97 lines
3.8 KiB
JavaScript
97 lines
3.8 KiB
JavaScript
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"use strict";
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Object.defineProperty(exports, "__esModule", { value: true });
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exports.BufferMemory = void 0;
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const messages_1 = require("@langchain/core/messages");
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const chat_memory_js_1 = require("./chat_memory.cjs");
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/**
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* The `BufferMemory` class is a type of memory component used for storing
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* and managing previous chat messages. It is a wrapper around
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* `ChatMessageHistory` that extracts the messages into an input variable.
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* This class is particularly useful in applications like chatbots where
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* it is essential to remember previous interactions. Note: The memory
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* instance represents the history of a single conversation. Therefore, it
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* is not recommended to share the same history or memory instance between
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* two different chains. If you deploy your LangChain app on a serverless
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* environment, do not store memory instances in a variable, as your
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* hosting provider may reset it by the next time the function is called.
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* @example
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* ```typescript
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* // Initialize the memory to store chat history and set up the language model with a specific temperature.
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* const memory = new BufferMemory({ memoryKey: "chat_history" });
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* const model = new ChatOpenAI({ temperature: 0.9 });
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*
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* // Create a prompt template for a friendly conversation between a human and an AI.
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* const prompt =
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* 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.
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*
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* Current conversation:
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* {chat_history}
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* Human: {input}
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* AI:`);
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*
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* // Set up the chain with the language model, prompt, and memory.
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* const chain = new LLMChain({ llm: model, prompt, memory });
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*
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* // Example usage of the chain to continue the conversation.
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* // The `call` method sends the input to the model and returns the AI's response.
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* const res = await chain.call({ input: "Hi! I'm Jim." });
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* console.log({ res });
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*
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* ```
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*/
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class BufferMemory extends chat_memory_js_1.BaseChatMemory {
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constructor(fields) {
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super({
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chatHistory: fields?.chatHistory,
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returnMessages: fields?.returnMessages ?? false,
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inputKey: fields?.inputKey,
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outputKey: fields?.outputKey,
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});
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Object.defineProperty(this, "humanPrefix", {
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enumerable: true,
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configurable: true,
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writable: true,
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value: "Human"
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});
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Object.defineProperty(this, "aiPrefix", {
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enumerable: true,
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configurable: true,
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writable: true,
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value: "AI"
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});
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Object.defineProperty(this, "memoryKey", {
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enumerable: true,
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configurable: true,
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writable: true,
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value: "history"
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});
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this.humanPrefix = fields?.humanPrefix ?? this.humanPrefix;
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this.aiPrefix = fields?.aiPrefix ?? this.aiPrefix;
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this.memoryKey = fields?.memoryKey ?? this.memoryKey;
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}
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get memoryKeys() {
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return [this.memoryKey];
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}
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/**
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* Loads the memory variables. It takes an `InputValues` object as a
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* parameter and returns a `Promise` that resolves with a
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* `MemoryVariables` object.
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* @param _values `InputValues` object.
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* @returns A `Promise` that resolves with a `MemoryVariables` object.
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*/
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async loadMemoryVariables(_values) {
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const messages = await this.chatHistory.getMessages();
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if (this.returnMessages) {
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const result = {
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[this.memoryKey]: messages,
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};
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return result;
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}
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const result = {
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[this.memoryKey]: (0, messages_1.getBufferString)(messages, this.humanPrefix, this.aiPrefix),
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};
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return result;
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}
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}
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exports.BufferMemory = BufferMemory;
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