BindingApi Class
Interface to extend for using existing binding decorator functions.
- Inheritance
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BindingApiBindingApi
Constructor
BindingApi(*args, **kwargs)Methods
| assistant_create_output |
The assistantCreate output binding creates a new assistant with a specified system prompt. parameter value :param kwargs: Keyword arguments for specifying additional binding fields to include in the binding json |
| assistant_post_input |
The assistantPost output binding sends a message to the assistant and saves the response in its internal state. assistant to respond to. :param model: The OpenAI chat model to use. :param data_type: Defines how Functions runtime should treat the parameter value :param kwargs: Keyword arguments for specifying additional binding fields to include in the binding json |
| assistant_query_input |
The assistantQuery input binding fetches the assistant history and passes it to the function. history to fetch. The timestamp should be in ISO 8601 format - for example, 2023-08-01T00:00:00Z. :param id: The ID of the Assistant to query. :param data_type: Defines how Functions runtime should treat the parameter value :param kwargs: Keyword arguments for specifying additional binding fields to include in the binding json |
| blob_input |
The blob_input decorator adds <xref:azure.functions.BlobInput> to the <xref:azure.functions.FunctionBuilder> object for building Function object used in worker function indexing model. This is equivalent to defining BlobInput in the function.json which enables function to write message(s) to the storage blobs. All optional fields will be given default value by function host when they are parsed by function host. Ref: https://aka.ms/azure-function-binding-storage-blob that specifies how to connect to Azure Blobs. :param data_type: Defines how Functions runtime should treat the parameter value. fields to include in the binding json. |
| blob_output |
The blob_output decorator adds <xref:azure.functions.BlobOutput> to the <xref:azure.functions.FunctionBuilder> object for building Function object used in worker function indexing model. This is equivalent to defining BlobOutput in the function.json which enables function to write message(s) to the storage blobs. All optional fields will be given default value by function host when they are parsed by function host. Ref: https://aka.ms/azure-function-binding-storage-blob fields to include in the binding json. :return: Decorator function. |
| cosmos_db_input |
The cosmos_db_input decorator adds <xref:azure.functions.CosmosDBInput> to the <xref:azure.functions.FunctionBuilder> object for building Function object used in worker function indexing model. This decorator will work only with extension bundle 4.x and above. For additional details, please refer https://aka.ms/cosmosdb-v4-update. This is equivalent to defining CosmosDBInput in the function.json which enables function to read from CosmosDB. All optional fields will be given default value by function host when they are parsed by function host. Ref: https://aka.ms/azure-function-binding-cosmosdb-v4 DocumentList input object in function code :param connection: The name of an app setting or setting container that specifies how to connect to the Azure Cosmos DB account being monitored containing your Azure Cosmos DB connection string document :param partition_key: Specifies the partition key value for the lookup :param id: The ID of the document to retrieve :param sql_query: An Azure Cosmos DB SQL query used for retrieving multiple documents :param preferred_locations: (Optional) Defines preferred locations (regions) for geo-replicated database accounts in the Azure Cosmos DB service. Values should be comma-separated. For example, East US,South Central US,North Europe :param data_type: Defines how Functions runtime should treat the parameter value :param kwargs: Keyword arguments for specifying additional binding fields to include in the binding json |
| cosmos_db_input_v3 |
The cosmos_db_input_v3 decorator adds <xref:azure.functions.CosmosDBInput> to the <xref:azure.functions.FunctionBuilder> object for building Function object used in worker function indexing model. This decorator will work only with extension bundle 2.x or 3.x. For additional details, please refer https://aka.ms/cosmosdb-v4-update. This is equivalent to defining CosmosDBInput in the function.json which enables function to read from CosmosDB. All optional fields will be given default value by function host when they are parsed by function host. Ref: https://aka.ms/azure-function-binding-cosmosdb-v2 DocumentList input object in function code. :param database_name: The database containing the document. :param collection_name: The name of the collection that contains the document. :param connection_string_setting: The name of the app setting containing your Azure Cosmos DB connection string. :param id: The ID of the document to retrieve. :param sql_query: An Azure Cosmos DB SQL query used for retrieving multiple documents. :param partition_key: Specifies the partition key value for the lookup. :param data_type: Defines how Functions runtime should treat the parameter value. :param kwargs: Keyword arguments for specifying additional binding fields to include in the binding json. |
| cosmos_db_output |
The cosmos_db_output decorator adds <xref:azure.functions.CosmosDBOutput> to the <xref:azure.functions.FunctionBuilder> object for building Function object used in worker function indexing model. This decorator will work only with extension bundle 4.x and above. For additional details, please refer https://aka.ms/cosmosdb-v4-update. This is equivalent to defining CosmosDBOutput in the function.json which enables function to write to the CosmosDB. All optional fields will be given default value by function host when they are parsed by function host. Ref: https://aka.ms/azure-function-binding-cosmosdb-v4 output object in function code. :param connection: The name of an app setting or setting collection that specifies how to connect to the Azure Cosmos DB account being monitored :param database_name: The name of the Azure Cosmos DB database with the collection being monitored :param container_name: The name of the container being monitored :param create_if_not_exists: A boolean value to indicate whether the collection is created when it doesn't exist :param partition_key: When CreateIfNotExists is true, it defines the partition key path for the created collection :param container_throughput: When createIfNotExists is true, it defines the throughput of the created container PreferredLocations, it can leverage multi-region writes in the Azure Cosmos DB service :param preferred_locations: Defines preferred locations (regions) for geo-replicated database accounts in the Azure Cosmos DB service :param data_type: Defines how Functions runtime should treat the parameter value :param kwargs: Keyword arguments for specifying additional binding fields to include in the binding json |
| cosmos_db_output_v3 |
The cosmos_db_output_v3 decorator adds <xref:azure.functions.CosmosDBOutput> to the <xref:azure.functions.FunctionBuilder> object for building Function object used in worker function indexing model. This decorator will work only with extension bundle 2.x or 3.x. For additional details, please refer https://aka.ms/cosmosdb-v4-update. This is equivalent to defining CosmosDBOutput in the function.json which enables function to write to the CosmosDB. All optional fields will be given default value by function host when they are parsed by function host. Ref: https://aka.ms/azure-function-binding-cosmosdb-v2 output object in function code. :param database_name: The name of the Azure Cosmos DB database with the collection being monitored. :param collection_name: The name of the collection being monitored. :param connection_string_setting: The name of an app setting or setting collection that specifies how to connect to the Azure Cosmos DB account being monitored. :param create_if_not_exists: A boolean value to indicate whether the collection is created when it doesn't exist. :param partition_key: When CreateIfNotExists is true, it defines the partition key path for the created collection. :param collection_throughput: When CreateIfNotExists is true, it defines the throughput of the created collection. :param use_multiple_write_locations: When set to true along with PreferredLocations, it can leverage multi-region writes in the Azure Cosmos DB service. :param preferred_locations: Defines preferred locations (regions) for geo-replicated database accounts in the Azure Cosmos DB service. :param data_type: Defines how Functions runtime should treat the parameter value. :param kwargs: Keyword arguments for specifying additional binding fields to include in the binding json. |
| dapr_binding_output |
The dapr_binding_output decorator adds <xref:azure.functions.DaprBindingOutput> to the <xref:azure.functions.FunctionBuilder> object for building Function object used in worker function indexing model. This is equivalent to defining DaprBindingOutput in the function.json which enables function to send a value to a Dapr output binding. All optional fields will be given default value by function host when they are parsed by function host. Ref: https://aka.ms/azure-function-dapr-binding-output-binding output object in function code. :param binding_name: The configured name of the binding. :param operation: The configured operation. :param dapr_address: Dapr address, it is optional field, by default it will be set to http://localhost:{daprHttpPort}. :param data_type: Defines how Functions runtime should treat the parameter value :param kwargs: Keyword arguments for specifying additional binding fields to include in the binding json |
| dapr_invoke_output |
The dapr_invoke_output decorator adds <xref:azure.functions.DaprInvokeOutput> to the <xref:azure.functions.FunctionBuilder> object for building Function object used in worker function indexing model. This is equivalent to defining DaprInvokeOutput in the function.json which enables function to invoke another Dapr App. All optional fields will be given default value by function host when they are parsed by function host. Ref: https://aka.ms/azure-function-dapr-invoke-output-binding output object in function code. :param app_id: The dapr app name to invoke. :param method_name: The method name of the app to invoke. :param http_verb: The http verb of the app to invoke. :param dapr_address: Dapr address, it is optional field, by default it will be set to http://localhost:{daprHttpPort}. :param data_type: Defines how Functions runtime should treat the parameter value :param kwargs: Keyword arguments for specifying additional binding fields to include in the binding json |
| dapr_publish_output |
The dapr_publish_output decorator adds <xref:azure.functions.DaprPublishOutput> to the <xref:azure.functions.FunctionBuilder> object for building Function object used in worker function indexing model. This is equivalent to defining DaprPublishOutput in the function.json which enables function to publish topic. All optional fields will be given default value by function host when they are parsed by function host. Ref: https://aka.ms/azure-function-dapr-publish-output-binding output object in function code. :param pub_sub_name: The pub/sub name to publish to. :param topic: The name of the topic to publish to. :param dapr_address: Dapr address, it is optional field, by default ßit will be set to http://localhost:{daprHttpPort}. :param data_type: Defines how Functions runtime should treat the parameter value :param kwargs: Keyword arguments for specifying additional binding fields to include in the binding json |
| dapr_secret_input |
