allow multi-file projects

README.md

@@ -7,12 +7,14 @@ The multi-agents are implemented using [Workflows](https://ts.llamaindex.ai/modu
 ## Getting Started
 
 1. Clone the repository:
+
    ```
    git clone https://github.com/run-llama/app-creator.git
    cd app-creator
    ```
 
 2. Install dependencies:
+
    ```
    pnpm install
    ```

agent.ts

@@ -6,13 +6,14 @@ import {
   WorkflowEvent,
 } from "@llamaindex/core/workflow";
 import { OpenAI, Settings } from "llamaindex";
+import { PackageEvent, packager } from "./packager";
 
 const MAX_REVIEWS = 3;
 
 // Create custom event types
 export class MessageEvent extends WorkflowEvent<{ msg: string }> {}
-export class CodeEvent extends WorkflowEvent<{ code: string }> {}
-export class ReviewEvent extends WorkflowEvent<{
+class CodeEvent extends WorkflowEvent<{ code: string }> {}
+class ReviewEvent extends WorkflowEvent<{
   review: string;
   code: string;
 }> {}
@@ -88,7 +89,7 @@ const reviewer = async (context: Context, ev: CodeEvent) => {
         msg: `Reviewer says: ${review}`,
       }),
     );
-    return new StopEvent({ result: code });
+    return new PackageEvent({ code });
   }
 
   return new ReviewEvent({ review, code });
@@ -98,7 +99,10 @@ export function createAgent(model: string): Workflow {
   const codeAgent = new Workflow({ validate: true });
   codeAgent.addStep(StartEvent, architect, { outputs: CodeEvent });
   codeAgent.addStep(ReviewEvent, coder, { outputs: CodeEvent });
-  codeAgent.addStep(CodeEvent, reviewer, { outputs: ReviewEvent });
+  codeAgent.addStep(CodeEvent, reviewer, {
+    outputs: [ReviewEvent, PackageEvent],
+  });
+  codeAgent.addStep(PackageEvent, packager, { outputs: StopEvent });
 
   // Update the llm model with the provided model
   Settings.llm = new OpenAI({ model, temperature: 1 });

main.ts

@@ -1,6 +1,7 @@
 import { createAgent, MessageEvent } from "./agent";
-import * as fs from 'fs/promises';
-import * as path from 'path';
+import * as fs from "fs/promises";
+import * as path from "path";
+import { PackageResult } from "./packager";
 
 const apps = [
   {
@@ -9,22 +10,45 @@ const apps = [
 database where they are mapped to answers. If there is a close match, it retrieves 
 the matched answer. If there isn't, it asks the user to provide an answer and 
 stores the question/answer pair in the database.`,
-    models: ["gpt-4o-mini", "gpt-4o", "o1-mini", "o1-preview"]
+    models: ["gpt-4o-mini", "gpt-4o", "o1-mini", "o1-preview"],
   },
   {
     name: "JavaScript Todo App",
     spec: `Create a full-stack NextJS todo app with a TailwindCSS frontend, that allows users to add, 
 remove, and mark tasks as complete. Use a Postgres database to persist the tasks.`,
-    models: ["gpt-4o-mini", "gpt-4o", "o1-mini"]  // didn't complete with o1-preview
+    models: ["gpt-4o-mini", "gpt-4o", "o1-mini"], // didn't complete with o1-preview
   },
   {
     name: "Iphone calculator",
     spec: `Iphone style scientific calculator in one html file, using tailwind css and javascript.`,
-    models: ["gpt-4o-mini", "gpt-4o", "o1-mini", "o1-preview"]  
-  }
+    models: ["gpt-4o-mini", "gpt-4o", "o1-mini", "o1-preview"],
+  },
   // Add more specifications as needed
 ];
 
+async function outputResult(
+  name: string,
+  model: string,
+  packageResult: PackageResult,
+) {
+  // Create output directory if it doesn't exist
+  const outputDir = path.join("output", name, model);
+  await fs.mkdir(outputDir, { recursive: true });
+
+  // Iterate over all files in the packageResult and store each file with their correct path
+  for (const file of packageResult.files) {
+    const filePath = path.join(outputDir, file.path);
+    const fileDir = path.dirname(filePath);
+
+    // Create directory if it doesn't exist
+    await fs.mkdir(fileDir, { recursive: true });
+
+    // Write file content
+    await fs.writeFile(filePath, file.content);
+    console.log(`File written to: ${filePath}`);
+  }
+}
+
 async function runGeneration(name: string, spec: string, model: string) {
   console.log(`Running generation with model: ${model}`);
   const codeAgent = createAgent(model);
@@ -34,15 +58,9 @@ async function runGeneration(name: string, spec: string, model: string) {
     console.log(`${msg}\n`);
   }
   const result = await run;
-  
-  // Create output directory if it doesn't exist
-  const outputDir = path.join('output', name);
-  await fs.mkdir(outputDir, { recursive: true });
-  
-  // Write the generated code to a file
-  const outputFile = path.join(outputDir, `${model}.code`);
-  await fs.writeFile(outputFile, result.data.result);
-  console.log(`Generated code written to: ${outputFile}\n`);
+  const packageResult = result.data.result as unknown as PackageResult;
+
+  await outputResult(name, model, packageResult);
 }
 
