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palic/log classifier classification #5642

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palic/log classifier classification #5642

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190db59
[log classifier] add classification
PaliC Sep 11, 2024
245965c
[log classifier] add classification
PaliC Sep 11, 2024
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47 changes: 26 additions & 21 deletions aws/lambda/log-classifier/src/bedrock.rs
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Original file line number Diff line number Diff line change
Expand Up @@ -64,36 +64,25 @@ fn validate_output_in_log(ai_output: &str, log: &Log) -> Option<String> {
None
}

/// Makes a query to an AI model using the provided log snippet.
/// Makes a query to an AI model using the provided prompt.
///
/// This function creates a log snippet, sends it to two different AI models,
/// and validates the output. If a valid response is found, it is returned.
/// This function sends the prompt to two different AI models and validates the output.
/// If a valid response is found, it is returned.
///
/// # Arguments
///
/// * `log` - A reference to the Log structure containing the full log
/// * `error_line` - The line number of the error
/// * `num_lines` - The maximum number of lines to include in the log snippet
/// * `prompt` - The prompt to send to the AI models
///
/// # Returns
///
/// An Option<String> containing the validated AI response, or None if no valid response was found.
pub async fn make_query(log: &Log, error_line: &usize, num_lines: usize) -> Option<String> {
pub async fn make_query(log: &Log, prompt: &str) -> Option<String> {
let model_id_primary = "anthropic.claude-3-haiku-20240307-v1:0";
let model_id_secondary = "anthropic.claude-3-5-sonnet-20240620-v1:0";
let line_numbers = vec![*error_line];

let log_snippet = get_snippets(log, line_numbers, num_lines / 2, num_lines + 1);

// ensure length is 1 of the log_snippet
if log_snippet.len() != 1 {
return None;
}

let input_text = log_snippet.first().unwrap();

// Try the primary model
let response = make_bedrock_call(&input_text, model_id_primary).await;
let response = make_bedrock_call(prompt, model_id_primary).await;
let validation = validate_output_in_log(
&response
.unwrap()
Expand All @@ -112,7 +101,7 @@ pub async fn make_query(log: &Log, error_line: &usize, num_lines: usize) -> Opti
}

// If primary model fails, try the secondary model
let response = make_bedrock_call(&input_text, model_id_secondary).await;
let response = make_bedrock_call(prompt, model_id_secondary).await;
let validation = validate_output_in_log(
&response
.unwrap()
Expand All @@ -134,14 +123,13 @@ pub async fn make_query(log: &Log, error_line: &usize, num_lines: usize) -> Opti
}

async fn make_bedrock_call(
input_text: &String,
prompt: &str,
model_id: &str,
) -> Result<ConverseOutput, SdkError<ConverseError, Response>> {
let config = aws_config::load_defaults(BehaviorVersion::v2024_03_28()).await;
let client = aws_sdk_bedrockruntime::Client::new(&config);
let prompt = FIND_ERROR_LINE_PROMPT.replace("{{LOG_SNIPPET}}", input_text);

let content_block = ContentBlock::Text(prompt);
let content_block = ContentBlock::Text(prompt.to_string());

let prompt_message = Message::builder()
.content(content_block)
Expand All @@ -159,6 +147,23 @@ async fn make_bedrock_call(
Ok(response)
}

// rewri

fn generate_prompt_error_line(log: &Log, error_line: &str, num_lines: usize) -> Option<String> {
let log_snippet = get_snippets(log, line_numbers, num_lines / 2, num_lines + 1);

// ensure length is 1 of the log_snippet
if log_snippet.len() != 1 {
return None;
}

let input_text = log_snippet.first().unwrap();
let prompt = FIND_ERROR_LINE.replace("{{LOG_SNIPPET}}", input_text);
Some(prompt)

}


#[cfg(test)]
mod test {
use super::*;
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