feat: RAG chat implemented

.github/workflows/jsr-publish.yml

@@ -22,4 +22,5 @@ jobs:
         run: |
           bun install
           bun run build
+          bunx kksh@latest verify --publish
           bunx jsr publish --allow-slow-types

.vscode/settings.json

@@ -0,0 +1,3 @@
+{
+    "deno.enable": true
+}

README.md

@@ -3,3 +3,29 @@
 RAG means Retrieval-Augmented Generation.
 
 This extension is a local RAG app, that allows you to index a local directory of files and search them using a LLM model.
+
+If you don't know what RAG is, see [Wikipedia: RAG](https://en.wikipedia.org/wiki/Retrieval-augmented_generation)
+
+Basically, this extension allows you index local files and directories and search them using a LLM model.
+
+For now, only text files and pdf files are supported.
+
+The following file extensions are supported for `Add Files`:
+
+- `.txt`
+- `.pdf`
+- `.md`
+- `.mdx`
+
+`.pdf` is not supported yet for `Add Directory`.
+
+> [!CAUTION]
+> If you want other file extensions to be supported, please send a issue to the repository.
+> I will add options to let user add dynamic file extensions if there are people using this extension.
+
+This is to prevent indexing other files you may not want to index, like lock files.
+
+## Sample Images
+
+![](https://i.imgur.com/SMwsks7.png)
+![](https://i.imgur.com/KPkwhMN.png)

deno-src/bucket.ts

@@ -1,17 +1,22 @@
 import { FaissStore } from '@langchain/community/vectorstores/faiss';
-import { OpenAIEmbeddings } from '@langchain/openai';
+import { ChatOpenAI, OpenAIEmbeddings } from '@langchain/openai';
 import * as v from 'valibot';
 import * as path from 'jsr:@std/path';
 import { existsSync, readdirSync } from 'node:fs';
 import { Document } from '@langchain/core/documents';
 import { RecursiveCharacterTextSplitter } from '@langchain/textsplitters';
 import { DirectoryLoader } from 'langchain/document_loaders/fs/directory';
-import { JSONLoader, JSONLinesLoader } from 'langchain/document_loaders/fs/json';
 import { TextLoader } from 'langchain/document_loaders/fs/text';
 import { computeSha256FromText } from './crypto.ts';
 import { PDFLoader } from '@langchain/community/document_loaders/fs/pdf';
+import { DenoAPI } from '../src/api.types.ts';
+import { txtExts } from './constants.ts';
+import { AIMessageChunk } from '@langchain/core/messages';
 
 export const embeddings = new OpenAIEmbeddings({
+	// configuration: {
+	// 	baseURL: 'https://api.deepseek.com'
+	// },
 	model: 'text-embedding-3-large'
 });
 
@@ -27,8 +32,8 @@ export async function getDocsFromDirectory(directoryPath: string): Promise<Docum
 	});
 
 	const loader = new DirectoryLoader(directoryPath, {
-		'.json': (path) => new JSONLoader(path, '/texts'),
-		'.jsonl': (path) => new JSONLinesLoader(path, '/html'),
+		// '.json': (path) => new JSONLoader(path, '/texts'),
+		// '.jsonl': (path) => new JSONLinesLoader(path, '/html'),
 		'.txt': (path) => new TextLoader(path),
 		'.md': (path) => new TextLoader(path),
 		'.mdx': (path) => new TextLoader(path)
@@ -38,23 +43,22 @@ export async function getDocsFromDirectory(directoryPath: string): Promise<Docum
 	return allSplits;
 }
 
-export class Bucket {
-	readonly bucketPath: string;
-	readonly faissStorePath: string;
-	readonly metadataPath: string;
+export class Bucket implements DenoAPI {
+	bucketPath: string = '';
+	faissStorePath: string = '';
+	metadataPath: string = '';
+	bucketDir: string = '';
+	bucketName: string = '';
 	private _vectorStore: FaissStore | null = null;
 	filesSha256: Set<string> = new Set();
 
-	constructor(
-		readonly bucketDir: string,
-		readonly bucketName: string
-	) {
+	async init(bucketDir: string, bucketName: string) {
+		this.bucketDir = bucketDir;
+		this.bucketName = bucketName;
 		this.bucketPath = path.join(this.bucketDir, this.bucketName);
 		this.faissStorePath = path.join(this.bucketPath, 'faiss-store');
 		this.metadataPath = path.join(this.bucketPath, 'metadata.json');
-	}
 
