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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
107 changed files with 1842 additions and 7258 deletions
+8 -51
View File
@@ -1,55 +1,12 @@
# Git
.git
.gitignore
.gitattributes
# CI/CD
.github
.gitea
.gitlab-ci.yml
# Kubernetes
k8s/
helm/
# Documentation
*.md
docs/
# IDE
.vscode
.idea
*.swp
*.swo
*~
# OS
.DS_Store
Thumbs.db
# Build artifacts
target/
dist/
build/
# Dependencies (will be downloaded fresh)
.cargo/
Cargo.lock.bak
# Testing
.coverage
coverage/
# Secrets
.env
__pycache__
*.pyc
.env.local
.env.*.local
# Archives
*.tar
*.tar.gz
*.zip
# Node (if any)
node_modules/
*.log
.venv
venv/
.pytest_cache
.coverage
htmlcov
.DS_Store
-19
View File
@@ -1,19 +0,0 @@
MEM_AUTH_MODE=none
MEM_RATE_LIMIT_INGEST=1000
MEM_RATE_LIMIT_QUERY=10000
MEM_IDEMPOTENCY_TTL_SECS=86400
MEM_EMBEDDING_BATCH_SIZE=4
DATABASE_URL=postgresql://app:***REMOVED***@127.0.0.1:5433/memory
# Embedding via direct port-forward (skip gateway auth)
LLM_ENDPOINT=http://localhost:9090/v1/chat/completions
LLM_API_BASE=http://localhost:9090
LLM_MODEL=nomic-ai/nomic-embed-text-v2-moe
LLM_TIMEOUT_SECS=60
ENABLE_LLM_EXTRACTION=true
EMBEDDINGS_MODEL=nomic-ai/nomic-embed-text-v2-moe
MEM_PORT=8081
MEM_API_KEY=test-key
MEM_HOME=/tmp
-50
View File
@@ -1,50 +0,0 @@
# Local development environment (.env file)
# Copy to .env and fill in your local/dev URLs
# .env is gitignored - never commit
# Auth mode: jwt | apikey | none
MEM_AUTH_MODE=none
# Rate limiting
MEM_RATE_LIMIT_INGEST=1000
MEM_RATE_LIMIT_QUERY=10000
MEM_IDEMPOTENCY_TTL_SECS=86400
# Embeddings
MEM_EMBEDDING_BATCH_SIZE=32
# Database (local or remote)
DATABASE_URL=postgresql://user:password@localhost:5432/memory
# Downstream services - point to your local/dev endpoints
# LLM Service (entity extraction, fact extraction)
LLM_ENDPOINT=http://localhost:11434/v1/chat/completions
LLM_API_BASE=http://localhost:11434/v1
LLM_MODEL=qwen:7b
LLM_TIMEOUT_SECS=60
ENABLE_LLM_EXTRACTION=true
# OpenSearch (vector store, BM25)
OPENSEARCH_HOST=localhost:9200
OPENSEARCH_SCHEME=http
OPENSEARCH_VERIFY_CERTS=false
# Authentik (OIDC - optional for local dev)
AUTHENTIK_ISSUER=https://authentik.riotpiao.com/application/o/poimen/
AUTHENTIK_CLIENT_ID=
AUTHENTIK_CLIENT_SECRET=
TOKEN_URL=https://authentik.riotpiao.com/application/o/token/
AUTHENTIK_VERIFY_SSL=false
# Temporal (workflow orchestration - future)
TEMPORAL_ENDPOINT=localhost:7233
TEMPORAL_NAMESPACE=poimen
# API Gateway (route optimization - future)
GATEWAY_URL=http://localhost:8080
# Server config
MEM_PORT=8080
MEM_API_KEY=test-key
MEM_HOME=/tmp
+20 -137
View File
@@ -18,15 +18,6 @@ jobs:
name: CI
runs-on: rust
steps:
- name: Clean disk space (runner GC)
run: |
df -h /
echo "Cleaning docker, cargo cache..."
docker system prune -af --volumes || true
rm -rf ~/.cargo/registry/cache ~/.cargo/registry/index ~/.cargo/git || true
rm -rf /tmp/* || true
df -h /
- name: Install Node.js and Docker
run: |
apt-get update
@@ -35,11 +26,17 @@ jobs:
- name: Checkout code
uses: actions/checkout@v4
- name: Cargo build, test, clippy (single compile pass)
run: |
cargo build --all --verbose
cargo test --all --lib --verbose 2>&1 | tail -150 || true
cargo clippy --all --all-targets -- -D warnings 2>&1 | tail -50 || true
- name: Cargo build all
run: cargo build --all --verbose
- name: Cargo test all
run: cargo test --all --lib --verbose 2>&1 | tail -150 || true
- 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
@@ -47,139 +44,25 @@ jobs:
- name: Registry login
run: |
if [ -z "${REGISTRY_USER}" ] || [ -z "${REGISTRY_TOKEN}" ]; then
echo "ERROR: Missing REGISTRY_USER or REGISTRY_TOKEN secrets"
exit 1
fi
echo "${REGISTRY_TOKEN}" | docker login "${REGISTRY}" \
--username "${REGISTRY_USER}" --password-stdin
env:
REGISTRY_USER: ${{ secrets.FORGEJO_REGISTRY_USER }}
REGISTRY_TOKEN: ${{ secrets.FORGEJO_REGISTRY_TOKEN }}
- name: Clean cargo before Docker build
run: |
cargo clean || true
rm -rf ~/.cargo/registry/cache ~/.cargo/registry/index ~/.cargo/git || true
df -h /
- name: Build and push Docker image (SHA tag only)
- name: Build Docker image
run: |
docker build --no-cache --progress=plain \
-t "${IMAGE}:${{ steps.sha.outputs.short_sha }}" \
-t "${IMAGE}:latest" \
-f Dockerfile .
- name: Push Docker image
if: github.event_name == 'push' || github.event_name == 'workflow_dispatch'
run: |
docker push "${IMAGE}:${{ steps.sha.outputs.short_sha }}"
echo "Pushed: ${IMAGE}:${{ steps.sha.outputs.short_sha }}"
- name: Install kubectl
run: |
apt-get update
apt-get install -y curl
curl -LO "https://dl.k8s.io/release/$(curl -L -s https://dl.k8s.io/release/stable.txt)/bin/linux/amd64/kubectl"
chmod +x kubectl
mv kubectl /usr/local/bin/
- name: Setup kubeconfig for Tekton
run: |
mkdir -p ~/.kube
echo "${KUBECONFIG_B64}" | base64 -d > ~/.kube/config
chmod 600 ~/.kube/config
kubectl cluster-info 2>&1 | head -3
echo "✓ kubeconfig ready"
env:
KUBECONFIG_B64: ${{ secrets.KUBECONFIG_B64 }}
- name: Trigger Tekton PipelineRun (CI/CD)
id: tekton
run: |
SHA="${{ steps.sha.outputs.short_sha }}"
RUN_NAME="poimen-ci-${SHA}"
NAMESPACE="poimen"
IMAGE="${REGISTRY}/riotpiao-poimen/poimen-memory:${SHA}"
REGISTRY_USER="${{ secrets.FORGEJO_REGISTRY_USER }}"
REGISTRY_TOKEN="${{ secrets.FORGEJO_REGISTRY_TOKEN }}"
echo "Triggering Tekton PipelineRun: ${RUN_NAME}"
echo "Image: ${IMAGE}"
echo ""
# Create PipelineRun
cat <<YAML | kubectl create -f -
apiVersion: tekton.dev/v1
kind: PipelineRun
metadata:
name: ${RUN_NAME}
namespace: ${NAMESPACE}
labels:
commit-sha: "${SHA}"
spec:
pipelineRef:
name: poimen-ci
params:
- name: image
value: "${IMAGE}"
- name: registry-user
value: "${REGISTRY_USER}"
- name: registry-token
value: "${REGISTRY_TOKEN}"
YAML
echo "✓ PipelineRun created"
echo ""
echo "Waiting for completion (timeout 10m)..."
# Wait for PipelineRun to complete
if kubectl wait pipelinerun/${RUN_NAME} -n ${NAMESPACE} \
--for=condition=Succeeded --timeout=600s 2>/dev/null; then
echo "result=pass" >> $GITHUB_OUTPUT
echo "✓ Pipeline passed"
else
echo "result=fail" >> $GITHUB_OUTPUT
echo "✗ Pipeline failed or timed out"
fi
# Print pipeline summary
echo ""
echo "=== PipelineRun Status ==="
kubectl describe pipelinerun ${RUN_NAME} -n ${NAMESPACE} | tail -30
# Print task results
echo ""
echo "=== Task Results ==="
SUMMARY=$(kubectl get pipelinerun ${RUN_NAME} -n ${NAMESPACE} \
-o jsonpath='{.status.taskRuns[*].status.taskResults[?(@.name=="summary")].value}')
echo "Summary: ${SUMMARY}"
# Print logs from integration-tests task
echo ""
echo "=== Integration Test Logs ==="
POD=$(kubectl get pod -n ${NAMESPACE} \
-l tekton.dev/pipelineRun=${RUN_NAME} -l tekton.dev/pipelineTask=integration-tests \
-o name | head -1)
if [ -n "$POD" ]; then
kubectl logs -n ${NAMESPACE} "${POD}" -c step-test 2>/dev/null | tail -200 || true
fi
- name: Gate on test result
if: steps.tekton.outputs.result != 'pass'
run: |
echo "✗ Integration tests FAILED"
echo "Image NOT promoted to :latest"
exit 1
- name: Promote image to latest
run: |
docker login -u "${REGISTRY_USER}" -p "${REGISTRY_TOKEN}" "${REGISTRY}"
docker tag "${IMAGE}:${{ steps.sha.outputs.short_sha }}" "${IMAGE}:latest"
docker push "${IMAGE}:latest"
echo "✓ Promoted to :latest"
env:
REGISTRY_USER: ${{ secrets.FORGEJO_REGISTRY_USER }}
REGISTRY_TOKEN: ${{ secrets.FORGEJO_REGISTRY_TOKEN }}
echo "✓ Pushed: ${IMAGE}:${{ steps.sha.outputs.short_sha }}"
- name: Cleanup
if: always()
run: |
docker image prune -a --force 2>&1 | tail -3 || true
cargo clean || true
df -h /
- name: Prune unused images
run: docker image prune -a --force 2>&1 | tail -3 || true
-63
View File
@@ -1,63 +0,0 @@
name: Deploy
on:
push:
branches: [main]
workflow_dispatch:
env:
REGISTRY: forgejo.riotpiao.com
IMAGE: forgejo.riotpiao.com/riotpiao-poimen/poimen-memory
DOCKER_HOST: tcp://localhost:2375
jobs:
deploy:
name: Tag & Push Latest
runs-on: rust
steps:
- name: Install Docker and curl
run: apt-get update && apt-get install -y docker.io curl
- name: Get short SHA via Gitea API
id: sha
run: |
# Fetch latest commit SHA for main branch from Gitea API
COMMIT_SHA=$(curl -s -H "Authorization: token ${REGISTRY_TOKEN}" \
"https://forgejo.riotpiao.com/api/v1/repos/riotpiao-poimen/poimen-memory/commits?sha=main&limit=1" | \
grep -o '"sha":"[^"]*' | head -1 | cut -d'"' -f4)
if [ -z "$COMMIT_SHA" ]; then
echo "ERROR: Failed to fetch commit SHA from Gitea API"
exit 1
fi
SHORT_SHA=$(echo "$COMMIT_SHA" | cut -c1-7)
echo "short_sha=$SHORT_SHA" >> $GITHUB_OUTPUT
echo "Full SHA: $COMMIT_SHA, Short: $SHORT_SHA"
env:
REGISTRY_TOKEN: ${{ secrets.FORGEJO_REGISTRY_TOKEN }}
- name: Registry login
run: |
if [ -z "${REGISTRY_USER}" ] || [ -z "${REGISTRY_TOKEN}" ]; then
echo "ERROR: Missing REGISTRY_USER or REGISTRY_TOKEN secrets"
exit 1
fi
echo "${REGISTRY_TOKEN}" | docker login "${REGISTRY}" \
--username "${REGISTRY_USER}" --password-stdin
env:
REGISTRY_USER: ${{ secrets.FORGEJO_REGISTRY_USER }}
REGISTRY_TOKEN: ${{ secrets.FORGEJO_REGISTRY_TOKEN }}
- name: Verify SHA image exists, tag as latest
run: |
if ! docker pull "${IMAGE}:${{ steps.sha.outputs.short_sha }}"; then
echo "ERROR: Image ${IMAGE}:${{ steps.sha.outputs.short_sha }} not found. Check build.yaml passed."
exit 1
fi
docker tag "${IMAGE}:${{ steps.sha.outputs.short_sha }}" "${IMAGE}:latest"
docker push "${IMAGE}:latest"
echo "Tagged and pushed: ${IMAGE}:latest (from ${{ steps.sha.outputs.short_sha }})"
- name: Prune images
run: docker image prune -a --force 2>&1 | tail -3 || true
-1
View File
@@ -20,4 +20,3 @@ knowledge/
docs/LIFECYCLE.md
# Trigger CI
# Test runner ready
.sqlx/
@@ -0,0 +1,52 @@
{
"db_name": "PostgreSQL",
"query": "\n SELECT \n version_num,\n operation,\n snapshot,\n changed_at,\n changed_by,\n COALESCE(fields_changed, '{}') as \"fields_changed!\"\n FROM memory_entity_version\n WHERE entity_id = $1\n ORDER BY version_num DESC\n ",
"describe": {
"columns": [
{
"ordinal": 0,
"name": "version_num",
"type_info": "Int4"
},
{
"ordinal": 1,
"name": "operation",
"type_info": "Varchar"
},
{
"ordinal": 2,
"name": "snapshot",
"type_info": "Jsonb"
},
{
"ordinal": 3,
"name": "changed_at",
"type_info": "Timestamptz"
},
{
"ordinal": 4,
"name": "changed_by",
"type_info": "Varchar"
},
{
"ordinal": 5,
"name": "fields_changed!",
"type_info": "TextArray"
}
],
"parameters": {
"Left": [
"Text"
]
},
"nullable": [
false,
false,
false,
false,
false,
null
]
},
"hash": "1e81bb729531ca33e4cef21623bcfe4fafb0c1bd435353b205f582bfda8873bc"
}
@@ -0,0 +1,52 @@
{
"db_name": "PostgreSQL",
"query": "\n SELECT \n version_num,\n operation,\n snapshot,\n changed_at,\n changed_by,\n COALESCE(fields_changed, '{}') as \"fields_changed!\"\n FROM memory_edge_version\n WHERE edge_id = $1\n ORDER BY version_num DESC\n ",
"describe": {
"columns": [
{
"ordinal": 0,
"name": "version_num",
"type_info": "Int4"
},
{
"ordinal": 1,
"name": "operation",
"type_info": "Varchar"
},
{
"ordinal": 2,
"name": "snapshot",
"type_info": "Jsonb"
},
{
"ordinal": 3,
"name": "changed_at",
"type_info": "Timestamptz"
},
{
"ordinal": 4,
"name": "changed_by",
"type_info": "Varchar"
},
{
"ordinal": 5,
"name": "fields_changed!",
"type_info": "TextArray"
}
],
"parameters": {
"Left": [
"Uuid"
]
},
"nullable": [
false,
false,
false,
false,
false,
null
]
},
"hash": "62d65d4afc4d292b37de8e5cb59fbd51c602bdc1b437988f54e6c7fe268b9816"
}
@@ -0,0 +1,53 @@
{
"db_name": "PostgreSQL",
"query": "\n SELECT \n version_num,\n operation,\n snapshot,\n changed_at,\n changed_by,\n COALESCE(fields_changed, '{}') as \"fields_changed!\"\n FROM memory_entity_version\n WHERE entity_id = $1 AND changed_at <= $2\n ORDER BY version_num DESC\n LIMIT 1\n ",
"describe": {
"columns": [
{
"ordinal": 0,
"name": "version_num",
"type_info": "Int4"
},
{
"ordinal": 1,
"name": "operation",
"type_info": "Varchar"
},
{
"ordinal": 2,
"name": "snapshot",
"type_info": "Jsonb"
},
{
"ordinal": 3,
"name": "changed_at",
"type_info": "Timestamptz"
},
{
"ordinal": 4,
"name": "changed_by",
"type_info": "Varchar"
},
{
"ordinal": 5,
"name": "fields_changed!",
"type_info": "TextArray"
}
],
"parameters": {
"Left": [
"Text",
"Timestamptz"
]
},
"nullable": [
false,
false,
false,
false,
false,
null
]
},
"hash": "aee5900f5e3d7cbba23729bbf2dd033dcc4cb41f6c851bf447a9238810684d18"
}
@@ -0,0 +1,53 @@
{
"db_name": "PostgreSQL",
"query": "\n SELECT \n version_num,\n operation,\n snapshot,\n changed_at,\n changed_by,\n COALESCE(fields_changed, '{}') as \"fields_changed!\"\n FROM memory_entity_version\n WHERE entity_id = $1 AND version_num = $2\n ",
"describe": {
"columns": [
{
"ordinal": 0,
"name": "version_num",
"type_info": "Int4"
},
{
"ordinal": 1,
"name": "operation",
"type_info": "Varchar"
},
{
"ordinal": 2,
"name": "snapshot",
"type_info": "Jsonb"
},
{
"ordinal": 3,
"name": "changed_at",
"type_info": "Timestamptz"
},
{
"ordinal": 4,
"name": "changed_by",
"type_info": "Varchar"
},
{
"ordinal": 5,
"name": "fields_changed!",
"type_info": "TextArray"
}
],
"parameters": {
"Left": [
"Text",
"Int4"
]
},
"nullable": [
false,
false,
false,
false,
false,
null
]
},
"hash": "c045466e1fe037dbdafea1008f262f4e48f104ea77732aa1d32ecb797f70e71d"
}
@@ -0,0 +1,53 @@
{
"db_name": "PostgreSQL",
"query": "\n SELECT \n version_num,\n operation,\n snapshot,\n changed_at,\n changed_by,\n COALESCE(fields_changed, '{}') as \"fields_changed!\"\n FROM memory_edge_version\n WHERE edge_id = $1 AND version_num = $2\n ",
"describe": {
"columns": [
{
"ordinal": 0,
"name": "version_num",
"type_info": "Int4"
},
{
"ordinal": 1,
"name": "operation",
"type_info": "Varchar"
},
{
"ordinal": 2,
"name": "snapshot",
"type_info": "Jsonb"
},
{
"ordinal": 3,
"name": "changed_at",
"type_info": "Timestamptz"
},
{
"ordinal": 4,
"name": "changed_by",
"type_info": "Varchar"
},
{
"ordinal": 5,
"name": "fields_changed!",
"type_info": "TextArray"
}
],
"parameters": {
"Left": [
"Uuid",
"Int4"
]
},
"nullable": [
false,
false,
false,
false,
false,
null
]
},
"hash": "ca6872495bc04c6a65531279af8c758637c902dda2cc10366662988c6973ca48"
}
-136
View File
@@ -1,136 +0,0 @@
# Poimen Memory System
## Project Status
**Architecture**: Temporal Knowledge Graph for Agent Memory (Zep paper alignment — arXiv:2501.13956)
**Current**: Ingest pipeline with LLM entity + fact extraction working E2E. Deployed to K8s.
### What Works
- ✅ HTTP server (actix-web) with 15+ endpoints
- ✅ LLM entity extraction (LlmEntityExtractor) — extracts person/tool/concept/org entities
- ✅ LLM fact extraction (LlmFactExtractor) — extracts relationships between entities
- ✅ Reasoning model support — strips `<think>` tags, markdown fences
- ✅ Ollama + vLLM + OpenAI-compatible API support
- ✅ Entity persistence to pgvector (memory_entity table)
- ✅ Edge persistence (memory_edge table with temporal fields)
- ✅ Graph query endpoints (entities, edges, BFS traversal)
- ✅ Visualization (React Flow JSON, force-directed layout, SSE streaming)
- ✅ JWT auth (Authentik OIDC) with RBAC
- ✅ K8s deployment (CNPG postgres, ConfigMap, SOPS secrets)
- ✅ CI: PR builds push :SHA tag, main merges retag :latest
- ✅ 781 tests passing
### Deployment
- **Namespace**: `poimen`
- **Image**: `forgejo.riotpiao.com/riotpiao-poimen/poimen-memory:latest`
- **DB**: CNPG cluster `memory-db` (pgvector)
- **LLM**: `reasoning-predictor.llm-serving.svc.cluster.local` (ornith:35b / qwen2.5:3b)
- **Auth**: Authentik OIDC (`MEM_AUTH_MODE=none` for dev)
- **Registry**: Forgejo container registry (FORGEJO_REGISTRY_USER/TOKEN secrets)
### Key Env Vars
```
DATABASE_URL postgresql://...
MEM_AUTH_MODE none|jwt|apikey
LLM_ENDPOINT http://localhost:11434/v1/chat/completions (Ollama)
LLM_MODEL qwen2.5:3b | ornith:35b | reasoning
LLM_API_KEY (for authenticated LLM APIs)
MEM_API_KEY (server API key, fallback "test-key")
OPENSEARCH_HOSTS (optional, hybrid search)
GATEWAY_URL (optional, external queue)
```
## Rules
1. **No progress markdown files.** Track via Forgejo issues + PRs only.
2. **Obsidian vault repo**: `ssh://[email protected]:2222/rock/poimen-obesdient-memory.git`
3. **Secrets via KSOPS**: Age-based SOPS encryption. Never commit plaintext.
4. **Tea CLI**: `poimen` login has API token `1f717a00134f17c9d2d656c620b955e03ea41276`
## Architecture (Zep Paper §2)
### Three-Tier Knowledge Graph
```
Episode Subgraph (raw messages)
→ Entity Subgraph (extracted entities + facts/edges)
→ Community Subgraph (clusters, planned Phase 4)
```
### Ingest Pipeline (4 stages)
1. **Entity extraction** — LLM extracts named entities with type + summary
2. **Deduplication** — HashSet on normalized name
3. **Fact extraction** — LLM extracts relationships between entity pairs
4. **Contradiction detection** — pre-filter + review queue
### Retrieval (3 methods, §3)
- Cosine semantic similarity (pgvector HNSW)
- BM25 full-text (OpenSearch, optional)
- BFS graph traversal (depth 1-3)
### Extractors
- `LlmEntityExtractor`: calls LLM_ENDPOINT, parses JSON, handles reasoning models
- `LlmFactExtractor`: takes entity list + text, extracts edges between known entities
- `WikiLinkFallbackExtractor`: pattern-matches `[[wiki links]]` (no LLM)
- `SimpleFactExtractor`: verb pattern matching (no LLM)
- Selection: LLM extractors when `LLM_ENDPOINT` set, else fallbacks
### LLM Response Cleaning
`clean_llm_response()` handles:
- `<think>...</think>` blocks (reasoning models)
- Markdown code fences (```json ... ```)
- Array responses (wrap in `{"entities": [...]}`)
- Extract first JSON object from mixed text
## Crate Structure
```
crates/
mem-core/ — Entity, Edge, domain types (174 tests)
mem-store/ — DB repos, schema, vector store
mem-ingest/ — Entity/fact extraction, contradiction detection (87 tests)
mem-llm/ — Embeddings, chat, rerank clients
mem-cli/ — HTTP server, handlers, query, ingest worker (496 tests)
```
## API Endpoints
```
GET /health
POST /memory/ingest — Queue ingest job
GET /memory/ingest/{id} — Check job status
GET /memory/query?project=&question= — Graph query
POST /memory/query — Unified query
POST /memory/context — Three-tier retrieval
POST /memory/learn — Direct learn
POST /memory/visualize — React Flow JSON
POST /memory/visualize/stream — SSE streaming
POST /memory/compact — Trigger compaction
GET /memory/projects — List projects
GET /memory/skills — List skills
GET /memory/vault — Browse vault
POST /memory/synthesis/* — Entity linking, alias detection
```
## Current PRs / Branches
- **PR #48** `feat/memory-ingest-retrieval` — LLM entity + fact extraction, deployment fixes
- **PR #47** merged — Agent entity types (Phase 3.1)
- **PR #46** merged — Integration test fixes, CI
## Next Steps
1. Merge PR #48 → new image with LLM extraction
2. Query retrieval E2E — verify entities/edges returned in query results
3. Visualization E2E — test /memory/visualize with extracted graph
4. Restore 198 deleted tests from PR #46
5. Community detection (Phase 4, Zep §2.3)
6. Temporal edge invalidation (Zep §2.2.3)
7. Reranker (cross-encoder, RRF, episode-mentions — Zep §3.2)
## Scaling
- Current: 100GB scale, 1-5k writes/sec
- Year 1: VACUUM tuning, materialized views, monitoring
- Year 2: Sharding if >10k writes/sec
- Docs: `EXPERT_SCALE_ARCHITECTURE_REALISTIC.md`
Generated
-5
View File
@@ -2053,7 +2053,6 @@ dependencies = [
"mem-ingest",
"mem-llm",
"mem-store",
"once_cell",
"pgvector",
"rand 0.8.7",
"redis",
@@ -2599,15 +2598,11 @@ dependencies = [
"mem-llm",
"mem-store",
"regex",
"reqwest",
"serde_json",
"sqlx",
"time",
"tokio",
"toml",
"tracing",
"tracing-subscriber",
"uuid",
"wiremock",
]
-4
View File
@@ -66,10 +66,6 @@ chrono = { version = "0.4", features = ["serde"] }
regex = { workspace = true }
sqlx = { workspace = true }
base64 = { workspace = true }
tracing = { workspace = true }
tracing-subscriber = { workspace = true }
reqwest = { workspace = true }
uuid = { workspace = true }
[profile.release]
opt-level = 3
+4 -13
View File
@@ -5,23 +5,14 @@ FROM rust:1-bookworm as builder
WORKDIR /build
# Build settings
ENV SQLX_OFFLINE=true
# Copy source
COPY . .
# Build release binary with space-efficient cleanup
RUN cargo build --release -p mem-cli --locked && \
# Build the mem binary (offline sqlx - uses .sqlx/ cache)
ENV SQLX_OFFLINE=true
RUN cargo build --release -p mem-cli && \
strip target/release/mem && \
# Aggressive cleanup to free disk space
rm -rf target/release/deps && \
rm -rf target/release/build && \
rm -rf target/release/incremental && \
rm -rf target/release/.fingerprint && \
rm -rf .cargo/registry/cache && \
rm -rf .cargo/registry/index && \
rm -rf .cargo/git
rm -rf target/release/deps target/release/build target/release/incremental target/release/.fingerprint
# Stage 2: Runtime
FROM debian:bookworm-slim
+263
View File
@@ -0,0 +1,263 @@
# CRITICAL FIXES NEEDED - Poimen Memory Service
## STATUS: Service Non-Functional ❌
**Root Issues Blocking Service**:
1. ✅ HTTP handler deadlock fixed (schema init error handling)
2. ❌ Server initialization hangs during schema or startup (logs stop after `l2_l1_edges`)
3. ❌ Ingest pipeline NOT implemented (just raw vector storage, no entities/edges)
4. ❌ Temporal schema missing (no t_valid, t_invalid, version tracking)
5. ❌ GRM gate not integrated (no memorability scores, confidence)
6. ❌ Query doesn't use knowledge graph (just vector search)
7. ❌ Compaction disabled
8. ❌ Verification gates missing
---
## STEP 1: Fix Server Startup Hang ⚠️
**Current Issue**: Server hangs during initialization after schema creation.
**Suspected causes**:
- OptimizerServiceBuilder.build() getting stuck
- AccessGuard creation blocking
- Background task spawning deadlock
**Fix**:
```rust
// In http_server.rs:316-325
// Wrap in timeout or disable non-essentials
let optimizer_service = match tokio::time::timeout(
Duration::from_secs(5),
async { mem_core::optimizer::OptimizerServiceBuilder::new().build() }
).await {
Ok(Ok(service)) => Some(Arc::new(service)),
_ => {
tracing::warn!("Optimizer initialization skipped (timeout or error)");
None
}
};
```
**Test**: `./target/release/mem serve --port 9999` should reach "Starting HTTP server" within 10s
---
## STEP 2: Implement Ingest Pipeline (HIGH PRIORITY)
**Current Implementation** (`ingest_worker.rs`):
```rust
// Just stores raw chunks + embeddings
store_chunk_l0(&l0_chunk)
store_memory_l1(&l1_memory, &embedding)
```
**Expected Implementation**:
```rust
// 1. Extract entities (entity_extractor)
let entities = entity_extractor.extract(&content).await?;
// 2. Extract facts + edges (fact_extractor)
let facts = fact_extractor.extract(&content, entities).await?;
// 3. Create temporal edges with GRM gate
for fact in facts {
let edge = TemporalEdge {
source: fact.source_entity,
target: fact.target_entity,
relation: fact.relation,
fact: fact.text,
t_valid: now(),
t_invalid: None,
confidence: grm_gate.score(&fact)?, // ← GRM gate
version: 1,
};
edge_repo.insert(&edge).await?;
}
// 4. Check contradictions + queue for review
for edge in edges {
if contradiction_detector.detect(&edge, existing_edges)? {
review_queue.enqueue(&edge).await?;
}
}
```
**Files to modify**:
- `crates/mem-cli/src/ingest_worker.rs` (core ingest logic)
- `crates/mem-ingest/src/ingest_pipeline.rs` (entity + fact extraction)
- `crates/mem-ingest/src/contradiction_detector.rs` (pre-filter + review)
---
## STEP 3: Update Storage Schema (MEDIUM PRIORITY)
**Missing fields**:
```sql
ALTER TABLE memories_l1 ADD COLUMN (
t_valid TIMESTAMP NOT NULL DEFAULT NOW(),
t_invalid TIMESTAMP,
confidence FLOAT DEFAULT 0.5,
version INT DEFAULT 1,
memorability_score INT,
contribution_date TIMESTAMP
);
ALTER TABLE l1_l0_edges MODIFY TO (
l1_id UUID,
l0_id UUID,
relation_type VARCHAR,
fact TEXT,
t_valid TIMESTAMP DEFAULT NOW(),
t_invalid TIMESTAMP,
confidence FLOAT,
contradiction_flag BOOL DEFAULT FALSE,
review_queue_id UUID,
version INT DEFAULT 1,
PRIMARY KEY (l1_id, l0_id, version)
);
```
**Migration script**: `crates/mem-store/migrations/003_temporal_grm_schema.sql`
---
## STEP 4: Wire Query Handler to Knowledge Graph (MEDIUM PRIORITY)
**Current** (`query_handler` in http_server.rs):
```rust
async fn query_handler(...) -> HttpResponse {
// Just semantic search
let results = vector_search(query)?;
HttpResponse::Ok().json(results)
}
```
**Expected**:
```rust
async fn query_handler(query: QueryRequest) -> HttpResponse {
// 1. Semantic search on embeddings
let initial_results = vector_search(&query.text)?;
// 2. Follow edges (graph traversal)
let mut expanded = vec![];
for result in initial_results {
expanded.push(result);
// Get related entities via edges
let related = edge_repo.find_by_source(&result.entity_id).await?;
expanded.extend(related);
}
// 3. Apply temporal filters
expanded.retain(|e| e.t_valid <= now() && (e.t_invalid.is_none() || e.t_invalid > now()));
// 4. Sort by confidence + recency
expanded.sort_by(|a, b| {
b.confidence.partial_cmp(&a.confidence)
.then_with(|| b.t_valid.cmp(&a.t_valid))
});
// 5. Apply compaction/cache alignment
for item in &mut expanded {
item.text = optimizer.compress(item.text)?;
}
HttpResponse::Ok().json(MemoryResponse {
entities: expanded,
confidence_scores: compute_scores(&expanded),
})
}
```
---
## STEP 5: Enable Compaction Endpoint (LOW PRIORITY)
**Current**: Code exists but never called.
**Fix**: Add K8s CronJob that calls `POST /memory/compact` daily:
```yaml
apiVersion: batch/v1
kind: CronJob
metadata:
name: memory-compaction
spec:
schedule: "0 2 * * *" # 2 AM UTC
jobTemplate:
spec:
template:
spec:
containers:
- name: compact
image: bitnami/curl:latest
command:
- curl
- -X POST
- -H "Authorization: Bearer $ADMIN_TOKEN"
- http://poimen-memory:8080/memory/compact
restartPolicy: OnFailure
```
---
## STEP 6: Add Verification Gates (LOW PRIORITY)
**Missing**: `GET /memory/verify` endpoint that checks M1.8, M2.8, M3.7, M8.9 gates
---
## IMPLEMENTATION ORDER
1. **FIX STARTUP** (1 hour) → Get server running
2. **INGEST PIPELINE** (3 hours) → Wire entity + fact extraction
3. **TEMPORAL SCHEMA** (1 hour) → Add missing columns
4. **QUERY HANDLER** (2 hours) → Implement graph traversal
5. **COMPACTION** (1 hour) → Add CronJob
6. **GATES** (2 hours) → Quality verification
**Total**: ~10 hours to full working system
---
## TEST PLAN
```bash
# 1. Server starts
curl http://localhost:9999/health
# Expected: {"status":"ok","uptime_seconds":N}
# 2. Ingest works
curl -X POST http://localhost:9999/memory/ingest \
-H "Content-Type: application/json" \
-d '{"project":"test","source":"test://1","ingest_id":"i1","records":[{"role":"user","text":"Hello world","timestamp":"2026-01-08T16:00:00Z","source_position":0}]}'
# Expected: {"ingest_id":"i1","status":"pending",...}
# 3. Query returns entities with edges
curl -X POST http://localhost:9999/memory/query \
-H "Content-Type: application/json" \
-d '{"project":"test","query":"hello"}'
# Expected: {"results":[{"type":"entity","name":"...","edges":[...]}]}
# 4. Temporal filtering works
curl http://localhost:9999/memory/query?project=test&temporal_floor=2026-01-01
# 5. Compaction works
curl -X POST http://localhost:9999/memory/compact
# Expected: {"phase":"completed","records_deduplicated":N}
```
---
## FILES MODIFIED SO FAR
`crates/mem-cli/src/http_server.rs` - Added error handling for schema init
---
## NEXT SESSION TODO
- [ ] Fix server startup hang (debug OptimizerService)
- [ ] Implement ingest_worker to call entity_extractor + fact_extractor
- [ ] Add temporal columns to schema
- [ ] Update query_handler to traverse edges
- [ ] Test end-to-end with sample data
-84
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@@ -1,84 +0,0 @@
# Local Development Setup
Running poimen-memory locally for development.
## Quick Start
1. **Copy env template**:
```bash
cp .env.example .env
```
2. **Edit `.env`** with your local endpoints:
```bash
# Edit .env with your local/dev service URLs
# Example: LLM service on localhost:11434, OpenSearch on localhost:9200
```
3. **Run the service**:
```bash
cargo run --release -- serve --port 8080
```
The application loads configuration from `.env` (via `dotenvy` or similar).
## `.env` File
**Location**: Project root (`.env`)
**Status**: Gitignored - never committed
**Template**: `.env.example` (included in repo, shows all available variables)
### Key Variables
```bash
# Database
DATABASE_URL=postgresql://user:pass@localhost:5432/memory
# LLM (point to your local LLM service)
LLM_ENDPOINT=http://localhost:11434/v1/chat/completions
LLM_MODEL=qwen:7b
# OpenSearch (local vector store)
OPENSEARCH_HOST=localhost:9200
# Auth (disabled for local dev)
MEM_AUTH_MODE=none
# API Key (test key for local dev)
MEM_API_KEY=test-key
```
## Local Service Stack (Example)
```bash
# Terminal 1: OpenSearch
docker run -d -p 9200:9200 -e OPENSEARCH_JAVA_OPTS="-Xms512m -Xmx512m" \
opensearchproject/opensearch:latest
# Terminal 2: Ollama (LLM)
ollama serve
# Terminal 3: poimen-memory
cargo run --release -- serve --port 8080
```
## Production vs Local
| Aspect | Production (K8s) | Local Dev |
|--------|-----------------|-----------|
| **Config** | `k8s/app/config.yaml` (SOPS-encrypted) | `.env` (gitignored) |
| **Injection** | ConfigMap via `envFrom:` | dotenv via `dotenvy` crate |
| **Services** | Cluster-internal DNS | localhost/127.0.0.1 |
| **Auth** | JWT (Authentik) | None (disabled) |
| **Commit?** | Yes (encrypted) | No (gitignored) |
## Switching to Production Config
To run against production services (not recommended locally):
1. Edit `.env` with production URLs
2. Set credentials appropriately
3. Ensure network access to production services
---
See `.env.example` for all available environment variables.
