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EmbeddingAgent

Defined in the embedding module.
Rust AI Agent SDK Agent for generating text embeddings. Provides embedding capabilities for text using AI embedding models, with support for batch processing and similarity calculations. # Supported Providers - OpenAI: text-embedding-3-small, text-embedding-3-large, text-embedding-ada-002 - Azure: azure/text-embedding-3-small - Cohere: cohere/embed-english-v3.0 - Voyage: voyage/voyage-3 - Mistral: mistral/mistral-embed

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Fields

NameTypeDescription
nameStringAgent name
modelStringModel name
configEmbeddingConfigEmbedding configuration
verboseboolVerbose output

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Methods

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new

fn new() -> EmbeddingAgentBuilder
Create a new builder

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simple

fn simple() -> Result<Self>
Create a simple embedding agent with default settings

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embed

async fn embed(&self, text: &str) -> Result<Vec<f32>>
Generate embedding for a single text. # Arguments * text - Text to embed # Returns Vector of floats representing the embedding Parameters:
NameType
text&str

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embed_batch

async fn embed_batch(&self, texts: &[&str]) -> Result<EmbeddingResult>
Generate embeddings for multiple texts. # Arguments * texts - Slice of texts to embed # Returns EmbeddingResult containing all embeddings Parameters:
NameType
texts&[&str]

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similarity

async fn similarity(&self, text1: &str, text2: &str) -> Result<f32>
Calculate cosine similarity between two texts. # Arguments * text1 - First text * text2 - Second text # Returns Cosine similarity score (0.0 to 1.0) Parameters:
NameType
text1&str
text2&str

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find_most_similar

async fn find_most_similar(
        &self,
        query: &str,
        candidates: &[&str],
        top_k: usize,
    ) -> Result<Vec<SimilarityResult>>
Find the most similar texts to a query. # Arguments * query - Query text * candidates - List of candidate texts to compare * top_k - Number of top results to return # Returns List of SimilarityResult sorted by score (descending) Parameters:
NameType
query&str
candidates&[&str]
top_kusize

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Source

View on GitHub

praisonai/src/embedding/mod.rs at line 229

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