refactor: rename models

README.md

@@ -64,10 +64,10 @@ RAGChat supports both Upstash-hosted models and all OpenAI and OpenAI-compatible
 To use an OpenAI model, first initialize RAGChat:
 
 ```typescript
-import { RAGChat, openaiModel } from "@upstash/rag-chat";
+import { RAGChat, openai } from "@upstash/rag-chat";
 
 export const ragChat = new RAGChat({
-  model: openaiModel("gpt-4-turbo"),
+  model: openai("gpt-4-turbo"),
 });
 ```
 
@@ -82,10 +82,10 @@ OPENAI_API_KEY=...
 To use an Upstash model, first initialize RAGChat:
 
 ```typescript
-import { RAGChat, upstashModel } from "@upstash/rag-chat";
+import { RAGChat, upstash } from "@upstash/rag-chat";
 
 export const ragChat = new RAGChat({
-  model: upstashModel("mistralai/Mistral-7B-Instruct-v0.2"),
+  model: upstash("mistralai/Mistral-7B-Instruct-v0.2"),
 });
 ```
 
@@ -94,10 +94,10 @@ export const ragChat = new RAGChat({
 To use an Upstash model, first initialize RAGChat:
 
 ````typescript
-import { RAGChat, upstashModel } from "@upstash/rag-chat";
+import { RAGChat, custom } from "@upstash/rag-chat";
 
 export const ragChat = new RAGChat({
-  model: customModel("codellama/CodeLlama-70b-Instruct-hf", {
+  model: custom("codellama/CodeLlama-70b-Instruct-hf", {
       apiKey: "TOGETHER_AI_TOKEN",
       baseUrl: "https://api.together.xyz/v1",
     }),
@@ -123,14 +123,14 @@ QSTASH_TOKEN=...
 Customize your RAGChat instance with advanced options:
 
 ```typescript
-import { RAGChat, openaiModel } from "@upstash/rag-chat";
+import { RAGChat, openai } from "@upstash/rag-chat";
 
 // 👇 Optional: For built-in rate limiting
 import { Ratelimit } from "@upstash/ratelimit";
 import { Redis } from "@upstash/redis";
 
 export const ragChat = new RAGChat({
-  model: openaiModel("gpt-4-turbo"),
+  model: openai("gpt-4-turbo"),
 
   prompt: ({ context, question, chatHistory }) =>
     `You are an AI assistant with access to an Upstash Vector Store.

examples/nextjs/server-actions/src/app/rag-chat.ts

@@ -1,5 +1,5 @@
-import { RAGChat, upstashModel } from "@upstash/rag-chat";
+import { RAGChat, upstash } from "@upstash/rag-chat";
 
 export const ragChat = new RAGChat({
-  model: upstashModel("meta-llama/Meta-Llama-3-8B-Instruct"),
+  model: upstash("meta-llama/Meta-Llama-3-8B-Instruct"),
 });

examples/nextjs/vercel-ai-sdk/src/app/api/chat/route.ts

@@ -1,4 +1,4 @@
-import { RAGChat, upstashModel } from "@upstash/rag-chat";
+import { RAGChat, upstash } from "@upstash/rag-chat";
 import { aiUseChatAdapter } from "@upstash/rag-chat/nextjs";
 import type { Message } from "ai";
 
@@ -12,10 +12,10 @@ export async function POST(request: Request) {
   if (!question) throw new Error("No question in the request");
 
   const ragChat = new RAGChat({
-    model: upstashModel("meta-llama/Meta-Llama-3-8B-Instruct"),
+    model: upstash("meta-llama/Meta-Llama-3-8B-Instruct"),
 
     // 👇 ALTERNATIVE
-    // model: openaiModel("gpt-4-turbo")
+    // model: openai("gpt-4-turbo")
   });
 
   const response = await ragChat.chat(question, { streaming: true });

examples/nodejs/src/server.ts

@@ -1,4 +1,4 @@
-import { RAGChat, upstashModel } from "@upstash/rag-chat";
+import { RAGChat, upstash } from "@upstash/rag-chat";
 import { streamToResponse } from "ai";
 import dotenv from "dotenv";
 import { createServer } from "http";
@@ -8,10 +8,10 @@ dotenv.config();
 
 const server = createServer(async (req, res) => {
   const ragChat = new RAGChat({
-    model: upstashModel("meta-llama/Meta-Llama-3-8B-Instruct"),
+    model: upstash("meta-llama/Meta-Llama-3-8B-Instruct"),
 