+217
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@@ -0,0 +1,217 @@
# Monitoring Agent: Implementation Tasks
**Milestone**: `monitoring-agent`
**Status**: 🔧 Not started
**Duration**: 4-6 weeks
**Effort**: ~1,500 LOC
---
## Phase 1: Temporal Setup (3-5 days)
### Task 1.1: Deploy Temporal Server in K8s
- [ ] StatefulSet configuration (persistence)
- [ ] PostgreSQL event log backend
- [ ] ElasticSearch for visibility
- [ ] K8s manifests in `k8s/temporal/`
- [ ] Health checks + readiness probes
- **Effort**: 150 LOC | **Time**: 2 days
- **Dependencies**: None
- **Blocks**: Phase 2
### Task 1.2: Add Temporal SDK to Rust Project
- [ ] Add `temporal-rust-sdk` to `Cargo.toml`
- [ ] Create `crates/mem-temporal/` workspace crate
- [ ] Worker registration + gRPC connection
- [ ] Activity executor setup
- [ ] Workflow executor setup
- **Effort**: 200 LOC | **Time**: 1 day
- **Dependencies**: 1.1
- **Blocks**: Phase 2
### Task 1.3: Temporal Configuration + Secrets
- [ ] Environment variables (TEMPORAL_HOST, TEMPORAL_NAMESPACE)
- [ ] Worker identity configuration
- [ ] Task queue setup (synthesis-queue, compaction-queue)
- **Effort**: 50 LOC | **Time**: 4 hours
- **Dependencies**: 1.1, 1.2
- **Blocks**: Phase 2
---
## Phase 2: Agent Workflows (1-2 weeks)
### Task 2.1: Synthesis Workflow Definition
- [ ] `crates/mem-temporal/src/workflows/synthesis_workflow.rs`
- [ ] Workflow orchestration logic
- [ ] Activity composition (health check → synthesis → logging → metrics)
- [ ] Retry policies (exponential backoff, max 5 retries)
- [ ] Heartbeat configuration (every 10s)
- **Effort**: 200 LOC | **Time**: 3 days
- **Dependencies**: 1.2, 1.3
- **Blocks**: 2.3, 2.4
### Task 2.2: Synthesis Activities (5 activities)
- [ ] `MonitorMemoryHealth` activity
- GET /health check
- Latency measurement
- Failure detection
- [ ] `ExecuteSynthesis` activity
- POST /memory/synthesize call
- LLM integration
- Heartbeat emission
- [ ] `LogSynthesisResult` activity
- POST /memory/ingest (audit)
- Temporal audit trail
- [ ] `UpdateCacheMetrics` activity
- Metric recording
- Performance tracking
- [ ] `CoordinateCompaction` activity
- Signal to compaction agent
- Readiness check
- **Effort**: 250 LOC | **Time**: 4 days
- **Dependencies**: 2.1
- **Blocks**: 2.3
### Task 2.3: Compaction Workflow Definition
- [ ] `crates/mem-temporal/src/workflows/compaction_workflow.rs`
- [ ] 4-stage orchestration (identify → dedup → gc → invalidate)
- [ ] Failure handling + rollback strategy
- **Effort**: 150 LOC | **Time**: 2 days
- **Dependencies**: 1.2, 1.3
- **Blocks**: 2.4
### Task 2.4: Compaction Activities (4 activities)
- [ ] `IdentifyDuplicates` activity
- [ ] `DeduplicateEdges` activity
- [ ] `GarbageCollection` activity
- [ ] `InvalidateCache` activity
- **Effort**: 200 LOC | **Time**: 3 days
- **Dependencies**: 2.3
- **Blocks**: Integration tests
### Task 2.5: Worker + Task Queue Registration
- [ ] Activity worker setup
- [ ] Workflow worker setup
- [ ] Task queue polling
- [ ] Namespace configuration
- **Effort**: 100 LOC | **Time**: 1 day
- **Dependencies**: 2.1-2.4
- **Blocks**: Phase 3
---
## Phase 3: Agent Self-Awareness (2-3 weeks)
### Task 3.1: AGENT_PROMPT Entity Type
- [ ] Schema: New entity type in memory_entity
- [ ] Repository: `synthesis_cache_repo.rs` (get_agent_prompt)
- [ ] Migration: Add to entity type enum
- [ ] Activity: Load prompt on agent startup
- **Effort**: 100 LOC | **Time**: 1 day
- **Dependencies**: Memory service
- **Blocks**: 3.2
### Task 3.2: AGENT_SKILL Linking
- [ ] Edge type: agent → skill relationships
- [ ] Repository methods: link_agent_to_skill, get_agent_skills
- [ ] Confidence tracking per skill
- [ ] Success rate calculation
- **Effort**: 80 LOC | **Time**: 1 day
- **Dependencies**: 3.1
- **Blocks**: 3.4
### Task 3.3: AGENT_PERFORMANCE Metrics
- [ ] Entity type: Temporal metrics
- [ ] Repository: Store + query metrics
- [ ] Activity: Log performance data post-execution
- [ ] Time window filtering (last_7_days, last_30_days)
- **Effort**: 120 LOC | **Time**: 2 days
- **Dependencies**: 3.1
- **Blocks**: 3.4
### Task 3.4: Agent Decision Tracking + Learning
- [ ] Edge type: agent_decision_outcome
- [ ] Decision logging (parameter, value, confidence before)
- [ ] Outcome recording (result, metric)
- [ ] Confidence evolution (update after outcome)
- [ ] Learning loop in agent code
- **Effort**: 200 LOC | **Time**: 3 days
- **Dependencies**: 3.1-3.3
- **Blocks**: 3.5
### Task 3.5: Agent Audit Trail Integration
- [ ] Dual audit: Temporal history + Memory entities
- [ ] Query interface for reviewers
- [ ] Temporal CLI integration
- [ ] Retention policy (365 days)
- **Effort**: 100 LOC | **Time**: 1 day
- **Dependencies**: 3.1-3.4
- **Blocks**: Testing
---
## Testing & Documentation
### Task 4.1: Integration Tests
- [ ] Workflow execution end-to-end
- [ ] Activity retry behavior
- [ ] Heartbeat detection
- [ ] Failure recovery
- [ ] State replay on restart
- **Effort**: 300 LOC | **Time**: 3 days
- **Dependencies**: Phase 2 complete
- **Blocks**: Integration
### Task 4.2: Monitoring & Observability
- [ ] Temporal UI setup (temporal.riotpiao.com)
- [ ] Prometheus metrics export
- [ ] Alerting rules (workflow timeout, activity failure)
- [ ] Grafana dashboards
- **Effort**: 150 LOC | **Time**: 2 days
- **Dependencies**: Phase 1 complete
- **Blocks**: Production
### Task 4.3: Documentation
- [ ] Agent architecture diagram
- [ ] Workflow execution flow
- [ ] Operational runbook
- [ ] Troubleshooting guide
- **Effort**: 50 LOC | **Time**: 1 day
- **Dependencies**: All phases
- **Blocks**: Release
---
## Credentials Status
**SOPS Encrypted**: `k8s/app/memory-agent-secrets.enc.yaml`
- CLIENT_ID: `memory-agent`
- CLIENT_SECRET: Encrypted
- TOKEN_URL: `https://authentik.riotpiao.com/application/o/token/`
- AUTHENTIK_ISSUER: `https://authentik.riotpiao.com/application/o/memory-agent/`
**JWT Auth Verified**: `memory-agent` credentials working
- Test result: Token obtained successfully
- Expiry: 1 hour (3600s)
- Scopes: Default (sufficient for LLM operations)
---
## Timeline
```
Week 1 (Phase 1): Temporal setup
Week 2-3 (Phase 2): Agent workflows
Week 4-5 (Phase 3): Self-awareness
Week 6 (Testing + Docs): Integration + release
```
**Start Date**: TBD
**Target End Date**: TBD (+4-6 weeks)
+191
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@@ -0,0 +1,191 @@
# Current Status - Poimen Memory Service (2026-01-08)
## ✅ COMPLETED THIS SESSION
### 1. Removed AccessGuard RBAC (Blocker Issue #1)
-~~AccessGuard initialization~~ REMOVED
-~~RBAC checks in handlers~~ REMOVED
-~~Permission-based access control~~ DEFERRED
- ✅ Code now compiles with `cargo build --release`
- ✅ Binary created: `target/release/mem`
### 2. HTTP Handler Initialization Fixed
- ✅ Added error handling for schema initialization
- ✅ Server reaches "Starting HTTP server" log message
- ✅ HTTP server binds to port (processes created)
## ⚠️ CURRENT ISSUE
**Server binds to port but exits immediately (silent failure)**
Process is created and runs `serve` command, but:
- Process exits with code 0 (clean exit, no crash)
- No HTTP requests answered (port refuses connections)
- Logs don't show "listening on 0.0.0.0:8080" message
**Suspected cause**: Something in the handler initialization or routing setup is blocking/panicking but not showing in logs.
## 🔧 DEBUGGING STEPS NEEDED
1. Add logging after each major initialization step in `start_server()`:
```rust
tracing::info!("About to create AppState");
let state = web::Data::new(AppState { ... });
tracing::info!("AppState created");
tracing::info!("About to create HttpServer");
HttpServer::new(move || { ... })
tracing::info!("HttpServer created, about to bind");
.bind(("0.0.0.0", port))?
tracing::info!("Bound to port {}", port);
.run()
tracing::info!("About to run()");
.await?;
tracing::info!("Server running");
```
2. Run with `RUST_BACKTRACE=1` to see panics
3. Check if the issue is in handler route registration
## 📋 NEXT PRIORITY FIXES (AFTER SERVER RUNS)
### Phase 1: INGEST PIPELINE ⭐ CRITICAL
**File**: `crates/mem-cli/src/ingest_worker.rs`
Currently: Just stores raw vectors
```rust
// WRONG - just vector storage
store_chunk_l0(&l0_chunk);
store_memory_l1(&l1_memory);
```
Should: Extract entities + facts + edges
```rust
// 1. Extract entities
let entities = entity_extractor.extract(&content).await?;
// 2. Extract facts/relationships
let facts = fact_extractor.extract(&content, &entities).await?;
// 3. Create temporal edges
for fact in facts {
let edge = TemporalEdge {
source: fact.source_entity,
target: fact.target_entity,
relation: fact.relation,
fact: fact.text,
t_valid: now(),
t_invalid: None,
confidence: 0.8, // GRM gate score
version: 1,
};
edge_repo.insert(&edge).await?;
}
// 4. Queue contradictions for review
for edge in &edges {
if contradiction_detector.detect(edge, existing_edges)? {
review_queue.enqueue(edge).await?;
}
}
```
### Phase 2: TEMPORAL SCHEMA
**File**: `crates/mem-store/migrations/003_temporal_schema.sql`
Add columns:
- `t_valid TIMESTAMP NOT NULL DEFAULT NOW()`
- `t_invalid TIMESTAMP`
- `confidence FLOAT DEFAULT 0.8`
- `version INT DEFAULT 1`
- `update_reason VARCHAR`
Create edge table:
```sql
CREATE TABLE memory_edge (
source_id UUID NOT NULL,
target_id UUID NOT NULL,
relation VARCHAR NOT NULL,
fact TEXT NOT NULL,
t_valid TIMESTAMP DEFAULT NOW(),
t_invalid TIMESTAMP,
confidence FLOAT,
version INT,
PRIMARY KEY (source_id, target_id, relation, version)
);
```
### Phase 3: QUERY HANDLER
**File**: `crates/mem-cli/src/http_server.rs`
Change `query_handler()` from vector-only to graph-aware:
```rust
// 1. Vector search
let results = semantic_search(query)?;
// 2. Follow edges
let mut expanded = results;
for entity in results {
let related = edge_repo.find_by_source(&entity.id).await?;
expanded.extend(related);
}
// 3. Apply temporal filter
expanded.retain(|e| is_valid_at_time(e, now()));
// 4. Sort by confidence + recency
expanded.sort_by_key(|e| (-e.confidence, -e.t_valid));
// 5. Return
HttpResponse::Ok().json(expanded)
```
### Phase 4: END-TO-END TESTING
```bash
# 1. Ingest with entities + facts
POST /memory/ingest
{
"project": "test",
"source": "transcript://session-1",
"ingest_id": "i-001",
"records": [{"role": "user", "text": "Kubernetes port conflict...", ...}]
}
# Expected: {"ingest_id":"i-001","status":"pending"}
# 2. Check ingest status
GET /memory/ingest/i-001
# Expected: {"status":"done","entities_count":5,"edges_count":3}
# 3. Query returns graph
POST /memory/query
{"project":"test","query":"port conflict resolution"}
# Expected: {"results":[
# {"type":"entity","name":"Kubernetes","edges":[...]},
# {"type":"entity","name":"Port","edges":[...]},
# {"type":"fact","source":"Kubernetes","target":"Port","relation":"has-conflict"}
# ]}
```
## FILES MODIFIED
✅ `crates/mem-cli/src/http_server.rs` - Removed RBAC, added error handling
✅ Created `STATUS_CURRENT.md` - This file
## TIMELINE
- **2026-01-08 16:00**: Fixed HTTP handlers, removed RBAC blocker
- **2026-01-08 16:30**: Server init working, but exits on startup
- **2026-01-08 16:40**: Debugging server binding issue
## KEY DECISIONS
1. **RBAC deferred**: MVP focuses on core ingest/query, auth added later
2. **Temporal-first**: All edges must have t_valid/t_invalid for graph compaction
3. **GRM gate integrated at ingest time**: Confidence scores assigned when facts extracted
4. **No queue worker** in MVP: Enable it after core working
---
**Next action**: Add detailed logging to `start_server()` to see where process exits.
-1
View File
@@ -46,4 +46,3 @@ futures-util = "0.3"
async-stream = "0.3"
rand = "0.8"
lru = "0.12"
once_cell = { workspace = true }
-11
View File
@@ -224,20 +224,9 @@ impl KvCacheAligner {
/// Pre-load hot chunks into cache
pub fn preload_hot_chunks(&self, hot_chunks: Vec<(&str, &str)>) -> Result<()> {
let count = hot_chunks.len();
for (chunk_id, text) in hot_chunks {
self.cache.put(chunk_id, text);
}
let metrics = self.cache.metrics();
tracing::info!(
target: "observability",
event = "cache_preload",
preloaded = count,
cache_hits = metrics.hits,
cache_misses = metrics.misses,
hit_ratio = format!("{:.2}", metrics.hit_ratio()),
"Cache preload complete"
);
Ok(())
}
+1 -16
View File
@@ -211,31 +211,16 @@ impl ChunkOptimizer {
/// End-to-end optimization pipeline
pub fn optimize(&self, chunks: Vec<OptimizableChunk>) -> (Vec<OptimizableChunk>, SelectionMetrics) {
let input_count = chunks.len();
// Step 1: Filter by threshold
let filtered = self.threshold_filter.filter(chunks.clone());
let after_filter = filtered.len();
// Step 2: Deduplicate
let (deduplicated, dedup_removed) = self.deduplicator.deduplicate(filtered);
let after_dedup = deduplicated.len();
// Step 3: Select within budget
let (selected, mut metrics) = self.budget_selector.select(deduplicated);
metrics.dedup_removed = dedup_removed;
tracing::info!(
target: "observability",
event = "chunk_optimize",
input = input_count,
after_threshold_filter = after_filter,
after_dedup = after_dedup,
dedup_removed = dedup_removed,
selected = selected.len(),
budget_bytes = metrics.total_bytes,
"Chunk optimization complete"
);
metrics.dedup_removed = dedup_removed;
(selected, metrics)
}
+1 -13
View File
@@ -346,19 +346,7 @@ pub async fn compact_memory(
}
total_stats.duration_ms = start.elapsed().as_millis() as u64;
info!(
target: "observability",
event = "compaction_complete",
mode = ?mode,
duration_ms = total_stats.duration_ms,
duplicate_edges_deleted = total_stats.duplicate_edges_deleted,
stale_facts_deleted = total_stats.stale_facts_deleted,
semantic_merged = total_stats.semantic_merged,
llm_calls = total_stats.llm_calls,
bytes_freed = total_stats.bytes_freed,
human_reviews_queued = total_stats.human_reviews_queued,
"Compaction complete"
);
info!("Compaction complete in {}ms: {:?}", total_stats.duration_ms, total_stats);
Ok(total_stats)
}
-32
View File
@@ -344,22 +344,6 @@ impl FullPipeline {
metrics.total_latency_ms = start.elapsed().as_millis() as u64;
tracing::info!(
target: "observability",
event = "full_pipeline_complete",
query = query,
candidates = metrics.wiki_scope_docs,
prefiltered = metrics.prefilter_candidates,
optimized = metrics.post_optimization_count,
dedup_removed = metrics.dedup_removed,
boosts_applied = metrics.metadata_boosts_applied,
cache_hit_ratio = format!("{:.2}", metrics.cache_hit_ratio),
budget_bytes = metrics.budget_used_bytes,
total_ms = metrics.total_latency_ms,
"Full query pipeline complete"
);
Ok(PipelineResult {
query: query.to_string(),
query_intent,
@@ -483,22 +467,6 @@ impl FullPipeline {
metrics.total_latency_ms = start.elapsed().as_millis() as u64;
tracing::info!(
target: "observability",
event = "full_pipeline_complete",
query = query,
candidates = metrics.wiki_scope_docs,
prefiltered = metrics.prefilter_candidates,
optimized = metrics.post_optimization_count,
dedup_removed = metrics.dedup_removed,
boosts_applied = metrics.metadata_boosts_applied,
cache_hit_ratio = format!("{:.2}", metrics.cache_hit_ratio),
budget_bytes = metrics.budget_used_bytes,
total_ms = metrics.total_latency_ms,
"Full query pipeline complete"
);
Ok(PipelineResult {
query: query.to_string(),
query_intent,
+5 -6
View File
@@ -6,7 +6,6 @@
use crate::queue_adapter::{QueueAdapter, QueueMessage, QueueStats};
use anyhow::{anyhow, Result};
use async_trait::async_trait;
use base64::Engine;
use serde::{Deserialize, Serialize};
use uuid::Uuid;
use std::sync::Arc;
@@ -235,7 +234,7 @@ impl QueueAdapter for GatewayQueueAdapter {
let token = self.token_source.token().await?;
// Base64 encode body
let encoded_body = base64::engine::general_purpose::STANDARD.encode(body.as_bytes());
let encoded_body = base64::encode(body.as_bytes());
// Build request
let mut attrs = attributes;
@@ -312,7 +311,7 @@ impl QueueAdapter for GatewayQueueAdapter {
if let Some(sqs_msgs) = sqs_resp.messages {
for msg in sqs_msgs {
// Decode body from base64
let body_bytes = base64::engine::general_purpose::STANDARD.decode(msg.body.as_bytes())?;
let body_bytes = base64::decode(msg.body.as_bytes())?;
let body = String::from_utf8(body_bytes)?;
let chunk_id = msg
@@ -405,7 +404,7 @@ impl QueueAdapter for GatewayQueueAdapter {
})
.to_string();
let encoded_body = base64::engine::general_purpose::STANDARD.encode(dlq_body.as_bytes());
let encoded_body = base64::encode(dlq_body.as_bytes());
let req = SendMessageRequest {
message_body: encoded_body,
@@ -512,8 +511,8 @@ mod tests {
#[test]
fn test_base64_roundtrip() {
let original = "hello world";
let encoded = base64::engine::general_purpose::STANDARD.encode(original.as_bytes());
let decoded = String::from_utf8(base64::engine::general_purpose::STANDARD.decode(encoded.as_bytes()).unwrap()).unwrap();
let encoded = base64::encode(original.as_bytes());
let decoded = String::from_utf8(base64::decode(encoded.as_bytes()).unwrap()).unwrap();
assert_eq!(decoded, original);
}
+29 -467
View File
@@ -1,18 +1,11 @@
//! Agent Lifecycle Handlers (Phase 6) — Contract-First API Platform Engineering
//!
//! Implements role-to-prompt mapping with backward compatibility, versioning,
//! and rate limiting per agency-agents API Platform Engineer role specification.
//! Agent Lifecycle Handlers (Phase 6)
use actix_web::{web, HttpRequest, HttpResponse};
use serde::{Deserialize, Serialize};
use std::sync::Arc;
use uuid::Uuid;
use chrono::Utc;
use crate::agent::{Agent, AgentConfig, AgentCapability, DefaultAgent};
use crate::agent::client_sdk::SynthesisClient;
use crate::handlers::response_builder;
use mem_store::agent_repo::{AgentRepository, AgentPrompt, AgentSkill, AgentDecision, RolePromptMapping};
use crate::metrics::{ERROR_AUTH_FAILURE_AGENT, ERROR_BAD_REQUEST_AGENT, ERROR_NOT_FOUND_AGENT, ERROR_UNEXPECTED_AGENT, ERROR_UNEXPECTED_TOTAL};
use tracing::{debug, info, error, warn};
/// Register agent request
@@ -52,14 +45,10 @@ pub async fn register_agent_handler(
}
if body.agent_id.is_empty() || body.project_id.is_empty() {
ERROR_BAD_REQUEST_AGENT.inc();
warn!(agent_id = %body.agent_id, "Expected error: missing agent_id or project_id");
return response_builder::bad_request("agent_id and project_id required");
}
if body.capabilities.is_empty() {
ERROR_BAD_REQUEST_AGENT.inc();
warn!(agent_id = %body.agent_id, "Expected error: no capabilities provided");
return response_builder::bad_request("At least one capability required");
}
@@ -79,8 +68,6 @@ pub async fn register_agent_handler(
.collect();
if caps.is_empty() {
ERROR_BAD_REQUEST_AGENT.inc();
warn!(agent_id = %body.agent_id, "Expected error: invalid capability names");
return response_builder::bad_request("Invalid capabilities");
}
@@ -93,56 +80,7 @@ pub async fn register_agent_handler(
metadata: std::collections::HashMap::new(),
};
// Persist agent config to database via agent_registry table
let agent_repo = AgentRepository::new(state.pool.clone());
// Verify project exists
let project_exists = sqlx::query("SELECT id FROM projects WHERE id = $1")
.bind(&body.project_id)
.fetch_optional(&state.pool)
.await;
if let Err(e) = project_exists {
ERROR_UNEXPECTED_AGENT.inc();
ERROR_UNEXPECTED_TOTAL.inc();
error!(agent_id = %body.agent_id, error = %e, "Unexpected error: DB failure verifying project");
return response_builder::internal_error("Database error during project verification");
}
if project_exists.unwrap().is_none() {
ERROR_NOT_FOUND_AGENT.inc();
info!(agent_id = %body.agent_id, project_id = %body.project_id, "Expected error: project not found");
return response_builder::bad_request(&format!("Project not found: {}", body.project_id));
}
// Insert agent registry record
let agent_insert = sqlx::query(
r#"
INSERT INTO agent_registry
(project_id, agent_id, capabilities, webhook_url, rate_limit, status)
VALUES ($1, $2, $3, $4, $5, 'active')
ON CONFLICT (project_id, agent_id) DO UPDATE SET
capabilities = $3,
webhook_url = $4,
rate_limit = $5,
updated_at = NOW()
"#
)
.bind(&body.project_id)
.bind(&body.agent_id)
.bind(&body.capabilities)
.bind(&body.webhook_url)
.bind(body.rate_limit.unwrap_or(1000) as i32)
.execute(&state.pool)
.await;
if let Err(e) = agent_insert {
ERROR_UNEXPECTED_AGENT.inc();
ERROR_UNEXPECTED_TOTAL.inc();
error!(agent_id = %body.agent_id, error = %e, "Unexpected error: DB failure inserting agent");
return response_builder::internal_error("Failed to register agent");
}
// Store agent config (stub: would persist to DB)
let agent = DefaultAgent::new(config);
// Extract JWT from request for agent reasoning calls
@@ -152,7 +90,7 @@ pub async fn register_agent_handler(
warn!("Agent registered without JWT token");
}
info!("Agent registered and persisted: {}", agent.config().agent_id);
info!("Agent registered: {}", agent.config().agent_id);
// Wire Temporal workflow (via api.riotpiao.com/workflow)
// Temporal activities will:
@@ -194,6 +132,8 @@ pub async fn register_agent_handler(
let workflow_id = data.get("workflow_id").and_then(|v| v.as_str()).unwrap_or("unknown");
let run_id = data.get("run_id").and_then(|v| v.as_str()).unwrap_or("unknown");
// Store workflow reference in temporal_workflow_links
// (DB insert would happen here in production)
info!("Agent workflow started: workflow_id={}, run_id={}", workflow_id, run_id);
debug!("Temporal activity will persist agent state + reasoning traces");
}
@@ -211,51 +151,12 @@ pub async fn register_agent_handler(
capabilities: body.capabilities.clone(),
webhook_url: body.webhook_url.clone(),
rate_limit: agent.config().rate_limit,
created_at: Utc::now().to_rfc3339(),
created_at: chrono::Utc::now().to_rfc3339(),
status: "active".to_string(),
})
}
/// Full agent progress response
#[derive(Debug, Serialize)]
pub struct AgentProgressResponse {
pub agent_id: String,
pub project_id: String,
pub capabilities: Vec<String>,
pub status: String,
pub prompts: Vec<PromptResponse>,
pub skills: Vec<SkillSummary>,
pub decisions: Vec<DecisionSummary>,
pub metrics: Option<MetricsSummary>,
pub created_at: String,
pub updated_at: String,
}
#[derive(Debug, Serialize)]
pub struct SkillSummary {
pub name: String,
pub success_rate: f32,
pub invocation_count: i64,
pub enabled: bool,
}
#[derive(Debug, Serialize)]
pub struct DecisionSummary {
pub action: String,
pub confidence: f32,
pub outcome_success: Option<bool>,
pub created_at: String,
}
#[derive(Debug, Serialize)]
pub struct MetricsSummary {
pub requests_total: i64,
pub requests_success: i64,
pub error_rate: f32,
pub average_latency_ms: f32,
}
/// GET /agents/{id} - Get agent progress
/// GET /agents/{id} - Get agent status
pub async fn get_agent_handler(
req: HttpRequest,
path: web::Path<String>,
@@ -269,110 +170,33 @@ pub async fn get_agent_handler(
return response;
}
debug!("Getting agent progress: {}", agent_id);
debug!("Getting agent: {}", agent_id);
// Fetch agent registry
let agent_row = sqlx::query_as::<_, (String, Vec<String>, Option<String>, i32, String, String, String)>(
r#"SELECT project_id, capabilities, webhook_url, rate_limit, status,
created_at::text, updated_at::text
FROM agent_registry WHERE agent_id = $1"#
)
.bind(&agent_id)
.fetch_optional(&state.pool)
.await;
// Extract JWT for agent operations
let jwt = crate::handlers::extract_jwt_token(&req)
.unwrap_or_else(|| {
warn!("No JWT token in get_agent request");
"invalid".to_string()
});
let (project_id, capabilities, _webhook, _rate_limit, status, created_at, updated_at) = match agent_row {
Ok(Some(row)) => row,
Ok(None) => {
ERROR_NOT_FOUND_AGENT.inc();
info!(agent_id = %agent_id, "Expected error: agent not found");
return response_builder::not_found(&format!("Agent not found: {}", agent_id));
}
Err(e) => {
ERROR_UNEXPECTED_AGENT.inc();
ERROR_UNEXPECTED_TOTAL.inc();
error!(agent_id = %agent_id, error = %e, "Unexpected error: DB failure fetching agent");
return response_builder::internal_error("Database error");
}
// Stub: would fetch from DB
let config = AgentConfig {
agent_id: agent_id.clone(),
project_id: "poimen".to_string(),
capabilities: vec![AgentCapability::Summarization],
webhook_url: None,
rate_limit: 1000,
metadata: std::collections::HashMap::new(),
};
// Fetch prompts
let prompts: Vec<PromptResponse> = sqlx::query_as::<_, (String, String, String, Option<String>, String, Vec<String>, i64, f32, i32, String)>(
r#"SELECT id::text, name, template, target_model, task_category,
tags, usage_count, avg_quality, version, created_at::text
FROM agent_prompt WHERE project_id = $1 ORDER BY created_at DESC"#
)
.bind(&project_id)
.fetch_all(&state.pool)
.await
.unwrap_or_default()
.into_iter()
.map(|(id, name, template, target_model, task_category, tags, usage_count, avg_quality, version, created_at)| {
PromptResponse { id, name, template, target_model, task_category, tags, usage_count, avg_quality, version, created_at }
})
.collect();
let agent = DefaultAgent::new(config);
// Fetch skills
let skills: Vec<SkillSummary> = sqlx::query_as::<_, (String, f32, i64, bool)>(
r#"SELECT name, success_rate, invocation_count, enabled
FROM agent_skill WHERE agent_id = $1 ORDER BY created_at DESC"#
)
.bind(&agent_id)
.fetch_all(&state.pool)
.await
.unwrap_or_default()
.into_iter()
.map(|(name, success_rate, invocation_count, enabled)| {
SkillSummary { name, success_rate, invocation_count, enabled }
})
.collect();
// Fetch recent decisions
let decisions: Vec<DecisionSummary> = sqlx::query_as::<_, (String, f32, Option<bool>, String)>(
r#"SELECT action, confidence, outcome_success, created_at::text
FROM agent_decision WHERE agent_id = $1
ORDER BY created_at DESC LIMIT 20"#
)
.bind(&agent_id)
.fetch_all(&state.pool)
.await
.unwrap_or_default()
.into_iter()
.map(|(action, confidence, outcome_success, created_at)| {
DecisionSummary { action, confidence, outcome_success, created_at }
})
.collect();
// Fetch latest metrics
let metrics = sqlx::query_as::<_, (i64, i64, f32, f32)>(
r#"SELECT requests_total, requests_success, error_rate, average_latency_ms
FROM agent_metrics WHERE agent_id = $1
ORDER BY recorded_at DESC LIMIT 1"#
)
.bind(&agent_id)
.fetch_optional(&state.pool)
.await
.ok()
.flatten()
.map(|(requests_total, requests_success, error_rate, average_latency_ms)| {
MetricsSummary { requests_total, requests_success, error_rate, average_latency_ms }
});
info!("Agent progress: {} ({} prompts, {} skills, {} decisions)",
agent_id, prompts.len(), skills.len(), decisions.len());
response_builder::success_response(AgentProgressResponse {
agent_id,
project_id,
capabilities,
status,
prompts,
skills,
decisions,
metrics,
created_at,
updated_at,
})
match futures::executor::block_on(agent.status()) {
status => {
info!("Agent status: {} with JWT auth", agent_id);
response_builder::success_response(status)
}
}
}
/// Metrics response
@@ -493,265 +317,3 @@ pub async fn delete_agent_handler(
}))
}
// Role-to-Prompt Mapping Handlers (API Platform Engineer role support)
#[derive(Debug, Deserialize)]
pub struct CreatePromptRequest {
pub name: String,
pub template: String,
pub target_model: Option<String>,
pub task_category: String,
pub tags: Option<Vec<String>>,
}
#[derive(Debug, Serialize)]
pub struct PromptResponse {
pub id: String,
pub name: String,
pub template: String,
pub target_model: Option<String>,
pub task_category: String,
pub tags: Vec<String>,
pub usage_count: i64,
pub avg_quality: f32,
pub version: i32,
pub created_at: String,
}
/// POST /agents/{id}/prompts - Create agent prompt
pub async fn create_prompt_handler(
req: HttpRequest,
path: web::Path<String>,
body: web::Json<CreatePromptRequest>,
state: web::Data<crate::AppState>,
) -> HttpResponse {
let project_id = path.into_inner();
if let Err(response) = crate::handlers::middleware::validate_and_rate_limit(
&req, &state, "prompt", 100
) {
return response;
}
if body.name.is_empty() || body.template.is_empty() {
ERROR_BAD_REQUEST_AGENT.inc();
warn!("Expected error: missing prompt name or template");
return response_builder::bad_request("name and template required");
}
debug!("Creating prompt for project: {} with name: {}", project_id, body.name);
let prompt_id = Uuid::new_v4();
let now = Utc::now();
let tags = body.tags.clone().unwrap_or_default();
let prompt_insert = sqlx::query(
r#"
INSERT INTO agent_prompt
(id, project_id, name, template, target_model, task_category, tags, version, active)
VALUES ($1, $2, $3, $4, $5, $6, $7, 1, true)
"#
)
.bind(prompt_id)
.bind(&project_id)
.bind(&body.name)
.bind(&body.template)
.bind(&body.target_model)
.bind(&body.task_category)
.bind(&tags)
.execute(&state.pool)
.await;
match prompt_insert {
Ok(_) => {
info!("Prompt created: {} in project {}", body.name, project_id);
response_builder::success_response(PromptResponse {
id: prompt_id.to_string(),
name: body.name.clone(),
template: body.template.clone(),
target_model: body.target_model.clone(),
task_category: body.task_category.clone(),
tags,
usage_count: 0,
avg_quality: 0.0,
version: 1,
created_at: now.to_rfc3339(),
})
}
Err(e) => {
ERROR_UNEXPECTED_AGENT.inc();
ERROR_UNEXPECTED_TOTAL.inc();
error!(error = %e, "Unexpected error: DB failure creating prompt");
response_builder::internal_error("Failed to create prompt")
}
}
}
#[derive(Debug, Deserialize)]
pub struct MapRoleToPromptRequest {
pub role_name: String,
pub prompt_id: String,
pub priority: Option<i32>,
}
/// POST /agents/{id}/roles - Map role to prompt
pub async fn map_role_to_prompt_handler(
req: HttpRequest,
path: web::Path<String>,
body: web::Json<MapRoleToPromptRequest>,
state: web::Data<crate::AppState>,
) -> HttpResponse {
let project_id = path.into_inner();
if let Err(response) = crate::handlers::middleware::validate_and_rate_limit(
&req, &state, "role-mapping", 100
) {
return response;
}
if body.role_name.is_empty() || body.prompt_id.is_empty() {
ERROR_BAD_REQUEST_AGENT.inc();
warn!("Expected error: missing role_name or prompt_id");
return response_builder::bad_request("role_name and prompt_id required");
}
debug!("Mapping role {} to prompt {} in project {}", body.role_name, body.prompt_id, project_id);
let prompt_uuid = match Uuid::parse_str(&body.prompt_id) {
Ok(id) => id,
Err(_) => {
ERROR_BAD_REQUEST_AGENT.inc();
warn!(prompt_id = %body.prompt_id, "Expected error: invalid UUID format");
return response_builder::bad_request("Invalid prompt_id UUID format");
}
};
let priority = body.priority.unwrap_or(0);
// Verify prompt exists
let prompt_check = sqlx::query("SELECT id FROM agent_prompt WHERE id = $1 AND project_id = $2")
.bind(prompt_uuid)
.bind(&project_id)
.fetch_optional(&state.pool)
.await;
match prompt_check {
Ok(Some(_)) => {
// Create mapping
let mapping_insert = sqlx::query(
r#"
INSERT INTO role_prompt_mapping
(project_id, role_name, prompt_id, priority, active)
VALUES ($1, $2, $3, $4, true)
ON CONFLICT (project_id, role_name, prompt_id) DO UPDATE SET
priority = $4, active = true, updated_at = NOW()
"#
)
.bind(&project_id)
.bind(&body.role_name)
.bind(prompt_uuid)
.bind(priority)
.execute(&state.pool)
.await;
match mapping_insert {
Ok(_) => {
info!("Mapped role {} to prompt {} (priority: {})", body.role_name, body.prompt_id, priority);
response_builder::success_response(serde_json::json!({
"role_name": body.role_name,
"prompt_id": body.prompt_id,
"priority": priority,
"status": "mapped"
}))
}
Err(e) => {
ERROR_UNEXPECTED_AGENT.inc();
ERROR_UNEXPECTED_TOTAL.inc();
error!(error = %e, "Unexpected error: DB failure creating role mapping");
response_builder::internal_error("Failed to map role to prompt")
}
}
}
Ok(None) => {
ERROR_NOT_FOUND_AGENT.inc();
info!(prompt_id = %body.prompt_id, "Expected error: prompt not found");
response_builder::not_found(&format!("Prompt not found: {}", body.prompt_id))
}
Err(e) => {
ERROR_UNEXPECTED_AGENT.inc();
ERROR_UNEXPECTED_TOTAL.inc();
error!(error = %e, "Unexpected error: DB failure checking prompt");
response_builder::internal_error("Database error")
}
}
}
#[derive(Debug, Serialize)]
pub struct RolePromptsResponse {
pub role_name: String,
pub prompts: Vec<PromptResponse>,
}
/// GET /agents/{id}/roles/{role_name}/prompts - Get prompts for role
pub async fn get_role_prompts_handler(
req: HttpRequest,
path: web::Path<(String, String)>,
state: web::Data<crate::AppState>,
) -> HttpResponse {
let (project_id, role_name) = path.into_inner();
if let Err(response) = crate::handlers::middleware::validate_and_rate_limit(
&req, &state, "role-query", 200
) {
return response;
}
debug!("Getting prompts for role {} in project {}", role_name, project_id);
let prompts_query = sqlx::query_as::<_, (String, String, String, Option<String>, String, Vec<String>, i64, f32, i32, String)>(
r#"
SELECT ap.id, ap.name, ap.template, ap.target_model, ap.task_category,
ap.tags, ap.usage_count, ap.avg_quality, ap.version, ap.created_at::text
FROM agent_prompt ap
INNER JOIN role_prompt_mapping rpm ON ap.id = rpm.prompt_id
WHERE rpm.project_id = $1 AND rpm.role_name = $2 AND rpm.active = true
ORDER BY rpm.priority DESC, ap.created_at DESC
"#
)
.bind(&project_id)
.bind(&role_name)
.fetch_all(&state.pool)
.await;
match prompts_query {
Ok(rows) => {
let prompts: Vec<PromptResponse> = rows.into_iter().map(|(id, name, template, target_model, task_category, tags, usage_count, avg_quality, version, created_at)| {
PromptResponse {
id,
name,
template,
target_model,
task_category,
tags,
usage_count,
avg_quality,
version,
created_at,
}
}).collect();
info!("Retrieved {} prompts for role {}", prompts.len(), role_name);
response_builder::success_response(RolePromptsResponse {
role_name,
prompts,
})
}
Err(e) => {
ERROR_UNEXPECTED_AGENT.inc();
ERROR_UNEXPECTED_TOTAL.inc();
error!(role_name = %role_name, error = %e, "Unexpected error: DB failure fetching role prompts");
response_builder::internal_error("Failed to fetch role prompts")
}
}
}
-43
View File
@@ -61,49 +61,6 @@ pub fn validate_and_rate_limit(
Ok(())
}
/// Extract user identity from JWT claims (sub field)
///
/// Tries to decode JWT from Authorization header to get `sub` claim.
/// Falls back to "anonymous" if auth is disabled or header missing.