The dapr_secret_input decorator adds <xref:azure.functions.DaprSecretInput> to the <xref:azure.functions.FunctionBuilder> object for building Function object used in worker function indexing model. This is equivalent to defining DaprSecretInput in the function.json which enables function to read secret from underlying secret store component. All optional fields will be given default value by function host when they are parsed by function host. Ref: https://aka.ms/azure-function-dapr-secret-input-binding input object in function code. :param secret_store_name: The name of the secret store to get the secret from. :param key: The key identifying the name of the secret to get. :param metadata: An array of metadata properties in the form "key1=value1&key2=value2". :param dapr_address: Dapr address, it is optional field, by default it will be set to http://localhost:{daprHttpPort}. :param data_type: Defines how Functions runtime should treat the parameter value. :param kwargs: Keyword arguments for specifying additional binding fields to include in the binding json. |
| dapr_state_input |
The dapr_state_input decorator adds <xref:azure.functions.DaprStateInput> to the <xref:azure.functions.FunctionBuilder> object for building Function object used in worker function indexing model. This is equivalent to defining DaprStateInput in the function.json which enables function to read state from underlying state store component. All optional fields will be given default value by function host when they are parsed by function host. Ref: https://aka.ms/azure-function-dapr-state-input-binding input object in function code. :param state_store: State store containing the state. :param key: The name of the key. :param dapr_address: Dapr address, it is optional field, by default it will be set to http://localhost:{daprHttpPort}. :param data_type: Defines how Functions runtime should treat the parameter value. :param kwargs: Keyword arguments for specifying additional binding fields to include in the binding json. |
| dapr_state_output |
The dapr_state_output decorator adds <xref:azure.functions.DaprStateOutput> to the <xref:azure.functions.FunctionBuilder> object for building Function object used in worker function indexing model. This is equivalent to defining DaprStateOutput in the function.json which enables function to write to the dapr state store. All optional fields will be given default value by function host when they are parsed by function host. Ref: https://aka.ms/azure-function-dapr-state-output-binding output object in function code. :param state_store: State store containing the state for keys. :param key: The name of the key. :param dapr_address: Dapr address, it is optional field, by default it will be set to http://localhost:{daprHttpPort}. :param data_type: Defines how Functions runtime should treat the parameter value :param kwargs: Keyword arguments for specifying additional binding fields to include in the binding json |
| durable_client_input |
Register a Durable-client Function. |
| embeddings_input |
The embeddings input decorator creates embeddings which will be used to measure the relatedness of text strings. Ref: https://platform.openai.com/docs/guides/embeddings embeddings for. :param input_type: The type of the input. :param model: The ID of the model to use. :param max_chunk_length: The maximum number of characters to chunk the input into. Default value: 8 * 1024 :param max_overlap: The maximum number of characters to overlap between chunks. Default value: 128 :param data_type: Defines how Functions runtime should treat the parameter value :param kwargs: Keyword arguments for specifying additional binding fields to include in the binding json |
| embeddings_store_output |
Supported list of embeddings store is extensible, and more can be added by authoring a specially crafted NuGet package. Visit the currently supported vector specific folder for specific usage information:
variable which contains a connection string value :param collection: The collection or table to search. :param model: The ID of the model to use. :param max_chunk_length: The maximum number of characters to chunk the input into. :param max_overlap: The maximum number of characters to overlap between chunks. :param data_type: Optional. Defines how Functions runtime should treat the parameter value. Default value: None :param kwargs: Keyword arguments for specifying additional binding fields to include in the binding json |
| event_grid_output |
The event_grid_output decorator adds <xref:azure.functions.EventGridOutput> to the <xref:azure.functions.FunctionBuilder> object for building Function object used in worker function indexing model. This is equivalent to defining output binding in the function.json which enables function to write events to a custom topic. All optional fields will be given default value by function host when they are parsed by function host. Ref: https://aka.ms/eventgridtrigger represents the event. :param data_type: Defines how Functions runtime should treat the parameter value. :param topic_endpoint_uri: The name of an app setting that contains the URI for the custom topic. :param topic_key_setting: The name of an app setting that contains an access key for the custom topic. :param connection: The value of the common prefix for the setting that contains the topic endpoint URI. :return: Decorator function. |
| event_hub_output |
The event_hub_output decorator adds <xref:azure.functions.EventHubOutput> to the <xref:azure.functions.FunctionBuilder> object for building Function object used in worker function indexing model. This is equivalent to defining EventHubOutput in the function.json which enables function to write message(s) to the event hub. All optional fields will be given default value by function host when they are parsed by function host. Ref: https://aka.ms/azure-function-binding-event-hubs output object in function code. :param connection: The name of an app setting or setting collection that specifies how to connect to Event Hub. :param event_hub_name: The name of the event hub. :param data_type: Defines how Functions runtime should treat the parameter value. :param kwargs: Keyword arguments for specifying additional binding fields to include in the binding json. |
| function_name |
Optional: Sets name of the Function object. If not set, it will default to the name of the method name. additional setting fields :return: Decorator function. |
| generic_input_binding |
The generic_input_binding decorator adds <xref:azure.functions.GenericInputBinding> to the <xref:azure.functions.FunctionBuilder> object for building Function object used in worker function indexing model. This is equivalent to defining a generic input binding in the function.json which enables function to read data from a custom defined input source. All optional fields will be given default value by function host when they are parsed by function host. Ref: https://aka.ms/azure-function-binding-custom fields to include in the binding json. |
| generic_output_binding |
The generic_output_binding decorator adds <xref:azure.functions.GenericOutputBinding> to the <xref:azure.functions.FunctionBuilder> object for building Function object used in worker function indexing model. This is equivalent to defining a generic output binding in the function.json which enables function to write data from a custom defined output source. All optional fields will be given default value by function host when they are parsed by function host. Ref: https://aka.ms/azure-function-binding-custom fields to include in the binding json. |
| http_type |
Set http type of the Function object. |
| kafka_output |
The kafka_output decorator adds <xref:azure.functions.KafkaOutput> to the <xref:azure.functions.FunctionBuilder> object for building Function object used in worker function indexing model. This is equivalent to defining output binding in the function.json which enables function to write events to a kafka topic. All optional fields will be given default value by function host when they are parsed by function host. Ref: https://aka.ms/kafkaoutput represents the event. :param topic: The topic monitored by the trigger. :param broker_list: The list of Kafka brokers monitored by the trigger. :param avro_schema: This should be used only if a generic record should be generated. :param username: SASL username for use with the PLAIN and SASL-SCRAM-.. mechanisms. Default is empty string. This is equivalent to 'sasl.username' in librdkafka. :param password: SASL password for use with the PLAIN and SASL-SCRAM-.. mechanisms. Default is empty string. This is equivalent to 'sasl.password' in librdkafka. :param ssl_key_location: Path to client's private key (PEM) used for authentication. Default is empty string. This is equivalent to 'ssl.key.location' in librdkafka. :param ssl_ca_location: Path to CA certificate file for verifying the broker's certificate. This is equivalent to 'ssl.ca.location' in librdkafka. :param ssl_certificate_location: Path to client's certificate. This is equivalent to 'ssl.certificate.location' in librdkafka. :param ssl_key_password: Password for client's certificate. This is equivalent to 'ssl.key.password' in librdkafka. :param schema_registry_url: URL for the Avro Schema Registry. :param schema_registry_username: Username for the Avro Schema Registry. :param schema_registry_password: Password for the Avro Schema Registry. :param o_auth_bearer_method: Either 'default' or 'oidc'. sasl.oauthbearer in librdkafka. :param o_auth_bearer_client_id: Specify only when o_auth_bearer_method is 'oidc'. sasl.oauthbearer.client.id in librdkafka. :param o_auth_bearer_client_secret: Specify only when o_auth_bearer_method is 'oidc'. sasl.oauthbearer.client.secret in librdkafka. :param o_auth_bearer_scope: Specify only when o_auth_bearer_method is 'oidc'. Client use this to specify the scope of the access request to the broker. sasl.oauthbearer.scope in librdkafka. :param o_auth_bearer_token_endpoint_url: Specify only when o_auth_bearer_method is 'oidc'. sasl.oauthbearer.token.endpoint.url in librdkafka. :param o_auth_bearer_extensions: Allow additional information to be provided to the broker. Comma-separated list of key=value pairs. E.g., "supportFeatureX=true,organizationId=sales-emea". sasl.oauthbearer.extensions in librdkafka :param max_message_bytes: Maximum transmit message size. Default is 1MB :param batch_size: Maximum number of messages batched in one MessageSet Default is 10000. :param enable_idempotence: When set to true, the producer will ensure that messages are successfully produced exactly once and in the original produce order. Default is false. enforced locally and limits the time a produced message waits for successful delivery. A time of 0 is infinite. This is the maximum time used to deliver a message (including retries). Delivery error occurs when either the retry count or the message timeout are exceeded. Default is 300000. :param request_timeout_ms: The ack timeout of the producer request in milliseconds. Default is 5000. :param max_retries: How many times to retry sending a failing Message. Default is 2147483647. Retrying may cause reordering unless 'EnableIdempotence' is set to 'True'. :param authentication_mode: SASL mechanism to use for authentication. Allowed values: Gssapi, Plain, ScramSha256, ScramSha512. Default is Plain. This is equivalent to 'sasl.mechanism' in librdkafka. :param protocol: Gets or sets the security protocol used to communicate with brokers. Default is plain text. This is equivalent to 'security.protocol' in librdkafka. :param linger_ms: Linger.MS property provides the time between batches of messages being sent to cluster. Larger value allows more batching results in high throughput. :param data_type: Defines how Functions runtime should treat the parameter value. :param kwargs: Keyword arguments for specifying additional binding fields to include in the binding json |
| queue_output |
The queue_output decorator adds <xref:azure.functions.QueueOutput> to the <xref:azure.functions.FunctionBuilder> object for building Function object used in worker function indexing model. This is equivalent to defining QueueOutput in the function.json which enables function to write message(s) to the storage queue. All optional fields will be given default value by function host when they are parsed by function host. Ref: https://aka.ms/azure-function-binding-queue queue output object in function code. :param queue_name: The name of the queue to poll. :param connection: The name of an app setting or setting collection that specifies how to connect to Azure Queues. :param data_type: Defines how Functions runtime should treat the parameter value. fields to include in the binding json. |
