Install
openclaw skills install cascadeflowOpenClaw-native domain cascading. Use when users need cost/latency reduction via cascading, domain-aware model assignment, OpenClaw-native event handling, and command setup including /model cflow and optional /cascade stats commands.
openclaw skills install cascadeflowUse CascadeFlow as an OpenClaw provider to lower cost and latency via cascading. Assign up to 17 domain-specific models (for coding, web search, reasoning, and more), including OpenClaw-native event handling, and cascade between them (small model first, verifier when needed). Keep setup minimal, then verify with one health check and one chat call.
/v1/chat/completions.metadata.method, metadata.event, and channel/category hints).Or ask your OpenClaw agent to set it up for you as an OpenClaw custom provider with OpenClaw-native events and domain understanding.
python3 -m venv .venv
source .venv/bin/activate
python -m pip install --upgrade "cascadeflow[openclaw]>=0.7,<0.8"
python -m pip show cascadeflow
python -m pip download --no-deps "cascadeflow[openclaw]>=0.7,<0.8" -d /tmp/cascadeflow_pkg
python -m pip hash /tmp/cascadeflow_pkg/cascadeflow-*.whl
Optional variants:
python -m pip install --upgrade "cascadeflow[openclaw,anthropic]>=0.7,<0.8" # Anthropic-only preset
python -m pip install --upgrade "cascadeflow[openclaw,openai]>=0.7,<0.8" # OpenAI-only preset
python -m pip install --upgrade "cascadeflow[openclaw,providers]>=0.7,<0.8" # Mixed preset
examples/configs/anthropic-only.yaml, examples/configs/openai-only.yaml, examples/configs/mixed-anthropic-openai.yamlANTHROPIC_API_KEY=... and/or OPENAI_API_KEY=... (required based on selected preset)--auth-token ... and --stats-auth-token ... (recommended for production; use long random values)set -a; source .env; set +a
python3 -m cascadeflow.integrations.openclaw.openai_server \
--host 127.0.0.1 --port 8084 \
--config examples/configs/anthropic-only.yaml \
--auth-token local-openclaw-token \
--stats-auth-token local-stats-token
Optional harness activation (runtime in-loop policy controls):
# Observe first (recommended): log decisions, no blocking
python3 -m cascadeflow.integrations.openclaw.openai_server \
--host 127.0.0.1 --port 8084 \
--config examples/configs/anthropic-only.yaml \
--harness-mode observe
# Enforce mode with limits
python3 -m cascadeflow.integrations.openclaw.openai_server \
--host 127.0.0.1 --port 8084 \
--config examples/configs/anthropic-only.yaml \
--harness-mode enforce \
--harness-budget 1.0 \
--harness-max-tool-calls 12 \
--harness-max-latency-ms 3500 \
--harness-compliance strict
baseUrl: http://<cascadeflow-host>:8084/v1 (local default: http://127.0.0.1:8084/v1)http://<server-ip>:8084/v1 or https://<domain>/v1 (TLS/reverse proxy)api: openai-completionsmodel: cascadeflowapiKey: same value as your --auth-token/model cflow: default OpenClaw model switch using alias cflow./cascade: optional custom command (if configured in OpenClaw)./cascade savings: optional custom subcommand for cost stats./cascade health: optional custom subcommand for service status.references/clawhub_publish_pack.mdreferences/market_positioning.mdhttps://github.com/lemony-ai/cascadeflow/blob/main/docs/guides/openclaw_provider.mdhttps://github.com/lemony-ai/cascadeflow