-	async init() {
 		if (!existsSync(this.bucketPath)) {
 			Deno.mkdirSync(this.bucketPath, { recursive: true });
 		}
@@ -69,9 +73,6 @@ export class Bucket {
 		}
 		this.updateMetadata();
 		this._vectorStore = await this.getVectorStore();
-		// if (this._vectorStore) {
-		//   await this._vectorStore.save(this.faissStorePath);
-		// }
 	}
 
 	updateMetadata() {
@@ -160,7 +161,7 @@ export class Bucket {
 		this.updateSha256(docs);
 		console.error('Updated sha256', this.filesSha256.size);
 		// await this.addDocuments(fileteredDocs);
-		return this.vectorStore.addDocuments(fileteredDocs).catch((err) => {
+		await this.vectorStore.addDocuments(fileteredDocs).catch((err) => {
 			console.error('Error adding documents', err);
 		});
 	}
@@ -184,4 +185,70 @@ export class Bucket {
 		this.updateSha256(docs);
 		await this.addDocuments(fileteredDocs);
 	}
+
+	async retrieve(query: string) {
+		const retriever = this.vectorStore.asRetriever();
+		const docs = await retriever.invoke(query);
+		const docsText = docs.map((d) => d.pageContent).join('');
+		return docsText;
+	}
+
+	async query(question: string) {
+		const docsText = await this.retrieve(question);
+		const systemPrompt = `You are an assistant for question-answering tasks.
+Use the following pieces of retrieved context to answer the question.
+If you don't know the answer, just say that you don't know.
+Use three sentences maximum and keep the answer concise.
+Context: {context}:`;
+
+		// Populate the system prompt with the retrieved context
+		const systemPromptFmt = systemPrompt.replace('{context}', docsText);
+
+		// Create a model
+		const model = new ChatOpenAI({
+			model: 'gpt-4o',
+			temperature: 0
+		});
+
+		// Generate a response
+		const ans: AIMessageChunk = await model.invoke([
+			{
+				role: 'system',
+				content: systemPromptFmt
+			},
+			{
+				role: 'user',
+				content: question
+			}
+		]);
+		return ans.content.toString();
+	}
+
+	async indexFiles(files: string[]) {
+		console.error('Indexing files', files);
+		for (const file of files) {
+			if (!existsSync(file)) {
+				throw new Error(`File ${file} does not exist`);
+			}
+			// check if file is directory
+			const stats = Deno.statSync(file);
+			console.error('Indexing file', file, 'stats.isFile', stats.isFile);
+			if (stats.isFile) {
+				const ext = path.extname(file);
+				if (txtExts.includes(ext)) {
+					console.error('Adding text file 1', file);
+					await this.addTextFile(file);
+					console.error('Finished adding text file', file);
+				} else if (ext === '.pdf') {
+					console.error('Adding pdf file', file);
+					await this.addPDF(file);
+				} else {
+					throw new Error(`Unsupported file type: ${ext}`);
+				}
+			} else {
+				console.error('Adding directory', file);
+				await this.addDirectory(file);
+			}
+		}
+	}
 }

