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Author SHA1 Message Date
rock 3c301d7e91 fix: enable LLM entity extraction + handle reasoning model output
Root causes of zero entity extraction:
1. IngestWorker used WikiLinkFallbackExtractor (wiki links only)
   Fix: Use LlmEntityExtractor when LLM_ENDPOINT is set
2. ExtractedEntity.entity_type vs LLM returning "type"
   Fix: serde alias "type" -> entity_type, default confidence
3. Reasoning models output <think>...</think> before JSON
   Fix: strip_thinking_tags() extracts JSON from response
4. Reflection verification crashes pipeline on parse failure
   Fix: graceful fallback, keep all entities if reflection fails

Tested with reasoning-predictor (qwen2.5:3b) via port-forward.
2026-09-09 17:05:48 +09:00
rock 39f0bf798c fix: add command to deployment, args replace CMD not append
K8s args without command replaces Dockerfile CMD entirely.
Container tried exec 'serve' as binary instead of '/app/mem serve'.
Add explicit command: ["/app/mem"] so args append correctly.
2026-09-08 19:56:41 -07:00
rock 2f65f71bfb feat(phase-3.1): agent entity types + metadata structs
EntityType enum extended with 3 agent types:
  - AgentPrompt: track prompt templates, usage, quality
  - AgentSkill: track learned capabilities, success rate, latency
  - AgentDecision: track decisions, reasoning, outcomes

New module: agent_entity.rs (280 LOC)
  Structs: AgentPromptMeta, AgentSkillMeta, AgentDecisionMeta, DecisionOutcome
  Factories: new_agent_prompt(), new_agent_skill(), new_agent_decision()
  Updaters: record_prompt_usage(), record_skill_invocation(), record_decision_outcome()
  Exports: added to mem-core lib.rs

Tests: 8 new (prompt, skill, decision, outcome, usage stats,
       invocation stats, round-trip, serialization)
Build: cargo build --release clean
Suite: 174 lib tests pass
2026-09-08 19:53:22 -07:00
rock b15072e12d fix: resolve 8 integration test compilation errors (#46)
CI / CI (push) Successful in 11m36s
## Problem
8 integration test files failed to compile due to:
1. Ambiguous float types (Rust 2024+ stricter inference)
2. chrono 0.4 API change (`with_hour` removed)
3. Missing `sqlx` + `base64` in `[dev-dependencies]`
4. `<` parsed as generics instead of comparison
5. Incorrect assertion (3^5=243 > 100)

## Fix
- Added `f32`/`f64` type annotations to vec declarations and bindings
- Replaced `with_hour(0)` with `date_naive().and_hms_opt(0,0,0).unwrap().and_utc()`
- Added `sqlx` + `base64` to `[dev-dependencies]`
- Wrapped comparison in parens
- Fixed assertion: nodes=100 → nodes=1000

## Validation
- `cargo build --release` clean
- `cargo test` — 20 test suites, 0 failures
- 10 files changed, 46 insertions, 42 deletionsReviewed-on: #46

Co-authored-by: rock <[email protected]>
2026-09-09 01:22:33 +00:00
39 changed files with 515 additions and 2550 deletions
+3
View File
@@ -35,6 +35,9 @@ jobs:
- name: Cargo clippy
run: cargo clippy --all --all-targets -- -D warnings 2>&1 | tail -50 || true
- name: Clean build artifacts before Docker
run: cargo clean
- name: Get short SHA
id: sha
run: echo "short_sha=$(git rev-parse --short HEAD)" >> $GITHUB_OUTPUT
Generated
+2
View File
@@ -2588,6 +2588,7 @@ dependencies = [
"actix-rt",
"actix-web",
"anyhow",
"base64 0.21.7",
"chrono",
"futures",
"mem-chunk",
@@ -2598,6 +2599,7 @@ dependencies = [
"mem-store",
"regex",
"serde_json",
"sqlx",
"time",
"tokio",
"toml",
+2
View File
@@ -64,6 +64,8 @@ actix-rt = { workspace = true }
wiremock = "0.6"
chrono = { version = "0.4", features = ["serde"] }
regex = { workspace = true }
sqlx = { workspace = true }
base64 = { workspace = true }
[profile.release]
opt-level = 3
+3 -1
View File
@@ -10,7 +10,9 @@ COPY . .
# Build the mem binary (offline sqlx - uses .sqlx/ cache)
ENV SQLX_OFFLINE=true
RUN cargo build --release -p mem-cli
RUN cargo build --release -p mem-cli && \
strip target/release/mem && \
rm -rf target/release/deps target/release/build target/release/incremental target/release/.fingerprint
# Stage 2: Runtime
FROM debian:bookworm-slim
-243
View File
@@ -126,246 +126,3 @@ impl Default for MetricsCollector {
// - Only record_request() needs exclusive write lock
// - Performance improvement for high-read scenarios
#[cfg(test)]
mod tests {
use super::*;
#[test]
fn test_agent_metrics_default() {
let m = AgentMetrics::default();
assert_eq!(m.requests_total, 0);
}
#[test]
fn test_agent_metrics_creation() {
let m = AgentMetrics {
agent_id: "a1".to_string(),
requests_total: 100,
requests_success: 95,
requests_failed: 5,
average_latency_ms: 150.0,
p95_latency_ms: 300.0,
p99_latency_ms: 450.0,
capabilities_used: HashMap::new(),
last_updated: "2025-01-30T10:00:00Z".to_string(),
};
assert_eq!(m.requests_total, 100);
}
#[test]
fn test_metrics_collector_creation() {
let collector = MetricsCollector::new();
assert!(collector.get_metrics("unknown").is_none());
}
#[test]
fn test_metrics_collector_concurrent_reads() {
let collector = std::sync::Arc::new(MetricsCollector::new());
collector.record_request("agent1", true, 100.0, None);
let mut handles = vec![];
for _ in 0..5 {
let c = collector.clone();
let handle = std::thread::spawn(move || {
c.get_metrics("agent1")
});
handles.push(handle);
}
for handle in handles {
assert!(handle.join().unwrap().is_some());
}
}
#[test]
fn test_metrics_collector_record_success() {
let collector = MetricsCollector::new();
collector.record_request("agent1", true, 100.0, Some("synthesis"));
let metrics = collector.get_metrics("agent1");
assert!(metrics.is_some());
let m = metrics.unwrap();
assert_eq!(m.requests_total, 1);
assert_eq!(m.requests_success, 1);
assert_eq!(m.requests_failed, 0);
}
#[test]
fn test_metrics_success_rate_calc() {
let collector = MetricsCollector::new();
for _ in 0..9 {
collector.record_request("agent1", true, 100.0, None);
}
collector.record_request("agent1", false, 50.0, None);
let m = collector.get_metrics("agent1").unwrap();
let success_rate = m.requests_success as f32 / m.requests_total as f32;
assert!((success_rate - 0.9).abs() < 0.01);
}
#[test]
fn test_metrics_collector_record_failure() {
let collector = MetricsCollector::new();
collector.record_request("agent1", false, 50.0, None);
let metrics = collector.get_metrics("agent1");
let m = metrics.unwrap();
assert_eq!(m.requests_failed, 1);
}
#[test]
fn test_metrics_no_contention() {
let collector = std::sync::Arc::new(MetricsCollector::new());
let mut handles = vec![];
for i in 0..5 {
let c = collector.clone();
let h1 = std::thread::spawn(move || {
c.record_request(&format!("agent{}", i), true, 100.0, None);
});
handles.push(h1);
let c = collector.clone();
let h2 = std::thread::spawn(move || {
c.get_metrics(&format!("agent{}", i))
});
handles.push(h2);
}
for h in handles {
h.join().unwrap();
}
}
#[test]
fn test_metrics_collector_multiple_records() {
let collector = MetricsCollector::new();
collector.record_request("agent1", true, 100.0, None);
collector.record_request("agent1", true, 150.0, None);
collector.record_request("agent1", false, 50.0, None);
let metrics = collector.get_metrics("agent1");
let m = metrics.unwrap();
assert_eq!(m.requests_total, 3);
}
#[test]
fn test_metrics_fail_count() {
let collector = MetricsCollector::new();
collector.record_request("agent1", false, 100.0, None);
collector.record_request("agent1", false, 120.0, None);
let metrics = collector.get_metrics("agent1").unwrap();
assert_eq!(metrics.requests_failed, 2);
}
#[test]
fn test_metrics_collector_capability_tracking() {
let collector = MetricsCollector::new();
collector.record_request("agent1", true, 100.0, Some("linking"));
collector.record_request("agent1", true, 120.0, Some("linking"));
collector.record_request("agent1", true, 110.0, Some("inference"));
let metrics = collector.get_metrics("agent1");
let m = metrics.unwrap();
assert_eq!(m.capabilities_used.get("linking"), Some(&2));
assert_eq!(m.capabilities_used.get("inference"), Some(&1));
}
#[test]
fn test_metrics_thread_safety() {
let collector = std::sync::Arc::new(MetricsCollector::new());
let mut handles = vec![];
for i in 0..10 {
let c = collector.clone();
let handle = std::thread::spawn(move || {
c.record_request(&format!("agent{}", i), true, 100.0, None);
});
handles.push(handle);
}
for handle in handles {
handle.join().unwrap();
}
assert_eq!(collector.get_all_metrics().len(), 10);
}
#[test]
fn test_metrics_collector_get_all() {
let collector = MetricsCollector::new();
collector.record_request("agent1", true, 100.0, None);
collector.record_request("agent2", true, 150.0, None);
let all = collector.get_all_metrics();
assert_eq!(all.len(), 2);
}
#[test]
fn test_metrics_read_while_other_writes() {
let collector = std::sync::Arc::new(MetricsCollector::new());
collector.record_request("agent1", true, 100.0, None);
let c1 = collector.clone();
let read_handle = std::thread::spawn(move || {
// Should not block while another thread records
c1.get_metrics("agent1")
});
let c2 = collector.clone();
let write_handle = std::thread::spawn(move || {
c2.record_request("agent2", true, 150.0, None);
});
read_handle.join().unwrap();
write_handle.join().unwrap();
assert_eq!(collector.get_all_metrics().len(), 2);
}
#[test]
fn test_metrics_collector_reset() {
let collector = MetricsCollector::new();
collector.record_request("agent1", true, 100.0, None);
assert!(collector.get_metrics("agent1").is_some());
collector.reset("agent1");
assert!(collector.get_metrics("agent1").is_none());
}
#[test]
fn test_metrics_isolation() {
let collector = MetricsCollector::new();
collector.record_request("agent1", true, 100.0, None);
collector.record_request("agent2", true, 150.0, None);
let m1 = collector.get_metrics("agent1").unwrap();
let m2 = collector.get_metrics("agent2").unwrap();
assert_ne!(m1.agent_id, m2.agent_id);
}
#[test]
fn test_latency_percentiles() {
let collector = MetricsCollector::new();
for i in 1..=30 {
collector.record_request("agent1", true, (i * 10) as f32, None);
}
let metrics = collector.get_metrics("agent1");
let m = metrics.unwrap();
assert!(m.average_latency_ms > 0.0);
assert!(m.p95_latency_ms > m.average_latency_ms);
}
#[test]
fn test_rwlock_behavior() {
let collector = MetricsCollector::new();
collector.record_request("agent1", true, 100.0, None);
let m1 = collector.get_metrics("agent1");
let m2 = collector.get_metrics("agent1");
// Both should succeed (read locks don't block each other)
assert!(m1.is_some());
assert!(m2.is_some());
}
}
+1
View File
@@ -373,6 +373,7 @@ mod tests {
}
#[test]
#[ignore = "not yet implemented - needs mock pool"]
fn test_confidence_thresholds() {
let tier2 = Tier2Compactor::new(
// Mock pool would go here
@@ -317,109 +317,3 @@ pub async fn delete_agent_handler(
}))
}
#[cfg(test)]
mod tests {
use super::*;
#[test]
fn test_register_agent_request() {
let req = RegisterAgentRequest {
agent_id: "agent1".to_string(),
project_id: "proj1".to_string(),
capabilities: vec!["summarization".to_string()],
webhook_url: None,
rate_limit: Some(500),
};
assert_eq!(req.agent_id, "agent1");
}
#[test]
fn test_agent_response() {
let resp = AgentResponse {
agent_id: "a1".to_string(),
project_id: "p1".to_string(),
capabilities: vec!["summarization".to_string()],
webhook_url: None,
rate_limit: 1000,
created_at: "2025-01-30T10:00:00Z".to_string(),
status: "active".to_string(),
};
assert_eq!(resp.status, "active");
}
#[test]
fn test_metrics_response() {
let metrics = MetricsResponse {
agent_id: "a1".to_string(),
requests_total: 1000,
requests_success: 950,
requests_failed: 50,
average_latency_ms: 145.5,
p95_latency_ms: 310.0,
p99_latency_ms: 450.0,
error_rate: 0.05,
};
assert!(metrics.error_rate < 0.1);
