import os, io, openai, vertexai, json import google.generativeai as genai 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 google.oauth2 import service_account from datetime import datetime import google.generativeai as genai 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): # 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 check_google_vertex_genai_api_key(self): results = {"palm2": False, "gemini": False} if self.cfg_private: try: # 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: try: # Assuming genai and vertexai are clients for Google services # os.environ["GOOGLE_API_KEY"] = os.getenv('PALM_API_KEY') genai.configure(api_key=os.getenv('PALM_API_KEY')) vertexai.init(project= os.getenv('GOOGLE_PROJECT_ID'), location=os.getenv('GOOGLE_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 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 = 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