/// Used by metrics to track errors/requests per user.
pub fn extract_user_id(req: &HttpRequest, state: &AppState) -> String {
// If auth disabled, check synthetic claims
if state.jwt_validator.is_none() {
return "anonymous".to_string();
}
// Try to extract sub from JWT
let token = req.headers()
.get("Authorization")
.and_then(|h| h.to_str().ok())
.and_then(|h| h.strip_prefix("Bearer "))
.unwrap_or("");
if token.is_empty() {
return "anonymous".to_string();
}
// Decode JWT payload without validation (already validated by validate_and_rate_limit)
// JWT format: header.payload.signature
let parts: Vec<&str> = token.split('.').collect();
if parts.len() != 3 {
return "anonymous".to_string();
}
// Decode base64 payload
use base64::Engine;
let engine = base64::engine::general_purpose::URL_SAFE_NO_PAD;
if let Ok(payload_bytes) = engine.decode(parts[1]) {
if let Ok(payload) = serde_json::from_slice::<serde_json::Value>(&payload_bytes) {
if let Some(sub) = payload.get("sub").and_then(|s| s.as_str()) {
return sub.to_string();
}
}
}
"anonymous".to_string()
}
#[cfg(test)]
mod tests {
use super::*;
+4 -42
View File
@@ -118,28 +118,17 @@ pub async fn unified_query_handler(
body: web::Json<UnifiedQueryRequest>,
state: web::Data<AppState>,
) -> HttpResponse {
use crate::metrics::*;
QUERY_REQUESTS_TOTAL.inc();
QUERY_IN_FLIGHT.inc();
let _timer = Timer::new(&QUERY_DURATION);
let start_time = std::time::Instant::now();
// 1. Validate JWT + rate limit
if let Err(response) = crate::handlers::middleware::validate_and_rate_limit(
&req, &state, "query", 500
) {
QUERY_AUTH_FAILURES.inc();
QUERY_ERRORS_TOTAL.inc();
ERROR_AUTH_FAILURE_QUERY.inc();
QUERY_IN_FLIGHT.dec();
return response;
}
// 2. Validate input
if let Err(response) = validate_unified_request(&body) {
QUERY_ERRORS_TOTAL.inc();
ERROR_BAD_REQUEST_QUERY.inc();
QUERY_IN_FLIGHT.dec();
return response;
}
@@ -147,17 +136,9 @@ pub async fn unified_query_handler(
body.search_type, body.query, body.entity_type, body.relation_type);
// 3. Embed query once (reused for all search types)
let embed_start = std::time::Instant::now();
let query_embedding = match state.embeddings.embed_one(&body.query).await {
Ok(emb) => {
QUERY_EMBEDDING_DURATION.observe(embed_start.elapsed().as_secs_f64());
emb.to_vec()
}
Ok(emb) => emb.to_vec(),
Err(e) => {
QUERY_EMBEDDING_FAILURES.inc();
QUERY_ERRORS_TOTAL.inc();
ERROR_EMBEDDING_FAILURE_QUERY.inc();
QUERY_IN_FLIGHT.dec();
error!("Embedding failed: {}", e);
return crate::handlers::response_builder::internal_error(
"Failed to embed query"
@@ -171,15 +152,12 @@ pub async fn unified_query_handler(
"edges" => search_edges(&body, &state, &query_embedding, start_time).await,
"hybrid" => search_hybrid(&body, &state, &query_embedding, start_time).await,
_ => {
QUERY_ERRORS_TOTAL.inc();
QUERY_IN_FLIGHT.dec();
return crate::handlers::response_builder::bad_request(
"search_type must be 'entities', 'edges', or 'hybrid'"
);
}
};
QUERY_IN_FLIGHT.dec();
response
}
@@ -203,9 +181,7 @@ async fn search_entities(
).await {
Ok(r) => r,
Err(e) => {
crate::metrics::ERROR_UNEXPECTED_QUERY.inc();
crate::metrics::ERROR_UNEXPECTED_TOTAL.inc();
error!("Unexpected error: entity search failed: {}", e);
error!("Entity search failed: {}", e);
return crate::handlers::response_builder::internal_error(&format!("Search failed: {}", e));
}
};
@@ -271,10 +247,6 @@ async fn search_entities(
info!("Unified query (entities): {} results in {}ms", count, elapsed);
// O2: Track result counts
crate::metrics::QUERY_RESULTS_TOTAL.inc_by(count as u64);
if count == 0 { crate::metrics::QUERY_EMPTY_RESULTS.inc(); }
let response = UnifiedQueryResponse {
query: req.query.clone(),
search_type: "entities".to_string(),
@@ -307,9 +279,7 @@ async fn search_edges(
).await {
Ok(r) => r,
Err(e) => {
crate::metrics::ERROR_UNEXPECTED_QUERY.inc();
crate::metrics::ERROR_UNEXPECTED_TOTAL.inc();
error!("Unexpected error: edge search failed: {}", e);
error!("Edge search failed: {}", e);
return crate::handlers::response_builder::internal_error(&format!("Search failed: {}", e));
}
};
@@ -335,9 +305,6 @@ async fn search_edges(
info!("Unified query (edges): {} results in {}ms", count, elapsed);
crate::metrics::QUERY_RESULTS_TOTAL.inc_by(count as u64);
if count == 0 { crate::metrics::QUERY_EMPTY_RESULTS.inc(); }
let response = UnifiedQueryResponse {
query: req.query.clone(),
search_type: "edges".to_string(),
@@ -371,9 +338,7 @@ async fn search_hybrid(
).await {
Ok(r) => r,
Err(e) => {
crate::metrics::ERROR_UNEXPECTED_QUERY.inc();
crate::metrics::ERROR_UNEXPECTED_TOTAL.inc();
error!("Unexpected error: hybrid search failed: {}", e);
error!("Hybrid search failed: {}", e);
return crate::handlers::response_builder::internal_error(&format!("Search failed: {}", e));
}
};
@@ -385,9 +350,6 @@ async fn search_hybrid(
info!("Unified query (hybrid): {} results in {}ms", count, elapsed);
crate::metrics::QUERY_RESULTS_TOTAL.inc_by(count as u64);
if count == 0 { crate::metrics::QUERY_EMPTY_RESULTS.inc(); }
let response = UnifiedQueryResponse {
query: req.query.clone(),
search_type: "hybrid".to_string(),
+10 -120
View File
@@ -374,30 +374,6 @@ pub async fn start_server(port: u16, api_key: String, database_url: &str) -> Res
});
tracing::info!("Starting HTTP server on port {}", port);
// O5/O7/O9: Background stats collector (every 60s)
{
let stats_pool = state.get_ref().pool.clone();
tokio::spawn(async move {
let mut interval = tokio::time::interval(std::time::Duration::from_secs(60));
loop {
interval.tick().await;
// O5: Table row counts
if let Ok(row) = sqlx::query_as::<_, (i64,)>("SELECT COUNT(*) FROM memory_entity")
.fetch_one(&stats_pool).await {
crate::metrics::DB_TABLE_ENTITY_ROWS.set(row.0 as u64);
}
if let Ok(row) = sqlx::query_as::<_, (i64,)>("SELECT COUNT(*) FROM memory_edge")
.fetch_one(&stats_pool).await {
crate::metrics::DB_TABLE_EDGE_ROWS.set(row.0 as u64);
}
// O9: Pool stats
crate::metrics::DB_POOL_SIZE.set(stats_pool.size() as u64);
crate::metrics::DB_POOL_IDLE.set(stats_pool.num_idle() as u64);
}
});
}
tracing::info!("Creating HttpServer instance...");
let server = HttpServer::new(move || {
@@ -406,7 +382,6 @@ pub async fn start_server(port: u16, api_key: String, database_url: &str) -> Res
.app_data(state.clone())
.wrap(Logger::default())
.route("/health", web::get().to(health_check))
.route("/metrics", web::get().to(crate::metrics::metrics_handler))
.route("/memory/ingest", web::post().to(ingest_handler))
.route("/memory/ingest/{ingest_id}", web::get().to(ingest_status))
.route("/memory/query", web::get().to(query_handler))
@@ -440,9 +415,6 @@ pub async fn start_server(port: u16, api_key: String, database_url: &str) -> Res
.route("/agents/{id}", web::put().to(crate::handlers::agent_handler::update_agent_handler))
.route("/agents/{id}", web::delete().to(crate::handlers::agent_handler::delete_agent_handler))
.route("/agents/{id}/metrics", web::get().to(crate::handlers::agent_handler::get_agent_metrics_handler))
.route("/agents/{id}/prompts", web::post().to(crate::handlers::agent_handler::create_prompt_handler))
.route("/agents/{id}/roles", web::post().to(crate::handlers::agent_handler::map_role_to_prompt_handler))
.route("/agents/{id}/roles/{role_name}/prompts", web::get().to(crate::handlers::agent_handler::get_role_prompts_handler))
});
tracing::info!("HttpServer instance created, binding to 0.0.0.0:{}", port);
@@ -456,24 +428,7 @@ pub async fn start_server(port: u16, api_key: String, database_url: &str) -> Res
/// Health check (no auth)
pub async fn health_check(state: web::Data<AppState>) -> HttpResponse {
use crate::metrics::*;
HEALTH_CHECKS_TOTAL.inc();
let uptime = state.start_time.elapsed().as_secs();
APP_UPTIME_SECONDS.set(uptime);
// O7: Check DB dependency
let db_start = std::time::Instant::now();
match sqlx::query("SELECT 1").execute(&state.pool).await {
Ok(_) => {
DEP_DB_UP.set(1);
DEP_DB_LATENCY.observe(db_start.elapsed().as_secs_f64());
}
Err(_) => {
DEP_DB_UP.set(0);
HEALTH_CHECK_FAILURES.inc();
}
}
HttpResponse::Ok().json(json!({"status": "ok", "uptime_seconds": uptime}))
}
@@ -483,75 +438,35 @@ pub async fn ingest_handler(
body: web::Json<IngestRequest>,
state: web::Data<AppState>,
) -> HttpResponse {
use crate::metrics::*;
INGEST_REQUESTS_TOTAL.inc();
INGEST_IN_FLIGHT.inc();
let _timer = Timer::new(&INGEST_DURATION);
// Auth + capability check
let (claims, _token) = match validate_auth(&req, &state).await {
Ok(c) => c,
Err(e) => {
INGEST_AUTH_FAILURES.inc();
INGEST_ERRORS_TOTAL.inc();
ERROR_AUTH_FAILURE_INGEST.inc();
INGEST_IN_FLIGHT.dec();
return e;
}
Err(e) => return e,
};
let user_id = &claims.sub;
if !has_capability(&claims, "memory:write") {
INGEST_AUTH_FAILURES.inc();
INGEST_ERRORS_TOTAL.inc();
ERROR_FORBIDDEN_INGEST.inc();
INGEST_IN_FLIGHT.dec();
return HttpResponse::Forbidden().json(json!({
"error": "forbidden",
"reason": "missing capability: memory:write"
}));
}
if let Err(e) = check_rate_limit(&claims, &state, "/memory/ingest") {
INGEST_RATE_LIMITED.inc();
ERROR_RATE_LIMITED_INGEST.inc();
INGEST_IN_FLIGHT.dec();
return e;
}
// Check idempotency
if let Some(cached) = state.idempotency_store.get(&body.ingest_id) {
tracing::info!("Returning cached response for ingest_id: {}", body.ingest_id);
INGEST_DUPLICATES_TOTAL.inc();
INGEST_IN_FLIGHT.dec();
return HttpResponse::Accepted().json(cached);
}
let byte_count: usize = body.records.iter().map(|r| r.text.len()).sum();
INGEST_BYTES_TOTAL.inc_by(byte_count as u64);
INGEST_RECORDS_TOTAL.inc_by(body.records.len() as u64);
// Extract X-Forward-User header for LLM auth (API Gateway pattern)
let x_forward_user = req
.headers()
.get("X-Forward-User")
.and_then(|h| h.to_str().ok())
.map(|s| s.to_string());
if let Some(ref user) = x_forward_user {
tracing::info!("Ingest request with X-Forward-User: {}", user);
}
// Execute ingest
let resp = execute_ingest(&state, &body, x_forward_user).await;
INGEST_IN_FLIGHT.dec();
resp
execute_ingest(&state, &body).await
}
/// Execute ingest job creation and spawn worker
async fn execute_ingest(
state: &web::Data<AppState>,
body: &IngestRequest,
x_forward_user: Option<String>,
) -> HttpResponse {
let records: Vec<(String, String)> = body.records
.iter()
@@ -582,9 +497,8 @@ async fn execute_ingest(
let worker = state.ingest_worker.clone();
let project = body.project.clone();
let ingest_id = body.ingest_id.clone();
let x_fwd = x_forward_user.clone();
tokio::spawn(async move {
if let Err(e) = worker.process_ingest_with_auth(&project, &ingest_id, records, x_fwd).await {
if let Err(e) = worker.process_ingest(&project, &ingest_id, records).await {
tracing::error!("Ingest failed: {}", e);
}
});
@@ -597,9 +511,7 @@ async fn execute_ingest(
HttpResponse::Accepted().json(response)
}
Err(e) => {
crate::metrics::ERROR_UNEXPECTED_INGEST.inc();
crate::metrics::ERROR_UNEXPECTED_TOTAL.inc();
tracing::error!(user_id = body.project.as_str(), "Unexpected DB error during ingest: {}", e);
tracing::error!("DB error: {}", e);
HttpResponse::InternalServerError().json(json!({"error": "database_error"}))
}
}
@@ -856,13 +768,8 @@ async fn store_compacted_memory(
.await;
match result {
Ok(_) => {
crate::metrics::WRITE_CHUNKS_TOTAL.inc();
crate::metrics::WRITE_BYTES_TOTAL.inc_by(memory.len() as u64);
true
}
Ok(_) => true,
Err(e) => {
crate::metrics::WRITE_ERRORS_TOTAL.inc();
tracing::error!("Failed to store compacted memory: {}", e);
false
}
@@ -923,9 +830,7 @@ pub async fn query_handler(
match query_temporal_graph(&state, &params).await {
Ok(response) => HttpResponse::Ok().json(response),
Err(e) => {
crate::metrics::ERROR_UNEXPECTED_QUERY.inc();
crate::metrics::ERROR_UNEXPECTED_TOTAL.inc();
tracing::error!(user_id = claims.sub.as_str(), "Unexpected error: temporal graph query failed: {}", e);
tracing::error!("Temporal graph query failed: {}", e);
HttpResponse::InternalServerError().json(json!({"error": "query_failed", "reason": e.to_string()}))
}
}
@@ -1061,23 +966,13 @@ pub async fn context_handler(
body: web::Json<crate::context_endpoint::ContextRequest>,
state: web::Data<AppState>,
) -> HttpResponse {
use crate::metrics::*;
CONTEXT_REQUESTS_TOTAL.inc();
let _timer = Timer::new(&CONTEXT_DURATION);
let (claims, _token) = match validate_auth(&req, &state).await {
Ok(c) => c,
Err(e) => {
CONTEXT_ERRORS_TOTAL.inc();
ERROR_AUTH_FAILURE_CONTEXT.inc();
return e;
}
Err(e) => return e,
};
let user_id = &claims.sub;
// Check read capability
if !has_capability(&claims, "memory:read") {
CONTEXT_ERRORS_TOTAL.inc();
ERROR_FORBIDDEN_CONTEXT.inc();
return HttpResponse::Forbidden().json(json!({
"error": "forbidden",
"reason": "missing capability: memory:read"
@@ -1102,14 +997,9 @@ pub async fn context_handler(
skills = response.skills.len(),
"context lookup successful"
);
// O3: Track tier hits
let total = response.lessons.len() + response.skills.len();
if total == 0 { CONTEXT_EMPTY_RESULTS.inc(); }
HttpResponse::Ok().json(response)
}
Err(e) => {
CONTEXT_ERRORS_TOTAL.inc();
ERROR_LOOKUP_FAILURE_CONTEXT.inc();
tracing::error!("context lookup error: {}", e);
HttpResponse::BadRequest().json(json!({
"error": "lookup_failed",
@@ -1454,7 +1344,7 @@ async fn query_temporal_graph(
) -> anyhow::Result<serde_json::Value> {
// Step 1: Find entities (order by name for deterministic results)
let entities_rows: Vec<(String, String, String)> = sqlx::query_as(
"SELECT id::TEXT, name, entity_type FROM memory_entity WHERE project_id = $1 LIMIT $2"
"SELECT id, name, entity_type FROM memory_entity WHERE project_id = $1 LIMIT $2"
)
.bind(&params.project)
.bind(params.limit as i32)
@@ -1470,7 +1360,7 @@ async fn query_temporal_graph(
for (entity_id, _name, _type_str) in &entities_rows {
let entity_edges: Vec<(String, String, String, String, f32, Option<chrono::DateTime<chrono::Utc>>, Option<chrono::DateTime<chrono::Utc>>)> =
sqlx::query_as(
"SELECT id::TEXT, target_id::TEXT, relation_type, fact, confidence, t_valid, t_invalid FROM memory_edge WHERE project_id = $1 AND source_id = $2::UUID"
"SELECT id, target_entity_id, relation_type, fact, confidence, t_valid, t_invalid FROM memory_edge WHERE project_id = $1 AND source_entity_id = $2"
)
.bind(&params.project)
.bind(entity_id)
+41 -286
View File
@@ -3,125 +3,19 @@ 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, LlmEntityExtractor};
use mem_ingest::fact_extractor::{SimpleFactExtractor, LlmFactExtractor};
use mem_ingest::fact_extractor::SimpleFactExtractor;
use mem_ingest::contradiction_detector::ContradictionHandler;
use sqlx::PgPool;
use uuid::Uuid;
use std::sync::Arc;
use pgvector::Vector;
/// Job status enumeration — type-safe alternative to magic strings
#[derive(Debug, Clone, Copy, PartialEq, Eq)]
pub enum JobStatus {
Processing,
Done,
DoneWithErrors,
}
impl JobStatus {
pub fn as_str(&self) -> &'static str {
match self {
JobStatus::Processing => "processing",
JobStatus::Done => "done",
JobStatus::DoneWithErrors => "done_with_errors",
}
}
}
impl std::fmt::Display for JobStatus {
fn fmt(&self, f: &mut std::fmt::Formatter<'_>) -> std::fmt::Result {
write!(f, "{}", self.as_str())
}
}
#[cfg(test)]
mod tests {
use super::*;
/// Mock JobStatusStore for testing
pub struct MockJobStatusStore {
updates: std::sync::Arc<std::sync::Mutex<Vec<(String, JobStatus)>>>,
}
impl MockJobStatusStore {
pub fn new() -> Self {
Self {
updates: std::sync::Arc::new(std::sync::Mutex::new(Vec::new())),
}
}
pub fn updates(&self) -> Vec<(String, JobStatus)> {
self.updates.lock().unwrap().clone()
}
}
#[async_trait::async_trait]
impl JobStatusStore for MockJobStatusStore {
async fn update_status(&self, ingest_id: &str, status: JobStatus) -> Result<()> {
self.updates.lock().unwrap().push((ingest_id.to_string(), status));
Ok(())
}
}
}
/// Structured logging context for ingest operations — ensures consistent field names across all logs
#[derive(Debug, Clone)]
pub struct IngestLogContext {
pub ingest_id: String,
pub project: String,
pub record_id: String,
pub source: String,
}
impl IngestLogContext {
fn new(ingest_id: &str, project: &str, record_id: &str, source: &str) -> Self {
Self {
ingest_id: ingest_id.to_string(),
project: project.to_string(),
record_id: record_id.to_string(),
source: source.to_string(),
}
}
}
/// Job status store trait — abstracts database persistence of job status (enables mocking)
#[async_trait::async_trait]
pub trait JobStatusStore: Send + Sync {
/// Update job status in storage
async fn update_status(&self, ingest_id: &str, status: JobStatus) -> Result<()>;
}
/// PostgreSQL implementation of JobStatusStore
pub struct PgJobStatusStore {
pool: PgPool,
}
impl PgJobStatusStore {
pub fn new(pool: PgPool) -> Self {
Self { pool }
}
}
#[async_trait::async_trait]
impl JobStatusStore for PgJobStatusStore {
async fn update_status(&self, ingest_id: &str, status: JobStatus) -> Result<()> {
sqlx::query("UPDATE ingest_jobs SET status=$1, started_at=NOW() WHERE ingest_id=$2")
.bind(status.as_str())
.bind(ingest_id)
.execute(&self.pool)
.await?;
Ok(())
}
}
/// Ingest worker — processes queued records through entity/fact extraction pipeline
pub struct IngestWorker {
pool: PgPool,
vector_store: Arc<VectorStore>,
embeddings: Arc<EmbeddingsClient>,
pipeline: Arc<IngestPipeline>,
job_status_store: Arc<dyn JobStatusStore>,
}
impl IngestWorker {
@@ -129,16 +23,6 @@ impl IngestWorker {
pub fn new(
pool: PgPool,
embeddings: EmbeddingsClient,
) -> Self {
let job_status_store = Arc::new(PgJobStatusStore::new(pool.clone()));
Self::with_job_store(pool, embeddings, job_status_store)
}
/// Create worker with custom job status store (for testing)
pub fn with_job_store(
pool: PgPool,
embeddings: EmbeddingsClient,
job_status_store: Arc<dyn JobStatusStore>,
) -> Self {
let vector_store = Arc::new(VectorStore::new(pool.clone()));
@@ -153,14 +37,7 @@ impl IngestWorker {
Arc::new(WikiLinkFallbackExtractor)
};
let fact_extractor: Arc<dyn mem_ingest::fact_extractor::FactExtractor> =
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 fact extractor: model={}", model);
Arc::new(LlmFactExtractor::new(&model))
} else {
tracing::info!("LLM_ENDPOINT not set, using simple pattern fact extractor");
Arc::new(SimpleFactExtractor)
};
Arc::new(SimpleFactExtractor);
let contradiction_detector = Arc::new(ContradictionHandler::default());
let pipeline = Arc::new(IngestPipeline::new(
entity_extractor,
@@ -173,43 +50,24 @@ impl IngestWorker {
vector_store,
embeddings: Arc::new(embeddings),
pipeline,
job_status_store,
}
}
/// Process ingest job with optional X-Forward-User auth header (API Gateway pattern)
///
/// # Arguments
/// * `project` - Project ID for namespacing
/// * `ingest_id` - Unique ingest job ID
/// * `records` - Vec of (content, source) tuples
/// * `x_forward_user` - Optional X-Forward-User header from API Gateway (None for backward compat)
pub async fn process_ingest_with_auth(
/// Process ingest job: records -> entities/facts/edges via pipeline -> temporal storage
pub async fn process_ingest(
&self,
project: &str,
ingest_id: &str,
records: Vec<(String, String)>, // (content, source)
x_forward_user: Option<String>,
) -> Result<()> {
tracing::info!(
target: "ingest",
event = "ingest_start",
ingest_id = ingest_id,
project = project,
record_count = records.len(),
"Starting ingest job"
);
tracing::info!("Processing ingest: project={}, id={}, records={}", project, ingest_id, records.len());
// Update job status to processing (via trait, testable)
if let Err(e) = self.job_status_store.update_status(ingest_id, JobStatus::Processing).await {
tracing::error!(
target: "ingest",
error = %e,
ingest_id = ingest_id,
"Failed to update job status to processing"
);
return Err(e.into());
}
// Update job status to processing
sqlx::query("UPDATE ingest_jobs SET status=$1, started_at=NOW() WHERE ingest_id=$2")
.bind("processing")
.bind(ingest_id)
.execute(&self.pool)
.await?;
let mut total_entities = 0;
let mut total_edges = 0;
@@ -217,92 +75,62 @@ impl IngestWorker {
// Process each record through the ingest pipeline
for (idx, (content, source)) in records.iter().enumerate() {
let record_id = format!("{}-{}", ingest_id, idx);
let log_ctx = IngestLogContext::new(ingest_id, project, &record_id, source);
tracing::debug!(
target: "ingest",
record_id = %log_ctx.record_id,
source = %log_ctx.source,
content_len = content.len(),
"Processing record"
);
// Create episode from record
let episode = Episode {
id: record_id.clone(),
id: format!("{}-{}", ingest_id, idx),
project_id: project.to_string(),
text: content.clone(),
wiki_links: extract_wiki_links(content),
};
// Run extraction pipeline (entity + fact extraction + contradiction detection)
let x_forward_user_ref = x_forward_user.as_deref();
match self.pipeline.ingest_with_auth(&episode, x_forward_user_ref).await {
match self.pipeline.ingest(&episode).await {
Ok(result) => {
tracing::debug!(
target: "ingest",
record_id = %log_ctx.record_id,
entity_count = result.entities.len(),
edge_count = result.edges.len(),
review_count = result.reviews.len(),
"Pipeline extraction successful"
"Pipeline extracted {} entities, {} edges for episode {}",
result.entities.len(),
result.edges.len(),
episode.id
);
// Save entities to database via helper fn
// Save entities to database (normally via EntityRepo, using direct SQL for now)
for entity in &result.entities {
match save_entity_with_logging(&self.pool, entity, &log_ctx).await {
Ok(saved) => if saved { total_entities += 1; }
Err(_) => { /* error already logged */ }
if let Err(e) = save_entity_to_db(&self.pool, entity).await {
tracing::warn!("Failed to save entity {}: {}", entity.name, e);
} else {
total_entities += 1;
}
}
// Save edges to database via helper fn
// Save edges to database (normally via EdgeRepo, using direct SQL for now)
for edge in &result.edges {
match save_edge_with_logging(&self.pool, edge, &log_ctx).await {
Ok(saved) => if saved { total_edges += 1; }
Err(_) => { /* error already logged */ }
if let Err(e) = save_edge_to_db(&self.pool, edge).await {
tracing::warn!("Failed to save edge: {}", e);
} else {
total_edges += 1;
}
}
total_reviews += result.reviews.len();
}
Err(e) => {
tracing::error!(
target: "ingest",
error = %e,
record_id = %log_ctx.record_id,
source = %log_ctx.source,
"Pipeline extraction failed"
);
// Continue processing other records (no error accumulation)
tracing::error!("Pipeline failed for episode {}: {}", episode.id, e);
// Continue processing other records
}
}
}
// Mark job complete (via trait, testable)
let final_status = JobStatus::Done;
if let Err(e) = self.job_status_store.update_status(ingest_id, final_status).await {
tracing::error!(
target: "ingest",
error = %e,
ingest_id = ingest_id,
"Failed to update job completion status"
);
}
// Mark job complete
sqlx::query("UPDATE ingest_jobs SET status=$1, completed_at=NOW() WHERE ingest_id=$2")
.bind("done")
.bind(ingest_id)
.execute(&self.pool)
.await?;
tracing::info!(
target: "ingest",
event = "ingest_complete",
ingest_id = ingest_id,
project = project,
entities = total_entities,
edges = total_edges,
reviews = total_reviews,
status = final_status.as_str(),
"Ingest job completed"
"Ingest completed: {} (entities={}, edges={}, reviews={})",
ingest_id, total_entities, total_edges, total_reviews
);
Ok(())
}
@@ -344,54 +172,15 @@ fn extract_wiki_links(text: &str) -> Vec<String> {
links
}
/// Save entity with logging — logs at debug level on success, warn on error
/// Returns Ok(true) if saved, Ok(false) if skipped, Err if fatal error
async fn save_entity_with_logging(
pool: &PgPool,
entity: &mem_core::entity::Entity,
log_ctx: &IngestLogContext,
) -> Result<bool> {
match save_entity_to_db(pool, entity).await {
Ok(_) => {
tracing::debug!(
target: "ingest",
record_id = %log_ctx.record_id,
entity_name = &entity.name,
entity_type = entity.entity_type.as_str(),
"Saved entity"
);
Ok(true)
}
Err(e) => {
tracing::warn!(
target: "ingest",
error = %e,
record_id = %log_ctx.record_id,
entity_name = &entity.name,
project = %log_ctx.project,
"Entity save failed"
);
// Return Ok(false) to allow processing to continue; don't panic
Ok(false)
}
}
}
/// Save entity to database via raw SQL (normally would use EntityRepo trait)
/// NOTE: async_trait requires manual implementation for non-trait functions
async fn save_entity_to_db(pool: &PgPool, entity: &mem_core::entity::Entity) -> Result<()> {
// Convert OffsetDateTime to PostgreSQL timestamp format
let t_created_str = entity.t_created.to_string();
sqlx::query(
"INSERT INTO memory_entity (id, project_id, name, entity_type, description, t_created, t_updated, confidence)
VALUES ($1::UUID, $2, $3, $4, $5, $6::TIMESTAMPTZ, $7::TIMESTAMPTZ, $8)
ON CONFLICT (project_id, name) DO UPDATE SET
entity_type = EXCLUDED.entity_type,
description = COALESCE(NULLIF(EXCLUDED.description, ''), memory_entity.description),
t_updated = NOW(),
confidence = GREATEST(memory_entity.confidence, EXCLUDED.confidence),
source_count = memory_entity.source_count + 1"
VALUES ($1, $2, $3, $4, $5, $6::TIMESTAMPTZ, $7::TIMESTAMPTZ, $8)
ON CONFLICT (id) DO NOTHING"
)
.bind(&entity.id)
.bind(&entity.project_id)
@@ -406,47 +195,13 @@ async fn save_entity_to_db(pool: &PgPool, entity: &mem_core::entity::Entity) ->
Ok(())
}
/// Save edge with logging — logs at debug level on success, warn on error
/// Returns Ok(true) if saved, Ok(false) if skipped, Err if fatal error
async fn save_edge_with_logging(
pool: &PgPool,
edge: &mem_core::edge::Edge,
log_ctx: &IngestLogContext,
) -> Result<bool> {
match save_edge_to_db(pool, edge).await {
Ok(_) => {
tracing::debug!(
target: "ingest",
record_id = %log_ctx.record_id,
relation_type = &edge.relation_type,
source_entity = &edge.source_entity_id,
target_entity = &edge.target_entity_id,
"Saved edge"
);
Ok(true)
}
Err(e) => {
tracing::warn!(
target: "ingest",
error = %e,
record_id = %log_ctx.record_id,
relation_type = &edge.relation_type,
project = %log_ctx.project,
"Edge save failed"
);
// Return Ok(false) to allow processing to continue
Ok(false)
}
}
}
/// Save edge to database via raw SQL (normally would use EdgeRepo trait)
/// NOTE: Production DB may have old schema. Gracefully skip if temporal columns missing.
async fn save_edge_to_db(pool: &PgPool, edge: &mem_core::edge::Edge) -> Result<()> {
// Try temporal schema first (id, project_id, source_entity_id, etc)
let result = sqlx::query(
"INSERT INTO memory_edge (id, project_id, source_id, target_id, relation_type, fact, t_valid, t_invalid, t_created, confidence)
VALUES ($1::UUID, $2, $3::UUID, $4::UUID, $5, $6, $7::TIMESTAMPTZ, $8::TIMESTAMPTZ, $9::TIMESTAMPTZ, $10)
"INSERT INTO memory_edge (id, project_id, source_entity_id, target_entity_id, relation_type, fact, t_valid, t_invalid, t_created, confidence)
VALUES ($1, $2, $3, $4, $5, $6, $7::TIMESTAMPTZ, $8::TIMESTAMPTZ, $9::TIMESTAMPTZ, $10)
ON CONFLICT (id) DO NOTHING"
)
.bind(&edge.id)
-3
View File
@@ -1,9 +1,6 @@
pub mod endpoints;
pub mod handlers;
pub mod http_server;
pub mod metrics;
pub mod metrics_snapshot;
pub mod relevance_judge;
pub mod query;
pub mod auth;
pub mod ingest_worker;
-700
View File
@@ -1,700 +0,0 @@
//! Prometheus metrics module (O10)
//!
//! Centralized metrics registry for poimen-memory observability.
//! All handlers instrument via these shared metrics.
//! Exposed at GET /metrics in Prometheus text format.
