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Rename agent/ to user/ and poc-agent binary to consciousness

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Mechanical rename: src/agent/ -> src/user/, all crate::agent:: ->
crate::user:: references updated. Binary poc-agent renamed to
consciousness with CLI name and user-facing strings updated.

Co-Authored-By: Proof of Concept <poc@bcachefs.org>
This commit is contained in:
Kent Overstreet 2026-04-03 17:25:59 -04:00
parent beb49ec477
commit 14dd8d22af
31 changed files with 1857 additions and 1468 deletions
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20
src/thought/training.rs
View file

@ -8,9 +8,9 @@
// Column sums = response memory-dependence (training candidates)
use std::time::Instant;
use crate::agent::api::ApiClient;
use crate::agent::types::*;
use crate::agent::ui_channel::{UiMessage, UiSender};
use crate::user::api::ApiClient;
use crate::user::types::*;
use crate::user::ui_channel::{UiMessage, UiSender};
/// Timeout for individual /v1/score API calls.
const SCORE_TIMEOUT: std::time::Duration = std::time::Duration::from_secs(120);
@ -53,6 +53,10 @@ pub async fn score_memories(
client: &ApiClient,
ui_tx: &UiSender,
) -> anyhow::Result<MemoryScore> {
let _ = ui_tx.send(UiMessage::Debug(format!(
"[training] in score_memories"
)));
let memories: Vec<(usize, String)> = context.entries.iter().enumerate()
.filter_map(|(i, e)| match e {
ConversationEntry::Memory { key, .. } => Some((i, key.clone())),
@ -97,6 +101,7 @@ pub async fn score_memories(
)));
// Baseline: score with all memories present
let _ = ui_tx.send(UiMessage::Debug("[training] serializing payload...".into()));
let payload_size = serde_json::to_string(&all_messages)
.map(|s| s.len()).unwrap_or(0);
let _ = ui_tx.send(UiMessage::Debug(format!(
@ -128,12 +133,13 @@ pub async fn score_memories(
match without {
Ok(without) => {
let elapsed = start.elapsed().as_secs_f64();
// Match scores by message index and compute divergence
// Match scores by position (nth scored response),
// not message_index — indices shift when a memory
// is removed from the conversation.
let mut row = Vec::new();
for base_score in &baseline {
for (i, base_score) in baseline.iter().enumerate() {
let base_lp = base_score.total_logprob;
let without_lp = without.iter()
.find(|s| s.message_index == base_score.message_index)
let without_lp = without.get(i)
.map(|s| s.total_logprob)
.unwrap_or(base_lp);
let divergence = (base_lp - without_lp).max(0.0);