app.py

import os
import base64
import gradio as gr
from mistralai import Mistral
from mistralai.models import OCRResponse
from pathlib import Path
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, Dict, List
from contextlib import contextmanager
import requests
from enum import Enum

# 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, api_key: str):
        if not api_key:
            raise ValueError("API key must be provided")
        self.api_key = api_key
        self.client = Mistral(api_key=self.api_key)
        try:
            self.client.models.list()  # Validate API key
        except Exception as e:
            raise ValueError(f"Invalid API key: {str(e)}")

    @staticmethod
    def _encode_image(image_path: str) -> str:
        try:
            with open(image_path, "rb") as image_file:
                return base64.b64encode(image_file.read()).decode('utf-8')
        except Exception as e:
            logger.error(f"Error encoding image {image_path}: {str(e)}")
            raise

    @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:
        try:
            return self.client.ocr.process(model="mistral-ocr-latest", document=document)
        except Exception as e:
            logger.error(f"OCR API call failed: {str(e)}")
            raise

    @retry(stop=stop_after_attempt(3), wait=wait_fixed(2))
    def _call_chat_complete(self, model: str, messages: List[Dict], **kwargs) -> Dict:
        try:
            return self.client.chat.complete(model=model, messages=messages, **kwargs)
        except Exception as e:
            logger.error(f"Chat complete API call failed: {str(e)}")
            raise

    def _get_file_content(self, file_input: Union[str, object]) -> bytes:
        try:
            if isinstance(file_input, str):  # File path
                with open(file_input, "rb") as f:
                    return f.read()
            elif hasattr(file_input, 'read'):  # File-like object
                return file_input.read()
            else:
                raise ValueError("Invalid file input: must be a path or file-like object")
        except Exception as e:
            logger.error(f"Error getting file content: {str(e)}")
            raise

    def _fetch_url_content(self, url: str) -> bytes:
        try:
            response = requests.get(url, timeout=10)
            response.raise_for_status()
            return response.content
        except requests.RequestException as e:
            logger.error(f"Error fetching URL {url}: {str(e)}")
            raise

    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, object]) -> 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, object]) -> 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, object]) -> 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 = chat_response.choices[0].message.content if chat_response.choices else "{}"
                try:
                    response_dict = json.loads(content)
                except json.JSONDecodeError:
                    logger.error("Invalid JSON response from chat API")
                    response_dict = {}
                return self._format_structured_response(temp_path, response_dict)
        except Exception as e:
            return self._handle_error("structured OCR", e)

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

    @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():
    with gr.Blocks(title="Mistral OCR & Structured Output App") as demo:
        gr.Markdown("# Mistral OCR & Structured Output App")
        gr.Markdown("Enter your Mistral API key below to use the app. Extract text from PDFs and images or get structured JSON output.")

        api_key_input = gr.Textbox(
            label="Mistral API Key",
            placeholder="Enter your Mistral API key here",
            type="password"
        )

        def initialize_processor(api_key):
            try:
                processor = OCRProcessor(api_key)
                return processor, "**Success:** API key set and validated!"
            except ValueError as e:
                return None, f"**Error:** {str(e)}"
            except Exception as e:
                return None, f"**Error:** Unexpected error: {str(e)}"

        processor_state = gr.State(value=None)
        api_status = gr.Markdown("API key not set. Please enter and set your key.")

        set_api_button = gr.Button("Set API Key")
        set_api_button.click(
            fn=initialize_processor,
            inputs=api_key_input,
            outputs=[processor_state, api_status]
        )

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

        for name, input_type, fn_name, 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:
                    inputs = input_type(label=label, file_types=file_types)
                output = gr.Markdown(label="Result")
                button_label = name.replace("OCR with ", "").replace("Structured ", "Get Structured ")

                def process_with_api(processor, input_data):
                    if not processor:
                        return "**Error:** Please set a valid API key first."
                    fn = getattr(processor, fn_name)
                    return fn(input_data)

                gr.Button(f"Process {button_label}").click(
                    fn=process_with_api,
                    inputs=[processor_state, 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")

            def doc_understanding_with_api(processor, url, q):
                if not processor:
                    return "**Error:** Please set a valid API key first."
                return processor.document_understanding(url, q)

            gr.Button("Ask Question").click(
                fn=doc_understanding_with_api,
                inputs=[processor_state, doc_url, question],
                outputs=output
            )

    return demo

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