contaigents/dist/tests/completeWorkflowDemo.js

Modular AI Content Ecosystem with Audio Generation

import { ChatService } from '../services/chatService.js';
import fs from 'fs/promises';
import path from 'path';
// Mock LLM that simulates the complete workflow from your example
class CompleteWorkflowMockLLM {
    constructor() {
        this.step = 0;
    }
    async executePrompt(prompt, _options) {
        console.log(`🤖 Mock LLM Step ${this.step + 1} - Prompt length: ${prompt.length}`);
        if (this.step === 0) {
            // Initial request - agent makes multiple tool calls
            this.step++;
            return {
                content: `I'll help you understand the project setup and update the README accordingly. Based on the provided file structure, I can see some files that might be useful to understand the project setup. I'll start by reading the README, package.json, and src/index.ts files to get a comprehensive understanding of the project. This will help me provide accurate information and update the README accordingly.

<tool_call name="read_file" id="1">
  <file_path>README.md</file_path>
</tool_call>

<tool_call name="read_file" id="2">
  <file_path>package.json</file_path>
</tool_call>

<tool_call name="read_file" id="3">
  <file_path>src/index.ts</file_path>
</tool_call>`
            };
        }
        else if (this.step === 1) {
            // Follow-up after first set of tool calls
            this.step++;
            return {
                content: `I can see the README.md has some reference to other md files, let me read those files to understand the project better.

<tool_call name="read_file" id="4">
  <file_path>content/ai-tools-research.md</file_path>
</tool_call>

<tool_call name="read_file" id="5">
  <file_path>templates/blog-post-template.md</file_path>
</tool_call>`
            };
        }
        else if (this.step === 2) {
            // Final step - update the README
            this.step++;
            return {
                content: `Based on the project files I've analyzed, I can see that the project is a CLI tool for managing content. Let me update the README.md file accordingly.

<tool_call name="write_file" id="6">
  <operation_type>rewrite</operation_type>
  <file_path>README.md</file_path>
  <content><![CDATA[
# Contaigents CLI

This is a CLI tool for managing content. It is built using TypeScript and uses the following dependencies:

## Dependencies
- ts-node: TypeScript execution environment
- typescript: TypeScript compiler

## Getting Started

The main entry point for the CLI is the \`src/index.ts\` file. 

### Running the CLI
\`\`\`bash
npm start
\`\`\`

## Project Structure

The CLI provides the following resources:
- \`content/ai-tools-research.md\`: Research on AI tools
- \`templates/blog-post-template.md\`: Template for writing blog posts

## Features

This CLI tool helps manage content creation and organization with AI-powered assistance.
]]></content>
</tool_call>`
            };
        }
        else {
            // Final response
            return {
                content: `I've updated the README.md file with the information I've gathered from the project files. The README now includes:

- Project description and purpose
- Dependencies information
- Getting started instructions
- Project structure overview
- Available resources and templates

The updated README provides a comprehensive overview of the Contaigents CLI tool and its capabilities. Please let me know if you need any additional information or modifications.`
            };
        }
    }
}
async function demonstrateCompleteWorkflow() {
    console.log('🚀 Complete Workflow Demonstration');
    console.log('='.repeat(60));
    // Create test directory and files
    const testDir = path.join(process.cwd(), 'test-complete-workflow');
    await fs.mkdir(testDir, { recursive: true });
    await fs.mkdir(path.join(testDir, 'src'), { recursive: true });
    await fs.mkdir(path.join(testDir, 'content'), { recursive: true });
    await fs.mkdir(path.join(testDir, 'templates'), { recursive: true });
    // Create test files
    await fs.writeFile(path.join(testDir, 'README.md'), `# Contaigents CLI
This is a CLI tool for managing content.`);
    await fs.writeFile(path.join(testDir, 'package.json'), JSON.stringify({
        "name": "contaigents",
        "version": "1.0.0",
        "description": "CLI tool for managing content",
        "main": "src/index.ts",
        "scripts": {
            "start": "ts-node src/index.ts"
        },
        "dependencies": {
            "ts-node": "^10.9.1",
            "typescript": "^5.2.2"
        }
    }, null, 2));
    await fs.writeFile(path.join(testDir, 'src/index.ts'), `import { ContaigentsCLI } from './contaigents-cli';
const cli = new ContaigentsCLI();
cli.run();`);
    await fs.writeFile(path.join(testDir, 'content/ai-tools-research.md'), `# AI Tools Research
This file contains research on AI tools.`);
    await fs.writeFile(path.join(testDir, 'templates/blog-post-template.md'), `# Blog Post Template
This is a template for writing blog posts.`);
    // Create chat service with mock LLM
    const mockLLM = new CompleteWorkflowMockLLM();
    const chatService = new ChatService(testDir);
    chatService.llmFactory = {
        createLLM: () => mockLLM
    };
    // Create session
    const session = chatService.createSession();
    console.log(`📝 Created chat session: ${session.id}`);
    // Simulate the complete workflow
    console.log('\n👤 User: "learn project setup in detail and update the readme"');
    console.log('\n🤖 Agent Response:');
    console.log('-'.repeat(50));
    const response1 = await chatService.sendMessage(session.id, 'learn project setup in detail and update the readme');
    console.log(response1.content);
    console.log('\n👤 User: (Tool responses provided)');
    console.log('\n🤖 Agent Response:');
    console.log('-'.repeat(50));
    // Simulate user providing tool responses (this would normally be automatic)
    const toolResponsesMessage = `<tool_response id="1">
  <tool_call name="read_file">
    <file_path>README.md</file_path>
  </tool_call>
  <result>
    <content>
      # Contaigents CLI
      This is a CLI tool for managing content.
    </content>
  </result>
</tool_response>

