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6 changes: 5 additions & 1 deletion .agents/skills/nemoclaw-contributor-update-docs/SKILL.md
Original file line number Diff line number Diff line change
Expand Up @@ -181,6 +181,10 @@ If the user invoked this skill for release prep, finish the release-specific doc
python3 scripts/docs-to-skills.py docs/ .agents/skills/ --prefix nemoclaw-user --doc-platform fern-mdx
```

Do not include the root `skills/` directory as an output target. That
directory is refreshed by a separate process and must not be updated by this
skill.

## Step 9: Build and Verify

After making changes, build the docs locally:
Expand Down Expand Up @@ -226,7 +230,7 @@ User says: "Catch up the docs for everything merged since v0.1.0."
4. Read the commit diffs and current doc pages.
5. Draft doc updates reflecting the source code changes in the commits following the style guide.
6. **Release prep only:** Determine the release label from the user-requested release version.
7. **Release prep only:** Run `python3 scripts/docs-to-skills.py docs/ .agents/skills/ skills/ --prefix nemoclaw-user --doc-platform fern-mdx`.
7. **Release prep only:** Run `python3 scripts/docs-to-skills.py docs/ .agents/skills/ --prefix nemoclaw-user --doc-platform fern-mdx`. Do not update root `skills/`.
8. Present the summary.
9. Build with `npm run docs` to verify.
10. **Release prep only:** Commit changes and open a pull request with the `area: docs`, `area: skills`, and corresponding `vX.Y.Z` release labels. Include a concise summary of the doc updates and a source summary that links each identified merged PR to its matching doc page. Include the PR number, affected doc page, links, and description of the doc change in this shape:
Expand Down
6 changes: 6 additions & 0 deletions .agents/skills/nemoclaw-user-configure-inference/SKILL.md
Original file line number Diff line number Diff line change
Expand Up @@ -175,6 +175,12 @@ NEMOCLAW_PROVIDER=ollama \
If `NEMOCLAW_MODEL` is not set, NemoClaw selects a default model based on available memory.
If `NEMOCLAW_MODEL` names a known bootstrap model (for example `qwen3.6:35b`) that does not fit the host's currently available GPU memory, NemoClaw warns and falls back to the largest known model that does fit.
Unknown or custom tags (any value the bootstrap registry has not seen) are still passed through; the Ollama runner validates the choice itself.
In interactive onboarding, registry-known installed tags that do not fit current GPU memory are filtered out of the installed-model menu.
If none of the installed registry-known tags fit, NemoClaw shows the starter-model choices and warns when even the smallest bootstrap tag may not fit.
After a selected model fails validation, NemoClaw excludes that tag from the next installed-model menu so pressing Enter cannot select the same failing model repeatedly.
When Ollama reports a loaded-model context length below `16384` and `NEMOCLAW_CONTEXT_WINDOW` is unset, NemoClaw raises the baked `contextWindow` to `16384` so the agent prompt and tool definitions fit better than the stock daemon default.
If the initial Ollama validation probe times out during a cold load, NemoClaw retries once with a 300-second probe budget.
This applies beyond DGX Spark, including tight-VRAM dGPU hosts where warm-up can spill from GPU to CPU.

`--yes` (or `NEMOCLAW_YES=1`) authorizes the Ollama model download without an interactive confirmation prompt.
Under `--non-interactive`, include `--yes` (or `NEMOCLAW_YES=1`) to authorize the download.
Expand Down
Original file line number Diff line number Diff line change
Expand Up @@ -297,6 +297,7 @@ When vLLM exposes runtime metadata such as `max_model_len`, NemoClaw uses that v
If vLLM is not running and your host matches a DGX Spark or DGX Station managed profile, NemoClaw shows the **Install vLLM** or **Start vLLM** entry by default.
Generic Linux NVIDIA GPU hosts still require `NEMOCLAW_EXPERIMENTAL=1` or `NEMOCLAW_PROVIDER=install-vllm` before the managed entry appears.
NemoClaw pulls the vLLM image, downloads model weights into `~/.cache/huggingface`, starts the `nemoclaw-vllm` container on `localhost:8000`, streams Hugging Face download progress, and polls `/v1/models` until the model is ready.
Managed DGX Spark and DGX Station profiles use the stable NGC `nvcr.io/nvidia/vllm:26.05.post1-py3` container image.
If Docker pull output stops making progress, a watchdog stops the stalled pull instead of failing slow but active downloads on a fixed wall-clock timeout.
If vLLM never becomes ready, NemoClaw prints a short tail of the vLLM container logs before exiting.
The first run can take 10 to 30 minutes.
Expand All @@ -307,7 +308,7 @@ Managed vLLM uses these profiles:
| Host profile | Default model |
|---|---|
| DGX Spark | `nvidia/Qwen3.6-35B-A3B-NVFP4` |
| DGX Station | `Qwen/Qwen3.6-27B-FP8` |
| DGX Station | `deepseek-ai/DeepSeek-V4-Flash` |
| Linux with an NVIDIA GPU | `nvidia/NVIDIA-Nemotron-3-Nano-4B-FP8` |

**Note:**
Expand Down Expand Up @@ -344,7 +345,8 @@ Recognized slugs are:

| Slug | Hugging Face model | Notes |
|---|---|---|
| `qwen3.6-27b` | `Qwen/Qwen3.6-27B-FP8` | Default on the DGX Station profile |
| `deepseek-v4-flash` | `deepseek-ai/DeepSeek-V4-Flash` | Default on the DGX Station profile |
| `qwen3.6-27b` | `Qwen/Qwen3.6-27B-FP8` | Supported override |