| semantic_search_input |
The semantic search feature allows you to import documents into a vector database using an output binding and query the documents in that database using an input binding. For example, you can have a function that imports documents into a vector database and another function that issues queries to OpenAI using content stored in the vector database as context (also known as the Retrieval Augmented Generation, or RAG technique). Ref: https://platform.openai.com/docs/guides/embeddings contains a connection string value. :param collection: The name of the collection or table to search or store. :param query: The semantic query text to use for searching. :param embeddings_model: The ID of the model to use for embeddings. The default value is "text-embedding-ada-002". :param chat_model: The name of the Large Language Model to invoke for chat responses. The default value is "gpt-3.5-turbo". :param system_prompt: Optional. The system prompt to use for prompting the large language model. :param max_knowledge_count: Optional. The number of knowledge items to inject into the SystemPrompt. Default value: 1 :param data_type: Optional. Defines how Functions runtime should treat the parameter value. Default value: None :param kwargs: Keyword arguments for specifying additional binding fields to include in the binding json |
| service_bus_queue_output |
The service_bus_queue_output decorator adds <xref:azure.functions.ServiceBusQueueOutput> to the <xref:azure.functions.FunctionBuilder> object for building Function object used in worker function indexing model. This is equivalent to defining ServiceBusQueueOutput in the function.json which enables function to write message(s) to the service bus queue. All optional fields will be given default value by function host when they are parsed by function host. Ref: https://aka.ms/azure-function-binding-service-bus bus queue output object in function code. :param connection: The name of an app setting or setting collection that specifies how to connect to Service Bus. :param queue_name: Name of the queue to monitor. :param data_type: Defines how Functions runtime should treat the parameter value. :param access_rights: Access rights for the connection string. :return: Decorator function. |
| service_bus_topic_output |
The service_bus_topic_output decorator adds <xref:azure.functions.ServiceBusTopicOutput> to the <xref:azure.functions.FunctionBuilder> object for building Function object used in worker function indexing model. This is equivalent to defining ServiceBusTopicOutput in the function.json which enables function to write message(s) to the service bus topic. All optional fields will be given default value by function host when they are parsed by function host. Ref: https://aka.ms/azure-function-binding-service-bus bus topic output object in function code. :param connection: The name of an app setting or setting collection that specifies how to connect to Service Bus. :param topic_name: Name of the topic to monitor. :param subscription_name: Name of the subscription to monitor. :param data_type: Defines how Functions runtime should treat the parameter value, defaults to DataType.UNDEFINED. :param access_rights: Access rights for the connection string. :return: Decorator function. |
| sql_input |
The sql_input decorator adds <xref:azure.functions.SqlInput> to the <xref:azure.functions.FunctionBuilder> object for building Function object used in worker function indexing model. This decorator will work only with extension bundle 4.x and above. This is equivalent to defining SqlInput in the function.json which enables the function to read from a Sql database. All optional fields will be given default value by function host when they are parsed by function host. Ref: https://aka.ms/sqlbindings SqlRowList input object in function code :param command_text: The Transact-SQL query command or name of the stored procedure executed by the binding :param connection_string_setting: The name of an app setting that contains the connection string for the database against which the query or stored procedure is being executed :param command_type: A CommandType value, which is Text for a query and StoredProcedure for a stored procedure :param parameters: Zero or more parameter values passed to the command during execution as a single string. Must follow the format @param1=param1,@param2=param2 :param data_type: Defines how Functions runtime should treat the parameter value :param kwargs: Keyword arguments for specifying additional binding fields to include in the binding json |
| sql_output |
The sql_output decorator adds <xref:azure.functions.SqlOutput> to the <xref:azure.functions.FunctionBuilder> object for building Function object used in worker function indexing model. This decorator will work only with extension bundle 4.x and above. This is equivalent to defining SqlOutput in the function.json which enables the function to write to a Sql database. All optional fields will be given default value by function host when they are parsed by function host. Ref: https://aka.ms/sqlbindings Sql output object in function code :param command_text: The Transact-SQL query command or name of the stored procedure executed by the binding :param connection_string_setting: The name of an app setting that contains the connection string for the database against which the query or stored procedure is being executed :param data_type: Defines how Functions runtime should treat the parameter value :param kwargs: Keyword arguments for specifying additional binding fields to include in the binding json |
| table_input |
The table_input decorator adds <xref:azure.functions.TableInput> to the <xref:azure.functions.FunctionBuilder> object for building Function object used in worker function indexing model. This is equivalent to defining TableInput in the function.json which enables function to read a table in an Azure Storage or Cosmos DB account All optional fields will be given default value by function host when they are parsed by function host. Ref: https://aka.ms/tablesbindings the table or entity in function code. :param connection: The name of an app setting or setting collection that specifies how to connect to the table service. :param table_name: The Name of the table :param row_key: The row key of the table entity to read. :param partition_key: The partition key of the table entity to read. :param take: The maximum number of entities to return :param filter: An OData filter expression for the entities to return from the table. |
| table_output |
The table_output decorator adds <xref:azure.functions.TableOutput> to the <xref:azure.functions.FunctionBuilder> object for building Function object used in worker function indexing model. This is equivalent to defining TableOutput in the function.json which enables function to write entities to a table in an Azure Storage All optional fields will be given default value by function host when they are parsed by function host. Ref: https://aka.ms/tablesbindings the table or entity in function code. :param connection: The name of an app setting or setting collection that specifies how to connect to the table service. :param table_name: The Name of the table :param row_key: The row key of the table entity to read. :param partition_key: The partition key of the table entity to read. :param data_type: Defines how Functions runtime should treat the parameter value. |
| text_completion_input |
The textCompletion input binding can be used to invoke the OpenAI Chat Completions API and return the results to the function. Ref: https://platform.openai.com/docs/guides/text-generation/chat-completions-vs-completions # NoQA The examples below define "who is" HTTP-triggered functions with a hardcoded "who is {name}?" prompt, where {name} is the substituted with the value in the HTTP request path. The OpenAI input binding invokes the OpenAI GPT endpoint to surface the answer to the prompt to the function, which then returns the result text as the response content. string. :param model: the ID of the model to use. :param temperature: The 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. :param top_p: An alternative to sampling with temperature, called nucleus sampling, where the model considers the results of the tokens with top_p probability mass. So 0.1 means only the tokens comprising the top 10% probability mass are considered. It's generally recommend to use this or temperature :param max_tokens: The maximum number of tokens to generate in the completion. The token count of your prompt plus max_tokens cannot exceed the model's context length. Most models have a context length of 2048 tokens (except for the newest models, which support 4096). :param data_type: Defines how Functions runtime should treat the parameter value :param kwargs: Keyword arguments for specifying additional binding fields to include in the binding json |
assistant_create_output
The assistantCreate output binding creates a new assistant with a specified system prompt.
parameter value :param kwargs: Keyword arguments for specifying additional binding fields to include in the binding json
assistant_create_output(arg_name: str, data_type: DataType | str | None = None, **kwargs) -> Callable[[...], Any]Parameters
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arg_name
Required
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data_type
Required
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Default value: None
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Returns
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Decorator function. |
assistant_post_input
The assistantPost output binding sends a message to the assistant and saves the response in its internal state.
assistant to respond to. :param model: The OpenAI chat model to use. :param data_type: Defines how Functions runtime should treat the parameter value :param kwargs: Keyword arguments for specifying additional binding fields to include in the binding json
assistant_post_input(arg_name: str, id: str, user_message: str, model: str | None = None, data_type: DataType | str | None = None, **kwargs) -> Callable[[...], Any]Parameters
| Name | Description |
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arg_name
Required
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id
Required
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user_message
Required
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|
|
model
Required
|
Default value: None
|
|
data_type
Required
|
Default value: None
|
Returns
| Type | Description |
|---|---|
|
Decorator function. |
assistant_query_input
The assistantQuery input binding fetches the assistant history and passes it to the function.
history to fetch. The timestamp should be in ISO 8601 format - for example, 2023-08-01T00:00:00Z. :param id: The ID of the Assistant to query. :param data_type: Defines how Functions runtime should treat the parameter value :param kwargs: Keyword arguments for specifying additional binding fields to include in the binding json
assistant_query_input(arg_name: str, id: str, timestamp_utc: str, data_type: DataType | str | None = None, **kwargs) -> Callable[[...], Any]Parameters
| Name | Description |
|---|---|
|
arg_name
Required
|
|
|
id
Required
|
|
|
timestamp_utc
Required
|
|
|
data_type
Required
|
Default value: None
|
Returns
| Type | Description |
|---|---|
|
Decorator function. |
blob_input
The blob_input decorator adds <xref:azure.functions.BlobInput> to the <xref:azure.functions.FunctionBuilder> object for building Function object used in worker function indexing model. This is equivalent to defining BlobInput in the function.json which enables function to write message(s) to the storage blobs. All optional fields will be given default value by function host when they are parsed by function host.