 async function main() {

package.json

@@ -13,10 +13,12 @@
   "license": "ISC",
   "dependencies": {
     "@llamaindex/core": "^0.2.0",
-    "llamaindex": "^0.6.0"
+    "llamaindex": "^0.6.0",
+    "zod": "^3.23.8",
+    "zod-to-json-schema": "^3.23.3"
   },
   "devDependencies": {
     "prettier": "^3.3.3",
     "tsx": "^4.19.1"
   }
-}
+}

packager.ts

@@ -0,0 +1,50 @@
+import { zodToJsonSchema } from "zod-to-json-schema";
+import { Context, StopEvent, WorkflowEvent } from "@llamaindex/core/workflow";
+import { OpenAI } from "llamaindex";
+import { z } from "zod";
+
+export class PackageEvent extends WorkflowEvent<{
+  code: string;
+}> {}
+
+const FileSchema = z.object({
+  path: z.string().describe("Path to the filename, e.g., 'app/main.py'"),
+  content: z.string().describe("Complete content of the file"),
+});
+
+const PackageResultSchema = z.object({
+  files: z.array(FileSchema),
+});
+
+export type PackageResult = z.infer<typeof PackageResultSchema>;
+
+export const packager = async (context: Context, ev: PackageEvent) => {
+  const { code } = ev.data;
+
+  // use own llm for extracting the files
+  const llm = new OpenAI({
+    model: "gpt-4o-mini",
+    additionalChatOptions: { response_format: { type: "json_object" } },
+  });
+
+  const schema = JSON.stringify(zodToJsonSchema(PackageResultSchema));
+
+  const response = await llm.chat({
+    messages: [
+      {
+        role: "system",
+        content: `You are an expert in extracting single files (path and content) from one large string.\n\nGenerate a valid JSON following the given schema below:\n\n${schema}`,
+      },
+      {
+        role: "user",
+        content: `Here is the large string: \n------\n${code}\n------`,
+      },
+    ],
+  });
+
+  const json = response.message.content as string;
+  const result = PackageResultSchema.parse(JSON.parse(json));
+
+  // TODO: allow different types of outputs in LlamaIndexTS
+  return new StopEvent({ result: result as unknown as string });
+};

pnpm-lock.yaml

@@ -13,6 +13,12 @@ importers:
       llamaindex:
         specifier: ^0.6.0
         version: 0.6.0(@aws-sdk/client-sso-oidc@3.650.0(@aws-sdk/client-sts@3.650.0))(@aws-sdk/credential-providers@3.650.0(@aws-sdk/client-sso-oidc@3.650.0(@aws-sdk/client-sts@3.650.0)))(@notionhq/client@2.2.15(encoding@0.1.13))(encoding@0.1.13)(typescript@5.6.2)
+      zod:
+        specifier: ^3.23.8
+        version: 3.23.8
+      zod-to-json-schema:
+        specifier: ^3.23.3
+        version: 3.23.3(zod@3.23.8)
     devDependencies:
       prettier:
         specifier: ^3.3.3
@@ -3738,6 +3744,14 @@ packages:
       }
     engines: { node: ">=12" }
 
+  zod-to-json-schema@3.23.3:
+    resolution:
+      {
+        integrity: sha512-TYWChTxKQbRJp5ST22o/Irt9KC5nj7CdBKYB/AosCRdj/wxEMvv4NNaj9XVUHDOIp53ZxArGhnw5HMZziPFjog==,
+      }
+    peerDependencies:
+      zod: ^3.23.3
+
   zod@3.23.8:
     resolution:
       {
@@ -6532,4 +6546,8 @@ snapshots:
       y18n: 5.0.8
       yargs-parser: 21.1.1
 
+  zod-to-json-schema@3.23.3(zod@3.23.8):
+    dependencies:
+      zod: 3.23.8
+
   zod@3.23.8: {}