Files
ImageApi/src/ai/daily_summary_job.rs
Cameron af35a996a3 Cleanup unused message embedding code
Fixup some warnings
2026-01-14 13:33:36 -05:00

404 lines
13 KiB
Rust

use anyhow::Result;
use chrono::{NaiveDate, Utc};
use opentelemetry::KeyValue;
use opentelemetry::trace::{Span, Status, TraceContextExt, Tracer};
use std::collections::HashMap;
use std::sync::{Arc, Mutex};
use tokio::time::sleep;
use crate::ai::{OllamaClient, SmsApiClient, SmsMessage};
use crate::database::{DailySummaryDao, InsertDailySummary};
use crate::otel::global_tracer;
/// Strip boilerplate prefixes and common phrases from summaries before embedding.
/// This improves embedding diversity by removing structural similarity.
pub fn strip_summary_boilerplate(summary: &str) -> String {
let mut text = summary.trim().to_string();
// Remove markdown headers
while text.starts_with('#') {
if let Some(pos) = text.find('\n') {
text = text[pos..].trim_start().to_string();
} else {
// Single line with just headers, try to extract content after #s
text = text.trim_start_matches('#').trim().to_string();
break;
}
}
// Remove "Summary:" prefix variations (with optional markdown bold)
let prefixes = [
"**Summary:**",
"**Summary**:",
"*Summary:*",
"Summary:",
"**summary:**",
"summary:",
];
for prefix in prefixes {
if text.to_lowercase().starts_with(&prefix.to_lowercase()) {
text = text[prefix.len()..].trim_start().to_string();
break;
}
}
// Remove common opening phrases that add no semantic value
let opening_phrases = [
"Today, Melissa and I discussed",
"Today, Amanda and I discussed",
"Today Melissa and I discussed",
"Today Amanda and I discussed",
"Melissa and I discussed",
"Amanda and I discussed",
"Today, I discussed",
"Today I discussed",
"The conversation covered",
"This conversation covered",
"In this conversation,",
"During this conversation,",
];
for phrase in opening_phrases {
if text.to_lowercase().starts_with(&phrase.to_lowercase()) {
text = text[phrase.len()..].trim_start().to_string();
// Remove leading punctuation/articles after stripping phrase
text = text
.trim_start_matches([',', ':', '-'])
.trim_start()
.to_string();
break;
}
}
// Remove any remaining leading markdown bold markers
if text.starts_with("**")
&& let Some(end) = text[2..].find("**")
{
// Keep the content between ** but remove the markers
let bold_content = &text[2..2 + end];
text = format!("{}{}", bold_content, &text[4 + end..]);
}
text.trim().to_string()
}
/// Generate and embed daily conversation summaries for a date range
/// Default: August 2024 ±30 days (July 1 - September 30, 2024)
pub async fn generate_daily_summaries(
contact: &str,
start_date: Option<NaiveDate>,
end_date: Option<NaiveDate>,
ollama: &OllamaClient,
sms_client: &SmsApiClient,
summary_dao: Arc<Mutex<Box<dyn DailySummaryDao>>>,
) -> Result<()> {
let tracer = global_tracer();
// Get current context (empty in background task) and start span with it
let current_cx = opentelemetry::Context::current();
let mut span = tracer.start_with_context("ai.daily_summary.generate_batch", &current_cx);
span.set_attribute(KeyValue::new("contact", contact.to_string()));
// Create context with this span for child operations
let parent_cx = current_cx.with_span(span);
// Default to August 2024 ±30 days
let start = start_date.unwrap_or_else(|| NaiveDate::from_ymd_opt(2024, 7, 1).unwrap());
let end = end_date.unwrap_or_else(|| NaiveDate::from_ymd_opt(2024, 9, 30).unwrap());
parent_cx
.span()
.set_attribute(KeyValue::new("start_date", start.to_string()));
parent_cx
.span()
.set_attribute(KeyValue::new("end_date", end.to_string()));
parent_cx.span().set_attribute(KeyValue::new(
"date_range_days",
(end - start).num_days() + 1,
));
log::info!("========================================");
log::info!("Starting daily summary generation for {}", contact);
log::info!(
"Date range: {} to {} ({} days)",
start,
end,
(end - start).num_days() + 1
);
log::info!("========================================");
// Fetch all messages for the contact in the date range
log::info!("Fetching messages for date range...");
