AI-Driven Network Emulation Agent Project
This project is an AI-driven network emulation agent designed to mimic real network device behavior using LangChain and LangGraph.
Core Components
1. Responder Agent
- Functionality:
- Processes user queries such as:
- CLI Command:
show interfaces - API Request:
GET /restconf/data/ietf-interfaces:interfaces
- CLI Command:
- Provides realistic outputs in:
- CLI Format
- JSON (API Response)
- Processes user queries such as:
2. State Agent
- Purpose:
- Tracks the emulator’s state to ensure that responses accurately reflect configuration changes.
3. Execution Interfaces
- SSH Server:
- Enables users to execute Ansible playbooks on the emulator.
- REST API Server:
- Supports executing Python or Terraform via RESTCONF for network automation.
Challenges Faced
- State Accuracy:
- Keeping responses consistent with real-time configuration changes remains complex.
- Realistic Response Timing:
- Simulating real device processing delays accurately is a significant challenge.
- Precision in CLI & API Responses:
- Achieving outputs that authentically mimic real network devices is still a work in progress.
- RAG & Prompt Engineering:
- Numerous attempts have been made to fix retrieval-augmented generation issues, yet inconsistencies persist.
Open Questions
- Can AI truly emulate real device performance?
- How reliably can AI handle real-time state changes compared to physical hardware?
- Will the response timings ever perfectly match those of actual devices under load?
- To what extent can AI-generated outputs mimic vendor-specific behavior?
Collaboration Opportunity
This is an ongoing experiment, and there’s still much to improve. If you’re interested in AI, network automation, or LLM-based emulation, I’d love to hear from you. Contributions, feedback, and collaborative ideas are highly welcome!
Let’s work together to push the boundaries of network emulation! ![]()
Feel free to reach out or share your thoughts. Your ideas and contributions are welcome!