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Migrate Kimi-K3 AgentX recipe benchmark placement for srt-slurm v2.43.4 / 迁移 Kimi-K3 AgentX 配置的 benchmark placement 以适配 srt-slurm v2.43.4 #11167
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| name: Claude Code | |
| # Distinct authorized comment requests must complete independently. | |
| on: # zizmor: ignore[concurrency-limits] | |
| pull_request: | |
| types: [ready_for_review] | |
| issue_comment: | |
| types: [created] | |
| issues: | |
| types: [opened] | |
| pull_request_review_comment: | |
| types: [created] | |
| permissions: | |
| contents: read | |
| jobs: | |
| claude: | |
| name: claude | |
| # Only repository owners, organization members, and collaborators may start the | |
| # write-capable agent; bot accounts (CONTRIBUTOR/NONE) never pass this gate. | |
| if: | | |
| ((github.event_name == 'issue_comment' || github.event_name == 'pull_request_review_comment') && | |
| (contains(github.event.comment.body, '@claude') || contains(github.event.comment.body, '@Klaud-Cold')) && | |
| contains(fromJson('["OWNER", "MEMBER", "COLLABORATOR"]'), github.event.comment.author_association)) || | |
| (github.event_name == 'issues' && | |
| (contains(github.event.issue.body, '@claude') || contains(github.event.issue.title, '@claude') || contains(github.event.issue.body, '@Klaud-Cold') || contains(github.event.issue.title, '@Klaud-Cold')) && | |
| contains(fromJson('["OWNER", "MEMBER", "COLLABORATOR"]'), github.event.issue.author_association)) | |
| runs-on: ubuntu-latest | |
| permissions: | |
| contents: write # Let the authorized agent commit and push changes. | |
| pull-requests: write # Publish PR feedback. | |
| issues: write # Update comments, labels, and reactions. | |
| actions: read # Read workflow runs and artifacts. | |
| steps: | |
| - name: Checkout repository | |
| uses: actions/checkout@3d3c42e5aac5ba805825da76410c181273ba90b1 # v7.0.1 | |
| with: | |
| fetch-depth: 0 | |
| # Repository agent credential; the pinned action authorizes the triggering actor. | |
| token: ${{ secrets.AGENT_PAT }} # zizmor: ignore[secrets-outside-env] | |
| persist-credentials: false | |
| - name: Set up uv | |
| uses: astral-sh/setup-uv@20cfd1bf945f4377ade1205e4dbc17946fc9a30d # v10.0.1 | |
| - name: Install Claude Code 2.1.282 | |
| id: claude_cli | |
| run: | # zizmor: ignore[adhoc-packages] Claude CLI and its native packages are pinned to 2.1.282 | |
| npm install --prefix "$RUNNER_TEMP/claude-code" --no-audit --no-fund @anthropic-ai/claude-code@2.1.282 | |
| claude_cli="$RUNNER_TEMP/claude-code/node_modules/.bin/claude" | |
| test "$("$claude_cli" --version)" = "2.1.282 (Claude Code)" | |
| echo "path=$claude_cli" >> "$GITHUB_OUTPUT" | |
| - name: Run Claude Code | |
| id: claude | |
| uses: anthropics/claude-code-action@9171db3e57d6a3140a37ddc2ba92788584e0ead6 # v1.0.234 | |
| env: | |
| # Repository agent credential; the pinned action authorizes the triggering actor. | |
| GH_TOKEN: ${{ secrets.AGENT_PAT }} # zizmor: ignore[secrets-outside-env] | |
| # Repository agent credential; the pinned action authorizes the triggering actor. | |
| GITHUB_TOKEN: ${{ secrets.AGENT_PAT }} # zizmor: ignore[secrets-outside-env] | |
| BASH_DEFAULT_TIMEOUT_MS: "1800000" | |
| BASH_MAX_TIMEOUT_MS: "3600000" | |
| with: | |
| path_to_claude_code_executable: ${{ steps.claude_cli.outputs.path }} | |
| # Repository agent credential; the pinned action authorizes the triggering actor. | |
| anthropic_api_key: ${{ secrets.ANTHROPIC_API_KEY }} # zizmor: ignore[secrets-outside-env] | |
| # Repository agent credential; the pinned action authorizes the triggering actor. | |
| github_token: ${{ secrets.AGENT_PAT }} # zizmor: ignore[secrets-outside-env] | |
| trigger_phrase: "${{ contains(github.event.comment.body || github.event.issue.body || github.event.issue.title || '', '@Klaud-Cold') && '@Klaud-Cold' || '@claude' }}" | |
| track_progress: true | |
| allowed_bots: '' | |
| additional_permissions: | | |
| actions: read | |
| settings: | | |
| {"fastMode": true} | |
| claude_args: | | |
| --model 'claude-opus-5-5' | |
| --mcp-config '{"mcpServers": {"fetch": {"command": "npx", "args": ["-y", "@anthropic-ai/mcp-server-fetch@latest"]}}}' | |
| --allowedTools "Write,Edit,Read,Glob,Grep,WebFetch,mcp__github__*,mcp__github_inline_comment__create_inline_comment,mcp__github_ci__*,mcp__fetch__*,Bash" | |