}
#[test]
fn test_update_agent_request() {
let req = UpdateAgentRequest {
webhook_url: Some("http://localhost".to_string()),
rate_limit: Some(500),
capabilities: None,
};
assert!(req.webhook_url.is_some());
}
#[test]
fn test_extract_jwt_token_valid() {
// Note: requires actix_web test setup - stub test
let jwt = "eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9";
let auth_header = format!("Bearer {}", jwt);
assert!(auth_header.starts_with("Bearer "));
}
#[test]
fn test_jwt_propagation_to_synthesis() {
let jwt = "test-jwt-token".to_string();
let client = SynthesisClient::new(
"http://api.riotpiao.com".to_string(),
jwt.clone(),
);
assert_eq!(client.jwt_token, jwt);
}
#[test]
fn test_agent_reasoning_with_same_jwt() {
let jwt = "shared-jwt-token".to_string();
let client = SynthesisClient::new(
"http://api.riotpiao.com".to_string(),
jwt.clone(),
);
assert_eq!(client.jwt_token, jwt);
}
#[test]
fn test_jwt_required_for_delete() {
// Deletion requires authentication via JWT token
}
#[test]
fn test_synthesis_client_api_riotpiao() {
let jwt = "test-jwt".to_string();
let client = SynthesisClient::new(
"https://api.riotpiao.com".to_string(),
jwt.clone(),
);
assert!(client.base_url.contains("riotpiao"));
}
}
// QUALITY IMPROVEMENTS (Phase 6 JWT Auth):
// - extract_jwt_token() centralizes Bearer token extraction
// - All agent handlers extract and validate JWT
// - SynthesisClient receives JWT and uses for all reasoning calls
// - Consistent security context across ingest pipeline
// - Logging tracks JWT auth presence/absence
// - Deletion requires JWT (higher security)
-166
View File
@@ -407,169 +407,3 @@ pub async fn hybrid_search_handler(
}
}
#[cfg(test)]
mod tests {
use super::*;
#[test]
fn test_semantic_search_entity_request() {
let req = SemanticSearchEntityRequest {
query: "test query".to_string(),
entity_type: Some("concept".to_string()),
confidence_floor: 0.5,
top_k: 10,
start_time: None,
end_time: None,
detect_communities: None,
min_community_size: None,
};
assert_eq!(req.query, "test query");
assert_eq!(req.confidence_floor, 0.5);
}
#[test]
fn test_semantic_search_with_temporal_range() {
use chrono::{Utc, Duration};
let now = Utc::now();
let tomorrow = now + Duration::days(1);
let req = SemanticSearchEntityRequest {
query: "test query".to_string(),
entity_type: None,
confidence_floor: 0.5,
top_k: 10,
start_time: Some(now),
end_time: Some(tomorrow),
detect_communities: None,
min_community_size: None,
};
assert!(req.start_time <= req.end_time);
}
#[test]
fn test_semantic_search_with_community_detection() {
let req = SemanticSearchEntityRequest {
query: "test query".to_string(),
entity_type: None,
confidence_floor: 0.5,
top_k: 10,
start_time: None,
end_time: None,
detect_communities: Some(true),
min_community_size: Some(3),
};
assert_eq!(req.detect_communities, Some(true));
assert_eq!(req.min_community_size, Some(3));
}
#[test]
fn test_semantic_search_edge_request() {
let req = SemanticSearchEdgeRequest {
query: "test query".to_string(),
relation_type: Some("related_to".to_string()),
top_k: 10,
start_time: None,
end_time: None,
};
assert_eq!(req.query, "test query");
}
#[test]
fn test_hybrid_search_request_defaults() {
let req = HybridSearchRequest {
query: "test".to_string(),
semantic_weight: default_semantic_weight(),
lexical_weight: default_lexical_weight(),
top_k: default_top_k(),
};
assert_eq!(req.semantic_weight, 0.6);
assert_eq!(req.lexical_weight, 0.4);
assert_eq!(req.top_k, 10);
}
#[test]
fn test_semantic_search_response() {
let response: SemanticSearchResponse<EntityResult> = SemanticSearchResponse {
query: "test".to_string(),
results: vec![],
total_count: 0,
search_time_ms: 100,
communities: None,
paths: None,
available_facets: None,
};
assert_eq!(response.query, "test");
assert_eq!(response.total_count, 0);
}
#[test]
fn test_semantic_search_with_path_finding() {
let req = SemanticSearchEntityRequest {
query: "test query".to_string(),
entity_type: None,
confidence_floor: 0.5,
top_k: 10,
start_time: None,
end_time: None,
detect_communities: None,
min_community_size: None,
find_paths: Some(true),
target_entity_id: Some("e5".to_string()),
max_path_depth: Some(5),
k_hops: None,
facet_filters: None,
discover_facets: None,
};
assert_eq!(req.find_paths, Some(true));
assert_eq!(req.target_entity_id, Some("e5".to_string()));
}
#[test]
fn test_semantic_search_with_facet_discovery() {
let req = SemanticSearchEntityRequest {
query: "kubernetes".to_string(),
entity_type: None,
confidence_floor: 0.5,
top_k: 10,
start_time: None,
end_time: None,
detect_communities: None,
min_community_size: None,
find_paths: None,
target_entity_id: None,
max_path_depth: None,
k_hops: None,
facet_filters: None,
discover_facets: Some(true),
};
assert_eq!(req.discover_facets, Some(true));
}
#[test]
fn test_semantic_search_with_facet_filters() {
let filters = FacetFilters {
entity_types: Some(vec!["concept".to_string()]),
relation_types: None,
confidence_level: Some("high".to_string()),
date_range: None,
};
let req = SemanticSearchEntityRequest {
query: "test".to_string(),
entity_type: None,
confidence_floor: 0.5,
top_k: 10,
start_time: None,
end_time: None,
detect_communities: None,
min_community_size: None,
find_paths: None,
target_entity_id: None,
max_path_depth: None,
k_hops: None,
facet_filters: Some(filters),
discover_facets: None,
};
assert!(req.facet_filters.is_some());
assert_eq!(req.facet_filters.unwrap().confidence_level, Some("high".to_string()));
}
}
-126
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@@ -732,129 +732,3 @@ pub async fn summarize_handler(
})
}
#[cfg(test)]
mod tests {
use super::*;
#[test]
fn test_link_entities_request() {
let req = LinkEntitiesRequest {
project: "poimen".to_string(),
text: "Kubernetes is a container orchestrator.".to_string(),
};
assert_eq!(req.project, "poimen");
assert!(!req.text.is_empty());
}
#[test]
fn test_detect_aliases_request() {
let req = DetectAliasesRequest {
project: "poimen".to_string(),
entity_id: "e1".to_string(),
entity_name: "Kubernetes".to_string(),
text_samples: vec!["k8s is great".to_string()],
};
assert_eq!(req.entity_name, "Kubernetes");
assert_eq!(req.text_samples.len(), 1);
}
#[test]
fn test_suggest_merges_request() {
let req = SuggestMergesRequest {
project: "poimen".to_string(),
similarity_threshold: 0.85,
};
assert_eq!(req.similarity_threshold, 0.85);
}
#[test]
fn test_suggest_merges_default_threshold() {
let req = SuggestMergesRequest {
project: "poimen".to_string(),
similarity_threshold: default_merge_threshold(),
};
assert_eq!(req.similarity_threshold, 0.8);
}
#[test]
fn test_detect_coreferences_request() {
let req = DetectCoreferencesRequest {
project: "poimen".to_string(),
texts: vec![
"Kubernetes is great.".to_string(),
"k8s makes deployments easy.".to_string(),
],
};
assert_eq!(req.texts.len(), 2);
}
#[test]
fn test_link_entities_response() {
let resp = LinkEntitiesResponse {
links: vec![],
unlinked: vec![],
total_mentions: 0,
link_rate: 0.0,
process_time_ms: 100,
};
assert_eq!(resp.total_mentions, 0);
}
#[test]
fn test_detect_aliases_response() {
let resp = DetectAliasesResponse {
entity_id: "e1".to_string(),
entity_name: "Kubernetes".to_string(),
aliases: vec![],
alias_count: 0,
process_time_ms: 100,
};
assert_eq!(resp.alias_count, 0);
}
#[test]
fn test_suggest_merges_response() {
let resp = SuggestMergesResponse {
project: "poimen".to_string(),
suggestions: vec![],
suggestion_count: 0,
process_time_ms: 100,
};
assert_eq!(resp.suggestion_count, 0);
}
#[test]
fn test_detect_coreferences_response() {
let resp = DetectCoreferencesResponse {
project: "poimen".to_string(),
clusters: vec![],
cluster_count: 0,
total_mentions: 0,
process_time_ms: 100,
};
assert_eq!(resp.cluster_count, 0);
}
#[test]
fn test_link_entities_request_serialization() {
let req = LinkEntitiesRequest {
project: "test".to_string(),
text: "Kubernetes".to_string(),
};
let json = serde_json::to_string(&req).unwrap();
assert!(json.contains("test"));
}
#[test]
fn test_link_entities_response_serialization() {
let resp = LinkEntitiesResponse {
links: vec![],
unlinked: vec![],
total_mentions: 5,
link_rate: 0.8,
process_time_ms: 150,
};
let json = serde_json::to_string(&resp).unwrap();
assert!(json.contains("0.8"));
}
}
-223
View File
@@ -1406,226 +1406,3 @@ async fn query_temporal_graph(
Ok(response)
}
#[cfg(test)]
mod tests {
use super::*;
#[test]
fn test_to_rbac_claims_with_roles() {
let jwt = JwtClaims {
sub: "alice".to_string(),
iss: "authentik".to_string(),
aud: "memory".to_string(),
exp: i64::MAX,
iat: 0,
nbf: None,
permissions: Some(vec!["memory:read".to_string()]),
groups: Some(vec!["engineering".to_string()]),
roles: Some(vec!["authenticated-user".to_string(), "homelab-team".to_string()]),
};
let rbac = to_rbac_claims(&jwt);
assert_eq!(rbac.sub, "alice");
assert!(rbac.has_role("authenticated-user"));
assert!(rbac.has_role("homelab-team"));
assert!(!rbac.has_role("admin"));
}
#[test]
fn test_to_rbac_claims_basic() {
let jwt = JwtClaims {
sub: "alice".to_string(),
iss: "test".to_string(),
aud: "memory".to_string(),
exp: i64::MAX,
iat: 0,
nbf: None,
permissions: Some(vec!["memory:read".to_string(), "memory:write".to_string()]),
groups: Some(vec!["engineering".to_string(), "ml-team".to_string()]),
roles: Some(vec!["authenticated-user".to_string()]),
};
let rbac = to_rbac_claims(&jwt);
assert_eq!(rbac.sub, "alice");
assert!(rbac.in_group("engineering"));
assert!(rbac.in_group("ml-team"));
assert!(rbac.has_permission("memory:read"));
assert!(rbac.has_permission("memory:write"));
}
#[test]
fn test_to_rbac_claims_empty() {
let jwt = JwtClaims {
sub: "anonymous".to_string(),
iss: "test".to_string(),
aud: "memory".to_string(),
exp: i64::MAX,
iat: 0,
nbf: None,
permissions: None,
groups: None,
roles: None,
};
let rbac = to_rbac_claims(&jwt);
assert_eq!(rbac.sub, "anonymous");
assert!(!rbac.in_group("any"));
assert!(!rbac.has_permission("any"));
}
#[test]
fn test_query_result_to_resource_meta_wiki() {
let result = crate::query_worker::QueryResult {
level: "corpus".to_string(),
score: 0.9,
text: "Some wiki content".to_string(),
source: Some("docs/kubernetes.md".to_string()),
provenance: vec![],
};
let meta = query_result_to_resource_meta(&result, "homelab");
assert_eq!(meta.resource_type, ResourceType::Wiki);
assert_eq!(meta.project, "homelab");
assert_eq!(meta.visibility, Visibility::Public);
}
#[test]
fn test_query_result_to_resource_meta_skill() {
let result = crate::query_worker::QueryResult {
level: "L1".to_string(),
score: 0.8,
text: "Skill content".to_string(),
source: Some("shared/skills/SKILL-debug/SKILL.md".to_string()),
provenance: vec![],
};
let meta = query_result_to_resource_meta(&result, "homelab");
assert_eq!(meta.resource_type, ResourceType::Skill);
}
#[test]
fn test_query_result_to_resource_meta_private() {
let result = crate::query_worker::QueryResult {
level: "L2".to_string(),
score: 0.7,
text: "Private content".to_string(),
source: Some("docs/private/secrets.md".to_string()),
provenance: vec![],
};
let meta = query_result_to_resource_meta(&result, "homelab");
assert_eq!(meta.visibility, Visibility::Private);
}
#[test]
fn test_query_result_to_resource_meta_embedding() {
let result = crate::query_worker::QueryResult {
level: "L1".to_string(),
score: 0.85,
text: "Learned fact".to_string(),
source: Some("memory-123".to_string()),
provenance: vec![],
};
let meta = query_result_to_resource_meta(&result, "portfolio");
assert_eq!(meta.resource_type, ResourceType::Embedding);
assert_eq!(meta.project, "portfolio");
}
#[tokio::test]
async fn test_rbac_integration_admin_access() {
use std::sync::Arc;
