Quick Start in 10 Minutes
Follow this path to get ACM v0.5.0 running locally and execute your first deterministic workflow.
1. Clone and install
# Clone the repository
git clone https://github.com/ddse-foundation/acm.git
cd acm/framework/node
# Install dependencies and build all packages
pnpm install
pnpm build
Tip — Use
pnpm --filter <package> <command>when iterating on a single package. The full build compiles every workspace package.
2. Start an LLM endpoint
ACM expects an OpenAI-compatible endpoint. The team validates releases against vLLM running Qwen/Qwen3-Coder-30B-A3B-Instruct-FP8.
pip install "vllm>=0.5"
python -m vllm.entrypoints.openai.api_server \
--model Qwen/Qwen3-Coder-30B-A3B-Instruct-FP8 \
--port 8001
Verify the server is ready:
curl http://localhost:8001/v1/models
Other providers — Bring any OpenAI-compatible endpoint (OpenAI, Ollama, Azure OpenAI). Adjust
--provider,--model, and--base-urlin the CLI.
3. Run the deterministic demos
# Refund workflow with vLLM
pnpm --filter @ddse/acm-examples demo -- \
--provider vllm \
--model Qwen/Qwen3-Coder-30B-A3B-Instruct-FP8 \
--base-url http://localhost:8001/v1 \
--scenario refunds
# Incident triage with checkpoints and replay export
pnpm --filter @ddse/acm-examples demo -- \
--scenario incidents \
--checkpoint-dir ./checkpoints \
--save-bundle
What you will see:
- Planning — Tool-call reasoning and Plan-A/Plan-B alternatives.
- Execution — Task progress with guard evaluation and policy hooks.
- Summary — Ledger counts, checkpoint paths, replay bundle locations.
4. Inspect replay bundles
ls checkpoints
cat checkpoints/run-*/ledger.json
Replay bundles contain:
- Planner output (plans + rationale)
- Selected plan and alternatives
- Ledger entries (task starts, guard evaluations, policies, verification)
- Tool-call envelopes and streaming transcripts
5. Author your first agent
Use the SDK and runtime directly:
import {Tool, Task} from '@ddse/acm-sdk';
import {executePlan, MemoryLedger} from '@ddse/acm-runtime';
import {StructuredLLMPlanner} from '@ddse/acm-planner';
Define tools, tasks, and registries, then run executePlan with a freshly generated plan. See the Core Concepts section for a step-by-step tutorial.
Next steps
- Learn the conceptual model.
- Explore the scenario playbook.
- Launch the AI Coder experience for an interactive workflow.