use once_cell::sync::Lazy;
use std::sync::atomic::{AtomicU64, Ordering};
use std::collections::HashMap;
use std::sync::Mutex;
use std::time::Instant;
// ─── Metric Types ───────────────────────────────────────────
/// Simple counter (monotonically increasing)
pub struct Counter {
value: AtomicU64,
name: &'static str,
help: &'static str,
}
impl Counter {
pub const fn new(name: &'static str, help: &'static str) -> Self {
Self { value: AtomicU64::new(0), name, help }
}
pub fn inc(&self) { self.value.fetch_add(1, Ordering::Relaxed); }
pub fn inc_by(&self, n: u64) { self.value.fetch_add(n, Ordering::Relaxed); }
pub fn get(&self) -> u64 { self.value.load(Ordering::Relaxed) }
}
/// Gauge (can go up and down)
pub struct Gauge {
value: AtomicU64,
name: &'static str,
help: &'static str,
}
impl Gauge {
pub const fn new(name: &'static str, help: &'static str) -> Self {
Self { value: AtomicU64::new(0), name, help }
}
pub fn set(&self, v: u64) { self.value.store(v, Ordering::Relaxed); }
pub fn inc(&self) { self.value.fetch_add(1, Ordering::Relaxed); }
pub fn dec(&self) { self.value.fetch_sub(1, Ordering::Relaxed); }
pub fn get(&self) -> u64 { self.value.load(Ordering::Relaxed) }
}
/// Gauge for f64 values (stored as bits)
pub struct GaugeF64 {
bits: AtomicU64,
name: &'static str,
help: &'static str,
}
impl GaugeF64 {
pub const fn new(name: &'static str, help: &'static str) -> Self {
Self { bits: AtomicU64::new(0), name, help }
}
pub fn set(&self, v: f64) { self.bits.store(v.to_bits(), Ordering::Relaxed); }
pub fn get(&self) -> f64 { f64::from_bits(self.bits.load(Ordering::Relaxed)) }
}
/// Histogram with fixed buckets for latency tracking
pub struct Histogram {
pub buckets: &'static [f64],
pub counts: Vec<AtomicU64>,
pub sum: AtomicU64, // stored as f64 bits
pub count: AtomicU64,
pub name: &'static str,
pub help: &'static str,
}
impl Histogram {
pub fn new(name: &'static str, help: &'static str, buckets: &'static [f64]) -> Self {
let counts = (0..buckets.len() + 1).map(|_| AtomicU64::new(0)).collect();
Self {
buckets, counts, name, help,
sum: AtomicU64::new(0f64.to_bits()),
count: AtomicU64::new(0),
}
}
pub fn observe(&self, value: f64) {
self.count.fetch_add(1, Ordering::Relaxed);
// Add to sum (CAS loop for f64)
loop {
let old_bits = self.sum.load(Ordering::Relaxed);
let old = f64::from_bits(old_bits);
let new = old + value;
if self.sum.compare_exchange(old_bits, new.to_bits(), Ordering::Relaxed, Ordering::Relaxed).is_ok() {
break;
}
}
// Increment bucket counters
for (i, &bound) in self.buckets.iter().enumerate() {
if value <= bound {
self.counts[i].fetch_add(1, Ordering::Relaxed);
}
}
// +Inf bucket
self.counts[self.buckets.len()].fetch_add(1, Ordering::Relaxed);
}
}
/// Labeled counter (key = label combination string)
pub struct LabeledCounter {
values: Mutex<HashMap<String, u64>>,
name: &'static str,
help: &'static str,
label_names: &'static [&'static str],
}
impl LabeledCounter {
pub fn new(name: &'static str, help: &'static str, label_names: &'static [&'static str]) -> Self {
Self { values: Mutex::new(HashMap::new()), name, help, label_names }
}
pub fn inc(&self, labels: &[&str]) {
let key = labels.join(",");
let mut map = self.values.lock().unwrap();
*map.entry(key).or_insert(0) += 1;
}
}
// ─── Timer helper ───────────────────────────────────────────
/// RAII timer: observes duration on drop
pub struct Timer<'a> {
histogram: &'a Histogram,
start: Instant,
}
impl<'a> Timer<'a> {
pub fn new(histogram: &'a Histogram) -> Self {
Self { histogram, start: Instant::now() }
}
}
impl<'a> Drop for Timer<'a> {
fn drop(&mut self) {
let elapsed = self.start.elapsed().as_secs_f64();
self.histogram.observe(elapsed);
}
}
// ─── Default buckets ────────────────────────────────────────
/// Latency buckets for HTTP handlers (seconds)
pub static HTTP_BUCKETS: &[f64] = &[0.005, 0.01, 0.025, 0.05, 0.1, 0.25, 0.5, 1.0, 2.5, 5.0, 10.0];
/// Latency buckets for LLM calls (seconds)
pub static LLM_BUCKETS: &[f64] = &[0.1, 0.25, 0.5, 1.0, 2.5, 5.0, 10.0, 30.0, 60.0];
/// Latency buckets for DB queries (seconds)
pub static DB_BUCKETS: &[f64] = &[0.001, 0.005, 0.01, 0.025, 0.05, 0.1, 0.25, 0.5, 1.0];
// ═══════════════════════════════════════════════════════════
// O1: Ingest handler metrics (I1-I12)
// ═══════════════════════════════════════════════════════════
pub static INGEST_REQUESTS_TOTAL: Counter = Counter::new(
"memory_ingest_requests_total", "Total ingest requests received");
pub static INGEST_ERRORS_TOTAL: Counter = Counter::new(
"memory_ingest_errors_total", "Total ingest request errors");
pub static INGEST_RECORDS_TOTAL: Counter = Counter::new(
"memory_ingest_records_total", "Total records ingested");
pub static INGEST_ENTITIES_EXTRACTED: Counter = Counter::new(
"memory_ingest_entities_extracted_total", "Total entities extracted during ingest");
pub static INGEST_EDGES_EXTRACTED: Counter = Counter::new(
"memory_ingest_edges_extracted_total", "Total edges extracted during ingest");
pub static INGEST_IN_FLIGHT: Gauge = Gauge::new(
"memory_ingest_in_flight", "Currently processing ingest jobs");
pub static INGEST_QUEUE_SIZE: Gauge = Gauge::new(
"memory_ingest_queue_size", "Number of jobs waiting in ingest queue");
pub static INGEST_DUPLICATES_TOTAL: Counter = Counter::new(
"memory_ingest_duplicates_total", "Total duplicate ingest requests (idempotency)");
pub static INGEST_BYTES_TOTAL: Counter = Counter::new(
"memory_ingest_bytes_total", "Total bytes ingested");
pub static INGEST_AUTH_FAILURES: Counter = Counter::new(
"memory_ingest_auth_failures_total", "Total auth failures on ingest endpoint");
pub static INGEST_RATE_LIMITED: Counter = Counter::new(
"memory_ingest_rate_limited_total", "Total rate-limited ingest requests");
pub static INGEST_DURATION: Lazy<Histogram> = Lazy::new(||
Histogram::new("memory_ingest_duration_seconds", "Ingest request duration", HTTP_BUCKETS));
// ═══════════════════════════════════════════════════════════
// O2: Query handler metrics (Q1-Q12)
// ═══════════════════════════════════════════════════════════
pub static QUERY_REQUESTS_TOTAL: Counter = Counter::new(
"memory_query_requests_total", "Total query requests received");
pub static QUERY_ERRORS_TOTAL: Counter = Counter::new(
"memory_query_errors_total", "Total query request errors");
pub static QUERY_RESULTS_TOTAL: Counter = Counter::new(
"memory_query_results_total", "Total results returned across all queries");
pub static QUERY_EMPTY_RESULTS: Counter = Counter::new(
"memory_query_empty_results_total", "Queries returning zero results");
pub static QUERY_EMBEDDING_FAILURES: Counter = Counter::new(
"memory_query_embedding_failures_total", "Total embedding failures during query");
pub static QUERY_IN_FLIGHT: Gauge = Gauge::new(
"memory_query_in_flight", "Currently processing queries");
pub static QUERY_AUTH_FAILURES: Counter = Counter::new(
"memory_query_auth_failures_total", "Total auth failures on query endpoint");
pub static QUERY_RATE_LIMITED: Counter = Counter::new(
"memory_query_rate_limited_total", "Total rate-limited query requests");
pub static QUERY_CACHE_HITS: Counter = Counter::new(
"memory_query_cache_hits_total", "Total query cache hits");
pub static QUERY_CACHE_MISSES: Counter = Counter::new(
"memory_query_cache_misses_total", "Total query cache misses");
pub static QUERY_DURATION: Lazy<Histogram> = Lazy::new(||
Histogram::new("memory_query_duration_seconds", "Query request duration", HTTP_BUCKETS));
pub static QUERY_EMBEDDING_DURATION: Lazy<Histogram> = Lazy::new(||
Histogram::new("memory_query_embedding_duration_seconds", "Embedding call duration during query", LLM_BUCKETS));
// ═══════════════════════════════════════════════════════════
// O3: Context endpoint metrics (C1-C8)
// ═══════════════════════════════════════════════════════════
pub static CONTEXT_REQUESTS_TOTAL: Counter = Counter::new(
"memory_context_requests_total", "Total context retrieval requests");
pub static CONTEXT_ERRORS_TOTAL: Counter = Counter::new(
"memory_context_errors_total", "Total context retrieval errors");
pub static CONTEXT_SEMANTIC_HITS: Counter = Counter::new(
"memory_context_semantic_hits_total", "Results from semantic (cosine) tier");
pub static CONTEXT_BM25_HITS: Counter = Counter::new(
"memory_context_bm25_hits_total", "Results from BM25 (lexical) tier");
pub static CONTEXT_GRAPH_HITS: Counter = Counter::new(
"memory_context_graph_hits_total", "Results from graph traversal tier");
pub static CONTEXT_EMPTY_RESULTS: Counter = Counter::new(
"memory_context_empty_results_total", "Context requests returning zero results");
pub static CONTEXT_DURATION: Lazy<Histogram> = Lazy::new(||
Histogram::new("memory_context_duration_seconds", "Context retrieval duration", HTTP_BUCKETS));
pub static CONTEXT_TIER_DURATION: Lazy<Histogram> = Lazy::new(||
Histogram::new("memory_context_tier_duration_seconds", "Per-tier retrieval duration", DB_BUCKETS));
// ═══════════════════════════════════════════════════════════
// O4: Relevance judge metrics (R1-R9)
// ═══════════════════════════════════════════════════════════
pub static RELEVANCE_EVALS_TOTAL: Counter = Counter::new(
"memory_relevance_evals_total", "Total relevance evaluations performed");
pub static RELEVANCE_ERRORS_TOTAL: Counter = Counter::new(
"memory_relevance_errors_total", "Total relevance evaluation errors");
pub static RELEVANCE_RELEVANT_TOTAL: Counter = Counter::new(
"memory_relevance_relevant_total", "Results judged relevant");
pub static RELEVANCE_IRRELEVANT_TOTAL: Counter = Counter::new(
"memory_relevance_irrelevant_total", "Results judged irrelevant");
pub static RELEVANCE_SCORE: Lazy<Histogram> = Lazy::new(||
Histogram::new("memory_relevance_score", "Distribution of relevance scores",
&[0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 1.0]));
pub static RELEVANCE_PRECISION: GaugeF64 = GaugeF64::new(
"memory_relevance_precision", "Current precision (relevant/retrieved)");
pub static RELEVANCE_RECALL: GaugeF64 = GaugeF64::new(
"memory_relevance_recall", "Current recall (relevant/total_relevant)");
pub static RELEVANCE_F1: GaugeF64 = GaugeF64::new(
"memory_relevance_f1_score", "Current F1 score");
pub static RELEVANCE_EVAL_DURATION: Lazy<Histogram> = Lazy::new(||
Histogram::new("memory_relevance_eval_duration_seconds", "Relevance evaluation duration", LLM_BUCKETS));
// ═══════════════════════════════════════════════════════════
// O5: Write volume and storage metrics (W1-W12)
// ═══════════════════════════════════════════════════════════
pub static WRITE_ENTITIES_TOTAL: Counter = Counter::new(
"memory_write_entities_total", "Total entities written to DB");
pub static WRITE_EDGES_TOTAL: Counter = Counter::new(
"memory_write_edges_total", "Total edges written to DB");
pub static WRITE_CHUNKS_TOTAL: Counter = Counter::new(
"memory_write_chunks_total", "Total chunks written to DB");
pub static WRITE_ERRORS_TOTAL: Counter = Counter::new(
"memory_write_errors_total", "Total write errors");
pub static WRITE_BYTES_TOTAL: Counter = Counter::new(
"memory_write_bytes_total", "Total bytes written to storage");
pub static DB_ENTITY_COUNT: Gauge = Gauge::new(
"memory_db_entity_count", "Current entity count in memory_entity table");
pub static DB_EDGE_COUNT: Gauge = Gauge::new(
"memory_db_edge_count", "Current edge count in memory_edge table");
pub static DB_CHUNK_COUNT: Gauge = Gauge::new(
"memory_db_chunk_count", "Current chunk count in memory_chunks table");
pub static WRITE_DURATION: Lazy<Histogram> = Lazy::new(||
Histogram::new("memory_write_duration_seconds", "Write operation duration", DB_BUCKETS));
pub static WRITE_BATCH_SIZE: Lazy<Histogram> = Lazy::new(||
Histogram::new("memory_write_batch_size", "Write batch sizes",
&[1.0, 5.0, 10.0, 25.0, 50.0, 100.0, 250.0, 500.0]));
// Storage gauges (updated periodically)
pub static DB_SIZE_BYTES: Gauge = Gauge::new(
"memory_db_size_bytes", "Total database size in bytes");
pub static DB_INDEX_SIZE_BYTES: Gauge = Gauge::new(
"memory_db_index_size_bytes", "Total index size in bytes");
// ═══════════════════════════════════════════════════════════
// O6: Pod resource observability (P1-P13)
// (Most collected by node-exporter/cAdvisor, but we track app-level)
// ═══════════════════════════════════════════════════════════
pub static APP_UPTIME_SECONDS: Gauge = Gauge::new(
"memory_app_uptime_seconds", "Application uptime in seconds");
pub static APP_ACTIVE_CONNECTIONS: Gauge = Gauge::new(
"memory_app_active_connections", "Active HTTP connections");
pub static APP_GOROUTINES: Gauge = Gauge::new(
"memory_app_tokio_tasks", "Active tokio tasks (approximate)");
pub static APP_HEAP_BYTES: Gauge = Gauge::new(
"memory_app_heap_bytes", "Approximate heap memory usage");
// ═══════════════════════════════════════════════════════════
// O7: Availability metrics and dependency health (A1-A10)
// ═══════════════════════════════════════════════════════════
pub static HEALTH_CHECKS_TOTAL: Counter = Counter::new(
"memory_health_checks_total", "Total health check requests");
pub static HEALTH_CHECK_FAILURES: Counter = Counter::new(
"memory_health_check_failures_total", "Total health check failures");
pub static DEP_DB_UP: Gauge = Gauge::new(
"memory_dependency_db_up", "Database dependency health (1=up, 0=down)");
pub static DEP_EMBEDDING_UP: Gauge = Gauge::new(
"memory_dependency_embedding_up", "Embedding service health (1=up, 0=down)");
pub static DEP_OPENSEARCH_UP: Gauge = Gauge::new(
"memory_dependency_opensearch_up", "OpenSearch dependency health (1=up, 0=down)");
pub static DEP_LLM_UP: Gauge = Gauge::new(
"memory_dependency_llm_up", "LLM service health (1=up, 0=down)");
pub static DEP_DB_LATENCY: Lazy<Histogram> = Lazy::new(||
Histogram::new("memory_dependency_db_latency_seconds", "DB health check latency", DB_BUCKETS));
pub static DEP_EMBEDDING_LATENCY: Lazy<Histogram> = Lazy::new(||
Histogram::new("memory_dependency_embedding_latency_seconds", "Embedding health check latency", LLM_BUCKETS));
pub static REQUEST_ERRORS_BY_STATUS: Lazy<LabeledCounter> = Lazy::new(||
LabeledCounter::new(
"memory_request_errors_by_status", "Request errors by HTTP status code",
&["status", "endpoint"]));
// ═══════════════════════════════════════════════════════════
// Named error counters (per error type, per endpoint)
// Format: memory_error_{ERROR_NAME}_{ENDPOINT}_total
// ═══════════════════════════════════════════════════════════
// Ingest errors
pub static ERROR_AUTH_FAILURE_INGEST: Counter = Counter::new(
"memory_error_auth_failure_ingest_total", "Auth failures on ingest endpoint");
pub static ERROR_FORBIDDEN_INGEST: Counter = Counter::new(
"memory_error_forbidden_ingest_total", "Forbidden (missing capability) on ingest");
pub static ERROR_RATE_LIMITED_INGEST: Counter = Counter::new(
"memory_error_rate_limited_ingest_total", "Rate limited on ingest");
pub static ERROR_BAD_REQUEST_INGEST: Counter = Counter::new(
"memory_error_bad_request_ingest_total", "Bad request on ingest");
pub static ERROR_DB_ERROR_INGEST: Counter = Counter::new(
"memory_error_db_error_ingest_total", "Database error during ingest");
// Query errors
pub static ERROR_AUTH_FAILURE_QUERY: Counter = Counter::new(
"memory_error_auth_failure_query_total", "Auth failures on query endpoint");
pub static ERROR_FORBIDDEN_QUERY: Counter = Counter::new(
"memory_error_forbidden_query_total", "Forbidden (missing capability) on query");
pub static ERROR_BAD_REQUEST_QUERY: Counter = Counter::new(
"memory_error_bad_request_query_total", "Bad request on query");
pub static ERROR_EMBEDDING_FAILURE_QUERY: Counter = Counter::new(
"memory_error_embedding_failure_query_total", "Embedding service failure during query");
pub static ERROR_SEARCH_FAILURE_QUERY: Counter = Counter::new(
"memory_error_search_failure_query_total", "Search execution failure during query");
// Context errors
pub static ERROR_AUTH_FAILURE_CONTEXT: Counter = Counter::new(
"memory_error_auth_failure_context_total", "Auth failures on context endpoint");
pub static ERROR_FORBIDDEN_CONTEXT: Counter = Counter::new(
"memory_error_forbidden_context_total", "Forbidden (missing capability) on context");
pub static ERROR_LOOKUP_FAILURE_CONTEXT: Counter = Counter::new(
"memory_error_lookup_failure_context_total", "Context lookup failure");
// Unexpected errors (unhandled 500s, panics, unknown failures)
pub static ERROR_UNEXPECTED_TOTAL: Counter = Counter::new(
"memory_error_unexpected_total", "Total unexpected/unhandled errors (500s)");
pub static ERROR_UNEXPECTED_INGEST: Counter = Counter::new(
"memory_error_unexpected_ingest_total", "Unexpected errors during ingest");
pub static ERROR_UNEXPECTED_QUERY: Counter = Counter::new(
"memory_error_unexpected_query_total", "Unexpected errors during query");
pub static ERROR_UNEXPECTED_CONTEXT: Counter = Counter::new(
"memory_error_unexpected_context_total", "Unexpected errors during context");
// Agent endpoint error counters
pub static ERROR_AUTH_FAILURE_AGENT: Counter = Counter::new(
"memory_error_auth_failure_agent_total", "Auth failures on agent endpoints");
pub static ERROR_BAD_REQUEST_AGENT: Counter = Counter::new(
"memory_error_bad_request_agent_total", "Bad request errors on agent endpoints (expected)");
pub static ERROR_NOT_FOUND_AGENT: Counter = Counter::new(
"memory_error_not_found_agent_total", "Not found errors on agent endpoints (expected)");
pub static ERROR_UNEXPECTED_AGENT: Counter = Counter::new(
"memory_error_unexpected_agent_total", "Unexpected errors on agent endpoints (DB failures, 500s)");
// Last error info (most recent error for debugging)
pub static LAST_ERROR_TIMESTAMP: Gauge = Gauge::new(
"memory_last_error_timestamp_seconds", "Unix timestamp of most recent error");
// ═══════════════════════════════════════════════════════════
// O8: Ingest rate pattern tracking (IR1-IR10)
// ═══════════════════════════════════════════════════════════
pub static INGEST_RATE_1M: GaugeF64 = GaugeF64::new(
"memory_ingest_rate_1m", "Ingest rate per second (1-minute window)");
pub static INGEST_RATE_5M: GaugeF64 = GaugeF64::new(
"memory_ingest_rate_5m", "Ingest rate per second (5-minute window)");
pub static INGEST_LLM_EXTRACT_DURATION: Lazy<Histogram> = Lazy::new(||
Histogram::new("memory_ingest_llm_extract_duration_seconds", "LLM entity extraction duration", LLM_BUCKETS));
pub static INGEST_FACT_EXTRACT_DURATION: Lazy<Histogram> = Lazy::new(||
Histogram::new("memory_ingest_fact_extract_duration_seconds", "LLM fact extraction duration", LLM_BUCKETS));
pub static INGEST_DEDUP_TOTAL: Counter = Counter::new(
"memory_ingest_dedup_total", "Total entities deduplicated");
pub static INGEST_CONTRADICTION_TOTAL: Counter = Counter::new(
"memory_ingest_contradiction_total", "Total contradictions detected");
pub static INGEST_PROJECTS: Gauge = Gauge::new(
"memory_ingest_active_projects", "Number of active projects with ingested data");
// ═══════════════════════════════════════════════════════════
// O9: Postgres internal observability (PG1-PG33)
// (Most collected by pg_exporter, we expose app-visible DB stats)
// ═══════════════════════════════════════════════════════════
pub static DB_POOL_SIZE: Gauge = Gauge::new(
"memory_db_pool_size", "Current connection pool size");
pub static DB_POOL_IDLE: Gauge = Gauge::new(
"memory_db_pool_idle", "Idle connections in pool");
pub static DB_POOL_ACTIVE: Gauge = Gauge::new(
"memory_db_pool_active", "Active connections in pool");
pub static DB_QUERY_TOTAL: Counter = Counter::new(
"memory_db_queries_total", "Total DB queries executed");
pub static DB_QUERY_ERRORS: Counter = Counter::new(
"memory_db_query_errors_total", "Total DB query errors");
pub static DB_QUERY_DURATION: Lazy<Histogram> = Lazy::new(||
Histogram::new("memory_db_query_duration_seconds", "DB query duration", DB_BUCKETS));
pub static DB_TRANSACTION_DURATION: Lazy<Histogram> = Lazy::new(||
Histogram::new("memory_db_transaction_duration_seconds", "DB transaction duration", DB_BUCKETS));
// Table-specific row counts (updated periodically)
pub static DB_TABLE_ENTITY_ROWS: Gauge = Gauge::new(
"memory_db_table_entity_rows", "Rows in memory_entity table");
pub static DB_TABLE_EDGE_ROWS: Gauge = Gauge::new(
"memory_db_table_edge_rows", "Rows in memory_edge table");
pub static DB_TABLE_CHUNK_ROWS: Gauge = Gauge::new(
"memory_db_table_chunk_rows", "Rows in memory_chunks table");
// ═══════════════════════════════════════════════════════════
// Metrics export (Prometheus text format)
// ═══════════════════════════════════════════════════════════
/// Render all metrics in Prometheus text exposition format
pub fn render_metrics() -> String {
let mut out = String::with_capacity(8192);
// Helper macros
macro_rules! counter {
($c:expr) => {
out.push_str(&format!("# HELP {} {}\n# TYPE {} counter\n{} {}\n",
$c.name, $c.help, $c.name, $c.name, $c.get()));
};
}
macro_rules! gauge {
($g:expr) => {
out.push_str(&format!("# HELP {} {}\n# TYPE {} gauge\n{} {}\n",
$g.name, $g.help, $g.name, $g.name, $g.get()));
};
}
macro_rules! gauge_f64 {
($g:expr) => {
out.push_str(&format!("# HELP {} {}\n# TYPE {} gauge\n{} {:.6}\n",
$g.name, $g.help, $g.name, $g.name, $g.get()));
};
}
macro_rules! histogram {
($h:expr) => {
out.push_str(&format!("# HELP {} {}\n# TYPE {} histogram\n", $h.name, $h.help, $h.name));
for (i, &bound) in $h.buckets.iter().enumerate() {
out.push_str(&format!("{}_bucket{{le=\"{}\"}} {}\n",
$h.name, bound, $h.counts[i].load(Ordering::Relaxed)));
}
out.push_str(&format!("{}_bucket{{le=\"+Inf\"}} {}\n",
$h.name, $h.counts[$h.buckets.len()].load(Ordering::Relaxed)));
out.push_str(&format!("{}_sum {:.6}\n", $h.name,
f64::from_bits($h.sum.load(Ordering::Relaxed))));
out.push_str(&format!("{}_count {}\n", $h.name,
$h.count.load(Ordering::Relaxed)));
};
}
// O1: Ingest
counter!(INGEST_REQUESTS_TOTAL);
counter!(INGEST_ERRORS_TOTAL);
counter!(INGEST_RECORDS_TOTAL);
counter!(INGEST_ENTITIES_EXTRACTED);
counter!(INGEST_EDGES_EXTRACTED);
gauge!(INGEST_IN_FLIGHT);
gauge!(INGEST_QUEUE_SIZE);
counter!(INGEST_DUPLICATES_TOTAL);
counter!(INGEST_BYTES_TOTAL);
counter!(INGEST_AUTH_FAILURES);
counter!(INGEST_RATE_LIMITED);
histogram!(INGEST_DURATION);
// O2: Query
counter!(QUERY_REQUESTS_TOTAL);
counter!(QUERY_ERRORS_TOTAL);
counter!(QUERY_RESULTS_TOTAL);
counter!(QUERY_EMPTY_RESULTS);
counter!(QUERY_EMBEDDING_FAILURES);
gauge!(QUERY_IN_FLIGHT);
counter!(QUERY_AUTH_FAILURES);
counter!(QUERY_RATE_LIMITED);
counter!(QUERY_CACHE_HITS);
counter!(QUERY_CACHE_MISSES);
histogram!(QUERY_DURATION);
histogram!(QUERY_EMBEDDING_DURATION);
// O3: Context
counter!(CONTEXT_REQUESTS_TOTAL);
counter!(CONTEXT_ERRORS_TOTAL);
counter!(CONTEXT_SEMANTIC_HITS);
counter!(CONTEXT_BM25_HITS);
counter!(CONTEXT_GRAPH_HITS);
counter!(CONTEXT_EMPTY_RESULTS);
histogram!(CONTEXT_DURATION);
histogram!(CONTEXT_TIER_DURATION);
// O4: Relevance
counter!(RELEVANCE_EVALS_TOTAL);
counter!(RELEVANCE_ERRORS_TOTAL);
counter!(RELEVANCE_RELEVANT_TOTAL);
counter!(RELEVANCE_IRRELEVANT_TOTAL);
histogram!(RELEVANCE_SCORE);
gauge_f64!(RELEVANCE_PRECISION);
gauge_f64!(RELEVANCE_RECALL);
gauge_f64!(RELEVANCE_F1);
histogram!(RELEVANCE_EVAL_DURATION);
// O5: Write volume
counter!(WRITE_ENTITIES_TOTAL);
counter!(WRITE_EDGES_TOTAL);
counter!(WRITE_CHUNKS_TOTAL);
counter!(WRITE_ERRORS_TOTAL);
counter!(WRITE_BYTES_TOTAL);
gauge!(DB_ENTITY_COUNT);
gauge!(DB_EDGE_COUNT);
gauge!(DB_CHUNK_COUNT);
histogram!(WRITE_DURATION);
histogram!(WRITE_BATCH_SIZE);
gauge!(DB_SIZE_BYTES);
gauge!(DB_INDEX_SIZE_BYTES);
// O6: Pod resources
gauge!(APP_UPTIME_SECONDS);
gauge!(APP_ACTIVE_CONNECTIONS);
gauge!(APP_GOROUTINES);
gauge!(APP_HEAP_BYTES);
// O7: Availability
counter!(HEALTH_CHECKS_TOTAL);
counter!(HEALTH_CHECK_FAILURES);
gauge!(DEP_DB_UP);
gauge!(DEP_EMBEDDING_UP);
gauge!(DEP_OPENSEARCH_UP);
gauge!(DEP_LLM_UP);
histogram!(DEP_DB_LATENCY);
histogram!(DEP_EMBEDDING_LATENCY);
// O8: Ingest rate
gauge_f64!(INGEST_RATE_1M);
gauge_f64!(INGEST_RATE_5M);
histogram!(INGEST_LLM_EXTRACT_DURATION);
histogram!(INGEST_FACT_EXTRACT_DURATION);
counter!(INGEST_DEDUP_TOTAL);
counter!(INGEST_CONTRADICTION_TOTAL);
gauge!(INGEST_PROJECTS);
// O9: Postgres
gauge!(DB_POOL_SIZE);
gauge!(DB_POOL_IDLE);
gauge!(DB_POOL_ACTIVE);
counter!(DB_QUERY_TOTAL);
counter!(DB_QUERY_ERRORS);
histogram!(DB_QUERY_DURATION);
histogram!(DB_TRANSACTION_DURATION);
gauge!(DB_TABLE_ENTITY_ROWS);
gauge!(DB_TABLE_EDGE_ROWS);
gauge!(DB_TABLE_CHUNK_ROWS);
// Named error counters
counter!(ERROR_AUTH_FAILURE_INGEST);
counter!(ERROR_FORBIDDEN_INGEST);
counter!(ERROR_RATE_LIMITED_INGEST);
counter!(ERROR_BAD_REQUEST_INGEST);
counter!(ERROR_DB_ERROR_INGEST);
counter!(ERROR_AUTH_FAILURE_QUERY);
counter!(ERROR_FORBIDDEN_QUERY);
counter!(ERROR_BAD_REQUEST_QUERY);
counter!(ERROR_EMBEDDING_FAILURE_QUERY);
counter!(ERROR_SEARCH_FAILURE_QUERY);
counter!(ERROR_AUTH_FAILURE_CONTEXT);
counter!(ERROR_FORBIDDEN_CONTEXT);
counter!(ERROR_LOOKUP_FAILURE_CONTEXT);
counter!(ERROR_UNEXPECTED_TOTAL);
counter!(ERROR_UNEXPECTED_INGEST);
counter!(ERROR_UNEXPECTED_QUERY);
counter!(ERROR_UNEXPECTED_CONTEXT);
counter!(ERROR_AUTH_FAILURE_AGENT);
counter!(ERROR_BAD_REQUEST_AGENT);
counter!(ERROR_NOT_FOUND_AGENT);
counter!(ERROR_UNEXPECTED_AGENT);
gauge!(LAST_ERROR_TIMESTAMP);
out
}
/// Render a labeled counter in Prometheus format
fn render_labeled_counter(out: &mut String, lc: &LabeledCounter) {
let map = lc.values.lock().unwrap();
if map.is_empty() { return; }
out.push_str(&format!("# HELP {} {}\n# TYPE {} counter\n", lc.name, lc.help, lc.name));
for (key, val) in map.iter() {
let parts: Vec<&str> = key.split(',').collect();
let labels: Vec<String> = lc.label_names.iter().zip(parts.iter())
.map(|(name, val)| format!("{}=\"{}\"", name, val))
.collect();
out.push_str(&format!("{}{{{}}} {}\n", lc.name, labels.join(","), val));
}
}
/// GET /metrics handler
pub async fn metrics_handler() -> actix_web::HttpResponse {
actix_web::HttpResponse::Ok()
.content_type("text/plain; version=0.0.4; charset=utf-8")
.body(render_metrics())
}
#[cfg(test)]
mod tests {
use super::*;
#[test]
fn test_counter() {
let c = Counter::new("test_counter", "test");
assert_eq!(c.get(), 0);
c.inc();
assert_eq!(c.get(), 1);
c.inc_by(5);
assert_eq!(c.get(), 6);
}
#[test]
fn test_gauge() {
let g = Gauge::new("test_gauge", "test");
assert_eq!(g.get(), 0);
g.set(42);
assert_eq!(g.get(), 42);
g.inc();
assert_eq!(g.get(), 43);
g.dec();
assert_eq!(g.get(), 42);
}
#[test]
fn test_gauge_f64() {
let g = GaugeF64::new("test_gauge_f64", "test");
assert_eq!(g.get(), 0.0);
g.set(3.14);
assert!((g.get() - 3.14).abs() < 0.001);
}
#[test]
fn test_histogram() {
let h = Histogram::new("test_hist", "test", &[0.1, 0.5, 1.0]);
h.observe(0.05);
h.observe(0.3);
h.observe(0.8);
h.observe(2.0);
assert_eq!(h.count.load(Ordering::Relaxed), 4);
}
#[test]
fn test_render_metrics_not_empty() {
INGEST_REQUESTS_TOTAL.inc();
QUERY_REQUESTS_TOTAL.inc();
let output = render_metrics();
assert!(output.contains("memory_ingest_requests_total"));
assert!(output.contains("memory_query_requests_total"));
assert!(output.contains("# HELP"));
assert!(output.contains("# TYPE"));
}
#[test]
fn test_timer_observes_on_drop() {
let h = Histogram::new("timer_test", "test", HTTP_BUCKETS);
{
let _t = Timer::new(&h);
std::thread::sleep(std::time::Duration::from_millis(1));
}
assert_eq!(h.count.load(Ordering::Relaxed), 1);
}
}
-418
View File
@@ -1,418 +0,0 @@
//! Metrics Snapshot & Assertion (Test Harness)
//!
//! Captures metric state before/after a test scenario,
//! then asserts expected deltas per metric.
//!
//! Usage:
//! ```rust
//! let snap = MetricsSnapshot::capture();
//! // ... run handler / scenario ...
//! snap.assert_counter_inc("memory_ingest_requests_total", 1);
//! snap.assert_counter_inc("memory_ingest_errors_total", 0);
//! snap.assert_gauge_eq("memory_ingest_in_flight", 0);
//! snap.assert_histogram_count_inc("memory_ingest_duration_seconds", 1);
//! ```
use std::collections::HashMap;
use std::sync::atomic::Ordering;
use crate::metrics;
/// Snapshot of all metric values at a point in time
#[derive(Debug, Clone)]
pub struct MetricsSnapshot {
counters: HashMap<&'static str, u64>,
gauges: HashMap<&'static str, u64>,
gauges_f64: HashMap<&'static str, f64>,
histogram_counts: HashMap<&'static str, u64>,
}
impl MetricsSnapshot {
/// Capture current state of all metrics
pub fn capture() -> Self {
let mut counters = HashMap::new();
let mut gauges = HashMap::new();
let mut gauges_f64 = HashMap::new();
let mut histogram_counts = HashMap::new();
// O1: Ingest counters
counters.insert("memory_ingest_requests_total", metrics::INGEST_REQUESTS_TOTAL.get());
counters.insert("memory_ingest_errors_total", metrics::INGEST_ERRORS_TOTAL.get());
counters.insert("memory_ingest_records_total", metrics::INGEST_RECORDS_TOTAL.get());
counters.insert("memory_ingest_entities_extracted_total", metrics::INGEST_ENTITIES_EXTRACTED.get());
counters.insert("memory_ingest_edges_extracted_total", metrics::INGEST_EDGES_EXTRACTED.get());
counters.insert("memory_ingest_duplicates_total", metrics::INGEST_DUPLICATES_TOTAL.get());
counters.insert("memory_ingest_bytes_total", metrics::INGEST_BYTES_TOTAL.get());
counters.insert("memory_ingest_auth_failures_total", metrics::INGEST_AUTH_FAILURES.get());
counters.insert("memory_ingest_rate_limited_total", metrics::INGEST_RATE_LIMITED.get());
// O1: Ingest gauges
gauges.insert("memory_ingest_in_flight", metrics::INGEST_IN_FLIGHT.get());
gauges.insert("memory_ingest_queue_size", metrics::INGEST_QUEUE_SIZE.get());
// O1: Ingest histogram (force Lazy init)
histogram_counts.insert("memory_ingest_duration_seconds",
{ let _ = &*metrics::INGEST_DURATION; metrics::INGEST_DURATION.count.load(Ordering::Relaxed) });
// O2: Query counters
counters.insert("memory_query_requests_total", metrics::QUERY_REQUESTS_TOTAL.get());
counters.insert("memory_query_errors_total", metrics::QUERY_ERRORS_TOTAL.get());
counters.insert("memory_query_results_total", metrics::QUERY_RESULTS_TOTAL.get());
counters.insert("memory_query_empty_results_total", metrics::QUERY_EMPTY_RESULTS.get());
counters.insert("memory_query_embedding_failures_total", metrics::QUERY_EMBEDDING_FAILURES.get());
counters.insert("memory_query_auth_failures_total", metrics::QUERY_AUTH_FAILURES.get());
counters.insert("memory_query_rate_limited_total", metrics::QUERY_RATE_LIMITED.get());
counters.insert("memory_query_cache_hits_total", metrics::QUERY_CACHE_HITS.get());
counters.insert("memory_query_cache_misses_total", metrics::QUERY_CACHE_MISSES.get());
// O2: Query gauges
gauges.insert("memory_query_in_flight", metrics::QUERY_IN_FLIGHT.get());
// O2: Query histograms
histogram_counts.insert("memory_query_duration_seconds",
{ let _ = &*metrics::QUERY_DURATION; metrics::QUERY_DURATION.count.load(Ordering::Relaxed) });
histogram_counts.insert("memory_query_embedding_duration_seconds",
{ let _ = &*metrics::QUERY_EMBEDDING_DURATION; metrics::QUERY_EMBEDDING_DURATION.count.load(Ordering::Relaxed) });
// O3: Context
counters.insert("memory_context_requests_total", metrics::CONTEXT_REQUESTS_TOTAL.get());
counters.insert("memory_context_errors_total", metrics::CONTEXT_ERRORS_TOTAL.get());
counters.insert("memory_context_semantic_hits_total", metrics::CONTEXT_SEMANTIC_HITS.get());
counters.insert("memory_context_bm25_hits_total", metrics::CONTEXT_BM25_HITS.get());
counters.insert("memory_context_graph_hits_total", metrics::CONTEXT_GRAPH_HITS.get());
counters.insert("memory_context_empty_results_total", metrics::CONTEXT_EMPTY_RESULTS.get());
histogram_counts.insert("memory_context_duration_seconds",
{ let _ = &*metrics::CONTEXT_DURATION; metrics::CONTEXT_DURATION.count.load(Ordering::Relaxed) });
// O4: Relevance histograms
histogram_counts.insert("memory_relevance_eval_duration_seconds",
{ let _ = &*metrics::RELEVANCE_EVAL_DURATION; metrics::RELEVANCE_EVAL_DURATION.count.load(Ordering::Relaxed) });
// O5: Write histogram
histogram_counts.insert("memory_write_duration_seconds",
{ let _ = &*metrics::WRITE_DURATION; metrics::WRITE_DURATION.count.load(Ordering::Relaxed) });
// O7: Dependency latency
histogram_counts.insert("memory_dependency_db_latency_seconds",
{ let _ = &*metrics::DEP_DB_LATENCY; metrics::DEP_DB_LATENCY.count.load(Ordering::Relaxed) });
// O4: Relevance
counters.insert("memory_relevance_evals_total", metrics::RELEVANCE_EVALS_TOTAL.get());
counters.insert("memory_relevance_errors_total", metrics::RELEVANCE_ERRORS_TOTAL.get());
counters.insert("memory_relevance_relevant_total", metrics::RELEVANCE_RELEVANT_TOTAL.get());
counters.insert("memory_relevance_irrelevant_total", metrics::RELEVANCE_IRRELEVANT_TOTAL.get());
gauges_f64.insert("memory_relevance_precision", metrics::RELEVANCE_PRECISION.get());
gauges_f64.insert("memory_relevance_recall", metrics::RELEVANCE_RECALL.get());
gauges_f64.insert("memory_relevance_f1_score", metrics::RELEVANCE_F1.get());
// O5: Write
counters.insert("memory_write_entities_total", metrics::WRITE_ENTITIES_TOTAL.get());
counters.insert("memory_write_edges_total", metrics::WRITE_EDGES_TOTAL.get());
counters.insert("memory_write_chunks_total", metrics::WRITE_CHUNKS_TOTAL.get());
counters.insert("memory_write_errors_total", metrics::WRITE_ERRORS_TOTAL.get());
counters.insert("memory_write_bytes_total", metrics::WRITE_BYTES_TOTAL.get());
// O7: Health
counters.insert("memory_health_checks_total", metrics::HEALTH_CHECKS_TOTAL.get());
counters.insert("memory_health_check_failures_total", metrics::HEALTH_CHECK_FAILURES.get());
gauges.insert("memory_dependency_db_up", metrics::DEP_DB_UP.get());
gauges.insert("memory_dependency_embedding_up", metrics::DEP_EMBEDDING_UP.get());
// O8: Ingest rate
counters.insert("memory_ingest_dedup_total", metrics::INGEST_DEDUP_TOTAL.get());
counters.insert("memory_ingest_contradiction_total", metrics::INGEST_CONTRADICTION_TOTAL.get());
// O9: DB
counters.insert("memory_db_queries_total", metrics::DB_QUERY_TOTAL.get());
counters.insert("memory_db_query_errors_total", metrics::DB_QUERY_ERRORS.get());
Self { counters, gauges, gauges_f64, histogram_counts }
}
/// Assert a counter increased by exactly `expected` since snapshot
pub fn assert_counter_inc(&self, name: &str, expected: u64) {
let before = self.counters.get(name)
.unwrap_or_else(|| panic!("Unknown counter: {}", name));
let after = Self::get_current_counter(name);
let delta = after - before;
assert_eq!(delta, expected,
"Counter {} expected +{} but got +{} (before={}, after={})",
name, expected, delta, before, after);
}
/// Assert a counter increased by at least `min` since snapshot
pub fn assert_counter_inc_at_least(&self, name: &str, min: u64) {
let before = self.counters.get(name)
.unwrap_or_else(|| panic!("Unknown counter: {}", name));
let after = Self::get_current_counter(name);
let delta = after - before;
assert!(delta >= min,
"Counter {} expected at least +{} but got +{} (before={}, after={})",
name, min, delta, before, after);
}
/// Assert a gauge equals exactly `expected`
pub fn assert_gauge_eq(&self, name: &str, expected: u64) {
let current = Self::get_current_gauge(name);
assert_eq!(current, expected,
"Gauge {} expected {} but got {}", name, expected, current);
}
/// Assert a histogram observation count increased by `expected`
pub fn assert_histogram_count_inc(&self, name: &str, expected: u64) {
let before = self.histogram_counts.get(name)
.unwrap_or_else(|| panic!("Unknown histogram: {}", name));
let after = Self::get_current_histogram_count(name);
let delta = after - before;
assert_eq!(delta, expected,
"Histogram {} count expected +{} but got +{} (before={}, after={})",
name, expected, delta, before, after);
}
/// Assert a f64 gauge is within tolerance
pub fn assert_gauge_f64_approx(&self, name: &str, expected: f64, tolerance: f64) {
let current = Self::get_current_gauge_f64(name);
assert!((current - expected).abs() <= tolerance,
"Gauge {} expected {:.4} (±{}) but got {:.4}",
name, expected, tolerance, current);
}
/// Get delta for a counter since snapshot
pub fn counter_delta(&self, name: &str) -> u64 {
let before = self.counters.get(name).copied().unwrap_or(0);
let after = Self::get_current_counter(name);
after - before
}
/// Print all deltas since snapshot (for debugging)
pub fn print_deltas(&self) {
println!("=== Metrics Deltas ===");
for (name, before) in &self.counters {
let after = Self::get_current_counter(name);
let delta = after - before;
if delta > 0 {
println!(" {} +{} ({} -> {})", name, delta, before, after);
}
}
for (name, before) in &self.histogram_counts {
let after = Self::get_current_histogram_count(name);
let delta = after - before;
if delta > 0 {
println!(" {} count +{}", name, delta);
}
}
}
// ─── Internal helpers ───────────────────────────────────
fn get_current_counter(name: &str) -> u64 {
match name {
"memory_ingest_requests_total" => metrics::INGEST_REQUESTS_TOTAL.get(),
"memory_ingest_errors_total" => metrics::INGEST_ERRORS_TOTAL.get(),
"memory_ingest_records_total" => metrics::INGEST_RECORDS_TOTAL.get(),
"memory_ingest_entities_extracted_total" => metrics::INGEST_ENTITIES_EXTRACTED.get(),
"memory_ingest_edges_extracted_total" => metrics::INGEST_EDGES_EXTRACTED.get(),
"memory_ingest_duplicates_total" => metrics::INGEST_DUPLICATES_TOTAL.get(),
"memory_ingest_bytes_total" => metrics::INGEST_BYTES_TOTAL.get(),
"memory_ingest_auth_failures_total" => metrics::INGEST_AUTH_FAILURES.get(),
"memory_ingest_rate_limited_total" => metrics::INGEST_RATE_LIMITED.get(),
"memory_query_requests_total" => metrics::QUERY_REQUESTS_TOTAL.get(),
"memory_query_errors_total" => metrics::QUERY_ERRORS_TOTAL.get(),
"memory_query_results_total" => metrics::QUERY_RESULTS_TOTAL.get(),
"memory_query_empty_results_total" => metrics::QUERY_EMPTY_RESULTS.get(),
"memory_query_embedding_failures_total" => metrics::QUERY_EMBEDDING_FAILURES.get(),
"memory_query_auth_failures_total" => metrics::QUERY_AUTH_FAILURES.get(),
"memory_query_rate_limited_total" => metrics::QUERY_RATE_LIMITED.get(),
"memory_query_cache_hits_total" => metrics::QUERY_CACHE_HITS.get(),
"memory_query_cache_misses_total" => metrics::QUERY_CACHE_MISSES.get(),
"memory_context_requests_total" => metrics::CONTEXT_REQUESTS_TOTAL.get(),
"memory_context_errors_total" => metrics::CONTEXT_ERRORS_TOTAL.get(),
"memory_context_semantic_hits_total" => metrics::CONTEXT_SEMANTIC_HITS.get(),
"memory_context_bm25_hits_total" => metrics::CONTEXT_BM25_HITS.get(),
"memory_context_graph_hits_total" => metrics::CONTEXT_GRAPH_HITS.get(),
"memory_context_empty_results_total" => metrics::CONTEXT_EMPTY_RESULTS.get(),
"memory_relevance_evals_total" => metrics::RELEVANCE_EVALS_TOTAL.get(),
"memory_relevance_errors_total" => metrics::RELEVANCE_ERRORS_TOTAL.get(),
"memory_relevance_relevant_total" => metrics::RELEVANCE_RELEVANT_TOTAL.get(),
"memory_relevance_irrelevant_total" => metrics::RELEVANCE_IRRELEVANT_TOTAL.get(),
"memory_write_entities_total" => metrics::WRITE_ENTITIES_TOTAL.get(),
"memory_write_edges_total" => metrics::WRITE_EDGES_TOTAL.get(),
"memory_write_chunks_total" => metrics::WRITE_CHUNKS_TOTAL.get(),
"memory_write_errors_total" => metrics::WRITE_ERRORS_TOTAL.get(),
"memory_write_bytes_total" => metrics::WRITE_BYTES_TOTAL.get(),
"memory_health_checks_total" => metrics::HEALTH_CHECKS_TOTAL.get(),
"memory_health_check_failures_total" => metrics::HEALTH_CHECK_FAILURES.get(),
"memory_ingest_dedup_total" => metrics::INGEST_DEDUP_TOTAL.get(),
"memory_ingest_contradiction_total" => metrics::INGEST_CONTRADICTION_TOTAL.get(),
"memory_db_queries_total" => metrics::DB_QUERY_TOTAL.get(),
"memory_db_query_errors_total" => metrics::DB_QUERY_ERRORS.get(),
_ => panic!("Unknown counter: {}", name),
}
}
fn get_current_gauge(name: &str) -> u64 {
match name {
"memory_ingest_in_flight" => metrics::INGEST_IN_FLIGHT.get(),
"memory_ingest_queue_size" => metrics::INGEST_QUEUE_SIZE.get(),
"memory_query_in_flight" => metrics::QUERY_IN_FLIGHT.get(),
"memory_dependency_db_up" => metrics::DEP_DB_UP.get(),
"memory_dependency_embedding_up" => metrics::DEP_EMBEDDING_UP.get(),
"memory_dependency_opensearch_up" => metrics::DEP_OPENSEARCH_UP.get(),
"memory_dependency_llm_up" => metrics::DEP_LLM_UP.get(),
"memory_app_uptime_seconds" => metrics::APP_UPTIME_SECONDS.get(),
"memory_db_pool_size" => metrics::DB_POOL_SIZE.get(),
"memory_db_pool_idle" => metrics::DB_POOL_IDLE.get(),
"memory_db_table_entity_rows" => metrics::DB_TABLE_ENTITY_ROWS.get(),
"memory_db_table_edge_rows" => metrics::DB_TABLE_EDGE_ROWS.get(),
"memory_db_table_chunk_rows" => metrics::DB_TABLE_CHUNK_ROWS.get(),
_ => panic!("Unknown gauge: {}", name),
}
}
fn get_current_gauge_f64(name: &str) -> f64 {
match name {
"memory_relevance_precision" => metrics::RELEVANCE_PRECISION.get(),
"memory_relevance_recall" => metrics::RELEVANCE_RECALL.get(),
"memory_relevance_f1_score" => metrics::RELEVANCE_F1.get(),
"memory_ingest_rate_1m" => metrics::INGEST_RATE_1M.get(),
"memory_ingest_rate_5m" => metrics::INGEST_RATE_5M.get(),
_ => panic!("Unknown gauge_f64: {}", name),
}
}
fn get_current_histogram_count(name: &str) -> u64 {
match name {
"memory_ingest_duration_seconds" =>
metrics::INGEST_DURATION.count.load(Ordering::Relaxed),
"memory_query_duration_seconds" =>
metrics::QUERY_DURATION.count.load(Ordering::Relaxed),
"memory_query_embedding_duration_seconds" =>
metrics::QUERY_EMBEDDING_DURATION.count.load(Ordering::Relaxed),
"memory_context_duration_seconds" =>
metrics::CONTEXT_DURATION.count.load(Ordering::Relaxed),
"memory_relevance_eval_duration_seconds" =>
metrics::RELEVANCE_EVAL_DURATION.count.load(Ordering::Relaxed),
"memory_write_duration_seconds" => {
// Force Lazy init
let _ = &*metrics::WRITE_DURATION;
metrics::WRITE_DURATION.count.load(Ordering::Relaxed)
}
"memory_dependency_db_latency_seconds" => {
let _ = &*metrics::DEP_DB_LATENCY;
metrics::DEP_DB_LATENCY.count.load(Ordering::Relaxed)
}
_ => panic!("Unknown histogram: {}", name),
}
}
}
#[cfg(test)]
mod tests {
use super::*;
use crate::relevance_judge::RelevanceJudge;
#[test]
fn test_snapshot_captures_state() {
let snap = MetricsSnapshot::capture();
assert!(snap.counters.contains_key("memory_ingest_requests_total"));
assert!(snap.counters.contains_key("memory_query_requests_total"));
assert!(snap.gauges.contains_key("memory_ingest_in_flight"));
assert!(snap.histogram_counts.contains_key("memory_ingest_duration_seconds"));
}
#[test]
fn test_counter_delta_zero_when_no_change() {
let snap = MetricsSnapshot::capture();
snap.assert_counter_inc("memory_write_entities_total", 0);
}
#[test]
fn test_counter_tracks_increment() {
let snap = MetricsSnapshot::capture();
metrics::WRITE_ENTITIES_TOTAL.inc_by(3);
snap.assert_counter_inc("memory_write_entities_total", 3);
}
#[test]
fn test_counter_delta_method() {
let snap = MetricsSnapshot::capture();
metrics::WRITE_EDGES_TOTAL.inc_by(7);
assert_eq!(snap.counter_delta("memory_write_edges_total"), 7);
}
#[test]
fn test_histogram_count_tracks() {
let snap = MetricsSnapshot::capture();
metrics::WRITE_DURATION.observe(0.05);
metrics::WRITE_DURATION.observe(0.10);
snap.assert_histogram_count_inc("memory_write_duration_seconds", 2);
}
#[test]
fn test_relevance_scenario_metrics() {
let snap = MetricsSnapshot::capture();
let judge = RelevanceJudge::new(0.5);
let results = vec![
("good result".to_string(), 0.9),
("bad result".to_string(), 0.1),
("ok result".to_string(), 0.6),
];
let summary = judge.evaluate_batch("test query", &results);
// Verify metrics match scenario
snap.assert_counter_inc("memory_relevance_evals_total", 3);
snap.assert_counter_inc("memory_relevance_relevant_total", 2); // 0.9 + 0.6
snap.assert_counter_inc("memory_relevance_irrelevant_total", 1); // 0.1
// Verify precision gauge
snap.assert_gauge_f64_approx("memory_relevance_precision", summary.precision, 0.01);
assert_eq!(summary.total, 3);
assert_eq!(summary.relevant, 2);
}
#[test]
fn test_ingest_counter_scenario() {
let snap = MetricsSnapshot::capture();
// Simulate ingest scenario
metrics::INGEST_REQUESTS_TOTAL.inc();
metrics::INGEST_RECORDS_TOTAL.inc_by(5);
metrics::INGEST_BYTES_TOTAL.inc_by(1024);
metrics::INGEST_ENTITIES_EXTRACTED.inc_by(3);
metrics::INGEST_EDGES_EXTRACTED.inc_by(2);
snap.assert_counter_inc("memory_ingest_requests_total", 1);
snap.assert_counter_inc("memory_ingest_records_total", 5);
snap.assert_counter_inc("memory_ingest_bytes_total", 1024);
snap.assert_counter_inc("memory_ingest_entities_extracted_total", 3);
snap.assert_counter_inc("memory_ingest_edges_extracted_total", 2);
snap.assert_counter_inc("memory_ingest_errors_total", 0);
}
#[test]
fn test_query_error_scenario() {
let snap = MetricsSnapshot::capture();
// Simulate query that fails at embedding
metrics::QUERY_REQUESTS_TOTAL.inc();
metrics::QUERY_IN_FLIGHT.inc();
metrics::QUERY_EMBEDDING_FAILURES.inc();
metrics::QUERY_ERRORS_TOTAL.inc();
metrics::QUERY_IN_FLIGHT.dec();
snap.assert_counter_inc("memory_query_requests_total", 1);
snap.assert_counter_inc("memory_query_embedding_failures_total", 1);
snap.assert_counter_inc("memory_query_errors_total", 1);
snap.assert_counter_inc("memory_query_results_total", 0);
snap.assert_gauge_eq("memory_query_in_flight", 0);
}
#[test]
fn test_print_deltas_works() {
let snap = MetricsSnapshot::capture();
metrics::HEALTH_CHECKS_TOTAL.inc();
snap.print_deltas(); // Should not panic
}
}
-11
View File
@@ -238,17 +238,6 @@ impl QueryRouter {
let latency_ms = start.elapsed().as_millis() as u64;
tracing::info!(
target: "observability",
event = "query_route",
route = "direct",
candidates = all_candidates.len(),
prefiltered = prefilter_size,
selected = selected_chunks.len(),
latency_ms = latency_ms,
"Query routing complete"
);
Ok(RoutedResult {
selected_chunks,
route,
-161
View File
@@ -1,161 +0,0 @@
//! Relevance Judge (O4)
//!
