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Update ollama and openai impls to use the rest embedder internally

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Louis Dureuil 2024-03-19 15:41:37 +01:00
parent 8708cbef25
commit ac52c857e8
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8 changed files with 394 additions and 779 deletions
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116
milli/src/vector/error.rs
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@ -2,9 +2,7 @@ use std::path::PathBuf;
use hf_hub::api::sync::ApiError;
use super::ollama::OllamaError;
use crate::error::FaultSource;
use crate::vector::openai::OpenAiError;
#[derive(Debug, thiserror::Error)]
#[error("Error while generating embeddings: {inner}")]
@ -52,43 +50,12 @@ pub enum EmbedErrorKind {
TensorValue(candle_core::Error),
#[error("could not run model: {0}")]
ModelForward(candle_core::Error),
#[error("could not reach OpenAI: {0}")]
OpenAiNetwork(ureq::Transport),
#[error("unexpected response from OpenAI: {0}")]
OpenAiUnexpected(ureq::Error),
#[error("could not authenticate against OpenAI: {0:?}")]
OpenAiAuth(Option<OpenAiError>),
#[error("sent too many requests to OpenAI: {0:?}")]
OpenAiTooManyRequests(Option<OpenAiError>),
#[error("received internal error from OpenAI: {0:?}")]
OpenAiInternalServerError(Option<OpenAiError>),
#[error("sent too many tokens in a request to OpenAI: {0:?}")]
OpenAiTooManyTokens(Option<OpenAiError>),
#[error("received unhandled HTTP status code {0} from OpenAI")]
OpenAiUnhandledStatusCode(u16),
#[error("attempt to embed the following text in a configuration where embeddings must be user provided: {0:?}")]
ManualEmbed(String),
#[error("could not initialize asynchronous runtime: {0}")]
OpenAiRuntimeInit(std::io::Error),
#[error("initializing web client for sending embedding requests failed: {0}")]
InitWebClient(reqwest::Error),
// Dedicated Ollama error kinds, might have to merge them into one cohesive error type for all backends.
#[error("unexpected response from Ollama: {0}")]
OllamaUnexpected(reqwest::Error),
#[error("sent too many requests to Ollama: {0}")]
OllamaTooManyRequests(OllamaError),
#[error("received internal error from Ollama: {0}")]
OllamaInternalServerError(OllamaError),
#[error("model not found. Meilisearch will not automatically download models from the Ollama library, please pull the model manually: {0}")]
OllamaModelNotFoundError(OllamaError),
#[error("received unhandled HTTP status code {0} from Ollama")]
OllamaUnhandledStatusCode(u16),
#[error("error serializing template context: {0}")]
RestTemplateContextSerialization(liquid::Error),
#[error(
"error rendering request template: {0}. Hint: available variable in the context: {{{{input}}}}'"
)]
RestTemplateError(liquid::Error),
#[error("model not found. Meilisearch will not automatically download models from the Ollama library, please pull the model manually: {0:?}")]
OllamaModelNotFoundError(Option<String>),
#[error("error deserialization the response body as JSON: {0}")]
RestResponseDeserialization(std::io::Error),
#[error("component `{0}` not found in path `{1}` in response: `{2}`")]
@ -128,77 +95,14 @@ impl EmbedError {
Self { kind: EmbedErrorKind::ModelForward(inner), fault: FaultSource::Runtime }
}
pub fn openai_network(inner: ureq::Transport) -> Self {
Self { kind: EmbedErrorKind::OpenAiNetwork(inner), fault: FaultSource::Runtime }
}
pub fn openai_unexpected(inner: ureq::Error) -> EmbedError {
Self { kind: EmbedErrorKind::OpenAiUnexpected(inner), fault: FaultSource::Bug }
