Better regex for structured decoding, adding some new prompts to train with

olmocr/pipeline.py

@@ -238,7 +238,7 @@ async def process_page(args, worker_id: int, pdf_orig_path: str, pdf_local_path:
 
         # Enable guided decoding regex if needed
         if args.guided_decoding:
-            query["guided_regex"] = r"---\nprimary_language: .*\nis_rotation_valid: .*\nrotation_correction: .*\nis_table: .*\nis_diagram: .*\n---\n[\s\S]*"
+            query["guided_regex"] = r"---\nprimary_language: .{1,20}\nis_rotation_valid: (?:True|False|true|false)\nrotation_correction:(?:0|90|180|270)\nis_table: (?:True|False|true|false)\nis_diagram: (?:True|False|true|false)\n---\n[\s\S]*"
 
         logger.info(f"Built page query for {pdf_orig_path}-{page_num}")
 

olmocr/train/config.py

@@ -48,6 +48,20 @@ class FinetuningPromptConfig(PipelineStepConfig):
     name: str = "FinetuningPrompt"
 
 
+@dataclass
+class NewYamlFinetuningPromptWithAnchoringConfig(PipelineStepConfig):
+    """Configuration for NewYamlFinetuningPromptWithAnchoring step."""
+
+    name: str = "NewYamlFinetuningPromptWithAnchoring"
+
+
+@dataclass
+class NewYamlFinetuningPromptWithNoAnchoringConfig(PipelineStepConfig):
+    """Configuration for NewYamlFinetuningPromptWithNoAnchoring step."""
+
+    name: str = "NewYamlFinetuningPromptWithNoAnchoring"
+
+
 @dataclass
 class FrontMatterOutputFormatConfig(PipelineStepConfig):
     """Configuration for FrontMatterOutputFormat step."""
@@ -282,6 +296,8 @@ class Config:
             FrontMatterOutputFormat,
             FrontMatterParser,
             InstructUserMessages,
+            NewYamlFinetuningPromptWithAnchoring,
+            NewYamlFinetuningPromptWithNoAnchoring,
             PDFRenderer,
             StaticLengthDocumentAnchoring,
             Tokenizer,
@@ -313,6 +329,12 @@ class Config:
             elif step_name == "FinetuningPrompt":
                 steps.append(FinetuningPrompt())
 
+            elif step_name == "NewYamlFinetuningPromptWithAnchoring":
+                steps.append(NewYamlFinetuningPromptWithAnchoring())
+
+            elif step_name == "NewYamlFinetuningPromptWithNoAnchoring":
+                steps.append(NewYamlFinetuningPromptWithNoAnchoring())
+
             elif step_name == "FrontMatterOutputFormat":
                 steps.append(FrontMatterOutputFormat())
 

olmocr/train/dataloader.py

@@ -286,6 +286,33 @@ class FinetuningPrompt(PipelineStep):
     def __call__(self, sample: Sample) -> Sample:
         sample["instruction_prompt"] = build_finetuning_prompt(sample["anchor_text"])
         return sample
+    
+
+@dataclass(frozen=True, slots=True)
+class NewYamlFinetuningPromptWithAnchoring(PipelineStep):
+    """Applies the standard fine tuning prompt"""
+
+    def __call__(self, sample: Sample) -> Sample:
+        sample["instruction_prompt"] = (
+            f"Attached is one page of a document, as well as some raw textual content that was previously extracted for it. "
+            f"Just return the plain text representation of this document as if you were reading it naturally. Convert equations to LateX and tables to markdown.\n"
+            f"RAW_TEXT_START\n{sample['anchor_text']}\nRAW_TEXT_END\n"
+            f"Return your output as markdown, with a front matter section on top specifying values for the primary_language, is_rotation_valid, rotation_correction, is_table, and is_diagram parameters."
+        )
+        return sample
+
+
+@dataclass(frozen=True, slots=True)
+class NewYamlFinetuningPromptWithNoAnchoring(PipelineStep):
+    """Applies the standard fine tuning prompt"""
+
+    def __call__(self, sample: Sample) -> Sample:
+        sample["instruction_prompt"] = (
+            f"Attached is one page of a document that you must process. "
+            f"Just return the plain text representation of this document as if you were reading it naturally. Convert equations to LateX and tables to markdown.\n"
+            f"Return your output as markdown, with a front matter section on top specifying values for the primary_language, is_rotation_valid, rotation_correction, is_table, and is_diagram parameters."
+        )
+        return sample
 
 
 @dataclass(frozen=True, slots=True)