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https://github.com/windmill-labs/windmill.git
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b0ddcf31e4
* ci: add path-gated AI agent integration tests workflow Runs integration_tests/ai_agent_tests against real LLM providers (Anthropic/OpenAI/Google) only when AI-agent backend code or the tests change, since runs make paid LLM calls. Adds a conftest fixture that skips provider-parametrized cases whose API keys are absent, so CI exercises only the providers it has secrets for. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com> * ci: add path-gated ai_evals global-mode smoke workflow Runs the global AI chat eval (global-test1) across one cheap model per provider (Anthropic/OpenAI/Google/DeepSeek) only when the eval harness or copilot chat code change, since runs make paid LLM calls. Builds Windmill CE from source as the AI proxy; global tools/drafts run in the Vitest bridge. Gates on the deterministic draft pipeline (run succeeded + produced a draft + used write_script), not the variable LLM judge score. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com> * ci: run AI smokes on PR ready-for-review instead of every push Switch the pull_request trigger from `synchronize` (every commit) to `ready_for_review`, with a job guard skipping draft PRs, so the paid LLM runs only fire when a PR is marked ready to merge (plus push-to-main and manual dispatch). Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com> * fix(ai_evals): lazily load cli mode so non-cli evals skip the cli toolchain The entrypoint eagerly imported modes/cli, which pulls the wmill CLI guidance modules and their JSR deps (@cliffy/*). Global/flow/script/app runs then crashed with "Cannot find module '@cliffy/ansi/colors'" when the cli workspace deps were not installed. Import createCliModeRunner dynamically inside runCliBenchmark instead. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com> * test(ai_agent): raise low max_completion_tokens to OpenAI's 16 minimum OpenAI's /v1/responses rejects max_output_tokens < 16 with a 400, failing test_low_max_tokens for openai. 16 still exercises a truncated response. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com> * ci: run ai_evals workflow on Node 22 for the frontend undici 8.x dep The Vitest bridge loads frontend/node_modules/undici@8.x, which requires Node >=22.19; Node 20 failed with "webidl.util.markAsUncloneable is not a function" when loading vitest.config.ts. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com> * fix(ai_evals): run frontend evals autonomously + give global-test1 more turns Frontend evals (flow/script/app/global) ran the production chat prompt, which assumes an interactive human — so cheaper models burned their turn budget asking for confirmation, waiting for approval, or presenting a plan, sometimes hitting maxTurns without producing a draft. Append a shared autonomy note in baseEvalRunner (the path all frontend modes share, mirroring cli mode): act directly on clear requests; only ask on genuinely ambiguous ones (preserving the askUserQuestion cases). Also raise global-test1's maxTurns 8 -> 10 so a model that over-explores still converges. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com> * ci(ai_evals): watch draft/prompt deps outside copilot/ The global eval runs production frontend code in-process, so the smoke's behavior depends on files outside frontend/src/lib/components/copilot/**: the draft model (userDraft.svelte.ts, userDraftDbSyncer.svelte.ts), script inference (infer.ts), and the chat system prompts ($system_prompts -> system_prompts/auto-generated). Add them to both push and PR path filters so a change there actually triggers the smoke that gates on draft production. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com> * fix: skip direct provider tests without credentials * feat: add ai evals skip judge flag * fix: simplify ai evals ci gate * fix: simplify ai evals smoke gate * fix: handle ai eval workflow triggers --------- Co-authored-by: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
167 lines
6.3 KiB
YAML
167 lines
6.3 KiB
YAML
name: AI Evals (global mode)
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# Smoke-tests the production global AI chat proxy/frontend execution path via
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# the ai_evals harness, one case across one cheap model per provider. Runs only
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# when the eval harness or the global chat code change, since each run makes real
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# (paid) LLM calls. The backend is built from source purely as the AI proxy the
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# harness routes model calls through; the global tools/drafts run in-process in
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# the Vitest bridge against production frontend code. To avoid spending on every
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# commit, the PR side triggers only when a PR is marked ready for review (out of
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# draft) — not on `synchronize` — plus push to main and manual dispatch.
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on:
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workflow_dispatch:
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push:
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branches: [main]
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paths:
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- "ai_evals/**"
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- "backend/windmill-api/src/ai.rs"
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- "backend/windmill-ai/**"
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- "frontend/src/lib/components/copilot/**"
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# The eval harness runs production frontend code in-process; these are the
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# AI/draft-specific deps outside copilot/ that the global smoke exercises.
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- "frontend/src/lib/userDraft.svelte.ts"
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- "frontend/src/lib/userDraftDbSyncer.svelte.ts"
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- "frontend/src/lib/infer.ts"
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- ".github/workflows/ai-evals-test.yml"
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pull_request:
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types: [opened, reopened, ready_for_review]
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paths:
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- "ai_evals/**"
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- "backend/windmill-api/src/ai.rs"
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- "backend/windmill-ai/**"
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- "frontend/src/lib/components/copilot/**"
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# The eval harness runs production frontend code in-process; these are the
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# AI/draft-specific deps outside copilot/ that the global smoke exercises.
