import redis
import json
from redis.commands.search.field import TagField, VectorField,TextField
from redis.commands.search.indexDefinition import IndexDefinition, IndexType
from redis.commands.search.query import Query
import logging
import numpy as np
import redis.commands.search
from typing import List, Dict, Any, Optional
import pdfplumber
import google.generativeai as genai
from openai import OpenAI
import os
import re
logging.basicConfig(level=logging.INFO)
logger = logging.getLogger()
r = redis.Redis(host='redis', port=6379, db=0, password=None,decode_responses=True)

class functions_doc:
    def __init__(self):
        self.client = OpenAI(api_key="sk-proj-YrJ4mMndLNB84kUXZ6WiT3BlbkFJJaAQjjupx7nImW0iAYcX")
        GENERATION_CONFIG = {
            "temperature": 0.2,
            "top_p": 0.75,
            "max_output_tokens": 6000,
            }
        SAFETY_SETTINGS= [
            {
                "category": "HARM_CATEGORY_HARASSMENT",
                "threshold": "BLOCK_MEDIUM_AND_ABOVE"
            },
            {
                "category": "HARM_CATEGORY_HATE_SPEECH",
                "threshold": "BLOCK_MEDIUM_AND_ABOVE"
            },
            {
                "category": "HARM_CATEGORY_SEXUALLY_EXPLICIT",
                "threshold": "BLOCK_MEDIUM_AND_ABOVE"
            },
            {
                "category": "HARM_CATEGORY_DANGEROUS_CONTENT",
                "threshold": "BLOCK_MEDIUM_AND_ABOVE"
            },
            ]
            # Define the default schema
            
            # Set up the model
        genai.configure(api_key="AIzaSyDksULr84HdEiR5ls42xo2_Wja3De3abVw")

        self.model = genai.GenerativeModel(model_name="gemini-1.5-pro-latest",
                                        generation_config=GENERATION_CONFIG,
                                        safety_settings=SAFETY_SETTINGS)

    def add_services_to_token(token: str, services: List[Dict]) -> Dict:
        """
        Add multiple services to a token's list of services, checking if a service with the same name already exists.
        Each service is a dictionary with 'servicename' and 'modelname' (which could be default or empty).

        :param token: The unique token of the user.
        :param services: List of service dictionaries to add.
        :return: A dictionary with a message and the list of added services.
        """
        services_key = f"token:{token}:docservices"
        try:
            existing_services = r.lrange(services_key, 0, -1)
            existing_service_names = [json.loads(service)['servicename'] for service in existing_services]
        except Exception as e:
            raise Exception("Failed to fetch or parse existing services: " + str(e))

        if not services or not isinstance(services, list):
            raise ValueError("Invalid services format. It must be a list of services.")

        added_services = []
        for service in services:
            if not isinstance(service, dict) or 'servicename' not in service:
                continue

            servicename = service.get('servicename')

            if servicename in existing_service_names:
                continue

            service_info = json.dumps({"servicename": servicename, "documents": []})
            try:
                r.rpush(services_key, service_info)
                added_services.append(servicename)
            except Exception as e:
                raise Exception(f"Failed to add service {servicename}: " + str(e))

        if not added_services:
            raise Exception("No new services were added. They may already exist or input was invalid.")

        return {"message": "Services successfully added.", "added_services": added_services}
    
    def remove_service_by_name(self, token, servicename):
            """
            Remove a service entry from Redis based on the servicename,
            and also remove all associated documents.

            Parameters:
                token (str): Token to identify the user data.
                servicename (str): Name of the service to be removed.

