mirror of
https://github.com/meilisearch/MeiliSearch
synced 2024-09-19 15:11:45 +02:00
Error changes
This commit is contained in:
Louis Dureuil
parent
ecee0c922f
commit
1a297c048e
@ -4,6 +4,7 @@ use std::path::PathBuf;
|
||||
use hf_hub::api::sync::ApiError;
|
||||
|
||||
use super::parsed_vectors::ParsedVectorsDiff;
|
||||
use super::rest::ConfigurationSource;
|
||||
use crate::error::FaultSource;
|
||||
use crate::{FieldDistribution, PanicCatched};
|
||||
|
||||
@ -45,48 +46,57 @@ pub struct EmbedError {
|
||||
|
||||
#[derive(Debug, thiserror::Error)]
|
||||
pub enum EmbedErrorKind {
|
||||
#[error("could not tokenize: {0}")]
|
||||
#[error("could not tokenize:\n - {0}")]
|
||||
Tokenize(Box<dyn std::error::Error + Send + Sync>),
|
||||
#[error("unexpected tensor shape: {0}")]
|
||||
#[error("unexpected tensor shape:\n - {0}")]
|
||||
TensorShape(candle_core::Error),
|
||||
#[error("unexpected tensor value: {0}")]
|
||||
#[error("unexpected tensor value:\n - {0}")]
|
||||
TensorValue(candle_core::Error),
|
||||
#[error("could not run model: {0}")]
|
||||
#[error("could not run model:\n - {0}")]
|
||||
ModelForward(candle_core::Error),
|
||||
#[error("attempt to embed the following text in a configuration where embeddings must be user provided: {0:?}")]
|
||||
#[error("attempt to embed the following text in a configuration where embeddings must be user provided:\n - `{0}`")]
|
||||
ManualEmbed(String),
|
||||
#[error("model not found. Meilisearch will not automatically download models from the Ollama library, please pull the model manually: {0:?}")]
|
||||
#[error("model not found. Meilisearch will not automatically download models from the Ollama library, please pull the model manually{}", option_info(.0.as_deref(), "server replied with "))]
|
||||
OllamaModelNotFoundError(Option<String>),
|
||||
#[error("error deserialization the response body as JSON: {0}")]
|
||||
#[error("error deserialization the response body as JSON:\n - {0}")]
|
||||
RestResponseDeserialization(std::io::Error),
|
||||
#[error("component `{0}` not found in path `{1}` in response: `{2}`")]
|
||||
RestResponseMissingEmbeddings(String, String, String),
|
||||
#[error("unexpected format of the embedding response: {0}")]
|
||||
RestResponseFormat(serde_json::Error),
|
||||
#[error("expected a response containing {0} embeddings, got only {1}")]
|
||||
RestResponseEmbeddingCount(usize, usize),
|
||||
#[error("could not authenticate against embedding server: {0:?}")]
|
||||
#[error("could not authenticate against embedding server{}", option_info(.0.as_deref(), "server replied with "))]
|
||||
RestUnauthorized(Option<String>),
|
||||
#[error("sent too many requests to embedding server: {0:?}")]
|
||||
#[error("sent too many requests to embedding server{}", option_info(.0.as_deref(), "server replied with "))]
|
||||
RestTooManyRequests(Option<String>),
|
||||
#[error("sent a bad request to embedding server: {0:?}")]
|
||||
RestBadRequest(Option<String>),
|
||||
#[error("received internal error from embedding server: {0:?}")]
|
||||
#[error("sent a bad request to embedding server{}{}",
|
||||
if ConfigurationSource::User == *.1 {
|
||||
"\n - Hint: check that the `request` in the embedder configuration matches the remote server's API"
|
||||
} else {
|
||||
""
|
||||
},
|
||||
option_info(.0.as_deref(), "server replied with "))]
|
||||
RestBadRequest(Option<String>, ConfigurationSource),
|
||||
#[error("received internal error HTTP {0} from embedding server{}", option_info(.1.as_deref(), "server replied with "))]
|
||||
RestInternalServerError(u16, Option<String>),
|
||||
#[error("received HTTP {0} from embedding server: {0:?}")]
|
||||
#[error("received unexpected HTTP {0} from embedding server{}", option_info(.1.as_deref(), "server replied with "))]
|
||||
RestOtherStatusCode(u16, Option<String>),
|
||||
#[error("could not reach embedding server: {0}")]
|
||||
#[error("could not reach embedding server:\n - {0}")]
|
||||
RestNetwork(ureq::Transport),
|
||||
#[error("was expected '{}' to be an object in query '{0}'", .1.join("."))]
