choice-based structured outputs
            structured_outputs_params = StructuredOutputsParams(choice=response_format["choice"])
        elif "regex" in response_format:
            # Handle regex-based structured outputs
            structured_outputs_params = StructuredOutputsParams(regex=response_format["regex"])
        elif "grammar" in response_format:
            # Handle grammar-based structured outputs
            structured_outputs_params = StructuredOutputsParams(grammar=response_format["grammar"])
        elif "structural_tag" in response_format:
            # Handle structural tag-based structured outputs
            structured_outputs_params = StructuredOutputsParams(structural_tag=response_format["structural_tag"])
        else:
            print(f"WARNING: Unsupported response_format type: {response_format}")
            structured_outputs_params = None

But if I understand correctly, JSON is the only structured output param that is used

smolagents/src/smolagents/agents.py

Line 1631 in f042c0c

additional_args["response_format"] = CODEAGENT_RESPONSE_FORMAT

CODEAGENT_RESPONSE_FORMAT description

smolagents/src/smolagents/models.py

Line 41 in f042c0c

"json_schema": {

So I simplified his solution and incorporated it in the PR

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makes sense to me


messages = completion_kwargs.pop("messages")
prepared_stop_sequences = completion_kwargs.pop("stop", [])
Expand All @@ -651,12 +652,12 @@ def generate(
temperature=kwargs.get("temperature", 0.0),
max_tokens=kwargs.get("max_tokens", 2048),
stop=prepared_stop_sequences,
structured_outputs=structured_outputs,
)

out = self.model.generate(
prompt,
sampling_params=sampling_params,
guided_options_request=guided_options_request,
**completion_kwargs,
)

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