mantis-configure

# Pipeline Configurator (/mantis-configure) ## System Goal Environment and Model Configurator. Configures `workflow.json` with appropriate sandbox execution mechanisms, AI model providers, API endpoints, and credential bindings. Provides instantaneous preflight verification to guarantee that LLM credentials and sandbox isolation requirements are fully operational before launching security review campaigns. ## Command Definition - **Command:** `/mantis-configure` - **Description:** Configures Mantis pipeline settings (sandboxes, models, credentials, preflight validation) in `workflow.json`. - **Execution Command:** ```bash python3 "${MANTIS_HOME:-/path/to/mantis}/reference/scripts/configure.py" [flags...] ``` **Path Anchoring Requirement (CRITICAL)**: The configuration script resides within the Mantis installation directory at `reference/scripts/configure.py`. **You MUST invoke this script via an absolute path or via `$MANTIS_HOME`**. NEVER execute `python3 reference/scripts/configure.py` using a relative path inside audited target repositories. - **CLI Options:** - `--sandbox` / `-s`: Sandbox mechanism (`static-only`, `gvisor`, `microsandbox`, `gce`). - `--model` / `-m`: Default LLM model (e.g. `gemini-3.7-flash`, `vertex_ai/claude-opus-5`, `vertex_ai/zai_org/glm-5.2-maas`, `openai/{MODEL_ID}`). - `--api-base`: Custom endpoint URL for OpenAI-compatible LLM servers (e.g. `http://localhost:8000/v1`). - `--reasoning-effort`: Reasoning effort level (`low`, `medium`, `high`). - `--timeout`: LLM request timeout in seconds. - `--project` / `-p`: GCP Project ID (for GCE sandbox or Vertex AI routing). - `--zone` / `-z`: GCP Zone (e.g. `us-central1-b`). - `--image` / `-i`: Sandbox image name (e.g. `mantis-sandbox-image` or `mantis-sandbox:latest`). - `--subnet`: GCE Subnet name (e.g. `mantis-isolated-subnet`). - `--workdir`: Sandbox guest workdir (default: `/workspace`). - `--workflow` / `-w`: Path to `workflow.json` (defaults to auto-discovery). - `--db` / `-d`: Path to SQLite knowledge database (default: `knowledge.db`). - `--auto`: Auto-detects host capabilities and configures optimal settings automatically. - `--save`: Explicitly saves configuration changes to `workflow.local.json`. - `--save-tracked` / `--global`: Saves configuration changes directly to base `workflow.json`. - `--interactive`: Interactive step-by-step terminal wizard. - `--test` / `--preflight`: Executes fast (1-2s) static validation tests verifying LLM configuration format and sandbox readiness. - `--probe` / `--probe-llm`: Actively probes LLM reachability, provider credentials, and client dependencies with a minimal test prompt (`test`, max 256 tokens). - `--show`: Displays current configuration and diagnostic status. - `--dry-run`: Simulates configuration changes without modifying files. - `--update-nodes`: Updates all agent nodes in `workflow.json` to use the specified default model. - `--json`: Outputs configuration status and preflight diagnostics in JSON. ## Supported Sandbox Mechanisms | Sandbox | Description | Isolation Level | Requirements | | :------------- | :---------------------------------------------------------------- | :----------------------- | :------------------------------------------- | | `static-only` | Static analysis only; reproducer and dynamic patching disabled. | Zero Host Risk | None (Always available) | | `gvisor` | Networkless OCI container executed under Google gVisor (`runsc`). | Process & Kernel sandbox | `docker` or `podman` with `runsc` registered | | `microsandbox` | Ephemeral Linux microVM with hardware virtualization. | Virtual Machine | `/dev/kvm` read/write access | | `gce` | Hardened ephemeral Google Compute Engine VM via IAP SSH tunnel. | Cloud Hypervisor | `gcloud` CLI, active GCP auth & project | ## Supported Model Providers 1. **Gemini Models (Google / Vertex AI)**: - `gemini-3.7-flash`, `gemini-3.5-flash-lite` - `vertex_ai/gemini-3.7-flash`, `vertex_ai/gemini-3.5-flash-lite` 2. **Claude Models (Vertex AI Model Garden)**: - `vertex_ai/claude-opus-5` 3. **MaaS & Open Source Models (Vertex Model Garden)**: - `vertex_ai/zai_org/glm-5.2-maas` 4. **Custom OpenAI-Compatible Endpoints**: - `openai/{MODEL_ID}` or `vertex_ai/openai/{MODEL_ID}` - Supports custom `--api-base` (e.g. vLLM, Ollama, LiteLLM proxy), `--reasoning-effort`, and `--timeout`. ## Common CLI Workflows ### 1. Fast Preflight Verification (~1s) & Active Reachability Probe Check if LLM configuration and sandbox requirements are operational: ```bash # Fast static validation (~1s): python3 "$MANTIS_HOME/reference/scripts/configure.py" --test # Active live reachability probe against LLM provider: python3 "$MANTIS_HOME/reference/scripts/configure.py" --test --probe ``` ### 2. Auto-Detect and Configure Automatically inspect host capabilities (`/dev/kvm`, `docker/runsc`, `gcloud`) and select the best available sandbox: ```bash python3 "$MANTIS_HOME/reference/scripts/configure.py" --auto ``` ### 3. Switch to Static Analysis (Zero Dependencies) ```bash python3 "$MANTIS_HOME/reference/scripts/configure.py" --sandbox static-only ``` ### 4. Configure gVisor Container Sandbox ```bash python3 "$MANTIS_HOME/reference/scripts/configure.py" --sandbox gvisor --image mantis-sandbox:latest ``` ### 5. Configure GCE Ephemeral Cloud Sandbox ```bash python3 "$MANTIS_HOME/reference/scripts/configure.py" --sandbox gce --project my-gcp-project --zone us-central1-b ``` ### 6. Switch AI Model to Claude or Custom Endpoint ```bash # Vertex AI Claude python3 "$MANTIS_HOME/reference/scripts/configure.py" --model vertex_ai/claude-opus-5 # Custom Local vLLM / OpenAI server python3 "$MANTIS_HOME/reference/scripts/configure.py" --model openai/my-model --api-base http://localhost:8000/v1 ``` ### 7. Interactive Configuration Wizard ```bash python3 "$MANTIS_HOME/reference/scripts/configure.py" --interactive ``` ## Python API Reference When invoked programmatically from Python: ```python from scripts.configure import ( detect_capabilities, ensure_configured, ensure_configured_async, is_default_or_unconfigured, run_preflight_checks, run_preflight_checks_async, update_workflow_config, ) # 1. Check if configuration contains default placeholders is_unconf, issues = is_default_or_unconfigured(config) # 2. Run fast preflight checks (sync or async) ok, messages = run_preflight_checks(config, test_llm=True, test_sandbox=True) # or: ok, messages = await run_preflight_checks_async(config) # 3. Ensure configured (auto-resolves defaults if unconfigured) valid_config = ensure_configured(auto=True) # or: valid_config = await ensure_configured_async(auto=True) ``` ## Input/Output Contract - **Reads**: - `workflow.json` and optional `workflow.local.json` overlay - Host environment (virtualization devices, container engines, cloud CLI credentials) - **Writes**: - `workflow.local.json` (or `workflow.json` when `--save-tracked` is set)