Update README.md

README.md

@@ -94,101 +94,35 @@ generated_texts = processor.batch_decode(
 print(generated_texts[0])
 ```
 
-#### Docling:
+#### Using Docling Example [here]() 
 
 
-```python
-import json
-import time
-from pathlib import Path
-
-import yaml
-
-from docling.datamodel.base_models import InputFormat
-from docling.datamodel.pipeline_options import SmolDoclingOptions, VlmPipelineOptions
-from docling.document_converter import DocumentConverter, PdfFormatOption
-from docling.pipeline.vlm_pipeline import VlmPipeline
-
-sources = [
-    # "https://arxiv.org/pdf/2408.09869",
-    "tests/data/2305.03393v1-pg9-img.png",
-    # "tests/data/2305.03393v1-pg9.pdf",
-]
-
-pipeline_options = VlmPipelineOptions()  # artifacts_path="~/local_model_artifacts/"
-pipeline_options.generate_page_images = True
-# If force_backend_text = True, text from backend will be used instead of generated text
-pipeline_options.force_backend_text = False
-
-
-vlm_options = SmolDoclingOptions(
-    # question="Convert this page to docling.",
-    # load_in_8bit=True,
-    # llm_int8_threshold=6.0,
-    # quantized=False,
-)
-
-pipeline_options.vlm_options = vlm_options
-
-from docling_core.types.doc import DocItemLabel, ImageRefMode
-from docling_core.types.doc.document import DEFAULT_EXPORT_LABELS
-
-converter = DocumentConverter(
-    format_options={
-        InputFormat.PDF: PdfFormatOption(
-            pipeline_cls=VlmPipeline,
-            pipeline_options=pipeline_options,
-        ),
-        InputFormat.IMAGE: PdfFormatOption(
-            pipeline_cls=VlmPipeline,
-            pipeline_options=pipeline_options,
-        ),
-    }
-)
-
-out_path = Path("scratch")
-out_path.mkdir(parents=True, exist_ok=True)
 
-for source in sources:
-    start_time = time.time()
-    print("================================================")
-    print("Processing... {}".format(source))
-    print("================================================")
-    print("")
+## Supported Instructions  
 
-    res = converter.convert(source)
+### 💻 Code  
+  - `Convert code to text`
+  - `<code>`  
 
-    print("------------------------------------------------")
-    print("MD:")
-    print("------------------------------------------------")
-    print("")
-    print(res.document.export_to_markdown())
+### 📊 Chart  
+  - `Convert chart to table.`
+  - `<chart>`  
 
-    # with (out_path / f"{res.input.file.stem}.html").open("w") as fp:
-    #     fp.write(res.document.export_to_html())
+### 🔢 Formula  
+  - `Convert formula to LaTeX.`  
+  - `<formula>`  
 
-    res.document.save_as_html(
-        filename=Path("{}/{}.html".format(out_path, res.input.file.stem)),
-        image_mode=ImageRefMode.REFERENCED,
-        labels=[*DEFAULT_EXPORT_LABELS, DocItemLabel.FOOTNOTE],
-    )
+### 📄 Docling  
+  - `Convert this page to Docling.`  
 
-    with (out_path / f"{res.input.file.stem}.json").open("w") as fp:
-        fp.write(json.dumps(res.document.export_to_dict()))
+### 📑 Table  
+  - `Convert table to OTSL.`  
+  - `<otsl>`  
 
-    with (out_path / f"{res.input.file.stem}.yaml").open("w") as fp:
-        fp.write(yaml.safe_dump(res.document.export_to_dict()))
-
-    pg_num = res.document.num_pages()
-
-    print("")
-    inference_time = time.time() - start_time
-    print(
-        f"Total document prediction time: {inference_time:.2f} seconds, pages: {pg_num}"
-    )
-
-print("================================================")
-print("done!")
-print("================================================")
-```
+### 🛠️ No-Code Actions/Pipelines  
+- `OCR the text in a specific location: <loc_155><loc_233><loc_206><loc_237>`  
+- `Identify element at: <loc_247><loc_482><loc_252><loc_486>`  
+- `Find all 'text' elements on the page.`,  `Retrieve all section headers.` 
+- `Detect footer elements on the page.`
+- More *Coming soon!* 🚧