vouchervision/API_validation.py

import os, io, openai, vertexai, json, tempfile
from mistralai.client import MistralClient
from mistralai.models.chat_completion import ChatMessage
from langchain.schema import HumanMessage
from langchain_openai import AzureChatOpenAI
from vertexai.language_models import TextGenerationModel
from vertexai.preview.generative_models import GenerativeModel
from google.cloud import vision
from datetime import datetime
import google.generativeai as genai
from google.oauth2 import service_account
from googleapiclient.discovery import build


class APIvalidation:

    def __init__(self, cfg_private, dir_home) -> None:
        self.cfg_private = cfg_private
        self.dir_home = dir_home
        self.formatted_date = self.get_formatted_date()

    def get_formatted_date(self):
        # Get the current date
        current_date = datetime.now()

        # Format the date as "Month day, year" (e.g., "January 23, 2024")
        formatted_date = current_date.strftime("%B %d, %Y")

        return formatted_date


    def has_API_key(self, val):
        if val:
            return True
        else:
            return False
            
    def check_openai_api_key(self):
        if self.cfg_private:
            openai.api_key = self.cfg_private['openai']['OPENAI_API_KEY']
        else:
            openai.api_key = os.getenv('OPENAI_API_KEY')

        try:
            openai.models.list()
            return True
        except:
            return False
        
    # def check_google_ocr_api_key(self): ##################################################################################### maybe check without initi, post the vertexai
    #     # if os.path.exists(self.cfg_private['google_cloud']['path_json_file']):
    #     #     os.environ["GOOGLE_APPLICATION_CREDENTIALS"] = self.cfg_private['google_cloud']['path_json_file']
    #     # elif os.path.exists(self.cfg_private['google_cloud']['path_json_file_service_account2']):
    #     #     os.environ["GOOGLE_APPLICATION_CREDENTIALS"] = self.cfg_private['google_cloud']['path_json_file_service_account2']
    #     # else:
    #     #     return False
        
    #     try:
    #         if not self.cfg_private:
    #             # Convert JSON key from string to a dictionary
    #             service_account_json_str = os.getenv('google_service_account_json')
    #             if not service_account_json_str:
    #                 print("Service account JSON not found in environment variables.")
    #                 return False

    #             # Convert JSON string to a dictionary
    #             service_account_info = json.loads(service_account_json_str)
    #             # Create credentials from the service account info
    #             credentials = service_account.Credentials.from_service_account_info(service_account_info)
    #             # Initialize the client with the credentials
    #             client = vision.ImageAnnotatorClient(credentials=credentials)
    #             logo_path = os.path.join(self.dir_home, 'img','logo.png')
    #             with io.open(logo_path, 'rb') as image_file:
    #                 content = image_file.read()
    #             image = vision.Image(content=content)
    #             response = client.document_text_detection(image=image)
    #             texts = response.text_annotations       
    #             normal_cleaned_text = texts[0].description if texts else None
    #             print(f"OCR TEST: {normal_cleaned_text}")
    #         else:
    #             logo_path = os.path.join(self.dir_home, 'img','logo.png')
    #             client = vision.ImageAnnotatorClient()
    #             with io.open(logo_path, 'rb') as image_file:
    #                 content = image_file.read()
    #             image = vision.Image(content=content)
    #             response = client.document_text_detection(image=image)
    #             texts = response.text_annotations       
    #             normal_cleaned_text = texts[0].description if texts else None
    #         if normal_cleaned_text:
    #             return True
    #         else:
    #             return False
    #     except:
    #         return False
        
    def check_azure_openai_api_key(self):
        if self.cfg_private:
            try:
                # Initialize the Azure OpenAI client
                model = AzureChatOpenAI(
                    deployment_name = 'gpt-35-turbo',#'gpt-35-turbo',
                    openai_api_version = self.cfg_private['openai_azure']['api_version'],
                    openai_api_key = self.cfg_private['openai_azure']['openai_api_key'],
                    azure_endpoint = self.cfg_private['openai_azure']['openai_api_base'],
                    openai_organization = self.cfg_private['openai_azure']['openai_organization'],
                )
                msg = HumanMessage(content="hello")
                # self.llm_object.temperature = self.config.get('temperature')
                response = model([msg])

                # Check the response content (you might need to adjust this depending on how your AzureChatOpenAI class handles responses)
                if response:
                    return True
                else:
                    return False

            except Exception as e:  # Use a more specific exception if possible
                return False
        else:
            try:
                azure_api_version = os.getenv('AZURE_API_VERSION')
                azure_api_key = os.getenv('AZURE_API_KEY')
                azure_api_base = os.getenv('AZURE_API_BASE')
                azure_organization = os.getenv('AZURE_ORGANIZATION')
                # Initialize the Azure OpenAI client
                model = AzureChatOpenAI(
                    deployment_name = 'gpt-35-turbo',#'gpt-35-turbo',
                    openai_api_version = azure_api_version,
                    openai_api_key = azure_api_key,
                    azure_endpoint = azure_api_base,
                    openai_organization = azure_organization,
                )
                msg = HumanMessage(content="hello")
                # self.llm_object.temperature = self.config.get('temperature')
                response = model([msg])

