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.env.eval.example
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Mutasem Aldmour
docs: Expand instance-ai eval-authoring skill with calibration learnings (#33844)
09 июл 2026, 12:07
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09 июл 2026, 12:07
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# Example env for running Instance AI workflow evals locally. # # This is ONE setup — a local instance that runs the build sandbox directly # (no hosted proxy). Other setups (proxy-vended sandbox/model, an instance you # already run) need different vars or none of these. Copy to `.env.eval` # (gitignored) and fill in real values, then load it alongside your usual env # however you manage env (a common way is `dotenvx run -f .env.local -f .env.eval`). # # See .agents/skills/create-instance-ai-eval/running-evals.md for what each # piece does and packages/@n8n/instance-ai/evaluations/README.md for the harness. N8N_LOG_LEVEL=debug # Enable AI features and the instance-ai module. N8N_AI_ENABLED=true N8N_ENABLED_MODULES=instance-ai # Model key for the builder and the eval helper (mock generation, verifier, # user-proxy, expectation judge). When the instance runs without the proxy, the # model client reads ANTHROPIC_API_KEY directly, so export that too if you go # that route. N8N_AI_ANTHROPIC_KEY=sk-ant-api03-REPLACE_ME # Sandbox where the builder executes its workflow-build code. N8N_INSTANCE_AI_SANDBOX_ENABLED=true N8N_INSTANCE_AI_SANDBOX_PROVIDER=daytona # Tear the sandbox down after each build instead of reusing it across cases. N8N_INSTANCE_AI_SANDBOX_EPHEMERAL=true # Daytona credentials — used when the instance provisions the sandbox directly # (rather than through the proxy). Get a key from https://app.daytona.io. DAYTONA_API_KEY=dtn_REPLACE_ME DAYTONA_API_URL=https://app.daytona.io/api