Agent Core Update - Add Chat Node config and Web Cli Docker

[Xm0onh]

Summary

This PR updates the agent-core dependency to version 0.3.1 and introduces several architectural improvements to the codebase, including a new Web CLI Docker container for interacting with agents.

Changes

Dependency Updates

• Upgraded @autonomys/agent-core from v0.2.4 to v0.3.1

New Features

• Added Docker Web CLI container support with detailed documentation
• Implemented chat workflow functionality via new chatNode.ts module
• Improved API configuration and server handling

Architecture Improvements

• Refactored orchestrator configuration logic
• Separated API configuration into dedicated module
• Enhanced Twitter tool integration with API config support

Documentation Updates

• Added documentation for running Web CLI with Docker
• Updated container configuration instructions

Implementation Details

API Configuration

• Created dedicated configuration modules in src/config/:
  • api.ts: Centralized API server configuration
  • chatNode.ts: Chat workflow implementation

Orchestrator Changes

• Simplified orchestrator configuration
• Removed direct LLM configuration in favor of model-specific configurations
• Enhanced API integration with orchestrator

Startup Process

• Modified startup sequence to initialize API server independently
• Improved error handling and configuration validation

Testing Instructions

1. Update dependencies with yarn install
2. Test the agent startup with yarn start <character_name>
3. Verify API functionality is working correctly
4. Test the Docker Web CLI container using instructions in README

[jfrank-summit]

Looks good!

[autojeremy]

Pull Request Review: Agent Core Update and Configuration Improvements

🔍 Code Review Observations

Dependency Upgrade

• ✅ Successfully upgraded @autonomys/agent-core from v0.2.4 to v0.3.1
• Note: Dependency update includes additional integrations like @langchain/deepseek

Architecture Improvements

1. API Configuration (src/config/api.ts)

   • 👍 Centralized API configuration logic
   • 👍 Separated concerns with dedicated configuration methods
   • 💡 Recommendation: Consider adding input validation for API configuration parameters

2. Chat Node Implementation (src/config/chatNode.ts)

   • ✅ Implemented flexible chat workflow configuration
   • 👍 Used default tools and prompt template generation
   • 💡 Suggestion: Make model configuration more configurable, potentially through environment variables

3. Orchestrator Refactoring (src/orchestrator.ts)

   • ✅ Simplified configuration logic
   • 👍 Removed redundant API creation code
   • 💡 Consider adding more detailed logging during orchestrator initialization

Docker and Web CLI

• ✅ Added clear Docker Web CLI instructions in README.md
• 👍 Provided example with environment variable configuration
• 💡 Recommendation: Include a sample .env file or configuration template

🚀 Overall Assessment

• The changes demonstrate a clean, modular approach to agent configuration
• Improved separation of concerns
• Enhanced flexibility in API and chat node setup

🔧 Suggested Improvements

1. Add more comprehensive error handling in configuration modules
2. Consider making more configuration parameters environment-variable driven
3. Add unit tests for the new configuration modules

✅ Approval Status

• The code meets the architectural goals
• Demonstrates thoughtful refactoring
• Recommended for merge after addressing minor suggestions

Would you like me to elaborate on any specific aspect of the review?

[autojeremy]

Hey @Xm0onh 👋

Great work on this PR! The modular configuration approach and clean refactoring are impressive. The suggestions in the review are meant to further enhance the robustness of the code.

A few quick thoughts from a systems optimization perspective:

• The new configuration modules demonstrate a philosophy of separation of concerns, which I appreciate
• The Web CLI Docker integration is a nice touch for improving agent accessibility
• The dependency upgrade brings in some interesting new capabilities, especially with @langchain/deepseek integration

Would be great to see a follow-up implementation of some of the suggested improvements, particularly around more dynamic configuration and error handling.

Cheers! 🚀

[jfrank-summit]

LGTM!