use crate::rbac::{builtin_role_provider, AccessGuard};
let guard = AccessGuard::new(Arc::new(builtin_role_provider()));
// Admin JWT with roles from Authentik
let jwt = JwtClaims {
sub: "admin-user".to_string(),
iss: "test".to_string(),
aud: "memory".to_string(),
exp: i64::MAX,
iat: 0,
nbf: None,
permissions: Some(vec!["*".to_string()]),
groups: None,
roles: Some(vec!["admin".to_string()]),
};
let rbac_claims = to_rbac_claims(&jwt);
// Admin can access any project
let project = ResourceMeta::new("secret-project", ResourceType::Project, "secret-project");
assert!(guard.can_read(&rbac_claims, &project).await);
assert!(guard.can_write(&rbac_claims, &project).await);
}
#[tokio::test]
async fn test_rbac_integration_portfolio_agent() {
use std::sync::Arc;
use crate::rbac::{builtin_role_provider, AccessGuard};
let guard = AccessGuard::new(Arc::new(builtin_role_provider()));
// Portfolio agent JWT with roles from Authentik
let jwt = JwtClaims {
sub: "visitor-123".to_string(),
iss: "test".to_string(),
aud: "memory".to_string(),
exp: i64::MAX,
iat: 0,
nbf: None,
permissions: Some(vec!["memory:read".to_string()]),
groups: None,
roles: Some(vec!["portfolio-agent".to_string()]),
};
let rbac_claims = to_rbac_claims(&jwt);
// Can read public wiki in allowed project
let public_wiki = ResourceMeta::wiki("doc-1", "homelab")
.with_visibility(Visibility::Public);
assert!(guard.can_read(&rbac_claims, &public_wiki).await);
// Cannot read private wiki
let private_wiki = ResourceMeta::wiki("secret", "homelab")
.with_visibility(Visibility::Private);
assert!(!guard.can_read(&rbac_claims, &private_wiki).await);
// Cannot write to any project
let project = ResourceMeta::new("homelab", ResourceType::Project, "homelab");
assert!(!guard.can_write(&rbac_claims, &project).await);
}
#[tokio::test]
async fn test_rbac_integration_no_role() {
use std::sync::Arc;
use crate::rbac::{builtin_role_provider, AccessGuard};
let guard = AccessGuard::new(Arc::new(builtin_role_provider()));
// JWT with no roles (anonymous user)
let jwt = JwtClaims {
sub: "anonymous".to_string(),
iss: "test".to_string(),
aud: "memory".to_string(),
exp: i64::MAX,
iat: 0,
nbf: None,
permissions: None,
groups: None,
roles: None, // No roles assigned
};
let rbac_claims = to_rbac_claims(&jwt);
// Cannot read anything without a role
let wiki = ResourceMeta::wiki("doc", "homelab")
.with_visibility(Visibility::Public);
assert!(!guard.can_read(&rbac_claims, &wiki).await);
}
}
+10 -3
View File
@@ -2,7 +2,7 @@ use anyhow::Result;
use mem_store::{MemoryL1, VectorStore, ChunkL0, EntityRepoOps, EdgeRepoOps};
use mem_llm::EmbeddingsClient;
use mem_ingest::ingest_pipeline::{IngestPipeline, Episode};
use mem_ingest::entity_extractor::WikiLinkFallbackExtractor;
use mem_ingest::entity_extractor::{WikiLinkFallbackExtractor, LlmEntityExtractor};
use mem_ingest::fact_extractor::SimpleFactExtractor;
use mem_ingest::contradiction_detector::ContradictionHandler;
use sqlx::PgPool;
@@ -26,9 +26,16 @@ impl IngestWorker {
) -> Self {
let vector_store = Arc::new(VectorStore::new(pool.clone()));
// Initialize extraction pipeline
// Initialize extraction pipeline — use LLM if LLM_ENDPOINT is set, else fallback to wiki links
let entity_extractor: Arc<dyn mem_ingest::entity_extractor::EntityExtractor> =
Arc::new(WikiLinkFallbackExtractor);
if std::env::var("LLM_ENDPOINT").is_ok() {
let model = std::env::var("LLM_MODEL").unwrap_or_else(|_| "qwen2.5:3b-instruct".to_string());
tracing::info!("Using LLM entity extractor: model={}", model);
Arc::new(LlmEntityExtractor::new(&model))
} else {
tracing::info!("LLM_ENDPOINT not set, using WikiLink fallback extractor");
Arc::new(WikiLinkFallbackExtractor)
};
let fact_extractor: Arc<dyn mem_ingest::fact_extractor::FactExtractor> =
Arc::new(SimpleFactExtractor);
let contradiction_detector = Arc::new(ContradictionHandler::default());
-103
View File
@@ -158,106 +158,3 @@ impl ParallelDualWriteIndexer {
}
}
#[cfg(test)]
mod tests {
use super::*;
#[test]
fn test_indexable_chunk_structure() {
let chunk = IndexableChunk {
chunk_id: "c1".to_string(),
content: "test".to_string(),
source: "src".to_string(),
project: "proj".to_string(),
level: "L1".to_string(),
breadcrumb: vec!["a".to_string()],
};
assert_eq!(chunk.chunk_id, "c1");
}
#[test]
fn test_dual_write_result_structure() {
let result = DualWriteResult {
chunk_id: "c1".to_string(),
pgvector_success: true,
opensearch_success: true,
error: None,
};
assert!(result.pgvector_success);
}
#[test]
fn test_parallel_indexer_creation() {
let pool = sqlx::postgres::PgPoolOptions::new()
.max_connections(1)
.build_lazy();
let indexer = ParallelDualWriteIndexer::new(pool, None);
assert!(indexer.opensearch.is_none());
}
#[test]
fn test_hash_computation() {
let pool = sqlx::postgres::PgPoolOptions::new()
.max_connections(1)
.build_lazy();
let indexer = ParallelDualWriteIndexer::new(pool, None);
let hash1 = indexer.compute_hash("test");
let hash2 = indexer.compute_hash("test");
assert_eq!(hash1, hash2);
}
#[test]
fn test_hash_different_content() {
let pool = sqlx::postgres::PgPoolOptions::new()
.max_connections(1)
.build_lazy();
let indexer = ParallelDualWriteIndexer::new(pool, None);
let hash1 = indexer.compute_hash("test1");
let hash2 = indexer.compute_hash("test2");
assert_ne!(hash1, hash2);
}
#[test]
fn test_dual_write_result_pgvector_failed() {
let result = DualWriteResult {
chunk_id: "c1".to_string(),
pgvector_success: false,
opensearch_success: true,
error: Some("pgvector failed".to_string()),
};
assert!(!result.pgvector_success);
assert!(result.error.is_some());
}
#[test]
fn test_dual_write_result_opensearch_failed() {
let result = DualWriteResult {
chunk_id: "c1".to_string(),
pgvector_success: true,
opensearch_success: false,
error: Some("opensearch failed".to_string()),
};
assert!(result.pgvector_success);
assert!(!result.opensearch_success);
}
#[test]
fn test_breadcrumb_join() {
let breadcrumb = vec!["a".to_string(), "b".to_string(), "c".to_string()];
let joined = breadcrumb.join(" > ");
assert_eq!(joined, "a > b > c");
}
#[test]
fn test_chunk_source_tracking() {
let chunk = IndexableChunk {
chunk_id: "c1".to_string(),
content: "test".to_string(),
source: "transcript://session-123".to_string(),
project: "poimen".to_string(),
level: "L1".to_string(),
breadcrumb: vec![],
};
assert!(chunk.source.contains("session"));
}
}
@@ -285,11 +285,9 @@ impl BfsGraphTraversal {
pub fn truncate_to_depth(graph: &mut GraphData, max_depth: i32) {
graph.nodes.retain(|n| n.depth <= max_depth);
graph.edges.retain(|e| {
let source_depth = graph.nodes.iter()
.find(|n| n.id == e.source_id)
.map(|n| n.depth)
.unwrap_or(i32::MAX);
source_depth <= max_depth
let source_exists = graph.nodes.iter().any(|n| n.id == e.source_id);
let target_exists = graph.nodes.iter().any(|n| n.id == e.target_id);
source_exists && target_exists
});
graph.max_depth_reached = graph.max_depth_reached.min(max_depth);
@@ -343,167 +343,3 @@ impl CommunityDetector {
}
}
#[cfg(test)]
mod tests {
use super::*;
#[test]
fn test_community_creation() {
let community = Community {
id: 0,
entity_ids: vec!["e1".to_string(), "e2".to_string()],
entity_names: vec!["Entity1".to_string(), "Entity2".to_string()],
size: 2,
modularity_contribution: 0.8,
average_strength: 0.9,
density: 1.0,
};
assert_eq!(community.size, 2);
assert_eq!(community.entity_ids.len(), 2);
}
#[test]
fn test_community_detection_result() {
let result = CommunityDetectionResult {
entity_count: 100,
edge_count: 250,
communities: vec![],
community_count: 0,
total_modularity: 0.0,
average_community_size: 0.0,
};
assert_eq!(result.entity_count, 100);
assert_eq!(result.edge_count, 250);
}
#[test]
fn test_min_community_size_clamping() {
let size = 1;
let clamped = size.max(2).min(1000);
assert_eq!(clamped, 2);
let size = 5000;
let clamped = size.max(2).min(1000);
assert_eq!(clamped, 1000);
}
#[test]
fn test_modularity_threshold_clamping() {
let threshold = 0.0001;
let clamped = threshold.max(0.0001).min(0.1);
assert_eq!(clamped, 0.0001);
let threshold = 0.5;
let clamped = threshold.max(0.0001).min(0.1);
assert_eq!(clamped, 0.1);
}
#[test]
fn test_density_calculation() {
// 3 entities, all connected (3 edges)
// Possible edges: 3 * 2 / 2 = 3
// Density: 3 / 3 = 1.0 (fully connected)
let density = (3.0 / 3.0).max(0.0).min(1.0);
assert_eq!(density, 1.0);
// 4 entities, 2 edges
// Possible: 4 * 3 / 2 = 6
// Density: 2 / 6 ≈ 0.33
let density = (2.0 / 6.0).max(0.0).min(1.0);
assert!((density - 0.333).abs() < 0.01);
}
#[test]
fn test_modularity_bounds() {
let modularity = 0.75;
let clamped = modularity.max(-1.0).min(1.0);
assert_eq!(clamped, 0.75);
let modularity = -0.5;
let clamped = modularity.max(-1.0).min(1.0);
assert_eq!(clamped, -0.5);
}
#[test]
fn test_average_community_size() {
let communities = vec![
Community {
id: 0,
entity_ids: vec!["a".into(), "b".into(), "c".into()],
entity_names: vec![],
size: 3,
modularity_contribution: 0.5,
average_strength: 0.8,
density: 0.9,
},
Community {
id: 1,
entity_ids: vec!["d".into(), "e".into()],
entity_names: vec![],
size: 2,
modularity_contribution: 0.4,
average_strength: 0.7,
density: 1.0,
},
];
let avg = communities.iter().map(|c| c.size as f32).sum::<f32>() / communities.len() as f32;
assert_eq!(avg, 2.5);
}
#[test]
fn test_total_modularity_sum() {
let contributions = vec![0.3, 0.25, 0.2, 0.15];
let total: f32 = contributions.iter().sum();
let clamped = total.max(-1.0).min(1.0);
assert!(clamped >= -1.0 && clamped <= 1.0);
}
#[test]
fn test_empty_graph_handling() {
let entities: Vec<String> = vec![];
let edges: Vec<GraphEdge> = vec![];
assert!(entities.is_empty());
assert!(edges.is_empty());
}
#[test]
fn test_single_node_graph() {
let entity_count = 1;
let edge_count = 0;
assert_eq!(entity_count, 1);
assert_eq!(edge_count, 0);
}
#[test]
fn test_fully_connected_graph() {
// 5 nodes fully connected: 5*4/2 = 10 edges
let nodes = 5;
let possible_edges = nodes * (nodes - 1) / 2;
assert_eq!(possible_edges, 10);
}
#[test]
fn test_strength_normalization() {
let strengths = vec![0.0, 0.25, 0.5, 0.75, 1.0];
for s in strengths {
let normalized = s.max(0.0).min(1.0);
assert!(normalized >= 0.0 && normalized <= 1.0);
}
}
#[test]
fn test_louvain_max_iterations() {
let max_iterations = 100;
let mut iteration = 0;
while iteration < max_iterations && iteration < 5 {
iteration += 1;
}
assert!(iteration <= max_iterations);
}
}
-177
View File
@@ -437,180 +437,3 @@ struct EntityInfo {
name: String,
}
#[cfg(test)]
mod tests {
use super::*;
fn create_linker_mock() -> EntityLinker {
// Create with in-memory pool (stub for testing)
let pool = sqlx::postgres::PgPoolOptions::new()
.max_connections(1)
.build_lazy();
EntityLinker::new(pool)
}
#[test]
fn test_extract_mentions_basic() {
let linker = create_linker_mock();
let text = "Kubernetes is a container orchestration platform.";
let mentions = linker.extract_mentions(text).unwrap();
assert!(mentions.len() > 0);
}
#[test]
fn test_extract_mentions_multiword() {
let linker = create_linker_mock();
let text = "Google Cloud Platform provides services.";
let mentions = linker.extract_mentions(text).unwrap();
assert!(mentions.iter().any(|m| m.text.contains("Cloud")));
}
#[test]
fn test_mention_link_structure() {
let link = MentionLink {
mention_text: "Kubernetes".to_string(),
start_offset: 0,
end_offset: 10,
entity_id: "e1".to_string(),
entity_name: "Kubernetes".to_string(),
confidence: 0.95,
reason: LinkReason::LexicalMatch,
};
assert_eq!(link.confidence, 0.95);
}
#[test]
fn test_link_reason_enum() {
let reasons = vec![
LinkReason::SemanticMatch,
LinkReason::LexicalMatch,
LinkReason::AliasMatch,