| `qwen3.6-35b-a3b-nvfp4` | `nvidia/Qwen3.6-35B-A3B-NVFP4` | Default on the DGX Spark profile |
| `nemotron-3-nano-4b` | `nvidia/NVIDIA-Nemotron-3-Nano-4B-FP8` | Default on the generic Linux + NVIDIA GPU profile |
| `deepseek-r1-distill-70b` | `deepseek-ai/DeepSeek-R1-Distill-Llama-70B` | Gated. Requires Hugging Face license acceptance |
Expand Down Expand Up @@ -377,13 +379,18 @@ NEMOCLAW_EXPERIMENTAL=1 nemoclaw onboard
Select **Local NVIDIA NIM [experimental]** from the provider list.
NemoClaw filters available models by GPU VRAM, pulls the NIM container image, starts it, and waits for it to become healthy before continuing.
On hosts with mixed NVIDIA GPU models, the preflight summary shows each detected GPU model and the total VRAM so you can confirm which device class the model selection used.
On Docker 29.x or containerd image-store hosts, NemoClaw resolves the host-platform manifest digest before pulling multi-architecture NIM images when the registry exposes an index.
It pulls `repo@digest` and retags the local image so NGC attestation metadata on other architectures does not block the selected platform.
If the registry does not expose a matching index, NemoClaw falls back to the tag pull.

NVIDIA hosts NIM container images on `nvcr.io`, and `docker pull` requires NGC registry authentication.
If Docker is not already logged in to `nvcr.io`, onboard prompts for an [NGC API key](https://org.ngc.nvidia.com/setup/api-key) and runs `docker login nvcr.io` over `--password-stdin` so the key is never written to disk or shell history.
The prompt masks the key during input and retries one time on a bad key before failing.
In non-interactive mode, onboard exits with login instructions if Docker is not already authenticated; run `docker login nvcr.io` yourself, then re-run `nemoclaw onboard --non-interactive`.
If `NGC_API_KEY` or `NVIDIA_API_KEY` is already exported, NemoClaw passes it into the managed NIM container through the process environment instead of command-line arguments.
If the NIM container exits before the health endpoint becomes ready, onboarding stops early and prints the last container log lines.
After NIM becomes healthy, NemoClaw reads `/v1/models` and uses the served model id for validation when it differs from the catalog name.
Unsafe served ids are rejected instead of being written into the sandbox config.

**Note:**

Expand Down
Original file line number Diff line number Diff line change
Expand Up @@ -20,7 +20,7 @@ For OpenClaw, it updates `agents.defaults.model.primary` and the matching provid
<AgentOnly variant="hermes">
Use `nemoclaw inference set` with the provider and model that match the upstream you want to use.
The command updates the OpenShell inference route and synchronizes the running agent config.
For Hermes, it updates `/sandbox/.hermes/config.yaml` (`model.default`, `model.base_url`, and `model.provider: custom`) without rebuilding or restarting Hermes.
For Hermes, it updates `/sandbox/.hermes/config.yaml` (`model.default`, `model.base_url`, `model.provider: custom`, API-family mode when needed, and the OpenShell proxy API-key placeholder) without rebuilding or restarting Hermes.
Pass `--sandbox <name>` when you do not want to use the default registered sandbox.
Under `nemoclaw`, pass `--sandbox <name>` when you have registered more than one Hermes sandbox.
</AgentOnly>
Expand Down Expand Up @@ -77,6 +77,16 @@ nemoclaw inference set --provider hermes-provider --model openai/gpt-5.4-mini

</AgentOnly>

### API Family Sync

Before patching the in-sandbox config, NemoClaw resolves the target route's API family: OpenAI chat completions, Anthropic Messages, or OpenAI Responses.
For OpenClaw, `inference set` syncs the provider API family and primary model reference into the running config.
For Hermes, `inference set` writes `model.api_mode: anthropic_messages` for Anthropic Messages routes, `model.api_mode: codex_responses` for OpenAI Responses routes, and removes `api_mode` for OpenAI-style chat-completions routes.
Hermes also keeps `model.api_key` on the OpenShell proxy placeholder so dashboard and API sessions continue to authenticate through the gateway after a route change.

Amazon Bedrock Runtime routes created through `compatible-anthropic-endpoint` are the exception.
When you switch within the same Bedrock Runtime compatible provider, NemoClaw keeps the route OpenAI-compatible and does not set Hermes to Anthropic Messages mode.

#### Switching from Responses API to Chat Completions

If onboarding selected `/v1/responses` but the agent fails at runtime, re-run onboarding so the wizard re-probes the endpoint and bakes the correct API path into the image.
Expand Down Expand Up @@ -148,6 +158,8 @@ NemoClaw ignores invalid values and bakes the default into the image.
For Local Ollama, onboarding loads the selected model first and uses Ollama's reported runtime context length when `NEMOCLAW_CONTEXT_WINDOW` is unset.
For local vLLM, onboarding uses the runtime `max_model_len` value when the server reports one and `NEMOCLAW_CONTEXT_WINDOW` is unset.
Use `NEMOCLAW_INFERENCE_INPUTS=text,image` only for a model that accepts image input through the selected provider.
During interactive onboarding, NemoClaw prompts for **Text only** or **Text + Image** when the discovered model name looks multimodal and `NEMOCLAW_INFERENCE_INPUTS` is not already valid.
Non-interactive onboarding uses the environment value or the default `text` setting.

