import os  
import base64
import random
import string
from base64 import urlsafe_b64encode 
import requests  
from supabase_models import Supabase_Client  
from authenticate import get_access_token_v1



def generate_custom_random_string():
    # Length of the provided string (16 characters)
    length = 16  
    # Define the character set (hexadecimal characters: 0-9 and a-f)
    characters = string.hexdigits.lower()
    # Generate the random string
    random_string = ''.join(random.choice(characters) for _ in range(length))
    # Add "RAN" in front of the string
    return "RAN" + random_string

async def extract_structure_store_message(filename:str,filename_path:str,user_id:str,email:str):
    message_id = generate_custom_random_string()
    attachment_id = 'UPLOADED_MANUALLY'
    if attachment_id and message_id:
        project_id = os.getenv('PROJECT_ID')
        processor_id = os.getenv('PROCESSOR_ID')
        document_entities = {}
        print(filename)
        attachment_extension = filename.split('.')[1]
        print("printing attachment extension")
        print(attachment_extension)
        print(filename)
        # file_name = f"{message_id}_{attachment_id}"
        # print(f"file_name: {file_name}")
        print(filename_path)
        supabase = Supabase_Client().instance
        try:
            response = supabase.storage.from_(f"all_card_assets").download(
                  filename_path
                )
            base64_data = urlsafe_b64encode(response).decode('utf-8')
            if attachment_extension == 'pdf':
                payload = {
                        "skipHumanReview": True,
                        "rawDocument": {
                            "mimeType": f"application/{attachment_extension}",
                            "content": base64_data
                        }
                    }
            elif attachment_extension == 'jpg' or attachment_extension == 'png':
                payload = {
                        "skipHumanReview": True,
                        "rawDocument": {
                            "mimeType": f"image/{attachment_extension}",
                            "content": base64_data
                        }
                    }
    
            access_token = get_access_token_v1()
            print(access_token)
            
            headers = {
                'Authorization': f'Bearer {access_token}',
                'Content-Type': 'application/json; charset=utf-8'
            }
    
            response = requests.post(
                f'https://us-documentai.googleapis.com/v1/projects/{project_id}/locations/us/processors/{processor_id}:process',
                headers=headers,
                json=payload
            )
            response_json = response.json()
            print(response_json)
            allowed_entities = [
                        "credit_card_last_four_digits",
                        "currency",
                        "end_date",
                        "net_amount",
                        "payment_type",
                        "purchase_time",
                        "receipt_date",
                        "start_date",
                        "supplier_address",
                        "supplier_city",
                        "supplier_name",
                        "tip_amount",
                        "total_amount",
                        "line_item/quantity",
                        "line_item/amount",
                        "line_item/unit_price"
                    ]
            raw_text = response_json.get('document').get('text' , None)
            entities = response_json.get('document').get('entities' , None)
            document_entities['user_id'] = user_id
            insert_ocr_data_response =  (
                        supabase.table("receipt_ocr_data")
                        .insert({'user_id':user_id , 'message_id':message_id,'receipt_text':raw_text ,'email':email,'file_type':attachment_extension})
                        .execute()
                    )
            
            print('Printing entities')
            print(entities)
            # if entities is not None:
            #     for ent in entities:
            #         if ent.get('type') is not None:
            #             if ent.get('type') in allowed_entities:
            #                 mention_text = ent.get('mentionText')
            #                 normalised_values = ent.get('normalizedValue') if 'normalizedValue' in ent else None
            #                 document_entities[ent.get('type')] = {"mention_text":mention_text,"normalizedValue":normalised_values}
            if entities is not None:
                for ent in entities:
                    if ent.get('type') is not None:
                        entity_type = ent.get('type')
                        if entity_type in allowed_entities:
                            mention_text = ent.get('mentionText')
                            normalized_values = ent.get('normalizedValue') if 'normalizedValue' in ent else None
    
                            # Initialize a list for the entity type if not already present
                            if entity_type not in document_entities:
                                document_entities[entity_type] = []
    
                            # Append the entity data to the list
                            document_entities[entity_type].append({
                                "mention_text": mention_text,
                                "normalizedValue": normalized_values
                            })
            document_entities['email'] = email
            document_entities['message_id'] = message_id
            print(document_entities)
            insert_data_response =  (
                        supabase.table("document_ai_entities")
                        .insert(document_entities)
                        .execute()
                    )
            print(insert_data_response)
            
        except Exception as e:
            print(f"Error downloading or encoding file: {e}")