Ref: https://aka.ms/azure-function-binding-storage-blob
that specifies how to connect to Azure Blobs. :param data_type: Defines how Functions runtime should treat the
parameter value.
fields to include in the binding json.
blob_input(arg_name: str, path: str, connection: str, data_type: DataType | None = None, **kwargs) -> Callable[[...], Any]Parameters
| Name | Description |
|---|---|
|
arg_name
Required
|
|
|
path
Required
|
|
|
connection
Required
|
|
|
data_type
Required
|
Default value: None
|
Returns
| Type | Description |
|---|---|
|
Decorator function. |
blob_output
The blob_output decorator adds <xref:azure.functions.BlobOutput> to the <xref:azure.functions.FunctionBuilder> object for building Function object used in worker function indexing model. This is equivalent to defining BlobOutput in the function.json which enables function to write message(s) to the storage blobs. All optional fields will be given default value by function host when they are parsed by function host.
Ref: https://aka.ms/azure-function-binding-storage-blob
fields to include in the binding json. :return: Decorator function.
blob_output(arg_name: str, path: str, connection: str, data_type: DataType | None = None, **kwargs) -> Callable[[...], Any]Parameters
| Name | Description |
|---|---|
|
arg_name
Required
|
The name of the variable that represents the blob in function code. |
|
path
Required
|
The path to the blob. |
|
connection
Required
|
The name of an app setting or setting collection that specifies how to connect to Azure Blobs. |
|
data_type
Required
|
Defines how Functions runtime should treat the parameter value. Default value: None
|
|
kwargs
Required
|
Keyword arguments for specifying additional binding |
cosmos_db_input
The cosmos_db_input decorator adds <xref:azure.functions.CosmosDBInput> to the <xref:azure.functions.FunctionBuilder> object for building Function object used in worker function indexing model. This decorator will work only with extension bundle 4.x and above. For additional details, please refer https://aka.ms/cosmosdb-v4-update. This is equivalent to defining CosmosDBInput in the function.json which
enables function to read from CosmosDB.
All optional fields will be given default value by function host when they are parsed by function host.
Ref: https://aka.ms/azure-function-binding-cosmosdb-v4
DocumentList input object in function code :param connection: The name of an app setting or setting container that
specifies how to connect to the Azure Cosmos DB account being monitored containing your Azure Cosmos DB connection string
document :param partition_key: Specifies the partition key value for the lookup :param id: The ID of the document to retrieve :param sql_query: An Azure Cosmos DB SQL query used for retrieving multiple documents :param preferred_locations: (Optional) Defines preferred locations (regions) for geo-replicated database accounts in the Azure Cosmos DB service. Values should be comma-separated. For example, East US,South Central US,North Europe :param data_type: Defines how Functions runtime should treat the parameter value :param kwargs: Keyword arguments for specifying additional binding fields to include in the binding json
cosmos_db_input(arg_name: str, connection: str, database_name: str, container_name: str, partition_key: str | None = None, id: str | None = None, sql_query: str | None = None, preferred_locations: str | None = None, data_type: DataType | str | None = None, **kwargs) -> Callable[[...], Any]Parameters
| Name | Description |
|---|---|
|
arg_name
Required
|
|
|
connection
Required
|
|
|
database_name
Required
|
|
|
container_name
Required
|
|
|
partition_key
Required
|
Default value: None
|
|
id
Required
|
Default value: None
|
|
sql_query
Required
|
Default value: None
|
|
preferred_locations
Required
|
Default value: None
|
|
data_type
Required
|
Default value: None
|
Returns
| Type | Description |
|---|---|
|
Decorator function. |
cosmos_db_input_v3
The cosmos_db_input_v3 decorator adds <xref:azure.functions.CosmosDBInput> to the <xref:azure.functions.FunctionBuilder> object for building Function object used in worker function indexing model. This decorator will work only with extension bundle 2.x or 3.x. For additional details, please refer https://aka.ms/cosmosdb-v4-update. This is equivalent to defining CosmosDBInput in the function.json which enables function to read from CosmosDB. All optional fields will be given default value by function host when they are parsed by function host.
Ref: https://aka.ms/azure-function-binding-cosmosdb-v2
DocumentList input object in function code. :param database_name: The database containing the document. :param collection_name: The name of the collection that contains the document. :param connection_string_setting: The name of the app setting containing your Azure Cosmos DB connection string. :param id: The ID of the document to retrieve. :param sql_query: An Azure Cosmos DB SQL query used for retrieving multiple documents. :param partition_key: Specifies the partition key value for the lookup. :param data_type: Defines how Functions runtime should treat the parameter value. :param kwargs: Keyword arguments for specifying additional binding fields to include in the binding json.
cosmos_db_input_v3(arg_name: str, database_name: str, collection_name: str, connection_string_setting: str, id: str | None = None, sql_query: str | None = None, partition_key: str | None = None, data_type: DataType | str | None = None, **kwargs) -> Callable[[...], Any]Parameters
| Name | Description |
|---|---|
|
arg_name
Required
|
|
|
database_name
Required
|
|
|
collection_name
Required
|
|
|
connection_string_setting
Required
|
|
|
id
Required
|
Default value: None
|
|
sql_query
Required
|
Default value: None
|
|
partition_key
Required
|
Default value: None
|
|
data_type
Required
|
Default value: None
|
Returns
| Type | Description |
|---|---|
|
Decorator function. |
cosmos_db_output
The cosmos_db_output decorator adds <xref:azure.functions.CosmosDBOutput> to the <xref:azure.functions.FunctionBuilder> object for building Function object used in worker function indexing model. This decorator will work only with extension bundle 4.x and above. For additional details, please refer https://aka.ms/cosmosdb-v4-update. This is equivalent to defining CosmosDBOutput in the function.json which enables function to write to the CosmosDB. All optional fields will be given default value by function host when they are parsed by function host.
Ref: https://aka.ms/azure-function-binding-cosmosdb-v4
output object in function code. :param connection: The name of an app setting or setting collection that specifies how to connect to the Azure Cosmos DB account being monitored :param database_name: The name of the Azure Cosmos DB database with the collection being monitored :param container_name: The name of the container being monitored :param create_if_not_exists: A boolean value to indicate whether the collection is created when it doesn't exist :param partition_key: When CreateIfNotExists is true, it defines the partition key path for the created collection :param container_throughput: When createIfNotExists is true, it defines the throughput of the created container PreferredLocations, it can leverage multi-region writes in the Azure Cosmos DB service :param preferred_locations: Defines preferred locations (regions) for geo-replicated database accounts in the Azure Cosmos DB service :param data_type: Defines how Functions runtime should treat the parameter value :param kwargs: Keyword arguments for specifying additional binding fields to include in the binding json
cosmos_db_output(arg_name: str, connection: str, database_name: str, container_name: str, create_if_not_exists: bool | None = None, partition_key: str | None = None, container_throughput: int | None = None, preferred_locations: str | None = None, data_type: DataType | str | None = None, **kwargs) -> Callable[[...], Any]Parameters
| Name | Description |
|---|---|
|
arg_name
Required
|
|
|
connection
Required
|
|
|
database_name
Required
|
|
|
container_name
Required
|
|
|
create_if_not_exists
Required
|
Default value: None
|
|
partition_key
Required
|
Default value: None
|
|
container_throughput
Required
|
Default value: None
|
|
preferred_locations
Required
|
Default value: None
|
|
data_type
Required
|
Default value: None
|
Returns
| Type | Description |
|---|---|
|
Decorator function. |
cosmos_db_output_v3
The cosmos_db_output_v3 decorator adds <xref:azure.functions.CosmosDBOutput> to the <xref:azure.functions.FunctionBuilder> object for building Function object used in worker function indexing model. This decorator will work only with extension bundle 2.x or 3.x. For additional details, please refer https://aka.ms/cosmosdb-v4-update.
This is equivalent to defining CosmosDBOutput
in the function.json which enables function to write to the CosmosDB. All optional fields will be given default value by function host when they are parsed by function host.