```bash
export NEMOCLAW_CONTEXT_WINDOW=65536
Expand Down
Original file line number Diff line number Diff line change
Expand Up @@ -38,6 +38,12 @@ The common failure mode is:
This is different from a network or policy block.
`nemoclaw <name> status`, `nemoclaw <name> logs`, and `nemoclaw debug --quick` can all look healthy while tool dispatch still fails inside the conversation.

### Nemotron Managed Inference

For the `nvidia/nemotron-3-super-120b-a12b` managed inference route on `inference.local`, NemoClaw disables OpenClaw's native code-based tool search surface.
That route otherwise tends to generate invalid JavaScript for the `tool_search_code` helper, which creates `[tools] tool_search_code failed` noise even when normal turns succeed.
The agent still uses the structured tool-calling surface that the model handles correctly.

## Recommended Fix

For persistent NemoClaw use, start vLLM with auto tool choice and the parser that matches your model family, then rerun onboarding and select **Local vLLM [experimental]** or **Other OpenAI-compatible endpoint**.
Expand Down
Original file line number Diff line number Diff line change
Expand Up @@ -425,17 +425,19 @@ The auto-pair watcher automatically approves device pairing requests from recogn

| Aspect | Detail |
|---|---|
| Default | The watcher approves devices with `clientId` set to `openclaw-control-ui` or `clientMode` set to `webchat`. All other clients are rejected and logged. |
| What you can change | This is not a user-facing knob. The allowlist is defined in the entrypoint script. |
| Default | Startup auto-pairing and `connect`-time approval share one policy. NemoClaw approves devices with `clientId` set to `openclaw-control-ui` or `clientMode` set to `webchat` or `cli`, and only for `operator.pairing`, `operator.read`, and `operator.write` scopes. All other clients or scopes are rejected and logged. |

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⚠️ Potential issue | 🟡 Minor | ⚡ Quick win

Split into one sentence per line.

