mirror of
https://github.com/perstarkse/minne.git
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error handling, and setting result as return
This commit is contained in:
43
src/error.rs
43
src/error.rs
@@ -1,10 +1,11 @@
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use async_openai::error::OpenAIError;
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use axum::{http::StatusCode, response::IntoResponse, Json};
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use serde_json::json;
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use thiserror::Error;
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use tokio::task::JoinError;
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use crate::{ingress::types::ingress_input::IngressContentError, rabbitmq::RabbitMQError};
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/// Error types for processing `TextContent`.
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#[derive(Error, Debug)]
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pub enum ProcessingError {
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#[error("SurrealDb error: {0}")]
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@@ -37,3 +38,43 @@ pub enum IngressConsumerError {
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#[error("Ingress content error: {0}")]
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IngressContent(#[from] IngressContentError),
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}
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#[derive(Error, Debug)]
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pub enum ApiError {
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#[error("Processing error: {0}")]
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ProcessingError(#[from] ProcessingError),
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#[error("Ingress content error: {0}")]
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IngressContentError(#[from] IngressContentError),
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#[error("Publishing error: {0}")]
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PublishingError(String),
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#[error("Database error: {0}")]
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DatabaseError(String),
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#[error("Query error: {0}")]
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QueryError(String),
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#[error("RabbitMQ error: {0}")]
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RabbitMQError(#[from] RabbitMQError),
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}
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impl IntoResponse for ApiError {
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fn into_response(self) -> axum::response::Response {
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let (status, error_message) = match &self {
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ApiError::ProcessingError(_) => (StatusCode::INTERNAL_SERVER_ERROR, self.to_string()),
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ApiError::PublishingError(_) => (StatusCode::INTERNAL_SERVER_ERROR, self.to_string()),
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ApiError::DatabaseError(_) => (StatusCode::INTERNAL_SERVER_ERROR, self.to_string()),
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ApiError::QueryError(_) => (StatusCode::BAD_REQUEST, self.to_string()),
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ApiError::IngressContentError(_) => {
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(StatusCode::INTERNAL_SERVER_ERROR, self.to_string())
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}
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ApiError::RabbitMQError(_) => (StatusCode::INTERNAL_SERVER_ERROR, self.to_string()),
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};
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(
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status,
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Json(json!({
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"error": error_message,
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"status": "error"
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})),
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)
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.into_response()
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}
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}
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@@ -1,41 +1,25 @@
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use crate::{
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error::ApiError,
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ingress::types::ingress_input::{create_ingress_objects, IngressInput},
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rabbitmq::publisher::RabbitMQProducer,
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storage::db::SurrealDbClient,
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};
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use axum::{http::StatusCode, response::IntoResponse, Extension, Json};
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use std::sync::Arc;
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use tracing::{error, info};
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use tracing::info;
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pub async fn ingress_handler(
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Extension(producer): Extension<Arc<RabbitMQProducer>>,
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Extension(db_client): Extension<Arc<SurrealDbClient>>,
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Json(input): Json<IngressInput>,
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) -> impl IntoResponse {
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) -> Result<impl IntoResponse, ApiError> {
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info!("Received input: {:?}", input);
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match create_ingress_objects(input, &db_client).await {
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Ok(objects) => {
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for object in objects {
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match producer.publish(&object).await {
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Ok(_) => {
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info!("Message published successfully");
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}
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Err(e) => {
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error!("Failed to publish message: {:?}", e);
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return (
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StatusCode::INTERNAL_SERVER_ERROR,
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"Failed to publish message",
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)
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.into_response();
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}
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}
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}
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StatusCode::OK.into_response()
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}
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Err(e) => {
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error!("Failed to process input: {:?}", e);
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(StatusCode::INTERNAL_SERVER_ERROR, "Failed to process input").into_response()
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}
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let ingress_objects = create_ingress_objects(input, &db_client).await?;
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for object in ingress_objects {
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producer.publish(&object).await?;
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}
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Ok(StatusCode::OK)
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}
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@@ -1,8 +1,12 @@
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use crate::storage::db::SurrealDbClient;
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use axum::{http::StatusCode, response::IntoResponse, Extension, Json};
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use crate::{
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error::ApiError,
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retrieval::vector::find_items_by_vector_similarity,
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storage::{db::SurrealDbClient, types::knowledge_entity::KnowledgeEntity},
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};
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use axum::{response::IntoResponse, Extension, Json};
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use serde::Deserialize;
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use std::sync::Arc;
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use tracing::{error, info};
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use tracing::info;
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#[derive(Debug, Deserialize)]
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pub struct QueryInput {
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@@ -12,6 +16,18 @@ pub struct QueryInput {
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pub async fn query_handler(
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Extension(db_client): Extension<Arc<SurrealDbClient>>,
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Json(query): Json<QueryInput>,
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) -> impl IntoResponse {
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) -> Result<impl IntoResponse, ApiError> {
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info!("Received input: {:?}", query);
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let openai_client = async_openai::Client::new();
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let closest_items: Vec<KnowledgeEntity> = find_items_by_vector_similarity(
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10,
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query.query,
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&db_client,
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"knowledge_entity".to_string(),
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&openai_client,
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)
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.await?;
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Ok(format!("{:?}", closest_items))
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}
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