Ref: https://aka.ms/azure-function-binding-cosmosdb-v2
output object in function code. :param database_name: The name of the Azure Cosmos DB database with the collection being monitored. :param collection_name: The name of the collection being monitored. :param connection_string_setting: The name of an app setting or setting collection that specifies how to connect to the Azure Cosmos DB account being monitored. :param create_if_not_exists: A boolean value to indicate whether the collection is created when it doesn't exist. :param partition_key: When CreateIfNotExists is true, it defines the partition key path for the created collection. :param collection_throughput: When CreateIfNotExists is true, it defines the throughput of the created collection. :param use_multiple_write_locations: When set to true along with PreferredLocations, it can leverage multi-region writes in the Azure Cosmos DB service. :param preferred_locations: Defines preferred locations (regions) for geo-replicated database accounts in the Azure Cosmos DB service. :param data_type: Defines how Functions runtime should treat the parameter value. :param kwargs: Keyword arguments for specifying additional binding fields to include in the binding json.
cosmos_db_output_v3(arg_name: str, database_name: str, collection_name: str, connection_string_setting: str, create_if_not_exists: bool | None = None, partition_key: str | None = None, collection_throughput: int | None = None, use_multiple_write_locations: bool | None = None, preferred_locations: str | None = None, data_type: DataType | str | None = None, **kwargs) -> Callable[[...], Any]Parameters
| Name | Description |
|---|---|
|
arg_name
Required
|
|
|
database_name
Required
|
|
|
collection_name
Required
|
|
|
connection_string_setting
Required
|
|
|
create_if_not_exists
Required
|
Default value: None
|
|
partition_key
Required
|
Default value: None
|
|
collection_throughput
Required
|
Default value: None
|
|
use_multiple_write_locations
Required
|
Default value: None
|
|
preferred_locations
Required
|
Default value: None
|
|
data_type
Required
|
Default value: None
|
Returns
| Type | Description |
|---|---|
|
Decorator function. |
dapr_binding_output
The dapr_binding_output decorator adds <xref:azure.functions.DaprBindingOutput> to the <xref:azure.functions.FunctionBuilder> object for building Function object used in worker function indexing model. This is equivalent to defining DaprBindingOutput in the function.json which enables function to send a value to a Dapr output binding. All optional fields will be given default value by function host when they are parsed by function host.
Ref: https://aka.ms/azure-function-dapr-binding-output-binding
output object in function code. :param binding_name: The configured name of the binding. :param operation: The configured operation. :param dapr_address: Dapr address, it is optional field, by default it will be set to http://localhost:{daprHttpPort}. :param data_type: Defines how Functions runtime should treat the parameter value :param kwargs: Keyword arguments for specifying additional binding fields to include in the binding json
dapr_binding_output(arg_name: str, binding_name: str, operation: str, dapr_address: str | None = None, data_type: DataType | str | None = None, **kwargs) -> Callable[[...], Any]Parameters
| Name | Description |
|---|---|
|
arg_name
Required
|
|
|
binding_name
Required
|
|
|
operation
Required
|
|
|
dapr_address
Required
|
Default value: None
|
|
data_type
Required
|
Default value: None
|
Returns
| Type | Description |
|---|---|
|
Decorator function. |
dapr_invoke_output
The dapr_invoke_output decorator adds <xref:azure.functions.DaprInvokeOutput> to the <xref:azure.functions.FunctionBuilder> object for building Function object used in worker function indexing model. This is equivalent to defining DaprInvokeOutput in the function.json which enables function to invoke another Dapr App. All optional fields will be given default value by function host when they are parsed by function host.
Ref: https://aka.ms/azure-function-dapr-invoke-output-binding
output object in function code. :param app_id: The dapr app name to invoke. :param method_name: The method name of the app to invoke. :param http_verb: The http verb of the app to invoke. :param dapr_address: Dapr address, it is optional field, by default it will be set to http://localhost:{daprHttpPort}. :param data_type: Defines how Functions runtime should treat the parameter value :param kwargs: Keyword arguments for specifying additional binding fields to include in the binding json
dapr_invoke_output(arg_name: str, app_id: str, method_name: str, http_verb: str, dapr_address: str | None = None, data_type: DataType | str | None = None, **kwargs) -> Callable[[...], Any]Parameters
| Name | Description |
|---|---|
|
arg_name
Required
|
|
|
app_id
Required
|
|
|
method_name
Required
|
|
|
http_verb
Required
|
|
|
dapr_address
Required
|
Default value: None
|
|
data_type
Required
|
Default value: None
|
Returns
| Type | Description |
|---|---|
|
Decorator function. |
dapr_publish_output
The dapr_publish_output decorator adds <xref:azure.functions.DaprPublishOutput> to the <xref:azure.functions.FunctionBuilder> object for building Function object used in worker function indexing model. This is equivalent to defining DaprPublishOutput in the function.json which enables function to publish topic. All optional fields will be given default value by function host when they are parsed by function host.
Ref: https://aka.ms/azure-function-dapr-publish-output-binding
output object in function code. :param pub_sub_name: The pub/sub name to publish to. :param topic: The name of the topic to publish to. :param dapr_address: Dapr address, it is optional field, by default ßit will be set to http://localhost:{daprHttpPort}. :param data_type: Defines how Functions runtime should treat the parameter value :param kwargs: Keyword arguments for specifying additional binding fields to include in the binding json
dapr_publish_output(arg_name: str, pub_sub_name: str, topic: str, dapr_address: str | None = None, data_type: DataType | str | None = None, **kwargs) -> Callable[[...], Any]Parameters
| Name | Description |
|---|---|
|
arg_name
Required
|
|
|
pub_sub_name
Required
|
|
|
topic
Required
|
|
|
dapr_address
Required
|
Default value: None
|
|
data_type
Required
|
Default value: None
|
Returns
| Type | Description |
|---|---|
|
Decorator function. |
dapr_secret_input
The dapr_secret_input decorator adds <xref:azure.functions.DaprSecretInput> to the <xref:azure.functions.FunctionBuilder> object for building Function object used in worker function indexing model. This is equivalent to defining DaprSecretInput in the function.json which enables function to read secret from underlying secret store component. All optional fields will be given default value by function host when they are parsed by function host.
Ref: https://aka.ms/azure-function-dapr-secret-input-binding
input object in function code. :param secret_store_name: The name of the secret store to get the secret from. :param key: The key identifying the name of the secret to get. :param metadata: An array of metadata properties in the form "key1=value1&key2=value2". :param dapr_address: Dapr address, it is optional field, by default it will be set to http://localhost:{daprHttpPort}. :param data_type: Defines how Functions runtime should treat the parameter value. :param kwargs: Keyword arguments for specifying additional binding fields to include in the binding json.
dapr_secret_input(arg_name: str, secret_store_name: str, key: str, metadata: str, dapr_address: str | None = None, data_type: DataType | str | None = None, **kwargs) -> Callable[[...], Any]Parameters
| Name | Description |
|---|---|
|
arg_name
Required
|
|
|
secret_store_name
Required
|
|
|
key
Required
|
|
|
metadata
Required
|
|
|
dapr_address
Required
|
Default value: None
|
|
data_type
Required
|
Default value: None
|
Returns
| Type | Description |
|---|---|
|
Decorator function. |
dapr_state_input
The dapr_state_input decorator adds <xref:azure.functions.DaprStateInput> to the <xref:azure.functions.FunctionBuilder> object for building Function object used in worker function indexing model. This is equivalent to defining DaprStateInput in the function.json which enables function to read state from underlying state store component. All optional fields will be given default value by function host when they are parsed by function host.
Ref: https://aka.ms/azure-function-dapr-state-input-binding
input object in function code. :param state_store: State store containing the state. :param key: The name of the key. :param dapr_address: Dapr address, it is optional field, by default it will be set to http://localhost:{daprHttpPort}. :param data_type: Defines how Functions runtime should treat the parameter value. :param kwargs: Keyword arguments for specifying additional binding fields to include in the binding json.
dapr_state_input(arg_name: str, state_store: str, key: str, dapr_address: str | None = None, data_type: DataType | str | None = None, **kwargs) -> Callable[[...], Any]Parameters
| Name | Description |
|---|---|
|
arg_name
Required
|
|
|
state_store
Required
|
|
|
key
Required
|
|
|
dapr_address
Required
|
Default value: None
|
|
data_type
Required
|
Default value: None
|
Returns
| Type | Description |
|---|---|
|
Decorator function. |
dapr_state_output
The dapr_state_output decorator adds <xref:azure.functions.DaprStateOutput> to the <xref:azure.functions.FunctionBuilder> object for building Function object used in worker function indexing model. This is equivalent to defining DaprStateOutput in the function.json which enables function to write to the dapr state store. All optional fields will be given default value by function host when they are parsed by function host.
Ref: https://aka.ms/azure-function-dapr-state-output-binding
output object in function code. :param state_store: State store containing the state for keys. :param key: The name of the key. :param dapr_address: Dapr address, it is optional field, by default it will be set to http://localhost:{daprHttpPort}. :param data_type: Defines how Functions runtime should treat the parameter value :param kwargs: Keyword arguments for specifying additional binding fields to include in the binding json
dapr_state_output(arg_name: str, state_store: str, key: str, dapr_address: str | None = None, data_type: DataType | str | None = None, **kwargs) -> Callable[[...], Any]Parameters
| Name | Description |
|---|---|
|
arg_name
Required
|
|
|
state_store
Required
|
|
|
key
Required
|
|
|
dapr_address
Required
|
Default value: None
|
|
data_type
Required
|
Default value: None
|
Returns
| Type | Description |
|---|---|
|
Decorator function. |
durable_client_input
Register a Durable-client Function.
durable_client_input(client_name: str, task_hub: str | None = None, connection_name: str | None = None)Parameters
| Name | Description |
|---|---|
|
client_name
Required
|
Parameter name of durable client. |
|
task_hub
Required
|
<xref:Optional>[str]
Used in scenarios where multiple function apps share the same storage account but need to be isolated from each other. If not specified, the default value from host.json is used. This value must match the value used by the target orchestrator functions. Default value: None
|
|
connection_name
Required
|
<xref:Optional>[str]
The name of an app setting that contains a storage account connection string. The storage account represented by this connection string must be the same one used by the target orchestrator functions. If not specified, the default storage account connection string for the function app is used. Default value: None
|
embeddings_input
The embeddings input decorator creates embeddings which will be used to measure the relatedness of text strings.