                # Check the response content (you might need to adjust this depending on how your AzureChatOpenAI class handles responses)
                if response:
                    return True
                else:
                    return False

            except Exception as e:  # Use a more specific exception if possible
                return False
        
    def check_mistral_api_key(self):
        try:
            if self.cfg_private:
                client = MistralClient(api_key=self.cfg_private['mistral']['mistral_key'])
            else:
                client = MistralClient(api_key=os.getenv('MISTRAL_API_KEY'))

            
            # Initialize the Mistral Client with the API key

            # Create a simple message
            messages = [ChatMessage(role="user", content="hello")]

            # Send the message and get the response
            chat_response = client.chat(
                model="mistral-tiny",  
                messages=messages,
            )

            # Check if the response is valid (adjust this according to the actual response structure)
            if chat_response and chat_response.choices:
                return True
            else:
                return False
        except Exception as e:  # Replace with a more specific exception if possible
            return False
        
    # def get_google_credentials(self):
    #     # Convert JSON key from string to a dictionary
    #     service_account_json_str = os.getenv('google_service_account_json')

    #     with tempfile.NamedTemporaryFile(mode="w+", delete=False,suffix=".json") as temp:
    #         temp.write(service_account_json_str)
    #         temp_filename = temp.name
        
    #     return temp_filename

    # def init_google_client(opt, opt2):
    #     # Fetch the credentials JSON string from Hugging Face Secrets
    #     creds_json_str = os.getenv('google_service_account_json')

    #     if creds_json_str:
    #         creds_dict = json.loads(creds_json_str)
    #         credentials = service_account.Credentials.from_service_account_info(creds_dict)

    #         # Initialize Google API client (if needed for your use case)
    #         client = build(opt, opt2, credentials=credentials)  # Adjust with actual service details

    #         return client, credentials
    #     else:
    #         print("Google API credentials not found.")

    def check_google_vertex_genai_api_key(self):
        results = {"palm2": False, "gemini": False}
        if self.cfg_private:
            try: # Local
                # Assuming genai and vertexai are clients for Google services
                # os.environ["GOOGLE_API_KEY"] = self.cfg_private['google_palm']['google_palm_api']
                # genai.configure(api_key=self.cfg_private['google_palm']['google_palm_api'])
                vertexai.init(project= self.cfg_private['google_palm']['project_id'], location=self.cfg_private['google_palm']['location'])

                try:
                    model = TextGenerationModel.from_pretrained("text-bison@001")
                    response = model.predict("Hello")
                    test_response_palm = response.text
                    # llm_palm = ChatGoogleGenerativeAI(model="text-bison@001")
                    # test_response_palm = llm_palm.invoke("Hello")
                    if test_response_palm:
                        results["palm2"] = True
                except Exception as e:  
                    pass

                try:
                    model = GenerativeModel("gemini-pro")
                    response = model.generate_content("Hello")
                    test_response_gemini = response.text
                    # llm_gemini = ChatGoogleGenerativeAI(model="gemini-pro")
                    # test_response_gemini = llm_gemini.invoke("Hello")
                    if test_response_gemini:
                        results["gemini"] = True
                except Exception as e:  
                    pass


                return results
            except Exception as e:  # Replace with a more specific exception if possible
                return results
        else:
            ### is hugging face
            try:
                # Assuming genai and vertexai are clients for Google services
                # os.environ["GOOGLE_API_KEY"] = os.getenv('PALM_API_KEY')
                # os.environ["GOOGLE_APPLICATION_CREDENTIALS"] = self.get_google_credentials()
                # client, credentials = self.init_google_client('gemini-pro', 'v1')
                # print(credentials)
                palm_api_key = os.getenv('PALM_API_KEY')
                google_project_id = os.getenv('GOOGLE_PROJECT_ID')
                google_location = os.getenv('GOOGLE_LOCATION')
                os.environ['GOOGLE_API_KEY'] =  os.getenv('PALM_API_KEY')
                vertexai.init(project=os.getenv('GOOGLE_PROJECT_ID'), location=os.getenv('GOOGLE_LOCATION'))
                # genai.configure(api_key=palm_api_key)
                # vertexai.init(project=google_project_id, location=google_location)#, credentials=credentials)