deno-src/dev.ts

@@ -1,77 +0,0 @@
-// import { FaissStore } from '@langchain/community/vectorstores/faiss';
-// import { Bucket, embeddings, getDocsFromDirectory } from './bucket.ts';
-// import { RecursiveCharacterTextSplitter } from '@langchain/textsplitters';
-// import { DirectoryLoader } from 'langchain/document_loaders/fs/directory';
-// import { JSONLoader, JSONLinesLoader } from 'langchain/document_loaders/fs/json';
-// import { TextLoader } from 'langchain/document_loaders/fs/text';
-// import { OpenAIEmbeddings } from '@langchain/openai';
-import { existsSync } from 'node:fs';
-// import path from 'path';
-import { txtExts } from './constants.ts';
-import { Bucket } from './bucket.ts';
-import path from 'node:path';
-
-async function indexFiles(bucketName: string, files: string[]): Promise<void> {
-	const bucket = new Bucket('./store', bucketName);
-	// const bucket = new Bucket(extensionSupportPath, bucketName);
-	console.error('bucket path', bucket.bucketPath);
-	console.error('files', files);
-	await bucket.init();
-	for (const file of files) {
-		if (!existsSync(file)) {
-			throw new Error(`File ${file} does not exist`);
-		}
-		console.error('file', file);
-		// check if file is directory
-		const stats = Deno.statSync(file);
-		if (stats.isFile) {
-			const ext = path.extname(file);
-			if (txtExts.includes(ext)) {
-				console.error('Adding text file', file);
-				await bucket.addTextFile(file);
-				console.error('Finished adding text file', file);
-			} else if (ext === '.pdf') {
-				console.error('Adding pdf file', file);
-				await bucket.addPDF(file);
-			} else if (stats.isDirectory) {
-				console.error('Adding directory', file);
-				await bucket.addDirectory(file);
-			} else {
-				throw new Error(`Unsupported file type: ${ext}`);
-			}
-		}
-	}
-	await bucket.save();
-}
-indexFiles('Kunkun Docs', ['/Users/hk/Dev/kunkun-docs/src/content/docs/developer/DX.mdx']);
-
-// const bucket = new Bucket(
-// 	'/Users/hk/Dev/kunkun-extension-repos/kunkun-ext-rag/extensions_support',
-// 	'Kunkun Docs'
-// );
-// await bucket.init();
-// const files = ['/Users/hk/Dev/kunkun-docs/src/content/docs/developer/manifest.mdx'];
-// for (const file of files) {
-// 	if (!existsSync(file)) {
-// 		throw new Error(`File ${file} does not exist`);
-// 	}
-// 	console.error('file', file);
-// 	// check if file is directory
-// 	const stats = Deno.statSync(file);
-// 	if (stats.isFile) {
-// 		const ext = path.extname(file);
-// 		if (txtExts.includes(ext)) {
-// 			console.error('Adding text file', file);
-// 			await bucket.addTextFile(file);
-// 		} else if (ext === '.pdf') {
-// 			console.error('Adding pdf file', file);
-// 			await bucket.addPDF(file);
-// 		} else if (stats.isDirectory) {
-// 			console.error('Adding directory', file);
-// 			await bucket.addDirectory(file);
-// 		} else {
-// 			throw new Error(`Unsupported file type: ${ext}`);
-// 		}
-// 	}
-// }
-// await bucket.save();

deno-src/index.ts

@@ -1,48 +1,5 @@
 import { expose } from '@kunkun/api/runtime/deno';
 import type { DenoAPI } from '../src/api.types.ts';
 import { Bucket } from './bucket.ts';
-import { existsSync } from 'node:fs';
-import path from 'node:path';
-import { txtExts } from './constants.ts';
 
-export const extensionSupportPath = Deno.env.get('EXTENSION_SUPPORT');
-if (!extensionSupportPath) {
-	throw new Error('EXTENSION_SUPPORT is not set');
-}
-
-expose({
-	async indexFiles(bucketName: string, files: string[]): Promise<void> {
-		const cwd = Deno.cwd();
-		console.error('cwd', cwd);
-		const bucket = new Bucket(extensionSupportPath, bucketName);
-		// const bucket = new Bucket(extensionSupportPath, bucketName);
-		console.error('bucket path', bucket.bucketPath);
-		console.error('files', files);
-		await bucket.init();
-		for (const file of files) {
-			if (!existsSync(file)) {
-				throw new Error(`File ${file} does not exist`);
-			}
-			console.error('file', file);
-			// check if file is directory
-			const stats = Deno.statSync(file);
-			if (stats.isFile) {
-				const ext = path.extname(file);
-				if (txtExts.includes(ext)) {
-					console.error('Adding text file', file);
-					await bucket.addTextFile(file);
-					console.error('Finished adding text file', file);
-				} else if (ext === '.pdf') {
-					console.error('Adding pdf file', file);
-					await bucket.addPDF(file);
-				} else if (stats.isDirectory) {
-					console.error('Adding directory', file);
-					await bucket.addDirectory(file);
-				} else {
-					throw new Error(`Unsupported file type: ${ext}`);
-				}
-			}
-		}
-		await bucket.save();
-	}
-} satisfies DenoAPI);
+expose(new Bucket() satisfies DenoAPI);

deno-src/main.ts

@@ -60,60 +60,60 @@ async function deleteDocuments(vectorStore: FaissStore, ids: string[]) {
 
 const vectorStore = await getVectorStore();
 