Line 428 contains three sentences.
The coding guidelines require one sentence per line in Markdown source to make diffs readable.

Suggested fix
-| Default | Startup auto-pairing and `connect`-time approval share one policy. NemoClaw approves devices with `clientId` set to `openclaw-control-ui` or `clientMode` set to `webchat` or `cli`, and only for `operator.pairing`, `operator.read`, and `operator.write` scopes. All other clients or scopes are rejected and logged. |
+| Default | Startup auto-pairing and `connect`-time approval share one policy.
+NemoClaw approves devices with `clientId` set to `openclaw-control-ui` or `clientMode` set to `webchat` or `cli`, and only for `operator.pairing`, `operator.read`, and `operator.write` scopes.
+All other clients or scopes are rejected and logged. |
🤖 Prompt for AI Agents
Verify each finding against current code. Fix only still-valid issues, skip the
rest with a brief reason, keep changes minimal, and validate.

In @.agents/skills/nemoclaw-user-configure-security/references/best-practices.md
at line 428, The Markdown table cell text beginning with "Default | Startup
auto-pairing and `connect`-time approval share one policy." contains three
sentences on one line; split it so each sentence lives on its own line in the
same table cell (e.g., one line for "Default | Startup auto-pairing and
`connect`-time approval share one policy.", one line for "NemoClaw approves
devices with `clientId` set to `openclaw-control-ui` or `clientMode` set to
`webchat` or `cli`.", and one line for "It only approves for `operator.pairing`,
`operator.read`, and `operator.write` scopes; all other clients or scopes are
rejected and logged.").

Source: Coding guidelines

| What you can change | This is not a user-facing knob. The allowlist is defined by NemoClaw's OpenClaw device-approval helper. |
| Risk if relaxed | Approving all device types without validation lets rogue or unexpected clients pair with the gateway unchallenged. |
| Recommendation | No action needed. The entrypoint handles this automatically. If you see `[auto-pair] rejected unknown client=...` in the logs, investigate the source of the unexpected connection. |
| Recommendation | No action needed. NemoClaw handles this automatically at startup and during `connect` for late scope upgrades. If you see `[auto-pair] rejected unknown client=...` in the logs, investigate the source of the unexpected connection. |

</AgentOnly>
<AgentOnly variant="hermes">

Hermes exposes an OpenAI-compatible API on the forwarded Hermes port and can optionally expose the native Hermes dashboard.
Do not publish those endpoints on shared or public networks unless you put them behind your own access controls.
NemoClaw still keeps provider credentials in OpenShell and routes model traffic through `inference.local`.
Generated Hermes runtime files use OpenShell resolver placeholders for managed-tool and messaging credentials.
Hermes startup rejects raw secret-shaped values in sandbox-visible environment or config fields, while allowing empty values, migration sentinels, OpenShell resolver placeholders, and expected Slack placeholder forms.

