refactor: pdf2image example (#778)

Co-authored-by: Diptanu Choudhury <diptanuc@gmail.com>

examples/pdf/image/README.md

@@ -1,15 +1,19 @@
 # PDF Image Extraction with Indexify
 
+This example shows how to extract images frm a pdf using Indexify. If you haven't already please read the [Getting Started](https://docs.getindexify.ai/getting_started/) guide to get acquinted with usage of Indexify,
+
 Pipeline to extract images from PDF. The pipeline uses - 
+1. tensorlake/pdfextractor to extract images from PDFs.
+We provide a script that downloads a PDF, uploads it to Indexify, and retrieves the extracted images.
 
-1. `tensorlake/pdfextractor` to extract images from PDFs.
+| Sample Page |
+|:-----------:|
+| <img src="https://docs.getindexify.ai/example_code/pdf/image/2310.06825v1_page-0004.jpg" width="600"/> |
 
-We provide a script that downloads a PDF, uploads it to Indexify, and retrieves the extracted images.
+Source: [https://arxiv.org/pdf/2310.06825.pdf](https://arxiv.org/pdf/2310.06825.pdf)
 
 ## Prerequisites
-
 Before we begin, ensure you have the following:
-
 - Create a virtual env with Python 3.9 or later
   ```shell
   python3.9 -m venv ve
@@ -19,56 +23,124 @@ Before we begin, ensure you have the following:
 - Required Python packages: `indexify`, `requests`
 
 ## Setup
-
 1. Install Indexify:
    ```bash
    curl https://getindexify.ai | sh
    ./indexify server -d
    ```
 
-3. Install the required extractor:
+2. Install the required extractor:
    ```bash
    pip install indexify-extractor-sdk
    indexify-extractor download tensorlake/pdfextractor
    indexify-extractor join-server
    ```
 
 ## File Descriptions
-
 1. `setup_graph.py`: This script sets up the extraction graph for converting PDFs to images.
-
 2. `upload_and_retreive.py`: This script downloads a PDF, uploads it to Indexify, and retrieves the extracted images.
 
 ## Usage
+1. First, run the [setup_graph.py](https://github.com/tensorlakeai/indexify/blob/main/examples/pdf/image/setup_graph.py) script to set up the extraction graph:
+
+```python
+from indexify import IndexifyClient, ExtractionGraph
+client = IndexifyClient()
+extraction_graph_spec = """
+name: 'image_extractor'
+extraction_policies:
+  - extractor: 'tensorlake/pdfextractor'
+    name: 'pdf_to_image'
+    input_params:
+      output_types: ["image"]
+"""
+extraction_graph = ExtractionGraph.from_yaml(extraction_graph_spec)
+client.create_extraction_graph(extraction_graph)
+```
+
+This script creates an ExtractionGraph and defines the extraction policy for PDF to image conversion.
 
-1. First, run the [`setup_graph.py`](https://github.com/tensorlakeai/indexify/blob/main/examples/pdf/image/setup_graph.py) script to set up the extraction graph:
    ```bash
    python setup_graph.py
    ```
 
-2. Then, run the [`upload_and_retrieve.py`](https://github.com/tensorlakeai/indexify/blob/main/examples/pdf/image/upload_and_retrieve.py) script to process a PDF and extract images:
+
+
+2. Then, run the [upload_and_retrieve.py](https://github.com/tensorlakeai/indexify/blob/main/examples/pdf/image/upload_and_retrieve.py) script to process a PDF and extract images:
+
+```python
+import os
+import requests
+from indexify import IndexifyClient
+
+def download_pdf(url, save_path):
+    response = requests.get(url)
+    with open(save_path, 'wb') as f:
+        f.write(response.content)
+    print(f"PDF downloaded and saved to {save_path}")
+
+def get_images(pdf_path):
+    client = IndexifyClient()
+
+    # Upload the PDF file
+    content_id = client.upload_file("image_extractor", pdf_path)
+
+    # Wait for the extraction to complete
+    client.wait_for_extraction(content_id)
+
+    # Retrieve the images content
+    images = client.get_extracted_content(
+        content_id=content_id,
+        graph_name="image_extractor",
+        policy_name="pdf_to_image"
+    )
+
+    return images
+
+# Example usage
+if __name__ == "__main__":
+    pdf_url = "https://arxiv.org/pdf/2310.06825.pdf"
+    pdf_path = "reference_document.pdf"
+
+    # Download the PDF
+    download_pdf(pdf_url, pdf_path)
+
+    # Get images from the PDF
+    images = get_images(pdf_path)
+    for image in images:
+        content_id = image["id"]
+        with open(f"{content_id}.png", 'wb') as f:
+            print("writing image ", image["id"])
+            f.write(image["content"])
+```
+
+This script downloads a PDF, uploads it to Indexify, extracts images, and saves them locally.
+
    ```bash
    python upload_and_retrieve.py
    ```
+
    Sample Page to extract image from:
    <img src="https://raw.githubusercontent.com/tensorlakeai/indexify/main/examples/pdf/image/2310.06825v1_page-0004.jpg" width="600"/>
    Sample Image extracted from page:
    <img src="https://raw.githubusercontent.com/tensorlakeai/indexify/main/examples/pdf/image/5561f24377d1c264.png" width="600"/>
 
-   This script will:
-   - Download a sample PDF from arXiv
-   - Upload the PDF to Indexify
-   - Extract images from the PDF
-   - Print the extracted image content
+| Extracted Image |
+|:---------------:|
+| <img src="https://docs.getindexify.ai/example_code/pdf/image/5561f24377d1c264.png" width="600"/> |
 
-## Customization
+This script will:
+- Download a sample PDF from arXiv
+- Upload the PDF to Indexify
+- Extract images from the PDF
+- Print the extracted image content
 
-You can customize the image extraction process by modifying the `extraction_graph_spec` in `setup_graph.py`. For example, you could add additional extraction steps or change the output format.
+## Customization
+You can customize the image extraction process by modifying the extraction_graph_spec in `setup_graph.py`. For example, you could add additional extraction steps or change the output format.
 
 In `upload_and_retrieve.py`, you can modify the `pdf_url` variable to process different PDF documents.
 
 ## Conclusion
-
 This project demonstrates the power and flexibility of Indexify for extracting images from PDF documents. While this example focuses on image extraction, Indexify can be used for various other document processing tasks, making it a versatile tool for handling large volumes of documents efficiently.
 
 For more information on Indexify and its capabilities, visit the [official documentation](https://docs.getindexify.ai).