Ref: https://platform.openai.com/docs/guides/embeddings
embeddings for. :param input_type: The type of the input. :param model: The ID of the model to use. :param max_chunk_length: The maximum number of characters to chunk the input into. Default value: 8 * 1024 :param max_overlap: The maximum number of characters to overlap between chunks. Default value: 128 :param data_type: Defines how Functions runtime should treat the parameter value :param kwargs: Keyword arguments for specifying additional binding fields to include in the binding json
embeddings_input(arg_name: str, input: str, input_type: InputType, model: str | None = None, max_chunk_length: int | None = 8192, max_overlap: int | None = 128, data_type: DataType | str | None = None, **kwargs) -> Callable[[...], Any]Parameters
| Name | Description |
|---|---|
|
arg_name
Required
|
|
|
input
Required
|
|
|
input_type
Required
|
|
|
model
Required
|
Default value: None
|
|
max_chunk_length
Required
|
Default value: 8192
|
|
max_overlap
Required
|
Default value: 128
|
|
data_type
Required
|
Default value: None
|
Returns
| Type | Description |
|---|---|
|
Decorator function. |
embeddings_store_output
Supported list of embeddings store is extensible, and more can be added by authoring a specially crafted NuGet package. Visit the currently supported vector specific folder for specific usage information:
Azure AI Search
Azure Data Explorer
Azure Cosmos DB using MongoDB
variable which contains a connection string value :param collection: The collection or table to search. :param model: The ID of the model to use. :param max_chunk_length: The maximum number of characters to chunk the input into. :param max_overlap: The maximum number of characters to overlap between chunks. :param data_type: Optional. Defines how Functions runtime should treat the parameter value. Default value: None :param kwargs: Keyword arguments for specifying additional binding fields to include in the binding json
embeddings_store_output(arg_name: str, input: str, input_type: InputType, connection_name: str, collection: str, model: OpenAIModels | None = OpenAIModels.DefaultEmbeddingsModel, max_chunk_length: int | None = 8192, max_overlap: int | None = 128, data_type: DataType | str | None = None, **kwargs) -> Callable[[...], Any]Parameters
| Name | Description |
|---|---|
|
arg_name
Required
|
|
|
input
Required
|
|
|
input_type
Required
|
|
|
connection_name
Required
|
|
|
collection
Required
|
|
|
model
Required
|
Default value: DefaultEmbeddingsModel
|
|
max_chunk_length
Required
|
Default value: 8192
|
|
max_overlap
Required
|
Default value: 128
|
|
data_type
Required
|
Default value: None
|
Returns
| Type | Description |
|---|---|
|
Decorator function. |
event_grid_output
The event_grid_output decorator adds <xref:azure.functions.EventGridOutput> to the <xref:azure.functions.FunctionBuilder> object for building Function object used in worker function indexing model. This is equivalent to defining output binding in the function.json which enables function to write events to a custom topic. All optional fields will be given default value by function host when they are parsed by function host.
Ref: https://aka.ms/eventgridtrigger
represents the event. :param data_type: Defines how Functions runtime should treat the parameter value. :param topic_endpoint_uri: The name of an app setting that contains the URI for the custom topic. :param topic_key_setting: The name of an app setting that contains an access key for the custom topic. :param connection: The value of the common prefix for the setting that contains the topic endpoint URI. :return: Decorator function.
event_grid_output(arg_name: str, topic_endpoint_uri: str | None = None, topic_key_setting: str | None = None, connection: str | None = None, data_type: DataType | str | None = None, **kwargs) -> Callable[[...], Any]Parameters
| Name | Description |
|---|---|
|
arg_name
Required
|
The variable name used in function code that |
|
topic_endpoint_uri
Required
|
Default value: None
|
|
topic_key_setting
Required
|
Default value: None
|
|
connection
Required
|
Default value: None
|
|
data_type
Required
|
Default value: None
|
event_hub_output
The event_hub_output decorator adds <xref:azure.functions.EventHubOutput> to the <xref:azure.functions.FunctionBuilder> object for building Function object used in worker function indexing model. This is equivalent to defining EventHubOutput in the function.json which enables function to write message(s) to the event hub. All optional fields will be given default value by function host when they are parsed by function host.
Ref: https://aka.ms/azure-function-binding-event-hubs
output object in function code. :param connection: The name of an app setting or setting collection that specifies how to connect to Event Hub. :param event_hub_name: The name of the event hub. :param data_type: Defines how Functions runtime should treat the parameter value. :param kwargs: Keyword arguments for specifying additional binding fields to include in the binding json.
event_hub_output(arg_name: str, connection: str, event_hub_name: str, data_type: DataType | str | None = None, **kwargs) -> Callable[[...], Any]Parameters
| Name | Description |
|---|---|
|
arg_name
Required
|
|
|
connection
Required
|
|
|
event_hub_name
Required
|
|
|
data_type
Required
|
Default value: None
|
Returns
| Type | Description |
|---|---|
|
Decorator function. |
function_name
Optional: Sets name of the Function object. If not set, it will default to the name of the method name.
additional setting fields :return: Decorator function.
function_name(name: str, setting_extra_fields: Dict[str, Any] | None = None) -> Callable[[...], Any]Parameters
| Name | Description |
|---|---|
|
name
Required
|
Name of the function. |
|
setting_extra_fields
Required
|
Keyword arguments for specifying Default value: None
|
generic_input_binding
The generic_input_binding decorator adds <xref:azure.functions.GenericInputBinding> to the <xref:azure.functions.FunctionBuilder> object for building Function object used in worker function indexing model. This is equivalent to defining a generic input binding in the function.json which enables function to read data from a custom defined input source. All optional fields will be given default value by function host when they are parsed by function host.
Ref: https://aka.ms/azure-function-binding-custom
fields to include in the binding json.
generic_input_binding(arg_name: str, type: str, data_type: DataType | str | None = None, **kwargs) -> Callable[[...], Any]Parameters
| Name | Description |
|---|---|
|
arg_name
Required
|
|
|
type
Required
|
|
|
data_type
Required
|
Default value: None
|
Returns
| Type | Description |
|---|---|
|
Decorator function. |
generic_output_binding
The generic_output_binding decorator adds <xref:azure.functions.GenericOutputBinding> to the <xref:azure.functions.FunctionBuilder> object for building Function object used in worker function indexing model. This is equivalent to defining a generic output binding in the function.json which enables function to write data from a custom defined output source. All optional fields will be given default value by function host when they are parsed by function host.
Ref: https://aka.ms/azure-function-binding-custom
fields to include in the binding json.
generic_output_binding(arg_name: str, type: str, data_type: DataType | str | None = None, **kwargs) -> Callable[[...], Any]Parameters
| Name | Description |
|---|---|
|
arg_name
Required
|
|
|
type
Required
|
|
|
data_type
Required
|
Default value: None
|
Returns
| Type | Description |
|---|---|
|
Decorator function. |
http_type
Set http type of the Function object.
http_type(http_type: str) -> Callable[[...], Any]Parameters
| Name | Description |
|---|---|
|
http_type
Required
|
Http type of the function. |
Returns
| Type | Description |
|---|---|
|
Decorator function. |
kafka_output
The kafka_output decorator adds <xref:azure.functions.KafkaOutput> to the <xref:azure.functions.FunctionBuilder> object for building Function object used in worker function indexing model. This is equivalent to defining output binding in the function.json which enables function to write events to a kafka topic. All optional fields will be given default value by function host when they are parsed by function host.
Ref: https://aka.ms/kafkaoutput
represents the event. :param topic: The topic monitored by the trigger. :param broker_list: The list of Kafka brokers monitored by the trigger. :param avro_schema: This should be used only if a generic record should be generated. :param username: SASL username for use with the PLAIN and SASL-SCRAM-..
mechanisms. Default is empty string. This is equivalent to
'sasl.username' in librdkafka. :param password: SASL password for use with the PLAIN and SASL-SCRAM-..
mechanisms. Default is empty string. This is equivalent to
'sasl.password' in librdkafka. :param ssl_key_location: Path to client's private key (PEM) used for
authentication. Default is empty string. This is equivalent to
'ssl.key.location' in librdkafka. :param ssl_ca_location: Path to CA certificate file for verifying the broker's certificate. This is equivalent to 'ssl.ca.location' in librdkafka. :param ssl_certificate_location: Path to client's certificate. This is equivalent to 'ssl.certificate.location' in librdkafka. :param ssl_key_password: Password for client's certificate. This is equivalent to 'ssl.key.password' in librdkafka. :param schema_registry_url: URL for the Avro Schema Registry. :param schema_registry_username: Username for the Avro Schema Registry. :param schema_registry_password: Password for the Avro Schema Registry. :param o_auth_bearer_method: Either 'default' or 'oidc'. sasl.oauthbearer in librdkafka. :param o_auth_bearer_client_id: Specify only when o_auth_bearer_method is 'oidc'. sasl.oauthbearer.client.id in librdkafka. :param o_auth_bearer_client_secret: Specify only when o_auth_bearer_method is 'oidc'. sasl.oauthbearer.client.secret in librdkafka. :param o_auth_bearer_scope: Specify only when o_auth_bearer_method is 'oidc'. Client use this to specify the scope of the access request to the broker. sasl.oauthbearer.scope in librdkafka. :param o_auth_bearer_token_endpoint_url: Specify only when o_auth_bearer_method is 'oidc'. sasl.oauthbearer.token.endpoint.url in librdkafka. :param o_auth_bearer_extensions: Allow additional information to be provided to the broker. Comma-separated list of key=value pairs. E.g., "supportFeatureX=true,organizationId=sales-emea". sasl.oauthbearer.extensions in librdkafka :param max_message_bytes: Maximum transmit message size. Default is 1MB :param batch_size: Maximum number of messages batched in one MessageSet Default is 10000. :param enable_idempotence: When set to true, the producer will ensure
that messages are successfully produced exactly once and in the original produce order. Default is false.