                try:
                    model = TextGenerationModel.from_pretrained("text-bison@001")
                    response = model.predict("Hello")
                    test_response_palm = response.text
                    # llm_palm = ChatGoogleGenerativeAI(model="text-bison@001")
                    # test_response_palm = llm_palm.invoke("Hello")
                    if test_response_palm:
                        results["palm2"] = True
                        print(f"palm2 pass [{test_response_palm}]")
                    else:
                        print(f"palm2 yes [{test_response_palm}]")

                except Exception as e:  
                    print(f"palm2 [{e}]")
                    pass

                try:
                    model = GenerativeModel("gemini-pro")
                    response = model.generate_content("Hello")
                    test_response_gemini = response.text
                    # llm_gemini = ChatGoogleGenerativeAI(model="gemini-pro")
                    # test_response_gemini = llm_gemini.invoke("Hello")
                    if test_response_gemini:
                        results["gemini"] = True
                        print(f"gemini pass [{test_response_palm}]")
                    else:
                        print(f"gemini yes [{test_response_palm}]")

                except Exception as e:  
                    print(f"gemini [{e}]")
                    pass

                return results
            except Exception as e:  # Replace with a more specific exception if possible
                print(f"Immediate [{e}]")
                return results

    def report_api_key_status(self):
        missing_keys = []
        present_keys = []

        if self.cfg_private:
            k_OPENAI_API_KEY = self.cfg_private['openai']['OPENAI_API_KEY']
            k_openai_azure = self.cfg_private['openai_azure']['api_version']
            k_google_palm_api = self.cfg_private['google_palm']['google_palm_api']
            k_project_id = self.cfg_private['google_palm']['project_id']
            k_location = self.cfg_private['google_palm']['location']
            k_mistral = self.cfg_private['mistral']['mistral_key']
            k_here = self.cfg_private['here']['api_key']
            k_opencage = self.cfg_private['open_cage_geocode']['api_key']
        else:
            k_OPENAI_API_KEY = os.getenv('OPENAI_API_KEY')
            k_openai_azure = os.getenv('AZURE_API_VERSION')
            k_google_palm_api = os.getenv('PALM_API_KEY')
            k_project_id = os.getenv('GOOGLE_PROJECT_ID')
            k_location = os.getenv('GOOGLE_LOCATION')
            k_mistral = os.getenv('MISTRAL_API_KEY')
            k_here = os.getenv('here_api_key')
            k_opencage = os.getenv('open_cage_geocode')


        # Check each key and add to the respective list
        # Google OCR key check
        if self.has_API_key(k_google_palm_api) and self.has_API_key(k_project_id) and self.has_API_key(k_location):
            is_valid = True #self.check_google_ocr_api_key() ###############################################################################################################################
            if is_valid:
                present_keys.append('Google OCR (Valid)')
            else:
                present_keys.append('Google OCR (Invalid)')
        else:
            missing_keys.append('Google OCR')
        
        
        # OpenAI key check
        if self.has_API_key(k_OPENAI_API_KEY):
            is_valid = self.check_openai_api_key()
            if is_valid:
                present_keys.append('OpenAI (Valid)')
            else:
                present_keys.append('OpenAI (Invalid)')
        else:
            missing_keys.append('OpenAI')

        # Azure OpenAI key check
        if self.has_API_key(k_openai_azure):
            is_valid = self.check_azure_openai_api_key()
            if is_valid:
                present_keys.append('Azure OpenAI (Valid)')
            else:
                present_keys.append('Azure OpenAI (Invalid)')
        else:
            missing_keys.append('Azure OpenAI')

        # Google PALM2/Gemini key check
        if self.has_API_key(k_google_palm_api) and self.has_API_key(k_project_id) and self.has_API_key(k_location):
            google_results = self.check_google_vertex_genai_api_key()
            if google_results['palm2']:
                present_keys.append('Palm2 (Valid)')
            else:
                present_keys.append('Palm2 (Invalid)')
            if google_results['gemini']:
                present_keys.append('Gemini (Valid)')
            else:
                present_keys.append('Gemini (Invalid)')
        else:
            missing_keys.append('Google VertexAI/GenAI')

        

        # Mistral key check
        if self.has_API_key(k_mistral):
            is_valid = self.check_mistral_api_key()
            if is_valid:
                present_keys.append('Mistral (Valid)')
            else:
                present_keys.append('Mistral (Invalid)')
        else:
            missing_keys.append('Mistral')


        if self.has_API_key(k_here):
            present_keys.append('HERE Geocode (Valid)')
        else:
            missing_keys.append('HERE Geocode (Invalid)')

        if self.has_API_key(k_opencage):
            present_keys.append('OpenCage Geocode (Valid)')
        else:
            missing_keys.append('OpenCage Geocode (Invalid)')

        # Create a report string
        report = "API Key Status Report:\n"
        report += "Present Keys: " + ", ".join(present_keys) + "\n"
        report += "Missing Keys: " + ", ".join(missing_keys) + "\n"

        print(report)
        return present_keys, missing_keys, self.formatted_date