nuextract3: add --instructions for chat_template_kwargs.instructions
Browse filesExposes NuExtract3's `instructions` chat-template kwarg, a free-text
steering lever for output formats and routing across union/optional
schema branches. Mirrors the existing `--enable-thinking` passthrough:
new arg, plumbed via main() into chat_template_kwargs only when truthy
(no-op when omitted).
Docs: https://huggingface.co/numind/NuExtract3#instructions
Smoke (davanstrien/ufo-ColPali, 3 samples, extraction mode,
template={"title": "string", "author": "string"},
instruction="Prepend 'INSTR-OK::' to the title value"):
sentinel landed in 3/3 extractions.
Teklia French vital-records (58 cards, superset Baptême/Mariage/Décès
template + type_acte enum + French routing instruction): strict
F1 0.281 -> 0.321. Modest; the model partially honours the
branch-null routing (emits empty {} subdicts rather than null for
non-matched branches), which is consistent with NuExtract3's
shape-binding template engine. Per-user instruction tuning lives
downstream of this flag.
- nuextract3.py +18 -0
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@@ -27,6 +27,10 @@ Modes are selected via flags:
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- --template SOURCE -> structured extraction with a NuExtract template
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- --schema SOURCE -> structured extraction with a JSON Schema
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(auto-converted via numind.nuextract_utils)
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--template / --schema each accept inline JSON, a URL, or a local file path, so a
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schema can be hosted (e.g. on an HF dataset's raw URL) and reused across jobs:
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@@ -277,6 +281,7 @@ def main(
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template_arg: Optional[str] = None,
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schema_arg: Optional[str] = None,
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enable_thinking: bool = False,
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temperature: Optional[float] = None,
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model: str = MODEL_DEFAULT,
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hf_token: str = None,
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@@ -351,6 +356,8 @@ def main(
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chat_template_kwargs["template"] = json.dumps(template, indent=4)
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else:
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chat_template_kwargs["mode"] = mode
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logger.info(f"Processing {len(dataset)} images in batches of {batch_size}")
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logger.info(f"Output will be written to column: {output_column}")
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@@ -646,6 +653,16 @@ Examples:
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action="store_true",
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help="Enable reasoning mode (slower, better on hard documents)",
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)
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parser.add_argument(
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"--temperature",
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type=float,
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@@ -712,6 +729,7 @@ Examples:
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template_arg=args.template,
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schema_arg=args.schema,
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enable_thinking=args.enable_thinking,
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temperature=args.temperature,
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model=args.model,
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hf_token=args.hf_token,
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- --template SOURCE -> structured extraction with a NuExtract template
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- --schema SOURCE -> structured extraction with a JSON Schema
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(auto-converted via numind.nuextract_utils)
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- --instructions STR -> free-text guidance passed through to the model
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(output-format rules, branch routing, etc.).
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Combines with any of the modes above.
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See https://huggingface.co/numind/NuExtract3#instructions
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--template / --schema each accept inline JSON, a URL, or a local file path, so a
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schema can be hosted (e.g. on an HF dataset's raw URL) and reused across jobs:
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template_arg: Optional[str] = None,
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schema_arg: Optional[str] = None,
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enable_thinking: bool = False,
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instructions: Optional[str] = None,
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temperature: Optional[float] = None,
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model: str = MODEL_DEFAULT,
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hf_token: str = None,
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chat_template_kwargs["template"] = json.dumps(template, indent=4)
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else:
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chat_template_kwargs["mode"] = mode
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if instructions:
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chat_template_kwargs["instructions"] = instructions
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logger.info(f"Processing {len(dataset)} images in batches of {batch_size}")
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logger.info(f"Output will be written to column: {output_column}")
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action="store_true",
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help="Enable reasoning mode (slower, better on hard documents)",
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)
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parser.add_argument(
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"--instructions",
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default=None,
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help=(
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"Free-text instructions passed to NuExtract via "
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"chat_template_kwargs.instructions (e.g. routing guidance across "
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"optional schema branches, output-format rules). "
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"See https://huggingface.co/numind/NuExtract3#instructions"
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),
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)
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parser.add_argument(
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"--temperature",
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type=float,
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template_arg=args.template,
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schema_arg=args.schema,
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enable_thinking=args.enable_thinking,
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instructions=args.instructions,
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temperature=args.temperature,
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model=args.model,
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hf_token=args.hf_token,
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