10c0cc007b
- Split agent crate into client/, model/, agent/ subdirs - Add billing.rs for token usage recording - Add sync.rs for upstream model sync - EmbedService: Qdrant-backed vector memory for semantic search - ChatService: wire EmbedService for memory lookup, passive skill awareness - ReAct loop: streamline with tokio::select! and proper error handling
30 lines
1.1 KiB
Rust
30 lines
1.1 KiB
Rust
pub mod client;
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pub mod qdrant;
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pub mod service;
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pub use client::{EmbedClient, EmbedPayload, EmbedVector, SearchResult};
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pub use qdrant::QdrantClient;
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pub use service::{EmbedService, Embeddable};
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pub async fn new_embed_client(config: &config::AppConfig) -> crate::Result<EmbedClient> {
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let base_url = config
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.get_embed_model_base_url()
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.map_err(|e| crate::AgentError::Internal(e.to_string()))?;
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let api_key = config
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.get_embed_model_api_key()
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.map_err(|e| crate::AgentError::Internal(e.to_string()))?;
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let qdrant_url = config
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.get_qdrant_url()
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.map_err(|e| crate::AgentError::Internal(e.to_string()))?;
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let qdrant_api_key = config.get_qdrant_api_key();
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let openai = rig::providers::openai::Client::builder()
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.api_key(&api_key)
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.base_url(&base_url)
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.build()
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.map_err(|e| crate::AgentError::Internal(format!("failed to build rig openai client: {}", e)))?;
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let qdrant = QdrantClient::new(&qdrant_url, qdrant_api_key.as_deref()).await?;
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Ok(EmbedClient::new(openai, qdrant))
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}
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