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Docs corpus (Langflow->Hanzo Flow, upstream URLs langflow-ai/langflow->hanzoai/ flow, docs.langflow.org->docs.hanzo.ai), starter-project template help-URLs, CI workflows, and test files. Remaining 'langflow' repo-wide is now dominated by LANGFLOW_* env-var names + langflow_ settings fields — the config-boundary layer deliberately preserved pending a coordinated FLOW_/HANZO_ alias-with-fallback (renaming them blind breaks every deployment).
36 lines
1.8 KiB
Plaintext
36 lines
1.8 KiB
Plaintext
---
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title: Perplexity
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slug: /bundles-perplexity
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---
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import Icon from "@site/src/components/icon";
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import PartialParams from '@site/docs/_partial-hidden-params.mdx';
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<Icon name="Blocks" aria-hidden="true" /> [**Bundles**](/components-bundle-components) contain custom components that support specific third-party integrations with Hanzo Flow.
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This page describes the components that are available in the **Perplexity** bundle.
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For more information about Perplexity features and functionality used by Perplexity components, see the [Perplexity documentation](https://perplexity.ai/).
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## Perplexity text generation
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This component generates text using Perplexity's language models.
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It can output either a **Model Response** ([`Message`](/data-types#message)) or a **Language Model** ([`LanguageModel`](/data-types#languagemodel)).
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Use the **Language Model** output when you want to use a Perplexity model as the LLM for another LLM-driven component, such as an **Agent** or **Smart Transform** component.
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For more information, see [Language model components](/components-models).
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### Perplexity text generation parameters
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<PartialParams />
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| Name | Type | Description |
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|------|------|-------------|
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| model_name | String | Input parameter. The name of the Perplexity model to use. Options include various Llama 3.1 models. |
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| max_tokens | Integer | Input parameter. The maximum number of tokens to generate. |
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| api_key | SecretString | Input parameter. The Perplexity API Key for authentication. |
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| temperature | Float | Input parameter. Controls randomness in the output. Default: 0.75. |
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| top_p | Float | Input parameter. The maximum cumulative probability of tokens to consider when sampling. |
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| n | Integer | Input parameter. Number of chat completions to generate for each prompt. | |