41 lines
1.5 KiB
TypeScript
41 lines
1.5 KiB
TypeScript
import { Redis } from "ioredis";
|
|
import { BaseCache } from "@langchain/core/caches";
|
|
import { Generation } from "@langchain/core/outputs";
|
|
/**
|
|
* Cache LLM results using Redis.
|
|
* @example
|
|
* ```typescript
|
|
* const model = new ChatOpenAI({
|
|
* cache: new RedisCache(new Redis(), { ttl: 60 }),
|
|
* });
|
|
*
|
|
* // Invoke the model with a prompt
|
|
* const response = await model.invoke("Do something random!");
|
|
* console.log(response);
|
|
*
|
|
* // Remember to disconnect the Redis client when done
|
|
* await redisClient.disconnect();
|
|
* ```
|
|
*/
|
|
export declare class RedisCache extends BaseCache {
|
|
protected redisClient: Redis;
|
|
protected ttl?: number;
|
|
constructor(redisClient: Redis, config?: {
|
|
ttl?: number;
|
|
});
|
|
/**
|
|
* Retrieves data from the Redis server using a prompt and an LLM key. If
|
|
* the data is not found, it returns null.
|
|
* @param prompt The prompt used to find the data.
|
|
* @param llmKey The LLM key used to find the data.
|
|
* @returns The corresponding data as an array of Generation objects, or null if not found.
|
|
*/
|
|
lookup(prompt: string, llmKey: string): Promise<Generation[] | null>;
|
|
/**
|
|
* Updates the data in the Redis server using a prompt and an LLM key.
|
|
* @param prompt The prompt used to store the data.
|
|
* @param llmKey The LLM key used to store the data.
|
|
* @param value The data to be stored, represented as an array of Generation objects.
|
|
*/
|
|
update(prompt: string, llmKey: string, value: Generation[]): Promise<void>;
|
|
}
|