Check for existing issues
The Feature
Add support for the Command Code API (https://api.commandcode.ai) as a LiteLLM provider.
Command Code currently exposes a custom streaming API at:
POST https://api.commandcode.ai/alpha/generate
The API is not OpenAI-compatible today, but it appears stable and externally callable with:
- bearer authentication
- versioned headers
- streaming event responses
- tool call events
- reasoning deltas
A provider adapter in LiteLLM would allow Command Code models to be exposed through the standard OpenAI-compatible LiteLLM proxy surface (/v1/chat/completions).
This would make Command Code usable with:
- Hermes
- OpenCode
- Cline
- OpenAI-compatible coding agents/tools
- existing LiteLLM routing/load-balancing infrastructure
Known integration details discovered during testing:
Required endpoint
https://api.commandcode.ai/alpha/generate
Required headers
Authorization: Bearer <API_KEY>
Content-Type: application/json
x-command-code-version: 0.24.1
Required payload structure
{
"config": {
"workingDir": "/tmp",
"date": "2026-05-10",
"environment": "terminal",
"structure": [],
"isGitRepo": false,
"currentBranch": "",
"mainBranch": "",
"gitStatus": "",
"recentCommits": []
},
"memory": "",
"taste": "",
"skills": null,
"permissionMode": "standard",
"params": {
"model": "deepseek/deepseek-v4-flash",
"messages": [
{
"role": "user",
"content": "hello"
}
],
"tools": [],
"system": "",
"max_tokens": 100,
"stream": true
}
}
Observed stream event types
text-delta
reasoning-delta
tool-call
finish
error
There is already an existing unofficial provider implementation for the Pi agent ecosystem:
The implementation there may help accelerate provider support and stream translation logic.
Motivation, pitch
LiteLLM is already the de-facto interoperability layer for LLM tooling.
Command Code is gaining visibility in coding-agent communities because it aggregates several open-source coding models behind a single API with aggressive pricing/subscription packaging.
However, because the API is not OpenAI-compatible, it currently cannot be used directly with most OpenAI-compatible coding agents and developer tooling.
A native LiteLLM provider would:
- make Command Code immediately usable across existing OpenAI-compatible ecosystems
- reduce the need for ad-hoc proxy wrappers
- improve compatibility with coding agents that already integrate with LiteLLM
- provide another routing option for users optimizing for cost-sensitive coding workloads
What part of LiteLLM is this about?
Proxy
LiteLLM is hiring a founding backend engineer, are you interested in joining us and shipping to all our users?
Yes
Twitter / LinkedIn details
https://x.com/JoyBoy_Ash
https://www.linkedin.com/in/arsh-tulshyan/
Check for existing issues
The Feature
Add support for the Command Code API (https://api.commandcode.ai) as a LiteLLM provider.
Command Code currently exposes a custom streaming API at:
The API is not OpenAI-compatible today, but it appears stable and externally callable with:
A provider adapter in LiteLLM would allow Command Code models to be exposed through the standard OpenAI-compatible LiteLLM proxy surface (/v1/chat/completions).
This would make Command Code usable with:
Known integration details discovered during testing:
Required endpoint
Required headers
Required payload structure
Observed stream event types
There is already an existing unofficial provider implementation for the Pi agent ecosystem:
The implementation there may help accelerate provider support and stream translation logic.
Motivation, pitch
LiteLLM is already the de-facto interoperability layer for LLM tooling.
Command Code is gaining visibility in coding-agent communities because it aggregates several open-source coding models behind a single API with aggressive pricing/subscription packaging.
However, because the API is not OpenAI-compatible, it currently cannot be used directly with most OpenAI-compatible coding agents and developer tooling.
A native LiteLLM provider would:
What part of LiteLLM is this about?
Proxy
LiteLLM is hiring a founding backend engineer, are you interested in joining us and shipping to all our users?
Yes
Twitter / LinkedIn details
https://x.com/JoyBoy_Ash
https://www.linkedin.com/in/arsh-tulshyan/