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TEAMS_LOCAL_DEPLOYMENT.md

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Back to Teams Extension README

Local deployment for Teams

To customize the accelerator or run it locally, first, copy the .env.sample file to your development environment's .env file, and edit it according to environment variable values table below.

Develop & run the Teams Backend

If you want to develop and run the Teams backend function container locally, use the following commands.

Running the Teams Backend locally

First, install Azure Functions Core Tools.

cd code\batch
func start

Or use the Azure Functions VS Code extension.

Develop & run the Teams Frontend

  1. Open the “extensions/teams” folder with Visual Studio Code

Teams

  1. Open the file env\.env.local

  2. Locate the environment variable AZURE_FUNCTION_URL.

  3. Replace the <AZURE_FUNCTION_URL> with your local Teams Backend URL (i.e., http://localhost:7071/api/GetConversationResponse)

    AZURE_FUNCTION_URL=http://localhost:7071/api/GetConversationResponse

    Env

  4. Save the file.

  5. Select Teams Toolkit from the navigation panel.

  6. Verify your signed into O365 and Azure with sideloading enabled.

  7. Select the "play" button next to Local.

Teams Toolkit

Environment variables

App Setting Value Note
AZURE_SEARCH_SERVICE The URL of your Azure AI Search resource. e.g. https://.search.windows.net
AZURE_SEARCH_INDEX The name of your Azure AI Search Index
AZURE_SEARCH_KEY An admin key for your Azure AI Search resource
AZURE_SEARCH_USE_SEMANTIC_SEARCH False Whether or not to use semantic search
AZURE_SEARCH_SEMANTIC_SEARCH_CONFIG default The name of the semantic search configuration to use if using semantic search.
AZURE_SEARCH_TOP_K 5 The number of documents to retrieve from Azure AI Search.
AZURE_SEARCH_ENABLE_IN_DOMAIN True Limits responses to only queries relating to your data.
AZURE_SEARCH_CONTENT_COLUMNS List of fields in your Azure AI Search index that contains the text content of your documents to use when formulating a bot response. Represent these as a string joined with "
AZURE_SEARCH_CONTENT_VECTOR_COLUMNS Field from your Azure AI Search index for storing the content's Vector embeddings
AZURE_SEARCH_DIMENSIONS 1536 Azure OpenAI Embeddings dimensions. 1536 for text-embedding-ada-002. A full list of dimensions can be found here.
AZURE_SEARCH_FIELDS_ID id AZURE_SEARCH_FIELDS_ID: Field from your Azure AI Search index that gives a unique idenitfier of the document chunk. id if you don't have a specific requirement.
AZURE_SEARCH_FILENAME_COLUMN AZURE_SEARCH_FILENAME_COLUMN: Field from your Azure AI Search index that gives a unique idenitfier of the source of your data to display in the UI.
AZURE_SEARCH_TITLE_COLUMN Field from your Azure AI Search index that gives a relevant title or header for your data content to display in the UI.
AZURE_SEARCH_URL_COLUMN Field from your Azure AI Search index that contains a URL for the document, e.g. an Azure Blob Storage URI. This value is not currently used.
AZURE_SEARCH_FIELDS_TAG tag Field from your Azure AI Search index that contains tags for the document. tag if you don't have a specific requirement.
AZURE_SEARCH_FIELDS_METADATA metadata Field from your Azure AI Search index that contains metadata for the document. metadata if you don't have a specific requirement.
AZURE_SEARCH_FILTER Filter to apply to search queries.
AZURE_OPENAI_RESOURCE the name of your Azure OpenAI resource
AZURE_OPENAI_MODEL The name of your model deployment
AZURE_OPENAI_MODEL_NAME gpt-35-turbo The name of the model
AZURE_OPENAI_API_KEY One of the API keys of your Azure OpenAI resource
AZURE_OPENAI_EMBEDDING_MODEL text-embedding-ada-002 The name of you Azure OpenAI embeddings model deployment
AZURE_OPENAI_TEMPERATURE 0 What sampling temperature to use, between 0 and 2. Higher values like 0.8 will make the output more random, while lower values like 0.2 will make it more focused and deterministic. A value of 0 is recommended when using your data.
AZURE_OPENAI_TOP_P 1.0 An alternative to sampling with temperature, called nucleus sampling, where the model considers the results of the tokens with top_p probability mass. We recommend setting this to 1.0 when using your data.
AZURE_OPENAI_MAX_TOKENS 1000 The maximum number of tokens allowed for the generated answer.
AZURE_OPENAI_STOP_SEQUENCE Up to 4 sequences where the API will stop generating further tokens. Represent these as a string joined with "
AZURE_OPENAI_SYSTEM_MESSAGE You are an AI assistant that helps people find information. A brief description of the role and tone the model should use
AZURE_OPENAI_API_VERSION 2024-02-01 API version when using Azure OpenAI on your data
AzureWebJobsStorage The connection string to the Azure Blob Storage for the Azure Functions Batch processing
BACKEND_URL The URL for the Backend Batch Azure Function. Use http://localhost:7071 for local execution
DOCUMENT_PROCESSING_QUEUE_NAME doc-processing The name of the Azure Queue to handle the Batch processing
AZURE_BLOB_ACCOUNT_NAME The name of the Azure Blob Storage for storing the original documents to be processed
AZURE_BLOB_ACCOUNT_KEY The key of the Azure Blob Storage for storing the original documents to be processed
AZURE_BLOB_CONTAINER_NAME The name of the Container in the Azure Blob Storage for storing the original documents to be processed
AZURE_FORM_RECOGNIZER_ENDPOINT The name of the Azure Form Recognizer for extracting the text from the documents
AZURE_FORM_RECOGNIZER_KEY The key of the Azure Form Recognizer for extracting the text from the documents
APPLICATIONINSIGHTS_CONNECTION_STRING The Application Insights connection string to store the application logs
ORCHESTRATION_STRATEGY openai_function Orchestration strategy. Use Azure OpenAI Functions (openai_function), Semantic Kernel (semantic_kernel) or LangChain (langchain) 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.
AZURE_CONTENT_SAFETY_ENDPOINT The endpoint of the Azure AI Content Safety service
AZURE_CONTENT_SAFETY_KEY The key of the Azure AI Content Safety service
AZURE_SPEECH_SERVICE_KEY The key of the Azure Speech service
AZURE_SPEECH_SERVICE_REGION The region (location) of the Azure Speech service