-// const llm = new ChatOpenAI({
-//   model: "gpt-4o-mini",
-//   temperature: 0,
-// });
+const llm = new ChatOpenAI({
+  model: "gpt-4o-mini",
+  temperature: 0,
+});
 
-// // Define prompt for question-answering
-// const promptTemplate = await pull<ChatPromptTemplate>("rlm/rag-prompt");
+// Define prompt for question-answering
+const promptTemplate = await pull<ChatPromptTemplate>("rlm/rag-prompt");
 
-// // Define state for application
-// const InputStateAnnotation = Annotation.Root({
-//   question: Annotation<string>,
-// });
+// Define state for application
+const InputStateAnnotation = Annotation.Root({
+  question: Annotation<string>,
+});
 
-// const StateAnnotation = Annotation.Root({
-//   question: Annotation<string>,
-//   context: Annotation<Document[]>,
-//   answer: Annotation<string>,
-// });
+const StateAnnotation = Annotation.Root({
+  question: Annotation<string>,
+  context: Annotation<Document[]>,
+  answer: Annotation<string>,
+});
 
-// // Define application steps
-// const retrieve = async (state: typeof InputStateAnnotation.State) => {
-//   const retrievedDocs = await vectorStore.similaritySearch(state.question);
-//   return { context: retrievedDocs };
-// };
+// Define application steps
+const retrieve = async (state: typeof InputStateAnnotation.State) => {
+  const retrievedDocs = await vectorStore.similaritySearch(state.question);
+  return { context: retrievedDocs };
+};
 
-// const generate = async (state: typeof StateAnnotation.State) => {
-//   const docsContent = state.context.map((doc) => doc.pageContent).join("\n");
-//   const messages = await promptTemplate.invoke({
-//     question: state.question,
-//     context: docsContent,
-//   });
-//   const response = await llm.invoke(messages);
-//   return { answer: response.content };
-// };
+const generate = async (state: typeof StateAnnotation.State) => {
+  const docsContent = state.context.map((doc) => doc.pageContent).join("\n");
+  const messages = await promptTemplate.invoke({
+    question: state.question,
+    context: docsContent,
+  });
+  const response = await llm.invoke(messages);
+  return { answer: response.content };
+};
 
-// // Compile application and test
-// const graph = new StateGraph(StateAnnotation)
-//   .addNode("retrieve", retrieve)
-//   .addNode("generate", generate)
-//   .addEdge("__start__", "retrieve")
-//   .addEdge("retrieve", "generate")
-//   .addEdge("generate", "__end__")
-//   .compile();
+// Compile application and test
+const graph = new StateGraph(StateAnnotation)
+  .addNode("retrieve", retrieve)
+  .addNode("generate", generate)
+  .addEdge("__start__", "retrieve")
+  .addEdge("retrieve", "generate")
+  .addEdge("generate", "__end__")
+  .compile();
 
-// let inputs = { question: "What is Task Decomposition?" };
+let inputs = { question: "What is Task Decomposition?" };
 
-// while (true) {
-//   const question = prompt("Enter your question (or 'exit' to quit): ");
-//   if (!question || question.toLowerCase() === "exit") {
-//     break;
-//   }
+while (true) {
+  const question = prompt("Enter your question (or 'exit' to quit): ");
+  if (!question || question.toLowerCase() === "exit") {
+    break;
+  }
 
-//   const result = await graph.invoke({ question });
-//   console.log("\nAnswer:");
-//   console.log(result.answer);
-//   console.log("\n-------------------\n");
-// }
+  const result = await graph.invoke({ question });
+  console.log("\nAnswer:");
+  console.log(result.answer);
+  console.log("\n-------------------\n");
+}

jsr.json

@@ -1,19 +1,22 @@
 {
 	"name": "@kunkun/kunkun-ext-rag",
-	"version": "0.0.4",
+	"version": "0.0.5",
 	"license": "MIT",
 	"exports": "./mod.ts",
 	"publish": {
 		"include": ["mod.ts", "deno-src", "build", "LICENSE", "README.md", "package.json"]
 	},
 	"imports": {
+		"@kunkun/api": "jsr:@kunkun/api@^0.0.52",
 		"@langchain/community": "npm:@langchain/community@^0.3.22",
 		"@langchain/core": "npm:@langchain/core@^0.3.27",
 		"@langchain/langgraph": "npm:@langchain/langgraph@^0.2.38",
 		"@langchain/openai": "npm:@langchain/openai@^0.3.16",
 		"@langchain/textsplitters": "npm:@langchain/textsplitters@^0.1.0",
+		"pdf-parse": "npm:pdf-parse@^1.1.1",
 		"@std/assert": "jsr:@std/assert@1",
+		"valibot": "jsr:@valibot/valibot@^0.42.1",
 		"faiss-node": "npm:faiss-node@^0.5.1",
-		"langchain": "npm:langchain@^0.3.9"
+		"langchain": "npm:langchain@^0.3.12"
 	}
 }

