Rename GelAI to RAGClient (#1198)

Related geldata/gel-python#578

edgedb/ai/index.ts

@@ -1,15 +1,24 @@
 import {
-  GelMessage,
-  GelSystemMessage,
-  GelUserMessage,
-  GelAssistantMessage,
-  GelToolMessage,
+  createRAGClient,
+  RAGClient,
+  Message,
+  SystemMessage,
+  UserMessage,
+  AssistantMessage,
+  ToolMessage,
+  RAGOptions,
 } from "@gel/ai";
 
 export * from "@gel/ai";
 
-export type EdgeDBSystemMessage = GelSystemMessage;
-export type EdgeDBUserMessage = GelUserMessage;
-export type EdgeDBAssistantMessage = GelAssistantMessage;
-export type EdgeDBToolMessage = GelToolMessage;
-export type EdgeDBMessage = GelMessage;
+export type EdgeDBAI = RAGClient;
+export const EdgeDBAI = RAGClient;
+
+export const createAI = createRAGClient;
+
+export type EdgeDBSystemMessage = SystemMessage;
+export type EdgeDBUserMessage = UserMessage;
+export type EdgeDBAssistantMessage = AssistantMessage;
+export type EdgeDBToolMessage = ToolMessage;
+export type EdgeDBMessage = Message;
+export type AIOptions = RAGOptions;

packages/ai/README.md

@@ -16,26 +16,26 @@ See the AI documentation for detailed guidance on setting up the AI extension an
 
 ## API Reference
 
-### `createAI(client: Client, options: Partial<AIOptions> = {}): GelAI`
+### `createRAGClient(client: Client, options: Partial<AIOptions> = {}): RAGClient`
 
-Creates an instance of `GelAI` with the specified client and options.
+Creates an instance of `RAGClient` with the specified client and options.
 
-- `client`: An Gel client instance.
+- `client`: A Gel client instance.
 - `options`: Configuration options for the AI model.
   - `model`: Required. Specifies the AI model to use. This could be some of the OpenAI, Mistral or Anthropic models supported by Gel AI.
   - `prompt`: Optional. Defines the input messages for the AI model. The prompt can have an `ID` or a `name` referencing a stored prompt. The referenced prompt will supply predefined messages. Optionally, include a custom list of messages using the `custom` field. These custom messages will be concatenated with messages from the stored prompt referenced by `id` or `name`. If no `id` or `name` is specified, only the `custom` messages will be used. If no `id`, `name`, or `custom` messages are provided, the built-in system prompt will be used by default.
 
-### `GelAI`
+### `RAGClient`
 
 #### Public Methods
 
-- `withConfig(options: Partial<AIOptions>): GelAI`
+- `withConfig(options: Partial<AIOptions>): RAGClient`
 
-  Returns a new `GelAI` instance with updated configuration options.
+  Returns a new `RAGClient` instance with updated configuration options.
 
-- `withContext(context: Partial<QueryContext>): GelAI`
+- `withContext(context: Partial<QueryContext>): RAGClient`
 
-  Returns a new `GelAI` instance with an updated query context.
+  Returns a new `RAGClient` instance with an updated query context.
 
