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Slots are defined in the slots section of your domain with their name,type and if and how they should influence the assistant'sbehavior.The following example defines a slot with name "slot_name", type text andpredefined slot mapping from_entity.

As of 3.0, slot mappings are defined in the slots section of the domain.This change removes the implicit mechanism of setting slots via auto-fill and replaces it with a new explicitmechanism of setting slots after every user message.You will need to explicitly define slot mappings for each slot in the slots section of domain.yml.If you are migrating from an earlier version, please read through the migration guideto update your assistant.

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For example, in the example below, an entity date uniquely sets the slot arrival_date,an entity city with a role from uniquely sets the slot departure_city andan entity city with a role to uniquely sets the slot arrival_city,therefore they can be used to fit corresponding slotseven if these slots were not requested.However, entity city without a role can fill both departure_city and arrival_cityslots, depending which one is requested, so if an entity city is extracted whenslot arrival_date is requested, it'll be ignored by the form.

Note that the unique from_entity mapping constraint will not prevent filling slots which are not in the active form's required_slots;those mappings will apply as usual, regardless of the uniqueness of the mapping. To limit applicability of a slot mapping toa specific form, see Mapping Conditions.

The from_text mapping will use the text of the last user utterance to fill the slotslot_name. If intent_name is None, the slot will be filled regardless of intent name.Otherwise, the slot will only be filled if the user's intent is intent_name.

If conditions are not included in a slot mapping, the slot mapping will be applicable regardless of whetherany form is active. As long as a slot is listed in a form's required_slots, the form will prompt for the slotif it is empty when the form is activated.

This means that if a user sends their first message after 60 minutes of inactivity, anew conversation session is triggered, and that any existing slots are carried overinto the new session. Setting the value of session_expiration_time to 0 meansthat sessions will not end (note that the action_session_start action will stillbe triggered at the very beginning of conversations).

A session start triggers the default action action_session_start. Its defaultimplementation moves all existing slots into the new session. Note that allconversations begin with an action_session_start. Overriding this action couldfor instance be used to initialize the tracker with slots from an external APIcall, or to start the conversation with a bot message. The docs onCustomizing the session start action shows you how to do that.

The config key in the domain file maintains the store_entities_as_slots parameter.This parameter is used only in the context of reading stories and turning them into trackers. If the parameter is setto True, this will result in slots being implicitly set from entities if applicable entities are present in the story.When an entity matches the from_entity slot mapping, store_entities_as_slots defines whether the entity value shouldbe placed in that slot. Therefore, this parameter skips adding an explicit slot_was_set step manually in the story.By default, this behaviour is switched on.

If your account has extra member slots and you want to change your payment method to a partner package, you can link your account as instructed by Netflix and your provider. Since extra members cannot be added to partner packages or third-party billed accounts, we will cancel your extra member(s) immediately once activation is complete. The extra member(s) will receive an email confirmation.

A BigQuery slot is a virtual CPU used by BigQueryto execute SQL queries. During the query execution, BigQueryautomatically calculates how many slots a query requires, depending on the querysize and complexity.

You have a choice of using an on-demand pricing modelor a capacity-based pricing model. Bothmodels useslots for data processing. With a capacity-based model, you can pay for dedicatedor autoscaled query processing capacity. The capacity-based model gives youexplicit control over slots and analytics capacity, whereas the on-demand modeldoes not.

Customers on the capacity-based pricing model explicitly choose how many slots toreserve. Your queries run within that capacity, and you pay for that capacitycontinuously every second it's deployed. For example, if you purchase 2,000BigQuery slots, your queries in aggregate are limited to using2,000 virtual CPUs at any given time. You have this capacity until you deleteit, and you pay for 2,000 slots until you delete them.

Projects on the BigQuery on-demand pricing model are subject toper-project slot quota with transient burstcapability. Most users on the on-demand model find the default slot capacitymore than sufficient. Depending on the workload, access to more slots improvesquery performance. To check how many slots your account uses, seeBigQuery monitoring.

BigQuery slots execute individual units of work at each stage ofthe query. For example, if BigQuery determines that a stage'soptimal parallelization factor is 10, it requests 10 slots to process thatstage.

If a query requests more slots than currently available, BigQueryqueues up individual units of work and waits for slots to become available.As progress on query execution is made, and as slots free up, thesequeued up units of work get dynamically picked up for execution.

BigQuery can request any number of slots for a particular stageof a query. The number of slots requested is not related to the amount ofcapacity you purchase, but rather an indication of the most optimalparallelization factor chosen by BigQuery for that stage. Unitsof work queue up and get executed as slots become available.

Slots are distributed fairly among projects and then within the jobs in theproject. This means that every query has access to all available slots at anytime, and capacity is dynamically and automatically re-allocated among activequeries as each query's capacity demands change. Queries complete and newqueries get submitted for execution under the following conditions:

Depending on complexity and size, a query might not require all the slots it hasthe right to, or it may require more. BigQuery dynamicallyensures that, given fair scheduling, all slots can be fully used at anypoint in time.

To change a slot type name or update its values, select the slot type in the left-hand navigation to open the slot detail page. The Slots using section shows all of the slots and intents currently using that type.

You can offer people a block of time on your calendar that they can book time slots within. For example, you can set aside 2 hours that you're available to meet with people in 30-minute slots. People can then book one of the 30-minute slots within that time.

When you create a block of appointment slots, the block shows up as a single event on your calendar. To confirm that an event is an appointment block, at the upper left corner of the event, find the Appointment block .

Tip: If you want to make the appointment block repeat, do so before you invite others to reserve a slot. When you make an existing appointment block with reserved slots repeat, the reserved slots get duplicated as new slots and double booking can occur. Learn how to make events repeat.

On work and school accounts, you can switch between appointment slots and appointment schedules any time. Any current slots or schedules remain active and available whether appointment schedules are on or off.

The Office of Head Start (OHS) recognizes that community needs shift over time for various reasons. These reasons may include changes during and after disasters and public health crises, changes in the availability of community resources relied upon to provide program services, and shifts in geographical location of eligible children and families. Section 640(g)(3) of the Head Start Act (the Act) allows programs to propose a reduction to their funded enrollment to maintain quality of program services. Additionally, Section 645(a)(5) permits a program to convert Head Start slots to Early Head Start slots to better meet community needs. Similarly, Section 640(f)(2) of the Act allows programs to convert part-day slots to full-working day slots to meet community needs.

A request to reduce funded enrollment or convert Head Start slots to Early Head Start slots is considered a change in scope request and requires OHS prior approval. Recipients may submit a change in scope request through a continuation application or as a separate application amendment in the Head Start Enterprise System (HSES). Change in scope requests must be submitted a minimum of 90 days prior to the planned implementation date. This Information Memorandum (IM) provides additional guidance for the development and submission of these requests.

Service duration should also be considered, as research supports the importance of longer hours of high-quality education and development services in achieving meaningful child outcomes and preparing children for success in school. Programs operating for longer hours may also better support parents' education, job training, and employment opportunities. Programs that received funding to increase service duration in fiscal years 2016 or 2018 must demonstrate they are not eliminating, converting, or reducing the duration of services to enrollment slots supported by duration funding. As a reminder, Head Start center-based programs are required to provide at least 1,020 annual hours of service over a period of at least eight months per year for at least 45% of their center-based enrollment. Family child care and Early Head Start center-based programs are required to provide at least 1,380 annual hours of service for 100% of their enrollment slots. These requirements are found in the HSPPS at Program Structure, 45 CFR 1302 Subpart B. 17dc91bb1f