package.json

@@ -3,7 +3,7 @@
 	"license": "MIT",
 	"name": "kunkun-ext-rag",
 	"draft": true,
-	"version": "0.0.4",
+	"version": "0.0.5",
 	"private": true,
 	"kunkun": {
 		"name": "RAG",
@@ -62,14 +62,25 @@
 				]
 			},
 			"shell:stdin-write",
-			"shell:kill"
+			"shell:kill",
+			{
+				"permission": "open:url",
+				"allow": [
+					{
+						"url": "https://en.wikipedia.org/wiki/Retrieval-augmented_generation"
+					},
+					{
+						"url": "https://github.com/kunkunsh/kunkun-ext-rag"
+					}
+				]
+			}
 		],
 		"customUiCmds": [
 			{
 				"main": "/",
 				"dist": "build",
 				"devMain": "http://localhost:5173",
-				"name": "RAG",
+				"name": "Local RAG",
 				"cmds": []
 			}
 		],
@@ -88,9 +99,11 @@
 		"@iconify/svelte": "^4.2.0",
 		"@kksh/api": "^0.0.55",
 		"@kksh/svelte5": "0.1.15",
+		"@langchain/openai": "^0.4.2",
 		"clsx": "^2.1.1",
 		"lucide-svelte": "^0.474.0",
 		"mode-watcher": "^0.5.1",
+		"svelte-markdown": "^0.4.1",
 		"sveltekit-superforms": "^2.23.1",
 		"tailwind-merge": "^2.6.0",
 		"tailwind-variants": "^0.3.1",

src/api.types.ts

@@ -1,3 +1,10 @@
 export interface DenoAPI {
-	indexFiles(bucketName: string, files: string[]): Promise<void>;
+	init(bucketDir: string, bucketName: string): Promise<void>;
+	addTextFile(filePath: string): Promise<void>;
+	addPDF(filePath: string): Promise<void>;
+	addDirectory(dir: string): Promise<void>;
+	indexFiles(files: string[]): Promise<void>;
+	save(): Promise<void>;
+	retrieve(query: string): Promise<string>;
+	query(query: string): Promise<string>;
 }

src/lib/components/DatabaseList.svelte

@@ -11,8 +11,9 @@
 			<Card.Title>{dbInfo.name}</Card.Title>
 			<Card.Description><strong>AI Provider:</strong> {dbInfo.ai}</Card.Description>
 		</Card.Header>
-		<Card.Content>
+		<Card.Content class="grid grid-cols-2 gap-2">
 			<Button
+				class="w-full"
 				variant="destructive"
 				size="lg"
 				onclick={() =>
@@ -24,7 +25,9 @@
 			>
 				Delete
 			</Button>
-			<a href={`/database/${dbInfo.id}`}><Button>Manage Database</Button></a>
+			<a class="w-full" href={`/database/${dbInfo.id}`}>
+				<Button size="lg" class="w-full">Use Database</Button>
+			</a>
 		</Card.Content>
 	</Card.Root>
 {/snippet}

src/lib/components/TauriLink.svelte

@@ -0,0 +1,16 @@
+<script lang="ts">
+	import { open } from '@kksh/api/ui/iframe';
+
+	let { href, children } = $props();
+</script>
+
+<a
+	class="text-blue-500 hover:underline"
+	{href}
+	onclick={(e) => {
+		e.preventDefault();
+		open.url(href);
+	}}
+>
+	{@render children()}
+</a>

src/lib/components/app-sidebar.svelte

@@ -1,8 +1,7 @@
 <script lang="ts">
 	import { ui } from '@kksh/api/ui/iframe';
 	import { Sidebar } from '@kksh/svelte5';
-	import Icon from '@iconify/svelte';
-	import { BotIcon, DatabaseIcon, MessageCircleIcon } from 'lucide-svelte';
+	import { DatabaseIcon, InfoIcon } from 'lucide-svelte';
 	import { onMount } from 'svelte';
 