//! Evaluates retrieval quality by scoring query-result relevance.
//! Uses LLM (Qwen-7B or similar) to judge if retrieved results are relevant.
//! Tracks precision, recall, F1 via Prometheus metrics.
use anyhow::Result;
use serde::{Deserialize, Serialize};
use tracing::{debug, error};
use crate::metrics;
/// Relevance evaluation result for a single query-result pair
#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct RelevanceResult {
pub query: String,
pub result_text: String,
pub score: f64,
pub relevant: bool,
}
/// Batch evaluation summary
#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct RelevanceSummary {
pub total: usize,
pub relevant: usize,
pub irrelevant: usize,
pub precision: f64,
pub recall: f64,
pub f1: f64,
pub avg_score: f64,
}
/// Simple relevance judge using cosine similarity threshold
/// (LLM-based judge can be plugged in later via trait)
pub struct RelevanceJudge {
threshold: f64,
}
impl RelevanceJudge {
pub fn new(threshold: f64) -> Self {
Self { threshold }
}
/// Evaluate a single query-result pair using similarity score
pub fn evaluate(&self, query: &str, result_text: &str, similarity: f64) -> RelevanceResult {
let start = std::time::Instant::now();
metrics::RELEVANCE_EVALS_TOTAL.inc();
let relevant = similarity >= self.threshold;
if relevant {
metrics::RELEVANCE_RELEVANT_TOTAL.inc();
} else {
metrics::RELEVANCE_IRRELEVANT_TOTAL.inc();
}
metrics::RELEVANCE_SCORE.observe(similarity);
metrics::RELEVANCE_EVAL_DURATION.observe(start.elapsed().as_secs_f64());
debug!("Relevance eval: query='{}', score={:.3}, relevant={}",
&query[..query.len().min(50)], similarity, relevant);
RelevanceResult {
query: query.to_string(),
result_text: result_text.to_string(),
score: similarity,
relevant,
}
}
/// Evaluate a batch of results and compute summary metrics
pub fn evaluate_batch(
&self,
query: &str,
results: &[(String, f64)], // (result_text, similarity_score)
) -> RelevanceSummary {
let mut relevant_count = 0;
let mut total_score = 0.0;
for (text, score) in results {
let result = self.evaluate(query, text, *score);
if result.relevant {
relevant_count += 1;
}
total_score += score;
}
let total = results.len();
let irrelevant = total - relevant_count;
let precision = if total > 0 { relevant_count as f64 / total as f64 } else { 0.0 };
// Recall requires knowing total relevant docs; approximate as precision for now
let recall = precision;
let f1 = if precision + recall > 0.0 {
2.0 * precision * recall / (precision + recall)
} else {
0.0
};
let avg_score = if total > 0 { total_score / total as f64 } else { 0.0 };
// Update gauge metrics
metrics::RELEVANCE_PRECISION.set(precision);
metrics::RELEVANCE_RECALL.set(recall);
metrics::RELEVANCE_F1.set(f1);
RelevanceSummary {
total,
relevant: relevant_count,
irrelevant,
precision,
recall,
f1,
avg_score,
}
}
}
#[cfg(test)]
mod tests {
use super::*;
#[test]
fn test_relevance_judge_above_threshold() {
let judge = RelevanceJudge::new(0.5);
let result = judge.evaluate("test query", "test result", 0.8);
assert!(result.relevant);
assert!((result.score - 0.8).abs() < 0.001);
}
#[test]
fn test_relevance_judge_below_threshold() {
let judge = RelevanceJudge::new(0.5);
let result = judge.evaluate("test query", "test result", 0.3);
assert!(!result.relevant);
}
#[test]
fn test_relevance_batch() {
let judge = RelevanceJudge::new(0.5);
let results = vec![
("relevant result".to_string(), 0.8),
("somewhat relevant".to_string(), 0.6),
("irrelevant".to_string(), 0.2),
];
let summary = judge.evaluate_batch("test", &results);
assert_eq!(summary.total, 3);
assert_eq!(summary.relevant, 2);
assert_eq!(summary.irrelevant, 1);
assert!((summary.precision - 0.6667).abs() < 0.01);
}
#[test]
fn test_relevance_empty_batch() {
let judge = RelevanceJudge::new(0.5);
let summary = judge.evaluate_batch("test", &[]);
assert_eq!(summary.total, 0);
assert_eq!(summary.precision, 0.0);
assert_eq!(summary.f1, 0.0);
}
}
-12
View File
@@ -235,18 +235,6 @@ impl BudgetCompressor {
let strategy = self.select_strategy(estimated);
let compressed = self.compressor.compress_batch(results, strategy);
let compressed_size: usize = compressed.iter().map(|c| c.text.as_ref().map_or(0, |t| t.len())).sum();
tracing::info!(
target: "observability",
event = "result_compress",
input_count = compressed.len(),
estimated_bytes = estimated,
compressed_bytes = compressed_size,
budget_bytes = self.max_budget_bytes,
strategy = ?strategy,
"Result compression complete"
);
(compressed, strategy)
}
}
-1
View File
@@ -2,7 +2,6 @@
///
/// These structures attach to Entity via entity_type discriminator.
/// AgentPrompt, AgentSkill, AgentDecision each carry domain-specific
#[allow(clippy::empty_line_after_doc_comments)]
/// fields that enable the agent to learn from its own behavior.
use serde::{Deserialize, Serialize};
-1
View File
@@ -1,6 +1,5 @@
/// Community domain model for temporal graph-RAG.
/// Single Responsibility: Community (cluster) storage and metadata.
#[allow(clippy::empty_line_after_doc_comments)]
/// Open/Closed: Algorithm field extensible for new clustering methods.
use serde::{Deserialize, Serialize};
-2
View File
@@ -1,6 +1,5 @@
/// Edge domain model for temporal graph-RAG.
/// Single Responsibility: Fact/relationship storage with bi-temporal validity.
#[allow(clippy::empty_line_after_doc_comments)]
/// Open/Closed: ContradictionStatus enum extensible.
use serde::{Deserialize, Serialize};
@@ -30,7 +29,6 @@ impl ContradictionStatus {
}
}
#[allow(clippy::should_implement_trait)]
pub fn from_str(s: &str) -> Self {
match s.to_lowercase().as_str() {
"active" => Self::Active,
+1 -13
View File
@@ -1,7 +1,6 @@
/// Entity domain model for temporal graph-RAG.
/// Single Responsibility: Entity identity and metadata.
/// Open/Closed: EntityType enum extensible.
#[allow(clippy::empty_line_after_doc_comments)]
/// Dependencies: Uses time::OffsetDateTime (consistent with mem-core).
use serde::{Deserialize, Serialize};
@@ -9,7 +8,7 @@ use time::OffsetDateTime;
use std::fmt;
/// Entity type classification (extensible enum).
#[derive(Debug, Clone, Copy, PartialEq, Eq, Serialize, Hash)]
#[derive(Debug, Clone, Copy, PartialEq, Eq, Serialize, Deserialize, Hash)]
#[serde(rename_all = "snake_case")]
pub enum EntityType {
Person,
@@ -44,7 +43,6 @@ impl EntityType {
}
}
#[allow(clippy::should_implement_trait)]
pub fn from_str(s: &str) -> Self {
match s.to_lowercase().as_str() {
"person" => Self::Person,
@@ -61,16 +59,6 @@ impl EntityType {
}
}
impl<'de> serde::Deserialize<'de> for EntityType {
fn deserialize<D>(deserializer: D) -> Result<Self, D::Error>
where
D: serde::Deserializer<'de>,
{
let s = String::deserialize(deserializer)?;
Ok(Self::from_str(&s))
}
}
impl fmt::Display for EntityType {
fn fmt(&self, f: &mut fmt::Formatter<'_>) -> fmt::Result {
write!(f, "{}", self.as_str())
+2 -1
View File
@@ -135,10 +135,11 @@ pub fn run_loop(
#[cfg(test)]
mod tests {
use super::*;
#[test]
fn test_loop_basic() {
// Placeholder test to verify it compiles
assert!(true);
}
}
+7 -7
View File
@@ -403,7 +403,7 @@ pub fn lookup(sig: &Signature, lessons: &[Lesson], floor: f32) -> Option<Hit> {
let mut best: Option<(f32, &Lesson)> = None;
for l in lessons.iter().filter(|l| l.tool == sig.tool) {
let s = similarity(&sig.normalised, &l.normalised);
if s >= floor && best.is_none_or(|(bs, _)| s > bs) {
if s >= floor && best.map_or(true, |(bs, _)| s > bs) {
best = Some((s, l));
}
}
@@ -503,7 +503,7 @@ pub fn tool_of_cmd(cmd: &str) -> String {
"kubectl" | "k" => "kubectl".into(),
"docker" | "podman" => "docker".into(),
"terraform" | "tofu" => "terraform".into(),
"" => "unknown".into(),
other if other.is_empty() => "unknown".into(),
other => other.to_string(),
}
}
@@ -549,7 +549,7 @@ pub fn render_skill(tool: &str, lessons: &[Lesson]) -> String {
s.push_str("`confirmed`, which outranks inferred lessons at equal similarity.\n\n");
let mut sorted: Vec<&Lesson> = lessons.iter().collect();
sorted.sort_by_key(|a| std::cmp::Reverse(a.seen));
sorted.sort_by(|a, b| b.seen.cmp(&a.seen));
for l in sorted {
s.push_str(&format!("## {}\n\n", l.raw.trim()));
@@ -557,7 +557,7 @@ pub fn render_skill(tool: &str, lessons: &[Lesson]) -> String {
"- seen: {} | last: {} | confidence: {:?}\n",
l.seen, l.last_seen, l.confidence
));
s.push_str(&format!("- signature: `{}`\n", &l.sig_sha[..12]));
s.push_str(&format!("- signature: `{}`\n", l.sig_sha[..12].to_string()));
s.push_str("- resolved by:\n");
for r in &l.resolution {
s.push_str(&format!(" ```\n {r}\n ```\n"));
@@ -712,7 +712,7 @@ mod tests {
ev("t2", "npm pkg set overrides.react=19", 0, ""),
ev("t3", "npm ci", 0, "ok"),
];
let ls = derive_lessons(&events, tool_of_cmd);
let ls = derive_lessons(&events, |c| tool_of_cmd(c));
assert_eq!(ls.len(), 1);
assert_eq!(ls[0].resolution, vec!["npm pkg set overrides.react=19"]);
assert_eq!(ls[0].confidence, Confidence::Inferred);
@@ -775,7 +775,7 @@ mod tests {
output: "error: flaky".into(),
};
let events = vec![ev("npm ci", 1), ev("npm ci", 0)];
assert!(derive_lessons(&events, tool_of_cmd).is_empty());
assert!(derive_lessons(&events, |c| tool_of_cmd(c)).is_empty());
}
#[test]
@@ -798,7 +798,7 @@ mod tests {
sig_sha: "abc".into(),
rule: "r".into(),
};
assert_eq!(lookup(&exact, std::slice::from_ref(&l), 0.5).unwrap().tier, Tier::Exact);
assert_eq!(lookup(&exact, &[l.clone()], 0.5).unwrap().tier, Tier::Exact);
let unrelated = Signature {
tool: "npm".into(),
+2 -2
View File
@@ -152,11 +152,11 @@ impl FormatHandler for CsvFormatter {
async fn format(&self, result: &OptimizationResult) -> Result<Vec<u8>, String> {
let output = format!(
"{},{},{},{:.2}\n",
"{},{},{},{}\n",
escape_csv(&result.plugin),
result.original.len(),
result.optimized.len(),
result.ratio
format!("{:.2}", result.ratio)
);
Ok(output.into_bytes())
}
+2 -2
View File
@@ -40,7 +40,7 @@ impl CcrStore {
// Remove oldest entry if at capacity
if cache.len() >= self.max_entries {
if let Some(oldest_key) = cache.keys().next().cloned() {
cache.swap_remove(&oldest_key);
cache.remove(&oldest_key);
}
}
@@ -57,7 +57,7 @@ impl CcrStore {
// Check if expired
let duration = OffsetDateTime::now_utc() - *timestamp;
if duration.whole_seconds() > self.ttl_secs as i64 {
cache.swap_remove(hash);
cache.remove(hash);
return Ok(None);
}
+5 -5
View File
@@ -7,7 +7,7 @@
//! - Drop: redundant homogeneous elements, long string values
use anyhow::Result;
use serde_json::Value;
use serde_json::{json, Value};
use std::collections::HashMap;
pub struct JsonCrusher;
@@ -45,8 +45,8 @@ impl JsonCrusher {
let mut result = Vec::new();
// Add start items
for item in items.iter().take(start_count.min(len)) {
result.push(item.clone());
for i in 0..start_count.min(len) {
result.push(items[i].clone());
}
// Select mid-array items by variance/importance
@@ -58,8 +58,8 @@ impl JsonCrusher {
// Add end items
if end_count > 0 {
for item in items.iter().skip(len.saturating_sub(end_count)) {
result.push(item.clone());
for i in (len - end_count)..len {
result.push(items[i].clone());
}
}
@@ -5,7 +5,7 @@
use super::plugin::OptimizerService;
use crate::prompt::CacheMetrics;
use crate::domain::Chunk;
use crate::domain::{Chunk, Record};
use anyhow::Result;
/// Query optimizer: compresses chunks before LLM processing
@@ -83,7 +83,7 @@ impl QueryOptimizer {
match service.optimize(&chunk_text, &content_type, Some("raw")).await {
Ok(bytes) => {
let text = String::from_utf8(bytes)
.unwrap_or(chunk_text);
.unwrap_or_else(|_| chunk_text);
Ok(text)
}
Err(_) => {
+1 -1
View File
@@ -42,7 +42,7 @@ impl ContentRouter {
/// Check if content is valid JSON
fn is_json(content: &str) -> bool {
let trimmed = content.trim();
if !(trimmed.starts_with('{') || trimmed.starts_with('[')) {
if !((trimmed.starts_with('{') || trimmed.starts_with('['))) {
return false;
}
serde_json::from_str::<serde_json::Value>(trimmed).is_ok()
+1 -1
View File
@@ -128,7 +128,7 @@ impl TextCompressor {
}
// Capitalization (usually proper nouns or emphatic)
if token.chars().next().is_some_and(|c| c.is_uppercase()) && token.len() > 1 {
if token.chars().next().map_or(false, |c| c.is_uppercase()) && token.len() > 1 {
score += 1.0;
}
+2 -4
View File
@@ -12,9 +12,7 @@ const CACHE_TURN: &str = include_str!("../../../templates/gru-mem-turn.txt");
const BUDGET_TOTAL: usize = 32768;
const BUDGET_RESPONSE: usize = 2048;
#[allow(dead_code)]
const BUDGET_SYSTEM: usize = 400;
#[allow(dead_code)]
const BUDGET_QUESTION: usize = 150;
const BUDGET_MEMORY_MAX: usize = 1024;
const BUDGET_CHUNK_MAX: usize = 5000;
@@ -370,7 +368,7 @@ fn estimate_tokens(text: &str) -> usize {
#[cfg(test)]
mod tests {
use super::*;
use crate::domain::{Chunk, Record, Role, Provenance};
use crate::domain::{Chunk, Record, Role, Provenance, Level};
use time::OffsetDateTime;
fn make_test_chunk(text: &str) -> Chunk {
@@ -647,7 +645,7 @@ mod tests {
let metrics = result.unwrap();
let ratio = metrics.compression_ratio();
assert!((0.0..=100.0).contains(&ratio));
assert!(ratio >= 0.0 && ratio <= 100.0);
}
#[test]
+2
View File
@@ -1,5 +1,7 @@
use crate::domain::{ProjectId, QueryId};
use anyhow::{anyhow, Result};
use serde::{Deserialize, Serialize};
use std::collections::HashMap;
use std::path::Path;
/// A single standing query.
+1 -7
View File
@@ -1,4 +1,4 @@
use crate::Level;
use crate::{Level, Query};
use anyhow::Result;
use serde::{Deserialize, Serialize};
@@ -17,12 +17,6 @@ pub struct QueryExecutor {
// For now: proof-of-concept with mock data
}
impl Default for QueryExecutor {
fn default() -> Self {
Self::new()
}
}
impl QueryExecutor {
/// Create executor.
pub fn new() -> Self {
+3 -2
View File
@@ -71,10 +71,11 @@ impl QueryLevels {
}
// Check level filter
if !self.level_filter.is_empty()
&& !self.level_filter.contains(&level.to_string()) {
if !self.level_filter.is_empty() {
if !self.level_filter.contains(&level.to_string()) {
return false;
}
}
// Check evidence/reference flags
if level == "R" {
-15
View File
@@ -6,7 +6,6 @@
/// - Single Responsibility: each scorer does one thing
/// - Open/Closed: add new scorers without modifying existing
/// - Liskov Substitution: all scorers implement DocumentScorer
#[allow(clippy::empty_line_after_doc_comments)]
/// - Dependency Inversion: depend on trait, not concrete types
use anyhow::Result;
@@ -54,7 +53,6 @@ impl DocumentScorer for GlobalTfIdfScorer {
}
/// Project-scoped TF-IDF Scorer: scoring within project boundaries
#[allow(dead_code)]
pub struct ProjectTfIdfScorer {
project: String,
vocabulary: Arc<std::collections::BTreeMap<String, f32>>,
@@ -95,18 +93,11 @@ impl DocumentScorer for ProjectTfIdfScorer {
}
/// Semantic Scorer: vector similarity (placeholder)
#[allow(dead_code)]
pub struct SemanticScorer {
_embeddings_client: Arc<()>, // Placeholder
_pgvector: Arc<()>, // Placeholder
}
impl Default for SemanticScorer {
fn default() -> Self {
Self::new()
}
}
impl SemanticScorer {
pub fn new() -> Self {
Self {
@@ -165,12 +156,6 @@ pub struct ScoringPipeline {
scorers: Vec<(String, f32, Arc<dyn DocumentScorer>)>, // name, weight, scorer
}
impl Default for ScoringPipeline {
fn default() -> Self {
Self::new()
}
}
impl ScoringPipeline {
pub fn new() -> Self {
Self {
+1 -2
View File
@@ -81,7 +81,6 @@ impl SymptomVector {
/// Internal structure for tokens during extraction
#[derive(Debug, Clone)]
#[allow(dead_code)]
struct SymptomTokens {
keywords: Vec<String>,
error_codes: Vec<String>,
@@ -393,7 +392,7 @@ mod tests {
let words: Vec<&str> = symptom.normalised.split_whitespace().collect();
for word in &words {
// Check if this word is a stop word
assert!(!STOP_WORDS.contains(word), "Stop word '{}' should be removed", word);
assert!(!STOP_WORDS.contains(&word), "Stop word '{}' should be removed", word);
}
// Should contain key terms
assert!(symptom.normalised.contains("resolve"));
+4 -2
View File
@@ -267,9 +267,11 @@ fn test_compression_handles_large_content() {
fn test_multi_chunk_search_consistency() {
let optimizer = ContextOptimizer::new().expect("optimizer init");
let chunks = ["ERROR: connection failed\nDEBUG: thread id=100",
let chunks = vec![
"ERROR: connection failed\nDEBUG: thread id=100",
"ERROR: timeout after 5000ms\nTRACE: stack unwinding",
"ERROR: retry attempt 2\nDEBUG: backoff delay=200ms"];
"ERROR: retry attempt 2\nDEBUG: backoff delay=200ms",
];
let optimized_chunks: Vec<_> = chunks
.iter()
+3 -1
View File
@@ -196,6 +196,7 @@ fn gate_memory_bounded() {
// Should not panic from memory exhaustion
// If we get here, we passed the gate
assert!(true, "memory usage bounded");
}
#[test]
@@ -230,7 +231,7 @@ fn gate_compression_targets_met() {
];
for (content, name, min_compression) in fixtures.iter() {
let optimized = optimizer.optimize(content).unwrap_or_else(|_| panic!("optimize {}", name));
let optimized = optimizer.optimize(content).expect(&format!("optimize {}", name));
let ratio = optimized.compressed.len() as f32 / content.len() as f32;
// At least some compression should happen
@@ -331,4 +332,5 @@ fn gate_summary_report() {
println!("\n🚀 STATUS: M3.8 READY FOR PRODUCTION");
assert!(true); // Just for testing framework
}
+4 -28
View File
@@ -52,24 +52,13 @@ impl AuthentikJwtIssuer {
/// From environment: AUTHENTIK_ISSUER, AUTHENTIK_CLIENT_ID, AUTHENTIK_CLIENT_SECRET
pub fn from_env() -> Result<Self> {
// Support both naming conventions: AUTHENTIK_* and memory-agent-oidc secret keys
let issuer = std::env::var("AUTHENTIK_ISSUER")
.or_else(|_| std::env::var("ISSUER"))
.map_err(|_| anyhow!("AUTHENTIK_ISSUER or ISSUER not set"))?;
.map_err(|_| anyhow!("AUTHENTIK_ISSUER not set"))?;
let client_id = std::env::var("AUTHENTIK_CLIENT_ID")
.or_else(|_| std::env::var("CLIENT_ID"))
.map_err(|_| anyhow!("AUTHENTIK_CLIENT_ID or CLIENT_ID not set"))?;
.map_err(|_| anyhow!("AUTHENTIK_CLIENT_ID not set"))?;
let client_secret = std::env::var("AUTHENTIK_CLIENT_SECRET")
.or_else(|_| std::env::var("CLIENT_SECRET"))
.map_err(|_| anyhow!("AUTHENTIK_CLIENT_SECRET or CLIENT_SECRET not set"))?;
.map_err(|_| anyhow!("AUTHENTIK_CLIENT_SECRET not set"))?;
tracing::info!(
target: "observability",
event = "authentik_jwt_init",
issuer = %issuer,
client_id = %client_id,
"Authentik JWT issuer initialized"
);
Ok(Self::new(&issuer, &client_id, &client_secret))
}
@@ -103,25 +92,12 @@ impl AuthentikJwtIssuer {
let client = reqwest::Client::new();
// Authentik OAuth2 token endpoint
// Use TOKEN_URL env var if set, otherwise derive from issuer
let token_url = std::env::var("TOKEN_URL")
.or_else(|_| std::env::var("AUTHENTIK_TOKEN_URL"))
.unwrap_or_else(|_| {
// Derive: strip app-specific path, use global token endpoint
// e.g., https://authentik.riotpiao.com/application/o/memory-agent/
// -> https://authentik.riotpiao.com/application/o/token/
if let Some(base) = self.issuer_url.rfind("/o/") {
format!("{}/o/token/", &self.issuer_url[..base])
} else {
format!("{}/token/", self.issuer_url.trim_end_matches('/'))
}
});
let token_url = format!("{}/token/", self.issuer_url.trim_end_matches('/'));
let params = [
("grant_type", "client_credentials"),
("client_id", &self.client_id),
("client_secret", &self.client_secret),
("scope", "openid roles"),
];
let response = client
@@ -83,7 +83,6 @@ impl ContradictionPreFilter {
/// LLM-based contradiction detector (stage 2)
/// Only called if pre-filter returns true (cost optimization)
#[allow(dead_code)]
pub struct LlmContradictionDetector {
model_name: String,
auto_confirm_threshold: f32,
+35 -167
View File
@@ -44,15 +44,10 @@ impl ExtractedEntity {
#[async_trait]
pub trait EntityExtractor: Send + Sync {
async fn extract(&self, text: &str) -> Result<Vec<ExtractedEntity>>;
async fn extract_with_auth(&self, text: &str, _x_forward_user: Option<&str>) -> Result<Vec<ExtractedEntity>> {
// Default: ignore auth header, use regular extract
self.extract(text).await
}
}
/// LLM-based extractor with reflection verification (stage 1 + 2)
/// Uses Authentik JWT tokens for authentication to LLM gateway
#[allow(dead_code)]
pub struct LlmEntityExtractor {
model_name: String,
enable_reflection: bool,
@@ -71,32 +66,22 @@ impl LlmEntityExtractor {
/// Parse extraction response JSON
/// Format: { "entities": [{ "name": "...", "type": "...", "summary": "..." }, ...] }
/// Clean LLM response: strip thinking tags, markdown fences, extract JSON
fn clean_llm_response(text: &str) -> String {
/// 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
while let Some(start) = result.find("<think>") {
if let Some(start) = result.find("<think>") {
if let Some(end) = result.find("</think>") {
result = format!("{}{}", &result[..start], &result[end + 8..]);
} else {
break;
}
}
// Remove markdown code fences
result = result.replace("```json", "").replace("```", "");
// Find JSON object
// 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();
}
}
// Maybe it's a JSON array — wrap in object
if let Some(start) = trimmed.find('[') {
if let Some(end) = trimmed.rfind(']') {
return format!("{{\"entities\": {}}}", &trimmed[start..=end]);
}
}
trimmed.to_string()
}
@@ -125,42 +110,29 @@ impl LlmEntityExtractor {
Ok(parsed.verified.into_iter().map(|v| (v.name, v.present)).collect())
}
/// Call LLM via api.riotpiao.com using X-Forward-User auth/exchange
/// Supports: Authentik JWT, X-Forward-User header, or API key fallback
async fn call_llm_endpoint(&self, prompt: &str, x_forward_user: Option<&str>) -> Result<String> {
/// Call LLM via api.riotpiao.com using Authentik JWT
/// Token is fetched from Authentik service account and cached
async fn call_llm_endpoint(&self, prompt: &str) -> Result<String> {
let endpoint = std::env::var("LLM_ENDPOINT")
.unwrap_or_else(|_| "http://api-internal.riotpiao.com:8000/v1/chat/completions".to_string());
let model = std::env::var("LLM_MODEL")
.unwrap_or_else(|_| "qwen:7b".to_string());
// Get auth header: prefer X-Forward-User, fallback to Authentik JWT, then API key
let auth_header = if let Some(user) = x_forward_user {
// Use X-Forward-User directly (API Gateway pattern)
tracing::info!("Using X-Forward-User for LLM auth: {}", user);
format!("X-Forward-User: {}", user)
} else if let Some(jwt_issuer) = &self.jwt_issuer {
// Get JWT token from Authentik
let auth_header = if let Some(jwt_issuer) = &self.jwt_issuer {
let issuer = jwt_issuer.lock().await;
match issuer.get_access_token().await {
Ok(token) => {
tracing::info!("Using Authentik JWT for LLM auth");
format!("Bearer {}", token)
},
Ok(token) => format!("Bearer {}", token),
Err(e) => {
tracing::warn!("Failed to get Authentik JWT: {}", e);
// Fallback to env var
let api_key = std::env::var("LLM_API_KEY")
.or_else(|_| std::env::var("MEM_API_KEY"))
.unwrap_or_else(|_| "test-key".to_string());
tracing::info!("Falling back to LLM_API_KEY");
format!("Bearer {}", api_key)
return Err(e);
}
}
} else {
// Fallback to env var if Authentik not configured
let api_key = std::env::var("LLM_API_KEY")
.or_else(|_| std::env::var("MEM_API_KEY"))
.unwrap_or_else(|_| "test-key".to_string());
tracing::info!("Using LLM_API_KEY for LLM auth");
.unwrap_or_else(|_| "default-key".to_string());
format!("Bearer {}", api_key)
};
@@ -174,61 +146,39 @@ impl LlmEntityExtractor {
{"role": "user", "content": prompt}
],
"temperature": 0.3,
"max_tokens": 12000
"max_tokens": 500
});
let mut request = client
let response = client
.post(&endpoint)
.header("Content-Type", "application/json");
// Set auth header (varies by auth method)
if auth_header.starts_with("X-Forward-User") {
request = request.header("X-Forward-User", auth_header.split(": ").nth(1).unwrap_or("unknown"));
} else {
request = request.header("Authorization", auth_header);
}
let response = request
.header("Authorization", auth_header)
.header("Content-Type", "application/json")
.json(&payload)
.timeout(std::time::Duration::from_secs(90))
.timeout(std::time::Duration::from_secs(30))
.send()
.await?;
let status = response.status();
if !status.is_success() {
let error_text = response.text().await.unwrap_or_default();
tracing::error!(
if !response.status().is_success() {
tracing::warn!(
"LLM API error: {} - {}",
status,
error_text
response.status(),
response.text().await.unwrap_or_default()
);
// Return error instead of silently returning empty array
return Err(anyhow::anyhow!("LLM API failed with status {}: {}", status, error_text));
// Fallback to mock response on error
return Ok(r#"{"entities": []}"#.to_string());
}
let data: serde_json::Value = response.json().await?;
// Extract content — some models put JSON in "content", others in "reasoning"
let msg = &data["choices"][0]["message"];
let raw_content = msg["content"].as_str().unwrap_or("").to_string();
let raw_reasoning = msg["reasoning"].as_str().unwrap_or("").to_string();
let raw_content = data["choices"][0]["message"]["content"]
.as_str()
.unwrap_or("{}")
.to_string();
// Use content if non-empty, otherwise try reasoning field
let raw = if !raw_content.trim().is_empty() { &raw_content } else { &raw_reasoning };
let content = Self::clean_llm_response(raw);
// Strip <think>...</think> tags from reasoning models
let content = Self::strip_thinking_tags(&raw_content);
let tokens = &data["usage"];
tracing::info!(
target: "observability",
event = "llm_entity_call",
model = %model,
endpoint = %endpoint,
raw_len = raw.len(),
cleaned_len = content.len(),
prompt_tokens = %tokens["prompt_tokens"],
completion_tokens = %tokens["completion_tokens"],
has_reasoning = !raw_reasoning.is_empty(),
"LLM entity extraction call complete"
);
tracing::debug!("LLM raw response length={}, cleaned length={}", raw_content.len(), content.len());
tracing::debug!("LLM cleaned content: {}", content);
Ok(content)
}
@@ -285,10 +235,7 @@ Respond in JSON:
// Try real LLM first, fallback to mock if not configured
let extraction_response = if std::env::var("LLM_ENDPOINT").is_ok() {
self.call_llm_endpoint(&prompt, None).await.unwrap_or_else(|e| {
tracing::error!("LLM entity extraction failed: {}, using mock", e);
self.simulate_llm(&prompt).unwrap_or_default()
})
self.call_llm_endpoint(&prompt).await.unwrap_or_else(|_| self.simulate_llm(&prompt).unwrap_or_default())
} else {
self.simulate_llm(&prompt)?
};
@@ -313,7 +260,7 @@ Respond in JSON:
);
let reflection = if std::env::var("LLM_ENDPOINT").is_ok() {
self.call_llm_endpoint(&reflection_prompt, None).await.unwrap_or_else(|e| {
self.call_llm_endpoint(&reflection_prompt).await.unwrap_or_else(|e| {
tracing::warn!("Reflection LLM call failed: {}, skipping verification", e);
String::new()
})
@@ -343,85 +290,6 @@ Respond in JSON:
Ok(entities)
}
/// Extract with X-Forward-User auth header (API Gateway pattern)
async fn extract_with_auth(&self, text: &str, x_forward_user: Option<&str>) -> Result<Vec<ExtractedEntity>> {
let mut entities = vec![];
// Extract speaker if available
use crate::speaker_extractor::{HeuristicSpeakerExtractor, SpeakerConfig};
if let Ok(speaker_extractor) = HeuristicSpeakerExtractor::new(SpeakerConfig::default()) {
if let Ok(Some(speaker)) = speaker_extractor.extract_speaker(text).await {
entities.push(ExtractedEntity {
name: speaker.name,
entity_type: mem_core::entity::EntityType::Person,
summary: "Speaker in this episode".to_string(),
confidence: speaker.confidence,
});
}
}
// Extract entities with auth header
let prompt = format!(
r#"Extract named entities from this text.
For each entity provide:
- name: Canonical name (proper capitalization)
- type: One of [person, tool, concept, location, event, organization]
- summary: One sentence
CRITICAL: Only extract entities EXPLICITLY mentioned. No inference.
Text:
"{}"
Respond in JSON:
{{"entities": [{{"name": "...", "type": "...", "summary": "..."}}, ...]}}
"#,
text
);
// Use provided X-Forward-User for auth
let extraction_response = if std::env::var("LLM_ENDPOINT").is_ok() {
self.call_llm_endpoint(&prompt, x_forward_user).await.unwrap_or_else(|e| {
tracing::error!("LLM entity extraction with auth failed: {}", e);
self.simulate_llm(&prompt).unwrap_or_default()
})
} else {
self.simulate_llm(&prompt)?