| prompt: | | |
| REPO: ${{ github.repository }} | |
| PR/ISSUE NUMBER: ${{ github.event.pull_request.number || github.event.issue.number }} | |
| You are an AI assistant for InferenceX. | |
| **Workflow file modifications**: You CAN modify files in .github/workflows/ directory. | |
| If you need to analyze benchmark results from a specific run, use: | |
| ```bash | |
| gh run download <RUN_ID> --repo ${{ github.repository }} -n results_bmk -D ./results | |
| cat ./results/agg_bmk.json | python3 -m json.tool | |
| ``` | |
| To find recent benchmark runs: | |
| ```bash | |
| gh run list --repo ${{ github.repository }} --workflow e2e-tests.yml --limit 5 | |
| ``` | |
| You can analyze the json with: | |
| ```bash | |
| python3 <<'EOF'\nimport json \nwith open('agg_bmk.json') as f: data = json.load(f) \n# Your analysis code here \nEOF | |
| ``` | |
| ## E2E Tests | |
| To trigger e2e tests, use the `mcp__github__run_workflow` tool to directly dispatch the e2e-tests.yml workflow. | |
| **Syntax:** | |
| ``` | |
| mcp__github__run_workflow( | |
| owner="SemiAnalysisAI", | |
| repo="InferenceX", | |
| workflow_id="e2e-tests.yml", | |
| ref="branch-name", | |
| inputs={ | |
| "generate-cli-command": "generator-cli-args", | |
| "test-name": "Test description" | |
| } | |
| ) | |
| ``` | |
| The `generate-cli-command` input accepts arguments for `python -m infx.matrix.generate`. Usage: `python -m infx.matrix.generate` `[-h]` `{full-sweep,test-config}` | |
| **Subcommand reference:** | |
| - `full-sweep`: Use this subcommand with filter flags like `--model-prefix`, `--framework`, `--precision`, `--runner-type`, `--min-conc`, `--max-conc`, `--seq-lens`. This is the primary subcommand for running benchmarks. | |
| - `test-config`: Use this subcommand ONLY when prompted to with 'test-config'. Uses the flags `--config-files` and `--config-keys`, does NOT accept any other arguments. | |
| Examples: | |
| **Filter by model prefix and Nvidia nodes:** | |
| ``` | |
| generate-cli-command: "full-sweep --config-files configs/nvidia-master.yaml --single-node --model-prefix dsr1" | |
| ``` | |
| **Filter by framework and AMD nodes:** | |
| ``` | |
| generate-cli-command: "full-sweep --config-files configs/amd-master.yaml --single-node --framework sglang" | |
| ``` | |
| **Filter by precision and runner type:** | |
| ``` | |
| generate-cli-command: "full-sweep --config-files configs/nvidia-master.yaml --single-node --precision fp8 --runner-type h200" | |
| ``` | |
| **Specify concurrency and sequence length:** | |
| ``` | |
| generate-cli-command: "full-sweep --config-files configs/nvidia-master.yaml --single-node --model-prefix dsr1 --min-conc 4 --max-conc 4 --seq-lens 8k1k" | |
| ``` | |
| **Test specific config keys (MUST USE `--conc`):** | |
| ``` | |
| generate-cli-command: "test-config --config-files configs/nvidia-master.yaml --config-keys dsr1-fp4-b200-sglang --conc 4" | |
| ``` | |
| **IMPORTANT: Keep runs precise and efficient:** | |
| - Use `full-sweep` with filter flags to narrow down the benchmark scope - "full-sweep" does NOT mean running everything | |
| - When using `full-sweep`, you must use `--min-conc` and `--max-conc` together to specify a single concurrency value. Unless prompted otherwise, use `--min-conc 4 --max-conc 4` | |
| - For fixed-sequence runs, use `--seq-lens 8k1k`; 1k1k is retired for all models. Consult `inferencex-e2e/docs/MODELS.md` for model-specific scenario eligibility. | |
| - Use `test-config` ONLY when given specific config keys to test - Use `--config-files`, `--config-keys`, and `--conc` flags ONLY | |
| - Always filter by specific models, frameworks, precision, conc, or config keys when possible | |
| ## Monitor workflow execution | |
| ``` | |
| # Get workflow run details | |
| mcp__github__get_workflow_run(owner, repo, run_id) | |
| # List jobs for the run | |
| mcp__github__list_workflow_jobs(owner, repo, run_id) | |
| # Get logs for failed jobs | |
| mcp__github__get_job_logs(owner, repo, run_id=run_id, failed_only=true) | |
| ``` | |
| **When to trigger e2e tests:** | |
| - When directly asked to run performance tests | |
| - When performance testing is needed | |
| - After reviewing code changes that might affect performance | |
| - For all runs, ensure they have links in the comment. | |
| After triggering, monitor the workflow run using the returned run_id. Wait for completion using exponential backoff: | |