     // 👇 ALTERNATIVE
-    // model: openaiModel("gpt-4-turbo")
+    // model: openai("gpt-4-turbo")
   });
 
   await ragChat.context.add({

examples/nuxt/server/api/add-data.ts

@@ -1,4 +1,4 @@
-import { RAGChat, upstashModel } from "@upstash/rag-chat";
+import { RAGChat, upstash } from "@upstash/rag-chat";
 import { Index } from "@upstash/vector";
 
 export default defineLazyEventHandler(async () => {
@@ -9,7 +9,7 @@ export default defineLazyEventHandler(async () => {
       token: apiKey.UPSTASH_VECTOR_REST_TOKEN,
       url: apiKey.UPSTASH_VECTOR_REST_URL,
     }),
-    model: upstashModel("meta-llama/Meta-Llama-3-8B-Instruct", { apiKey: apiKey.QSTASH_TOKEN }),
+    model: upstash("meta-llama/Meta-Llama-3-8B-Instruct", { apiKey: apiKey.QSTASH_TOKEN }),
   });
 
   return defineEventHandler(async (event: any) => {

examples/nuxt/server/api/chat.ts

@@ -1,4 +1,4 @@
-import { RAGChat, upstashModel } from "@upstash/rag-chat";
+import { RAGChat, upstash } from "@upstash/rag-chat";
 import { aiUseChatAdapter } from "@upstash/rag-chat/nextjs";
 import { Index } from "@upstash/vector";
 import { Message } from "ai";
@@ -19,10 +19,10 @@ export default defineLazyEventHandler(async () => {
         token: apiKey.UPSTASH_VECTOR_REST_TOKEN,
         url: apiKey.UPSTASH_VECTOR_REST_URL,
       }),
-      model: upstashModel("meta-llama/Meta-Llama-3-8B-Instruct", { apiKey: apiKey.QSTASH_TOKEN }),
+      model: upstash("meta-llama/Meta-Llama-3-8B-Instruct", { apiKey: apiKey.QSTASH_TOKEN }),
 
       // 👇 ALTERNATIVE
-      // model: openaiModel("gpt-4"),
+      // model: openai("gpt-4"),
     });
 
     const response = await ragChat.chat(question, { streaming: true });

examples/solidjs/src/routes/api/chat/index.ts

@@ -1,5 +1,5 @@
 import { APIEvent } from "@solidjs/start/server";
-import { RAGChat, upstashModel } from "@upstash/rag-chat";
+import { RAGChat, upstash } from "@upstash/rag-chat";
 import { aiUseChatAdapter } from "@upstash/rag-chat/nextjs";
 import { Index } from "@upstash/vector";
 import { Message } from "ai";
@@ -15,12 +15,12 @@ export const POST = async (event: APIEvent) => {
       token: process.env.UPSTASH_VECTOR_REST_TOKEN,
       url: process.env.UPSTASH_VECTOR_REST_URL,
     }),
-    model: upstashModel("meta-llama/Meta-Llama-3-8B-Instruct", {
+    model: upstash("meta-llama/Meta-Llama-3-8B-Instruct", {
       apiKey: process.env.QSTASH_TOKEN!,
     }),
 
     // 👇 ALTERNATIVE
-    // model: openaiModel("gpt-4-turbo")
+    // model: openai("gpt-4-turbo")
   });
 
   const response = await ragChat.chat(question, { streaming: true });

examples/sveltekit/src/routes/api/add-data/+server.ts

@@ -1,6 +1,6 @@
 import { env } from "$env/dynamic/private";
 import type { RequestHandler } from "@sveltejs/kit";
-import { RAGChat, upstashModel } from "@upstash/rag-chat";
+import { RAGChat, upstash } from "@upstash/rag-chat";
 import { Index } from "@upstash/vector";
 
 function sleep(ms: number) {
@@ -10,7 +10,7 @@ function sleep(ms: number) {
 export const POST = (async () => {
   const ragChat = new RAGChat({
     vector: new Index({ token: env.UPSTASH_VECTOR_REST_TOKEN, url: env.UPSTASH_VECTOR_REST_URL }),
-    model: upstashModel("meta-llama/Meta-Llama-3-8B-Instruct", { apiKey: env.QSTASH_TOKEN }),
+    model: upstash("meta-llama/Meta-Llama-3-8B-Instruct", { apiKey: env.QSTASH_TOKEN }),
   });
   await Promise.all([
     ragChat.context.add({

examples/sveltekit/src/routes/api/chat/+server.ts

@@ -1,6 +1,6 @@
 import { env } from "$env/dynamic/private";
 import type { Message } from "@ai-sdk/svelte";
-import { RAGChat, upstashModel } from "@upstash/rag-chat";
+import { RAGChat, upstash } from "@upstash/rag-chat";
 import { aiUseChatAdapter } from "@upstash/rag-chat/nextjs";
 import { Index } from "@upstash/vector";
 import type { RequestHandler } from "./$types";
@@ -13,11 +13,11 @@ export const POST = (async ({ request }) => {
 