|
||||
RestNotAnObject(serde_json::Value, Vec<String>),
|
||||
#[error("while embedding tokenized, was expecting embeddings of dimension `{0}`, got embeddings of dimensions `{1}`")]
|
||||
OpenAiUnexpectedDimension(usize, usize),
|
||||
#[error("error extracting embeddings from the response:\n - {0}")]
|
||||
RestExtractionError(String),
|
||||
#[error("was expecting embeddings of dimension `{0}`, got embeddings of dimensions `{1}`")]
|
||||
UnexpectedDimension(usize, usize),
|
||||
#[error("no embedding was produced")]
|
||||
MissingEmbedding,
|
||||
#[error(transparent)]
|
||||
PanicInThreadPool(#[from] PanicCatched),
|
||||
}
|
||||
|
||||
fn option_info(info: Option<&str>, prefix: &str) -> String {
|
||||
match info {
|
||||
Some(info) => format!("\n - {prefix}`{info}`"),
|
||||
None => String::new(),
|
||||
}
|
||||
}
|
||||
|
||||
impl EmbedError {
|
||||
pub fn tokenize(inner: Box<dyn std::error::Error + Send + Sync>) -> Self {
|
||||
Self { kind: EmbedErrorKind::Tokenize(inner), fault: FaultSource::Runtime }
|
||||
@ -119,28 +129,6 @@ impl EmbedError {
|
||||
}
|
||||
}
|
||||
|
||||
pub(crate) fn rest_response_missing_embeddings<S: AsRef<str>>(
|
||||
response: serde_json::Value,
|
||||
component: &str,
|
||||
response_field: &[S],
|
||||
) -> EmbedError {
|
||||
let response_field: Vec<&str> = response_field.iter().map(AsRef::as_ref).collect();
|
||||
let response_field = response_field.join(".");
|
||||
|
||||
Self {
|
||||
kind: EmbedErrorKind::RestResponseMissingEmbeddings(
|
||||
component.to_owned(),
|
||||
response_field,
|
||||
serde_json::to_string_pretty(&response).unwrap_or_default(),
|
||||
),
|
||||
fault: FaultSource::Undecided,
|
||||
}
|
||||
}
|
||||
|
||||
pub(crate) fn rest_response_format(error: serde_json::Error) -> EmbedError {
|
||||
Self { kind: EmbedErrorKind::RestResponseFormat(error), fault: FaultSource::Undecided }
|
||||
}
|
||||
|
||||
pub(crate) fn rest_response_embedding_count(expected: usize, got: usize) -> EmbedError {
|
||||
Self {
|
||||
kind: EmbedErrorKind::RestResponseEmbeddingCount(expected, got),
|
||||
@ -159,8 +147,14 @@ impl EmbedError {
|
||||
}
|
||||
}
|
||||
|
||||
pub(crate) fn rest_bad_request(error_response: Option<String>) -> EmbedError {
|
||||
Self { kind: EmbedErrorKind::RestBadRequest(error_response), fault: FaultSource::User }
|
||||
pub(crate) fn rest_bad_request(
|
||||
error_response: Option<String>,
|
||||
configuration_source: ConfigurationSource,
|
||||
) -> EmbedError {
|
||||
Self {
|
||||
kind: EmbedErrorKind::RestBadRequest(error_response, configuration_source),
|
||||
fault: FaultSource::User,
|
||||
}
|
||||
}
|
||||
|
||||
pub(crate) fn rest_internal_server_error(
|
||||
@ -184,22 +178,19 @@ impl EmbedError {
|
||||
Self { kind: EmbedErrorKind::RestNetwork(transport), fault: FaultSource::Runtime }
|
||||
}
|
||||
|
||||
pub(crate) fn rest_not_an_object(
|
||||
query: serde_json::Value,
|
||||
input_path: Vec<String>,
