app.py

import os
import base64
import gradio as gr
from mistralai import Mistral
from mistralai.models import OCRResponse
from pathlib import Path
from enum import Enum
from pydantic import BaseModel
import pycountry
import json
import logging
from tenacity import retry, stop_after_attempt, wait_fixed
import tempfile
from typing import Union, Optional, Dict, List
from contextlib import contextmanager

# Constants
DEFAULT_LANGUAGE = "English"
SUPPORTED_IMAGE_TYPES = [".jpg", ".png"]
SUPPORTED_PDF_TYPES = [".pdf"]
TEMP_FILE_EXPIRY = 7200  # 2 hours in seconds

# Configure logging
logging.basicConfig(level=logging.INFO, format='%(asctime)s - %(name)s - %(levelname)s - %(message)s')
logger = logging.getLogger(__name__)

class OCRProcessor:
    def __init__(self):
        self.api_key = os.environ.get("MISTRAL_API_KEY")
        if not self.api_key:
            raise ValueError("MISTRAL_API_KEY environment variable is not set")
        self.client = Mistral(api_key=self.api_key)

    @staticmethod
    def _encode_image(image_path: str) -> str:
        with open(image_path, "rb") as image_file:
            return base64.b64encode(image_file.read()).decode('utf-8')

    @staticmethod
    @contextmanager
    def _temp_file(content: bytes, suffix: str) -> str:
        temp_file = tempfile.NamedTemporaryFile(delete=False, suffix=suffix)
        try:
            temp_file.write(content)
            temp_file.close()
            yield temp_file.name
        finally:
            if os.path.exists(temp_file.name):
                os.unlink(temp_file.name)

    @retry(stop=stop_after_attempt(3), wait=wait_fixed(2))
    def _call_ocr_api(self, document: Dict) -> OCRResponse:
        return self.client.ocr.process(model="mistral-ocr-latest", document=document)

    @retry(stop=stop_after_attempt(3), wait=wait_fixed(2))
    def _call_chat_complete(self, model: str, messages: List[Dict], **kwargs) -> Dict:
        return self.client.chat.complete(model=model, messages=messages, **kwargs)

    def _get_file_content(self, file_input: Union[str, bytes]) -> bytes:
        if isinstance(file_input, str):
            with open(file_input, "rb") as f:
                return f.read()
        return file_input.read() if hasattr(file_input, 'read') else file_input

    def ocr_pdf_url(self, pdf_url: str) -> str:
        logger.info(f"Processing PDF URL: {pdf_url}")
        try:
            response = self._call_ocr_api({"type": "document_url", "document_url": pdf_url})
            return self._extract_markdown(response)
        except Exception as e:
            return self._handle_error("PDF URL processing", e)

    def ocr_uploaded_pdf(self, pdf_file: Union[str, bytes]) -> str:
        file_name = getattr(pdf_file, 'name', 'unknown')
        logger.info(f"Processing uploaded PDF: {file_name}")
        try:
            content = self._get_file_content(pdf_file)
            with self._temp_file(content, ".pdf") as temp_path:
                uploaded_file = self.client.files.upload(
                    file={"file_name": temp_path, "content": open(temp_path, "rb")},
                    purpose="ocr"
                )
                signed_url = self.client.files.get_signed_url(file_id=uploaded_file.id, expiry=TEMP_FILE_EXPIRY)
                response = self._call_ocr_api({"type": "document_url", "document_url": signed_url.url})
                return self._extract_markdown(response)
        except Exception as e:
            return self._handle_error("uploaded PDF processing", e)

    def ocr_image_url(self, image_url: str) -> str:
        logger.info(f"Processing image URL: {image_url}")
        try:
            response = self._call_ocr_api({"type": "image_url", "image_url": image_url})
            return self._extract_markdown(response)
        except Exception as e:
            return self._handle_error("image URL processing", e)

    def ocr_uploaded_image(self, image_file: Union[str, bytes]) -> str:
        file_name = getattr(image_file, 'name', 'unknown')
        logger.info(f"Processing uploaded image: {file_name}")
        try:
            content = self._get_file_content(image_file)
            with self._temp_file(content, ".jpg") as temp_path:
                encoded_image = self._encode_image(temp_path)
                base64_url = f"data:image/jpeg;base64,{encoded_image}"
                response = self._call_ocr_api({"type": "image_url", "image_url": base64_url})
                return self._extract_markdown(response)
        except Exception as e:
            return self._handle_error("uploaded image processing", e)