let _start_timestamp = start.and_hms_opt(0, 0, 0).unwrap().and_utc().timestamp();
let _end_timestamp = end.and_hms_opt(23, 59, 59).unwrap().and_utc().timestamp();
let all_messages = sms_client.fetch_all_messages_for_contact(contact).await?;
// Filter to date range and group by date
let mut messages_by_date: HashMap<NaiveDate, Vec<SmsMessage>> = HashMap::new();
for msg in all_messages {
let msg_dt = chrono::DateTime::from_timestamp(msg.timestamp, 0);
if let Some(dt) = msg_dt {
let date = dt.date_naive();
if date >= start && date <= end {
messages_by_date.entry(date).or_default().push(msg);
}
}
}
log::info!(
"Grouped messages into {} days with activity",
messages_by_date.len()
);
if messages_by_date.is_empty() {
log::warn!("No messages found in date range");
return Ok(());
}
// Sort dates for ordered processing
let mut dates: Vec<NaiveDate> = messages_by_date.keys().cloned().collect();
dates.sort();
let total_days = dates.len();
let mut processed = 0;
let mut skipped = 0;
let mut failed = 0;
log::info!("Processing {} days with messages...", total_days);
for (idx, date) in dates.iter().enumerate() {
let messages = messages_by_date.get(date).unwrap();
let date_str = date.format("%Y-%m-%d").to_string();
// Check if summary already exists
{
let mut dao = summary_dao.lock().expect("Unable to lock DailySummaryDao");
let otel_context = opentelemetry::Context::new();
if dao
.summary_exists(&otel_context, &date_str, contact)
.unwrap_or(false)
{
skipped += 1;
if idx % 10 == 0 {
log::info!(
"Progress: {}/{} ({} processed, {} skipped)",
idx + 1,
total_days,
processed,
skipped
);
}
continue;
}
}
// Generate summary for this day
match generate_and_store_daily_summary(
&parent_cx,
date,
contact,
messages,
ollama,
summary_dao.clone(),
)
.await
{
Ok(_) => {
processed += 1;
log::info!(
"✓ {}/{}: {} ({} messages)",
idx + 1,
total_days,
date_str,
messages.len()
);
}
Err(e) => {
failed += 1;
log::error!("✗ Failed to process {}: {:?}", date_str, e);
}
}
// Rate limiting: sleep 500ms between summaries
if idx < total_days - 1 {
sleep(std::time::Duration::from_millis(500)).await;
}
// Progress logging every 10 days
if idx % 10 == 0 && idx > 0 {
log::info!(
"Progress: {}/{} ({} processed, {} skipped, {} failed)",
idx + 1,
total_days,
processed,
skipped,
failed
);
}
}
log::info!("========================================");
log::info!("Daily summary generation complete!");
log::info!(
"Processed: {}, Skipped: {}, Failed: {}",
processed,
skipped,
failed
);
log::info!("========================================");
// Record final metrics in span
parent_cx
.span()
.set_attribute(KeyValue::new("days_processed", processed as i64));
parent_cx
.span()
.set_attribute(KeyValue::new("days_skipped", skipped as i64));
parent_cx
.span()
.set_attribute(KeyValue::new("days_failed", failed as i64));
parent_cx
.span()
.set_attribute(KeyValue::new("total_days", total_days as i64));
if failed > 0 {
parent_cx
.span()
.set_status(Status::error(format!("{} days failed to process", failed)));
} else {
parent_cx.span().set_status(Status::Ok);
}
Ok(())
}
/// Generate and store a single day's summary
async fn generate_and_store_daily_summary(
parent_cx: &opentelemetry::Context,
date: &NaiveDate,
contact: &str,
messages: &[SmsMessage],
ollama: &OllamaClient,
summary_dao: Arc<Mutex<Box<dyn DailySummaryDao>>>,
) -> Result<()> {
let tracer = global_tracer();
let mut span = tracer.start_with_context("ai.daily_summary.generate_single", parent_cx);
span.set_attribute(KeyValue::new("date", date.to_string()));
span.set_attribute(KeyValue::new("contact", contact.to_string()));
span.set_attribute(KeyValue::new("message_count", messages.len() as i64));
// Format messages for LLM
let messages_text: String = messages
.iter()
.take(200) // Limit to 200 messages per day to avoid token overflow
.map(|m| {
if m.is_sent {
format!("Me: {}", m.body)
} else {
format!("{}: {}", m.contact, m.body)
}
})
.collect::<Vec<_>>()
.join("\n");
let weekday = date.format("%A");
let prompt = format!(
r#"Summarize this day's conversation between me and {}.