<tool_response id="2">
  <tool_call name="read_file">
    <file_path>package.json</file_path>
  </tool_call>
  <result>
    <content>
      {
        "name": "contaigents",
        "version": "1.0.0",
        "description": "CLI tool for managing content",
        "main": "src/index.ts",
        "scripts": {
          "start": "ts-node src/index.ts"
        },
        "dependencies": {
          "ts-node": "^10.9.1",
          "typescript": "^5.2.2"
        }
      }
    </content>
  </result>
</tool_response>

<tool_response id="3">
  <tool_call name="read_file">
    <file_path>src/index.ts</file_path>
  </tool_call>
  <result>
    <content>
      import { ContaigentsCLI } from './contaigents-cli';
      const cli = new ContaigentsCLI();
      cli.run();
    </content>
  </result>
</tool_response>`;
    const response2 = await chatService.sendMessage(session.id, toolResponsesMessage);
    console.log(response2.content);
    // Continue the workflow...
    console.log('\n👤 User: (Additional tool responses provided)');
    console.log('\n🤖 Agent Response:');
    console.log('-'.repeat(50));
    const additionalToolResponses = `<tool_response id="4">
  <tool_call name="read_file">
    <file_path>content/ai-tools-research.md</file_path>
  </tool_call>
  <result>
    <content>
      # AI Tools Research
      This file contains research on AI tools.
    </content>
  </result>
</tool_response>

<tool_response id="5">
  <tool_call name="read_file">
    <file_path>templates/blog-post-template.md</file_path>
  </tool_call>
  <result>
    <content>
      # Blog Post Template
      This is a template for writing blog posts.
    </content>
  </result>
</tool_response>`;
    const response3 = await chatService.sendMessage(session.id, additionalToolResponses);
    console.log(response3.content);
    // Final update
    console.log('\n👤 User: (Final tool response provided)');
    console.log('\n🤖 Agent Response:');
    console.log('-'.repeat(50));
    const finalToolResponse = `<tool_response id="6">
  <tool_call name="write_file">
    <operation_type>rewrite</operation_type>
    <file_path>README.md</file_path>
    <content><![CDATA[
# Contaigents CLI

This is a CLI tool for managing content. It is built using TypeScript and uses the following dependencies:

## Dependencies
- ts-node: TypeScript execution environment
- typescript: TypeScript compiler

## Getting Started

The main entry point for the CLI is the \`src/index.ts\` file. 

### Running the CLI
\`\`\`bash
npm start
\`\`\`

## Project Structure

The CLI provides the following resources:
- \`content/ai-tools-research.md\`: Research on AI tools
- \`templates/blog-post-template.md\`: Template for writing blog posts

## Features

This CLI tool helps manage content creation and organization with AI-powered assistance.
]]></content>
  </tool_call>
  <result>
    <content>
      README.md updated successfully!
    </content>
  </result>
</tool_response>`;
    const response4 = await chatService.sendMessage(session.id, finalToolResponse);
    console.log(response4.content);
    // Show the updated README
    console.log('\n📄 Updated README.md:');
    console.log('-'.repeat(50));
    const updatedReadme = await fs.readFile(path.join(testDir, 'README.md'), 'utf-8');
    console.log(updatedReadme);
    // Cleanup
    await fs.rm(testDir, { recursive: true });
    console.log('\n🎉 Complete Workflow Demonstration Finished!');
    console.log('\n🎯 Workflow Features Demonstrated:');
    console.log('- ✅ Multi-step tool call sequences');
    console.log('- ✅ XML tool call format with IDs');
    console.log('- ✅ Structured XML tool responses');
    console.log('- ✅ Complex content handling with CDATA');
    console.log('- ✅ File reading and writing operations');
    console.log('- ✅ Conversational flow with tool integration');
}
// Run the demonstration
demonstrateCompleteWorkflow().catch(console.error);