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feat(vlm): upgrade Granite Vision model to 4.1 for table + chart extraction (#3382)
* feat(table-structure): swap VLM model to granite-vision-4.1-4b Updates GraniteVisionTableStructureModel to use the 4.1 model. The 4.1 weights are pre-merged, so merge_lora_adapters() is now hasattr-guarded. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> Signed-off-by: Eli Schwartz <eliyahu.schwartz@ibm.com> * feat(chart-extraction): swap V4 VLM model to granite-vision-4.1-4b Updates ChartExtractionModelGraniteVisionV4 to use the 4.1 model. hasattr-guards the merge_lora_adapters() call since 4.1 weights are pre-merged. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> Signed-off-by: Eli Schwartz <eliyahu.schwartz@ibm.com> * docs(example): mention granite-vision-4.1-4b in table-structure example Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> Signed-off-by: Eli Schwartz <eliyahu.schwartz@ibm.com> * docs(catalog): update Granite Vision entry to 4.1-4b Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> Signed-off-by: Eli Schwartz <eliyahu.schwartz@ibm.com> * feat(chart-extraction): honor cuda_use_flash_attention2 in V4 loader Mirrors the table-structure loader so ChartExtractionModelGraniteVisionV4 also passes _attn_implementation based on AcceleratorOptions. Without this the chart model falls back to the transformers SDPA default, which can hit cuDNN backend failures on some torch/cuDNN stacks while the table model (which already passed the flag) runs cleanly. Stores accelerator_options on the base class so subclasses can read it. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> Signed-off-by: Eli Schwartz <eliyahu.schwartz@ibm.com> * fix(model-downloader): update Granite Vision log message to 4.1 The log message in download_models still mentioned "Granite Vision 4.0" after the model swap. Correct it to match the current model version. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> Signed-off-by: Eli Schwartz <eliyahu.schwartz@ibm.com> * fix(chart-extraction): fall back to bare CSV when V4 model omits ```csv``` fence granite-vision-4.1-4b sometimes emits raw CSV without a ```csv``` code fence for the <chart2csv> prompt, which caused _extract_csv_to_dataframe to raise ValueError and drop the chart's tabular_chart metadata. Mirror the tolerant parsing already used by the v3 class: prefer a fenced block, otherwise strip any stray backtick prefix/suffix and parse the text as-is. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> Signed-off-by: Eli Schwartz <eliyahu.schwartz@ibm.com> --------- Signed-off-by: Eli Schwartz <eliyahu.schwartz@ibm.com> Co-authored-by: Eli Schwartz <eliyahu.schwartz@ibm.com> Co-authored-by: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
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@@ -54,6 +54,7 @@ class _BaseChartExtractionModelGraniteVision(BaseItemAndImageEnrichmentModel):
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):
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self.enabled = enabled
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self.options = options
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self.accelerator_options = accelerator_options
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if self.enabled:
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self.device = decide_device(
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@@ -338,9 +339,9 @@ class ChartExtractionModelGraniteVision(_BaseChartExtractionModelGraniteVision):
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class ChartExtractionModelGraniteVisionV4(_BaseChartExtractionModelGraniteVision):
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_model_repo_folder = "ibm-granite--granite-4.0-3b-vision"
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_model_repo_id = "ibm-granite/granite-4.0-3b-vision"
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_model_repo_revision = "f0d034897bae1cd438c961c8c170a3a3089ebf01"
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_model_repo_folder = "ibm-granite--granite-vision-4.1-4b"
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_model_repo_id = "ibm-granite/granite-vision-4.1-4b"
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_model_repo_revision = "dd48e97503de471803850df70843cf9eb5da8712"
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def _load_model(self, artifacts_path: Path) -> None:
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with warnings.catch_warnings():
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@@ -363,9 +364,16 @@ class ChartExtractionModelGraniteVisionV4(_BaseChartExtractionModelGraniteVision
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artifacts_path,
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device_map=self.device,
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dtype=torch.bfloat16,
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_attn_implementation=(
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"flash_attention_2"
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if self.device.startswith("cuda")
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and self.accelerator_options.cuda_use_flash_attention2
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else "sdpa"
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),
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trust_remote_code=True,
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)
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cast(Any, self._model).merge_lora_adapters()
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if hasattr(self._model, "merge_lora_adapters"):
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cast(Any, self._model).merge_lora_adapters()
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self._model.eval()
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def __call__(
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@@ -475,11 +483,15 @@ class ChartExtractionModelGraniteVisionV4(_BaseChartExtractionModelGraniteVision
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yield item
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def _extract_csv_to_dataframe(self, decoded_text: str) -> pd.DataFrame:
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# decoded_text is already the raw generated output (no conversation wrapper)
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# decoded_text is already the raw generated output (no conversation wrapper).
