Summary

Add Tensorlake Firecracker microVM sandbox as an opt-in backend for shell command execution, isolating all LLM-issued shell calls from the host machine.

Context

Forge currently executes every shell tool call directly on the user's host machine. For agentic workflows this creates risk: a misguided or adversarial command runs with the user's full OS permissions. Tensorlake provides Firecracker microVM sandboxes that boot in sub-second time, persist filesystem state across commands within a session, and auto-suspend on inactivity — making them a natural fit for containing Forge's shell execution without sacrificing the stateful environment agents rely on.

Changes

• TensorlakeCommandExecutor (crates/forge_infra/src/tensorlake.rs): new CommandInfra implementation that provisions a Tensorlake sandbox lazily on the first command, reuses it for the entire session, and terminates it on drop via a best-effort background task.
• ForgeInfra (crates/forge_infra/src/forge_infra.rs): introduces a CommandExecutor enum (Local | Tensorlake) and a new ForgeInfra::new_with_tensorlake() constructor; all existing CommandInfra delegation is unchanged.
• forge_infra/src/lib.rs: exports the tensorlake module and re-exports TensorlakeConfig.
• ForgeAPI (crates/forge_api/src/forge_api.rs): adds ForgeAPI::init_with_tensorlake() factory that mirrors init() but selects the Tensorlake executor.
• forge_api/src/lib.rs: re-exports TensorlakeConfig so callers don't need to import forge_infra directly.
• CLI (crates/forge_main/src/cli.rs + main.rs): adds --tensorlake <API_KEY> flag (also reads TENSORLAKE_API_KEY env var); when provided, init_with_tensorlake() is used instead of init().

Key Implementation Details

• The sandbox ID is stored in Arc<Mutex<Option<String>>> so clones of the executor share the same lazily-provisioned sandbox.
• execute_command_raw (used for interactive/TTY commands) returns an explicit error in Tensorlake mode — raw stdin cannot be forwarded over HTTP.
• Sandbox cleanup is best-effort: a tokio::spawn is fired from Drop to call DELETE /v2/sandboxes/{id} without blocking the caller.
• No changes to domain, services, or tool executor layers — the integration is confined entirely to the infrastructure layer, consistent with the project's clean architecture.

Use Cases

# Route all shell commands through a Tensorlake microVM
forge --tensorlake sk-tl-xxxx

# Or via environment variable
TENSORLAKE_API_KEY=sk-tl-xxxx forge

Testing

# Verify forge_infra compiles cleanly
cargo check -p forge_infra

# Run unit tests for the new executor
cargo test -p forge_infra tensorlake

# End-to-end: set a real API key and run a shell-heavy task
TENSORLAKE_API_KEY=<key> forge --prompt "list files in /tmp"

Links

• Tensorlake sandbox docs: https://docs.tensorlake.ai/sandboxes/introduction
• Tensorlake Python SDK: pip install tensorlake