            Returns:
                dict: Status and message of the operation.
            """
            try:
                # Define the user key
                user_key = f"token:{token}:docservices"
                # Start a Redis pipeline
                pipe = r.pipeline()
                
                # Retrieve the length of the list
                list_length = r.llen(user_key)
                
                for i in range(list_length):
                    # Retrieve each JSON string from the list
                    service_data = r.lindex(user_key, i)
                    if service_data:
                        # Convert JSON string to dictionary
                        data = json.loads(service_data)
                        if data["servicename"] == servicename:
                            # Remove all associated documents
                            documents = data["documents"]
                            document_names = [doc['documentname'] for doc in documents]
                            print(document_names)
                            self.remove_documents_from_service( token, servicename, document_names)
                            # Delete each document found
                            # Remove the JSON string from the list
                            pipe.lrem(user_key, 0, service_data)

                # Execute the pipeline
                pipe.execute()
                return {"success": True, "message": f"Service {servicename} and all associated documents removed."}
            except Exception as e:
                return {"success": False, "message": str(e)}
    def add_and_store_document(token: str, service_name: str, document_name: str, encoded_file: bytes) -> dict:
        """
        Adds a document to a specific service within a user's token and immediately stores the document in Redis.
        If the document name already exists in the service, it is not appended or stored again.

        :param token: The unique token of the user.
        :param service_name: The name of the service to which the document will be added.
        :param document_name: The name of the document to add.
        :param encoded_file: The base64 encoded file to be stored.
        :return: A dictionary with a message indicating the result.
        """
        services_key = f"token:{token}:docservices"
        binary_key_key = f"token:{token}:{service_name}:binarykey"

        try:
            existing_services = r.lrange(services_key, 0, -1)
            service_found = False
            for i, service in enumerate(existing_services):
                service_data = json.loads(service)
                if service_data['servicename'] == service_name:
                    service_found = True
                    documents = service_data.get('documents', [])

                    if any(doc['documentname'] == document_name for doc in documents):
                        return {"message": "Document already exists in the service."}

                    # Auto-increment binary key
                    binary_key = r.incr(binary_key_key)

                    # Append new document info dictionary
                    documents.append({'documentname': document_name, 'binarykey': str(binary_key)})
                    service_data['documents'] = documents
                    updated_service = json.dumps(service_data)
                    r.lset(services_key, i, updated_service)

                    # Store the document in Redis
                    r.set(service_name + "_" + str(binary_key), encoded_file)
                    logging.info("Document stored successfully in Redis.")
                    return {"message": "Document successfully added and stored in the service."}

            if not service_found:
                return {"message": "Service not found."}

        except redis.RedisError as e:
            logging.error(f"Failed to store document: {e}")
            return {"status": "error", "message": str(e)}

        except Exception as e:
            logging.error(f"An error occurred: {e}")
            return {"status": "error", "message": "An unexpected error occurred"}
    def personalize_chunking(self, real_text, pdf_path, start_page, end_page):
        text = ""
        with pdfplumber.open(pdf_path) as pdf:
            # Only iterate over the desired page range
            for page_number in range(start_page - 1, end_page):
                page = pdf.pages[page_number]
                # Extract text from the page with specific tolerances
                text+= page.extract_text(x_tolerance=2, y_tolerance=4)
        return text.split(real_text)
    
    def extract_text_from_pdf(self, pdf_path, start_page, end_page):
        chunks = []
        with pdfplumber.open(pdf_path) as pdf:
            # Only iterate over the desired page range
            for page_number in range(start_page - 1, end_page):
                page = pdf.pages[page_number]
                # Extract text from the page with specific tolerances
                text = page.extract_text(x_tolerance=2, y_tolerance=4)
                chunks.append(text)
        return chunks
    def get_document(self, token: str, service_name: str, document_name: str) -> Optional[bytes]:
        """
        Retrieve a stored PDF file from Redis based on the token, service_name, and document_name.
        Each document is assumed to be stored with a unique key constructed from these parameters.
        """
        
        try:

            # Generate a binary key based on inputs
            binary_key = self.get_binary_key(token=token, service_name=service_name, document_name=document_name)