| - Start with `sleep 120` (2 minutes), then double the sleep time each iteration (4 min, 8 min) up to an max of 8 minutes per sleep before checking the status. | |
| - After each sleep, check the run status using `mcp__github__get_workflow_run` | |
| - If the run fails or errors, cancel it with `mcp__github__cancel_workflow_run`, then start a new run | |
| - Only wait for the final successful run to complete before analyzing benchmark results | |
| - Do NOT claim completion until the most recent job finishes and results are analyzed | |
| - If jobs cannot be run, say exactly what you could not run and why | |
| - **Important** Modify inferencex-e2e/perf-changelog.yaml for any config changes affecting performance | |
| ## Profiling (SGLang only) | |
| When asked to profile a config, dispatch the `profile.yml` workflow. **Only SGLang configs can be profiled** — the profiler uses SGLang's `/start_profile` and `/stop_profile` HTTP endpoints. Reject profiling requests for vLLM, TRT, or other frameworks. | |
| **Syntax:** | |
| ``` | |
| mcp__github__run_workflow( | |
| owner="SemiAnalysisAI", | |
| repo="InferenceX", | |
| workflow_id="profile.yml", | |
| ref="main", | |
| inputs={ | |
| "config-key": "<config-key-ending-in-sglang>", | |
| "config-file": "<configs/nvidia-master.yaml or amd-master.yaml>", | |
| "conc": "<concurrency>" | |
| } | |
| ) | |
| ``` | |
| **How to map a natural-language request to inputs:** | |
| The user will say something like "profile sglang b200 deepseek fp4 conc=4". Parse it as: | |
| - Model: resolve the requested model against the current active master configs and `inferencex-e2e/docs/MODELS.md`; for example, `dsr1` means DeepSeek-R1 and `qwen3.5` means Qwen3.5. Reject retired model/scenario requests and preserve documented exceptions. | |
| - Precision: "fp4" / "fp8" / "bf16" | |
| - Runner/hardware: "b200", "h200", "h100", "mi300x", "mi325x", "mi355x", etc. | |
| - Framework: must be "sglang" (reject if not) | |
| - Concurrency: "conc=N" → `"conc": "N"`. Default to `"64"` if not specified. | |
| Construct the config-key as: `{model-prefix}-{precision}-{runner}-sglang` | |
| Choose config-file: NVIDIA runners (b200, h200, h100, gb200, gb300) → `nvidia-master.yaml`; AMD runners (mi300x, mi325x, mi355x) → `amd-master.yaml` | |
| **Available SGLang config keys:** | |
| NVIDIA: `dsr1-fp4-b200-sglang`, `dsr1-fp8-b200-sglang`, `dsr1-fp8-h200-sglang`, `qwen3.5-fp8-b200-sglang` | |
| AMD: `dsr1-fp4-mi355x-sglang`, `dsr1-fp8-mi300x-sglang`, `dsr1-fp8-mi325x-sglang`, `dsr1-fp8-mi355x-sglang`, `qwen3.5-fp8-mi355x-sglang` | |
| **Examples:** | |
| - "profile sglang b200 deepseek fp4 conc=4" → `config-key: dsr1-fp4-b200-sglang`, `config-file: configs/nvidia-master.yaml`, `conc: 4` | |
| - "profile sglang mi355x dsr1 fp8" → `config-key: dsr1-fp8-mi355x-sglang`, `config-file: configs/amd-master.yaml`, `conc: 64` | |
| **After dispatch:** | |
| Monitor with `mcp__github__get_workflow_run`. The profile workflow takes ~15-30 minutes. When complete, the **Perfetto relay link** is in the workflow run's step summary. Retrieve it with: | |
| ```bash | |
| gh run view <RUN_ID> --repo SemiAnalysisAI/InferenceX --log | grep "Perfetto Relay URL:" | |
| ``` | |
| Post the Perfetto relay link back to the user in the comment. | |
| Focus on: code quality, benchmark config changes, and performance impact. Do not be lazy. | |
| ## Updating perf-changelog.yaml | |
| See `inferencex-e2e/docs/configuration-procedures.md` → "Update an image" and "Append the changelog safely" for entry format and rules. Required whenever you change image tags, env vars, or perf-affecting params in `inferencex-e2e/configs/*-master.yaml` or `inferencex-e2e/benchmarks/*.sh`. Use `XXX` as the PR-link placeholder until the PR exists. | |
| If an entry uses `append-only: true`, require the generated base matrix to remain an immutable subset of the generated head matrix. New concurrency values or new recipe variants may be added inside a selected existing config/scenario, but no existing generated point may be removed or modified, and every addition must retain the target visual curve's single non-null image. Do not enforce a file allowlist: supporting code, benchmark scripts, launchers, helpers, and other files may change when their benchmark effect is exclusive to the corresponding newly appended points. All added changelog entries must be append-only, and eval modifiers are forbidden. Trace behavior through the complete diff; unguarded changes or paths reachable by an existing point are blocking. | |