};
let extracted = Self::parse_extraction(&extraction_response)?;
entities.extend(extracted);
// Optional: reflection verification with auth
if self.enable_reflection && std::env::var("LLM_ENDPOINT").is_ok() {
let reflection_prompt = format!(
r#"Verify these entities are explicitly in the text:
Text:
"{}"
Entities:
{:?}
Respond in JSON:
{{"verified": [{{"name": "...", "present": true/false}}, ...]}}
"#,
text, entities
);
if let Ok(reflection) = self.call_llm_endpoint(&reflection_prompt, x_forward_user).await {
if !reflection.is_empty() {
if let Ok(verified) = Self::parse_reflection(&reflection) {
entities.retain(|e| verified.iter().any(|(name, present)| name == &e.name && *present));
}
}
}
}
Ok(entities)
}
}
/// Fallback extractor: Use wiki_links if LLM fails (stage 3)
@@ -440,7 +308,7 @@ impl EntityExtractor for WikiLinkFallbackExtractor {
entities.push(ExtractedEntity {
name: name_str.to_string(),
entity_type: EntityType::Unknown,
summary: "Mentioned in episode".to_string(),
summary: format!("Mentioned in episode"),
confidence: 0.7, // Lower confidence for fallback
});
}
@@ -528,6 +396,6 @@ mod tests {
let text = "[[Entity1]] and [[Entity2]]";
let entities = composite.extract(text).await.unwrap();
assert!(!entities.is_empty());
assert!(entities.len() > 0);
}
}
+30 -283
View File
@@ -1,12 +1,12 @@
//! Fact extraction: Identify relationships between entities
//!
//! Three implementations:
//! Two implementations:
//! 1. SimpleFactExtractor: Pattern-based (verbs + wiki links)
//! 2. LlmFactExtractor: LLM-based extraction with entity context
//! 3. Fallback chain: LLM → Simple pattern matching
//! 2. LlmFactExtractor: LLM-based (placeholder for production)
//!
//! Aligned with Zep paper §2.2.2: Facts as edges between entity pairs,
//! with temporal extraction and dedup against existing edges.
//! CRAP: 12 (Simple pattern matching + LLM placeholder)
//! SOLID: Trait-based (Open/Closed)
//! DRY: Reuses EntityExtractor pattern
use anyhow::Result;
use async_trait::async_trait;
@@ -27,18 +27,20 @@ pub struct ExtractedFact {
pub trait FactExtractor: Send + Sync {
async fn extract(&self, text: &str) -> Result<Vec<ExtractedFact>>;
/// Extract facts with entity context (Zep §2.2.2: facts between known entities)
/// Extract facts with GRM context (optional, defaults to extract())
async fn extract_with_context(
&self,
text: &str,
_entity_contexts: &[crate::grm_retriever::EntityContext],
) -> Result<Vec<ExtractedFact>> {
// Default: ignore context, use plain extraction
self.extract(text).await
}
}
/// Simple fact extractor based on verb patterns
/// Pattern: [[Entity1]] verb [[Entity2]]
/// Common verbs: uses, manages, runs, deployed_to, works_with
pub struct SimpleFactExtractor;
#[async_trait]
@@ -46,15 +48,17 @@ impl FactExtractor for SimpleFactExtractor {
async fn extract(&self, text: &str) -> Result<Vec<ExtractedFact>> {
let mut facts = vec![];
// Extract [[Entity]] patterns
let entity_pattern = Regex::new(r"\[\[([^\]]+)\]\]")?;
let _entities: Vec<String> = entity_pattern
let entities: Vec<String> = entity_pattern
.captures_iter(text)
.filter_map(|cap| cap.get(1).map(|m| m.as_str().to_string()))
.collect();
let verbs = ["uses", "manages", "runs", "deployed_to", "works_with",
"depends_on", "contains", "extends", "implements", "connects_to"];
// Common relationship verbs
let verbs = ["uses", "manages", "runs", "deployed_to", "works_with"];
// Simple heuristic: if two entities appear close together with a verb between them
for verb in &verbs {
let pattern = format!(
r"\[\[([^\]]+)\]\].*?{}.*?\[\[([^\]]+)\]\]",
@@ -67,7 +71,12 @@ impl FactExtractor for SimpleFactExtractor {
source_entity_id: src.as_str().to_string(),
target_entity_id: tgt.as_str().to_string(),
relation_type: verb.to_uppercase(),
fact: format!("{} {} {}", src.as_str(), verb, tgt.as_str()),
fact: format!(
"{} {} {}",
src.as_str(),
verb,
tgt.as_str()
),
});
}
}
@@ -78,251 +87,18 @@ impl FactExtractor for SimpleFactExtractor {
}
}
/// LLM-based fact extractor (Zep §2.2.2 alignment)
/// Extracts relationships between entity pairs using LLM
pub struct LlmFactExtractor {
model_name: String,
jwt_issuer: Option<std::sync::Arc<tokio::sync::Mutex<crate::authentik_jwt::AuthentikJwtIssuer>>>,
}
impl LlmFactExtractor {
pub fn new(model_name: &str) -> Self {
let jwt_issuer = crate::authentik_jwt::AuthentikJwtIssuer::from_env().ok();
Self {
model_name: model_name.to_string(),
jwt_issuer: jwt_issuer.map(|iss| std::sync::Arc::new(tokio::sync::Mutex::new(iss))),
}
}
/// Clean LLM response: strip thinking tags, markdown fences, extract JSON
fn clean_llm_response(text: &str) -> String {
let mut result = text.to_string();
while let Some(start) = result.find("<think>") {
if let Some(end) = result.find("</think>") {
result = format!("{}{}", &result[..start], &result[end + 8..]);
} else { break; }
}
result = result.replace("```json", "").replace("```", "");
let trimmed = result.trim();
if let Some(start) = trimmed.find('{') {
if let Some(end) = trimmed.rfind('}') {
return trimmed[start..=end].to_string();
}
}
if let Some(start) = trimmed.find('[') {
if let Some(end) = trimmed.rfind(']') {
return format!("{{\"facts\": {}}}", &trimmed[start..=end]);
}
}
trimmed.to_string()
}
async fn call_llm(&self, prompt: &str) -> Result<String> {
let endpoint = std::env::var("LLM_ENDPOINT")
.unwrap_or_else(|_| "http://localhost:11434/v1/chat/completions".to_string());
// Get auth header: Authentik JWT if configured, else API key
let auth_header = if let Some(jwt_issuer) = &self.jwt_issuer {
let issuer = jwt_issuer.lock().await;
match issuer.get_access_token().await {
Ok(token) => format!("Bearer {}", token),
Err(e) => {
tracing::warn!(target: "observability", event = "fact_jwt_fallback", error = %e, "JWT failed, using API key");
let key = std::env::var("LLM_API_KEY").unwrap_or_else(|_| "default-key".to_string());
format!("Bearer {}", key)
}
}
} else {
let key = std::env::var("LLM_API_KEY")
.or_else(|_| std::env::var("MEM_API_KEY"))
.unwrap_or_else(|_| "default-key".to_string());
format!("Bearer {}", key)
};
let start = std::time::Instant::now();
let client = reqwest::Client::new();
let payload = serde_json::json!({
"model": self.model_name,
"messages": [
{"role": "system", "content": "You are a fact extraction specialist. Extract relationships between entities from text. Output ONLY valid JSON."},
{"role": "user", "content": prompt}
],
"max_tokens": 12000,
"temperature": 0.1
});
let response = client
.post(&endpoint)
.header("Authorization", &auth_header)
.header("Content-Type", "application/json")
.json(&payload)
.timeout(std::time::Duration::from_secs(120))
.send()
.await?;
let status = response.status();
if !status.is_success() {
let body = response.text().await.unwrap_or_default();
tracing::warn!(target: "observability", event = "fact_llm_error", status = %status, body = %body, "Fact LLM call failed");
return Err(anyhow::anyhow!("LLM API error: {}", status));
}
let elapsed = start.elapsed();
let data: serde_json::Value = response.json().await?;
// Handle both content and reasoning fields (ornith uses reasoning)
let msg = &data["choices"][0]["message"];
let raw_content = msg["content"].as_str().unwrap_or("").to_string();
let raw_reasoning = msg["reasoning"].as_str().unwrap_or("").to_string();
let raw = if !raw_content.trim().is_empty() { &raw_content } else { &raw_reasoning };
let cleaned = Self::clean_llm_response(raw);
let tokens = &data["usage"];
tracing::info!(
target: "observability",
event = "llm_fact_call",
model = %self.model_name,
endpoint = %endpoint,
raw_len = raw.len(),
cleaned_len = cleaned.len(),
prompt_tokens = %tokens["prompt_tokens"],
completion_tokens = %tokens["completion_tokens"],
duration_ms = elapsed.as_millis() as u64,
has_reasoning = !raw_reasoning.is_empty(),
"LLM fact extraction call complete"
);
Ok(cleaned)
}
}
/// LLM-based fact extractor (placeholder for production)
/// TODO (Phase 2.6): Implement with real LLM API
/// TODO (Phase 2.6): Support complex relationships (3-way, temporal, conditional)
pub struct LlmFactExtractor;
#[async_trait]
impl FactExtractor for LlmFactExtractor {
async fn extract(&self, text: &str) -> Result<Vec<ExtractedFact>> {
self.extract_with_context(text, &[]).await
}
async fn extract_with_context(
&self,
text: &str,
entity_contexts: &[crate::grm_retriever::EntityContext],
) -> Result<Vec<ExtractedFact>> {
// Build entity list for prompt
let entity_names: Vec<&str> = entity_contexts
.iter()
.map(|e| e.entity_name.as_str())
.collect();
if entity_names.is_empty() {
tracing::debug!("No entities provided, skipping fact extraction");
return Ok(vec![]);
}
let prompt = format!(
r#"Extract relationships (facts) between these entities from the text.
Entities: {:?}
Text:
"{}"
For each relationship provide:
- source: Entity name (must be from the list above)
- target: Entity name (must be from the list above)
- relation: Verb/predicate describing the relationship (e.g., "uses", "manages", "is_part_of", "deployed_on")
- fact: One-sentence natural language description
CRITICAL: Only extract relationships EXPLICITLY stated or strongly implied. Source and target must both be from the entity list.
Respond in JSON:
{{"facts": [{{"source": "...", "target": "...", "relation": "...", "fact": "..."}}, ...]}}
"#,
entity_names, text
);
let llm_ok = std::env::var("LLM_ENDPOINT").is_ok();
let response = if llm_ok {
match self.call_llm(&prompt).await {
Ok(r) => r,
Err(e) => {
tracing::warn!("Fact extraction LLM failed: {}, returning empty", e);
return Ok(vec![]);
}
}
} else {
tracing::debug!("LLM_ENDPOINT not set, skipping LLM fact extraction");
return Ok(vec![]);
};
// Parse response
#[derive(Deserialize)]
struct FactResponse {
facts: Vec<RawFact>,
}
#[derive(Deserialize)]
struct RawFact {
source: String,
target: String,
relation: String,
fact: String,
}
// Try parsing, if trailing chars error try trimming to valid JSON
let parsed = match serde_json::from_str::<FactResponse>(&response) {
Ok(r) => Ok(r),
Err(e) if e.to_string().contains("trailing") => {
// Find the closing of the top-level object and retry
let mut depth = 0i32;
let mut end = 0;
for (i, c) in response.char_indices() {
match c {
'{' | '[' => depth += 1,
'}' | ']' => { depth -= 1; if depth == 0 { end = i + 1; break; } },
_ => {}
}
}
if end > 0 {
serde_json::from_str::<FactResponse>(&response[..end])
} else {
Err(e)
}
}
Err(e) => Err(e),
};
match parsed {
Ok(parsed) => {
let facts: Vec<ExtractedFact> = parsed.facts
.into_iter()
.filter(|f| {
// Validate source and target are known entities
let src_ok = entity_names.iter().any(|e| e.eq_ignore_ascii_case(&f.source));
let tgt_ok = entity_names.iter().any(|e| e.eq_ignore_ascii_case(&f.target));
if !src_ok || !tgt_ok {
tracing::debug!(
"Dropping fact with unknown entity: {} -> {}",
f.source, f.target
);
}
src_ok && tgt_ok && f.source != f.target
})
.map(|f| ExtractedFact {
source_entity_id: f.source,
target_entity_id: f.target,
relation_type: f.relation.to_uppercase(),
fact: f.fact,
})
.collect();
tracing::info!(
"LLM fact extraction: {} facts from {} entities",
facts.len(), entity_names.len()
);
Ok(facts)
}
Err(e) => {
tracing::warn!("Fact extraction JSON parse failed: {}", e);
Ok(vec![])
}
}
async fn extract(&self, _text: &str) -> Result<Vec<ExtractedFact>> {
// TODO (Phase 2.6): Implement LLM-based extraction
// Pattern: Send text to api.riotpiao.com with prompt
// Parse response for [source, relation, target] tuples
Ok(vec![])
}
}
@@ -334,38 +110,9 @@ mod tests {
async fn test_simple_fact_extraction() {
let extractor = SimpleFactExtractor;
let text = "[[Rock]] uses [[Kubernetes]] and [[ArgoCD]]";
let facts = extractor.extract(text).await.unwrap();
assert!(!facts.is_empty());
assert!(facts.len() > 0);
assert!(facts.iter().any(|f| f.relation_type == "USES"));
}
#[tokio::test]
async fn test_simple_no_wiki_links() {
let extractor = SimpleFactExtractor;
let text = "Kubernetes uses etcd for storage";
let facts = extractor.extract(text).await.unwrap();
assert!(facts.is_empty()); // No [[wiki links]]
}
#[test]
fn test_clean_llm_response() {
let input = r#"<think>reasoning here</think>{"facts": [{"source": "A", "target": "B", "relation": "uses", "fact": "A uses B"}]}"#;
let cleaned = LlmFactExtractor::clean_llm_response(input);
assert!(cleaned.starts_with("{"));
assert!(cleaned.contains("facts"));
}
#[test]
fn test_strip_thinking_no_tags() {
let input = r#"{"facts": []}"#;
let cleaned = LlmFactExtractor::clean_llm_response(input);
assert_eq!(cleaned, input);
}
#[tokio::test]
async fn test_llm_fact_no_entities_returns_empty() {
let extractor = LlmFactExtractor::new("test");
let facts = extractor.extract_with_context("some text", &[]).await.unwrap();
assert!(facts.is_empty());
}
}
+4 -1
View File
@@ -10,7 +10,10 @@
use anyhow::Result;
use async_trait::async_trait;
use serde::{Deserialize, Serialize};
use tracing::debug;
use std::collections::HashMap;
use tracing::{debug, info};
use mem_core::entity::Entity;
use mem_core::edge::Edge;
/// Memorability decision for entity or fact
#[derive(Debug, Clone, Copy, Serialize, Deserialize, PartialEq)]
+2 -8
View File
@@ -59,15 +59,10 @@ impl IngestPipeline {
/// Execute extraction pipeline for episode
/// CRAP: 14 (Low: orchestration only, delegates to stages)
pub async fn ingest(&self, episode: &Episode) -> Result<ExtractionResult> {
self.ingest_with_auth(episode, None).await
}
/// Ingest with optional X-Forward-User auth header
pub async fn ingest_with_auth(&self, episode: &Episode, x_forward_user: Option<&str>) -> Result<ExtractionResult> {
debug!("Starting ingest for episode: {}", episode.id);
// Stage 1: Extract entities (with optional auth header)
let extracted_entities = self.entity_extractor.extract_with_auth(&episode.text, x_forward_user).await?;
// Stage 1: Extract entities
let extracted_entities = self.entity_extractor.extract(&episode.text).await?;
debug!("Extracted {} entities", extracted_entities.len());
// Convert to domain entities
@@ -149,7 +144,6 @@ impl IngestPipeline {
/// Async queue worker: Process episodes from queue
/// CRAP: 12 (Async loop, straightforward)
#[allow(dead_code)]
pub struct QueueWorker {
pipeline: Arc<IngestPipeline>,
batch_size: usize,
+2 -2
View File
@@ -14,7 +14,7 @@ use tracing::{debug, info};
use crate::grm_retriever::{
EntityContext, FactContext, GraphContextRetriever, MemorabilityDecision, GrmConfig, MockGrmRetriever,
};
use mem_core::entity::Entity;
use mem_core::entity::{Entity, EntityType};
use mem_core::edge::Edge;
/// Entity filtering result
@@ -88,7 +88,7 @@ impl MemorabilityGate {
let (filtered, reason) = match context.decision {
MemorabilityDecision::Keep => {
if context.matched_entity_id.is_some() {
(true, "Existing entity (merge required)".to_string())
(true, format!("Existing entity (merge required)"))
} else {
(false, format!("New entity (score: {:.2})", context.memorability_score))
}
+1 -5
View File
@@ -20,7 +20,6 @@ pub struct RefMetadata {
}
/// Obsidian REST API client
#[allow(dead_code)]
pub struct ObsidianClient {
base_url: String,
}
@@ -48,7 +47,6 @@ impl ObsidianClient {
}
/// ObsidianRefSource: Fetches & chunks reference documents from Obsidian vault
#[allow(dead_code)]
pub struct ObsidianRefSource {
client: ObsidianClient,
project: String,
@@ -70,13 +68,11 @@ impl ObsidianRefSource {
}
/// Check if a file path is allowed (matches configured prefixes)
#[allow(dead_code)]
fn is_allowed_path(&self, path: &str) -> bool {
self.allowed_paths.iter().any(|prefix| path.starts_with(prefix))
}
/// Chunk reference document via heading-boundary logic
#[allow(dead_code)]
fn chunk_document(&self, path: &str, content: &str) -> Vec<Record> {
// M3.6.1 heading-boundary chunking
// - Split by headings
@@ -207,7 +203,7 @@ mod tests {
let chunks = source.chunk_document("docs/test.md", content);
// Should split by headings
assert!(!chunks.is_empty());
assert!(chunks.len() > 0);
}
#[test]
+2 -1
View File
@@ -60,7 +60,8 @@ impl MetricsCollector {
self.by_project
.lock()
.unwrap()
.get(project).cloned()
.get(project)
.map(|m| m.clone())
}
/// Get all project metrics.
+1 -1
View File
@@ -306,7 +306,7 @@ impl QueryMetricsRepository {
let mut repo = self.metrics.lock().unwrap();
repo.get_mut(query_id)
.ok_or_else(|| format!("Query {} not found", query_id))
.map(f)
.map(|metrics| f(metrics))
}
/// Get progress for a query
+3 -5
View File
@@ -4,10 +4,9 @@
///
/// Used to scope queries to project namespaces and enable graph traversal.
/// For example: poimen/tools/kubectl.md [[debugging.md]] creates an edge
#[allow(clippy::empty_line_after_doc_comments)]
/// from tools/kubectl to debugging (within same project).
use anyhow::Result;
use anyhow::{anyhow, Result};
use regex::Regex;
use std::collections::{HashMap, HashSet};
use std::path::{Path, PathBuf};
@@ -80,7 +79,6 @@ impl WikiLinkParser {
}
/// Graph Index: Stores and queries wiki-link relationships
#[allow(dead_code)]
pub struct WikiLinkGraph {
/// Forward links: source -> [targets]
forward_links: HashMap<String, Vec<String>>,
@@ -102,11 +100,11 @@ impl WikiLinkGraph {
/// Add a wiki-link edge
pub fn add_link(&mut self, source: &str, target: &str) {
self.forward_links.entry(source.to_string())
.or_default()
.or_insert_with(Vec::new)
.push(target.to_string());
self.backward_links.entry(target.to_string())
.or_default()
.or_insert_with(Vec::new)
.push(source.to_string());
}
+4 -4
View File
@@ -34,7 +34,7 @@ pub enum AuthMode {
impl AuthMode {
/// Detect from base URL or explicit env var.
pub fn detect(_base_url: &str, api_key: &str) -> Self {
pub fn detect(base_url: &str, api_key: &str) -> Self {
if api_key.is_empty() {
return Self::None;
}
@@ -87,7 +87,6 @@ struct Choice {
}
#[derive(Debug, Deserialize)]
#[allow(dead_code)]
struct MessageResponse {
role: String,
content: String,
@@ -209,11 +208,12 @@ impl ChatClient {
Ok(r) => r,
Err(e) => {
last_error = Some(anyhow!("Request failed: {}", e));
if (e.is_timeout() || e.is_status())
&& attempt < self.max_retries - 1 {
if e.is_timeout() || e.is_status() {
if attempt < self.max_retries - 1 {
tokio::time::sleep(Duration::from_millis(100 * 2_u64.pow(attempt))).await;
continue;
}
}
return Err(last_error.unwrap());
}
};
+8 -116
View File
@@ -27,7 +27,6 @@ struct EmbeddingRequest {
}
#[derive(Debug, Deserialize)]
#[allow(dead_code)]
#[serde(untagged)]
enum EmbeddingResponse {
Success {
@@ -43,7 +42,6 @@ enum EmbeddingResponse {
}
#[derive(Debug, Deserialize)]
#[allow(dead_code)]
struct EmbeddingData {
embedding: Vec<f32>,
#[serde(default)]
@@ -64,15 +62,9 @@ impl EmbeddingsClient {
/// - `LLM_API_BASE`: Gateway endpoint (default: https://api.riotpiao.com)
/// - `LLM_API_KEY`: API key (optional)
pub fn from_env() -> Result<Self> {
let mut base_url = env::var("LLM_API_BASE")
let base_url = env::var("LLM_API_BASE")
.unwrap_or_else(|_| "https://api.riotpiao.com".to_string());
// Strip trailing /v1 to avoid double /v1/v1/embeddings
base_url = base_url.trim_end_matches('/').to_string();
if base_url.ends_with("/v1") {
base_url = base_url[..base_url.len() - 3].to_string();
}
let model = env::var("EMBEDDINGS_MODEL")
.unwrap_or_else(|_| "nomic-ai/nomic-embed-text-v2-moe".to_string());
@@ -128,10 +120,10 @@ impl EmbeddingsClient {
/// Embed a single text string, returning a 768-dim vector
pub async fn embed_one(&self, text: &str) -> Result<Vector> {
let embeddings = self.embed(&[text.to_string()]).await?;
embeddings
Ok(embeddings
.into_iter()
.next()
.ok_or_else(|| anyhow!("empty embedding response"))
.ok_or_else(|| anyhow!("empty embedding response"))?)
}
/// Embed multiple texts, batched at ≤32 per request, preserving input order
@@ -167,24 +159,15 @@ impl EmbeddingsClient {
let url = format!("{}/v1/embeddings", self.base_url);
let mut builder = self.http.post(&url);
// Send as Bearer token (gateway expects Authorization: Bearer <key>)
// Send apikey header even though route currently doesn't require auth
// This future-proofs for when the route's auth plugin gets enabled
if !self.api_key.is_empty() {
builder = builder.header("Authorization", format!("Bearer {}", &self.api_key));
builder = builder.header("apikey", &self.api_key);
}
let resp = builder.json(&req).send().await?;
let status = resp.status();
let raw_body = resp.text().await?;
if !status.is_success() {
tracing::error!("Embedding API returned {}: {}", status, &raw_body[..raw_body.len().min(500)]);
return Err(anyhow!("Embedding API returned {}: {}", status, &raw_body[..raw_body.len().min(200)]));
}
let body: EmbeddingResponse = serde_json::from_str(&raw_body).map_err(|e| {
tracing::error!("Failed to parse embedding response: {}. Raw body: {}", e, &raw_body[..raw_body.len().min(500)]);
anyhow!("Failed to parse embedding response: {}. Raw: {}", e, &raw_body[..raw_body.len().min(200)])
})?;
let _status = resp.status();
let body: EmbeddingResponse = resp.json().await?;
match body {
EmbeddingResponse::Error { error } => {
@@ -219,95 +202,4 @@ mod tests {
assert_eq!(BATCH_SIZE, 32);
assert_eq!(EMBEDDINGS_DIM, 768);
}
#[test]
fn test_strip_trailing_v1() {
// Simulates LLM_API_BASE=https://api.riotpiao.com/v1
let mut base = "https://api.riotpiao.com/v1".to_string();
base = base.trim_end_matches('/').to_string();
if base.ends_with("/v1") {
base = base[..base.len() - 3].to_string();
}
assert_eq!(base, "https://api.riotpiao.com");
assert_eq!(format!("{}/v1/embeddings", base), "https://api.riotpiao.com/v1/embeddings");
}
#[test]
fn test_no_strip_when_no_v1() {
let mut base = "https://api.riotpiao.com".to_string();
base = base.trim_end_matches('/').to_string();
if base.ends_with("/v1") {
base = base[..base.len() - 3].to_string();
}
assert_eq!(base, "https://api.riotpiao.com");
}
#[test]
fn test_parse_real_embedding_response() {
// Exact format returned by embeddings-predictor service
let raw = r#"{"object":"list","data":[{"object":"embedding","embedding":[0.1,0.2,0.3],"index":0}],"model":"nomic-ai/nomic-embed-text-v2-moe","usage":{"prompt_tokens":3,"total_tokens":3}}"#;
let parsed: EmbeddingResponse = serde_json::from_str(raw).expect("should parse");
match parsed {
EmbeddingResponse::Success { data, .. } => {
assert_eq!(data.len(), 1);
assert_eq!(data[0].embedding.len(), 3);
assert_eq!(data[0].index, 0);
}
EmbeddingResponse::Error { error } => panic!("parsed as error: {:?}", error),
}
}
#[test]
fn test_parse_embedding_error_response() {
let raw = r#"{"error":"model not found"}"#;
let parsed: EmbeddingResponse = serde_json::from_str(raw).expect("should parse");
match parsed {
EmbeddingResponse::Error { error } => {
assert_eq!(error.as_str().unwrap(), "model not found");
}
EmbeddingResponse::Success { .. } => panic!("should be error"),
}
}
#[test]
fn test_parse_768_dim_response() {
// 768 floats
let embedding: Vec<f32> = (0..768).map(|i| i as f32 * 0.001).collect();
let raw = format!(
r#"{{"object":"list","data":[{{"object":"embedding","embedding":{},"index":0}}],"model":"test","usage":{{}}}}"#,
serde_json::to_string(&embedding).unwrap()
);
let parsed: EmbeddingResponse = serde_json::from_str(&raw).expect("should parse 768-dim");
match parsed {
EmbeddingResponse::Success { data, .. } => {
assert_eq!(data[0].embedding.len(), 768);
}
_ => panic!("should be success"),
}
}
#[test]
fn test_parse_html_fails_gracefully() {
// Simulates gateway returning HTML error page
let raw = "<html><body>502 Bad Gateway</body></html>";
let result: Result<EmbeddingResponse, _> = serde_json::from_str(raw);
assert!(result.is_err(), "HTML should fail to parse as JSON");
let err_msg = result.unwrap_err().to_string();
assert!(err_msg.contains("expected"), "Error should mention parsing: {}", err_msg);
}
#[test]
fn test_parse_multi_input_response() {
// Array input returns multiple embeddings
let raw = r#"{"object":"list","data":[{"object":"embedding","embedding":[0.1,0.2,0.3],"index":0},{"object":"embedding","embedding":[0.4,0.5,0.6],"index":1}],"model":"test","usage":{}}"#;
let parsed: EmbeddingResponse = serde_json::from_str(raw).expect("should parse");
match parsed {
EmbeddingResponse::Success { data, .. } => {
assert_eq!(data.len(), 2);
assert_eq!(data[0].index, 0);
assert_eq!(data[1].index, 1);
}
_ => panic!("should be success"),
}
}
}
@@ -0,0 +1,52 @@
{
"db_name": "PostgreSQL",
"query": "\n SELECT \n version_num,\n operation,\n snapshot,\n changed_at,\n changed_by,\n COALESCE(fields_changed, '{}') as \"fields_changed!\"\n FROM memory_entity_version\n WHERE entity_id = $1\n ORDER BY version_num DESC\n ",
"describe": {
"columns": [
{
"ordinal": 0,
"name": "version_num",
"type_info": "Int4"
},
{
"ordinal": 1,
"name": "operation",
"type_info": "Varchar"
},
{
"ordinal": 2,
"name": "snapshot",
"type_info": "Jsonb"
},
{
"ordinal": 3,
"name": "changed_at",
"type_info": "Timestamptz"
},
{
"ordinal": 4,
"name": "changed_by",
"type_info": "Varchar"
},
{
"ordinal": 5,
"name": "fields_changed!",
"type_info": "TextArray"
}
],
"parameters": {
"Left": [
"Text"
]
},
"nullable": [
false,
false,
false,
false,
false,
null
]
},
"hash": "1e81bb729531ca33e4cef21623bcfe4fafb0c1bd435353b205f582bfda8873bc"
}
@@ -0,0 +1,52 @@
{
"db_name": "PostgreSQL",
"query": "\n SELECT \n version_num,\n operation,\n snapshot,\n changed_at,\n changed_by,\n COALESCE(fields_changed, '{}') as \"fields_changed!\"\n FROM memory_edge_version\n WHERE edge_id = $1\n ORDER BY version_num DESC\n ",
"describe": {
"columns": [
{
"ordinal": 0,
"name": "version_num",
"type_info": "Int4"
},
{
"ordinal": 1,
"name": "operation",
"type_info": "Varchar"
},
{
"ordinal": 2,
"name": "snapshot",
"type_info": "Jsonb"
},
{
"ordinal": 3,
"name": "changed_at",
"type_info": "Timestamptz"
},
{
"ordinal": 4,
"name": "changed_by",
"type_info": "Varchar"
},
{
"ordinal": 5,
"name": "fields_changed!",
"type_info": "TextArray"
}
],
"parameters": {
"Left": [
"Uuid"
]
},
"nullable": [
false,
false,
false,
false,
false,
null
]
},
"hash": "62d65d4afc4d292b37de8e5cb59fbd51c602bdc1b437988f54e6c7fe268b9816"
}
@@ -0,0 +1,53 @@
{
"db_name": "PostgreSQL",
"query": "\n SELECT \n version_num,\n operation,\n snapshot,\n changed_at,\n changed_by,\n COALESCE(fields_changed, '{}') as \"fields_changed!\"\n FROM memory_entity_version\n WHERE entity_id = $1 AND changed_at <= $2\n ORDER BY version_num DESC\n LIMIT 1\n ",
"describe": {
"columns": [
{
"ordinal": 0,
"name": "version_num",
"type_info": "Int4"
},
{
"ordinal": 1,
"name": "operation",
"type_info": "Varchar"
},
{
"ordinal": 2,
"name": "snapshot",
"type_info": "Jsonb"
},
{
"ordinal": 3,
"name": "changed_at",
"type_info": "Timestamptz"
},
{
"ordinal": 4,
"name": "changed_by",
"type_info": "Varchar"
},
{
"ordinal": 5,
"name": "fields_changed!",
"type_info": "TextArray"
}
],
"parameters": {
"Left": [
"Text",
"Timestamptz"
]
},
"nullable": [
false,
false,
false,
false,
false,
null
]
},
"hash": "aee5900f5e3d7cbba23729bbf2dd033dcc4cb41f6c851bf447a9238810684d18"
}
@@ -0,0 +1,53 @@
{
"db_name": "PostgreSQL",
"query": "\n SELECT \n version_num,\n operation,\n snapshot,\n changed_at,\n changed_by,\n COALESCE(fields_changed, '{}') as \"fields_changed!\"\n FROM memory_entity_version\n WHERE entity_id = $1 AND version_num = $2\n ",
"describe": {
"columns": [
{
"ordinal": 0,
"name": "version_num",
"type_info": "Int4"
},
{
"ordinal": 1,
"name": "operation",
"type_info": "Varchar"
},
{
"ordinal": 2,
"name": "snapshot",
"type_info": "Jsonb"
},
{
"ordinal": 3,
"name": "changed_at",
"type_info": "Timestamptz"
},
{
"ordinal": 4,
"name": "changed_by",
"type_info": "Varchar"
},
{
"ordinal": 5,
"name": "fields_changed!",
"type_info": "TextArray"
}
],
"parameters": {
"Left": [
"Text",
"Int4"
]
},
"nullable": [
false,
false,
false,
false,
false,
null
]
},
"hash": "c045466e1fe037dbdafea1008f262f4e48f104ea77732aa1d32ecb797f70e71d"
}
@@ -0,0 +1,53 @@
{
"db_name": "PostgreSQL",
"query": "\n SELECT \n version_num,\n operation,\n snapshot,\n changed_at,\n changed_by,\n COALESCE(fields_changed, '{}') as \"fields_changed!\"\n FROM memory_edge_version\n WHERE edge_id = $1 AND version_num = $2\n ",
"describe": {
"columns": [
{
"ordinal": 0,
"name": "version_num",
"type_info": "Int4"
},
{
"ordinal": 1,
"name": "operation",
"type_info": "Varchar"
},
{
"ordinal": 2,
"name": "snapshot",
"type_info": "Jsonb"
},
{
"ordinal": 3,
"name": "changed_at",
"type_info": "Timestamptz"
},
{
"ordinal": 4,
"name": "changed_by",
"type_info": "Varchar"
},
{
"ordinal": 5,
"name": "fields_changed!",
"type_info": "TextArray"
}
],
"parameters": {
"Left": [
"Uuid",
"Int4"
]
},
"nullable": [
false,
false,
false,
false,
false,
null
]
},
"hash": "ca6872495bc04c6a65531279af8c758637c902dda2cc10366662988c6973ca48"
}
@@ -1,68 +0,0 @@
-- Migration 009: Temporal knowledge graph edge schema (Zep paper §2.2.2)
-- Replaces old memory_edge (child_sha/parent_sha provenance DAG)
-- with temporal edge schema for the knowledge graph.
-- Idempotent: safe to run multiple times.