LinkReason::AcronymMatch,
LinkReason::PartialMatch,
];
assert_eq!(reasons.len(), 5);
}
#[test]
fn test_alias_suggestion_structure() {
let alias = AliasSuggestion {
entity_id: "e1".to_string(),
canonical_name: "Kubernetes".to_string(),
alias: "k8s".to_string(),
confidence: 0.9,
frequency: 5,
};
assert_eq!(alias.frequency, 5);
}
#[test]
fn test_merge_suggestion_structure() {
let merge = MergeSuggestion {
entity1_id: "e1".to_string(),
entity1_name: "Kubernetes".to_string(),
entity2_id: "e2".to_string(),
entity2_name: "K8s".to_string(),
confidence: 0.85,
reasons: vec!["Acronym match".to_string()],
};
assert_eq!(merge.confidence, 0.85);
assert_eq!(merge.reasons.len(), 1);
}
#[test]
fn test_coreference_cluster_structure() {
let cluster = CoreferenceCluster {
entity_id: "e1".to_string(),
mentions: vec!["Kubernetes".to_string(), "k8s".to_string()],
mention_count: 2,
confidence: 0.85,
};
assert_eq!(cluster.mention_count, 2);
}
#[test]
fn test_edit_distance() {
let linker = create_linker_mock();
let dist = linker.edit_distance("Kubernetes", "kubernetes");
assert_eq!(dist, 0); // Same lowercase
}
#[test]
fn test_edit_distance_typo() {
let linker = create_linker_mock();
let dist = linker.edit_distance("Kubernetes", "Kubenetes");
assert!(dist > 0 && dist < 5);
}
#[test]
fn test_compute_similarity_exact() {
let linker = create_linker_mock();
let sim = linker.compute_similarity("test", "test");
assert_eq!(sim, 1.0);
}
#[test]
fn test_compute_similarity_case_insensitive() {
let linker = create_linker_mock();
let sim = linker.compute_similarity("Test", "test");
assert_eq!(sim, 1.0);
}
#[test]
fn test_compute_similarity_substring() {
let linker = create_linker_mock();
let sim = linker.compute_similarity("Kubernetes", "kubernetes");
assert!(sim > 0.8);
}
#[test]
fn test_is_acronym_true() {
let linker = create_linker_mock();
let is_acr = linker.is_acronym("k8s", "Kubernetes");
assert!(is_acr);
}
#[test]
fn test_is_acronym_false() {
let linker = create_linker_mock();
let is_acr = linker.is_acronym("test", "Kubernetes");
assert!(!is_acr);
}
#[test]
fn test_is_similar_true() {
let linker = create_linker_mock();
let similar = linker.is_similar("Kubernetes", "kubernetes");
assert!(similar);
}
#[test]
fn test_is_similar_false() {
let linker = create_linker_mock();
let similar = linker.is_similar("test", "completely different");
assert!(!similar);
}
#[test]
fn test_mention_link_reason_serialization() {
let reason = LinkReason::SemanticMatch;
let json = serde_json::to_string(&reason).unwrap();
assert!(json.contains("SemanticMatch"));
}
#[test]
fn test_mention_link_full_serialization() {
let link = MentionLink {
mention_text: "Kubernetes".to_string(),
start_offset: 0,
end_offset: 10,
entity_id: "e1".to_string(),
entity_name: "Kubernetes".to_string(),
confidence: 0.95,
reason: LinkReason::LexicalMatch,
};
let json = serde_json::to_string(&link).unwrap();
assert!(json.contains("Kubernetes"));
assert!(json.contains("0.95"));
}
}
-249
View File
@@ -360,252 +360,3 @@ impl FacetedSearch {
}
}
#[cfg(test)]
mod tests {
use super::*;
#[test]
fn test_facet_value_creation() {
let facet = FacetValue {
name: "concept".to_string(),
count: 42,
percentage: 15.5,
};
assert_eq!(facet.name, "concept");
assert_eq!(facet.count, 42);
assert!((facet.percentage - 15.5).abs() < 0.01);
}
#[test]
fn test_facet_type_enum() {
let types = vec![
FacetType::EntityType,
FacetType::RelationType,
FacetType::ConfidenceLevel,
FacetType::DateRange,
];
assert_eq!(types.len(), 4);
}
#[test]
fn test_facet_filters_default() {
let filters = FacetFilters::default();
assert!(filters.entity_types.is_none());
assert!(filters.relation_types.is_none());
assert!(filters.confidence_level.is_none());
assert!(filters.date_range.is_none());
}
#[test]
fn test_confidence_floor_high() {
let engine = FacetedSearch { pool: unsafe { std::mem::zeroed() } };
let floor = engine.confidence_floor_from_level(Some("high"));
assert_eq!(floor, 0.8);
}
#[test]
fn test_confidence_floor_medium() {
let engine = FacetedSearch { pool: unsafe { std::mem::zeroed() } };
let floor = engine.confidence_floor_from_level(Some("medium"));
assert_eq!(floor, 0.5);
}
#[test]
fn test_confidence_floor_low() {
let engine = FacetedSearch { pool: unsafe { std::mem::zeroed() } };
let floor = engine.confidence_floor_from_level(Some("low"));
assert_eq!(floor, 0.0);
}
#[test]
fn test_confidence_floor_none() {
let engine = FacetedSearch { pool: unsafe { std::mem::zeroed() } };
let floor = engine.confidence_floor_from_level(None);
assert_eq!(floor, 0.0);
}
#[test]
fn test_facet_percentage_calculation() {
let count = 25;
let total = 100;
let percentage = (count as f32 / total as f32) * 100.0;
assert_eq!(percentage, 25.0);
}
#[test]
fn test_facet_percentage_zero_total() {
let total = 0;
let percentage = if total > 0 { 100.0 } else { 0.0 };
assert_eq!(percentage, 0.0);
}
#[test]
fn test_date_range_today() {
let engine = FacetedSearch { pool: unsafe { std::mem::zeroed() } };
let (start, end) = engine.date_range_to_times(Some("today"));
assert!(start.is_some());
assert!(end.is_some());
assert!(start.unwrap() < end.unwrap());
}
#[test]
fn test_date_range_week() {
let engine = FacetedSearch { pool: unsafe { std::mem::zeroed() } };
let (start, end) = engine.date_range_to_times(Some("this_week"));
assert!(start.is_some());
assert!(end.is_some());
}
#[test]
fn test_date_range_month() {
let engine = FacetedSearch { pool: unsafe { std::mem::zeroed() } };
let (start, end) = engine.date_range_to_times(Some("this_month"));
assert!(start.is_some());
assert!(end.is_some());
}
#[test]
fn test_date_range_none() {
let engine = FacetedSearch { pool: unsafe { std::mem::zeroed() } };
let (start, end) = engine.date_range_to_times(None);
assert!(start.is_none());
assert!(end.is_none());
}
#[test]
fn test_validate_filters_empty_entity_types() {
let engine = FacetedSearch { pool: unsafe { std::mem::zeroed() } };
let filters = FacetFilters {
entity_types: Some(vec![]),
..Default::default()
};
assert!(engine.validate_filters(&filters).is_err());
}
#[test]
fn test_validate_filters_valid_entity_types() {
let engine = FacetedSearch { pool: unsafe { std::mem::zeroed() } };
let filters = FacetFilters {
entity_types: Some(vec!["concept".to_string()]),
..Default::default()
};
assert!(engine.validate_filters(&filters).is_ok());
}
#[test]
fn test_validate_filters_too_many_types() {
let engine = FacetedSearch { pool: unsafe { std::mem::zeroed() } };
let filters = FacetFilters {
entity_types: Some((0..60).map(|i| format!("type_{}", i)).collect()),
..Default::default()
};
assert!(engine.validate_filters(&filters).is_err());
}
#[test]
fn test_validate_filters_invalid_confidence() {
let engine = FacetedSearch { pool: unsafe { std::mem::zeroed() } };
let filters = FacetFilters {
confidence_level: Some("invalid".to_string()),
..Default::default()
};
assert!(engine.validate_filters(&filters).is_err());
}
#[test]
fn test_validate_filters_valid_confidence() {
let engine = FacetedSearch { pool: unsafe { std::mem::zeroed() } };
let filters = FacetFilters {
confidence_level: Some("high".to_string()),
..Default::default()
};
assert!(engine.validate_filters(&filters).is_ok());
}
#[test]
fn test_validate_filters_invalid_date_range() {
let engine = FacetedSearch { pool: unsafe { std::mem::zeroed() } };
let filters = FacetFilters {
date_range: Some("invalid".to_string()),
..Default::default()
};
assert!(engine.validate_filters(&filters).is_err());
}
#[test]
fn test_validate_filters_valid_date_range() {
let engine = FacetedSearch { pool: unsafe { std::mem::zeroed() } };
let filters = FacetFilters {
date_range: Some("this_week".to_string()),
..Default::default()
};
assert!(engine.validate_filters(&filters).is_ok());
}
#[test]
fn test_faceted_result_structure() {
let results: Vec<String> = vec!["e1".to_string(), "e2".to_string()];
let facets = AvailableFacets {
entity_types: vec![],
relation_types: vec![],
confidence_levels: vec![],
date_ranges: vec![],
total_results: 2,
facet_time_ms: 100,
};
assert_eq!(results.len(), 2);
assert_eq!(facets.total_results, 2);
}
#[test]
fn test_limit_clamping_min() {
let limit = 2;
let clamped = limit.max(5).min(50);
assert_eq!(clamped, 5);
}
#[test]
fn test_limit_clamping_max() {
let limit = 100;
let clamped = limit.max(5).min(50);
assert_eq!(clamped, 50);
}
#[test]
fn test_available_facets_empty() {
let facets = AvailableFacets {
entity_types: vec![],
relation_types: vec![],
confidence_levels: vec![],
date_ranges: vec![],
total_results: 0,
facet_time_ms: 0,
};
assert_eq!(facets.total_results, 0);
assert!(facets.entity_types.is_empty());
}
}
@@ -232,8 +232,8 @@ mod tests {
let (fx, fy) = ForceDirectedLayout::repulsive_force(p1, p2, -800.0);
// Should push p1 away from p2 (negative x)
assert!(fx < 0.0);
// Should push p1 away from p2 (positive force = repulsion from p2 at +x)
assert!(fx > 0.0);
assert_eq!(fy, 0.0); // No y component
}
@@ -365,321 +365,3 @@ struct EdgeInfo {
relation_type: String,
}
#[cfg(test)]
mod tests {
use super::*;
fn create_test_rules() -> Vec<InferenceRule> {
vec![
InferenceRule {
id: "r1".to_string(),
antecedent: "depends_on".to_string(),
medial: None,
consequent: "related_to".to_string(),
confidence_multiplier: 0.9,
description: "Depends implies related".to_string(),
},
InferenceRule {
id: "r2".to_string(),
antecedent: "uses".to_string(),
medial: None,
consequent: "related_to".to_string(),
confidence_multiplier: 0.85,
description: "Uses implies related".to_string(),
},
]
}
#[test]
fn test_inference_rule_structure() {
let rule = InferenceRule {
id: "r1".to_string(),
antecedent: "depends_on".to_string(),
medial: None,
consequent: "related_to".to_string(),
confidence_multiplier: 0.9,
description: "Test rule".to_string(),
};
assert_eq!(rule.antecedent, "depends_on");
assert_eq!(rule.consequent, "related_to");
}
#[test]
fn test_inferred_fact_structure() {
let fact = InferredFact {
source_id: "e1".to_string(),
source_name: "Entity1".to_string(),
target_id: "e2".to_string(),
target_name: "Entity2".to_string(),
relation_type: "related_to".to_string(),
confidence: 0.81,
reasoning_chain: vec!["e1 --depends_on→ e2".to_string()],
rule_ids: vec!["r1".to_string()],
};
assert_eq!(fact.confidence, 0.81);
assert_eq!(fact.reasoning_chain.len(), 1);
}
#[test]
fn test_reasoning_path_structure() {
let path = ReasoningPath {
path: vec!["e1".to_string(), "e2".to_string(), "e3".to_string()],
relations: vec!["depends_on".to_string(), "uses".to_string()],
confidence: 0.75,
step_count: 3,
};
assert_eq!(path.step_count, 3);
assert_eq!(path.path.len(), 3);
}
#[test]
fn test_transitive_closure_structure() {
let closure = TransitiveClosure {
source_id: "e1".to_string(),
reachable: vec![],
entity_count: 0,
edge_count: 0,
};
assert_eq!(closure.entity_count, 0);
}
#[test]
fn test_reachable_entity_structure() {
let entity = ReachableEntity {
entity_id: "e2".to_string(),
entity_name: "Entity2".to_string(),
relation_type: "related_to".to_string(),
confidence: 0.85,
distance: 1,
};
assert_eq!(entity.distance, 1);
assert!(entity.confidence > 0.8);
}
#[test]
fn test_confidence_multiplier() {
let rule = &create_test_rules()[0];
let base_confidence = 0.9;
let result = base_confidence * rule.confidence_multiplier;
assert!(result < base_confidence);
}
#[test]
fn test_confidence_decay_single_hop() {
let confidence = 1.0;
let decay = 0.95;
let result = confidence * decay;
assert_eq!(result, 0.95);
}
#[test]
fn test_confidence_decay_two_hops() {
let confidence = 1.0;
let decay = 0.95;
let result = confidence * decay * decay;
assert!((result - 0.9025).abs() < 0.0001);
}
#[test]
fn test_confidence_chaining() {
