g.py

import os
from google import genai
from pydantic import BaseModel, Field

# create client
client = genai.Client(api_key=os.getenv("GEMINI_API_KEY","xxx"))

class PageText(BaseModel):
    """Represents the content of a page in the PDF document in markdown format."""

    text: str = Field(description="Extracted text of the page in markdown format.")

EXTRACT_MARKDOWN = """
You are given an image of a page from a PDF document.
Your task is to extract the text accurately and convert it into Markdown format, ensuring proper structure and readability.
Requirements:
- Preserve Formatting: Maintain bold, italics, headings, lists, and other structural elements as they appear in the original text.
- Extract Tables: If a table is present and can be accurately extracted, convert it into Markdown table format.
- Charts & Graphics:
    - If the page contains a chart, table, or graphic that cannot be extracted as text, insert a contextually recognizable placeholder where it appears (e.g., [CHART: Sales Performance Q1], [GRAPHIC: Workflow Diagram], [TABLE: Financial Summary]).
    - The placeholder should be descriptive based on the content it represents to ensure easy identification later.
    - Use this format for each placeholder: "[TYPE: Description]" (e.g., [CHART: Sales Performance Q1 - Bar Chart]).
- Accuracy: Ensure correct text extraction without modifying the content.
- No Extra Output: Return only the formatted Markdown text—no explanations, comments, or additional information.
- If the image is empty or contains no text, return an empty string.
"""  # noqa: E501

for img_path in ["../assets/2.png", "../assets/7.png", "../assets/9.png"]:
    # Upload the file to the File API
    image = client.files.upload(file=img_path)
    for i in range(10):
        print(f"Attempt {i+1} of 10 for {img_path}")
        try:
            response = client.models.generate_content(
                model="gemini-2.5-flash-preview-04-17",
                contents=[EXTRACT_MARKDOWN, image],
            config={
                'response_mime_type': 'application/json',
                'response_schema': PageText,
            })
            print(response.parsed.text)
        except Exception as e:
            print(e)