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Integratie / Sales & Customer Support

Perplexity AI integratie

Perplexity AI provides conversational AI models for generating human-like text responses

Over Perplexity AI

Perplexityai delivers natural, conversational AI models for generating human-like text. Instantly get context-aware, high-quality responses for chat, search, or complex workflows.

Alle integraties
Categorie
Sales & Customer Support, AI & Machine Learning
Verbinding
API-sleutel
Type
Tool
Acties
9
Tags
library

Voorbeeldprompts

Wat je Growf kunt vragen te doen met Perplexity AI

  • Summarize the latest AI research papers
  • Generate a creative story about space travel
  • Explain quantum computing in simple terms
  • Provide a list of sources on climate change

Beschikbare acties

9 acties die je agents kunnen uitvoeren in Perplexity AI

  • Create Async Chat Completion

    Create Async Chat Completion (POST /v1/async/sonar). Submits an asynchronous chat completion request for long-running tasks. Returns immediately with a request ID that can be polled using the Get Async Chat Completion action. Only the 'sonar-deep-research' model is supported for async processing. A…

  • Create Chat Completion

    Perplexity Sonar Chat Completions (POST /v1/sonar). Generates web-grounded conversational AI responses with citations. Supports multiple Sonar models optimized for different use cases: - sonar: Fast, cost-effective for simple queries - sonar-pro: Enhanced quality for complex questions - sonar-reaso…

  • Create Contextualized Embeddings

    Create Contextualized Embeddings (POST /v1/contextualizedembeddings). Generates document-aware embeddings where chunks from the same document share context. Unlike standard embeddings, these recognize sequential relationships within documents, improving retrieval quality. Models: pplx-embed-context…

  • CreateEmbeddings

    Generate vector embeddings for independent texts (queries, sentences, documents). This action takes one or more input texts and generates vector embeddings using Perplexity AI's embedding models. Embeddings are useful for semantic search, similarity matching, and machine learning downstream tasks. …

  • Execute Agent

    Create Agent Response (POST /v1/agent). Orchestrates multi-step agentic workflows with built-in tools (web search, URL fetching, function calling), reasoning, and multi-model support. Streaming is not supported by this action. At least one of 'model', 'models', or 'preset' must be provided. Availab…

  • Get Async Chat Completion

    Get Async Chat Completion (GET /v1/async/sonar/{id}). Retrieves the result of an asynchronous chat completion request by its ID. Use this to poll for the result after creating an async job. The response includes the status and, when completed, the full completion.

  • List Async Chat Completions

    List Async Chat Completions (GET /v1/async/sonar). Retrieves a list of all asynchronous chat completion requests for the authenticated user. Use this to see the status of all your pending, completed, and failed async jobs.

  • List Models

    List Models (GET /v1/models). Lists models available for the Agent API. Returns model identifiers that can be used with the Agent endpoint. The response follows the OpenAI List Models format for compatibility. This is a public endpoint that does not require authentication.

  • Perplexity Search (Raw Results)

    Search the Web (POST /search). Returns raw, ranked web search results directly from Perplexity's index without LLM processing. Faster and cheaper than chat completions when you need raw results. Supports filtering by domain, date, language, country, and recency. Max 20 results per request. Importan…

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