> For clean Markdown of any page, append .md to the page URL.
> For a complete documentation index, see https://docs.nvidia.com/nemo/guardrails/llms.txt.
> For full documentation content, see https://docs.nvidia.com/nemo/guardrails/llms-full.txt.
> For AI client integration (Claude Code, Cursor, etc.), connect to the MCP server at https://docs.nvidia.com/nemo/guardrails/_mcp/server.

# nemoguardrails.integrations.langchain.providers.huggingface.pipeline

## Module Contents

### Classes

| Name                                                                                                                                   | Description                                                                 |
| -------------------------------------------------------------------------------------------------------------------------------------- | --------------------------------------------------------------------------- |
| [`HuggingFacePipelineCompatible`](#nemoguardrails-integrations-langchain-providers-huggingface-pipeline-HuggingFacePipelineCompatible) | Hackish way to add backward-compatibility functions to the Langchain class. |

### API

```python
class nemoguardrails.integrations.langchain.providers.huggingface.pipeline.HuggingFacePipelineCompatible()
```

**Bases:** `HuggingFacePipeline`

Hackish way to add backward-compatibility functions to the Langchain class.
TODO: Planning to add this fix directly to Langchain repo.

```python
nemoguardrails.integrations.langchain.providers.huggingface.pipeline.HuggingFacePipelineCompatible._acall(
    prompt: str,
    stop: typing.Optional[typing.List[str]] = None,
    run_manager: typing.Optional[langchain_core.callbacks.manager.AsyncCallbackManagerForLLMRun] = None,
    kwargs: typing.Any = {}
) -> str
```

async

Hackish way to add async support

```python
nemoguardrails.integrations.langchain.providers.huggingface.pipeline.HuggingFacePipelineCompatible._call(
    prompt: str,
    stop: typing.Optional[typing.List[str]] = None,
    run_manager: typing.Optional[langchain_core.callbacks.manager.CallbackManagerForLLMRun] = None,
    kwargs: typing.Any = {}
) -> str
```

Hackish way to perform a single llm call since Langchain dropped support