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get rids of log in milli and add logs for the bucket sort

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Tamo 2024-02-06 10:49:23 +01:00 • committed by Louis Dureuil
parent f158e96fe7
commit e773dfa9ba
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14 changed files with 24 additions and 18 deletions
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14
milli/src/vector/openai.rs
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@ -173,12 +173,16 @@ impl Embedder {
let retry_duration = match result {
Ok(embeddings) => return Ok(embeddings),
Err(retry) => {
log::warn!("Failed: {}", retry.error);
tracing::warn!("Failed: {}", retry.error);
tokenized |= retry.must_tokenize();
retry.into_duration(attempt)
}
}?;
log::warn!("Attempt #{}, retrying after {}ms.", attempt, retry_duration.as_millis());
tracing::warn!(
"Attempt #{}, retrying after {}ms.",
attempt,
retry_duration.as_millis()
);
tokio::time::sleep(retry_duration).await;
}
@ -244,7 +248,7 @@ impl Embedder {
.map_err(EmbedError::openai_unexpected)
.map_err(Retry::retry_later)?;
log::warn!("OpenAI: input was too long, retrying on tokenized version. For best performance, limit the size of your prompt.");
tracing::warn!("OpenAI: input was too long, retrying on tokenized version. For best performance, limit the size of your prompt.");
return Err(Retry::retry_tokenized(EmbedError::openai_too_many_tokens(
error_response.error,
@ -266,7 +270,7 @@ impl Embedder {
client: &reqwest::Client,
) -> Result<Vec<Embeddings<f32>>, Retry> {
for text in texts {
log::trace!("Received prompt: {}", text.as_ref())
tracing::trace!("Received prompt: {}", text.as_ref())
}
let request = OpenAiRequest {
model: self.options.embedding_model.name(),
@ -289,7 +293,7 @@ impl Embedder {
.map_err(EmbedError::openai_unexpected)
.map_err(Retry::retry_later)?;
log::trace!("response: {:?}", response.data);
tracing::trace!("response: {:?}", response.data);
Ok(response
.data