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
55 lines
1.5 KiB
Rust
55 lines
1.5 KiB
Rust
use thiserror::Error;
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#[derive(Error, Debug)]
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pub enum AgentError {
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#[error("openai error: {0}")]
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OpenAi(String),
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#[error("qdrant error: {0}")]
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Qdrant(String),
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#[error("internal error: {0}")]
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Internal(String),
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#[error("not found: {0}")]
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NotFound(String),
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/// The task exceeded its timeout limit.
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#[error("task {task_id} timed out after {seconds}s")]
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Timeout { task_id: i64, seconds: u64 },
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/// The agent has been rate-limited; retry after the indicated delay.
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#[error("rate limited, retry after {retry_after_secs}s")]
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RateLimited { retry_after_secs: u64 },
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/// A transient error that can be retried.
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#[error("retryable error (attempt {attempt}): {message}")]
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Retryable { attempt: u32, message: String },
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/// The requested tool is not registered in the tool registry.
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#[error("tool not found: {tool}")]
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ToolNotFound { tool: String },
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/// A tool execution failed.
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#[error("tool '{tool}' execution failed: {cause}")]
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ToolExecutionFailed { tool: String, cause: String },
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/// The request contains invalid input.
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#[error("invalid input in '{field}': {reason}")]
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InvalidInput { field: String, reason: String },
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}
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pub type Result<T> = std::result::Result<T, AgentError>;
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impl From<qdrant_client::QdrantError> for AgentError {
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fn from(e: qdrant_client::QdrantError) -> Self {
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AgentError::Qdrant(e.to_string())
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}
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}
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impl From<sea_orm::DbErr> for AgentError {
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fn from(e: sea_orm::DbErr) -> Self {
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AgentError::Internal(e.to_string())
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}
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}
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