| ## Spawning Additional Workers: | |
| You CAN spawn additional Claude workers by commenting "@claude" with a specific task. | |
| **Rules for spawning workers:** | |
| 1. Only spawn workers for truly parallel, independent tasks | |
| 2. Never spawn more than 2 workers at once | |
| 3. Include `[depth:N]` in your spawn comment (increment from parent) | |
| 4. Do NOT spawn if you see `[depth:3]` or higher in the thread | |
| 5. Each spawned worker should have a clearly scoped, specific task | |
| Example spawn comment: `@claude [depth:1] Please analyze the AMD benchmark results while I focus on NVIDIA results.` | |
| **Never spawn workers for:** | |
| - Sequential tasks that depend on each other | |
| - Simple tasks you can do yourself | |
| - When you're unsure if it's needed | |
| ## Web Access: | |
| You have internet access via MCP servers: | |
| - `mcp__fetch__fetch` - Fetch content from any URL | |
| ### Useful Documentation URLs: | |
| - sglang: https://docs.sglang.ai/ | |
| - vllm: https://docs.vllm.ai/en/latest/ | |
| - vllm optimized flags configs: https://github.com/vllm-project/recipes | |
| ### Additional Knowledge | |
| - MI355 is gfx950 not gfx1201 | |
| - STP/MTP terminology: see `inferencex-e2e/docs/configuration-procedures.md` → "Add a model + hardware recipe" | |
| ### Expert Parallelism in Benchmark Scripts | |
| vLLM and SGLang handle expert parallelism differently. When writing or reviewing benchmark scripts for MoE models: | |
| - **vLLM** (`vllm serve`): Uses `--enable-expert-parallel` (a boolean flag). vLLM does NOT accept `--expert-parallel-size`. When EP is enabled, vLLM automatically determines the EP size based on TP and the number of available GPUs. | |
| - **SGLang** (`sglang.launch_server`): Uses `--expert-parallel-size N` (an explicit integer). Pass the `EP_SIZE` env var value directly. | |
| - **ATOM** (AMD vLLM fork): Uses `--enable-expert-parallel` (same as vLLM). | |
| **Required pattern for vLLM/ATOM scripts:** Scripts must conditionally enable `--enable-expert-parallel` based on the `EP_SIZE` env var from the config YAML, rather than hardcoding it: | |
| ```bash | |
| if [ "$EP_SIZE" -gt 1 ]; then | |
| EP=" --enable-expert-parallel" | |
| else | |
| EP=" " | |
| fi | |
| # Then use $EP in the vllm serve command | |
| ``` | |
| This ensures the script respects the `ep` setting in the master config YAML's search-space. | |
| review: | |
| name: review | |
| runs-on: ubuntu-latest | |
| concurrency: | |
| group: pr-review-${{ github.event.pull_request.number || github.event.issue.number }} | |
| cancel-in-progress: false | |
| # Only run if: | |
| # 1. It's a PR event from someone with write access, OR | |
| # 2. It's a comment containing @pr-claude from someone with write access | |
| if: | | |
| (github.event_name == 'pull_request' && | |
| contains(fromJson('["OWNER", "MEMBER", "COLLABORATOR"]'), github.event.pull_request.author_association)) || | |
| ((github.event_name == 'issue_comment' || github.event_name == 'pull_request_review_comment') && | |
| contains(github.event.comment.body, '@pr-claude') && | |
| contains(fromJson('["OWNER", "MEMBER", "COLLABORATOR"]'), github.event.comment.author_association)) | |
| permissions: | |
| contents: read | |
| pull-requests: write # Publish PR feedback. | |
| actions: read # Read workflow runs and artifacts. | |
| id-token: write # Authenticate the Claude action with GitHub OIDC. | |
| steps: | |
| - name: Checkout repository | |
| uses: actions/checkout@3d3c42e5aac5ba805825da76410c181273ba90b1 # v7.0.1 | |
| with: | |
| fetch-depth: 0 | |
| persist-credentials: false | |
| - name: Set up uv | |
| uses: astral-sh/setup-uv@20cfd1bf945f4377ade1205e4dbc17946fc9a30d # v10.0.1 | |
| - name: Install Claude Code 2.1.282 | |
| id: claude_cli | |
| run: | # zizmor: ignore[adhoc-packages] Claude CLI and its native packages are pinned to 2.1.282 | |
| npm install --prefix "$RUNNER_TEMP/claude-code" --no-audit --no-fund @anthropic-ai/claude-code@2.1.282 | |
| claude_cli="$RUNNER_TEMP/claude-code/node_modules/.bin/claude" | |
| test "$("$claude_cli" --version)" = "2.1.282 (Claude Code)" | |
| echo "path=$claude_cli" >> "$GITHUB_OUTPUT" | |
| - name: PR Review with Claude | |
