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.env.sample
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.env.sample
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# Azure Search for storing the processed documents
AZURE_SEARCH_SERVICE=
AZURE_SEARCH_INDEX=
AZURE_SEARCH_KEY=
AZURE_SEARCH_USE_SEMANTIC_SEARCH=False
AZURE_SEARCH_SEMANTIC_SEARCH_CONFIG=default
AZURE_SEARCH_TOP_K=5
AZURE_SEARCH_ENABLE_IN_DOMAIN=False
AZURE_SEARCH_FIELDS_ID=id
AZURE_SEARCH_CONTENT_COLUMN=content
AZURE_SEARCH_CONTENT_VECTOR_COLUMN=content_vector
AZURE_SEARCH_DIMENSIONS=1536
AZURE_SEARCH_FIELDS_TAG=tag
AZURE_SEARCH_FIELDS_METADATA=metadata
AZURE_SEARCH_FILENAME_COLUMN=filepath
AZURE_SEARCH_TITLE_COLUMN=title
AZURE_SEARCH_URL_COLUMN=url
AZURE_SEARCH_CONVERSATIONS_LOG_INDEX=conversations-log
AZURE_SEARCH_USE_INTEGRATED_VECTORIZATION=false
AZURE_SEARCH_INDEXER_NAME=
AZURE_SEARCH_DATASOURCE_NAME=
# Azure OpenAI for generating the answer and computing the embedding of the documents
AZURE_OPENAI_RESOURCE=
AZURE_OPENAI_API_KEY=
AZURE_OPENAI_MODEL_INFO="{\"model\":\"gpt-35-turbo-16k\",\"modelName\":\"gpt-35-turbo-16k\",\"modelVersion\":\"0613\"}"
AZURE_OPENAI_EMBEDDING_MODEL_INFO="{\"model\":\"text-embedding-ada-002\",\"modelName\":\"text-embedding-ada-002\",\"modelVersion\":\"2\"}"
AZURE_OPENAI_TEMPERATURE=0
AZURE_OPENAI_TOP_P=1.0
AZURE_OPENAI_MAX_TOKENS=1000
AZURE_OPENAI_STOP_SEQUENCE=
AZURE_OPENAI_SYSTEM_MESSAGE=You are an AI assistant that helps people find information.
AZURE_OPENAI_API_VERSION=2024-02-01
AZURE_OPENAI_STREAM=True
# Backend for processing the documents and application logging in the app
AzureWebJobsStorage=
BACKEND_URL=http://localhost:7071
DOCUMENT_PROCESSING_QUEUE_NAME=
# Azure Blob Storage for storing the original documents to be processed
AZURE_BLOB_ACCOUNT_NAME=
AZURE_BLOB_ACCOUNT_KEY=
AZURE_BLOB_CONTAINER_NAME=
# Azure Form Recognizer for extracting the text from the documents
AZURE_FORM_RECOGNIZER_ENDPOINT=
AZURE_FORM_RECOGNIZER_KEY=
# Azure AI Content Safety for filtering out the inappropriate questions or answers
AZURE_CONTENT_SAFETY_ENDPOINT=
AZURE_CONTENT_SAFETY_KEY=
# Orchestration strategy. Use Azure OpenAI Functions (openai_function), Semantic Kernel (semantic_kernel), LangChain (langchain) or Prompt Flow (prompt_flow) for messages orchestration. If you are using a new model version 0613 select any strategy, if you are using a 0314 model version select "langchain". Note that both `openai_function` and `semantic_kernel` use OpenAI function calling.
ORCHESTRATION_STRATEGY=openai_function
# If selected Prompt Flow as orchestration strategy, please provide the following environment variables. Note that Prompt Flow does not support RBAC authentication currently.
AZURE_ML_WORKSPACE_NAME=
PROMPT_FLOW_DEPLOYMENT_NAME=
PROMPT_FLOW_ENDPOINT_NAME=
#Speech-to-text feature
AZURE_SPEECH_SERVICE_KEY=
AZURE_SPEECH_SERVICE_REGION=
# Auth type environment variables.
# When AZURE_AUTH_TYPE=rbac, please make sure variable USE_KEY_VAULT=false
# When USE_KEY_VAULT=true, please make sure to set AZURE_KEY_VAULT_ENDPOINT
AZURE_AUTH_TYPE=keys
USE_KEY_VAULT=true
AZURE_KEY_VAULT_ENDPOINT=
# Chat conversation type to decide between custom or byod (bring your own data) conversation type
CONVERSATION_FLOW=
# Chat History CosmosDB Integration Settings
AZURE_COSMOSDB_INFO="{\"accountName\":\"cosmos-abc123\",\"databaseName\":\"db_conversation_history\",\"containerName\":\"conversations\"}"
AZURE_COSMOSDB_ACCOUNT_KEY=
AZURE_COSMOSDB_ENABLE_FEEDBACK=