|
||||
) -> EmbedError {
|
||||
Self { kind: EmbedErrorKind::RestNotAnObject(query, input_path), fault: FaultSource::User }
|
||||
}
|
||||
|
||||
pub(crate) fn openai_unexpected_dimension(expected: usize, got: usize) -> EmbedError {
|
||||
pub(crate) fn rest_unexpected_dimension(expected: usize, got: usize) -> EmbedError {
|
||||
Self {
|
||||
kind: EmbedErrorKind::OpenAiUnexpectedDimension(expected, got),
|
||||
kind: EmbedErrorKind::UnexpectedDimension(expected, got),
|
||||
fault: FaultSource::Runtime,
|
||||
}
|
||||
}
|
||||
pub(crate) fn missing_embedding() -> EmbedError {
|
||||
Self { kind: EmbedErrorKind::MissingEmbedding, fault: FaultSource::Undecided }
|
||||
}
|
||||
|
||||
pub(crate) fn rest_extraction_error(error: String) -> EmbedError {
|
||||
Self { kind: EmbedErrorKind::RestExtractionError(error), fault: FaultSource::Runtime }
|
||||
}
|
||||
}
|
||||
|
||||
#[derive(Debug, thiserror::Error)]
|
||||
@ -290,10 +281,17 @@ impl NewEmbedderError {
|
||||
fault: FaultSource::Runtime,
|
||||
}
|
||||
}
|
||||
|
||||
pub(crate) fn rest_could_not_parse_template(message: String) -> NewEmbedderError {
|
||||
Self {
|
||||
kind: NewEmbedderErrorKind::CouldNotParseTemplate(message),
|
||||
fault: FaultSource::User,
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
#[derive(Debug, thiserror::Error)]
|
||||
#[error("could not open config at {filename:?}: {inner}")]
|
||||
#[error("could not open config at {filename}: {inner}")]
|
||||
pub struct OpenConfig {
|
||||
pub filename: PathBuf,
|
||||
pub inner: std::io::Error,
|
||||
@ -339,18 +337,20 @@ pub enum NewEmbedderErrorKind {
|
||||
UnsupportedModel(UnsupportedModel),
|
||||
#[error(transparent)]
|
||||
OpenTokenizer(OpenTokenizer),
|
||||
#[error("could not build weights from Pytorch weights: {0}")]
|
||||
#[error("could not build weights from Pytorch weights:\n - {0}")]
|
||||
PytorchWeight(candle_core::Error),
|
||||
#[error("could not build weights from Safetensor weights: {0}")]
|
||||
#[error("could not build weights from Safetensor weights:\n - {0}")]
|
||||
SafetensorWeight(candle_core::Error),
|
||||
#[error("could not spawn HG_HUB API client: {0}")]
|
||||
#[error("could not spawn HG_HUB API client:\n - {0}")]
|
||||
NewApiFail(ApiError),
|
||||
#[error("fetching file from HG_HUB failed: {0}")]
|
||||
#[error("fetching file from HG_HUB failed:\n - {0}")]
|
||||
ApiGet(ApiError),
|
||||
#[error("could not determine model dimensions: test embedding failed with {0}")]
|
||||
#[error("could not determine model dimensions:\n - test embedding failed with {0}")]
|
||||
CouldNotDetermineDimension(EmbedError),
|
||||
#[error("loading model failed: {0}")]
|
||||
#[error("loading model failed:\n - {0}")]
|
||||
LoadModel(candle_core::Error),
|
||||
#[error("{0}")]
|
||||
CouldNotParseTemplate(String),
|
||||
}
|
||||
|
||||
pub struct PossibleEmbeddingMistakes {
|
||||
|
||||
Loading…
Reference in New Issue
Block a user