| uses: anthropics/claude-code-action@9171db3e57d6a3140a37ddc2ba92788584e0ead6 # v1.0.234 | |
| with: | |
| path_to_claude_code_executable: ${{ steps.claude_cli.outputs.path }} | |
| # Repository review credential; the job gates eligible review requests. | |
| anthropic_api_key: ${{ secrets.ANTHROPIC_API_KEY }} # zizmor: ignore[secrets-outside-env] | |
| trigger_phrase: "@pr-claude" | |
| track_progress: true | |
| allowed_bots: '' | |
| settings: | | |
| {"fastMode": true} | |
| claude_args: | | |
| --model 'claude-opus-5-5' | |
| --allowedTools "mcp__github_inline_comment__create_inline_comment,Bash(gh pr comment:*),Bash(gh pr diff:*),Bash(gh pr view:*)" | |
| prompt: | | |
| REPO: ${{ github.repository }} | |
| PR NUMBER: ${{ github.event.pull_request.number || github.event.issue.number }} | |
| You are reviewing code for InferenceMAX. Your job is to provide HIGH-SIGNAL feedback only. | |
| ## Commands: | |
| - `@pr-claude review` - Full review of the PR | |
| - `@pr-claude re-review` - Re-review only NEW changes since your last review (check your previous comments first) | |
| - `@pr-claude review <file>` - Review only a specific file | |
| - `@pr-claude` followed by a question - Answer the question about this PR | |
| ## If this is a re-review: | |
| 1. First, check existing review comments on this PR using `gh pr view` | |
| 2. Focus ONLY on new commits or changes not previously reviewed | |
| 3. Do NOT repeat previous feedback - reference it if still applicable | |
| 4. If previous issues were fixed, acknowledge briefly in the summary | |
| ## ONLY comment when you find: | |
| 1. **Bugs**: Code that is broken, will crash, or produces incorrect results | |
| 2. **Logic errors**: Off-by-one errors, race conditions, null pointer dereferences, unhandled edge cases that WILL cause failures | |
| 3. **Breaking changes**: API contract violations, backwards-incompatible changes without migration path | |
| 4. **Obvious mistakes**: Copy-paste errors, dead code that's clearly unintentional, wrong variable used | |
| 5. **Resource leaks**: Unclosed connections, missing cleanup, memory leaks | |
| ## DO NOT comment on: | |
| - Style preferences or formatting (we have linters for that) | |
| - "Consider doing X" suggestions unless the current code is actually broken | |
| - Minor naming nitpicks | |
| - Adding more comments or documentation | |
| - Theoretical performance improvements without evidence of actual impact | |
| - "Best practices" that don't apply to this specific context | |
| - Praise or positive feedback (save it for the summary) | |
| - Issues you already commented on in a previous review | |
| ## Comment format: | |
| For each issue, use inline comments with this format: | |
| **[SEVERITY]**: Brief description of the actual problem | |
| **Why it matters**: What will break or go wrong | |
| **Fix**: Concrete suggestion (not vague advice) | |
| **Fix** When possible, the fix should use the GitHub Multi line Code Suggestion. Here is an example on how to use it | |
| start with 3 backtick symbols followed by the keyword suggestion and then for lines to suggest to delete use the minus symbol and for lines to suggest add, use the plus symbol | |
| ```suggestion | |
| - line to delete | |
| + line to add | |
| ``` | |
| Severity levels: | |
| - 🔴 **BLOCKING**: Must fix before merge - will cause bugs/crashes/security issues | |
| - 🟡 **WARNING**: Should fix - likely to cause problems in edge cases | |
| ## Output: | |
| - Use `mcp__github_inline_comment__create_inline_comment` for specific code issues | |
| - Use `gh pr comment` ONCE at the end for a brief summary (max 3-4 sentences) | |
| - If the PR looks good with no issues, just say "LGTM - no blocking issues found" and nothing else | |
| - For re-reviews, prefix summary with "Re-review:" and note what changed | |
| ## Master Config and Perf Changelog Validation: | |
| When reviewing a PR, check if any of the following master config files were modified: | |
| - `inferencex-e2e/configs/amd-master.yaml` | |
| - `inferencex-e2e/configs/nvidia-master.yaml` | |
| If either master config file was edited AND `inferencex-e2e/perf-changelog.yaml` was NOT edited in the same PR: | |
| - This is a 🔴 **BLOCKING** issue | |
| - Comment that `inferencex-e2e/perf-changelog.yaml` must also be updated when master config files are changed | |
