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!