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# Prefer a fenced ```csv ... ``` block, but fall back to bare CSV if the
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# model omits the fence (observed with granite-vision-4.1-4b).
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csv_match = re.search(r"```csv\s*\n(.*?)\n```", decoded_text, re.DOTALL)
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if not csv_match:
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raise ValueError("No ```csv``` block found in model output")
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csv_content = csv_match.group(1).strip()
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if csv_match:
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csv_content = csv_match.group(1).strip()
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else:
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csv_content = re.sub(r"^```+(?:csv)?\s*", "", decoded_text.strip())
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csv_content = re.sub(r"```+\s*$", "", csv_content).strip()
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try:
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return pd.read_csv(StringIO(csv_content), header=None)
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except Exception as e:
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@@ -140,11 +140,11 @@ def _parse_otsl_output(
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class GraniteVisionTableStructureModel(BaseTableStructureModel):
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"""Table structure model using ibm-granite/granite-4.0-3b-vision with <tables_otsl>."""
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"""Table structure model using ibm-granite/granite-vision-4.1-4b with <tables_otsl>."""
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_model_repo_id: ClassVar[str] = "ibm-granite/granite-4.0-3b-vision"
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_model_repo_folder: ClassVar[str] = "ibm-granite--granite-4.0-3b-vision"
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_model_repo_revision: ClassVar[str] = "f0d034897bae1cd438c961c8c170a3a3089ebf01"
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_model_repo_id: ClassVar[str] = "ibm-granite/granite-vision-4.1-4b"
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_model_repo_folder: ClassVar[str] = "ibm-granite--granite-vision-4.1-4b"
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_model_repo_revision: ClassVar[str] = "dd48e97503de471803850df70843cf9eb5da8712"
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def __init__(
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self,
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@@ -224,7 +224,8 @@ class GraniteVisionTableStructureModel(BaseTableStructureModel):
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),
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trust_remote_code=True,
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)
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cast(Any, self._model).merge_lora_adapters()
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if hasattr(self._model, "merge_lora_adapters"):
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cast(Any, self._model).merge_lora_adapters()
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self._model.eval()
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def predict_tables(
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@@ -174,7 +174,7 @@ def download_models(
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)
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if with_granite_chart_extraction_v4:
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_log.info("Downloading Granite Vision 4.0 Charts Extraction model...")
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_log.info("Downloading Granite Vision 4.1 Charts Extraction model...")
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ChartExtractionModelGraniteVisionV4.download_models(
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local_dir=output_dir
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/ ChartExtractionModelGraniteVisionV4._model_repo_folder,
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+1
-1
@@ -17,7 +17,7 @@
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# - Defaults to `tests/data/pdf/2206.01062.pdf`. Change `input_doc_path` as needed.
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#
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# Notes
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# - The Granite Vision model (`ibm-granite/granite-4.0-3b-vision`) is downloaded
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# - The Granite Vision model (`ibm-granite/granite-vision-4.1-4b`) is downloaded
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# automatically from HuggingFace on first run.
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# - The model outputs table structure in OTSL (Open Table Structure Language) format,
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# which Docling parses into structured table cells.
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Vendored
+1
-1
@@ -88,7 +88,7 @@ The following table shows all processing stages in Docling, their model families
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<td rowspan="3">Vision-Language Model<br/>(Granite Vision)</td>
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<td>
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<ul>
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<li><code>granite-4.0-3b-vision</code></li>
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<li><code>granite-vision-4.1-4b</code></li>
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</ul>
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</td>
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</tr>
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