feat: rename template to prompt and allow getting history from ragcha…

src/config.ts

@@ -11,7 +11,7 @@ export class Config {
   public readonly ratelimit?: Ratelimit;
 
   public readonly model?: BaseLanguageModelInterface;
-  public readonly template?: PromptTemplate;
+  public readonly prompt?: PromptTemplate;
 
   constructor(config: RAGChatConfig) {
     this.vector = config.vector;
@@ -20,6 +20,6 @@ export class Config {
     this.ratelimit = config.ratelimit;
 
     this.model = config.model;
-    this.template = config.template;
+    this.prompt = config.prompt;
   }
 }

src/prompts.ts

@@ -1,6 +1,6 @@
 import { PromptTemplate } from "@langchain/core/prompts";
 
-export const QA_TEMPLATE =
+export const QA_PROMPT_TEMPLATE =
   PromptTemplate.fromTemplate(`You are a friendly AI assistant augmented with an Upstash Vector Store.
 To help you answer the questions, a context will be provided. This context is generated by querying the vector store with the user question.
 Answer the question at the end using only the information available in the context and chat history.

src/rag-chat-base.ts

@@ -17,18 +17,18 @@ export class RAGChatBase {
   protected historyService: HistoryService;
 
   #model: BaseLanguageModelInterface;
-  #template: PromptTemplate;
+  #prompt: PromptTemplate;
 
   constructor(
     retrievalService: RetrievalService,
     historyService: HistoryService,
-    config: { model: BaseLanguageModelInterface; template: PromptTemplate }
+    config: { model: BaseLanguageModelInterface; prompt: PromptTemplate }
   ) {
     this.retrievalService = retrievalService;
     this.historyService = historyService;
 
     this.#model = config.model;
-    this.#template = config.template;
+    this.#prompt = config.prompt;
   }
 
   protected async prepareChat({
@@ -69,7 +69,7 @@ export class RAGChatBase {
         question: (input) => input.question,
         context: (input) => input.context,
       },
-      this.#template,
+      this.#prompt,
       this.#model,
     ]);
 

src/rag-chat.test.ts

@@ -129,7 +129,7 @@ describe("RAG Chat with custom template", () => {
       token: process.env.UPSTASH_REDIS_REST_TOKEN!,
       url: process.env.UPSTASH_REDIS_REST_URL!,
     }),
-    template: PromptTemplate.fromTemplate("Just say `I'm a cookie monster`. Nothing else."),
+    prompt: PromptTemplate.fromTemplate("Just say `I'm a cookie monster`. Nothing else."),
     model: new ChatOpenAI({
       modelName: "gpt-3.5-turbo",
       streaming: false,

src/rag-chat.ts

@@ -1,7 +1,7 @@
 import type { AIMessage } from "@langchain/core/messages";
 import type { StreamingTextResponse } from "ai";
 
-import { QA_TEMPLATE } from "./prompts";
+import { QA_PROMPT_TEMPLATE } from "./prompts";
 
 import { UpstashModelError } from "./error/model";
 import { RatelimitUpstashError } from "./error/ratelimit";
@@ -29,7 +29,7 @@ export class RAGChat extends RAGChatBase {
     }
     super(retrievalService, historyService, {
       model: config.model,
-      template: config.template ?? QA_TEMPLATE,
+      prompt: config.prompt ?? QA_PROMPT_TEMPLATE,
     });
     this.#ratelimitService = ratelimitService;
   }
@@ -38,7 +38,7 @@ export class RAGChat extends RAGChatBase {
     // Adds chat session id and ratelimit session id if not provided.
     const options_ = appendDefaultsIfNeeded(options);
 
-    //Checks ratelimit of the user. If not enabled `success` will be always true.
+    // Checks ratelimit of the user. If not enabled `success` will be always true.
     const { success, resetTime } = await this.#ratelimitService.checkLimit(
       options_.ratelimitSessionId
     );
@@ -50,14 +50,16 @@ export class RAGChat extends RAGChatBase {
       });
     }
 
-    //Sanitizes the given input by stripping all the newline chars then queries vector db with sanitized question.
+    // Sanitizes the given input by stripping all the newline chars. Then, queries vector db with sanitized question.
     const { question, facts } = await this.prepareChat({
       question: input,
       similarityThreshold: options_.similarityThreshold,
       metadataKey: options_.metadataKey,
       topK: options_.topK,
     });
 
+    // Calls LLM service with organized prompt. Prompt holds chat_history, facts gathered from vector db and sanitized question.
+    // Allows either streaming call via Vercel AI SDK or non-streaming call
     return options.stream
       ? this.streamingChainCall(options_, question, facts)
       : this.chainCall(options_, question, facts);
@@ -71,4 +73,9 @@ export class RAGChat extends RAGChatBase {
     );
     return retrievalServiceStatus === "Success" ? "OK" : "NOT-OK";
   }
+
+  /** Method to get history of messages used in the RAG Chat*/
+  getHistory() {
+    return this.historyService;
+  }
 }

src/types.ts

@@ -84,7 +84,7 @@ type RAGChatConfigCommon = {
         Question: {question}
         Helpful answer:`)
    */
-  template?: PromptTemplate;
+  prompt?: PromptTemplate;
   /**
    * Ratelimit instance
    * @example new Ratelimit({