CRITICAL FORMAT RULES:
- Do NOT start with "Based on the conversation..." or "Here is a summary..." or similar preambles
- Do NOT repeat the date at the beginning
- Start DIRECTLY with the content - begin with a person's name or action
- Write in past tense, as if recording what happened
NARRATIVE (3-5 sentences):
- What specific topics, activities, or events were discussed?
- What places, people, or organizations were mentioned?
- What plans were made or decisions discussed?
- Clearly distinguish between what "I" did versus what {} did
KEYWORDS (comma-separated):
5-10 specific keywords that capture this conversation's unique content:
- Proper nouns (people, places, brands)
- Specific activities ("drum corps audition" not just "music")
- Distinctive terms that make this day unique
Date: {} ({})
Messages:
{}
YOUR RESPONSE (follow this format EXACTLY):
Summary: [Start directly with content, NO preamble]
Keywords: [specific, unique terms]"#,
contact,
contact,
date.format("%B %d, %Y"),
weekday,
messages_text
);
// Generate summary with LLM
let summary = ollama
.generate(
&prompt,
Some("You are a conversation summarizer. Create clear, factual summaries with precise subject attribution AND extract distinctive keywords. Focus on specific, unique terms that differentiate this conversation from others."),
)
.await?;
log::debug!(
"Generated summary for {}: {}",
date,
summary.chars().take(100).collect::<String>()
);
span.set_attribute(KeyValue::new("summary_length", summary.len() as i64));
// Strip boilerplate before embedding to improve vector diversity
let stripped_summary = strip_summary_boilerplate(&summary);
log::debug!(
"Stripped summary for embedding: {}",
stripped_summary.chars().take(100).collect::<String>()
);
// Embed the stripped summary (store original summary in DB)
let embedding = ollama.generate_embedding(&stripped_summary).await?;
span.set_attribute(KeyValue::new(
"embedding_dimensions",
embedding.len() as i64,
));
// Store in database
let insert = InsertDailySummary {
date: date.format("%Y-%m-%d").to_string(),
contact: contact.to_string(),
summary: summary.trim().to_string(),
message_count: messages.len() as i32,
embedding,
created_at: Utc::now().timestamp(),
// model_version: "nomic-embed-text:v1.5".to_string(),
model_version: "mxbai-embed-large:335m".to_string(),
};
// Create context from current span for DB operation
let child_cx = opentelemetry::Context::current_with_span(span);
let mut dao = summary_dao.lock().expect("Unable to lock DailySummaryDao");
let result = dao
.store_summary(&child_cx, insert)
.map_err(|e| anyhow::anyhow!("Failed to store summary: {:?}", e));
match &result {
Ok(_) => child_cx.span().set_status(Status::Ok),
Err(e) => child_cx.span().set_status(Status::error(e.to_string())),
}
result?;
Ok(())
}