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fix(agent): use config max_tool_iterations, add memory relevance filtering, rebalance search weights

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Three fixes for conversation quality issues:

1. loop_.rs and channels now read max_tool_iterations from AgentConfig
   instead of using a hardcoded constant of 10, making it configurable.

2. Memory recall now filters entries below a configurable
   min_relevance_score threshold (default 0.4), preventing unrelated
   memories from bleeding into conversation context.

3. Default hybrid search weights rebalanced from 70/30 vector/keyword
   to 40/60, reducing cross-topic semantic bleed.

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
This commit is contained in:
Edvard 2026-02-17 20:09:06 -05:00 • committed by Chummy
parent 21c5f58363
commit 8a1e7cc7ef
6 changed files with 90 additions and 24 deletions
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13
src/config/schema.rs
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@ -753,6 +753,11 @@ pub struct MemoryConfig {
/// Weight for keyword BM25 in hybrid search (0.0–1.0)
#[serde(default = "default_keyword_weight")]
pub keyword_weight: f64,
/// Minimum hybrid score (0.0–1.0) for a memory to be included in context.
/// Memories scoring below this threshold are dropped to prevent irrelevant
/// context from bleeding into conversations. Default: 0.4
#[serde(default = "default_min_relevance_score")]
pub min_relevance_score: f64,
/// Max embedding cache entries before LRU eviction
#[serde(default = "default_cache_size")]
pub embedding_cache_size: usize,
@ -811,10 +816,13 @@ fn default_embedding_dims() -> usize {
1536
}
fn default_vector_weight() -> f64 {
0.7
0.4
}
fn default_keyword_weight() -> f64 {
0.3
0.6
}
fn default_min_relevance_score() -> f64 {
0.4
}
fn default_cache_size() -> usize {
10_000
@ -843,6 +851,7 @@ impl Default for MemoryConfig {
embedding_dimensions: default_embedding_dims(),
vector_weight: default_vector_weight(),
keyword_weight: default_keyword_weight(),
min_relevance_score: default_min_relevance_score(),
embedding_cache_size: default_cache_size(),
chunk_max_tokens: default_chunk_size(),
response_cache_enabled: false,