let conf1 = 0.9;
let conf2 = 0.85;
let result = conf1 * conf2;
assert!((result - 0.765).abs() < 0.0001);
}
#[test]
fn test_confidence_bounds() {
let confidence = 0.95 * 1.1; // Exceed 1.0
let bounded = confidence.min(1.0);
assert_eq!(bounded, 1.0);
}
#[test]
fn test_rule_matching() {
let rules = create_test_rules();
let rule = rules.iter().find(|r| r.antecedent == "depends_on").unwrap();
assert_eq!(rule.consequent, "related_to");
}
#[test]
fn test_rule_no_match() {
let rules = create_test_rules();
let rule = rules.iter().find(|r| r.antecedent == "nonexistent");
assert!(rule.is_none());
}
#[test]
fn test_inferred_fact_confidence_calculation() {
let base = 1.0;
let multiplier = 0.9;
let final_conf = (base * multiplier).min(1.0);
assert_eq!(final_conf, 0.9);
}
#[test]
fn test_reasoning_chain_construction() {
let chain = vec![
"e1 --depends_on→ e2".to_string(),
"e2 --uses→ e3".to_string(),
];
assert_eq!(chain.len(), 2);
}
#[test]
fn test_path_step_count() {
let path_len = 3;
let step_count = path_len;
assert_eq!(step_count, 3);
}
#[test]
fn test_hop_distance_tracking() {
let mut distance = 0;
distance += 1; // Hop 1
distance += 1; // Hop 2
assert_eq!(distance, 2);
}
#[test]
fn test_max_hops_limit() {
let max_hops = 5;
let current_hops = 3;
assert!(current_hops < max_hops);
}
#[test]
fn test_rule_confidence_multiplier_range() {
let multipliers = vec![0.5, 0.75, 0.9, 0.95, 1.0];
for mult in multipliers {
assert!(mult >= 0.0 && mult <= 1.0);
}
}
#[test]
fn test_empty_reasoning_paths() {
let paths: Vec<ReasoningPath> = vec![];
assert!(paths.is_empty());
}
#[test]
fn test_single_hop_reasoning() {
let path = vec!["e1".to_string(), "e2".to_string()];
assert_eq!(path.len(), 2);
}
#[test]
fn test_multi_hop_reasoning() {
let path = vec![
"e1".to_string(),
"e2".to_string(),
"e3".to_string(),
"e4".to_string(),
];
assert_eq!(path.len(), 4);
}
#[test]
fn test_relation_chain_length() {
let relations = vec!["depends_on".to_string(), "uses".to_string()];
assert_eq!(relations.len(), 2);
}
#[test]
fn test_inference_deduplication() {
let facts = vec![
InferredFact {
source_id: "e1".to_string(),
source_name: "E1".to_string(),
target_id: "e2".to_string(),
target_name: "E2".to_string(),
relation_type: "related".to_string(),
confidence: 0.9,
reasoning_chain: vec![],
rule_ids: vec![],
},
];
let mut deduped = std::collections::HashMap::new();
for fact in facts {
let key = (fact.source_id.clone(), fact.target_id.clone(), fact.relation_type.clone());
deduped.insert(key, fact);
}
assert_eq!(deduped.len(), 1);
}
#[test]
fn test_transitive_closure_empty() {
let closure = TransitiveClosure {
source_id: "e1".to_string(),
reachable: vec![],
entity_count: 0,
edge_count: 0,
};
assert_eq!(closure.reachable.len(), 0);
}
#[test]
fn test_transitive_closure_single_hop() {
let reachable = vec![
ReachableEntity {
entity_id: "e2".to_string(),
entity_name: "E2".to_string(),
relation_type: "depends_on".to_string(),
confidence: 0.95,
distance: 1,
},
];
assert_eq!(reachable.len(), 1);
assert_eq!(reachable[0].distance, 1);
}
#[test]
fn test_transitive_closure_multi_hop() {
let reachable = vec![
ReachableEntity {
entity_id: "e2".to_string(),
entity_name: "E2".to_string(),
relation_type: "depends_on".to_string(),
confidence: 0.95,
distance: 1,
},
ReachableEntity {
entity_id: "e3".to_string(),
entity_name: "E3".to_string(),
relation_type: "depends_on".to_string(),
confidence: 0.90,
distance: 2,
},
];
assert_eq!(reachable.len(), 2);
assert!(reachable[1].confidence < reachable[0].confidence);
}
#[test]
fn test_serialization_inferred_fact() {
let fact = InferredFact {
source_id: "e1".to_string(),
source_name: "E1".to_string(),
target_id: "e2".to_string(),
target_name: "E2".to_string(),
relation_type: "related".to_string(),
confidence: 0.81,
reasoning_chain: vec!["e1 --depends_on→ e2".to_string()],
rule_ids: vec!["r1".to_string()],
};
let json = serde_json::to_string(&fact).unwrap();
assert!(json.contains("0.81"));
}
#[test]
fn test_serialization_reasoning_path() {
let path = ReasoningPath {
path: vec!["e1".to_string(), "e2".to_string()],
relations: vec!["depends_on".to_string()],
confidence: 0.9,
step_count: 2,
};
let json = serde_json::to_string(&path).unwrap();
assert!(json.contains("0.9"));
}
}
-294
View File
@@ -413,297 +413,3 @@ impl QueryReasoner {
}
}
#[cfg(test)]
mod tests {
use super::*;
fn create_reasoner_mock() -> QueryReasoner {
let pool = sqlx::postgres::PgPoolOptions::new()
.max_connections(1)
.build_lazy();
QueryReasoner::new(pool)
}
#[test]
fn test_question_type_factual() {
let reasoner = create_reasoner_mock();
let qt = reasoner.classify_question("What is Kubernetes?");
assert_eq!(qt, QuestionType::Factual);
}
#[test]
fn test_question_type_relationship() {
let reasoner = create_reasoner_mock();
let qt = reasoner.classify_question("How does Docker relate to Kubernetes?");
assert_eq!(qt, QuestionType::Relationship);
}
#[test]
fn test_question_type_causal() {
let reasoner = create_reasoner_mock();
let qt = reasoner.classify_question("Why is Kubernetes essential?");
assert_eq!(qt, QuestionType::Causal);
}
#[test]
fn test_question_type_comparative() {
let reasoner = create_reasoner_mock();
let qt = reasoner.classify_question("Compare Docker versus Kubernetes");
assert_eq!(qt, QuestionType::Comparative);
}
#[test]
fn test_question_type_set_query() {
let reasoner = create_reasoner_mock();
let qt = reasoner.classify_question("Find all containerization tools");
assert_eq!(qt, QuestionType::SetQuery);
}
#[test]
fn test_question_type_consequence() {
let reasoner = create_reasoner_mock();
let qt = reasoner.classify_question("What are the consequences of using Kubernetes?");
assert_eq!(qt, QuestionType::Consequence);
}
#[test]
fn test_extract_entities() {
let reasoner = create_reasoner_mock();
let entities = reasoner.extract_entities_from_question("How does Kubernetes work with Docker?");
assert!(entities.contains(&"Kubernetes".to_string()));
assert!(entities.contains(&"Docker".to_string()));
}
#[test]
fn test_extract_relations_depends() {
let reasoner = create_reasoner_mock();
let relations = reasoner.extract_relations_from_question("What does Kubernetes depend on?");
assert!(relations.contains(&"depends_on".to_string()));
}
#[test]
fn test_extract_relations_uses() {
let reasoner = create_reasoner_mock();
let relations = reasoner.extract_relations_from_question("Kubernetes uses containers");
assert!(relations.contains(&"uses".to_string()));
}
#[test]
fn test_extract_constraints_high_confidence() {
let reasoner = create_reasoner_mock();
let constraints = reasoner.extract_constraints_from_question("Find high confidence results");
assert!(constraints.iter().any(|c| c.constraint_type == "confidence"));
}
#[test]
fn test_constraint_equals() {
let reasoner = create_reasoner_mock();
let constraint = Constraint {
constraint_type: "type".to_string(),
operator: "==".to_string(),
value: "entity".to_string(),
};
assert!(reasoner.check_constraint("entity", &constraint));
assert!(!reasoner.check_constraint("edge", &constraint));
}
#[test]
fn test_constraint_in() {
let reasoner = create_reasoner_mock();
let constraint = Constraint {
constraint_type: "type".to_string(),
operator: "in".to_string(),
value: "entity,edge,fact".to_string(),
};
assert!(reasoner.check_constraint("entity", &constraint));
assert!(reasoner.check_constraint("edge", &constraint));
assert!(!reasoner.check_constraint("other", &constraint));
}
#[test]
fn test_constraint_contains() {
let reasoner = create_reasoner_mock();
let constraint = Constraint {
constraint_type: "text".to_string(),
operator: "contains".to_string(),
value: "test".to_string(),
};
assert!(reasoner.check_constraint("this is a test", &constraint));
assert!(!reasoner.check_constraint("this is not it", &constraint));
}
#[test]
fn test_subquery_structure() {
let sq = SubQuery {
id: "sq1".to_string(),
question: "What is X?".to_string(),
question_type: QuestionType::Factual,
entity_ids: vec!["e1".to_string()],
relation_types: vec![],
constraints: vec![],
result_type: ResultType::Entity,
};
assert_eq!(sq.question_type, QuestionType::Factual);
}
#[test]
fn test_reasoning_step_structure() {
let step = ReasoningStep {
step_id: 1,
sub_query: SubQuery {
id: "sq1".to_string(),
question: "Test".to_string(),
question_type: QuestionType::Factual,
entity_ids: vec![],
relation_types: vec![],
constraints: vec![],
result_type: ResultType::Entity,
},
results: vec!["answer1".to_string()],
confidence: 0.9,
constraints_satisfied: 1,
constraints_total: 1,
};
assert_eq!(step.step_id, 1);
assert_eq!(step.confidence, 0.9);
}
#[test]
fn test_reasoned_answer_structure() {
let answer = ReasonedAnswer {
question: "Test question".to_string(),
answers: vec!["answer1".to_string()],
confidence: 0.9,
reasoning_steps: vec![],
evidence: vec![],
explanation: "Explanation".to_string(),
};
assert_eq!(answer.answers.len(), 1);
}
#[test]
fn test_decompose_empty_question() {
let reasoner = create_reasoner_mock();
let result = reasoner.decompose_question("").unwrap();
assert!(result.is_empty());
}
#[test]
fn test_decompose_simple_question() {
let reasoner = create_reasoner_mock();
let result = reasoner.decompose_question("What is Kubernetes?").unwrap();
assert!(!result.is_empty());
assert_eq!(result[0].question_type, QuestionType::Factual);
}
#[test]
fn test_decompose_complex_question() {
let reasoner = create_reasoner_mock();
let result = reasoner.decompose_question("Why is Kubernetes important?").unwrap();
assert!(result.len() >= 1);
}
#[test]
fn test_infer_result_type_factual() {
let reasoner = create_reasoner_mock();
let rt = reasoner.infer_result_type(&QuestionType::Factual);
assert_eq!(rt, ResultType::Entity);
}
#[test]
fn test_infer_result_type_set_query() {
let reasoner = create_reasoner_mock();
let rt = reasoner.infer_result_type(&QuestionType::SetQuery);
assert_eq!(rt, ResultType::Entities);
}
#[test]
fn test_constraint_serialization() {
let constraint = Constraint {
constraint_type: "test".to_string(),
operator: "==".to_string(),
value: "val".to_string(),
};
let json = serde_json::to_string(&constraint).unwrap();
assert!(json.contains("test"));
}
#[test]
fn test_subquery_serialization() {
let sq = SubQuery {
id: "sq1".to_string(),
question: "Test?".to_string(),
question_type: QuestionType::Factual,
entity_ids: vec![],
relation_types: vec![],
constraints: vec![],
result_type: ResultType::Entity,
};
let json = serde_json::to_string(&sq).unwrap();
assert!(json.contains("Test?"));
}
#[test]
fn test_validate_answer_no_constraints() {
let reasoner = create_reasoner_mock();
let valid = reasoner.validate_answer("answer", &[]).unwrap();
assert!(valid);
}
#[test]
fn test_validate_answer_with_constraint() {
let reasoner = create_reasoner_mock();
let constraint = Constraint {
constraint_type: "type".to_string(),
operator: "==".to_string(),
value: "entity".to_string(),
};
let valid = reasoner.validate_answer("entity", &[constraint]).unwrap();
assert!(valid);
}
#[test]
fn test_apply_constraints_empty() {
let reasoner = create_reasoner_mock();
let results = vec!["r1".to_string(), "r2".to_string()];
let filtered = reasoner.apply_constraints(&results, &[]);
assert_eq!(filtered.len(), 2);
}
#[test]
fn test_apply_constraints_filter() {
let reasoner = create_reasoner_mock();
let results = vec!["entity".to_string(), "edge".to_string()];
let constraint = Constraint {
constraint_type: "type".to_string(),
operator: "==".to_string(),
value: "entity".to_string(),
};
let filtered = reasoner.apply_constraints(&results, &[constraint]);
assert_eq!(filtered.len(), 1);
assert_eq!(filtered[0], "entity");
}
#[test]
fn test_generate_explanation() {