enforced locally and limits the time a produced message waits for successful delivery. A time of 0 is infinite. This is the maximum time
used to deliver a message (including retries). Delivery error occurs
when either the retry count or the message timeout are exceeded. Default is 300000. :param request_timeout_ms: The ack timeout of the producer request in milliseconds. Default is 5000. :param max_retries: How many times to retry sending a failing Message. Default is 2147483647. Retrying may cause reordering unless 'EnableIdempotence' is set to 'True'. :param authentication_mode: SASL mechanism to use for authentication. Allowed values: Gssapi, Plain, ScramSha256, ScramSha512. Default is Plain. This is equivalent to 'sasl.mechanism' in librdkafka. :param protocol: Gets or sets the security protocol used to communicate
with brokers. Default is plain text. This is equivalent to
'security.protocol' in librdkafka. :param linger_ms: Linger.MS property provides the time between batches of messages being sent to cluster. Larger value allows more batching results in high throughput. :param data_type: Defines how Functions runtime should treat the parameter value. :param kwargs: Keyword arguments for specifying additional binding fields to include in the binding json
kafka_output(arg_name: str, topic: str, broker_list: str, avro_schema: str | None = None, username: str | None = None, password: str | None = None, ssl_key_location: str | None = None, ssl_ca_location: str | None = None, ssl_certificate_location: str | None = None, ssl_key_password: str | None = None, schema_registry_url: str | None = None, schema_registry_username: str | None = None, schema_registry_password: str | None = None, o_auth_bearer_method: OAuthBearerMethod | str | None = None, o_auth_bearer_client_id: str | None = None, o_auth_bearer_client_secret: str | None = None, o_auth_bearer_scope: str | None = None, o_auth_bearer_token_endpoint_url: str | None = None, o_auth_bearer_extensions: str | None = None, max_message_bytes: int = 1000000, batch_size: int = 10000, enable_idempotence: bool = False, message_timeout_ms: int = 300000, request_timeout_ms: int = 5000, max_retries: int = 2147483647, authentication_mode: BrokerAuthenticationMode | str | None = 'NOTSET', protocol: BrokerProtocol | str | None = 'NOTSET', linger_ms: int = 5, data_type: DataType | str | None = None, **kwargs) -> Callable[[...], Any]Parameters
| Name | Description |
|---|---|
|
arg_name
Required
|
|
|
topic
Required
|
|
|
broker_list
Required
|
|
|
avro_schema
Required
|
Default value: None
|
|
username
Required
|
Default value: None
|
|
password
Required
|
Default value: None
|
|
ssl_key_location
Required
|
Default value: None
|
|
ssl_ca_location
Required
|
Default value: None
|
|
ssl_certificate_location
Required
|
Default value: None
|
|
ssl_key_password
Required
|
Default value: None
|
|
schema_registry_url
Required
|
Default value: None
|
|
schema_registry_username
Required
|
Default value: None
|
|
schema_registry_password
Required
|
Default value: None
|
|
o_auth_bearer_method
Required
|
Default value: None
|
|
o_auth_bearer_client_id
Required
|
Default value: None
|
|
o_auth_bearer_client_secret
Required
|
Default value: None
|
|
o_auth_bearer_scope
Required
|
Default value: None
|
|
o_auth_bearer_token_endpoint_url
Required
|
Default value: None
|
|
o_auth_bearer_extensions
Required
|
Default value: None
|
|
max_message_bytes
Required
|
Default value: 1000000
|
|
batch_size
Required
|
Default value: 10000
|
|
enable_idempotence
Required
|
Default value: False
|
|
message_timeout_ms
Required
|
Default value: 300000
|
|
request_timeout_ms
Required
|
Default value: 5000
|
|
max_retries
Required
|
Default value: 2147483647
|
|
authentication_mode
Required
|
Default value: NOTSET
|
|
protocol
Required
|
Default value: NOTSET
|
|
linger_ms
Required
|
Default value: 5
|
|
data_type
Required
|
Default value: None
|
Returns
| Type | Description |
|---|---|
|
Decorator function. |
queue_output
The queue_output decorator adds <xref:azure.functions.QueueOutput> to the <xref:azure.functions.FunctionBuilder> object for building Function object used in worker function indexing model. This is equivalent to defining QueueOutput in the function.json which enables function to write message(s) to the storage queue. All optional fields will be given default value by function host when they are parsed by function host.
Ref: https://aka.ms/azure-function-binding-queue
queue output object in function code. :param queue_name: The name of the queue to poll. :param connection: The name of an app setting or setting collection that specifies how to connect to Azure Queues. :param data_type: Defines how Functions runtime should treat the
parameter value.
fields to include in the binding json.
queue_output(arg_name: str, queue_name: str, connection: str, data_type: DataType | None = None, **kwargs) -> Callable[[...], Any]Parameters
| Name | Description |
|---|---|
|
arg_name
Required
|
|
|
queue_name
Required
|
|
|
connection
Required
|
|
|
data_type
Required
|
Default value: None
|
Returns
| Type | Description |
|---|---|
|
Decorator function. |
semantic_search_input
The semantic search feature allows you to import documents into a vector database using an output binding and query the documents in that database using an input binding. For example, you can have a function that imports documents into a vector database and another function that issues queries to OpenAI using content stored in the vector database as
context (also known as the Retrieval Augmented Generation, or RAG technique).
Ref: https://platform.openai.com/docs/guides/embeddings
contains a connection string value. :param collection: The name of the collection or table to search or store. :param query: The semantic query text to use for searching. :param embeddings_model: The ID of the model to use for embeddings. The default value is "text-embedding-ada-002". :param chat_model: The name of the Large Language Model to invoke for chat responses. The default value is "gpt-3.5-turbo". :param system_prompt: Optional. The system prompt to use for prompting the large language model. :param max_knowledge_count: Optional. The number of knowledge items to inject into the SystemPrompt. Default value: 1 :param data_type: Optional. Defines how Functions runtime should treat the parameter value. Default value: None :param kwargs: Keyword arguments for specifying additional binding fields to include in the binding json
semantic_search_input(arg_name: str, connection_name: str, collection: str, query: str | None = None, embeddings_model: OpenAIModels | None = OpenAIModels.DefaultEmbeddingsModel, chat_model: OpenAIModels | None = OpenAIModels.DefaultChatModel, system_prompt: str | None = 'You are a helpful assistant. You are responding to requests\n from a user about internal emails and documents. You can and\n should refer to the internal documents to help respond to\n requests. If a user makes a request that\'s not covered by the\n internal emails and documents, explain that you don\'t know the\n answer or that you don\'t have access to the information.\n\n The following is a list of documents that you can refer to when\n answering questions. The documents are in the format\n [filename]: [text] and are separated by newlines. If you answer\n a question by referencing any of the documents, please cite the\n document in your answer. For example, if you answer a question\n by referencing info.txt, you should add "Reference: info.txt"\n to the end of your answer on a separate line.', max_knowledge_count: int | None = 1, data_type: DataType | str | None = None, **kwargs) -> Callable[[...], Any]Parameters
| Name | Description |
|---|---|
|
arg_name
Required
|
|
|
connection_name
Required
|
|
|
collection
Required
|
|
|
query
Required
|
Default value: None
|
|
embeddings_model
Required
|
Default value: DefaultEmbeddingsModel
|
|
chat_model
Required
|
Default value: DefaultChatModel
|
|
system_prompt
Required
|
Default value: You are a helpful assistant. You are responding to requests
from a user about internal emails and documents. You can and
should refer to the internal documents to help respond to
requests. If a user makes a request that's not covered by the
internal emails and documents, explain that you don't know the
answer or that you don't have access to the information.
The following is a list of documents that you can refer to when
answering questions. The documents are in the format
[filename]: [text] and are separated by newlines. If you answer
a question by referencing any of the documents, please cite the
document in your answer. For example, if you answer a question
by referencing info.txt, you should add "Reference: info.txt"
to the end of your answer on a separate line.
|
|
max_knowledge_count
Required
|
Default value: 1
|
|
data_type
Required
|
Default value: None
|
Returns
| Type | Description |
|---|---|
|
Decorator function. |
service_bus_queue_output
The service_bus_queue_output decorator adds <xref:azure.functions.ServiceBusQueueOutput> to the <xref:azure.functions.FunctionBuilder> object for building Function object used in worker function indexing model. This is equivalent to defining ServiceBusQueueOutput in the function.json which enables function to write message(s) to the service bus queue. All optional fields will be given default value by function host when they are parsed by function host.
