What problem or use case are you trying to solve?
The goal is to enable and optimize the Multi-Agent System (MAS) in OpenHands for effective task distribution among agents such as Delegator Agent, Browsing Agent, and CodeAct Agent. This includes ensuring seamless collaboration, resource optimization, and minimizing execution costs using features like Batch API. Additionally, it should provide better system monitoring and diagnostics.
Describe the UX of the solution you'd like:
Dashboard Enhancements:
Add a visual indicator for active agents and their roles.
Display task distribution between agents in real-time.
Include an overview of system performance (e.g., CPU, memory usage, token consumption).
Batch API Integration:
Automatically detect and group similar tasks for batch execution.
Provide insights into batch task usage and token savings.
Version and Update Monitoring:
Display the current OpenHands version in the interface.
Provide an automatic update feature or notifications for new releases.
Token Consumption Statistics:
A breakdown of token usage for each agent.
A graph or counter tracking token consumption from a predefined limit (e.g., 1 million tokens).
Diagnostics Panel:
Real-time diagnostics for agent status (active, idle, error states).
Provide clear error messages and suggestions for resolution.
Do you have thoughts on the technical implementation?
Agent System:
Ensure proper coordination between agents with an internal task queue.
Enhance agent APIs to handle task delegation and completion feedback efficiently.
Batch API:
Introduce logic to detect identical or related tasks and group them for batch processing.
Use API features like OpenAI’s batching or Anthropic’s batch handling for cost-effective task execution.
Dashboard and Metrics:
Leverage a frontend framework (React/TypeScript) to add real-time visualizations.
Integrate with backend logging for agent monitoring and diagnostics.
Describe alternatives you've considered:
Manual execution of agents and tasks via CLI or API, which lacks seamless coordination and visual feedback.
Using third-party tools for diagnostics and monitoring, which may complicate system integration and increase operational overhead.
Additional context
Environment Details:
macOS Ventura, Docker 24.0.1, Python 3.12.
Latest OpenHands version synced from main branch.
Suggested Improvements:
Support secure, persistent storage of API keys (e.g., OpenAI, Anthropic) with encryption.
Integrate caching mechanisms like Redis for faster performance.
Add testing tools to validate the MAS functionality and Batch API efficiency.
Thank you for considering this request! I look forward to your feedback and guidance on implementing these features to enhance OpenHands.
What problem or use case are you trying to solve? The goal is to enable and optimize the Multi-Agent System (MAS) in OpenHands for effective task distribution among agents such as Delegator Agent, Browsing Agent, and CodeAct Agent. This includes ensuring seamless collaboration, resource optimization, and minimizing execution costs using features like Batch API. Additionally, it should provide better system monitoring and diagnostics.
Describe the UX of the solution you'd like: Dashboard Enhancements: Add a visual indicator for active agents and their roles. Display task distribution between agents in real-time. Include an overview of system performance (e.g., CPU, memory usage, token consumption). Batch API Integration: Automatically detect and group similar tasks for batch execution. Provide insights into batch task usage and token savings. Version and Update Monitoring: Display the current OpenHands version in the interface. Provide an automatic update feature or notifications for new releases. Token Consumption Statistics: A breakdown of token usage for each agent. A graph or counter tracking token consumption from a predefined limit (e.g., 1 million tokens). Diagnostics Panel: Real-time diagnostics for agent status (active, idle, error states). Provide clear error messages and suggestions for resolution. Do you have thoughts on the technical implementation? Agent System: Ensure proper coordination between agents with an internal task queue. Enhance agent APIs to handle task delegation and completion feedback efficiently. Batch API: Introduce logic to detect identical or related tasks and group them for batch processing. Use API features like OpenAI’s batching or Anthropic’s batch handling for cost-effective task execution. Dashboard and Metrics: Leverage a frontend framework (React/TypeScript) to add real-time visualizations. Integrate with backend logging for agent monitoring and diagnostics. Describe alternatives you've considered: Manual execution of agents and tasks via CLI or API, which lacks seamless coordination and visual feedback. Using third-party tools for diagnostics and monitoring, which may complicate system integration and increase operational overhead. Additional context Environment Details:
macOS Ventura, Docker 24.0.1, Python 3.12. Latest OpenHands version synced from main branch. Suggested Improvements:
Support secure, persistent storage of API keys (e.g., OpenAI, Anthropic) with encryption. Integrate caching mechanisms like Redis for faster performance. Add testing tools to validate the MAS functionality and Batch API efficiency. Thank you for considering this request! I look forward to your feedback and guidance on implementing these features to enhance OpenHands.