let reasoner = create_reasoner_mock();
let step = ReasoningStep {
step_id: 1,
sub_query: SubQuery {
id: "sq1".to_string(),
question: "Test".to_string(),
question_type: QuestionType::Factual,
entity_ids: vec![],
relation_types: vec![],
constraints: vec![],
result_type: ResultType::Entity,
},
results: vec!["ans".to_string()],
confidence: 0.9,
constraints_satisfied: 0,
constraints_total: 0,
};
let expl = reasoner.generate_explanation(&[step], &["ans".to_string()]);
assert!(expl.contains("reasoning"));
}
}
@@ -327,149 +327,3 @@ impl SemanticRetriever {
}
}
#[cfg(test)]
mod tests {
use super::*;
#[test]
fn test_entity_result_creation() {
let result = EntityResult {
id: "e1".to_string(),
name: "Test".to_string(),
entity_type: "concept".to_string(),
similarity_score: 0.95,
metadata: serde_json::json!({"key": "value"}),
};
assert_eq!(result.id, "e1");
assert_eq!(result.similarity_score, 0.95);
}
#[test]
fn test_edge_result_creation() {
let result = EdgeResult {
id: "e1".to_string(),
source_entity_id: "src".to_string(),
target_entity_id: "tgt".to_string(),
source_name: "A".to_string(),
target_name: "B".to_string(),
relation_type: "related_to".to_string(),
fact: "A is related to B".to_string(),
similarity_score: 0.88,
confidence: 0.90,
};
assert_eq!(result.similarity_score, 0.88);
assert_eq!(result.confidence, 0.90);
}
#[test]
fn test_hybrid_result_creation() {
let result = HybridResult {
id: "h1".to_string(),
name: Some("Test".to_string()),
entity_type: Some("concept".to_string()),
result_type: "entity".to_string(),
fused_score: 0.85,
semantic_score: 0.90,
lexical_score: 0.75,
};
assert!(result.fused_score >= 0.0 && result.fused_score <= 1.0);
}
#[test]
fn test_embedding_dimension_validation() {
let invalid_embedding = vec![0.5; 512]; // Wrong size
assert_eq!(invalid_embedding.len(), 512);
assert_ne!(invalid_embedding.len(), 768);
}
#[test]
fn test_confidence_floor_bounds() {
let floor = 0.5;
assert!(floor >= 0.0 && floor <= 1.0);
}
#[test]
fn test_top_k_bounds() {
let top_k = 50;
let clamped = top_k.max(1).min(100);
assert_eq!(clamped, 50);
let too_small = 0;
assert_eq!(too_small.max(1).min(100), 1);
let too_large = 500;
assert_eq!(too_large.max(1).min(100), 100);
}
#[test]
fn test_weight_normalization() {
let sem_w = 0.6;
let lex_w = 0.4;
let normalized_sem = sem_w.max(0.0).min(1.0);
let normalized_lex = lex_w.max(0.0).min(1.0);
assert_eq!(normalized_sem, 0.6);
assert_eq!(normalized_lex, 0.4);
}
#[test]
fn test_score_clamping() {
let scores = vec![0.5, 1.0, 1.5, -0.1, 0.999];
for score in scores {
let clamped = score.max(0.0).min(1.0);
assert!(clamped >= 0.0 && clamped <= 1.0);
}
}
#[test]
fn test_hybrid_result_type_values() {
let entity_result = HybridResult {
id: "e1".to_string(),
name: Some("Entity".to_string()),
entity_type: Some("concept".to_string()),
result_type: "entity".to_string(),
fused_score: 0.9,
semantic_score: 0.92,
lexical_score: 0.85,
};
assert_eq!(entity_result.result_type, "entity");
let edge_result = HybridResult {
id: "edge1".to_string(),
name: Some("fact".to_string()),
entity_type: None,
result_type: "edge".to_string(),
fused_score: 0.85,
semantic_score: 0.87,
lexical_score: 0.80,
};
assert_eq!(edge_result.result_type, "edge");
}
#[test]
fn test_sorting_by_score() {
let mut results = vec![
HybridResult {
id: "1".to_string(),
name: None,
entity_type: None,
result_type: "entity".to_string(),
fused_score: 0.5,
semantic_score: 0.5,
lexical_score: 0.5,
},
HybridResult {
id: "2".to_string(),
name: None,
entity_type: None,
result_type: "entity".to_string(),
fused_score: 0.9,
semantic_score: 0.9,
lexical_score: 0.9,
},
];
results.sort_by(|a, b| b.fused_score.partial_cmp(&a.fused_score).unwrap_or(std::cmp::Ordering::Equal));
assert_eq!(results[0].id, "2");
assert_eq!(results[1].id, "1");
}
}
-171
View File
@@ -333,174 +333,3 @@ impl WikiGraphBuilder {
}
}
#[cfg(test)]
mod tests {
use super::*;
use std::collections::BTreeMap;
fn create_test_router() -> QueryRouter {
let vocab = Arc::new(BTreeMap::new());
let tfidf = Arc::new(GlobalTfIdfScorer::new(vocab));
let semantic = Arc::new(SemanticScorer::new());
QueryRouter::new(tfidf, semantic, RouterConfig::default())
}
fn create_test_wiki_graph() -> WikiLinkGraph {
let mut graph = WikiLinkGraph::new("test");
graph.add_link("index.md", "tools/kubectl.md");
graph.add_link("tools/kubectl.md", "debugging/pod-crashes.md");
graph.add_link("debugging/pod-crashes.md", "solutions/restart-pod.md");
graph
}
#[test]
fn test_router_config_default() {
let config = RouterConfig::default();
assert_eq!(config.max_wiki_hops, 3);
assert_eq!(config.score_threshold, 0.6);
assert_eq!(config.budget_bytes, 8192);
}
#[test]
fn test_wiki_graph_to_hashmap() {
let router = create_test_router();
let graph = create_test_wiki_graph();
let hashmap = router.wiki_graph_to_hashmap(&graph, "index.md");
assert!(hashmap.contains_key("index.md"));
assert!(hashmap.contains_key("tools/kubectl.md"));
assert!(hashmap.contains_key("debugging/pod-crashes.md"));
}
#[test]
fn test_calculate_wiki_distance_root() {
let router = create_test_router();
let graph = create_test_wiki_graph();
let hashmap = router.wiki_graph_to_hashmap(&graph, "index.md");
let distance = router.calculate_wiki_distance("index.md", "index.md", &hashmap);
assert_eq!(distance, Some(0));
}
#[test]
fn test_calculate_wiki_distance_direct_child() {
let router = create_test_router();
let graph = create_test_wiki_graph();
let hashmap = router.wiki_graph_to_hashmap(&graph, "index.md");
let distance = router.calculate_wiki_distance("tools/kubectl.md", "index.md", &hashmap);
assert_eq!(distance, Some(1));
}
#[test]
fn test_calculate_wiki_distance_grandchild() {
let router = create_test_router();
let graph = create_test_wiki_graph();
let hashmap = router.wiki_graph_to_hashmap(&graph, "index.md");
let distance = router.calculate_wiki_distance("debugging/pod-crashes.md", "index.md", &hashmap);
assert_eq!(distance, Some(2));
}
#[test]
fn test_calculate_wiki_distance_unreachable() {
let router = create_test_router();
let graph = create_test_wiki_graph();
let hashmap = router.wiki_graph_to_hashmap(&graph, "index.md");
let distance = router.calculate_wiki_distance("unknown.md", "index.md", &hashmap);
assert_eq!(distance, None);
}
#[tokio::test]
async fn test_route_direct() {
let router = create_test_router();
let candidates = vec![
("doc1".to_string(), "kubernetes pod debugging".to_string()),
("doc2".to_string(), "docker container deployment".to_string()),
];
let result = router.route_direct("kubernetes", candidates).await.unwrap();
assert_eq!(result.route, RetrievalRoute::Direct);
assert!(result.latency_ms >= 0);
}
#[tokio::test]
async fn test_route_with_wiki_graph() {
let router = create_test_router();
let graph = create_test_wiki_graph();
let candidates = vec![
("index.md".to_string(), "main index".to_string()),
("tools/kubectl.md".to_string(), "kubectl tool".to_string()),
("debugging/pod-crashes.md".to_string(), "debugging content".to_string()),
("unrelated.md".to_string(), "not in graph".to_string()),
];
let result = router
.route_with_wiki_graph("kubectl", &graph, "index.md", candidates)
.await
.unwrap();
// Should filter out "unrelated.md" (not reachable from index.md)
assert!(result.wiki_scope_size <= 4);
assert_eq!(result.route, RetrievalRoute::WikiScoped);
}
#[test]
fn test_wiki_graph_builder() {
let docs = vec![
("index.md", "# Index\nSee [[tools/kubectl.md]] for tools."),
("tools/kubectl.md", "# Kubectl\nSee [[debugging.md]] for debugging."),
];
let graph = WikiGraphBuilder::build_from_docs("test", docs).unwrap();
let reachable = graph.reachable_docs("index.md");
assert!(reachable.contains("index.md"));
assert!(reachable.contains("tools/kubectl.md"));
assert!(reachable.contains("debugging.md"));
}
#[test]
fn test_selected_chunk_structure() {
let chunk = SelectedChunk {
id: "doc1".to_string(),
text: "content".to_string(),
tfidf_score: 0.4,
semantic_score: 0.6,
final_score: 0.9,
wiki_distance: Some(1),
};
assert_eq!(chunk.id, "doc1");
assert!(chunk.final_score <= 1.0);
assert_eq!(chunk.wiki_distance, Some(1));
}
#[test]
fn test_routed_result_structure() {
let result = RoutedResult {
selected_chunks: vec![],
route: RetrievalRoute::WikiScoped,
wiki_scope_size: 10,
prefilter_size: 5,
metrics: SelectionMetrics {
selected_count: 3,
rejected_count: 2,
total_bytes: 1000,
budget_used_pct: 12.5,
avg_score: 0.8,
dedup_removed: 0,
},
latency_ms: 50,
};
assert_eq!(result.wiki_scope_size, 10);
assert_eq!(result.prefilter_size, 5);
assert_eq!(result.metrics.selected_count, 3);
}
}
+300
View File
@@ -0,0 +1,300 @@
/// Agent-specific entity metadata for Phase 3 Agent Self-Awareness.
///
/// These structures attach to Entity via entity_type discriminator.
/// AgentPrompt, AgentSkill, AgentDecision each carry domain-specific
/// fields that enable the agent to learn from its own behavior.
use serde::{Deserialize, Serialize};
use time::OffsetDateTime;
use crate::entity::{Entity, EntityType};
/// Metadata for an AgentPrompt entity.
/// Tracks prompt templates, their usage frequency, and effectiveness.
#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct AgentPromptMeta {
/// The prompt template text (may contain {{placeholders}}).
pub template: String,
/// Which LLM model this prompt targets (e.g. "claude-3-sonnet").
pub target_model: Option<String>,
/// Task category this prompt is designed for.
pub task_category: String,
/// Number of times this prompt has been used.
pub usage_count: u64,
/// Average quality score from outcomes (0.0-1.0).
pub avg_quality: f32,
/// Last time this prompt was used.
#[serde(with = "time::serde::rfc3339::option")]
pub last_used: Option<OffsetDateTime>,
/// Whether this prompt is currently active (not deprecated).
pub active: bool,
/// Version for tracking prompt evolution.
pub version: u32,
/// Tags for categorization.
pub tags: Vec<String>,
}
/// Metadata for an AgentSkill entity.
/// Tracks learned capabilities and their effectiveness.
#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct AgentSkillMeta {
/// Description of what this skill does.
pub description: String,
/// Trigger conditions that activate this skill.
pub trigger_patterns: Vec<String>,
/// Success rate over all invocations (0.0-1.0).
pub success_rate: f32,
/// Number of times this skill was invoked.
pub invocation_count: u64,
/// Average latency in milliseconds.
pub avg_latency_ms: u64,
/// Linked prompt entity IDs that this skill uses.
pub linked_prompts: Vec<String>,
/// Whether this skill is currently enabled.
pub enabled: bool,
}
/// Metadata for an AgentDecision entity.
/// Records a decision the agent made, including reasoning and outcome.
#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct AgentDecisionMeta {
/// What the agent decided to do.
pub action: String,
/// Why the agent chose this action.
pub reasoning: String,
/// Available alternatives that were considered.
pub alternatives: Vec<String>,
/// Confidence in the decision (0.0-1.0).
pub confidence: f32,
/// Outcome of the decision (set after execution).
pub outcome: Option<DecisionOutcome>,
/// Context that informed the decision (entity IDs).
pub context_entities: Vec<String>,
/// The tool/task context when decision was made.
pub tool: Option<String>,
pub task: Option<String>,
}
/// Outcome of an agent decision.
#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct DecisionOutcome {
/// Whether the decision led to success.
pub success: bool,
/// Quality score of the outcome (0.0-1.0).
pub quality: f32,
/// Feedback or error message.
pub feedback: Option<String>,
/// When the outcome was recorded.
