Teams AI library(JS/C#) - General Availability! #1060
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Great job team!!!! |
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Will there be a Python library in the future, in addition to the existing JavaScript and C# libraries? |
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Hi and thank you for a great release! I'm struggling to find how are the chained prompts supposed to work? The /**
* Chains into another prompt and executes the plan that is returned.
* @summary
* This method is used to chain into another prompt. It will call the prompt manager to
* get the plan for the prompt and then execute the plan. The return value indicates whether
* that plan was completely executed or not, and can be used to make decisions about whether the
* outer plan should continue executing.
* @param {TurnContext} context Current turn context.
* @param {TState} state Current turn state.
* @param {string | PromptTemplate} prompt Optional. Prompt name or prompt template to use. If omitted, the AI systems default prompt will be used.
* @param {Partial<AIOptions<TState>>} options Optional. Override options for the prompt. If omitted, the AI systems configured options will be used.
* @returns {boolean} True if the plan was completely executed, otherwise false.
*/
public async chain(
context: TurnContext,
state: TState,
prompt?: string | PromptTemplate,
options?: Partial<AIOptions<TState>>
): Promise<boolean> {} |
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Versions 1.0.0 released
We are thrilled to announce that the Teams AI Library (JS/C#), which was initially introduced in public preview on May 5th, has now reached General Availability! This marks a significant milestone in our journey to empower developers with a powerful platform for building intuitive, AI-driven applications within the Teams ecosystem. The updated SDK brings a host of enhancements designed to simplify the process of developing conversational apps, making it more developer-friendly and feature-rich than ever before.
In response to valuable user feedback and continuous improvements, we have streamlined several aspects of the SDK.
TurnState
object, eliminating the need for aTurnStateManager
class.Planner
, offering better token management and reducing the likelihood of overflowing the model's context window.ActionPlanner
unifies all these features into a single planner that developers can pass to the Application object, streamlining the development process.Resources:
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