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import os, io, openai, vertexai
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
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:
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):
if self.cfg_private:
client = MistralClient(api_key=self.cfg_private['mistral']['mistral_key'])
else:
client = MistralClient(api_key=os.getenv('MISTRAL_API_KEY'))
try:
# 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=self.cfg_private['google_palm']['google_palm_api'])
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
# 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')
# 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')
# 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 |