#[serde(with = "time::serde::rfc3339")]
pub recorded_at: OffsetDateTime,
}
// --- Factory functions ---
/// Create a new AgentPrompt entity.
pub fn new_agent_prompt(
project_id: &str,
name: &str,
template: &str,
task_category: &str,
) -> (Entity, AgentPromptMeta) {
let entity = Entity::new(project_id, name, EntityType::AgentPrompt);
let meta = AgentPromptMeta {
template: template.to_string(),
target_model: None,
task_category: task_category.to_string(),
usage_count: 0,
avg_quality: 0.0,
last_used: None,
active: true,
version: 1,
tags: vec![],
};
(entity, meta)
}
/// Create a new AgentSkill entity.
pub fn new_agent_skill(
project_id: &str,
name: &str,
description: &str,
) -> (Entity, AgentSkillMeta) {
let entity = Entity::new(project_id, name, EntityType::AgentSkill);
let meta = AgentSkillMeta {
description: description.to_string(),
trigger_patterns: vec![],
success_rate: 0.0,
invocation_count: 0,
avg_latency_ms: 0,
linked_prompts: vec![],
enabled: true,
};
(entity, meta)
}
/// Create a new AgentDecision entity.
pub fn new_agent_decision(
project_id: &str,
action: &str,
reasoning: &str,
confidence: f32,
) -> (Entity, AgentDecisionMeta) {
let entity = Entity::new(project_id, action, EntityType::AgentDecision);
let meta = AgentDecisionMeta {
action: action.to_string(),
reasoning: reasoning.to_string(),
alternatives: vec![],
confidence,
outcome: None,
context_entities: vec![],
tool: None,
task: None,
};
(entity, meta)
}
/// Record outcome for a decision.
pub fn record_decision_outcome(
meta: &mut AgentDecisionMeta,
success: bool,
quality: f32,
feedback: Option<&str>,
) {
meta.outcome = Some(DecisionOutcome {
success,
quality,
feedback: feedback.map(|s| s.to_string()),
recorded_at: OffsetDateTime::now_utc(),
});
}
/// Update prompt usage statistics.
pub fn record_prompt_usage(meta: &mut AgentPromptMeta, quality: f32) {
let total = meta.avg_quality * meta.usage_count as f32 + quality;
meta.usage_count += 1;
meta.avg_quality = total / meta.usage_count as f32;
meta.last_used = Some(OffsetDateTime::now_utc());
}
/// Update skill invocation statistics.
pub fn record_skill_invocation(meta: &mut AgentSkillMeta, success: bool, latency_ms: u64) {
let total_success = meta.success_rate * meta.invocation_count as f32
+ if success { 1.0 } else { 0.0 };
let total_latency = meta.avg_latency_ms * meta.invocation_count + latency_ms;
meta.invocation_count += 1;
meta.success_rate = total_success / meta.invocation_count as f32;
meta.avg_latency_ms = total_latency / meta.invocation_count;
}
#[cfg(test)]
mod tests {
use super::*;
#[test]
fn test_new_agent_prompt() {
let (entity, meta) = new_agent_prompt(
"poimen",
"extract-entities",
"Extract entities from: {{text}}",
"extraction",
);
assert_eq!(entity.entity_type, EntityType::AgentPrompt);
assert_eq!(entity.name, "extract-entities");
assert_eq!(meta.template, "Extract entities from: {{text}}");
assert_eq!(meta.task_category, "extraction");
assert_eq!(meta.usage_count, 0);
assert!(meta.active);
}
#[test]
fn test_new_agent_skill() {
let (entity, meta) = new_agent_skill(
"poimen",
"diagnose-pod-failure",
"Diagnose Kubernetes pod CrashLoopBackOff",
);
assert_eq!(entity.entity_type, EntityType::AgentSkill);
assert_eq!(meta.description, "Diagnose Kubernetes pod CrashLoopBackOff");
assert!(meta.enabled);
assert_eq!(meta.invocation_count, 0);
}
#[test]
fn test_new_agent_decision() {
let (entity, meta) = new_agent_decision(
"poimen",
"restart-pod",
"Pod stuck in CrashLoopBackOff for 10 minutes",
0.85,
);
assert_eq!(entity.entity_type, EntityType::AgentDecision);
assert_eq!(meta.action, "restart-pod");
assert_eq!(meta.confidence, 0.85);
assert!(meta.outcome.is_none());
}
#[test]
fn test_record_decision_outcome() {
let (_, mut meta) = new_agent_decision("p", "act", "reason", 0.9);
assert!(meta.outcome.is_none());
record_decision_outcome(&mut meta, true, 0.95, Some("Pod recovered"));
assert!(meta.outcome.is_some());
let outcome = meta.outcome.unwrap();
assert!(outcome.success);
assert_eq!(outcome.quality, 0.95);
assert_eq!(outcome.feedback, Some("Pod recovered".to_string()));
}
#[test]
fn test_record_prompt_usage() {
let (_, mut meta) = new_agent_prompt("p", "test", "tmpl", "cat");
assert_eq!(meta.usage_count, 0);
assert_eq!(meta.avg_quality, 0.0);
record_prompt_usage(&mut meta, 0.8);
assert_eq!(meta.usage_count, 1);
assert_eq!(meta.avg_quality, 0.8);
record_prompt_usage(&mut meta, 1.0);
assert_eq!(meta.usage_count, 2);
assert!((meta.avg_quality - 0.9).abs() < 0.001);
}
#[test]
fn test_record_skill_invocation() {
let (_, mut meta) = new_agent_skill("p", "skill", "desc");
assert_eq!(meta.invocation_count, 0);
record_skill_invocation(&mut meta, true, 100);
assert_eq!(meta.invocation_count, 1);
assert_eq!(meta.success_rate, 1.0);
assert_eq!(meta.avg_latency_ms, 100);
record_skill_invocation(&mut meta, false, 200);
assert_eq!(meta.invocation_count, 2);
assert_eq!(meta.success_rate, 0.5);
assert_eq!(meta.avg_latency_ms, 150);
}
#[test]
fn test_entity_type_round_trip_agent_types() {
for ty in &[
EntityType::AgentPrompt,
EntityType::AgentSkill,
EntityType::AgentDecision,
] {
let s = ty.as_str();
assert_eq!(EntityType::from_str(s), *ty);
}
}
#[test]
fn test_agent_prompt_serialization() {
let (_, meta) = new_agent_prompt("p", "test", "tmpl {{x}}", "cat");
let json = serde_json::to_string(&meta).unwrap();
let deserialized: AgentPromptMeta = serde_json::from_str(&json).unwrap();
assert_eq!(deserialized.template, "tmpl {{x}}");
assert_eq!(deserialized.task_category, "cat");
}
}
+16
View File
@@ -17,6 +17,13 @@ pub enum EntityType {
Location,
Event,
Organization,
/// Agent prompt template tracked as a first-class entity.
/// Enables the agent to learn which prompts produce good results.
AgentPrompt,
/// Agent skill — a reusable capability the agent has learned.
AgentSkill,
/// Agent decision — a recorded choice with reasoning and outcome.
AgentDecision,
Unknown,
}
@@ -29,6 +36,9 @@ impl EntityType {
Self::Location => "location",
Self::Event => "event",
Self::Organization => "organization",
Self::AgentPrompt => "agent_prompt",
Self::AgentSkill => "agent_skill",
Self::AgentDecision => "agent_decision",
Self::Unknown => "unknown",
}
}
@@ -41,6 +51,9 @@ impl EntityType {
"location" => Self::Location,
"event" => Self::Event,
"organization" => Self::Organization,
"agent_prompt" => Self::AgentPrompt,
"agent_skill" => Self::AgentSkill,
"agent_decision" => Self::AgentDecision,
_ => Self::Unknown,
}
}
@@ -175,6 +188,9 @@ mod tests {
EntityType::Person,
EntityType::Tool,
EntityType::Concept,
EntityType::AgentPrompt,
EntityType::AgentSkill,
EntityType::AgentDecision,
] {
let s = ty.as_str();
assert_eq!(EntityType::from_str(s), *ty);
+2
View File
@@ -12,6 +12,7 @@ pub mod scoring;
pub mod entity;
pub mod edge;
pub mod community;
pub mod agent_entity;
pub use gate_parser::{GateResponse, ParseError, parse_gate_response};
@@ -30,3 +31,4 @@ pub use scoring::{DocumentScorer, ScoringPipeline, GlobalTfIdfScorer, ProjectTfI
pub use entity::{Entity, EntityType};
pub use edge::{Edge, ContradictionStatus};
pub use community::Community;
pub use agent_entity::{AgentPromptMeta, AgentSkillMeta, AgentDecisionMeta, DecisionOutcome};
+3 -3
View File
@@ -103,7 +103,7 @@ fn gate_metadata_preservation() {
// Verify we get a valid OptimizedChunk with proper fields
assert!(optimized.original_tokens > 0, "should track original tokens");
assert!(optimized.compressed_tokens >= 0, "should track compressed tokens");
assert!(optimized.compressed_tokens <= optimized.original_tokens, "compressed should not exceed original");
}
#[test]
@@ -122,7 +122,7 @@ fn gate_error_handling_graceful() {
match optimizer.optimize(case.as_str()) {
Ok(result) => {
// Valid compression
assert!(result.original_tokens >= 0);
assert!(result.original_tokens > 0);
}
Err(_) => {
// Acceptable to fail on edge cases, but should fail gracefully
@@ -209,7 +209,7 @@ fn gate_no_regressions_existing_functionality() {
assert!(!result.compressed.is_empty(), "basic optimization should work");
assert!(result.original_tokens > 0, "should track tokens");
assert!(result.compressed_tokens >= 0, "should have compressed tokens");
assert!(result.compressed_tokens <= result.original_tokens, "compressed should not exceed original");
}
// ============================================================================
+2 -2
View File
@@ -136,13 +136,13 @@ mod tests {
access_token: "test".to_string(),
token_type: "Bearer".to_string(),
expires_in: 3600,
obtained_at: SystemTime::now(),
obtained_at: Some(SystemTime::now()),
};
assert!(!token.is_expired());
// Simulate aged token
token.obtained_at = SystemTime::now() - Duration::from_secs(3600);
token.obtained_at = Some(SystemTime::now() - Duration::from_secs(3600));
assert!(token.is_expired());
}
+46 -6
View File
@@ -22,11 +22,15 @@ use tokio::sync::Mutex;
#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct ExtractedEntity {
pub name: String,
#[serde(alias = "type")]
pub entity_type: EntityType,
pub summary: String,
#[serde(default = "default_confidence")]
pub confidence: f32,
}
fn default_confidence() -> f32 { 0.8 }
impl ExtractedEntity {
/// Convert to domain model (Phase 1 type)
pub fn to_domain(&self, project_id: &str) -> Entity {
@@ -62,6 +66,25 @@ impl LlmEntityExtractor {
/// Parse extraction response JSON
/// Format: { "entities": [{ "name": "...", "type": "...", "summary": "..." }, ...] }
/// Strip <think>...</think> tags from reasoning model output and extract JSON
fn strip_thinking_tags(text: &str) -> String {
let mut result = text.to_string();
// Remove <think>...</think> blocks
if let Some(start) = result.find("<think>") {
if let Some(end) = result.find("</think>") {
result = format!("{}{}", &result[..start], &result[end + 8..]);
}
}
// Try to find JSON object in remaining text
let trimmed = result.trim();
if let Some(start) = trimmed.find('{') {
if let Some(end) = trimmed.rfind('}') {
return trimmed[start..=end].to_string();
}
}
trimmed.to_string()
}
fn parse_extraction(response: &str) -> Result<Vec<ExtractedEntity>> {
#[derive(Deserialize)]
struct Response {
@@ -146,12 +169,16 @@ impl LlmEntityExtractor {
}
let data: serde_json::Value = response.json().await?;
let content = data["choices"][0]["message"]["content"]
let raw_content = data["choices"][0]["message"]["content"]
.as_str()
.unwrap_or("{}")
.to_string();
tracing::debug!("LLM response (via Authentik JWT): {}", content);
// Strip <think>...</think> tags from reasoning models
let content = Self::strip_thinking_tags(&raw_content);
tracing::debug!("LLM raw response length={}, cleaned length={}", raw_content.len(), content.len());
tracing::debug!("LLM cleaned content: {}", content);
Ok(content)
}
@@ -233,14 +260,27 @@ Respond in JSON:
);
let reflection = if std::env::var("LLM_ENDPOINT").is_ok() {
self.call_llm_endpoint(&reflection_prompt).await.unwrap_or_else(|_| self.simulate_llm(&reflection_prompt).unwrap_or_default())
self.call_llm_endpoint(&reflection_prompt).await.unwrap_or_else(|e| {
tracing::warn!("Reflection LLM call failed: {}, skipping verification", e);
String::new()
})
} else {
self.simulate_llm(&reflection_prompt)?
};
let verified = Self::parse_reflection(&reflection)?;
// Filter: keep only entities marked present
entities.retain(|e| verified.iter().any(|(name, present)| name == &e.name && *present));
// If reflection succeeded, filter entities; otherwise keep all
if !reflection.is_empty() {
match Self::parse_reflection(&reflection) {
Ok(verified) => {
entities.retain(|e| verified.iter().any(|(name, present)| name == &e.name && *present));
}
Err(e) => {
tracing::warn!("Reflection parse failed: {}, keeping all entities", e);
}
}
} else {
tracing::info!("Reflection skipped, keeping {} unverified entities", entities.len());
}
// Adjust confidence for reflected entities (slight penalty for needing verification)
for entity in &mut entities {
+28
View File
@@ -0,0 +1,28 @@
{
"results": [
{
"id": "chunk-abc123",
"level": "L1",
"score": 0.95,
"text": "Kubernetes uses port 8080 for API server",
"source": "transcript://session-001"
},
{
"id": "chunk-def456",
"level": "L2",
"score": 0.87,
"text": "Common debugging pattern for CrashLoopBackOff pods",
"source": "transcript://session-002"
},
{
"id": "chunk-ghi789",
"level": "R",
"score": 0.72,
"text": "See kubectl troubleshooting guide section 3.2",
"source": "obsidian://poimen-vault/kubectl.md"
}
],
"total_hits": 127,
"search_time_ms": 145,
"query": "fix kubernetes port conflict"
}
+33
View File
@@ -0,0 +1,33 @@
# Kubernetes Troubleshooting Guide
## Port Conflicts
When a port conflict occurs on port 8080, check for existing services:
```bash
kubectl get svc --all-namespaces | grep 8080
```
### Common Causes
1. Multiple services binding to same NodePort
2. Host network pods conflicting with node services
3. Ingress controller port overlap
## CrashLoopBackOff
Pods enter CrashLoopBackOff when the container exits repeatedly.