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- "frontend/src/lib/userDraft.svelte.ts"
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- "frontend/src/lib/userDraftDbSyncer.svelte.ts"
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- "frontend/src/lib/infer.ts"
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- ".github/workflows/ai-evals-test.yml"
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concurrency:
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group: ai-evals-test-${{ github.ref }}
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cancel-in-progress: true
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jobs:
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ai_evals_global:
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# Provider secrets are unavailable to forked and Dependabot PRs.
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if: >-
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github.event_name != 'pull_request' ||
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(
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github.event.pull_request.draft == false &&
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github.event.pull_request.head.repo.full_name == github.repository &&
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github.event.pull_request.user.login != 'dependabot[bot]'
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)
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runs-on: ubicloud-standard-16
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services:
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postgres:
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image: postgres:16
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ports:
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- 5432:5432
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env:
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POSTGRES_DB: windmill
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POSTGRES_PASSWORD: changeme
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options: >-
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--health-cmd pg_isready --health-interval 10s --health-timeout 5s
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--health-retries 5
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steps:
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- uses: actions/checkout@v4
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- uses: actions-rust-lang/setup-rust-toolchain@v1
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with:
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cache-workspaces: backend
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toolchain: 1.93.0
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- uses: oven-sh/setup-bun@v2
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with:
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bun-version: 1.3.10
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- uses: actions/setup-node@v4
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with:
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# Node 22.19+ is required by the frontend's undici 8.x, which the
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# Vitest bridge loads; Node 20 fails with markAsUncloneable.
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node-version: "22"
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# CE build used only as the AI proxy (login, workspace, provider resource,
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# /ai/proxy). No worker execution or MCP needed — global tools/drafts run
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# in the Vitest bridge. quickjs matches the standard CE feature set.
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- name: Build Windmill (AI proxy)
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working-directory: ./backend
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env:
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SQLX_OFFLINE: true
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CARGO_BUILD_JOBS: 12
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RUSTFLAGS: ""
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run: cargo build --features quickjs
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- name: Start Windmill
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working-directory: ./backend
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env:
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DATABASE_URL: postgres://postgres:changeme@localhost:5432/windmill
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RUST_LOG: info
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run: |
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mkdir -p ../ai_evals/logs
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./target/debug/windmill > ../ai_evals/logs/windmill.log 2>&1 &
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echo "Waiting for Windmill to be ready..."
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for i in $(seq 1 60); do
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if curl -sf http://localhost:8000/api/version > /dev/null 2>&1; then
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echo "Windmill is ready"
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break
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fi
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sleep 2
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done
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curl -sf http://localhost:8000/api/version > /dev/null || { echo "Windmill failed to start"; tail -50 ../ai_evals/logs/windmill.log; exit 1; }
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- name: Install frontend deps + generate client
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working-directory: ./frontend
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run: |
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npm ci
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npm run generate-backend-client
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- name: Run global AI evals
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timeout-minutes: 20
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working-directory: ./ai_evals
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env:
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WMILL_AI_EVAL_BACKEND_URL: http://localhost:8000
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WMILL_AI_EVAL_BACKEND_WORKSPACE: integration-tests
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# Anthropic backs the haiku model. Google AI uses GEMINI_API_KEY.
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ANTHROPIC_API_KEY: ${{ secrets.ANTHROPIC_API_KEY }}
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OPENAI_API_KEY: ${{ secrets.OPENAI_API_KEY }}
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GEMINI_API_KEY: ${{ secrets.GOOGLE_API_KEY }}
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DEEPSEEK_API_KEY: ${{ secrets.DEEPSEEK_API_KEY }}
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run: |
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bun install
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mkdir -p results
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# One cheap model per provider (anthropic/openai/googleai/deepseek).
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fail=0
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for m in haiku 4o gemini-3-flash-preview deepseek-v4-flash; do
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echo "::group::global-test1-script-create ($m)"
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if ! bun run cli -- run global global-test1-script-create \
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--model "$m" --execution-only --output "$PWD/results/ci-$m.json"; then
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echo "$m: harness/proxy errored"
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fail=1
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echo "::endgroup::"
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continue
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fi
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# The CLI exits 0 when the harness records failed attempts, so gate
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# on execution-only pass counts while ignoring model output quality.
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if jq -e \
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'.attemptCount > 0 and .passedAttempts == .attemptCount' \
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"results/ci-$m.json" > /dev/null; then
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echo "$m: OK — proxy/frontend execution completed"
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else
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echo "$m: FAILED proxy/frontend execution"
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jq -c '.cases[0].attempts[0].checks' "results/ci-$m.json" || true
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fail=1
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fi
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echo "::endgroup::"
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done
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[ "$fail" = 0 ] || { echo "ai_evals global smoke failed"; exit 1; }
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- name: Archive logs and results
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uses: actions/upload-artifact@v4
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if: always()
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with:
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name: ai-evals-global-logs
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path: |
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ai_evals/logs
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ai_evals/results
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