Codex CLI is OpenAI’s open-source agentic coding assistant that runs in your terminal. It can read files, write code, run commands, and iterate on its work using the Responses API.
Requires Responses API - Codex CLI uses the /v1/responses endpoint which Infercom supports with MiniMax-M2.7.
Prerequisites
Installation
npm install -g @openai/codex
macOS users: If macOS blocks the binary as “malware”, go to System Preferences > Security & Privacy and click “Allow Anyway”, or run:xattr -d com.apple.quarantine $(which codex)
Configuration
Codex CLI supports custom providers via a TOML configuration file.
Step 1: Set Environment Variable
export INFERCOM_API_KEY="your-infercom-api-key"
Add this to your shell profile (~/.bashrc, ~/.zshrc) for persistence.
Step 2: Create Config File
Create ~/.codex/config.toml:
# Define Infercom as a provider
[model_providers.infercom]
name = "Infercom (EU Sovereign)"
base_url = "https://api.infercom.ai/v1"
env_key = "INFERCOM_API_KEY"
wire_api = "responses"
# Default profile using MiniMax-M2.7
model_provider = "infercom"
model = "MiniMax-M2.7"
For complex tasks requiring deeper reasoning, Codex CLI supports profiles with different models. You can use a frontier model (Claude, GPT, Gemini) for planning and MiniMax-M2.7 for execution. See Codex documentation for profile configuration. Step 3: Verify Setup
Run Codex in any project directory:
You should see Codex start with:
model: MiniMax-M2.7
provider: infercom
Model
Use MiniMax-M2.7 - optimized for agentic coding with 192K context and built-in reasoning.
Usage
Interactive Mode
Start Codex in your project directory:
Type your request and Codex will:
- Read relevant files
- Write or edit code
- Run terminal commands
- Iterate until the task is complete
Example Tasks
- “Add error handling to the login function”
- “Write unit tests for the User class”
- “Refactor this file to use async/await”
- “Find and fix the bug causing the test to fail”
Non-Interactive Mode
For scripted or one-shot use, use the exec subcommand:
codex exec "Add input validation to auth.py"
Configuration Options
Full ~/.codex/config.toml reference:
# Default model to use
model = "MiniMax-M2.7"
# Provider to use
model_provider = "infercom"
# Approval mode: "suggest" (default), "auto-edit", or "full-auto"
approval_mode = "suggest"
# Sandbox mode for command execution
sandbox = "docker" # or "none" to disable
[model_providers.infercom]
name = "Infercom (EU Sovereign)"
base_url = "https://api.infercom.ai/v1"
env_key = "INFERCOM_API_KEY"
wire_api = "responses"
Approval Modes
| Mode | Behavior |
|---|
suggest | Shows diffs and asks before applying (default) |
auto-edit | Automatically applies file changes, asks for commands |
full-auto | Automatically applies all changes |
Troubleshooting
Connection Errors
Verify your configuration:
# Check API key is set
echo $INFERCOM_API_KEY
# Test API directly
curl -s https://api.infercom.ai/v1/responses \
-H "Authorization: Bearer $INFERCOM_API_KEY" \
-H "Content-Type: application/json" \
-d '{"model":"MiniMax-M2.7","input":"Hello"}' | jq .status
"completed"
Model Not Found
Ensure the model name is exact (case-sensitive): MiniMax-M2.7
Slow Responses
MiniMax-M2.7 runs at 400+ tokens/sec. If responses seem slow:
- Check your network connection
- Large context (many files) increases processing time
- First request may be slower due to model loading
Why Codex CLI with Infercom?
| Feature | Benefit |
|---|
| EU Sovereign | Data processed in Germany, GDPR compliant |
| Responses API | Native support for Codex’s agentic architecture |
| Fast inference | 400+ tokens/sec with MiniMax-M2.7 |
| No vendor lock-in | Open-source tool, standard API |
Next Steps
- Aider - Alternative terminal-based tool
- OpenCode - Modern TUI with similar features
- Responses API - API documentation for custom integrations