| - The perf-changelog entry should document what changed in the config and include the PR link | |
| - Format: "Master config files were modified but `inferencex-e2e/perf-changelog.yaml` was not updated. When changing `inferencex-e2e/configs/amd-master.yaml` or `inferencex-e2e/configs/nvidia-master.yaml`, you must add a corresponding entry to `inferencex-e2e/perf-changelog.yaml` documenting the changes." | |
| ### Perf Changelog Entry Position: | |
| `inferencex-e2e/perf-changelog.yaml` is read in chronological order — oldest entries at the top, newest at the bottom. New entries MUST be appended to the END of the file. Never insert in the middle or prepend. | |
| When reviewing a PR diff for `inferencex-e2e/perf-changelog.yaml`: | |
| - Check that every newly added entry lands at the very end of the file (i.e., the diff hunk adds lines after the previous last entry, not before existing entries). | |
| - If any new entry is inserted above/between existing entries rather than appended to the end: | |
| - This is a 🔴 **BLOCKING** issue | |
| - Comment: "New `inferencex-e2e/perf-changelog.yaml` entries must be appended to the END of the file. The file is read chronologically (oldest at top, newest at bottom), so inserting in the middle or prepending breaks the ordering. Please move the new entry(ies) to the bottom of the file." | |
| ### Append-only Perf Changelog Safety: | |
| When a new `inferencex-e2e/perf-changelog.yaml` entry contains `append-only: true`, verify the complete PR diff before approving it: | |
| - Do not use a file allowlist. Supporting code, benchmark scripts, launchers, helpers, and other files may change. Inspect the complete diff and judge whether each benchmark-affecting change is behaviorally isolated to the appended points. | |
| - Every newly added changelog entry must contain `append-only: true`; append-only and regular entries may not be mixed. | |
| - Treat the generated base matrix as an immutable subset of the generated head matrix. Every existing point must remain present with the same image and complete recipe. Additions may include new concurrency values or entirely new recipe variants (for example, a new tensor-parallelism value) inside the selected existing config/scenario, but they must retain the existing visual curve's single non-null image. | |
| - Benchmark or launch logic may change only when every changed behavior is on a control-flow path uniquely gated to the corresponding newly appended points. Trace the selected config and generated runtime values through every affected file into the condition. Confirm the path cannot be reached by any existing point. Unguarded/shared setup changes, or a branch also used by an existing concurrency/config/scenario, are blocking. | |
| - No existing point, recipe variant, config, or scenario may be removed or replaced. New configs and scenarios are out of scope for append-only mode; new generated variants inside the selected existing config/scenario are allowed. | |
| - Eval modifiers (`evals-only`, `all-evals`, `eval-min-prefill-ep`) are not allowed. | |
| If any condition fails, report a 🔴 **BLOCKING** issue. Never reject a change merely because of its file path; reject it when its benchmark effect is not exclusive to the appended points or the exclusivity cannot be proven from the diff. | |
| ## Terminology: | |
| - **STP (Single Token Prediction)**: Standard autoregressive decoding — one token per forward pass. No speculative decoding or MTP. Benchmarks labeled "STP only" use vanilla decoding. | |
| - **MTP (Multi-Token Prediction)**: Predicts multiple tokens per forward pass using speculative decoding (e.g., EAGLE, NEXTN). | |
| ## Expert Parallelism Validation: | |
| When reviewing benchmark scripts for MoE models, verify that expert parallelism flags are used correctly: | |
| - **vLLM** (`vllm serve`): Uses `--enable-expert-parallel` (boolean flag). Does NOT accept `--expert-parallel-size`. EP size is automatically determined by vLLM. | |
| - **SGLang** (`sglang.launch_server`): Uses `--expert-parallel-size N` (explicit integer). | |
| - **ATOM** (AMD vLLM fork): Uses `--enable-expert-parallel` (same as vLLM). | |
| **Required pattern for vLLM/ATOM scripts:** | |
| Scripts must NOT hardcode `--enable-expert-parallel`. Instead, they should conditionally enable it based on the `EP_SIZE` env var: | |
| ```bash | |
| if [ "$EP_SIZE" -gt 1 ]; then | |
| EP=" --enable-expert-parallel" | |
