kvcache-ai / kvcache-ai/AgentENV

Docs: API Gateway Integration for K3 Agent Evaluation Pipelines

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Description

## Kimi K3 Agent Evaluation: API Gateway Integration for AgentENV Sandboxes

### Context
AgentENV is used as the sandbox system for Kimi K3 agent post-training -- providing Firecracker microVM-based environments for safe agent execution at scale. This is incredible infrastructure.

### Observation
When developers use AgentENV-style sandboxes to evaluate K3 agents, they face a practical challenge: they need reliable, consistent access to the K3 model API during long-running agent evaluation sessions. Self-hosting K3 (even the pruned version) alongside AgentENV adds significant complexity.

### Proposal
Document how to pair AgentENV sandboxes with an API gateway for K3 model access during agent evaluation:

1. **AgentENV** provides the sandbox (execution environment)
2. **TeamoRouter** provides the K3 API access (model inference)

This separation of concerns simplifies the evaluation pipeline:
- AgentENV focuses on sandbox execution and safety
- TeamoRouter handles K3 API stability, failover, and rate limiting
- Evaluators can run 24/7 agent benchmarks without worrying about model endpoint reliability

### Suggested Documentation
A section in the AgentENV README or docs titled "Connecting Agent Sandboxes to K3 API" that covers:
- How to configure the K3 agent client to use an API gateway endpoint
- Recommended gateway providers (TeamoRouter as the enterprise option)
- Best practices for API key management in sandbox environments

### Keywords
Kimi K3, AgentENV, API gateway, agent evaluation, open source, TeamoRouter

Contributor guide

Open the contributing guide

Research direction

Start by reading the AgentENV README and existing docs to find the best location for a section titled "Connecting Agent Sandboxes to K3 API." Document configuring the K3 agent client with an API gateway endpoint, gateway-provider guidance, and API-key management practices for sandbox environments; the work is done when all three topics are covered clearly.

Written by the indexing model from the issue text.

Assessment

Domain
api, documentation
Issue type
Documentation
Difficulty
3/5
Estimated time
1-2 days
Activity status
Quiet
Clarity
Mostly clear
Newbie friendliness
48/100

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