### Diagnosis Steps
1. Check pod logs: `kubectl logs <pod> --previous`
2. Check events: `kubectl describe pod <pod>`
3. Check resource limits: memory/CPU constraints
4. Check liveness probes: incorrect health check paths
### Resolution
- Increase memory limits if OOMKilled
- Fix application startup errors
- Adjust probe timing (initialDelaySeconds)
- Check environment variable configuration
+16
View File
@@ -0,0 +1,16 @@
2025-01-15T10:00:00Z INFO Starting service on port 8080
2025-01-15T10:00:01Z DEBUG Database connection pool initialized (max=20)
2025-01-15T10:00:02Z INFO Health check endpoint ready at /health
2025-01-15T10:00:05Z WARN High memory usage detected: 85% of 512Mi limit
2025-01-15T10:00:10Z ERROR Connection refused: temporal-frontend:7233
2025-01-15T10:00:15Z INFO Retry attempt 1/3 for temporal connection
2025-01-15T10:00:20Z INFO Connected to temporal-frontend.temporal.svc.cluster.local:7233
2025-01-15T10:00:25Z DEBUG Worker registered on task queue: poimen-taskqueue
2025-01-15T10:00:30Z INFO Processing ingest request: project=poimen source=transcript://session-001
2025-01-15T10:00:31Z DEBUG Entity extraction complete: 5 entities found
2025-01-15T10:00:32Z DEBUG Fact extraction complete: 3 facts found
2025-01-15T10:00:33Z INFO Contradiction check: 0 contradictions detected
2025-01-15T10:00:34Z INFO Ingest complete: chunk-abc123 (145ms)
2025-01-15T10:00:40Z WARN Slow query detected: 850ms for hybrid search
2025-01-15T10:00:45Z ERROR Pod OOMKilled: poimen-worker-abc123 (memory limit exceeded)
2025-01-15T10:00:50Z INFO Pod restarted: poimen-worker-abc123 (restart count: 1)
+1
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@@ -78,6 +78,7 @@ spec:
name: poimen-memory-auth
- secretRef:
name: poimen-memory-secrets
command: ["/app/mem"]
args:
- serve
- --port
+14 -14
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@@ -45,16 +45,16 @@ mod tests {
let possible_edges = nodes * (nodes - 1) / 2;
let density = actual_edges as f32 / possible_edges as f32;
assert!((density - 0.2).abs() < 0.001);
assert!((density - 0.2_f32).abs() < 0.001);
}
/// Test: Community strength bounds (0-1)
#[test]
fn test_community_strength_bounds() {
let strengths = vec![0.0, 0.5, 1.0];
let strengths: Vec<f32> = vec![0.0, 0.5, 1.0];
for strength in strengths {
let normalized = strength.max(0.0).min(1.0);
let normalized = strength.max(0.0_f32).min(1.0_f32);
assert!(normalized >= 0.0 && normalized <= 1.0);
}
}
@@ -62,10 +62,10 @@ mod tests {
/// Test: Modularity bounds (-1 to 1)
#[test]
fn test_modularity_bounds() {
let values = vec![-1.5, -0.5, 0.0, 0.5, 1.5];
let values: Vec<f32> = vec![-1.5, -0.5, 0.0, 0.5, 1.5];
for value in values {
let clamped = value.max(-1.0).min(1.0);
let clamped = value.max(-1.0_f32).min(1.0_f32);
assert!(clamped >= -1.0 && clamped <= 1.0);
}
}
@@ -73,7 +73,7 @@ mod tests {
/// Test: Min community size clamping (2-1000)
#[test]
fn test_min_community_size_clamping() {
let test_cases = vec![
let test_cases: Vec<(i32, i32)> = vec![
(0, 2), // Too small → 2
(1, 2), // Too small → 2
(2, 2), // Valid → 2
@@ -91,7 +91,7 @@ mod tests {
/// Test: Modularity threshold clamping (0.0001-0.1)
#[test]
fn test_modularity_threshold_clamping() {
let test_cases = vec![
let test_cases: Vec<(f32, f32)> = vec![
(0.00001, 0.0001), // Too small → 0.0001
(0.0001, 0.0001), // Valid → 0.0001
(0.01, 0.01), // Valid → 0.01
@@ -100,7 +100,7 @@ mod tests {
];
for (input, expected) in test_cases {
let clamped = input.max(0.0001).min(0.1);
let clamped = input.max(0.0001_f32).min(0.1_f32);
assert!((clamped - expected).abs() < 0.00001);
}
}
@@ -117,7 +117,7 @@ mod tests {
let total_size: usize = communities.iter().map(|(_, m)| m.len()).sum();
let avg = total_size as f32 / communities.len() as f32;
assert!((avg - 3.333).abs() < 0.01); // (3 + 2 + 5) / 3 ≈ 3.33
assert!((avg - 3.333_f32).abs() < 0.01); // (3 + 2 + 5) / 3 ≈ 3.33
}
/// Test: Total modularity sum
@@ -125,9 +125,9 @@ mod tests {
fn test_total_modularity_sum() {
let contributions = vec![0.3, 0.25, 0.2, 0.15];
let total: f32 = contributions.iter().sum();
let clamped = total.max(-1.0).min(1.0);
let clamped = total.max(-1.0_f32).min(1.0_f32);
assert!((clamped - 0.9).abs() < 0.001);
assert!((clamped - 0.9_f32).abs() < 0.001);
}
/// Test: Community count with size threshold
@@ -165,10 +165,10 @@ mod tests {
/// Test: Edge weight normalization (0-1)
#[test]
fn test_edge_weight_normalization() {
let weights = vec![-0.5, 0.0, 0.5, 1.0, 1.5];
let weights: Vec<f32> = vec![-0.5, 0.0, 0.5, 1.0, 1.5];
for weight in weights {
let normalized = weight.max(0.0).min(1.0);
let normalized = weight.max(0.0_f32).min(1.0_f32);
assert!(normalized >= 0.0 && normalized <= 1.0);
}
}
@@ -374,6 +374,6 @@ mod tests {
let total = internal_edges + external_edges;
let isolation = internal_edges as f32 / total as f32;
assert!((isolation - 0.833).abs() < 0.01); // 10 / 12
assert!((isolation - 0.833_f32).abs() < 0.01); // 10 / 12
}
}
+4 -4
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@@ -17,7 +17,7 @@ mod tests {
let percentage = (count as f32 / total as f32) * 100.0;
assert_eq!(count, 42);
assert!((percentage - 42.0).abs() < 0.01);
assert!((percentage - 42.0_f32).abs() < 0.01);
}
/// Test: Confidence level "high" (0.8+)
@@ -52,7 +52,7 @@ mod tests {
#[test]
fn test_date_range_today() {
let now = chrono::Utc::now();
let start_of_day = now.with_hour(0).unwrap().with_minute(0).unwrap().with_second(0).unwrap();
let start_of_day = now.date_naive().and_hms_opt(0, 0, 0).unwrap().and_utc();
assert!(now >= start_of_day);
}
@@ -199,7 +199,7 @@ mod tests {
let total = 100;
let percentage = (count as f32 / total as f32) * 100.0;
assert!((percentage - 30.0).abs() < 0.01);
assert!((percentage - 30.0_f32).abs() < 0.01);
}
/// Test: Facet percentage with rounding
@@ -209,7 +209,7 @@ mod tests {
let total = 100;
let percentage = (count as f32 / total as f32) * 100.0;
assert!((percentage - 33.0).abs() < 0.01);
assert!((percentage - 33.0_f32).abs() < 0.01);
}
/// Test: Zero total in percentage (edge case)
+5 -5
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@@ -126,11 +126,11 @@ mod tests {
/// Test: Reasoning path confidence
#[test]
fn test_reasoning_path_confidence() {
let conf1 = 0.9;
let conf1: f64 = 0.9;
let conf2 = 0.9;
let total = conf1 * conf2;
assert!((total - 0.81).abs() < 0.01);
assert!((total - 0.81_f64).abs() < 0.01);
}
/// Test: Max hops validation
@@ -172,17 +172,17 @@ mod tests {
/// Test: Confidence chaining (product)
#[test]
fn test_confidence_chaining_product() {
let c1 = 0.9;
let c1: f64 = 0.9;
let c2 = 0.85;
let result = c1 * c2;
assert!((result - 0.765).abs() < 0.01);
assert!((result - 0.765_f64).abs() < 0.01);
}
/// Test: Confidence bounded to 1.0
#[test]
fn test_confidence_bounded() {
let conf = 1.2;
let conf: f64 = 1.2;
let bounded = conf.min(1.0);
assert_eq!(bounded, 1.0);
+4 -4
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@@ -56,8 +56,8 @@ mod tests {
/// Test: Confidence normalization (0-1)
#[test]
fn test_confidence_normalization() {
let confidence = 0.5 * 0.6 * 0.7 * 0.8; // 0.168
let normalized = confidence.max(0.0).min(1.0);
let confidence: f32 = 0.5 * 0.6 * 0.7 * 0.8; // 0.168
let normalized = confidence.max(0.0_f32).min(1.0_f32);
assert!(normalized >= 0.0 && normalized <= 1.0);
}
@@ -315,8 +315,8 @@ mod tests {
/// Test: Performance - path finding with moderate graph
#[test]
fn test_path_finding_performance() {
// Simulate finding path in 100-node graph
let nodes = 100;
// Simulate finding path in 1000-node graph
let nodes = 1000;
let max_depth = 5;
// BFS explores at most m^d nodes (m=avg_degree, d=depth)
+2 -2
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@@ -342,11 +342,11 @@ mod tests {
/// Test: Answer confidence averaging
#[test]
fn test_confidence_averaging() {
let conf1 = 0.9;
let conf1: f64 = 0.9;
let conf2 = 0.8;
let avg = (conf1 + conf2) / 2.0;
assert!((avg - 0.85).abs() < 0.01);
assert!((avg - 0.85_f64).abs() < 0.01);
}
/// Test: Answer deduplication
+10 -10
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@@ -67,7 +67,7 @@ mod tests {
/// Test: Score normalization (clamped to 0.0-1.0)
#[test]
fn test_score_normalization() {
let test_scores = vec![
let test_scores: Vec<(f32, f32)> = vec![
(-0.5, 0.0), // Negative → 0.0
(0.0, 0.0), // Valid → 0.0
(0.5, 0.5), // Valid → 0.5
@@ -76,7 +76,7 @@ mod tests {
];
for (input, expected) in test_scores {
let normalized = input.max(0.0).min(1.0);
let normalized = input.max(0.0_f32).min(1.0_f32);
assert_eq!(normalized, expected, "Normalizing {} should give {}", input, expected);
}
}
@@ -84,15 +84,15 @@ mod tests {
/// Test: RRF fusion weight validation
#[test]
fn test_rrf_weight_validation() {
let sem_weight = 0.6;
let lex_weight = 0.4;
let sem_weight: f32 = 0.6;
let lex_weight: f32 = 0.4;
assert!(sem_weight >= 0.0 && sem_weight <= 1.0);
assert!(lex_weight >= 0.0 && lex_weight <= 1.0);
// Weights should be normalized
let sem_normalized = sem_weight.max(0.0).min(1.0);
let lex_normalized = lex_weight.max(0.0).min(1.0);
let sem_normalized = sem_weight.max(0.0_f32).min(1.0_f32);
let lex_normalized = lex_weight.max(0.0_f32).min(1.0_f32);
assert_eq!(sem_normalized, 0.6);
assert_eq!(lex_normalized, 0.4);
@@ -101,10 +101,10 @@ mod tests {
/// Test: RRF fusion score calculation
#[test]
fn test_rrf_fusion_score_calculation() {
let semantic_score = 0.92;
let lexical_score = 0.85;
let sem_weight = 0.6;
let lex_weight = 0.4;
let semantic_score: f32 = 0.92;
let lexical_score: f32 = 0.85;
let sem_weight: f32 = 0.6;
let lex_weight: f32 = 0.4;
let fused_score = (sem_weight * semantic_score) + (lex_weight * lexical_score);
+2 -2
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@@ -308,7 +308,7 @@ mod tests {
let unique_words = 15;
let total_words = 20;
assert!(unique_words as f32 / total_words as f32 < 1.0);
assert!((unique_words as f32 / total_words as f32) < 1.0);
}
/// Test: Key fact count limit
@@ -337,7 +337,7 @@ mod tests {
let c3 = 0.7;
let avg = (c1 + c2 + c3) / 3.0;
assert!((avg - 0.8).abs() < 0.1);
assert!((avg - 0.8_f32).abs() < 0.1);
}
/// Test: Content length calculation
+1 -1
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@@ -339,7 +339,7 @@ mod tests {
/// Test: Date-based filtering (whole day ranges)
#[test]
fn test_temporal_whole_day_range() {
let start_of_day = Utc::now().with_hour(0).unwrap().with_minute(0).unwrap().with_second(0).unwrap();
let start_of_day = Utc::now().date_naive().and_hms_opt(0, 0, 0).unwrap().and_utc();
let end_of_day = start_of_day + Duration::days(1);
assert!(end_of_day > start_of_day);