}
pub(crate) fn openai_auth_error(inner: Option<OpenAiError>) -> EmbedError {
Self { kind: EmbedErrorKind::OpenAiAuth(inner), fault: FaultSource::User }
}
pub(crate) fn openai_too_many_requests(inner: Option<OpenAiError>) -> EmbedError {
Self { kind: EmbedErrorKind::OpenAiTooManyRequests(inner), fault: FaultSource::Runtime }
}
pub(crate) fn openai_internal_server_error(inner: Option<OpenAiError>) -> EmbedError {
Self { kind: EmbedErrorKind::OpenAiInternalServerError(inner), fault: FaultSource::Runtime }
}
pub(crate) fn openai_too_many_tokens(inner: Option<OpenAiError>) -> EmbedError {
Self { kind: EmbedErrorKind::OpenAiTooManyTokens(inner), fault: FaultSource::Bug }
}
pub(crate) fn openai_unhandled_status_code(code: u16) -> EmbedError {
Self { kind: EmbedErrorKind::OpenAiUnhandledStatusCode(code), fault: FaultSource::Bug }
}
pub(crate) fn embed_on_manual_embedder(texts: String) -> EmbedError {
Self { kind: EmbedErrorKind::ManualEmbed(texts), fault: FaultSource::User }
}
pub(crate) fn openai_runtime_init(inner: std::io::Error) -> EmbedError {
Self { kind: EmbedErrorKind::OpenAiRuntimeInit(inner), fault: FaultSource::Runtime }
}
pub fn openai_initialize_web_client(inner: reqwest::Error) -> Self {
Self { kind: EmbedErrorKind::InitWebClient(inner), fault: FaultSource::Runtime }
}
pub(crate) fn ollama_unexpected(inner: reqwest::Error) -> EmbedError {
Self { kind: EmbedErrorKind::OllamaUnexpected(inner), fault: FaultSource::Bug }
}
pub(crate) fn ollama_model_not_found(inner: OllamaError) -> EmbedError {
pub(crate) fn ollama_model_not_found(inner: Option<String>) -> EmbedError {
Self { kind: EmbedErrorKind::OllamaModelNotFoundError(inner), fault: FaultSource::User }
}
pub(crate) fn ollama_too_many_requests(inner: OllamaError) -> EmbedError {
Self { kind: EmbedErrorKind::OllamaTooManyRequests(inner), fault: FaultSource::Runtime }
}
pub(crate) fn ollama_internal_server_error(inner: OllamaError) -> EmbedError {
Self { kind: EmbedErrorKind::OllamaInternalServerError(inner), fault: FaultSource::Runtime }
}
pub(crate) fn ollama_unhandled_status_code(code: u16) -> EmbedError {
Self { kind: EmbedErrorKind::OllamaUnhandledStatusCode(code), fault: FaultSource::Bug }
}
pub(crate) fn rest_template_context_serialization(error: liquid::Error) -> EmbedError {
Self {
kind: EmbedErrorKind::RestTemplateContextSerialization(error),
fault: FaultSource::Bug,
}
}
pub(crate) fn rest_template_render(error: liquid::Error) -> EmbedError {
Self { kind: EmbedErrorKind::RestTemplateError(error), fault: FaultSource::User }
}
pub(crate) fn rest_response_deserialization(error: std::io::Error) -> EmbedError {
Self {
kind: EmbedErrorKind::RestResponseDeserialization(error),
@ -335,17 +239,6 @@ impl NewEmbedderError {
fault: FaultSource::Runtime,
}
}
pub fn ollama_could_not_determine_dimension(inner: EmbedError) -> NewEmbedderError {
Self {
kind: NewEmbedderErrorKind::CouldNotDetermineDimension(inner),
fault: FaultSource::User,
}
}
pub fn openai_invalid_api_key_format(inner: reqwest::header::InvalidHeaderValue) -> Self {
Self { kind: NewEmbedderErrorKind::InvalidApiKeyFormat(inner), fault: FaultSource::User }
}
}
#[derive(Debug, thiserror::Error)]
@ -392,7 +285,4 @@ pub enum NewEmbedderErrorKind {
CouldNotDetermineDimension(EmbedError),
#[error("loading model failed: {0}")]
LoadModel(candle_core::Error),
// openai
#[error("The API key passed to Authorization error was in an invalid format: {0}")]
InvalidApiKeyFormat(reqwest::header::InvalidHeaderValue),
}