</AgentOnly>

Expand All @@ -460,7 +462,7 @@ The scanner intercepts Write, Edit, and similar tool calls targeting memory and
| Aspect | Detail |
|---|---|
| Default | Enabled. The plugin registers a `before_tool_call` hook that scans for 14 high-confidence secret patterns. |
| What it covers | Three classifiers, all enforced through `isMemoryPath()`: (1) absolute `MEMORY_PATH_SEGMENTS` such as `/.openclaw/memory/`, `/.openclaw/workspace/`, `/.openclaw/agents/`, `/.openclaw/skills/`, `/.openclaw/hooks/`, `/.openclaw/credentials/`, `/.openclaw/openclaw.json`, `/.nemoclaw/`; (2) canonical workspace basenames in `MEMORY_BASENAMES` (`IDENTITY.md`, `MEMORY.md`, `SOUL.md`, `USER.md`, `AGENTS.md`) matched regardless of the surrounding path; and (3) lexically-normalized workspace-relative writes matching `MEMORY_RELATIVE_PREFIXES` (`.openclaw/`, `.nemoclaw/`, `memory/`) or named workspace daily memory paths, for embedded-fallback mode where the host's path resolver is unavailable. |
| What it covers | Three path classifiers, all enforced through `isMemoryPath()`, plus credential-shaped text such as provider API keys, OpenAI project keys with `sk-proj-` prefixes, and Slack app-level `xapp-` tokens. The path classifiers are: (1) absolute `MEMORY_PATH_SEGMENTS` such as `/.openclaw/memory/`, `/.openclaw/workspace/`, `/.openclaw/agents/`, `/.openclaw/skills/`, `/.openclaw/hooks/`, `/.openclaw/credentials/`, `/.openclaw/openclaw.json`, `/.nemoclaw/`; (2) canonical workspace basenames in `MEMORY_BASENAMES` (`IDENTITY.md`, `MEMORY.md`, `SOUL.md`, `USER.md`, `AGENTS.md`) matched regardless of the surrounding path; and (3) lexically-normalized workspace-relative writes matching `MEMORY_RELATIVE_PREFIXES` (`.openclaw/`, `.nemoclaw/`, `memory/`) or named workspace daily memory paths, for embedded-fallback mode where the host's path resolver is unavailable. |

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⚠️ Potential issue | 🟡 Minor | ⚡ Quick win

Split into one sentence per line.

Line 465 contains two sentences.
The coding guidelines require one sentence per line in Markdown source to make diffs readable.

Suggested fix
-| What it covers | Three path classifiers, all enforced through `isMemoryPath()`, plus credential-shaped text such as provider API keys, OpenAI project keys with `sk-proj-` prefixes, and Slack app-level `xapp-` tokens. The path classifiers are: (1) absolute `MEMORY_PATH_SEGMENTS` such as `/.openclaw/memory/`, `/.openclaw/workspace/`, `/.openclaw/agents/`, `/.openclaw/skills/`, `/.openclaw/hooks/`, `/.openclaw/credentials/`, `/.openclaw/openclaw.json`, `/.nemoclaw/`; (2) canonical workspace basenames in `MEMORY_BASENAMES` (`IDENTITY.md`, `MEMORY.md`, `SOUL.md`, `USER.md`, `AGENTS.md`) matched regardless of the surrounding path; and (3) lexically-normalized workspace-relative writes matching `MEMORY_RELATIVE_PREFIXES` (`.openclaw/`, `.nemoclaw/`, `memory/`) or named workspace daily memory paths, for embedded-fallback mode where the host's path resolver is unavailable. |
+| What it covers | Three path classifiers, all enforced through `isMemoryPath()`, plus credential-shaped text such as provider API keys, OpenAI project keys with `sk-proj-` prefixes, and Slack app-level `xapp-` tokens.
+The path classifiers are: (1) absolute `MEMORY_PATH_SEGMENTS` such as `/.openclaw/memory/`, `/.openclaw/workspace/`, `/.openclaw/agents/`, `/.openclaw/skills/`, `/.openclaw/hooks/`, `/.openclaw/credentials/`, `/.openclaw/openclaw.json`, `/.nemoclaw/`; (2) canonical workspace basenames in `MEMORY_BASENAMES` (`IDENTITY.md`, `MEMORY.md`, `SOUL.md`, `USER.md`, `AGENTS.md`) matched regardless of the surrounding path; and (3) lexically-normalized workspace-relative writes matching `MEMORY_RELATIVE_PREFIXES` (`.openclaw/`, `.nemoclaw/`, `memory/`) or named workspace daily memory paths, for embedded-fallback mode where the host's path resolver is unavailable. |
🤖 Prompt for AI Agents
Verify each finding against current code. Fix only still-valid issues, skip the
rest with a brief reason, keep changes minimal, and validate.

In @.agents/skills/nemoclaw-user-configure-security/references/best-practices.md
at line 465, The paragraph describing path classifiers and credential patterns
must be split so each sentence is on its own line; update the Markdown around
the isMemoryPath() description so the sentence about three path classifiers and
credential-shaped text is one line and the following sentence enumerating the
three classifiers (referencing MEMORY_PATH_SEGMENTS, MEMORY_BASENAMES, and
MEMORY_RELATIVE_PREFIXES) is on its own line; ensure the three classifier
categories remain intact and keep the symbol names (isMemoryPath(),
MEMORY_PATH_SEGMENTS, MEMORY_BASENAMES, MEMORY_RELATIVE_PREFIXES) unchanged for
clarity.

