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With planners, however, you can use alternative strategies to optimize the number of functions you can call per LLM request. For example, with the Handlebars planner, you can generate an entire plan with loops and if statements all with a single LLM call. For complex request, this means you can save both time and money.

If you previously used the Action, Sequential, or Stepwise planners, please upgrade to the latest planners: Handlebars and Function calling stepwise planner. You can follow the migration guide on our blog to learn how to make the move.

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All planners are currently marked experimental in the C# SDK until we finalize the API surface. If you would like to use them, add SKEXP0060 in your .csproj file for the Handlebars planner or SKEXP0061 in your .csproj file for the stepwise planner. Alternatively, you can add #pragma warning disable SKEXP0060 or #pragma warning disable SKEXP0061 in the file that uses the planners.

For example, if you had task and calendar event plugins, planner could combine them to create workflows like "remind me to buy milk when I go to the store" or "remind me to call my mom tomorrow" without you explicitly having to write code for those scenarios.

Now that we have planner, we can use it to create a plan for a user's ask and then invoke the plan to get a result. The following code asks our planner to solve a math problem that is difficult for an LLM to solve on its own because it requires multiple steps and it has numbers with decimal points.

As demonstrated by this example, planners are extremely powerful because they can automatically recombine functions you have already defined, and as AI models improve and as the community develops better planners, you will be able to rely on them to achieve increasingly more sophisticated user scenarios.

There are, however, considerations you should make before using a planner. The following table describes the top considerations you should make along with mitigations you can take to reduce their impact.

You now have the skills necessary to automatically generate plans for your users. You can use these skills to create more advanced AI apps that can handle increasingly complex scenarios. In the next section, you'll learn how to evaluate your planners with Prompt flow.

A: Choosing the right planner depends on your needs and preferences. Consider factors such as layout (daily, weekly, monthly), size, design, and additional features like goal-setting pages or habit trackers. Assess your organizational style and find a planner that aligns with it.

The new Microsoft Planner is bringing together the simplicity of Microsoft To Do, the collaboration of Microsoft Planner, the power of Microsoft Project for the web, and the intelligence of Microsoft Copilot into a simple, familiar experience. Sign up to be the first to know when it will be available as preview and generally available on Microsoft Teams in Spring 2024. Learn more about the announcement at aka.ms/thenewplanner.

I have used this planner for several years and, mostly, love it. Great quality paper, love space for notes on each week and an area to list Things To Do. My only issue is I take it back and forth to work every day and the corners end up getting bent/frayed. I realize this is pretty OCD of me but it makes me crazy! I even bought a tote that has a special spot where I put it (where normal people would put their laptop but I leave mine at work) and am very careful. Currently researching ways to protect the corners. Otherwise...it's The Bomb!

Hi Christine,

Thanks so much for your review, we appreciate the feedback! We are passing on your color preference to our product development team. We are always looking at customer feedback to set the colors for each iteration of our planners.

Thanks again!

Kindly,

The Appointed Team

I have been buying my yearly task planner from Appointed for the last 3 years and I love it. I love how there is a place for everything, the size and color options, but i especially love how simple it is. Planners these days have way too much going on and I like to be able to decide what i'm putting where in mine. Customer for life!

Add a splash of inspiration to your goal-achievement journey with theYour Best Year Ever Sticker Pack. This lively collection of high-quality vinyl stickers is perfect for turning your planner, laptop, or workspace into a canvas of motivation and fun.

More flexible than ever. Experience the ultimate customization with Loose Leaf 2.0. Rearrange your Rituals, Ideal Week, and more, exactly how you want them. With Loose Leaf 2.0, you can set up a planner that's as unique as your goals.

Top-quality Day-Timer planner covers are designed to give you flexibility in how you plan your successes and record your achievements. Available for loose-leaf or wirebound pages, planner covers come in a variety of sizes and styles that allow you to create the planner that best accommodates your planning routine.

The task of the planner/optimizer is to create an optimal execution plan. A given SQL query (and hence, a query tree) can be actually executed in a wide variety of different ways, each of which will produce the same set of results. If it is computationally feasible, the query optimizer will examine each of these possible execution plans, ultimately selecting the execution plan that is expected to run the fastest.

The planner's search procedure actually works with data structures called paths, which are simply cut-down representations of plans containing only as much information as the planner needs to make its decisions. After the cheapest path is determined, a full-fledged plan tree is built to pass to the executor. This represents the desired execution plan in sufficient detail for the executor to run it. In the rest of this section we'll ignore the distinction between paths and plans.

The planner/optimizer starts by generating plans for scanning each individual relation (table) used in the query. The possible plans are determined by the available indexes on each relation. There is always the possibility of performing a sequential scan on a relation, so a sequential scan plan is always created. Assume an index is defined on a relation (for example a B-tree index) and a query contains the restriction relation.attribute OPR constant. If relation.attribute happens to match the key of the B-tree index and OPR is one of the operators listed in the index's operator class, another plan is created using the B-tree index to scan the relation. If there are further indexes present and the restrictions in the query happen to match a key of an index, further plans will be considered. Index scan plans are also generated for indexes that have a sort ordering that can match the query's ORDER BY clause (if any), or a sort ordering that might be useful for merge joining (see below).

When the query involves more than two relations, the final result must be built up by a tree of join steps, each with two inputs. The planner examines different possible join sequences to find the cheapest one.

If the query uses fewer than geqo_threshold relations, a near-exhaustive search is conducted to find the best join sequence. The planner preferentially considers joins between any two relations for which there exists a corresponding join clause in the WHERE qualification (i.e., for which a restriction like where rel1.attr1=rel2.attr2 exists). Join pairs with no join clause are considered only when there is no other choice, that is, a particular relation has no available join clauses to any other relation. All possible plans are generated for every join pair considered by the planner, and the one that is (estimated to be) the cheapest is chosen.

The finished plan tree consists of sequential or index scans of the base relations, plus nested-loop, merge, or hash join nodes as needed, plus any auxiliary steps needed, such as sort nodes or aggregate-function calculation nodes. Most of these plan node types have the additional ability to do selection (discarding rows that do not meet a specified Boolean condition) and projection (computation of a derived column set based on given column values, that is, evaluation of scalar expressions where needed). One of the responsibilities of the planner is to attach selection conditions from the WHERE clause and computation of required output expressions to the most appropriate nodes of the plan tree. 17dc91bb1f