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.env_example
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##################################
# The following are used in objects to set values by default
# and used for operator infrastructure
# And are used in notebooks
###################################
# To get credentials go to
# ms.portal.azure.com > Cognitive Services > Azure Open AI > Keys and Endpoint
AZURE_OPENAI_CHAT_ENDPOINT="https://endpoint.openai.azure.com/"
AZURE_OPENAI_CHAT_KEY="<Provide Azure OpenAI key here>"
AZURE_OPENAI_CHAT_DEPLOYMENT="<Provide Azure OpenAI chat deployment name here>"
# Set optional AZURE_OPENAI_CHAT_ADDITIONAL_REQUEST_HEADERS to include additional HTTP headers in a dictionary format for API requests, e.g., {'key1': 'value1'}.
AZURE_OPENAI_CHAT_ADDITIONAL_REQUEST_HEADERS="<Provide headers using a dictionary format. Ex., {'key1':'value1'}>"
# To get credentials of GPT-V deployment go to
# ms.portal.azure.com > Cognitive Services > Azure Open AI > Keys and Endpoint
AZURE_OPENAI_GPTV_CHAT_ENDPOINT="https://endpoint.openai.azure.com/"
AZURE_OPENAI_GPTV_CHAT_KEY="<Provide Azure OpenAI key here>"
AZURE_OPENAI_GPTV_CHAT_DEPLOYMENT="<Provide Azure OpenAI GPT-V chat deployment name here>"
# To get credentials go to
# ms.portal.azure.com > Cognitive Services > Azure Open AI > Keys and Endpoint
AZURE_OPENAI_COMPLETION_ENDPOINT="https://completionendpoint.openai.azure.com/"
AZURE_OPENAI_COMPLETION_KEY="<Provide Azure OpenAI completion key here>"
AZURE_OPENAI_COMPLETION_DEPLOYMENT="completion_deployment_name"
# To get credentials go to
# ms.portal.azure.com > Cognitive Services > Azure Open AI > Keys and Endpoint
AZURE_OPENAI_EMBEDDING_ENDPOINT="https://embeddingendpoint.openai.azure.com/"
AZURE_OPENAI_EMBEDDING_KEY="<Provide Azure OpenAI embedding key here>"
AZURE_OPENAI_EMBEDDING_DEPLOYMENT="<Provide Azure OpenAI embedding deployment name here>"
# To get credentials go to
# ms.portal.azure.com > Azure ML workspace > Endpoints
AZURE_ML_KEY="<Provide Azure ML API key>"
AZURE_ML_MANAGED_ENDPOINT="https://aml-endpoint.inference.ml.azure.com/score"
# To find these values go to
# ms.portal.azure.com > Storage Account > Storage Browser > Blob containers > ... > Container Properties > URL
# ms.portal.azure.com > Storage Account > Storage Browser > Blob containers > ... > Generate SAS > Blob SAS token
AZURE_STORAGE_ACCOUNT_CONTAINER_URL="https://<storage-account-name>.blob.core.windows.net/<container-name>"
AZURE_STORAGE_ACCOUNT_SAS_TOKEN="<Provide Container SAS Token>"
# To get credentials go to AzureOpenAI Studio -> Deployments
AZURE_DALLE_ENDPOINT = "<DALLE ENDPOINT HERE>"
AZURE_DALLE_API_KEY = "<API KEY>"
AZURE_DALLE_DEPLOYMENT = "<deployment name>"
# To get credentials go to AzureOpenAI Studio -> Deployments
AZURE_TTS_ENDPOINT = "<TTS ENDPOINT HERE>"
AZURE_TTS_KEY = "<API KEY>"
AZURE_TTS_DEPLOYMENT = "<deployment name>"
##################################
# The following are used in deployment notebooks
###################################
# AZURE ML Workspace Details
# Azure Configuration
AZURE_SUBSCRIPTION_ID="<Provide Azure Subscription ID here>"
AZURE_RESOURCE_GROUP="<Provide Azure resource group name here>"
AZURE_ML_WORKSPACE_NAME="<Provide Azure ML workspace name here>"
AZURE_ML_REGISTRY_NAME="azureml"
# AZURE ML and HF Model Download/Register Compute Configuration
# Update with your model ID
HF_MODEL_ID="mistralai/Mistral-7B-Instruct-v0.1"
# Update with your task name
TASK_NAME="text-generation"
AZURE_ML_COMPUTE_TYPE="amlcompute"
# Update with your preferred instance type
AZURE_ML_INSTANCE_SIZE="STANDARD_D4_v2"
# Update with your compute name
AZURE_ML_COMPUTE_NAME="model-import-cluster-d4-v2"
# values could be 'latest' or any version
AZURE_ML_MODEL_IMPORT_VERSION="0.0.22"
AZURE_ML_MIN_INSTANCES=0
AZURE_ML_MAX_INSTANCES=1
IDLE_TIME_BEFORE_SCALE_DOWN=14400
# Deploy Configuration
AZURE_ML_MODEL_NAME_TO_DEPLOY="mistralai-Mistral-7B-Instruct-v01"
AZURE_ML_MODEL_VERSION_TO_DEPLOY=5
AZURE_ML_MODEL_DEPLOY_INSTANCE_SIZE="Standard_DS3_v2"
AZURE_ML_MODEL_DEPLOY_INSTANCE_COUNT=1
AZURE_ML_MODEL_DEPLOY_REQUEST_TIMEOUT_MS=90000
AZURE_ML_MODEL_DEPLOY_LIVENESS_PROBE_INIT_DELAY_SECS=1200
# AZURE ML Inference Configuration
AZURE_ML_SCORE_DEPLOYMENT_NAME="mistralai-mixtral-8x7b-instru-1"
# Azure Machine Learning scoring endpoint
AZURE_ML_SCORE_URI="<Provide Azure ML scoring URI here>"
# Azure Machine Learning scoring API key
AZURE_ML_SCORE_API_KEY="<Provide Azure ML API key here>"
# The following are not used to set objects by default
# OpenAI API Key. You can get yours at https://platform.openai.com/account/api-keys
OPENAI_API_KEY=""
# Open API Organization ID. You can get yours at https://platform.openai.com/account/org-settings
OPENAI_ORG_ID=""
# Hard-coded Azure credentials that are used during testing and development.
AZ_ACCESS_TOKEN=""
# Azure Cognitive Speech Tokens
AZURE_SPEECH_KEY_TOKEN=""
AZURE_SPEECH_REGION=""
# Custom
DATABASE_NAME=""
MAX_CONVERSATION_TURN=5