Source: Coding guidelines

| What you can change | This is not a user-facing knob. The plugin enforces it automatically. |
| Risk if relaxed | Without scanning, the agent could persist API keys or tokens in memory files that survive across sessions and backups. |
| Recommendation | No action needed. If a write is blocked, the agent receives an actionable error listing the detected patterns. |
Expand Down
Original file line number Diff line number Diff line change
Expand Up @@ -13,6 +13,9 @@ The sandbox-side OpenClaw gateway token is generated at container startup and is
</AgentOnly>
<AgentOnly variant="hermes">
Hermes API credentials and provider credentials are managed through the same OpenShell provider boundary; generated Hermes runtime files are recreated during rebuilds.
Those files should contain resolver placeholders, not live provider credentials.
For managed tools and messaging, NemoClaw keeps host-side auth in OpenShell providers or host brokers and writes placeholder values into `/sandbox/.hermes/config.yaml`, `/sandbox/.hermes/.env`, and process environment entries visible to the sandbox.
Hermes startup rejects raw secret-shaped values in those sandbox-visible surfaces.
</AgentOnly>

## Where Credentials Live
Expand Down
4 changes: 2 additions & 2 deletions .agents/skills/nemoclaw-user-deploy-remote/SKILL.md
Original file line number Diff line number Diff line change
@@ -1,6 +1,6 @@
---
name: "nemoclaw-user-deploy-remote"
description: "Explains how to run NemoClaw on a remote GPU instance, including the deprecated Brev compatibility path and the preferred installer plus onboard flow. Use when deploying NemoClaw to a remote VM, onboarding a Brev instance, or migrating away from the legacy `nemoclaw deploy` wrapper. Trigger keywords - deploy nemoclaw remote gpu, nemoclaw brev cloud deployment, nemoclaw plugins, openclaw plugins, install openclaw plugin, nemoclaw onboard from dockerfile, nemoclaw brev web ui, nemoclaw getting started, brev quickstart, nvidia nemotron agent, nemoclaw sandbox hardening, container security, docker capabilities, process limits."
description: "Explains how to run NemoClaw on a remote GPU instance, including the deprecated Brev compatibility path and the preferred installer plus onboard flow. Use when deploying NemoClaw to a remote VM, onboarding a Brev instance, or migrating away from the legacy `nemoclaw deploy` wrapper. Trigger keywords - deploy nemoclaw remote gpu, nemoclaw brev cloud deployment, nemoclaw plugins, openclaw plugins, install openclaw plugin, nemoclaw onboard from dockerfile, nemoclaw dockerignore, nemoclaw brev web ui, nemoclaw getting started, brev quickstart, nvidia nemotron agent, nemoclaw sandbox hardening, container security, docker capabilities, process limits."
license: "Apache-2.0"
---

Expand Down Expand Up @@ -145,7 +145,7 @@ nemoclaw deploy <instance-name>

## References

- **Load [references/install-openclaw-plugins.md](references/install-openclaw-plugins.md)** when users ask how to install, build, or configure OpenClaw plugins under NemoClaw. Explains the difference between OpenClaw plugins and agent skills, and shows the current Dockerfile-based workflow for baking a plugin into a NemoClaw sandbox.
- **Load [references/install-openclaw-plugins.md](references/install-openclaw-plugins.md)** when users ask how to install, build, or configure OpenClaw plugins under NemoClaw. Explains the difference between OpenClaw plugins and agent skills, and shows the current Dockerfile-based workflow for baking a plugin into a NemoClaw sandbox, including `.dockerignore` handling for custom build contexts.
- **Load [references/brev-web-ui.md](references/brev-web-ui.md)** when a user wants to try NemoClaw without installing the CLI, or asks how to get started on Brev. Guides users through deploying NemoClaw with the Brev web UI.
- **Load [references/sandbox-hardening.md](references/sandbox-hardening.md)** when reviewing sandbox image security controls, auditing capability drops, or looking up the runtime resource limits. Includes the sandbox container image hardening reference, covering Docker capabilities and process limits.

Expand Down
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