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Major update. Support for 15 LLMs, World Flora Online taxonomy validation, geolocation, 2 OCR methods, significant UI changes, stability improvements, consistent JSON parsing
ae215ea
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 google.cloud import vision_v1p3beta1 as vision_beta | |
# from langchain_google_genai import ChatGoogleGenerativeAI | |
from langchain_google_vertexai import VertexAI | |
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, is_hf) -> None: | |
self.cfg_private = cfg_private | |
self.dir_home = dir_home | |
self.is_hf = is_hf | |
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): | |
return isinstance(val, str) and bool(val.strip()) | |
# if val: | |
# return True | |
# else: | |
# return False | |
def check_openai_api_key(self): | |
if self.is_hf: | |
openai.api_key = os.getenv('OPENAI_API_KEY') | |
else: | |
openai.api_key = self.cfg_private['openai']['OPENAI_API_KEY'] | |
try: | |
openai.models.list() | |
return True | |
except: | |
return False | |
def check_azure_openai_api_key(self): | |
if not self.is_hf: | |
try: | |
# Initialize the Azure OpenAI client | |
model = AzureChatOpenAI( | |
deployment_name = 'gpt-35-turbo',#'gpt-35-turbo', | |
openai_api_version = self.cfg_private['openai_azure']['OPENAI_API_VERSION'], | |
openai_api_key = self.cfg_private['openai_azure']['OPENAI_API_KEY_AZURE'], | |
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 not self.is_hf: | |
client = MistralClient(api_key=self.cfg_private['mistral']['MISTRAL_API_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_vision_client(self): | |
results = {"ocr_print": False, "ocr_hand": False} | |
if self.is_hf: | |
client_beta = vision_beta.ImageAnnotatorClient(credentials=self.get_google_credentials()) | |
client = vision.ImageAnnotatorClient(credentials=self.get_google_credentials()) | |
else: | |
client_beta = vision_beta.ImageAnnotatorClient(credentials=self.get_google_credentials()) | |
client = vision.ImageAnnotatorClient(credentials=self.get_google_credentials()) | |
try: | |
with open(os.path.join(self.dir_home,'demo', 'ocr_test', 'ocr_test.jpg'), "rb") as image_file: | |
content = image_file.read() | |
except: | |
with open("./demo/ocr_test/ocr_test.jpg", "rb") as image_file: | |
content = image_file.read() | |
try: | |
image = vision_beta.Image(content=content) | |
image_context = vision_beta.ImageContext(language_hints=["en-t-i0-handwrit"]) | |
response = client_beta.document_text_detection(image=image, image_context=image_context) | |
texts = response.text_annotations | |
print(f"OCR Hand:\n{texts[0].description}") | |
if len(texts[0].description) > 0: | |
results['ocr_hand'] = True | |
except: | |
pass | |
try: | |
image = vision.Image(content=content) | |
response = client.document_text_detection(image=image) | |
texts = response.text_annotations | |
print(f"OCR Print:\n{texts[0].description}") | |
if len(texts[0].description) > 0: | |
results['ocr_print'] = True | |
except: | |
pass | |
return results | |
def check_google_vertex_genai_api_key(self): | |
results = {"palm2": False, "gemini": False, "palm2_langchain": False} | |
try: | |
model = TextGenerationModel.from_pretrained("text-bison@001") | |
response = model.predict("Hello") | |
test_response_palm = response.text | |
if test_response_palm: | |
results["palm2"] = True | |
print(f"palm2 pass [{test_response_palm}]") | |
else: | |
print(f"palm2 fail [{test_response_palm}]") | |
except Exception as e: | |
# print(f"palm2 fail2 [{e}]") | |
print(f"palm2 fail2") | |
try: | |
model = VertexAI(model="text-bison@001", max_output_tokens=10) | |
response = model.predict("Hello") | |
test_response_palm2 = response | |
if test_response_palm2: | |
results["palm2_langchain"] = True | |
print(f"palm2_langchain pass [{test_response_palm2}]") | |
else: | |
print(f"palm2_langchain fail [{test_response_palm2}]") | |
except Exception as e: | |
print(f"palm2 fail2 [{e}]") | |
print(f"palm2_langchain fail2") | |
try: | |
model = GenerativeModel("gemini-pro") | |
response = model.generate_content("Hello") | |
test_response_gemini = response.text | |
if test_response_gemini: | |
results["gemini"] = True | |
print(f"gemini pass [{test_response_gemini}]") | |
else: | |
print(f"gemini fail [{test_response_gemini}]") | |
except Exception as e: | |
# print(f"palm2 fail2 [{e}]") | |
print(f"palm2 fail2") | |
return results | |
def get_google_credentials(self): | |
if self.is_hf: | |
creds_json_str = os.getenv('GOOGLE_APPLICATION_CREDENTIALS') | |
credentials = service_account.Credentials.from_service_account_info(json.loads(creds_json_str)) | |
return credentials | |
else: | |
with open(self.cfg_private['google']['GOOGLE_APPLICATION_CREDENTIALS'], 'r') as file: | |
data = json.load(file) | |
creds_json_str = json.dumps(data) | |
credentials = service_account.Credentials.from_service_account_info(json.loads(creds_json_str)) | |
os.environ['GOOGLE_APPLICATION_CREDENTIALS'] = creds_json_str | |
return credentials | |
def report_api_key_status(self): | |
missing_keys = [] | |
present_keys = [] | |
if self.is_hf: | |
k_OPENAI_API_KEY = os.getenv('OPENAI_API_KEY') | |
k_openai_azure = os.getenv('AZURE_API_VERSION') | |
k_google_application_credentials = os.getenv('GOOGLE_APPLICATION_CREDENTIALS') | |
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('OPENCAGE_API_KEY') | |
else: | |
k_OPENAI_API_KEY = self.cfg_private['openai']['OPENAI_API_KEY'] | |
k_openai_azure = self.cfg_private['openai_azure']['OPENAI_API_KEY_AZURE'] | |
k_project_id = self.cfg_private['google']['GOOGLE_PROJECT_ID'] | |
k_location = self.cfg_private['google']['GOOGLE_LOCATION'] | |
k_google_application_credentials = self.cfg_private['google']['GOOGLE_APPLICATION_CREDENTIALS'] | |
k_mistral = self.cfg_private['mistral']['MISTRAL_API_KEY'] | |
k_here = self.cfg_private['here']['API_KEY'] | |
k_opencage = self.cfg_private['open_cage_geocode']['API_KEY'] | |
# Check each key and add to the respective list | |
# Google OCR key check | |
if self.has_API_key(k_google_application_credentials) and self.has_API_key(k_project_id) and self.has_API_key(k_location): | |
google_ocr_results = self.check_google_vision_client() | |
if google_ocr_results['ocr_print']: | |
present_keys.append('Google OCR Print (Valid)') | |
else: | |
present_keys.append('Google OCR Print (Invalid)') | |
if google_ocr_results['ocr_hand']: | |
present_keys.append('Google OCR Handwriting (Valid)') | |
else: | |
present_keys.append('Google OCR Handwriting (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_application_credentials) and self.has_API_key(k_project_id) and self.has_API_key(k_location): ################## | |
vertexai.init(project=k_project_id, location=k_location, credentials=self.get_google_credentials()) | |
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['palm2_langchain']: | |
present_keys.append('Palm2 LangChain (Valid)') | |
else: | |
present_keys.append('Palm2 LangChain (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 |