 	onMount(() => {
@@ -16,9 +15,9 @@
 			icon: DatabaseIcon
 		},
 		{
-			title: 'Chat',
-			url: '/chat',
-			icon: MessageCircleIcon
+			title: 'About',
+			url: '/about',
+			icon: InfoIcon
 		}
 	];
 </script>

src/lib/deno.ts

@@ -1,7 +1,7 @@
 import { fs, shell, path, toast } from '@kksh/api/ui/iframe';
-import type { DenoAPI } from '../api.types';
+import type { DenoAPI } from '../api.types.ts';
 
-export async function getRpcAPI(env: { OPENAI_API_KEY: string; EXTENSION_SUPPORT: string }) {
+export async function getRpcAPI(env: { OPENAI_API_KEY: string }) {
 	await installDenoDeps().catch((err) => {
 		return toast.error(`Failed to install deno dependencies; ${err.message}`);
 	});
@@ -13,7 +13,7 @@ export async function getRpcAPI(env: { OPENAI_API_KEY: string; EXTENSION_SUPPORT
 		{
 			cwd,
 			// allowAllEnv: true,
-			allowEnv: ['OPENAI_API_KEY', 'EXTENSION_SUPPORT', 'CWD'],
+			allowEnv: ['OPENAI_API_KEY', 'CWD'],
 			allowWrite: ['$EXTENSION_SUPPORT'],
 			allowAllRead: true,
 			// allowAllWrite: true,

src/routes/about/+page.svelte

@@ -1,15 +1,30 @@
 <script>
 	import { base } from '$app/paths';
+	import TauriLink from '@/components/TauriLink.svelte';
 	import { Alert, Button, ThemeWrapper } from '@kksh/svelte5';
 </script>
 
-<ThemeWrapper>
-	<Alert.Root>
-		<Alert.Title class="text-3xl font-bold">About Page</Alert.Title>
-		<Alert.Description>
-			<a href="{base}/">
-				<Button>Home Page</Button>
-			</a>
-		</Alert.Description>
-	</Alert.Root>
-</ThemeWrapper>
+<div class="prose container">
+	<h1 class="text-3xl font-bold">About Page</h1>
+	<strong>Source Code:</strong>
+	<TauriLink href="https://github.com/kunkunsh/kunkun-ext-rag">
+		https://github.com/kunkunsh/kunkun-ext-rag
+	</TauriLink>.
+	<br />
+	<br />
+	<p>
+		Kunkun RAG Extension is a local RAG app, that allows you to index a local directory of files and
+		search them using a LLM model.
+	</p>
+	<p>
+		If you don't know what RAG is, you can read more about it
+		<TauriLink href="https://en.wikipedia.org/wiki/Retrieval-augmented_generation">
+			https://en.wikipedia.org/wiki/Retrieval-augmented_generation
+		</TauriLink>.
+	</p>
+	<p>You can add files to a database. Currently only text files are supported.</p>
+	<p>
+		Text Files with extension <code>.txt</code>, <code>.md</code>, <code>.mdx</code> are supported. If
+		you need other file types, send a feature request to the repo.
+	</p>
+</div>

src/routes/database/[id]/+page.svelte

@@ -1,43 +1,51 @@
 <script lang="ts">
-	import { dialog, path } from '@kksh/api/ui/iframe';
+	import { dialog, path, toast } from '@kksh/api/ui/iframe';
 	import { dbStore } from '@/stores/db';
-	import { Button } from '@kksh/svelte5';
+	import { Button, Input, Popover } from '@kksh/svelte5';
 	import { getRpcAPI } from '@/deno';
+	import { enhance } from '$app/forms';
 	import { goto } from '$app/navigation';
-	import { toast } from '@kksh/api/headless';
-	let { data } = $props();
+	import { onDestroy, onMount } from 'svelte';
+	import { InfoIcon, LoaderIcon } from 'lucide-svelte';
+	import SvelteMarkdown from 'svelte-markdown';
 
