community: ZeroxPDFLoader (#27800)

# OCR-based PDF loader

This implements [Zerox](https://github.com/getomni-ai/zerox) PDF
document loader.
Zerox utilizes simple but very powerful (even though slower and more
costly) approach to parsing PDF documents: it converts PDF to series of
images and passes it to a vision model requesting the contents in
markdown.

It is especially suitable for complex PDFs that are not parsed well by
other alternatives.

## Example use:
```python
from langchain_community.document_loaders.pdf import ZeroxPDFLoader

os.environ["OPENAI_API_KEY"] = "" ## your-api-key

model = "gpt-4o-mini" ## openai model
pdf_url = "https://assets.ctfassets.net/f1df9zr7wr1a/soP1fjvG1Wu66HJhu3FBS/034d6ca48edb119ae77dec5ce01a8612/OpenAI_Sacra_Teardown.pdf"

loader = ZeroxPDFLoader(file_path=pdf_url, model=model)
docs = loader.load()
```

The Zerox library supports wide range of provides/models. See Zerox
documentation for details.

- **Dependencies:** `zerox`
- **Twitter handle:** @martintriska1

If no one reviews your PR within a few days, please @-mention one of
baskaryan, efriis, eyurtsev, ccurme, vbarda, hwchase17.

---------

Co-authored-by: Erick Friis <erickfriis@gmail.com>

libs/community/langchain_community/document_loaders/pdf.py

@@ -945,5 +945,82 @@ class DocumentIntelligenceLoader(BasePDFLoader):
         yield from self.parser.parse(blob)
 
 
+class ZeroxPDFLoader(BasePDFLoader):
+    """
+    Document loader utilizing Zerox library:
+    https://github.com/getomni-ai/zerox
+
+    Zerox converts PDF document to serties of images (page-wise) and
+    uses vision-capable LLM model to generate Markdown representation.
+
+    Zerox utilizes anyc operations. Therefore when using this loader
+    inside Jupyter Notebook (or any environment running async)
+    you will need to:
+    ```python
+        import nest_asyncio
+        nest_asyncio.apply()
+    ```
+    """
+
+    def __init__(
+        self,
+        file_path: Union[str, Path],
+        model: str = "gpt-4o-mini",
+        **zerox_kwargs: Any,
+    ) -> None:
+        super().__init__(file_path=file_path)
+        """
+        Initialize the parser with arguments to be passed to the zerox function.
+        Make sure to set necessary environmnet variables such as API key, endpoint, etc.
+        Check zerox documentation for list of necessary environment variables for
+        any given model.
+
+        Args:
+            file_path:
+                Path or url of the pdf file
+            model:
+                Vision capable model to use. Defaults to "gpt-4o-mini".
+                Hosted models are passed in format "<provider>/<model>"
+                Examples: "azure/gpt-4o-mini", "vertex_ai/gemini-1.5-flash-001"
+                          See more details in zerox documentation.
+            **zerox_kwargs: 
+                Arguments specific to the zerox function.
+                see datailed list of arguments here in zerox repository:
+                https://github.com/getomni-ai/zerox/blob/main/py_zerox/pyzerox/core/zerox.py#L25
+        """  # noqa: E501
+        self.zerox_kwargs = zerox_kwargs
+        self.model = model
+
+    def lazy_load(self) -> Iterator[Document]:
+        """
+        Loads documnts from pdf utilizing zerox library:
+        https://github.com/getomni-ai/zerox
+
+        Returns:
+            Iterator[Document]: An iterator over parsed Document instances.
+        """
+        import asyncio
+
+        from pyzerox import zerox
+
+        # Directly call asyncio.run to execute zerox synchronously
+        zerox_output = asyncio.run(
+            zerox(file_path=self.file_path, model=self.model, **self.zerox_kwargs)
+        )
+
+        # Convert zerox output to Document instances and yield them
+        if len(zerox_output.pages) > 0:
+            num_pages = zerox_output.pages[-1].page
+            for page in zerox_output.pages:
+                yield Document(
+                    page_content=page.content,
+                    metadata={
+                        "source": self.source,
+                        "page": page.page,
+                        "num_pages": num_pages,
+                    },
+                )
+
+
 # Legacy: only for backwards compatibility. Use PyPDFLoader instead
 PagedPDFSplitter = PyPDFLoader