Documentation

Build LLM-powered agents
with production-ready TypeScript

DSPy for TypeScript. Working with LLMs is complex—they don't always do what you want. DSPy makes it easier to build amazing things with LLMs. Just define your inputs and outputs (signature) and an efficient prompt is auto-generated and used. Connect together various signatures to build complex systems and workflows using LLMs.

15+ LLM Providers
End-to-end Streaming
Auto Prompt Tuning

AxPreparedChatRequest

type AxPreparedChatRequest<TChatRequest> = object;

Defined in: https://github.com/ax-llm/ax/blob/a8847bd2906efff202fde10d776fddd20fd2ff57/src/ax/ai/types.ts#L646

Result of preparing a chat request with context cache support.

Type Parameters

Type Parameter
TChatRequest

Properties

apiConfig

apiConfig: AxAPI;

Defined in: https://github.com/ax-llm/ax/blob/a8847bd2906efff202fde10d776fddd20fd2ff57/src/ax/ai/types.ts#L648

API endpoint configuration


cachedContentName?

optional cachedContentName: string;

Defined in: https://github.com/ax-llm/ax/blob/a8847bd2906efff202fde10d776fddd20fd2ff57/src/ax/ai/types.ts#L654

Cache name to use in the request (if using existing cache)


cacheOperations?

optional cacheOperations: AxContextCacheOperation[];

Defined in: https://github.com/ax-llm/ax/blob/a8847bd2906efff202fde10d776fddd20fd2ff57/src/ax/ai/types.ts#L652

Optional cache operations to execute before the main request


request

request: TChatRequest;

Defined in: https://github.com/ax-llm/ax/blob/a8847bd2906efff202fde10d776fddd20fd2ff57/src/ax/ai/types.ts#L650

The prepared chat request