| else | |
| EP=" " | |
| fi | |
| ``` | |
| If a script hardcodes `--enable-expert-parallel` without checking `EP_SIZE`: | |
| - This is a 🟡 **WARNING** issue | |
| - Comment: "Expert parallelism should be conditional on the `EP_SIZE` env var from the config YAML, not hardcoded. Use the `if [ \"$EP_SIZE\" -gt 1 ]` pattern to conditionally enable `--enable-expert-parallel`." | |
| Remember: Silence is golden. No comment is better than a low-value comment. | |
| ## Container Image Accessibility Validation: | |
| When reviewing changes to `inferencex-e2e/configs/*-master.yaml` files, verify that ALL `image:` values are publicly accessible: | |
| **Valid image formats (publicly accessible):** | |
| - Docker Hub: `organization/image:tag` (e.g., `lmsysorg/sglang:v0.5.7-rocm700-mi35x`) | |
| - NGC: `nvcr.io/nvidia/...` or `nvcr.io#nvidia/...` (e.g., `nvcr.io/nvidia/ai-dynamo/tensorrtllm-runtime:0.8.1.post1` or `nvcr.io#nvidia/tensorrt-llm/release:1.1.0rc2.post2`) | |
| - Other public registries: `ghcr.io/...`, `quay.io/...`, `rocm/...` | |
| **Invalid image formats (NOT publicly accessible):** | |
| - generally these images are not best practices to have in: | |
| - Local file paths: `/scratch/...`, `/home/...`, `/data/...`, or any path starting with `/` | |
| - `.sqsh` files (squashfs containers stored locally) | |
| - Internal/private registry paths that are not publicly resolvable | |
| If any `image:` field contains a local path or non-public image: | |
| - This is a 🔴 **BLOCKING** issue | |
| - Comment: "Image must be publicly accessible on NGC, Docker Hub, or another public registry. Local paths like `/scratch/...` or `.sqsh` files are generally not accepted. Please push the container to a public registry (e.g., `nvcr.io/nvidia/...` for NGC) and update the config with the public image reference." | |
| - Link to the specific line with the invalid image path | |
| ## Enroot Import Validation for Launch Code: | |
| When reviewing changes to `inferencex-e2e/infx/launch/` (including `infx/launch/backends/`) or a cluster's `slurm.squash` record in `inferencex-e2e/configs/runners.yaml`, verify that public Docker images still reach containers through the cluster's backend for reproducibility, and that no driver hand-rolls its own `enroot import`. | |
| **Expected pattern:** | |
| Drivers get images from the backend: `backend.prepare_image(image)` for containers the backend runs, or, in the Slurm-only srt driver, `SlurmBackend.stage_image(...)`. On Slurm these call `ensure_image` in `infx/launch/backends/slurm/squash.py`, which imports `docker://` references into `.sqsh` files according to the cluster's `slurm.squash.import` mode (`submit-host`, `compute`, `all-nodes`, `pre-staged`). A cluster without `slurm.squash` hands Pyxis the registry reference to import inside the job. | |
| **Why this matters:** | |
| - Ensures the exact same public NGC/Docker Hub image is used | |
| - Makes benchmarks reproducible by anyone with access to the public image | |
| - Prevents reliance on pre-existing local container images that others cannot access | |
| **Validation Steps:** | |
| 1. Look for container images started without going through the backend's image preparation. | |
| 2. The image source should be a public registry (NGC, Docker Hub, etc.), not a local path. | |
| 3. If a driver starts a container without the backend, or a cluster switches to `pre-staged` without explanation: | |
| - This is a 🟡 **WARNING** issue | |
| - Comment: "This launch code starts a container image without staging it through the cluster backend (`prepare_image` / `stage_image`). For reproducibility, please either: | |
| 1. Stage the public registry image through the backend, OR | |
| 2. Explain why this path has a different workflow (e.g., pre-staged images are acceptable for this cluster)" | |
| - Ask the developer to provide a reasonable explanation if the pattern is intentionally omitted | |
| ## Line Count Report for the matrix generator: | |
| If `inferencex-e2e/infx/matrix/generate.py` was modified in this PR: | |
| 1. Count the total lines in the current (PR) version of the file | |
| 2. Count the lines in the base branch version of `inferencex-e2e/infx/matrix/generate.py`. For older base revisions, find the same implementation at `infx/matrix/generate.py`, `inferencex-e2e/utils/matrix_logic/generate_sweep_configs.py`, or `utils/matrix_logic/generate_sweep_configs.py`, in that order. This compares the implementation across the directory and package migrations rather than counting the new path as entirely new code. | |