   const ragChat = new RAGChat({
     vector: new Index({ token: env.UPSTASH_VECTOR_REST_TOKEN, url: env.UPSTASH_VECTOR_REST_URL }),
-    model: upstashModel("meta-llama/Meta-Llama-3-8B-Instruct", { apiKey: env.QSTASH_TOKEN }),
+    model: upstash("meta-llama/Meta-Llama-3-8B-Instruct", { apiKey: env.QSTASH_TOKEN }),
   });
   //OR
   //   const ragChat = new RAGChat({
-  //     model: openaiModel("gpt-4"),
+  //     model: openai("gpt-4"),
   //   });
 
   const response = await ragChat.chat(question, { streaming: true });

src/config.ts

@@ -3,7 +3,7 @@ import type { Ratelimit } from "@upstash/ratelimit";
 import { Redis } from "@upstash/redis";
 import { Index } from "@upstash/vector";
 import { DEFAULT_PROMPT } from "./constants";
-import { openaiModel, upstashModel } from "./models";
+import { upstash, openai } from "./models";
 import type { CustomPrompt } from "./rag-chat-base";
 import type { RAGChatConfig } from "./types";
 
@@ -47,11 +47,10 @@ const initializeModel = () => {
   const qstashToken = process.env.QSTASH_TOKEN;
   const openAIToken = process.env.OPENAI_API_KEY;
 
-  if (qstashToken)
-    return upstashModel("meta-llama/Meta-Llama-3-8B-Instruct", { apiKey: qstashToken });
+  if (qstashToken) return upstash("meta-llama/Meta-Llama-3-8B-Instruct", { apiKey: qstashToken });
 
   if (openAIToken) {
-    return openaiModel("gpt-4o", { apiKey: openAIToken });
+    return openai("gpt-4o", { apiKey: openAIToken });
   }
 
   throw new Error(

src/error/model.ts

@@ -1,4 +1,4 @@
-export class UpstashModelError extends Error {
+export class upstashError extends Error {
   constructor(message: string) {
     super(message);
     this.name = "ModelError";

src/models.ts

@@ -30,7 +30,7 @@ export type UpstashChatModel =
 
 type ModelOptions = Omit<LLMClientConfig, "model">;
 
-export const upstashModel = (model: UpstashChatModel, options?: Omit<ModelOptions, "baseUrl">) => {
+export const upstash = (model: UpstashChatModel, options?: Omit<ModelOptions, "baseUrl">) => {
   return new LLMClient({
     model,
     baseUrl: "https://qstash.upstash.io/llm/v1",
@@ -39,7 +39,7 @@ export const upstashModel = (model: UpstashChatModel, options?: Omit<ModelOption
   });
 };
 
-export const customModel = (model: string, options?: ModelOptions) => {
+export const custom = (model: string, options?: ModelOptions) => {
   if (!options?.baseUrl) throw new Error("baseUrl cannot be empty or undefined.");
 
   return new LLMClient({
@@ -48,7 +48,7 @@ export const customModel = (model: string, options?: ModelOptions) => {
   });
 };
 
-export const openaiModel = (model: OpenAIChatModel, options?: Omit<ModelOptions, "baseUrl">) => {
+export const openai = (model: OpenAIChatModel, options?: Omit<ModelOptions, "baseUrl">) => {
   return new ChatOpenAI({
     modelName: model,
     temperature: 0,

src/rag-chat.test.ts

@@ -5,7 +5,7 @@ import { Redis } from "@upstash/redis";
 import { Index } from "@upstash/vector";
 import { LangChainAdapter, StreamingTextResponse } from "ai";
 import { afterAll, beforeAll, describe, expect, test } from "bun:test";
-import { customModel } from "./models";
+import { custom } from "./models";
 import { RAGChat } from "./rag-chat";
 import { awaitUntilIndexed } from "./test-utils";
 import { RatelimitUpstashError } from "./error";
@@ -480,7 +480,7 @@ describe("RAGChat init with custom model", () => {
 
   const ragChat = new RAGChat({
     vector,
-    model: customModel("meta-llama/Meta-Llama-3-8B-Instruct", {
+    model: custom("meta-llama/Meta-Llama-3-8B-Instruct", {
       apiKey: process.env.QSTASH_TOKEN!,
       baseUrl: "https://qstash.upstash.io/llm/v1",
     }),

src/rag-chat.ts

@@ -1,4 +1,4 @@
-import { UpstashModelError } from "./error/model";
+import { upstashError } from "./error/model";
 
 import { Config } from "./config";
 import { Database } from "./database";
@@ -37,7 +37,7 @@ export class RAGChat extends RAGChatBase {
     });
 
     if (!model) {
-      throw new UpstashModelError("Model can not be undefined!");
+      throw new upstashError("Model can not be undefined!");
     }
 
     super(vectorService, historyService, {