Ref: https://aka.ms/azure-function-binding-service-bus
bus queue output object in function code. :param connection: The name of an app setting or setting collection that specifies how to connect to Service Bus. :param queue_name: Name of the queue to monitor. :param data_type: Defines how Functions runtime should treat the parameter value. :param access_rights: Access rights for the connection string. :return: Decorator function.
service_bus_queue_output(arg_name: str, connection: str, queue_name: str, data_type: DataType | str | None = None, access_rights: AccessRights | str | None = None, **kwargs) -> Callable[[...], Any]Parameters
| Name | Description |
|---|---|
|
arg_name
Required
|
The name of the variable that represents service |
|
connection
Required
|
|
|
queue_name
Required
|
|
|
data_type
Required
|
Default value: None
|
|
access_rights
Required
|
Default value: None
|
service_bus_topic_output
The service_bus_topic_output decorator adds <xref:azure.functions.ServiceBusTopicOutput> to the <xref:azure.functions.FunctionBuilder> object for building Function object used in worker function indexing model. This is equivalent to defining ServiceBusTopicOutput in the function.json which enables function to write message(s) to the service bus topic. All optional fields will be given default value by function host when they are parsed by function host.
Ref: https://aka.ms/azure-function-binding-service-bus
bus topic output object in function code. :param connection: The name of an app setting or setting collection that specifies how to connect to Service Bus. :param topic_name: Name of the topic to monitor. :param subscription_name: Name of the subscription to monitor. :param data_type: Defines how Functions runtime should treat the parameter value, defaults to DataType.UNDEFINED. :param access_rights: Access rights for the connection string. :return: Decorator function.
service_bus_topic_output(arg_name: str, connection: str, topic_name: str, subscription_name: str | None = None, data_type: DataType | str | None = None, access_rights: AccessRights | str | None = None, **kwargs) -> Callable[[...], Any]Parameters
| Name | Description |
|---|---|
|
arg_name
Required
|
The name of the variable that represents service |
|
connection
Required
|
|
|
topic_name
Required
|
|
|
subscription_name
Required
|
Default value: None
|
|
data_type
Required
|
Default value: None
|
|
access_rights
Required
|
Default value: None
|
sql_input
The sql_input decorator adds <xref:azure.functions.SqlInput> to the <xref:azure.functions.FunctionBuilder> object for building Function object used in worker function indexing model. This decorator will work only with extension bundle 4.x and above. This is equivalent to defining SqlInput in the function.json which enables the function to read from a Sql database. All optional fields will be given default value by function host when they are parsed by function host.
Ref: https://aka.ms/sqlbindings
SqlRowList input object in function code :param command_text: The Transact-SQL query command or name of the stored procedure executed by the binding :param connection_string_setting: The name of an app setting that contains the connection string for the database against which the query or stored procedure is being executed :param command_type: A CommandType value, which is Text for a query and StoredProcedure for a stored procedure :param parameters: Zero or more parameter values passed to the command during execution as a single string. Must follow the format @param1=param1,@param2=param2 :param data_type: Defines how Functions runtime should treat the parameter value :param kwargs: Keyword arguments for specifying additional binding fields to include in the binding json
sql_input(arg_name: str, command_text: str, connection_string_setting: str, command_type: str | None = 'Text', parameters: str | None = None, data_type: DataType | None = None, **kwargs) -> Callable[[...], Any]Parameters
| Name | Description |
|---|---|
|
arg_name
Required
|
|
|
command_text
Required
|
|
|
connection_string_setting
Required
|
|
|
command_type
Required
|
Default value: Text
|
|
parameters
Required
|
Default value: None
|
|
data_type
Required
|
Default value: None
|
Returns
| Type | Description |
|---|---|
|
Decorator function. |
sql_output
The sql_output decorator adds <xref:azure.functions.SqlOutput> to the <xref:azure.functions.FunctionBuilder> object for building Function object used in worker function indexing model. This decorator will work only with extension bundle 4.x and above. This is equivalent to defining SqlOutput in the function.json which enables the function to write to a Sql database. All optional fields will be given default value by function host when they are parsed by function host.
Ref: https://aka.ms/sqlbindings
Sql output object in function code :param command_text: The Transact-SQL query command or name of the stored procedure executed by the binding :param connection_string_setting: The name of an app setting that contains the connection string for the database against which the query or stored procedure is being executed :param data_type: Defines how Functions runtime should treat the parameter value :param kwargs: Keyword arguments for specifying additional binding fields to include in the binding json
sql_output(arg_name: str, command_text: str, connection_string_setting: str, data_type: DataType | None = None, **kwargs) -> Callable[[...], Any]Parameters
| Name | Description |
|---|---|
|
arg_name
Required
|
|
|
command_text
Required
|
|
|
connection_string_setting
Required
|
|
|
data_type
Required
|
Default value: None
|
Returns
| Type | Description |
|---|---|
|
Decorator function. |
table_input
The table_input decorator adds <xref:azure.functions.TableInput> to the <xref:azure.functions.FunctionBuilder> object for building Function object used in worker function indexing model. This is equivalent to defining TableInput in the function.json which enables function to read a table in an Azure Storage or Cosmos DB account All optional fields will be given default value by function host when they are parsed by function host.
Ref: https://aka.ms/tablesbindings
the table or entity in function code. :param connection: The name of an app setting or setting collection that specifies how to connect to the table service. :param table_name: The Name of the table :param row_key: The row key of the table entity to read. :param partition_key: The partition key of the table entity to read. :param take: The maximum number of entities to return :param filter: An OData filter expression for the entities to return
from the table.
table_input(arg_name: str, connection: str, table_name: str, row_key: str | None = None, partition_key: str | None = None, take: int | None = None, filter: str | None = None, data_type: DataType | str | None = None) -> Callable[[...], Any]Parameters
| Name | Description |
|---|---|
|
data_type
|
Defines how Functions runtime should treat the parameter value. Default value: None
|
|
arg_name
Required
|
Default value: None
|
|
connection
Required
|
Default value: None
|
|
table_name
Required
|
Default value: None
|
|
row_key
|
Default value: None
|
|
partition_key
|
Default value: None
|
|
take
|
Default value: None
|
|
filter
|
Default value: None
|
Returns
| Type | Description |
|---|---|
|
Decorator function. |
table_output
The table_output decorator adds <xref:azure.functions.TableOutput> to the <xref:azure.functions.FunctionBuilder> object for building Function object used in worker function indexing model. This is equivalent to defining TableOutput in the function.json which enables function to write entities to a table in an Azure Storage All optional fields will be given default value by function host when they are parsed by function host.
Ref: https://aka.ms/tablesbindings
the table or entity in function code. :param connection: The name of an app setting or setting collection that specifies how to connect to the table service. :param table_name: The Name of the table :param row_key: The row key of the table entity to read. :param partition_key: The partition key of the table entity to read. :param data_type: Defines how Functions runtime should treat the
parameter value.
table_output(arg_name: str, connection: str, table_name: str, row_key: str | None = None, partition_key: str | None = None, data_type: DataType | str | None = None) -> Callable[[...], Any]Parameters
| Name | Description |
|---|---|
|
arg_name
Required
|
|
|
connection
Required
|
|
|
table_name
Required
|
|
|
row_key
Required
|
Default value: None
|
|
partition_key
Required
|
Default value: None
|
|
data_type
Required
|
Default value: None
|
Returns
| Type | Description |
|---|---|
|
Decorator function. |
text_completion_input
The textCompletion input binding can be used to invoke the OpenAI Chat Completions API and return the results to the function.
Ref: https://platform.openai.com/docs/guides/text-generation/chat-completions-vs-completions # NoQA
The examples below define "who is" HTTP-triggered functions with a hardcoded "who is {name}?" prompt, where {name} is the substituted with the value in the HTTP request path. The OpenAI input binding invokes the OpenAI GPT endpoint to surface the answer to the prompt to the function, which then returns the result text as the response content.
string. :param model: the ID of the model to use. :param temperature: The 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. :param top_p: An alternative to sampling with temperature, called nucleus sampling, where the model considers the results of the tokens with top_p probability mass. So 0.1 means only the tokens comprising the top 10% probability mass are considered. It's generally recommend to use this or temperature :param max_tokens: The maximum number of tokens to generate in the completion. The token count of your prompt plus max_tokens cannot exceed the model's context length. Most models have a context length of 2048 tokens (except for the newest models, which support 4096). :param data_type: Defines how Functions runtime should treat the parameter value :param kwargs: Keyword arguments for specifying additional binding fields to include in the binding json
text_completion_input(arg_name: str, prompt: str, model: OpenAIModels | None = OpenAIModels.DefaultChatModel, temperature: str | None = '0.5', top_p: str | None = None, max_tokens: str | None = '100', data_type: DataType | str | None = None, **kwargs) -> Callable[[...], Any]Parameters
| Name | Description |
|---|---|
|
arg_name
Required
|
|
|
prompt
Required
|
|
|
model
Required
|
Default value: DefaultChatModel
|
|
temperature
Required
|
Default value: 0.5
|
|
top_p
Required
|
Default value: None
|
|
max_tokens
Required
|
Default value: 100
|
|
data_type
Required
|
Default value: None
|
Returns
| Type | Description |
|---|---|
|
Decorator function. |
Attributes
app_script_file
Name of function app script file in which all the functions are defined.
Script file defined here is for placeholder purpose, please refer to worker defined script file path as the single point of truth.
Returns
| Type | Description |
|---|---|
|
Script file name. |
Azure SDK for Python