            # Retrieve the document from Redis
            stored_file = r.get(service_name + "_" + str(binary_key))

            if stored_file is None:
                # Log and handle the case where no file is found
                logging.info("No document found for the specified key.")
                return  {"status": "error", "message": "No document found for the specified key"}
            else:
                # Log success
                logging.info("Document retrieved successfully from Redis.")
                return    {"status": "success", "message": "Document retrieved successfully from Redis.","document":stored_file}

        except redis.RedisError as e:
            # Log the Redis error
            logging.error(f"Failed to retrieve document: {e}")
            return {"status": "error", "message":f"Failed to retrieve document: {e}"}

        except Exception as e:
            # Handle other possible exceptions
            logging.error(f"An error occurred: {e}")
            return None
    def get_documents_from_service(self, token: str, servicename: str) -> dict:
        """
        Retrieve document names from a specific service within a specific token's list of services.

        :param token: The unique token of the user.
        :param servicename: The name of the service from which documents will be retrieved.
        :return: A dictionary with a list of documents or a message indicating the result.
        """
        services_key = f"token:{token}:docservices"
        try:
            existing_services = r.lrange(services_key, 0, -1)
            for service in existing_services:
                service_data = json.loads(service)
                if service_data['servicename'] == servicename:
                    documents = service_data.get('documents', [])
                    
                    return {"success": True, "documents": documents}
            
            return {"message": "Service not found."}
        except Exception as e:
            raise Exception("Failed to fetch or parse services: " + str(e))
        
    def get_binary_key(self, token:str, service_name:str, document_name:str):
        result = self.get_documents_from_service(token=token, servicename=service_name)
        docs = result.get("documents",[])
        for doc in docs:
            if doc['documentname']==document_name:
                return doc['binarykey']
        return None
    # def remove_documents_from_service(self, token: str, service_name: str, document_names: list) -> dict:
    #         """
    #         Removes multiple PDF documents from Redis and their references from a specific service within a specific token's list of services.
    #         """
    #         try:
    #             services_key = f"token:{token}:docservices"
    #             existing_services = r.lrange(services_key, 0, -1)
    #             updated = False

    #             for i, service in enumerate(existing_services):
    #                 service_data = json.loads(service)
    #                 if service_data['servicename'] == service_name:
    #                     documents = service_data.get('documents', [])
    #                     new_documents = [doc for doc in documents if doc['documentname'] not in document_names]

    #                     if len(documents) != len(new_documents):
    #                         # Update the service data if any documents are removed
    #                         service_data['documents'] = new_documents
    #                         updated_service = json.dumps(service_data)
    #                         r.lset(services_key, i, updated_service)
    #                         updated = True

    #                         # Remove documents from direct Redis storage
    #                         for document_name in document_names:
    #                             binary_key = self.get_binary_key(token = token, service_name = service_name, document_name =document_name)
    #                             redis_key = service_name + "_" + str(binary_key)
    #                             if r.exists(redis_key):
    #                                 r.delete(redis_key)
    #                                 logging.info(f"Document with key {redis_key} removed successfully from Redis.")

    #             if updated:
    #                 return {"status": "success", "message": "Documents removed successfully from both Redis storage and service list."}
    #             else:
    #                 return {"status": "error", "message": "No documents found in the service list or no changes were made."}

    #         except redis.RedisError as e:
    #             logging.error(f"Failed to delete documents: {e}")
    #             return {"status": "error", "message": str(e)}

    #         except Exception as e:
    #             logging.error(f"An error occurred: {e}")
    #             return {"status": "error", "message": "An unexpected error occurred"}
    def remove_documents_from_service(self, token: str, service_name: str, document_names: List[str]) -> dict:
            """
            Removes multiple PDF documents from Redis and their references from a specific service within a specific token's list of services.
            """
            try:
                services_key = f"token:{token}:docservices"
                existing_services = r.lrange(services_key, 0, -1)
                updated = False
                for i, service in enumerate(existing_services):
                    service_data = json.loads(service)
                    if service_data['servicename'] == service_name:

                        documents = service_data.get('documents', [])
                        new_documents = [doc for doc in documents if doc['documentname'] not in document_names]

                        if len(documents) != len(new_documents):
                            # Remove documents from direct Redis storage
                            for document_name in document_names:
                                binary_key = self.get_binary_key(token=token, service_name=service_name, document_name=document_name)
                                redis_key = service_name + "_" + str(binary_key)
                                print("Redis key",redis_key)
                                if r.exists(redis_key):
                                    r.delete(redis_key)
                                    logging.info(f"Document with key {redis_key} removed successfully from Redis.")
                                    
                            # Update the service data if any documents are removed
                            service_data['documents'] = new_documents
                            updated_service = json.dumps(service_data)
                            r.lset(services_key, i, updated_service)
                            updated = True

                            

                if updated:
                    return {"status": "success", "message": "Documents removed successfully from both Redis storage and service list."}
                else:
                    return {"status": "error", "message": "No documents found in the service list or no changes were made."}

            except redis.RedisError as e:
                logging.error(f"Failed to delete documents: {e}")
                return {"status": "error", "message": str(e)}

            except Exception as e:
                logging.error(f"An error occurred: {e}")
                return {"status": "error", "message": "An unexpected error occurred"}
    def get_json(self, schema, context, model,comment):
        prompt = "Your task is to extract information from context."
        var = ""
        if comment:
            var = f"""**expilcation of keys in schema**: {comment}"""
        instruction = f"""
        **JSON Format (High Priority)**: Provide the output in a properly formatted JSON structure.
        **Respect Schema (High Priority)**: Utilize the schema below to organize the extracted information from the context. If certain information is absent, leave the corresponding field empty.
        **Error Handling**: If the context does not contain sufficient information to fulfill the requirements, return the following JSON response: {{"message": "Context lacks the desired information"}}.

        ```json
        {{
        {schema}
        }}```
        {var}
        """
        template = f"""
        {prompt}
        Consider the following:
        {instruction}

        CONTEXT:
        {context}
        """
        if model=="gpt-3.5-turbo":
            response =  self.client.chat.completions.create(
              model="gpt-3.5-turbo",
              messages=[{"role": "user", "content": template}
              ])
            pred_reponse = response.choices[0].message.content
            return self.parse_json(pred_reponse)
        elif model=="gemini":

            response = self.model.generate_content(template)
            pred_reponse = response.text
            return self.parse_json(pred_reponse)
    def clean_and_load_json(self, s):
        # Remove comments
        s = re.sub(r'#.*?\n', '', s)

        # Remove trailing commas before closing brackets in lists and dictionaries
        s = re.sub(r',\s*\n\s*(\]|\})', r'\1', s)
        # Remove patterns like '\n       ...\n'
        s = re.sub(r'\n\s*\.\.\.\n', '', s)
        # Remove comma before } or ]
        s = re.sub(r',\s*(\]|\})', r'\1', s)
        # Remove unnecessary whitespace
        s = s.strip()
        #print(s)
        # Load the cleaned JSON string
        return json.loads(s)
    def parse_json(self, s):
        try:
            json_str = json.loads(s)
        except:
            # Find the index of the first occurrence of '{\n'
            start_idx = s.find('{')

            # Find the index of the last occurrence of '\n}'
            end_idx = s.rfind('}')

            # If either index is not found, raise an error
            if start_idx == -1 or end_idx == -1:
                raise ValueError("Could not find JSON object in the provided string.")

            # Extract the JSON substring from start_idx to end_idx (inclusive) + 3 to include the closing '\n}'
            json_str = s[start_idx:end_idx+1]
            try:
                json_str = json.loads(json_str)
            except:
                json_str =  self.lean_and_load_json(json_str)
        return json_str