chore: fix cortex bundle relative path lookup

.github/workflows/cortex-build.yml

@@ -1,4 +1,4 @@
-name: CI Cortex CPP
+name: CI Cortex Release
 
 on:
   push:

cortex-js/package.json

@@ -12,9 +12,9 @@
     "dev": "nest dev",
     "build": "nest build && cpx \"cpuinfo/bin/**\" dist/bin",
     "build:binary": "run-script-os && cpx \"cpuinfo/bin/**\" dist/bin",
-    "build:binary:windows": "bun build --compile --target=bun-windows-x64 ./src/command.js --outfile cortex.exe --external @nestjs/microservices --external @nestjs/websockets/socket-module --external class-transformer/storage",
-    "build:binary:linux": "bun build --compile --target=bun-linux-x64 ./src/command.js --outfile cortex --external @nestjs/microservices --external @nestjs/websockets/socket-module --external class-transformer/storage",
-    "build:binary:macos": "bun build --compile --target=bun-darwin-arm64 ./src/command.js --outfile cortex --external @nestjs/microservices --external @nestjs/websockets/socket-module --external class-transformer/storage",
+    "build:binary:windows": "bun build --compile --target=bun-windows-x64 ./src/command.ts --outfile cortex.exe --external @nestjs/microservices --external @nestjs/websockets/socket-module --external class-transformer/storage",
+    "build:binary:linux": "bun build --compile --target=bun-linux-x64 ./src/command.ts --outfile cortex --external @nestjs/microservices --external @nestjs/websockets/socket-module --external class-transformer/storage",
+    "build:binary:macos": "bun build --compile --target=bun-darwin-arm64 ./src/command.ts --outfile cortex --external @nestjs/microservices --external @nestjs/websockets/socket-module --external class-transformer/storage",
     "format": "prettier --write \"src/**/*.ts\" \"test/**/*.ts\"",
     "build:extensions": "run-script-os",
     "build:extensions:windows": "powershell -command \"$jobs = Get-ChildItem -Path './src/extensions' -Directory | ForEach-Object { Start-Job -Name ($_.Name) -ScriptBlock { param($_dir); try { Set-Location $_dir; yarn; yarn build; Write-Output 'Build successful in ' + $_dir } catch { Write-Error 'Error in ' + $_dir; throw } } -ArgumentList $_.FullName }; $jobs | Wait-Job; $jobs | ForEach-Object { Receive-Job -Job $_ -Keep } | ForEach-Object { Write-Host $_ }; $failed = $jobs | Where-Object { $_.State -ne 'Completed' -or $_.ChildJobs[0].JobStateInfo.State -ne 'Completed' }; if ($failed) { Exit 1 }\"",

cortex-js/src/app.ts

@@ -0,0 +1,72 @@
+import { NestFactory } from '@nestjs/core';
+import { DocumentBuilder, SwaggerModule } from '@nestjs/swagger';
+import { AppModule } from './app.module';
+import { FileManagerService } from './infrastructure/services/file-manager/file-manager.service';
+import { ValidationPipe } from '@nestjs/common';
+export const getApp = async () => {
+  const app = await NestFactory.create(AppModule, {
+    snapshot: true,
+    cors: true,
+    logger: console
+  });
+
+  const fileService = app.get(FileManagerService);
+  await fileService.getConfig();
+
+  app.useGlobalPipes(
+    new ValidationPipe({
+      transform: true,
+      enableDebugMessages: true,
+    }),
+  );
+
+  const config = new DocumentBuilder()
+    .setTitle('Cortex API')
+    .setDescription(
+      'Cortex API provides a command-line interface (CLI) for seamless interaction with large language models (LLMs). Fully compatible with the [OpenAI API](https://platform.openai.com/docs/api-reference), it enables straightforward command execution and management of LLM interactions.',
+    )
+    .setVersion('1.0')
+    .addTag(
+      'Inference',
+      'This endpoint initiates interaction with a Language Learning Model (LLM).',
+    )
+    .addTag(
+      'Assistants',
+      'These endpoints manage the lifecycle of an Assistant within a conversation thread.',
+    )
+    .addTag(
+      'Models',
+      'These endpoints provide a list and descriptions of all available models within the Cortex framework.',
+    )
+    .addTag(
+      'Messages',
+      'These endpoints manage the retrieval and storage of conversation content, including responses from LLMs and other metadata related to chat interactions.',
+    )
+    .addTag(
+      'Threads',
+      'These endpoints handle the creation, retrieval, updating, and deletion of conversation threads.',
+    )
+    .addTag(
+      'Embeddings',
+      'Endpoint for creating and retrieving embedding vectors from text inputs using specified models.',
+    )
+    .addTag(
+      'Status',
+      "Endpoint for actively querying the health status of the Cortex's API server.",
+    )
+    .addTag(
+      'Processes',
+      'Endpoint for terminating the Cortex API server processes.',
+    )
+    .addTag(
+      'Events',
+      'Endpoints for  observing Cortex statuses through event notifications.',
+    )
+    .addServer('http://localhost:1337')
+    .addServer('http://localhost:1337/v1')
+    .build();
+  const document = SwaggerModule.createDocument(app, config);
+
+  SwaggerModule.setup('api', app, document);
+  return app;
+};