+	let { data } = $props();
+	let query = $state('');
+	let ans = $state('');
+	let loading = $state(false);
 	const selectedDb = $dbStore.find((db) => db.id === data.id);
-	if (!selectedDb) {
-		toast.error('Database not found', { description: 'Name: ' + data.id });
-		goto('/');
-	}
 	let rpc: Awaited<ReturnType<typeof getRpcAPI>> | undefined;
 
-	async function indexFiles(files: string[]) {
+	onMount(async () => {
 		if (!selectedDb) {
 			toast.error('Database not found', { description: 'Name: ' + data.id });
 			return goto('/');
 		}
+		rpc = await getRpcAPI({
+			OPENAI_API_KEY: selectedDb.apiKey
+		});
+		rpc.command.stderr.on('data', (data) => {
+			console.warn(data);
+		});
+		const extSupportDir = await path.extensionSupportDir();
+		await rpc?.api.init(extSupportDir, selectedDb!.name);
+	});
+
+	onDestroy(async () => {
+		await rpc?.process.kill();
+	});
+
+	async function indexFiles(files: string[]) {
 		try {
-			const extSupportDir = await path.extensionSupportDir();
-			rpc = await getRpcAPI({
-				OPENAI_API_KEY: selectedDb.apiKey,
-				EXTENSION_SUPPORT: extSupportDir
-			});
-			rpc.command.stderr.on('data', (data) => {
-				console.warn(data);
-			});
-			console.log('Start indexing files');
-			await rpc.api.indexFiles(selectedDb!.name, files);
+			console.log('Start indexing files', files);
+
+			await rpc?.api.indexFiles(files);
+			await rpc?.api.save();
 			console.log('Finished indexing files');
+			toast.success('Finished indexing files');
 		} catch (error) {
 			console.error('Error indexing files', error);
 			toast.error('Failed to index files');
-		} finally {
-			setTimeout(async () => {
-				await rpc?.process.kill();
-			}, 2_000);
 		}
 	}
 
@@ -65,7 +73,51 @@
 </script>
 
 <div class="container">
-	<h1 class="text-2xl font-bold">Manage Database</h1>
-	<Button onclick={addFiles}>Add Files</Button>
-	<Button onclick={addDirectory}>Add Directory</Button>
+	<h1 class="text-2xl font-bold">
+		Manage Database
+		<Popover.Root>
+			<Popover.Trigger>
+				<Button size="icon" variant="ghost">
+					<InfoIcon />
+				</Button>
+			</Popover.Trigger>
+			<Popover.Content>
+				Pick the files or directories you want to index into vector database. Then you can use the
+				database to answer questions.
+			</Popover.Content>
+		</Popover.Root>
+	</h1>
+	<div class="flex gap-2">
+		<Button class="w-full" onclick={addFiles}>Add Files</Button>
+		<Button class="w-full" onclick={addDirectory}>Add Directory</Button>
+	</div>
+	<form
+		method="POST"
+		use:enhance={async ({ formElement, formData, action, cancel, submitter }) => {
+			cancel();
+			ans = '';
+			loading = true;
+			if (query.length === 0) {
+				toast.error('Question is required');
+				return;
+			}
+			ans = (await rpc?.api.query(query)) ?? '';
+			query = '';
+			loading = false;
+		}}
+	>
+		<div class="mt-4 flex gap-1">
+			<Input name="query" type="text" bind:value={query} placeholder="Question" />
+			<Button type="submit">Submit</Button>
+		</div>
+		{#if loading}
+			<div class="flex h-64 items-center justify-center">
+				<LoaderIcon class="animate-spin" />
+			</div>
+		{:else}
+			<div class="container mt-4">
+				<SvelteMarkdown source={ans} />
+			</div>
+		{/if}
+	</form>
 </div>

src/routes/database/[id]/+page.ts

@@ -1,5 +1,7 @@
 import type { PageLoad } from './$types';
 
+export const prerender = false;
+
 export const load: PageLoad = ({ params: { id } }) => {
 	return { id: parseInt(id) };
 };

svelte.config.js

@@ -11,7 +11,9 @@ const config = {
 		// adapter-auto only supports some environments, see https://kit.svelte.dev/docs/adapter-auto for a list.
 		// If your environment is not supported, or you settled on a specific environment, switch out the adapter.
 		// See https://kit.svelte.dev/docs/adapters for more information about adapters.
-		adapter: adapter({}),
+		adapter: adapter({
+			fallback: '400.html'
+		}),
 		alias: {
 			'@/*': './src/lib/*'
 		}