通过 Aident Loadout 使用 Perplexityai Tools 的 Perplexityai Create Embeddings。执行前查看输入、输出、设置、价格和风险。
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 learnin…
input必填Input text to embed, encoded as a string or array of strings. Maximum 512 texts per request. Each input must not exceed 32K tokens. All inputs in a single request must not exceed 120,000 tokens combined. Empty strings are not allowed.
model必填stringThe embedding model to use. pplx-embed-v1-0.6b is smaller and faster, while pplx-embed-v1-4b is larger and more accurate.
dimensionsintegerNumber of dimensions for output embeddings (Matryoshka). Range: 128-1024 for pplx-embed-v1-0.6b, 128-2560 for pplx-embed-v1-4b. Defaults to full dimensions (1024 or 2560).
encoding_formatstringEncoding format for embeddings output.
data必填Data from the action execution
errorstringError if any occurred during the execution of the action
successful必填booleanWhether or not the action execution was successful or not
API 密钥连接。风险等级 2/5。
免费操作
目前没有已发布技能明确引用此操作。