 - `async queryRag(message: string, context?: QueryContext): Promise<string>`
 
@@ -62,54 +62,54 @@ The following example demonstrates how to use the `@gel/ai` package to query an
 
 ```typescript
 import { createClient } from "gel";
-import { createAI } from "./src/index.js";
+import { createRAGClient } from "@gel/ai";
 
-const client = createClient({
+const client = createRAGClient({
   instanceName: "_localdev",
   database: "main",
   tlsSecurity: "insecure",
 });
 
-const gpt4Ai = createAI(client, {
-  model: "gpt-4-turbo-preview",
+const gpt4Rag = createRAGClient(client, {
+  model: "gpt-4-turbo",
 });
 
-const astronomyAi = gpt4Ai.withContext({ query: "Astronomy" });
+const astronomyRag = gpt4Rag.withContext({ query: "Astronomy" });
 
 console.time("gpt-4 Time");
-console.log(await astronomyAi.queryRag("What color is the sky on Mars?"));
+console.log(await astronomyRag.queryRag("What color is the sky on Mars?"));
 console.timeEnd("gpt-4 Time");
 
-const fastAstronomyAi = astronomyAi.withConfig({
-  model: "gpt-3.5-turbo",
+const fastAstronomyRag = astronomyRag.withConfig({
+  model: "gpt-4o",
 });
 
-console.time("gpt-3.5 Time");
-console.log(await fastAstronomyAi.queryRag("What color is the sky on Mars?"));
-console.timeEnd("gpt-3.5 Time");
+console.time("gpt-4o Time");
+console.log(await fastAstronomyRag.queryRag("What color is the sky on Mars?"));
+console.timeEnd("gpt-4o Time");
 
-const fastChemistryAi = fastAstronomyAi.withContext({ query: "Chemistry" });
+const fastChemistryRag = fastAstronomyRag.withContext({ query: "Chemistry" });
 
 console.log(
-  await fastChemistryAi.queryRag("What is the atomic number of gold?"),
+  await fastChemistryRag.queryRag("What is the atomic number of gold?"),
 );
 
 // handle the Response object
-const response = await fastChemistryAi.streamRag(
+const response = await fastChemistryRag.streamRag(
   "What is the atomic number of gold?",
 );
 handleReadableStream(response); // custom function that reads the stream
 
 // handle individual chunks as they arrive
-for await (const chunk of fastChemistryAi.streamRag(
+for await (const chunk of fastChemistryRag.streamRag(
   "What is the atomic number of gold?",
 )) {
   console.log("chunk", chunk);
 }
 
 // embeddings
 console.log(
-  await fastChemistryAi.generateEmbeddings(
+  await fastChemistryRag.generateEmbeddings(
     ["What is the atomic number of gold?"],
     "text-embedding-ada-002",
   ),

packages/ai/src/core.ts

@@ -7,7 +7,7 @@ import {
   type AuthenticatedFetch,
 } from "gel/dist/utils.js";
 import {
-  type AIOptions,
+  type RAGOptions,
   type QueryContext,
   type StreamingMessage,
   type RagRequest,
@@ -18,25 +18,25 @@ import { getHTTPSCRAMAuth } from "gel/dist/httpScram.js";
 import { cryptoUtils } from "gel/dist/browserCrypto.js";
 import { extractMessageFromParsedEvent, handleResponseError } from "./utils.js";
 
-export function createAI(client: Client, options: AIOptions) {
-  return new GelAI(client, options);
+export function createRAGClient(client: Client, options: RAGOptions) {
+  return new RAGClient(client, options);
 }
 
 const httpSCRAMAuth = getHTTPSCRAMAuth(cryptoUtils);
 
-export class GelAI {
+export class RAGClient {
   /** @internal */
   private readonly authenticatedFetch: Promise<AuthenticatedFetch>;
-  private readonly options: AIOptions;
+  private readonly options: RAGOptions;
   private readonly context: QueryContext;
 
   /** @internal */
   constructor(
     public readonly client: Client,
-    options: AIOptions,
+    options: RAGOptions,
     context: Partial<QueryContext> = {},
   ) {
-    this.authenticatedFetch = GelAI.getAuthenticatedFetch(client);
+    this.authenticatedFetch = RAGClient.getAuthenticatedFetch(client);
     this.options = options;
     this.context = {
       query: context.query ?? "",
@@ -53,16 +53,16 @@ export class GelAI {
     return getAuthenticatedFetch(connectConfig, httpSCRAMAuth, "ext/ai/");
   }
 
-  withConfig(options: Partial<AIOptions>) {
-    return new GelAI(
+  withConfig(options: Partial<RAGOptions>) {
+    return new RAGClient(
       this.client,
       { ...this.options, ...options },
       this.context,
     );
   }
 
   withContext(context: Partial<QueryContext>) {
-    return new GelAI(this.client, this.options, {
+    return new RAGClient(this.client, this.options, {
       ...this.context,
       ...context,
     });

packages/ai/src/types.ts

@@ -1,16 +1,16 @@
 export type ChatParticipantRole = "system" | "user" | "assistant" | "tool";
 
-export interface GelSystemMessage {
+export interface SystemMessage {
   role: "system";
   content: string;
 }
 
-export interface GelUserMessage {
+export interface UserMessage {
   role: "user";
   content: { type: "text"; text: string }[];
 }
 
-export interface GelAssistantMessage {
+export interface AssistantMessage {
   role: "assistant";
   content: string;
   tool_calls?: {
@@ -20,24 +20,24 @@ export interface GelAssistantMessage {
   }[];
 }
 
-export interface GelToolMessage {
+export interface ToolMessage {
   role: "tool";
   content: string;
   tool_call_id: string;
 }
 
-export type GelMessage =
-  | GelSystemMessage
-  | GelUserMessage
-  | GelAssistantMessage
-  | GelToolMessage;
+export type Message =
+  | SystemMessage
+  | UserMessage
+  | AssistantMessage
+  | ToolMessage;
 
 export type Prompt =
-  | { name: string; custom?: GelMessage[] }
-  | { id: string; custom?: GelMessage[] }
-  | { custom: GelMessage[] };
+  | { name: string; custom?: Message[] }
+  | { id: string; custom?: Message[] }
+  | { custom: Message[] };
 
-export interface AIOptions {
+export interface RAGOptions {
   model: string;
   prompt?: Prompt;
 }
@@ -55,7 +55,7 @@ export interface RagRequestPrompt {
 }
 
 export interface RagRequestMessages {
-  messages: GelMessage[];
+  messages: Message[];
   [key: string]: unknown;
 }