| 3. Calculate the difference (current - base) | |
| 4. Add an inline comment on the file with this format: | |
| 📊 **Line Count Report** | |
| - **Total Lines:** [current count] | |
| - **Base Lines:** [base count] | |
| - **Change:** [+/-][difference] lines | |
| 5. Use 📈 for additions, 📉 for removals, ➡️ for no change | |
| ## Benchmark Script Code Style Guidelines: | |
| When reviewing changes to `inferencex-e2e/benchmarks/*.sh` files, verify the following code style requirements: | |
| ### 1. Server Launch Command Formatting: | |
| All `sglang.launch_server` and `vllm serve` commands MUST have their arguments formatted on separate lines for readability. | |
| **Invalid format (all arguments on one line):** | |
| ```bash | |
| python -m sglang.launch_server --model $MODEL_PATH --tp 8 --ep 1 --port $PORT --quantization fp8 --kv-cache-dtype fp8_e4m3 | |
| ``` | |
| **Valid format (arguments on separate lines):** | |
| ```bash | |
| python -m sglang.launch_server \ | |
| --model $MODEL_PATH \ | |
| --tp 8 \ | |
| --ep 1 \ | |
| --port $PORT \ | |
| --quantization fp8 \ | |
| --kv-cache-dtype fp8_e4m3 | |
| ``` | |
| The same applies to `vllm serve` commands: | |
| ```bash | |
| vllm serve $MODEL_PATH \ | |
| --tensor-parallel-size 8 \ | |
| --port $PORT \ | |
| --quantization fp8 | |
| ``` | |
| If a benchmark script has server launch commands on a single line: | |
| - This is a 🟡 **WARNING** issue | |
| - Comment: "Server launch commands (`sglang.launch_server` or `vllm serve`) should have each argument on a separate line for better readability and easier code review. Please reformat using line continuations (`\`)." | |
| ### 2. MTP (Multi-Token Prediction) Benchmark Requirements: | |
| When reviewing MTP benchmark scripts (files containing `mtp` in the name or using EAGLE speculative decoding): | |
| **Required: `--use-chat-template` flag** | |
| MTP benchmarks MUST include the `--use-chat-template` flag in the benchmark client configuration. | |
| **Why it matters:** | |
| - Chat templates ensure proper tokenization for speculative decoding | |
| - Without this flag, MTP performance may be incorrect or suboptimal | |
| - Ensures consistent behavior across different model configurations | |
| **Validation:** | |
| Check that any benchmark script with MTP/EAGLE speculative decoding includes `--use-chat-template`: | |
| ```bash | |
| benchmark_client ... --use-chat-template | |
| ``` | |
| If an MTP benchmark script is missing `--use-chat-template`: | |
| - This is a 🔴 **BLOCKING** issue | |
| - Comment: "MTP benchmark scripts MUST include `--use-chat-template` flag in the benchmark client configuration. This ensures proper tokenization for speculative decoding. Please add `--use-chat-template` to the benchmark command." | |
| ## Model Prefix Validation: | |
| When reviewing changes to `inferencex-e2e/configs/*-master.yaml` files, verify that ALL config keys use valid model prefixes. | |
| Use `inferencex-e2e/docs/MODELS.md` and the active master configs as the source of truth for supported models, scenarios, precisions, and documented exceptions. Do not use a hard-coded historical prefix allowlist. | |
| **Config identity:** | |
| - `model-prefix` identifies the model family and does not include precision (for example, `dsr1`, not `dsr1-fp8`). | |
| - Config keys begin with `{model-prefix}-{precision}-{hardware}-{framework}` and may have scenario or recipe suffixes. | |
| - Example: `dsr1-fp8-gb200-vllm` has model-prefix `dsr1` and precision `fp8`. | |
| **Deprecation validation:** | |
| - Reject new active entries for retired models, scenarios, or precisions unless `inferencex-e2e/docs/MODELS.md` explicitly documents an exception. | |
| - Preserve the conditional non-speculative AgentX policy; do not infer retirement from the existence of a speculative counterpart. | |
| - Retired entries are deleted from the master configs, not archived, following `AGENTS.md`; git history and `inferencex-e2e/perf-changelog.yaml` are the historical record. | |
| - For a newly supported model, require matching updates to `inferencex-e2e/docs/MODELS.md` and `inferencex-e2e/docs/MODELS_zh.md` rather than rejecting it against an obsolete model list. |