    def document_understanding(self, doc_url: str, question: str) -> str:
        logger.info(f"Document understanding - URL: {doc_url}, Question: {question}")
        try:
            messages = [{"role": "user", "content": [
                {"type": "text", "text": question},
                {"type": "document_url", "document_url": doc_url}
            ]}]
            response = self._call_chat_complete(model="mistral-small-latest", messages=messages)
            return response.choices[0].message.content if response.choices else "No response received"
        except Exception as e:
            return self._handle_error("document understanding", e)

    def structured_ocr(self, image_file: Union[str, bytes]) -> str:
        file_name = getattr(image_file, 'name', 'unknown')
        logger.info(f"Processing structured OCR for: {file_name}")
        try:
            content = self._get_file_content(image_file)
            with self._temp_file(content, ".jpg") as temp_path:
                encoded_image = self._encode_image(temp_path)
                base64_url = f"data:image/jpeg;base64,{encoded_image}"
                ocr_response = self._call_ocr_api({"type": "image_url", "image_url": base64_url})
                markdown = self._extract_markdown(ocr_response)

                chat_response = self._call_chat_complete(
                    model="pixtral-12b-latest",
                    messages=[{
                        "role": "user",
                        "content": [
                            {"type": "image_url", "image_url": base64_url},
                            {"type": "text", "text": (
                                f"OCR result:\n<BEGIN_IMAGE_OCR>\n{markdown}\n<END_IMAGE_OCR>\n"
                                "Convert to structured JSON with file_name, topics, languages, and ocr_contents"
                            )}
                        ]
                    }],
                    response_format={"type": "json_object"},
                    temperature=0
                )

                content = json.loads(chat_response.choices[0].message.content if chat_response.choices else "{}")
                return self._format_structured_response(temp_path, content)
        except Exception as e:
            return self._handle_error("structured OCR", e)

    @staticmethod
    def _extract_markdown(response: OCRResponse) -> str:
        return response.pages[0].markdown if response.pages else "No text extracted"

    @staticmethod
    def _handle_error(context: str, error: Exception) -> str:
        logger.error(f"Error in {context}: {str(error)}")
        return f"**Error:** {str(error)}"

    @staticmethod
    def _format_structured_response(file_path: str, content: Dict) -> str:
        languages = {lang.alpha_2: lang.name for lang in pycountry.languages if hasattr(lang, 'alpha_2')}
        valid_langs = [l for l in content.get("languages", [DEFAULT_LANGUAGE]) if l in languages.values()]
        
        response = {
            "file_name": Path(file_path).name,
            "topics": content.get("topics", []),
            "languages": valid_langs or [DEFAULT_LANGUAGE],
            "ocr_contents": content.get("ocr_contents", {})
        }
        return f"```json\n{json.dumps(response, indent=4)}\n```"

def create_interface():
    processor = OCRProcessor()
    with gr.Blocks(title="Mistral OCR & Structured Output App") as demo:
        gr.Markdown("# Mistral OCR & Structured Output App")
        gr.Markdown("Extract text from PDFs and images or get structured JSON output")

        tabs = [
            ("OCR with PDF URL", gr.Textbox, processor.ocr_pdf_url, "PDF URL", None),
            ("OCR with Uploaded PDF", gr.File, processor.ocr_uploaded_pdf, "Upload PDF", SUPPORTED_PDF_TYPES),
            ("OCR with Image URL", gr.Textbox, processor.ocr_image_url, "Image URL", None),
            ("OCR with Uploaded Image", gr.File, processor.ocr_uploaded_image, "Upload Image", SUPPORTED_IMAGE_TYPES),
            ("Structured OCR", gr.File, processor.structured_ocr, "Upload Image", SUPPORTED_IMAGE_TYPES),
        ]

        for name, input_type, fn, label, file_types in tabs:
            with gr.Tab(name):
                if input_type == gr.Textbox:
                    inputs = input_type(label=label, placeholder=f"e.g., https://example.com/{label.lower().replace(' ', '')}")
                else:  # gr.File
                    inputs = input_type(label=label, file_types=file_types)
                output = gr.Markdown(label="Result")
                # Use a more reliable way to get the button label
                button_label = name.replace("OCR with ", "").replace("Structured ", "Get Structured ")
                gr.Button(f"Process {button_label}").click(fn, inputs=inputs, outputs=output)

        with gr.Tab("Document Understanding"):
            doc_url = gr.Textbox(label="Document URL", placeholder="e.g., https://arxiv.org/pdf/1805.04770")
            question = gr.Textbox(label="Question", placeholder="e.g., What is the last sentence?")
            output = gr.Markdown(label="Answer")
            gr.Button("Ask Question").click(processor.document_understanding, inputs=[doc_url, question], outputs=output)

    return demo

if __name__ == "__main__":
    create_interface().launch(share=True, debug=True)