cortex-js/src/infrastructure/commanders/serve.command.ts

@@ -1,13 +1,13 @@
-import { spawn } from 'child_process';
 import {
   defaultCortexJsHost,
   defaultCortexJsPort,
 } from '@/infrastructure/constants/cortex';
 import { CommandRunner, SubCommand, Option } from 'nest-commander';
-import { join } from 'path';
 import { SetCommandContext } from './decorators/CommandContext';
 import { ServeStopCommand } from './sub-commands/serve-stop.command';
 import { ContextService } from '../services/context/context.service';
+import { getApp } from '@/app';
+import { Logger } from '@nestjs/common';
 
 type ServeOptions = {
   address?: string;
@@ -30,32 +30,14 @@ export class ServeCommand extends CommandRunner {
     const host = options?.address || defaultCortexJsHost;
     const port = options?.port || defaultCortexJsPort;
 
-    return this.startServer(host, port, options);
+    return this.startServer(host, port);
   }
 
-  private async startServer(
-    host: string,
-    port: number,
-    options: ServeOptions = { detach: false },
-  ) {
-    const serveProcess = spawn(
-      'node',
-      [join(__dirname, '../../../dist/src/main.js')],
-      {
-        env: {
-          ...process.env,
-          CORTEX_JS_HOST: host,
-          CORTEX_JS_PORT: port.toString(),
-          NODE_ENV: 'production',
-        },
-        stdio: options?.detach ? 'ignore' : 'inherit',
-        detached: options?.detach,
-      },
-    );
-    if (options?.detach) {
-      serveProcess.unref();
-      console.log('Started server at http://%s:%d', host, port);
-    }
+  private async startServer(host: string, port: number) {
+    const app = await getApp();
+
+    await app.listen(port, host);
+    console.log(`Started server at http://${host}:${port}`);
   }
 
   @Option({
@@ -73,14 +55,4 @@ export class ServeCommand extends CommandRunner {
   parsePort(value: string) {
     return parseInt(value, 10);
   }
-
-  @Option({
-    flags: '-d, --detach',
-    description: 'Run the server in detached mode',
-    defaultValue: false,
-    name: 'detach',
-  })
-  parseDetach() {
-    return true;
-  }
 }

cortex-js/src/main.ts

@@ -1,78 +1,11 @@
-import { NestFactory } from '@nestjs/core';
-import { AppModule } from './app.module';
-import { DocumentBuilder, SwaggerModule } from '@nestjs/swagger';
-import { ValidationPipe } from '@nestjs/common';
 import {
   defaultCortexJsHost,
   defaultCortexJsPort,
 } from '@/infrastructure/constants/cortex';
-import { FileManagerService } from './infrastructure/services/file-manager/file-manager.service';
+import { getApp } from './app';
 
 async function bootstrap() {
-  const app = await NestFactory.create(AppModule, {
-    snapshot: true,
-    cors: true,
-  });
-
-  const fileService = app.get(FileManagerService);
-  await fileService.getConfig();
-
-  app.useGlobalPipes(
-    new ValidationPipe({
-      transform: true,
-      enableDebugMessages: true,
-    }),
-  );
-
-  const config = new DocumentBuilder()
-    .setTitle('Cortex API')
-    .setDescription(
-      'Cortex API provides a command-line interface (CLI) for seamless interaction with large language models (LLMs). Fully compatible with the [OpenAI API](https://platform.openai.com/docs/api-reference), it enables straightforward command execution and management of LLM interactions.',
-    )
-    .setVersion('1.0')
-    .addTag(
-      'Inference',
-      'This endpoint initiates interaction with a Language Learning Model (LLM).',
-    )
-    .addTag(
-      'Assistants',
-      'These endpoints manage the lifecycle of an Assistant within a conversation thread.',
-    )
-    .addTag(
-      'Models',
-      'These endpoints provide a list and descriptions of all available models within the Cortex framework.',
-    )
-    .addTag(
-      'Messages',
-      'These endpoints manage the retrieval and storage of conversation content, including responses from LLMs and other metadata related to chat interactions.',
-    )
-    .addTag(
-      'Threads',
-      'These endpoints handle the creation, retrieval, updating, and deletion of conversation threads.',
-    )
-    .addTag(
-      'Embeddings',
-      'Endpoint for creating and retrieving embedding vectors from text inputs using specified models.',
-    )
-    .addTag(
-      'Status',
-      "Endpoint for actively querying the health status of the Cortex's API server.",
-    )
-    .addTag(
-      'Processes',
-      'Endpoint for terminating the Cortex API server processes.',
-    )
-    .addTag(
-      'Events',
-      'Endpoints for  observing Cortex statuses through event notifications.',
-    )    
-    .addServer('http://localhost:1337')
-    .addServer('http://localhost:1337/v1')
-    .build();
-  const document = SwaggerModule.createDocument(app, config);
-
-  SwaggerModule.setup('api', app, document);
-
+  const app = await getApp();
   // getting port from env
   const host = process.env.CORTEX_JS_HOST || defaultCortexJsHost;
   const port = process.env.CORTEX_JS_PORT || defaultCortexJsPort;