agsamantha/node_modules/langchain/dist/memory/buffer_memory.js
2024-10-02 15:15:21 -05:00

92 lines
3.7 KiB
JavaScript

import { getBufferString } from "@langchain/core/messages";
import { BaseChatMemory } from "./chat_memory.js";
/**
* The `BufferMemory` class is a type of memory component used for storing
* and managing previous chat messages. It is a wrapper around
* `ChatMessageHistory` that extracts the messages into an input variable.
* This class is particularly useful in applications like chatbots where
* it is essential to remember previous interactions. Note: The memory
* instance represents the history of a single conversation. Therefore, it
* is not recommended to share the same history or memory instance between
* two different chains. If you deploy your LangChain app on a serverless
* environment, do not store memory instances in a variable, as your
* hosting provider may reset it by the next time the function is called.
* @example
* ```typescript
* // Initialize the memory to store chat history and set up the language model with a specific temperature.
* const memory = new BufferMemory({ memoryKey: "chat_history" });
* const model = new ChatOpenAI({ temperature: 0.9 });
*
* // Create a prompt template for a friendly conversation between a human and an AI.
* const prompt =
* PromptTemplate.fromTemplate(`The following is a friendly conversation between a human and an AI. The AI is talkative and provides lots of specific details from its context. If the AI does not know the answer to a question, it truthfully says it does not know.
*
* Current conversation:
* {chat_history}
* Human: {input}
* AI:`);
*
* // Set up the chain with the language model, prompt, and memory.
* const chain = new LLMChain({ llm: model, prompt, memory });
*
* // Example usage of the chain to continue the conversation.
* // The `call` method sends the input to the model and returns the AI's response.
* const res = await chain.call({ input: "Hi! I'm Jim." });
* console.log({ res });
*
* ```
*/
export class BufferMemory extends BaseChatMemory {
constructor(fields) {
super({
chatHistory: fields?.chatHistory,
returnMessages: fields?.returnMessages ?? false,
inputKey: fields?.inputKey,
outputKey: fields?.outputKey,
});
Object.defineProperty(this, "humanPrefix", {
enumerable: true,
configurable: true,
writable: true,
value: "Human"
});
Object.defineProperty(this, "aiPrefix", {
enumerable: true,
configurable: true,
writable: true,
value: "AI"
});
Object.defineProperty(this, "memoryKey", {
enumerable: true,
configurable: true,
writable: true,
value: "history"
});
this.humanPrefix = fields?.humanPrefix ?? this.humanPrefix;
this.aiPrefix = fields?.aiPrefix ?? this.aiPrefix;
this.memoryKey = fields?.memoryKey ?? this.memoryKey;
}
get memoryKeys() {
return [this.memoryKey];
}
/**
* Loads the memory variables. It takes an `InputValues` object as a
* parameter and returns a `Promise` that resolves with a
* `MemoryVariables` object.
* @param _values `InputValues` object.
* @returns A `Promise` that resolves with a `MemoryVariables` object.
*/
async loadMemoryVariables(_values) {
const messages = await this.chatHistory.getMessages();
if (this.returnMessages) {
const result = {
[this.memoryKey]: messages,
};
return result;
}
const result = {
[this.memoryKey]: getBufferString(messages, this.humanPrefix, this.aiPrefix),
};
return result;
}
}