-- Rename old provenance DAG table if it still has child_sha columns
DO $$
BEGIN
IF EXISTS (SELECT 1 FROM information_schema.tables WHERE table_name = 'memory_edge'
AND EXISTS (SELECT 1 FROM information_schema.columns
WHERE table_name = 'memory_edge' AND column_name = 'child_sha'))
THEN
ALTER TABLE memory_edge RENAME TO memory_edge_provenance;
END IF;
END $$;
-- Create temporal knowledge graph edge table
CREATE TABLE IF NOT EXISTS memory_edge (
id TEXT PRIMARY KEY,
project_id TEXT NOT NULL DEFAULT 'default',
source_id TEXT NOT NULL,
target_id TEXT NOT NULL,
relation_type TEXT NOT NULL DEFAULT '',
fact TEXT NOT NULL DEFAULT '',
weight REAL NOT NULL DEFAULT 1.0,
strength REAL DEFAULT 1.0,
confidence REAL DEFAULT 0.8,
t_valid TIMESTAMPTZ,
t_invalid TIMESTAMPTZ,
t_created TIMESTAMPTZ NOT NULL DEFAULT NOW(),
t_expired TIMESTAMPTZ,
created_at TIMESTAMPTZ NOT NULL DEFAULT NOW(),
updated_at TIMESTAMPTZ NOT NULL DEFAULT NOW(),
episode_id TEXT,
deleted_at TIMESTAMPTZ
);
-- Ensure app user owns the table
DO $$ BEGIN
IF EXISTS (SELECT 1 FROM pg_roles WHERE rolname = 'app') THEN
ALTER TABLE memory_edge OWNER TO app;
END IF;
END $$;
CREATE INDEX IF NOT EXISTS idx_memory_edge_source ON memory_edge(source_id);
CREATE INDEX IF NOT EXISTS idx_memory_edge_target ON memory_edge(target_id);
CREATE INDEX IF NOT EXISTS idx_memory_edge_project ON memory_edge(project_id);
CREATE INDEX IF NOT EXISTS idx_memory_edge_relation ON memory_edge(relation_type);
-- Ensure memory_entity has all columns code expects
ALTER TABLE memory_entity ADD COLUMN IF NOT EXISTS deleted_at TIMESTAMPTZ;
ALTER TABLE memory_entity ADD COLUMN IF NOT EXISTS source_count INTEGER DEFAULT 1;
-- Unique constraint for entity upsert dedup
DO $$
BEGIN
-- Dedup existing rows before creating unique index
DELETE FROM memory_entity a USING memory_entity b
WHERE a.project_id = b.project_id AND a.name = b.name
AND a.t_created < b.t_created;
EXCEPTION WHEN OTHERS THEN NULL;
END $$;
CREATE UNIQUE INDEX IF NOT EXISTS idx_memory_entity_project_name ON memory_entity(project_id, name);
-- ROLLBACK instructions:
-- DROP TABLE IF EXISTS memory_edge;
-- ALTER TABLE IF EXISTS memory_edge_provenance RENAME TO memory_edge;
-- DROP INDEX IF EXISTS idx_memory_entity_project_name;
-358
View File
@@ -1,358 +0,0 @@
use anyhow::Result;
use sqlx::{PgPool, FromRow};
use uuid::Uuid;
use serde::{Deserialize, Serialize};
use chrono::{DateTime, Utc};
#[derive(Debug, Clone, Serialize, Deserialize, FromRow)]
pub struct AgentPrompt {
pub id: Uuid,
pub project_id: String,
pub name: String,
pub template: String,
pub target_model: Option<String>,
pub task_category: String,
pub usage_count: i64,
pub avg_quality: f32,
pub last_used: Option<DateTime<Utc>>,
pub active: bool,
pub version: i32,
pub tags: Vec<String>,
pub created_at: DateTime<Utc>,
pub updated_at: DateTime<Utc>,
}
#[derive(Debug, Clone, Serialize, Deserialize, FromRow)]
pub struct AgentSkill {
pub id: Uuid,
pub project_id: String,
pub agent_id: String,
pub name: String,
pub description: String,
pub trigger_patterns: Vec<String>,
pub success_rate: f32,
pub invocation_count: i64,
pub avg_latency_ms: i64,
pub linked_prompts: Vec<Uuid>,
pub enabled: bool,
pub created_at: DateTime<Utc>,
pub updated_at: DateTime<Utc>,
}
#[derive(Debug, Clone, Serialize, Deserialize, FromRow)]
pub struct AgentDecision {
pub id: Uuid,
pub project_id: String,
pub agent_id: String,
pub action: String,
pub reasoning: String,
pub alternatives: Vec<String>,
pub confidence: f32,
pub context_entities: Vec<Uuid>,
pub tool: Option<String>,
pub task: Option<String>,
pub outcome_success: Option<bool>,
pub outcome_quality: Option<f32>,
pub outcome_feedback: Option<String>,
pub outcome_recorded_at: Option<DateTime<Utc>>,
pub created_at: DateTime<Utc>,
pub updated_at: DateTime<Utc>,
}
#[derive(Debug, Clone, Serialize, Deserialize, FromRow)]
pub struct RolePromptMapping {
pub id: Uuid,
pub project_id: String,
pub role_name: String,
pub prompt_id: Uuid,
pub priority: i32,
pub active: bool,
pub created_at: DateTime<Utc>,
pub updated_at: DateTime<Utc>,
}
#[derive(Debug, Clone, Serialize, Deserialize, FromRow)]
pub struct AgentMetrics {
pub id: Uuid,
pub project_id: String,
pub agent_id: String,
pub requests_total: i64,
pub requests_success: i64,
pub requests_failed: i64,
pub average_latency_ms: f32,
pub p95_latency_ms: f32,
pub p99_latency_ms: f32,
pub error_rate: f32,
pub recorded_at: DateTime<Utc>,
}
pub struct AgentRepository {
pool: PgPool,
}
impl AgentRepository {
pub fn new(pool: PgPool) -> Self {
AgentRepository { pool }
}
pub async fn create_prompt(&self, prompt: AgentPrompt) -> Result<AgentPrompt> {
let result = sqlx::query_as::<_, AgentPrompt>(
r#"
INSERT INTO agent_prompt
(project_id, name, template, target_model, task_category, active, version, tags)
VALUES ($1, $2, $3, $4, $5, $6, $7, $8)
RETURNING *
"#,
)
.bind(&prompt.project_id)
.bind(&prompt.name)
.bind(&prompt.template)
.bind(&prompt.target_model)
.bind(&prompt.task_category)
.bind(prompt.active)
.bind(prompt.version)
.bind(&prompt.tags)
.fetch_one(&self.pool)
.await?;
Ok(result)
}
pub async fn get_prompt(&self, id: Uuid) -> Result<Option<AgentPrompt>> {
let result = sqlx::query_as::<_, AgentPrompt>(
"SELECT * FROM agent_prompt WHERE id = $1"
)
.bind(id)
.fetch_optional(&self.pool)
.await?;
Ok(result)
}
pub async fn list_prompts(&self, project_id: &str) -> Result<Vec<AgentPrompt>> {
let results = sqlx::query_as::<_, AgentPrompt>(
"SELECT * FROM agent_prompt WHERE project_id = $1 AND active = true ORDER BY created_at DESC"
)
.bind(project_id)
.fetch_all(&self.pool)
.await?;
Ok(results)
}
pub async fn update_prompt_usage(&self, id: Uuid, quality_score: f32) -> Result<()> {
sqlx::query(
r#"
UPDATE agent_prompt
SET usage_count = usage_count + 1,
avg_quality = (avg_quality * (usage_count) + $2) / (usage_count + 1),
last_used = NOW(),
updated_at = NOW()
WHERE id = $1
"#,
)
.bind(id)
.bind(quality_score)
.execute(&self.pool)
.await?;
Ok(())
}
pub async fn create_skill(&self, skill: AgentSkill) -> Result<AgentSkill> {
let result = sqlx::query_as::<_, AgentSkill>(
r#"
INSERT INTO agent_skill
(project_id, agent_id, name, description, enabled)
VALUES ($1, $2, $3, $4, $5)
RETURNING *
"#,
)
.bind(&skill.project_id)
.bind(&skill.agent_id)
.bind(&skill.name)
.bind(&skill.description)
.bind(skill.enabled)
.fetch_one(&self.pool)
.await?;
Ok(result)
}
pub async fn get_skill(&self, id: Uuid) -> Result<Option<AgentSkill>> {
let result = sqlx::query_as::<_, AgentSkill>(
"SELECT * FROM agent_skill WHERE id = $1"
)
.bind(id)
.fetch_optional(&self.pool)
.await?;
Ok(result)
}
pub async fn list_skills(&self, project_id: &str, agent_id: &str) -> Result<Vec<AgentSkill>> {
let results = sqlx::query_as::<_, AgentSkill>(
"SELECT * FROM agent_skill WHERE project_id = $1 AND agent_id = $2 AND enabled = true ORDER BY created_at DESC"
)
.bind(project_id)
.bind(agent_id)
.fetch_all(&self.pool)
.await?;
Ok(results)
}
pub async fn create_decision(&self, decision: AgentDecision) -> Result<AgentDecision> {
let result = sqlx::query_as::<_, AgentDecision>(
r#"
INSERT INTO agent_decision
(project_id, agent_id, action, reasoning, confidence, tool, task)
VALUES ($1, $2, $3, $4, $5, $6, $7)
RETURNING *
"#,
)
.bind(&decision.project_id)
.bind(&decision.agent_id)
.bind(&decision.action)
.bind(&decision.reasoning)
.bind(decision.confidence)
.bind(&decision.tool)
.bind(&decision.task)
.fetch_one(&self.pool)
.await?;
Ok(result)
}
pub async fn record_decision_outcome(
&self,
id: Uuid,
success: bool,
quality: f32,
feedback: Option<&str>,
) -> Result<()> {
sqlx::query(
r#"
UPDATE agent_decision
SET outcome_success = $2,
outcome_quality = $3,
outcome_feedback = $4,
outcome_recorded_at = NOW(),
updated_at = NOW()
WHERE id = $1
"#,
)
.bind(id)
.bind(success)
.bind(quality)
.bind(feedback)
.execute(&self.pool)
.await?;
Ok(())
}
pub async fn create_role_mapping(&self, mapping: RolePromptMapping) -> Result<RolePromptMapping> {
let result = sqlx::query_as::<_, RolePromptMapping>(
r#"
INSERT INTO role_prompt_mapping
(project_id, role_name, prompt_id, priority, active)
VALUES ($1, $2, $3, $4, $5)
RETURNING *
"#,
)
.bind(&mapping.project_id)
.bind(&mapping.role_name)
.bind(mapping.prompt_id)
.bind(mapping.priority)
.bind(mapping.active)
.fetch_one(&self.pool)
.await?;
Ok(result)
}
pub async fn get_prompts_for_role(&self, project_id: &str, role_name: &str) -> Result<Vec<AgentPrompt>> {
let results = sqlx::query_as::<_, AgentPrompt>(
r#"
SELECT ap.* FROM agent_prompt ap
INNER JOIN role_prompt_mapping rpm ON ap.id = rpm.prompt_id
WHERE rpm.project_id = $1 AND rpm.role_name = $2 AND rpm.active = true
ORDER BY rpm.priority DESC, ap.created_at DESC
"#,
)
.bind(project_id)
.bind(role_name)
.fetch_all(&self.pool)
.await?;
Ok(results)
}
pub async fn save_metrics(&self, metrics: AgentMetrics) -> Result<()> {
sqlx::query(
r#"
INSERT INTO agent_metrics
(project_id, agent_id, requests_total, requests_success, requests_failed,
average_latency_ms, p95_latency_ms, p99_latency_ms, error_rate)
VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9)
ON CONFLICT (project_id, agent_id, DATE(recorded_at)) DO UPDATE SET
requests_total = EXCLUDED.requests_total,
requests_success = EXCLUDED.requests_success,
requests_failed = EXCLUDED.requests_failed,
average_latency_ms = EXCLUDED.average_latency_ms,
p95_latency_ms = EXCLUDED.p95_latency_ms,
p99_latency_ms = EXCLUDED.p99_latency_ms,
error_rate = EXCLUDED.error_rate
"#,
)
.bind(&metrics.project_id)
.bind(&metrics.agent_id)
.bind(metrics.requests_total)
.bind(metrics.requests_success)
.bind(metrics.requests_failed)
.bind(metrics.average_latency_ms)
.bind(metrics.p95_latency_ms)
.bind(metrics.p99_latency_ms)
.bind(metrics.error_rate)
.execute(&self.pool)
.await?;
Ok(())
}
pub async fn log_prompt_usage(
&self,
project_id: &str,
prompt_id: Uuid,
agent_id: Option<&str>,
model: Option<&str>,
input_tokens: Option<i32>,
output_tokens: Option<i32>,
quality_score: Option<f32>,
duration_ms: i64,
error_message: Option<&str>,
) -> Result<()> {
sqlx::query(
r#"
INSERT INTO prompt_usage_log
(project_id, prompt_id, agent_id, model_used, input_tokens, output_tokens,
quality_score, duration_ms, error_message)
VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9)
"#,
)
.bind(project_id)
.bind(prompt_id)
.bind(agent_id)
.bind(model)
.bind(input_tokens)
.bind(output_tokens)
.bind(quality_score)
.bind(duration_ms)
.bind(error_message)
.execute(&self.pool)
.await?;
Ok(())
}
}
+1
View File
@@ -1,6 +1,7 @@
use chrono::{DateTime, Utc};
use sqlx::PgPool;
use uuid::Uuid;
use serde_json::json;
/// Minimal audit logger - records version snapshots on mutation
#[derive(Clone)]
-1
View File
@@ -8,7 +8,6 @@ pub mod edge_repo;
pub mod community_repo;
pub mod versioning;
pub mod audit_logger;
pub mod agent_repo;
// pub mod db_repo; // TODO: Fix Entity schema integration
pub use event_log::{EventRecord, LogWriter};
+1 -69
View File
@@ -218,74 +218,6 @@ pub async fn init_schema(pool: &PgPool) -> Result<()> {
.execute(pool)
.await?;
// Memory entity table (temporal knowledge graph)
sqlx::query(
r#"
CREATE TABLE IF NOT EXISTS memory_entity (
id UUID PRIMARY KEY DEFAULT gen_random_uuid(),
project_id VARCHAR(255) NOT NULL,
name VARCHAR(500) NOT NULL,
name_embedding VECTOR(768),
summary TEXT,
description TEXT,
summary_embedding VECTOR(768),
entity_type VARCHAR(50),
t_created TIMESTAMPTZ DEFAULT NOW(),
t_updated TIMESTAMPTZ DEFAULT NOW(),
t_expired TIMESTAMPTZ,
confidence FLOAT DEFAULT 1.0,
source_count INT DEFAULT 1,
source_episodes UUID[] DEFAULT '{}',
access_count BIGINT DEFAULT 0,
last_accessed TIMESTAMPTZ,
UNIQUE(project_id, name)
)
"#,
)
.execute(pool)
.await?;
sqlx::query("CREATE INDEX IF NOT EXISTS idx_entity_project ON memory_entity(project_id)")
.execute(pool)
.await?;
sqlx::query("CREATE INDEX IF NOT EXISTS idx_entity_type ON memory_entity(project_id, entity_type)")
.execute(pool)
.await?;
// Memory edge table (temporal knowledge graph)
sqlx::query(
r#"
CREATE TABLE IF NOT EXISTS memory_edge (
id UUID PRIMARY KEY DEFAULT gen_random_uuid(),
project_id VARCHAR(255) NOT NULL,
source_id UUID NOT NULL,
target_id UUID NOT NULL,
relation_type VARCHAR(100) NOT NULL,
fact TEXT NOT NULL,
fact_embedding VECTOR(768),
t_valid TIMESTAMPTZ,
t_invalid TIMESTAMPTZ,
t_created TIMESTAMPTZ DEFAULT NOW(),
t_expired TIMESTAMPTZ,
confidence FLOAT DEFAULT 1.0,
contradiction_status VARCHAR(20) DEFAULT 'active',
contradiction_confidence FLOAT
)
"#,
)
.execute(pool)
.await?;
sqlx::query("CREATE INDEX IF NOT EXISTS idx_edge_project ON memory_edge(project_id)")
.execute(pool)
.await?;
sqlx::query("CREATE INDEX IF NOT EXISTS idx_edge_source ON memory_edge(source_id)")
.execute(pool)
.await?;
sqlx::query("CREATE INDEX IF NOT EXISTS idx_edge_target ON memory_edge(target_id)")
.execute(pool)
.await?;
tracing::info!("Database schema initialized (including memory_entity + memory_edge)");
tracing::info!("Database schema initialized");
Ok(())
}
+103 -26
View File
@@ -1,16 +1,15 @@
use serde::{Deserialize, Serialize};
use sqlx::{PgPool, FromRow};
use sqlx::PgPool;
use uuid::Uuid;
use chrono::{DateTime, Utc};
#[derive(Debug, Clone, Serialize, Deserialize, FromRow)]
#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct VersionSnapshot {
pub version_num: i32,
pub operation: String, // 'create' | 'update' | 'delete'
pub snapshot: serde_json::Value,
pub changed_at: DateTime<Utc>,
pub changed_by: String,
#[sqlx(default)]
pub fields_changed: Vec<String>,
}
@@ -41,7 +40,8 @@ impl EntityVersioningService {
/// Get all versions of an entity in descending order
pub async fn get_versions(&self, entity_id: &str) -> Result<Vec<VersionSnapshot>, sqlx::Error> {
sqlx::query_as::<_, VersionSnapshot>(
sqlx::query_as!(
VersionSnapshot,
r#"
SELECT
version_num,
@@ -49,13 +49,13 @@ impl EntityVersioningService {
snapshot,
changed_at,
changed_by,
COALESCE(fields_changed, '{}') as fields_changed
COALESCE(fields_changed, '{}') as "fields_changed!"
FROM memory_entity_version
WHERE entity_id = $1
ORDER BY version_num DESC
"#,
entity_id
)
.bind(entity_id)
.fetch_all(&self.pool)
.await
}
@@ -66,7 +66,8 @@ impl EntityVersioningService {
entity_id: &str,
version_num: i32,
) -> Result<Option<VersionSnapshot>, sqlx::Error> {
sqlx::query_as::<_, VersionSnapshot>(
sqlx::query_as!(
VersionSnapshot,
r#"
SELECT
version_num,
@@ -74,13 +75,13 @@ impl EntityVersioningService {
snapshot,
changed_at,
changed_by,
COALESCE(fields_changed, '{}') as fields_changed
COALESCE(fields_changed, '{}') as "fields_changed!"
FROM memory_entity_version
WHERE entity_id = $1 AND version_num = $2
"#,
entity_id,
version_num
)
.bind(entity_id)
.bind(version_num)
.fetch_optional(&self.pool)
.await
}
@@ -94,7 +95,78 @@ impl EntityVersioningService {
) -> Result<DiffResult, sqlx::Error> {
let from_snap = self.get_version(entity_id, from_v).await?;
let to_snap = self.get_version(entity_id, to_v).await?;
compute_diff(from_snap, to_snap, from_v, to_v)
let from_obj = from_snap
.as_ref()
.and_then(|s| s.snapshot.as_object())
.map(|o| o.clone());
let to_obj = to_snap
.as_ref()
.and_then(|s| s.snapshot.as_object())
.map(|o| o.clone());
let mut added = Vec::new();
let mut removed = Vec::new();
let mut modified = Vec::new();
// Check removed and modified
if let Some(ref from) = from_obj {
for (key, from_val) in from {
if let Some(to) = &to_obj {
if let Some(to_val) = to.get(key) {
if from_val != to_val {
modified.push(DiffField {
name: key.clone(),
from_value: Some(from_val.clone()),
to_value: Some(to_val.clone()),
});
}
} else {
removed.push(DiffField {
name: key.clone(),
from_value: Some(from_val.clone()),
to_value: None,
});
}
} else {
removed.push(DiffField {
name: key.clone(),
from_value: Some(from_val.clone()),
to_value: None,
});
}
}
}
// Check added
if let Some(to) = to_obj {
for (key, to_val) in to {
if let Some(from) = &from_obj {
if !from.contains_key(&key) {
added.push(DiffField {
name: key,
from_value: None,
to_value: Some(to_val),
});
}
} else {
added.push(DiffField {
name: key,
from_value: None,
to_value: Some(to_val),
});
}
}
}
Ok(DiffResult {
from_version: from_v,
to_version: to_v,
added_fields: added,
removed_fields: removed,
modified_fields: modified,
})
}
/// Get entity state at a point in time
@@ -103,7 +175,8 @@ impl EntityVersioningService {
entity_id: &str,
as_of: DateTime<Utc>,
) -> Result<Option<VersionSnapshot>, sqlx::Error> {
sqlx::query_as::<_, VersionSnapshot>(
sqlx::query_as!(
VersionSnapshot,
r#"
SELECT
version_num,
@@ -111,15 +184,15 @@ impl EntityVersioningService {
snapshot,
changed_at,
changed_by,
COALESCE(fields_changed, '{}') as fields_changed
COALESCE(fields_changed, '{}') as "fields_changed!"
FROM memory_entity_version
WHERE entity_id = $1 AND changed_at <= $2
ORDER BY version_num DESC
LIMIT 1
"#,
entity_id,
as_of
)
.bind(entity_id)
.bind(as_of)
.fetch_optional(&self.pool)
.await
}
@@ -137,7 +210,8 @@ impl EdgeVersioningService {
/// Get all versions of an edge
pub async fn get_versions(&self, edge_id: Uuid) -> Result<Vec<VersionSnapshot>, sqlx::Error> {
sqlx::query_as::<_, VersionSnapshot>(
sqlx::query_as!(
VersionSnapshot,
r#"
SELECT
version_num,
@@ -145,13 +219,13 @@ impl EdgeVersioningService {
snapshot,
changed_at,
changed_by,
COALESCE(fields_changed, '{}') as fields_changed
COALESCE(fields_changed, '{}') as "fields_changed!"
FROM memory_edge_version
WHERE edge_id = $1
ORDER BY version_num DESC
"#,
edge_id
)
.bind(edge_id)
.fetch_all(&self.pool)
.await
}
@@ -163,7 +237,8 @@ impl EdgeVersioningService {
from_v: i32,
to_v: i32,
) -> Result<DiffResult, sqlx::Error> {
let from_snap = sqlx::query_as::<_, VersionSnapshot>(
let from_snap = sqlx::query_as!(
VersionSnapshot,
r#"
SELECT
version_num,
@@ -171,17 +246,18 @@ impl EdgeVersioningService {
snapshot,
changed_at,
changed_by,
COALESCE(fields_changed, '{}') as fields_changed
COALESCE(fields_changed, '{}') as "fields_changed!"
FROM memory_edge_version
WHERE edge_id = $1 AND version_num = $2
"#,
edge_id,
from_v
)
.bind(edge_id)
.bind(from_v)
.fetch_optional(&self.pool)
.await?;
let to_snap = sqlx::query_as::<_, VersionSnapshot>(
let to_snap = sqlx::query_as!(
VersionSnapshot,
r#"
SELECT
version_num,
@@ -189,16 +265,17 @@ impl EdgeVersioningService {
snapshot,
changed_at,
changed_by,
COALESCE(fields_changed, '{}') as fields_changed
COALESCE(fields_changed, '{}') as "fields_changed!"
FROM memory_edge_version
WHERE edge_id = $1 AND version_num = $2
"#,
edge_id,
to_v
)
.bind(edge_id)
.bind(to_v)
.fetch_optional(&self.pool)
.await?;
// Same diff logic as entities
compute_diff(from_snap, to_snap, from_v, to_v)
}
}
-21
View File
@@ -1,21 +0,0 @@
version: '3.8'
services:
postgres-test:
image: postgres:16-alpine
environment:
POSTGRES_USER: app
POSTGRES_PASSWORD: testpass
POSTGRES_DB: memory
ports:
- "5433:5432"
volumes:
- postgres-test-data:/var/lib/postgresql/data
healthcheck:
test: ["CMD-SHELL", "pg_isready -U app -d memory"]
interval: 2s
timeout: 5s
retries: 10
volumes:
postgres-test-data:
-157
View File
@@ -1,157 +0,0 @@
# Poimen Memory - Environment Configuration Guide
All downstream service URIs are read from environment variables, sourced from ConfigMap.
## How It Works
1. **ConfigMap provides URIs**: `k8s/app/config.yaml` (production, SOPS-encrypted)
2. **Deployment injects via envFrom**: `envFrom: configMapRef: poimen-memory-config`
3. **Application reads from ENV**: Code parses `LLM_ENDPOINT`, `OPENSEARCH_HOST`, `AUTHENTIK_ISSUER`, etc.
```yaml
# deployment.yaml
envFrom:
- configMapRef:
name: poimen-memory-config # All vars injected as ENV
```
## Environment Variables
### LLM Service (Entity & Fact Extraction)
- `LLM_ENDPOINT` — full URL to chat/completions endpoint
- `LLM_API_BASE` — base API URL (used for client initialization)
- `LLM_MODEL` — model identifier (ornith:35b, qwen:7b, etc.)
- `LLM_TIMEOUT_SECS` — timeout for LLM requests
- `ENABLE_LLM_EXTRACTION` — enable/disable LLM extraction (true/false)
### OpenSearch (Vector Store, BM25)
- `OPENSEARCH_HOST` — hostname:port
- `OPENSEARCH_SCHEME` — http or https
- `OPENSEARCH_VERIFY_CERTS` — SSL certificate verification (true/false)
### Authentik (OIDC)
- `AUTHENTIK_ISSUER` — OIDC issuer URL
- `AUTHENTIK_VERIFY_SSL` — SSL certificate verification (true/false)
- `MEM_AUTH_MODE` — auth mode: jwt | apikey | none
### Temporal (Workflow Orchestration - Future)
- `TEMPORAL_ENDPOINT` — temporal frontend hostname:port
- `TEMPORAL_NAMESPACE` — temporal namespace
### API Gateway (Route Optimization - Future)
- `GATEWAY_URL` — gateway base URL
### Memory Service Config
- `MEM_AUTH_MODE` — jwt | apikey | none
- `MEM_RATE_LIMIT_INGEST` — ingest requests per second
- `MEM_RATE_LIMIT_QUERY` — query requests per second
- `MEM_EMBEDDING_BATCH_SIZE` — batch size for embeddings
---
## Deployment Scenarios
### Production (SOPS-Encrypted ConfigMap)
**File**: `k8s/app/config.yaml`
Services use cluster-internal DNS:
```yaml
LLM_ENDPOINT: http://reasoning-predictor.llm-serving.svc.cluster.local:8000/v1/chat/completions
OPENSEARCH_HOST: opensearch.poimen.svc.cluster.local:9200
AUTHENTIK_ISSUER: https://authentik.auth.svc.cluster.local:9443/application/o/poimen/
TEMPORAL_ENDPOINT: temporal-frontend.temporal.svc.cluster.local:7233
GATEWAY_URL: http://api-gw.poimen.svc.cluster.local:8080
MEM_AUTH_MODE: jwt
```
**Deploy**:
```bash
# SOPS auto-decrypts based on .sops.yaml age key
kubectl apply -f k8s/app/config.yaml -k k8s/app/
```
### Local/Development (Plaintext ConfigMap)
**File**: `k8s/app/config.local.yaml`
Services via external URLs (ingress):
```yaml
LLM_ENDPOINT: https://api.riotpiao.com/v1/chat/completions
OPENSEARCH_HOST: opensearch.riotpiao.com:443
AUTHENTIK_ISSUER: https://authentik.riotpiao.com/application/o/poimen/
TEMPORAL_ENDPOINT: temporal.riotpiao.com:443
GATEWAY_URL: https://api.riotpiao.com
MEM_AUTH_MODE: none
```
**Deploy** (override production config):
```bash
# Delete prod config, apply local
kubectl delete configmap poimen-memory-config -n poimen
kubectl apply -f k8s/app/config.local.yaml
```
---
## Encrypting with SOPS
Production `config.yaml` is encrypted with SOPS (Age-based).
**Encrypt**:
```bash
sops -e k8s/app/config.yaml > k8s/app/config.yaml.enc
mv k8s/app/config.yaml.enc k8s/app/config.yaml
```
**Decrypt for editing** (SOPS auto-handles with $EDITOR):
```bash
sops k8s/app/config.yaml
```
**View decrypted** (without editing):
```bash
sops -d k8s/app/config.yaml
```
**.sops.yaml** defines encryption key:
```yaml
creation_rules:
- path_regex: k8s/app/config.yaml
key_groups:
- age:
- <age-public-key>
```
---
## Application Code Pattern
Example: Application should read URIs from ENV at startup.
```rust
// Pseudocode
let llm_endpoint = env::var("LLM_ENDPOINT")
.unwrap_or("http://localhost:11434/v1/chat/completions".to_string());
let opensearch_host = env::var("OPENSEARCH_HOST")
.unwrap_or("localhost:9200".to_string());
let auth_mode = env::var("MEM_AUTH_MODE")
.unwrap_or("none".to_string());
// Initialize clients with these URIs
let llm_client = LlmClient::new(llm_endpoint)?;
let search_client = OpenSearchClient::new(opensearch_host)?;
```
---
## Summary
| Aspect | Production | Local |
|--------|-----------|-------|
| **Config File** | `config.yaml` | `config.local.yaml` |
| **Encryption** | SOPS (Age) | Plaintext |
| **Service URIs** | Cluster-internal DNS | External HTTPS |
| **Auth Mode** | JWT (Authentik) | None (disabled) |
| **Rate Limits** | 100/1000 | 1000/10000 |
| **Deploy** | `kubectl apply -k k8s/app/` | `kubectl apply -f config.local.yaml` |
-47
View File
@@ -1,47 +0,0 @@
# Local/Development configuration (plaintext, external URLs via ingress)
# Use this instead of config.yaml for local testing
# kubectl apply -f config.local.yaml
apiVersion: v1
kind: ConfigMap
metadata:
name: poimen-memory-config
namespace: poimen
labels:
app.kubernetes.io/name: poimen-memory
app.kubernetes.io/component: config
data:
# Auth mode: jwt | apikey | none (disabled for local testing)
MEM_AUTH_MODE: "none"
# Rate limiting (higher for testing)
MEM_RATE_LIMIT_INGEST: "1000"
MEM_RATE_LIMIT_QUERY: "10000"
MEM_IDEMPOTENCY_TTL_SECS: "86400"
# Embeddings
MEM_EMBEDDING_BATCH_SIZE: "32"
# Downstream services - external URLs via ingress
# LLM Service (via api.riotpiao.com ingress)
LLM_ENDPOINT: "https://api.riotpiao.com/v1/chat/completions"
LLM_API_BASE: "https://api.riotpiao.com/v1"
LLM_MODEL: "qwen:7b"
LLM_TIMEOUT_SECS: "60"
ENABLE_LLM_EXTRACTION: "true"
# OpenSearch (via ingress)
OPENSEARCH_HOST: "opensearch.riotpiao.com:443"
OPENSEARCH_SCHEME: "https"
OPENSEARCH_VERIFY_CERTS: "true"
# Authentik (via ingress - optional for local)
AUTHENTIK_ISSUER: "https://authentik.riotpiao.com/application/o/poimen/"
AUTHENTIK_VERIFY_SSL: "true"
# Temporal (via ingress)
TEMPORAL_ENDPOINT: "temporal.riotpiao.com:443"
TEMPORAL_NAMESPACE: "poimen"
# API Gateway (via ingress)
GATEWAY_URL: "https://api.riotpiao.com"
+11 -32
View File
@@ -1,7 +1,5 @@
# Production environment configuration for poimen-memory
# All services use cluster-internal DNS names
# This file is encrypted with SOPS in production
# For local dev, use plaintext version with external URLs
# Non-sensitive environment variables for poimen-memory
# Change these without redeploying secrets.
apiVersion: v1
kind: ConfigMap
metadata:
@@ -11,39 +9,20 @@ metadata:
app.kubernetes.io/name: poimen-memory
app.kubernetes.io/component: config
data:
# Auth mode: jwt | apikey | none
MEM_AUTH_MODE: "jwt"
# Auth mode: jwt | apikey
MEM_AUTH_MODE: "none"
# Rate limiting
MEM_RATE_LIMIT_INGEST: "100"
MEM_RATE_LIMIT_QUERY: "1000"
MEM_IDEMPOTENCY_TTL_SECS: "86400"
# Embeddings
MEM_EMBEDDING_BATCH_SIZE: "32"
# Downstream services - read by application from ENV
# Internal cluster DNS (prod) / external URLs (local)
# LLM Service (entity extraction, fact extraction)
LLM_ENDPOINT: "http://reasoning-predictor.llm-serving.svc.cluster.local:8000/v1/chat/completions"
LLM_API_BASE: "http://reasoning-predictor.llm-serving.svc.cluster.local:8000/v1"
LLM_MODEL: "ornith:35b"
# OpenSearch
OPENSEARCH_HOST: "opensearch.poimen.svc.cluster.local:9200"
# Obsidian
OBSIDIAN_URL: "http://obsidian-server.poimen.svc.cluster.local:8080"
# LLM Configuration (for entity extraction)
LLM_ENDPOINT: "http://api-internal.riotpiao.com:8000/v1/chat/completions"
LLM_MODEL: "qwen:7b"
LLM_TIMEOUT_SECS: "30"
ENABLE_LLM_EXTRACTION: "true"
# OpenSearch (vector store, BM25 retrieval)
OPENSEARCH_HOST: "opensearch.poimen.svc.cluster.local:9200"
OPENSEARCH_SCHEME: "http"
OPENSEARCH_VERIFY_CERTS: "false"
# Authentik (OIDC provider)
AUTHENTIK_ISSUER: "https://authentik.auth.svc.cluster.local:9443/application/o/poimen/"
AUTHENTIK_VERIFY_SSL: "false"
# Temporal (workflow orchestration - future)
TEMPORAL_ENDPOINT: "temporal-frontend.temporal.svc.cluster.local:7233"
TEMPORAL_NAMESPACE: "poimen"
# API Gateway (external queue, route optimization - future)
GATEWAY_URL: "http://api-gw.poimen.svc.cluster.local:8080"
+9 -27
View File
@@ -1,6 +1,6 @@
# Poimen Memory API Server
# Serves HTTP endpoints for memory ingest, query, visualization.
# Connects to memory-db (pgvector) + api.riotpiao.com (LLM via Authentik JWT).
# Serves 7 HTTP endpoints for memory ingest, query, and management.
# Connects to memory-db (pgvector) for persistent storage.
apiVersion: apps/v1
kind: Deployment
metadata:
@@ -60,43 +60,24 @@ spec:
key: password
- name: DATABASE_URL
value: "postgresql://$(DATABASE_USER):$(DATABASE_PASSWORD)@$(DATABASE_HOST):$(DATABASE_PORT)/$(DATABASE_NAME)?sslmode=disable"
# All downstream service URIs read from ConfigMap
# (LLM_ENDPOINT, LLM_API_BASE, LLM_MODEL, OPENSEARCH_HOST, etc.)
# These are injected via envFrom below
# Authentik service account (memory-agent-oidc secret)
# Only needed if MEM_AUTH_MODE=jwt in ConfigMap
- name: AUTHENTIK_CLIENT_ID
valueFrom:
secretKeyRef:
name: memory-agent-oidc
key: CLIENT_ID
- name: AUTHENTIK_CLIENT_SECRET
valueFrom:
secretKeyRef:
name: memory-agent-oidc
key: CLIENT_SECRET
- name: TOKEN_URL
valueFrom:
secretKeyRef:
name: memory-agent-oidc
key: TOKEN_URL
# Server config
# LLM Gateway API key
- name: MEM_API_KEY
valueFrom:
secretKeyRef:
name: poimen-memory-secrets
key: llm-api-key
# Server config (from ConfigMap)
- name: MEM_PORT
value: "8080"
- name: MEM_HOME
value: "/tmp"
envFrom:
# ConfigMap with all service URIs (prod: encrypted, local: plaintext)
- configMapRef:
name: poimen-memory-config
- secretRef:
name: poimen-memory-auth
- secretRef:
name: poimen-memory-secrets
command: ["/app/mem"]
args:
- serve
@@ -130,6 +111,7 @@ spec:
- name: tmp
emptyDir:
sizeLimit: 64Mi
# Tolerate control-plane nodes
tolerations:
- key: node-role.kubernetes.io/control-plane
operator: Exists
+5 -4
View File
@@ -1,12 +1,13 @@
apiVersion: kustomize.config.k8s.io/v1beta1
kind: Kustomization
namespace: poimen
resources:
# vault-pvc.yaml removed — memory service uses pgvector, not local storage
- deployment.yaml
- service.yaml
- config.yaml # Production config (SOPS-encrypted)
- tekton-pipeline.yaml
- config.yaml
- obsidian.yaml
# Legacy secret managed separately
# - secrets.yaml
generators:
- secret-generator.yaml
+24
View File
@@ -0,0 +1,24 @@
apiVersion: ENC[AES256_GCM,data:gSI=,iv:nfXxHTEXSY6eDPOLfQWxQaX/Ge7s08QF6GqQ847cdKg=,tag:szUjeOolHuomGQQdrV7U4A==,type:str]
kind: ENC[AES256_GCM,data:HC8zcR8G,iv:wk4XliU5bPi32M0QV6OhJs3tSkirOczWJjR+1MgjxpM=,tag:jcD8R327PRv8x7wYh4Tdrg==,type:str]
metadata:
name: ENC[AES256_GCM,data:HouUGg1P3iPycnr5doLc9w==,iv:kzODDxNBix4e/kAGrF8io165crqPHewyuG8MCZhr3mM=,tag:hX9peWSY5LwM7/08S+QLuw==,type:str]
namespace: ENC[AES256_GCM,data:OCIDOqNz,iv:GhtxD5cXXTnl/7Po1rY3I+jacI9Kz4bXp+Nz2UVTOTE=,tag:F7TuNLkSluKm4TZZ1Q33VQ==,type:str]
type: ENC[AES256_GCM,data:ErqH5L3k,iv:JioZqat2ZYSO83vEnl1MY6YiCC3RttfEkGc2OumJHBY=,tag:K68wmCX8sMzcnGUz1aBpWA==,type:str]
stringData:
id_ed25519: ENC[AES256_GCM,data:YqrAUmZCvEDC2q8c4Ns+WxW2l+oC31arj1MPYwt6AkIv026kZk9ucywkOWT/Ww0VgiUWF/0t/gzkm7K5D5fSk5vP6PyWV5Zqvlo8Zqy1VBLc3V9gbQeCsA4i8+FO3zZ0k2l3HAefEqhJ4Bnj3dKDOTX4bsbE/H/4n8WCojYnOLdU4esqm5r4bOCnFv5wBkbkob6AwfqekdaBZfuPOqW2sstDSRN6km1UZafCYuMY0XQTxCKYM8Izt3px8sfBq37oA6syDpxNuEpAk0uYumHhSBHKRAnsDY61pjfCbR2xy/3IeEPr6EVf5HwV+2ElhtSB/Zfzin5GZvAgX3gu3HuFznHUYH5olLEEFvVtw8fWLh3avwwCsAlUsDKZoTV1t1bzGni1OPYK3ZfsAmQqI1lvdFlRj++e6L3vDBkVG5qowTelbSb6/TWMDpJw/CsX3bgeKEoFUt2vi9IxwdYO/onuExVrT23WeanoSmrnXRaBqr6xIV5yW5CCbBBRmRU7a6jkwtkhe8dHFTKejaqjBpzPdlZOvhzKBHlOy4eDGjeV7CkzrRw=,iv:bSGkeMli13DSDFAu1+4Kg5sqSJ8LbdpLfN5oIwzLyTM=,tag:9DYK17ET7rkfmmpwxjicog==,type:str]
known_hosts: ENC[AES256_GCM,data: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,iv:mv3hoMwPcEmOBbsIRoKLUuEsUolotv1VtikLiItwuJg=,tag:7amQiuiaVwowLAQcNoq72A==,type:str]
sops:
age:
- enc: |
-----BEGIN AGE ENCRYPTED FILE-----
YWdlLWVuY3J5cHRpb24ub3JnL3YxCi0+IFgyNTUxOSBINTF2OGRmUWoxTmFEZUdv
SWJKRlFhaVkzbUtOaTVnbHFjd1UzR2RFdVFNClpFODhlQVJIQjhlOEJBL2pDVmJa
UjlZZmFHKzA4eDJEMk9KTDMyOGZ2VWcKLS0tIFRHREo1dXNRKzJVYkROQSt1WjFV
ZXZYVjAwSlZhT0ZMbG1qNDVUWnJyQ2cKfs4t6HsQG5Wiyp6QvFqvm4+/o4NAL3qu
6L9vyhl2jufrbxmR+IsEBCxYS7rh6dCbxTUFap3MD2lYIGF9hRnGjQ==
-----END AGE ENCRYPTED FILE-----
recipient: age1e5fq3hwxy78psus2nfvmtmua36g0u3suk78ephw6246l974d2utsvn0hla
lastmodified: "2026-08-28T23:27:09Z"
mac: ENC[AES256_GCM,data:wJC6YCHXq6I/bqUjfwFRvpULZ1Yt39PoWFKzzOAq6h/pHsUrWEgrkm+3+dLaPpz663b0B75BiCQjQb4igXWr38O5I+FKonRHsbsH+D+pO+dq++yNYG8T30KGaquVfnsm8ijWGWxOY9nULUXfKcYfqvsR9P7KCV7bdcWuZ5xzZ5o=,iv:w5f3h0hb2ooeNYK1QZactpmpT8mAYa94V8FBewP0MUY=,tag:qlgUutFanhjk1HIBJqmLQg==,type:str]
unencrypted_suffix: _unencrypted
version: 3.13.2
+159
View File
@@ -0,0 +1,159 @@
---
# Obsidian server deployment
# Serves local vault with web UI and API
apiVersion: apps/v1
kind: Deployment
metadata:
name: obsidian-server
namespace: poimen
labels:
app.kubernetes.io/name: obsidian-server
app.kubernetes.io/part-of: poimen-memory
spec:
replicas: 1
selector:
matchLabels:
app.kubernetes.io/name: obsidian-server
template:
metadata:
labels:
app.kubernetes.io/name: obsidian-server
app.kubernetes.io/part-of: poimen-memory
spec:
serviceAccountName: obsidian-server
securityContext:
runAsNonRoot: true
runAsUser: 1000
runAsGroup: 1000
fsGroup: 1000
seccompProfile:
type: RuntimeDefault
initContainers:
- name: git-sync-init
image: alpine/git:latest
securityContext:
runAsNonRoot: false
runAsUser: 0
allowPrivilegeEscalation: false
capabilities:
drop:
- ALL
add:
- CHOWN
- DAC_OVERRIDE
command:
- sh
- -c
- |
export GIT_SSH_COMMAND="ssh -i /root/.ssh/id_ed25519 -o StrictHostKeyChecking=no"
git config --global --add safe.directory /vault
if [ -d /vault/.git ]; then
cd /vault && git pull origin main || true
else
# Clone into temp, move contents into vault
rm -rf /tmp/repo
git clone ssh://[email protected]:2222/rock/poimen-obesdient-memory.git /tmp/repo
cp -a /tmp/repo/. /vault/
rm -rf /tmp/repo
fi
chown -R 1000:1000 /vault
volumeMounts:
- name: vault
mountPath: /vault
- name: ssh-key
mountPath: /root/.ssh
readOnly: true
containers:
- name: obsidian-server
image: ppatlabs/obsidian:latest
imagePullPolicy: IfNotPresent
securityContext:
allowPrivilegeEscalation: false
capabilities:
drop:
- ALL
ports:
- name: http
containerPort: 27124
protocol: TCP
env:
- name: VAULT_NAME
value: poimen-vault
- name: VAULT_PATH
value: /vault
- name: REST_API_ENABLED
value: "true"
- name: REST_API_PORT
value: "8080"
volumeMounts:
- name: vault
mountPath: /vault
- name: config
mountPath: /config
resources:
requests:
cpu: 100m
memory: 256Mi
limits:
cpu: 500m
memory: 512Mi
livenessProbe:
httpGet:
path: /
port: http
scheme: HTTPS
initialDelaySeconds: 30
periodSeconds: 10
timeoutSeconds: 5
readinessProbe:
httpGet:
path: /
port: http
scheme: HTTPS
initialDelaySeconds: 15
periodSeconds: 5
timeoutSeconds: 5
volumes:
- name: vault
persistentVolumeClaim:
claimName: obsidian-vault
- name: config
emptyDir: {}
- name: ssh-key
secret:
secretName: obsidian-git-ssh
defaultMode: 0400
# PVC managed by homelab repo (k8s/infra/databases/obsidian-vault-pvc.yaml)
---
# Service for Obsidian server
apiVersion: v1
kind: Service
metadata:
name: obsidian-server
namespace: poimen
labels:
app.kubernetes.io/name: obsidian-server
spec:
type: ClusterIP
ports:
- name: http
port: 80
targetPort: 27124
protocol: TCP
selector:
app.kubernetes.io/name: obsidian-server
---
# ServiceAccount for Obsidian
apiVersion: v1
kind: ServiceAccount
metadata:
name: obsidian-server
namespace: poimen
labels:
app.kubernetes.io/name: obsidian-server
# Ingress managed by homelab repo (obsidian.riotpiao.com)
# See: homelab/k8s/bootstrap/ingress/ingress.yaml
-121
View File
@@ -1,121 +0,0 @@
---
# Tekton Pipeline: poimen-ci
# Runs smoke tests against the live service after image push.
# Referenced by .gitea/workflows/build.yaml CI.
apiVersion: tekton.dev/v1
kind: Pipeline
metadata:
name: poimen-ci
namespace: poimen
spec:
params:
- name: image
type: string
- name: registry-user
type: string
default: ""
- name: registry-token
type: string
default: ""
tasks:
- name: integration-tests
taskRef:
name: poimen-integration-test
params:
- name: image
value: $(params.image)
- name: gate-on-tests
runAfter:
- integration-tests
taskSpec:
steps:
- name: check
image: alpine:latest
script: |
echo "Integration tests passed"
---
# Tekton Task: smoke test against live poimen-memory service
apiVersion: tekton.dev/v1
kind: Task
metadata:
name: poimen-integration-test
namespace: poimen
spec:
params:
- name: image
type: string
results:
- name: summary
type: string
steps:
- name: test
image: curlimages/curl:latest
env:
- name: DB_PASSWORD
valueFrom:
secretKeyRef:
key: password
name: memory-db-app
script: |
#!/bin/sh
set -e
SVC="http://poimen-memory.poimen.svc.cluster.local:8080"
PASS=0; FAIL=0
echo "=== Smoke Test: poimen-memory ==="
# 1. Health
echo "1. GET /health"
if curl -sf "$SVC/health" | grep -q '"status":"ok"'; then
echo " PASS"; PASS=$((PASS+1))
else
echo " FAIL"; FAIL=$((FAIL+1))
fi
# 2. Projects
echo "2. GET /memory/projects"
if curl -sf "$SVC/memory/projects" | grep -q '"projects"'; then
echo " PASS"; PASS=$((PASS+1))
else
echo " FAIL"; FAIL=$((FAIL+1))
fi
# 3. Ingest
echo "3. POST /memory/ingest"
ID="smoke-$(date +%s)"
RESP=$(curl -sf -X POST "$SVC/memory/ingest" \
-H "Content-Type: application/json" \
-d "{\"project\":\"ci-smoke\",\"source\":\"tekton\",\"ingest_id\":\"$ID\",\"records\":[{\"role\":\"user\",\"text\":\"[[Kubernetes]] uses [[Docker]]\",\"timestamp\":\"2026-01-01T00:00:00Z\",\"source_position\":0}]}")
if echo "$RESP" | grep -q '"status"'; then
echo " PASS"; PASS=$((PASS+1))
else
echo " FAIL"; FAIL=$((FAIL+1))
fi
sleep 3
# 4. Poll status
echo "4. GET /memory/ingest/$ID"
if curl -sf "$SVC/memory/ingest/$ID" | grep -q '"status"'; then
echo " PASS"; PASS=$((PASS+1))
else
echo " FAIL"; FAIL=$((FAIL+1))
fi
# 5. Query
echo "5. GET /memory/query"
if curl -sf "$SVC/memory/query?project=ci-smoke&question=Docker" | grep -q '"project"'; then
echo " PASS"; PASS=$((PASS+1))
else
echo " FAIL"; FAIL=$((FAIL+1))
fi
echo ""
echo "Result: $PASS passed, $FAIL failed"
if [ $FAIL -eq 0 ]; then
echo "PASS: $PASS/$((PASS+FAIL))" > /tekton/results/summary
else
echo "FAIL: $FAIL/$((PASS+FAIL))" > /tekton/results/summary
exit 1
fi
-1
View File
@@ -6,4 +6,3 @@ kind: Kustomization
resources:
- memory-db.yaml
- opensearch.yaml
- opensearch-secrets.enc.yaml
+38 -16
View File
@@ -1,6 +1,8 @@
# Dedicated CNPG Postgres for Poimen Memory (GitOps, wave 2).
# Matches homelab/k8s/infra/databases/memory-db.yaml — single source of truth.
# CNPG generates secret `memory-db-app` + service `memory-db-rw` in ns poimen.
---
# CNPG Postgres cluster for Poimen Memory system (GitOps, declarative extensions).
# 2 instances, pgvector 0.7.0 via spec.extensions (not manual CREATE EXTENSION).
# Storage: 10Gi longhorn, consistent with temporal-db.yaml.
# No manual psql needed — all via git/ArgoCD.
apiVersion: postgresql.cnpg.io/v1
kind: Cluster
metadata:
@@ -9,24 +11,15 @@ metadata:
annotations:
argocd.argoproj.io/sync-options: SkipDryRunOnMissingResource=true
spec:
instances: 3
instances: 2
imageName: ghcr.io/cloudnative-pg/postgresql:16.2
bootstrap:
initdb:
database: memory
owner: app
encoding: UTF8
localeCollate: C
localeCType: C
postInitApplicationSQL:
- "CREATE EXTENSION vector;"
enableSuperuserAccess: false
storage:
size: 10Gi
storageClass: longhorn
resources:
requests: { memory: "512Mi", cpu: "250m" }
limits: { memory: "2Gi", cpu: "1" }
storage:
size: 20Gi
storageClass: longhorn
affinity:
podAntiAffinityType: preferred
topologyKey: kubernetes.io/hostname
@@ -34,3 +27,32 @@ spec:
- key: node-role.kubernetes.io/control-plane
operator: Exists
effect: NoSchedule
bootstrap:
initdb:
database: memory
owner: app
encoding: UTF8
localeCollate: C
localeCType: C
monitoring:
enabled: true
podMonitorTemplate:
spec:
interval: 30s
scrapeTimeout: 10s
---
# Database resource with pgvector extension (declarative, git-managed).
# CNPG 1.30.0+ supports this via spec.extensions on the Database CRD.
# Ensures pgvector is installed and available for HNSW indexing.
apiVersion: postgresql.cnpg.io/v1
kind: Database
metadata:
name: memory
namespace: poimen
spec:
cluster:
name: memory-db
owner: app
extensions:
- name: vector
ensure: present
@@ -1,47 +0,0 @@
apiVersion: ENC[AES256_GCM,data:qM0=,iv:znTNMu1+efRh38Vn0GWlNZTk/6VjCJfJeaEzbM17N8c=,tag:sPSc9mwoZWYvjD1bzM+uzg==,type:str]
kind: ENC[AES256_GCM,data:pHDYbqGy,iv:8kUzizuj3tkgx8FU19FBr8lcz1DFEN2abQTJCFLPL0w=,tag:YqiHCVZ8Pwyx51YkxLSykQ==,type:str]
metadata:
name: ENC[AES256_GCM,data:yC5ph8jQnEd2Jn60tCNYJQq2,iv:QRAhTVXNt77kcbcLXDJo9Y1X3hRu1EZXADwTS3rPq/g=,tag:X80UnBGCV28GiOWNo3K/bA==,type:str]
namespace: ENC[AES256_GCM,data:7N36Xqio,iv:a8yemv8LA1WdXUyNRgTu5teZIB23ClufXh7ovd9m5GU=,tag:ukU63zxVZdD9PwppgAmaEw==,type:str]
type: ENC[AES256_GCM,data:9NGNI47z,iv:tiaioFpXheBY4BimysI3sr5OzFOEI1mG68ObCDiqAIU=,tag:wpEln7lSyAPfxpVjcWhpVg==,type:str]
stringData:
admin-password: ENC[AES256_GCM,data:HeKM7q8662fdrlJbpWh/7VJuhr7h2sRYK6/sN+eBtBo=,iv:4ur6YKAYp6+kvIkmBcx9/0DK2MvK7XDedoZhKl8gjBY=,tag:pct7MAlre1h7bm8Polvutg==,type:str]
sops:
age:
- enc: |
-----BEGIN AGE ENCRYPTED FILE-----
YWdlLWVuY3J5cHRpb24ub3JnL3YxCi0+IFgyNTUxOSBGV2NJQzhDN0ZacXBDeklV
aGE1eGlmMkp6b1RDL2ZiblNwSk1PUkJZdFZjCi84dWpXMFNNcFYrLzkwOUFGZDZ4
SGM0NG9UMkJTME82dUU0MkxFNjVzcTAKLS0tIE5xNlg2RUdheUxyUytsblI3UTFH
UktjaHNGOUlmZGxiSlhoSkJSMW5LMkkKdNAzdge1HaAgBqbE4dCkJgZBlIAP76P+
4GOsh7RbuVDDMzUHTS4aNv2zoM5WC5pv+ZKtf8Yu7LIwiOPAp2u/7g==
-----END AGE ENCRYPTED FILE-----
recipient: age1e5fq3hwxy78psus2nfvmtmua36g0u3suk78ephw6246l974d2utsvn0hla
lastmodified: "2026-09-12T14:22:55Z"
mac: ENC[AES256_GCM,data:lO+5lWN4ZVIkg4XAG4mz6n2SxqNfU6KdahoZqj9nZ33maX/9OT7aunwl3eIoE8JlN4vN1UU/s0l1ioT0+PxdGtlQfhisZ0ypzA3z8Nxkcw18XzQaMf99A0Icw1OEGRRx/T6Bf8+l0ZI4HIH+KZmlUg2lAfGK+WTxqr5xJefw5XA=,iv:kWNox9QX7Jv9muHjBo6yuwRjBRuhawaKJ+5+O9E57z4=,tag:qZ+5ceNo2C8cPIt0PBtqiw==,type:str]
unencrypted_suffix: _unencrypted
version: 3.13.2
---
apiVersion: ENC[AES256_GCM,data:jew=,iv:bzrjT8rJssrSv4xZCn9ihNtyelKteybg/XZVJRUawvo=,tag:qN50XwBiN2lnWH1CS35W/g==,type:str]
kind: ENC[AES256_GCM,data:clwtkPLP,iv:Y2sF8dpOJslo4OHeRprK/wcuvUzdOW30Bz3M0Kh8yE4=,tag:TkQo8zZZow/zdAlxViWQlA==,type:str]
metadata:
name: ENC[AES256_GCM,data:UiOyRh0x7Yor3qudRqgwtrv5bBHkHnFMK0Smxw==,iv:a3hB+wBIMjD0Xj7p3ZIqDf3/la1xlzbCYRRc/LV80ig=,tag:ivw42aZepKgOa+cVm0URZg==,type:str]
namespace: ENC[AES256_GCM,data:a37Jp+qA,iv:cDVuBJ/aFo4EcZTC/N9NGk8UdrCROHKiirWBWlrSDMQ=,tag:/LNyMpSaEhgQYIE8PJcXBg==,type:str]
type: ENC[AES256_GCM,data:ql+XYM25,iv:OCfk13+9Ft4Vq6Tq3R6v54zK1tz7imzyr/g8ytcpBEk=,tag:PpJBFsUSpMo3ktGynr8AUw==,type:str]
stringData:
password: ENC[AES256_GCM,data:lT7f3cY+VLqRcfuYnf9lnI5QVqfmmt5pc9tb2EEuRbE=,iv:2Dnwssmj5ddcr4UypVVkm4UydeLc1L/ExsaRsbu/CVw=,tag:6++s/j3MOBIirkKS66Z46Q==,type:str]
sops:
age:
- enc: |
-----BEGIN AGE ENCRYPTED FILE-----
YWdlLWVuY3J5cHRpb24ub3JnL3YxCi0+IFgyNTUxOSBGV2NJQzhDN0ZacXBDeklV
aGE1eGlmMkp6b1RDL2ZiblNwSk1PUkJZdFZjCi84dWpXMFNNcFYrLzkwOUFGZDZ4
SGM0NG9UMkJTME82dUU0MkxFNjVzcTAKLS0tIE5xNlg2RUdheUxyUytsblI3UTFH
UktjaHNGOUlmZGxiSlhoSkJSMW5LMkkKdNAzdge1HaAgBqbE4dCkJgZBlIAP76P+
4GOsh7RbuVDDMzUHTS4aNv2zoM5WC5pv+ZKtf8Yu7LIwiOPAp2u/7g==
-----END AGE ENCRYPTED FILE-----
recipient: age1e5fq3hwxy78psus2nfvmtmua36g0u3suk78ephw6246l974d2utsvn0hla
lastmodified: "2026-09-12T14:22:55Z"
mac: ENC[AES256_GCM,data:lO+5lWN4ZVIkg4XAG4mz6n2SxqNfU6KdahoZqj9nZ33maX/9OT7aunwl3eIoE8JlN4vN1UU/s0l1ioT0+PxdGtlQfhisZ0ypzA3z8Nxkcw18XzQaMf99A0Icw1OEGRRx/T6Bf8+l0ZI4HIH+KZmlUg2lAfGK+WTxqr5xJefw5XA=,iv:kWNox9QX7Jv9muHjBo6yuwRjBRuhawaKJ+5+O9E57z4=,tag:qZ+5ceNo2C8cPIt0PBtqiw==,type:str]
unencrypted_suffix: _unencrypted
version: 3.13.2
+35 -8
View File
@@ -65,7 +65,8 @@ data:
# Cluster settings
cluster.name: poimen-memory
node.name: ${HOSTNAME}
discovery.type: single-node
cluster.initial_master_nodes: opensearch-0
discovery.seed_hosts: opensearch-0.opensearch.poimen.svc.cluster.local
# Network
network.host: 0.0.0.0
@@ -126,12 +127,16 @@ spec:
spec:
serviceAccountName: opensearch
hostNetwork: false
securityContext:
fsGroup: 1000
tolerations:
- key: node-role.kubernetes.io/control-plane
operator: Exists
effect: NoSchedule
initContainers:
- name: sysctl
image: busybox:1.28
command:
- sysctl
- -w
- vm.max_map_count=262144
securityContext:
privileged: true
containers:
- name: opensearch
@@ -395,6 +400,18 @@ spec:
---
# Secret: OpenSearch Dashboards password
apiVersion: v1
kind: Secret
metadata:
name: opensearch-dashboards-secret
namespace: poimen
type: Opaque
stringData:
password: "admin" # ⚠️ Change in production
---
# ServiceAccount for OpenSearch Dashboards
apiVersion: v1
kind: ServiceAccount
@@ -402,4 +419,14 @@ metadata:
name: opensearch-dashboards
namespace: poimen
# Secrets moved to opensearch-secrets.enc.yaml (SOPS-encrypted)
---
# Secret for OpenSearch Admin Password
apiVersion: v1
kind: Secret
metadata:
name: opensearch-secrets
namespace: poimen
type: Opaque
stringData:
admin-password: "OpenSearch@Admin123!"
-131
View File
@@ -1,131 +0,0 @@
{
"annotations": { "list": [] },
"editable": true,
"fiscalYearStartMonth": 0,
"graphTooltip": 0,
"id": null,
"links": [],
"panels": [
{
"title": "Ingest Rate (req/s)",
"type": "timeseries",
"gridPos": { "h": 8, "w": 12, "x": 0, "y": 0 },
"targets": [
{ "expr": "rate(memory_ingest_requests_total[5m])", "legendFormat": "ingest req/s" }
]
},
{
"title": "Query Rate (req/s)",
"type": "timeseries",
"gridPos": { "h": 8, "w": 12, "x": 12, "y": 0 },
"targets": [
{ "expr": "rate(memory_query_requests_total[5m])", "legendFormat": "query req/s" }
]
},
{
"title": "Ingest Latency (p50/p95/p99)",
"type": "timeseries",
"gridPos": { "h": 8, "w": 12, "x": 0, "y": 8 },
"targets": [
{ "expr": "histogram_quantile(0.5, rate(memory_ingest_duration_seconds_bucket[5m]))", "legendFormat": "p50" },
{ "expr": "histogram_quantile(0.95, rate(memory_ingest_duration_seconds_bucket[5m]))", "legendFormat": "p95" },
{ "expr": "histogram_quantile(0.99, rate(memory_ingest_duration_seconds_bucket[5m]))", "legendFormat": "p99" }
]
},
{
"title": "Query Latency (p50/p95/p99)",
"type": "timeseries",
"gridPos": { "h": 8, "w": 12, "x": 12, "y": 8 },
"targets": [
{ "expr": "histogram_quantile(0.5, rate(memory_query_duration_seconds_bucket[5m]))", "legendFormat": "p50" },
{ "expr": "histogram_quantile(0.95, rate(memory_query_duration_seconds_bucket[5m]))", "legendFormat": "p95" },
{ "expr": "histogram_quantile(0.99, rate(memory_query_duration_seconds_bucket[5m]))", "legendFormat": "p99" }
]
},
{
"title": "Error Rates",
"type": "timeseries",
"gridPos": { "h": 8, "w": 12, "x": 0, "y": 16 },
"targets": [
{ "expr": "rate(memory_ingest_errors_total[5m])", "legendFormat": "ingest errors" },
{ "expr": "rate(memory_query_errors_total[5m])", "legendFormat": "query errors" },
{ "expr": "rate(memory_query_embedding_failures_total[5m])", "legendFormat": "embedding failures" }
]
},
{
"title": "Embedding Latency",
"type": "timeseries",
"gridPos": { "h": 8, "w": 12, "x": 12, "y": 16 },
"targets": [
{ "expr": "histogram_quantile(0.5, rate(memory_query_embedding_duration_seconds_bucket[5m]))", "legendFormat": "p50" },
{ "expr": "histogram_quantile(0.95, rate(memory_query_embedding_duration_seconds_bucket[5m]))", "legendFormat": "p95" }
]
},
{
"title": "DB Row Counts",
"type": "stat",
"gridPos": { "h": 4, "w": 12, "x": 0, "y": 24 },
"targets": [
{ "expr": "memory_db_table_entity_rows", "legendFormat": "entities" },
{ "expr": "memory_db_table_edge_rows", "legendFormat": "edges" },
{ "expr": "memory_db_table_chunk_rows", "legendFormat": "chunks" }
]
},
{
"title": "Dependency Health",
"type": "stat",
"gridPos": { "h": 4, "w": 12, "x": 12, "y": 24 },
"targets": [
{ "expr": "memory_dependency_db_up", "legendFormat": "DB" },
{ "expr": "memory_dependency_embedding_up", "legendFormat": "Embedding" },
{ "expr": "memory_dependency_opensearch_up", "legendFormat": "OpenSearch" },
{ "expr": "memory_dependency_llm_up", "legendFormat": "LLM" }
]
},
{
"title": "DB Pool Stats",
"type": "timeseries",
"gridPos": { "h": 8, "w": 12, "x": 0, "y": 28 },
"targets": [
{ "expr": "memory_db_pool_size", "legendFormat": "pool size" },
{ "expr": "memory_db_pool_idle", "legendFormat": "idle" },
{ "expr": "memory_db_pool_active", "legendFormat": "active" }
]
},
{
"title": "Relevance Metrics",
"type": "timeseries",
"gridPos": { "h": 8, "w": 12, "x": 12, "y": 28 },
"targets": [
{ "expr": "memory_relevance_precision", "legendFormat": "precision" },
{ "expr": "memory_relevance_recall", "legendFormat": "recall" },
{ "expr": "memory_relevance_f1_score", "legendFormat": "F1" }
]
},
{
"title": "In-Flight Operations",
"type": "timeseries",
"gridPos": { "h": 8, "w": 12, "x": 0, "y": 36 },
"targets": [
{ "expr": "memory_ingest_in_flight", "legendFormat": "ingest" },
{ "expr": "memory_query_in_flight", "legendFormat": "query" }
]
},
{
"title": "Write Volume",
"type": "timeseries",
"gridPos": { "h": 8, "w": 12, "x": 12, "y": 36 },
"targets": [
{ "expr": "rate(memory_write_entities_total[5m])", "legendFormat": "entities/s" },
{ "expr": "rate(memory_write_edges_total[5m])", "legendFormat": "edges/s" },
{ "expr": "rate(memory_write_chunks_total[5m])", "legendFormat": "chunks/s" }
]
}
],
"schemaVersion": 39,
"tags": ["poimen", "memory", "observability"],
"templating": { "list": [] },
"time": { "from": "now-1h", "to": "now" },
"title": "Poimen Memory Observability",
"uid": "poimen-memory-obs"
}
-130
View File
@@ -1,130 +0,0 @@
# Prometheus alerting rules for Poimen Memory (O12)
# Deploy: kubectl apply -f k8s/infra/prometheus-alerts.yaml
apiVersion: monitoring.coreos.com/v1
kind: PrometheusRule
metadata:
name: poimen-memory-alerts
namespace: poimen
labels:
app: poimen-memory
prometheus: k8s
role: alert-rules
spec:
groups:
- name: poimen-memory.availability
rules:
- alert: MemoryServiceDown
expr: up{job="poimen-memory"} == 0
for: 2m
labels:
severity: critical
annotations:
summary: "Poimen memory service is down"
description: "Memory service has been unreachable for > 2 minutes"
- alert: MemoryDBDown
expr: memory_dependency_db_up == 0
for: 1m
labels:
severity: critical
annotations:
summary: "Memory service cannot reach database"
description: "DB dependency health check failing for > 1 minute"
- alert: MemoryEmbeddingDown
expr: memory_dependency_embedding_up == 0
for: 5m
labels:
severity: warning
annotations:
summary: "Embedding service unreachable"
description: "Embedding dependency health check failing for > 5 minutes"
- name: poimen-memory.latency
rules:
- alert: MemoryIngestLatencyHigh
expr: histogram_quantile(0.95, rate(memory_ingest_duration_seconds_bucket[5m])) > 5
for: 5m
labels:
severity: warning
annotations:
summary: "Ingest p95 latency > 5s"
description: "95th percentile ingest latency is {{ $value }}s"
- alert: MemoryQueryLatencyHigh
expr: histogram_quantile(0.95, rate(memory_query_duration_seconds_bucket[5m])) > 2
for: 5m
labels:
severity: warning
annotations:
summary: "Query p95 latency > 2s"
description: "95th percentile query latency is {{ $value }}s"
- alert: MemoryEmbeddingLatencyHigh
expr: histogram_quantile(0.95, rate(memory_query_embedding_duration_seconds_bucket[5m])) > 10
for: 5m
labels:
severity: warning
annotations:
summary: "Embedding p95 latency > 10s"
description: "95th percentile embedding call latency is {{ $value }}s"
- name: poimen-memory.errors
rules:
- alert: MemoryIngestErrorRateHigh
expr: rate(memory_ingest_errors_total[5m]) / rate(memory_ingest_requests_total[5m]) > 0.1
for: 5m
labels:
severity: warning
annotations:
summary: "Ingest error rate > 10%"
description: "{{ $value | humanizePercentage }} of ingest requests are failing"
- alert: MemoryQueryErrorRateHigh
expr: rate(memory_query_errors_total[5m]) / rate(memory_query_requests_total[5m]) > 0.1
for: 5m
labels:
severity: warning
annotations:
summary: "Query error rate > 10%"
description: "{{ $value | humanizePercentage }} of query requests are failing"
- alert: MemoryEmbeddingFailureRate
expr: rate(memory_query_embedding_failures_total[5m]) > 0.5
for: 3m
labels:
severity: critical
annotations:
summary: "Embedding failures > 0.5/s"
description: "Embedding service failing at {{ $value }}/s — queries cannot embed"
- name: poimen-memory.storage
rules:
- alert: MemoryDBPoolExhausted
expr: memory_db_pool_idle == 0
for: 5m
labels:
severity: warning
annotations:
summary: "DB connection pool exhausted"
description: "No idle DB connections for > 5 minutes"
- alert: MemoryWriteErrorsHigh
expr: rate(memory_write_errors_total[5m]) > 1
for: 5m
labels:
severity: warning
annotations:
summary: "Write errors > 1/s"
description: "Database write errors at {{ $value }}/s"
- name: poimen-memory.quality
rules:
- alert: MemoryRelevanceLow
expr: memory_relevance_precision < 0.3
for: 15m
labels:
severity: warning
annotations:
summary: "Retrieval relevance precision < 30%"
description: "Relevance precision is {{ $value | humanizePercentage }}"
-94
View File
@@ -1,94 +0,0 @@
# CronJob for periodic relevance evaluation (O13)
# Runs sample queries against memory service and evaluates result relevance
# Pushes metrics to Prometheus via pushgateway or direct scrape
apiVersion: batch/v1
kind: CronJob
metadata:
name: memory-relevance-eval
namespace: poimen
labels:
app: memory-relevance-eval
spec:
# Run every 6 hours
schedule: "0 */6 * * *"
successfulJobsHistoryLimit: 3
failedJobsHistoryLimit: 1
jobTemplate:
spec:
template:
metadata:
labels:
app: memory-relevance-eval
spec:
securityContext:
runAsNonRoot: true
runAsUser: 1000
seccompProfile:
type: RuntimeDefault
containers:
- name: eval
image: curlimages/curl:8.13.0
securityContext:
allowPrivilegeEscalation: false
capabilities:
drop: ["ALL"]
command:
- /bin/sh
- -c
- |
MEMORY_URL="http://poimen-memory.poimen.svc.cluster.local:8080"
echo "=== Relevance evaluation at $(date) ==="
# Sample queries for evaluation
QUERIES='[
"kubernetes deployment",
"database migration",
"LLM entity extraction",
"tea cli forgejo",
"SOPS encryption secrets"
]'
TOTAL=0
RELEVANT=0
for q in "kubernetes deployment" "database migration" "LLM entity extraction"; do
echo "Testing query: $q"
RESULT=$(curl -s --max-time 30 -X POST "$MEMORY_URL/memory/query" \
-H "Content-Type: application/json" \
-d "{\"query\": \"$q\", \"search_type\": \"entities\", \"top_k\": 5}")
COUNT=$(echo "$RESULT" | grep -o '"total_count":[0-9]*' | cut -d: -f2)
TOTAL=$((TOTAL + 1))
if [ "${COUNT:-0}" -gt 0 ]; then
RELEVANT=$((RELEVANT + 1))
echo " Result: $COUNT results (relevant)"
else
echo " Result: 0 results (irrelevant)"
fi
done
PRECISION=$(echo "scale=2; $RELEVANT / $TOTAL" | bc 2>/dev/null || echo "0")
echo ""
echo "=== Summary ==="
echo "Total queries: $TOTAL"
echo "Queries with results: $RELEVANT"
echo "Precision: $PRECISION"
echo ""
echo "=== Health check ==="
curl -s "$MEMORY_URL/health"
echo ""
echo "=== Metrics snapshot ==="
curl -s "$MEMORY_URL/metrics" | grep -E "^memory_(query|relevance|ingest)_" | head -20
resources:
requests:
cpu: 10m
memory: 16Mi
limits:
cpu: 50m
memory: 32Mi
restartPolicy: OnFailure
-121
View File
@@ -1,121 +0,0 @@
# CronJob to periodically clean Gitea Actions runner disk space
# Prevents "no space left on device" errors during Docker builds
# Deploy to: kubectl apply -f k8s/infra/runner-cleanup-cronjob.yaml
apiVersion: batch/v1
kind: CronJob
metadata:
name: runner-disk-cleanup
namespace: ci # Adjust to your runner namespace
labels:
app: runner-cleanup
spec:
# Run daily at 2 AM
schedule: "0 2 * * *"
# Keep last 3 successful jobs
successfulJobsHistoryLimit: 3
failedJobsHistoryLimit: 1
jobTemplate:
spec:
template:
metadata:
labels:
app: runner-cleanup
spec:
serviceAccountName: runner-cleanup
# Run on node with Gitea Actions runner
affinity:
nodeAffinity:
requiredDuringSchedulingIgnoredDuringExecution:
nodeSelectorTerms:
- matchExpressions:
- key: kubernetes.io/hostname
operator: In
values:
- runner-node # Adjust to your runner node name
containers:
- name: cleanup
image: docker:24
securityContext:
privileged: true # Needed to access Docker daemon
command:
- /bin/sh
- -c
- |
echo "=== Runner disk cleanup at $(date) ==="
df -h /
echo ""
echo "Cleaning Docker..."
docker system prune -af --volumes 2>&1 | tail -5
echo ""
echo "Cleaning Cargo cache..."
rm -rf /root/.cargo/registry/cache 2>/dev/null
rm -rf /root/.cargo/registry/index 2>/dev/null
rm -rf /root/.cargo/git 2>/dev/null
echo ""
echo "Cleaning /tmp..."
rm -rf /tmp/* 2>/dev/null
echo ""
echo "Disk after cleanup:"
df -h /
volumeMounts:
- name: docker-sock
mountPath: /var/run/docker.sock
- name: runner-home
mountPath: /root
volumes:
# Access Docker daemon on host
- name: docker-sock
hostPath:
path: /var/run/docker.sock
# Access runner home directory
- name: runner-home
hostPath:
path: /home/runner # Adjust to your runner home path
restartPolicy: OnFailure
---
# ServiceAccount for cleanup job
apiVersion: v1
kind: ServiceAccount
metadata:
name: runner-cleanup
namespace: ci
---
# Role for cleanup job
apiVersion: rbac.authorization.k8s.io/v1
kind: ClusterRole
metadata:
name: runner-cleanup
rules:
- apiGroups: [""]
resources: ["nodes"]
verbs: ["get", "list"]
---
# RoleBinding
apiVersion: rbac.authorization.k8s.io/v1
kind: ClusterRoleBinding
metadata:
name: runner-cleanup
roleRef:
apiGroup: rbac.authorization.k8s.io
kind: ClusterRole
name: runner-cleanup
subjects:
- kind: ServiceAccount
name: runner-cleanup
namespace: ci
-136
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@@ -1,136 +0,0 @@
---
# ClusterRole for CI/Tekton triggers to deploy and manage resources across cluster
apiVersion: rbac.authorization.k8s.io/v1
kind: ClusterRole
metadata:
name: ci-tekton-trigger
rules:
# Tekton resources
- apiGroups: ["tekton.dev"]
resources: ["pipelineruns", "taskruns", "pipelines", "tasks"]
verbs: ["create", "get", "list", "watch", "patch", "update", "delete"]
# Deployments and pods
- apiGroups: ["apps"]
resources: ["deployments", "statefulsets", "daemonsets"]
verbs: ["get", "list", "watch", "create", "patch", "update"]
- apiGroups: [""]
resources: ["pods", "pods/log", "pods/status"]
verbs: ["get", "list", "watch"]
# Services and networking
- apiGroups: [""]
resources: ["services", "endpoints"]
verbs: ["get", "list", "watch"]
# ConfigMaps and Secrets
- apiGroups: [""]
resources: ["configmaps", "secrets"]
verbs: ["get", "list", "watch"]
# Events
- apiGroups: [""]
resources: ["events"]
verbs: ["create", "patch"]
# Namespaces
- apiGroups: [""]
resources: ["namespaces"]
verbs: ["get", "list", "watch"]
# Persistent volumes
- apiGroups: [""]
resources: ["persistentvolumeclaims", "persistentvolumes"]
verbs: ["get", "list", "watch"]
---
# ClusterRoleBinding for ci-tekton-trigger service account
apiVersion: rbac.authorization.k8s.io/v1
kind: ClusterRoleBinding
metadata:
name: ci-tekton-trigger
roleRef:
apiGroup: rbac.authorization.k8s.io
kind: ClusterRole
name: ci-tekton-trigger
subjects:
- kind: ServiceAccount
name: ci-tekton-trigger
namespace: api
---
# Additional ClusterRole for poimen namespace operations
apiVersion: rbac.authorization.k8s.io/v1
kind: Role
metadata:
name: ci-tekton-trigger-poimen
namespace: poimen
rules:
# Allow full access in poimen namespace for CI
- apiGroups: ["*"]
resources: ["*"]
verbs: ["*"]
---
# RoleBinding in poimen namespace
apiVersion: rbac.authorization.k8s.io/v1
kind: RoleBinding
metadata:
name: ci-tekton-trigger-poimen
namespace: poimen
roleRef:
apiGroup: rbac.authorization.k8s.io
kind: Role
name: ci-tekton-trigger-poimen
subjects:
- kind: ServiceAccount
name: ci-tekton-trigger
namespace: api
---
# RoleBinding in tekton-pipelines namespace
apiVersion: rbac.authorization.k8s.io/v1
kind: RoleBinding
metadata:
name: ci-tekton-trigger
namespace: tekton-pipelines
roleRef:
apiGroup: rbac.authorization.k8s.io
kind: ClusterRole
name: ci-tekton-trigger
subjects:
- kind: ServiceAccount
name: ci-tekton-trigger
namespace: api
---
# RoleBinding in llm-serving namespace (for LLM checks)
apiVersion: rbac.authorization.k8s.io/v1
kind: RoleBinding
metadata:
name: ci-tekton-trigger
namespace: llm-serving
roleRef:
apiGroup: rbac.authorization.k8s.io
kind: ClusterRole
name: ci-tekton-trigger
subjects:
- kind: ServiceAccount
name: ci-tekton-trigger
namespace: api
---
# RoleBinding in kube-system namespace (for cluster info)
apiVersion: rbac.authorization.k8s.io/v1
kind: RoleBinding
metadata:
name: ci-tekton-trigger
namespace: kube-system
roleRef:
apiGroup: rbac.authorization.k8s.io
kind: ClusterRole
name: ci-tekton-trigger
subjects:
- kind: ServiceAccount
name: ci-tekton-trigger
namespace: api
-131
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@@ -1,131 +0,0 @@
apiVersion: tekton.dev/v1
kind: Task
metadata:
name: agent-memory-migration
namespace: tekton-pipelines
spec:
description: Apply agent memory schema migration (004) to production database
params:
- name: migration-version
description: Migration version number
default: "004"
- name: database-name
description: Database name
default: "memory"
workspaces:
- name: source
description: Git source with migrations
- name: db-credentials
description: Database credentials secret
steps:
- name: apply-migration
image: postgres:16-alpine
workingDir: $(workspaces.source.path)
env:
- name: PGPASSWORD
valueFrom:
secretKeyRef:
name: memory-db-app
key: password
- name: PGHOST
value: memory-db-rw.poimen.svc.cluster.local
- name: PGUSER
value: app
- name: PGDATABASE
value: $(params.database-name)
script: |
#!/bin/sh
set -e
echo "Applying migration $(params.migration-version)_agent_memory_schema.sql"
# Wait for database to be ready
until pg_isready -h $PGHOST -U $PGUSER -d $PGDATABASE; do
echo "Waiting for database..."
sleep 2
done
# Apply migration
psql -h $PGHOST -U $PGUSER -d $PGDATABASE \
-f migrations/$(params.migration-version)_agent_memory_schema.sql
# Verify tables created
TABLES=$(psql -h $PGHOST -U $PGUSER -d $PGDATABASE -t -c \
"SELECT count(*) FROM information_schema.tables WHERE table_schema='public' AND table_name IN ('agent_prompt', 'agent_skill', 'agent_decision', 'role_prompt_mapping', 'agent_metrics')")
if [ "$TABLES" -eq 5 ]; then
echo "✓ All agent memory tables created successfully"
exit 0
else
echo "✗ Migration failed: expected 5 tables, found $TABLES"
exit 1
fi
- name: verify-indexes
image: postgres:16-alpine
env:
- name: PGPASSWORD
valueFrom:
secretKeyRef:
name: memory-db-app
key: password
- name: PGHOST
value: memory-db-rw.poimen.svc.cluster.local
- name: PGUSER
value: app
- name: PGDATABASE
value: $(params.database-name)
script: |
#!/bin/sh
set -e
echo "Verifying indexes..."
INDEXES=$(psql -h $PGHOST -U $PGUSER -d $PGDATABASE -t -c \
"SELECT count(*) FROM pg_indexes WHERE schemaname='public' AND tablename LIKE 'agent_%'")
if [ "$INDEXES" -gt 0 ]; then
echo "✓ Found $INDEXES indexes on agent tables"
psql -h $PGHOST -U $PGUSER -d $PGDATABASE -c \
"SELECT indexname FROM pg_indexes WHERE schemaname='public' AND tablename LIKE 'agent_%' ORDER BY indexname;"
else
echo "✗ No indexes found on agent tables"
exit 1
fi
- name: verify-schemas
image: postgres:16-alpine
env:
- name: PGPASSWORD
valueFrom:
secretKeyRef:
name: memory-db-app
key: password
- name: PGHOST
value: memory-db-rw.poimen.svc.cluster.local
- name: PGUSER
value: app
- name: PGDATABASE
value: $(params.database-name)
script: |
#!/bin/sh
set -e
echo "Verifying table schemas..."
# Verify agent_prompt table
psql -h $PGHOST -U $PGUSER -d $PGDATABASE -c "
SELECT column_name, data_type, is_nullable
FROM information_schema.columns
WHERE table_name='agent_prompt'
ORDER BY ordinal_position;"
echo "✓ Agent prompt schema verified"
# Verify role_prompt_mapping has foreign key
psql -h $PGHOST -U $PGUSER -d $PGDATABASE -c "
SELECT constraint_name, constraint_type
FROM information_schema.table_constraints
WHERE table_name='role_prompt_mapping';"
echo "✓ All table schemas verified"
-76
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@@ -1,76 +0,0 @@
---
# PipelineRun: Agent Memory Feature Testing
# Tests role-to-prompt mapping with API Platform Engineer role requirements
# Runs migrations, integration tests, and validates all constraints
apiVersion: tekton.dev/v1
kind: PipelineRun
metadata:
name: agent-memory-test-run
namespace: poimen
generateName: agent-memory-test-
spec:
pipelineRef:
name: poimen-ci
params:
- name: image
value: "forgejo.riotpiao.com/riotpiao-poimen/poimen-memory:latest"
- name: registry-user
value: "riotpiao-poimen"
- name: registry-token
value: "${FORGEJO_REGISTRY_TOKEN}" # Injected by ArgoCD/SOPS
workspaces:
- name: source
emptyDir: {} # Or use PVC for persistent builds
serviceAccountName: tekton-builder
timeouts:
pipeline: "1h"
tasks: "30m"
---
# ServiceAccount for Tekton Pipeline (builder with DB access)
apiVersion: v1
kind: ServiceAccount
metadata:
name: tekton-builder
namespace: poimen
---
# ClusterRoleBinding: Allow pipeline to query database via pod exec
apiVersion: rbac.authorization.k8s.io/v1
kind: ClusterRoleBinding
metadata:
name: tekton-builder-db-access
roleRef:
apiGroup: rbac.authorization.k8s.io
kind: ClusterRole
name: tekton-builder-db-access
subjects:
- kind: ServiceAccount
name: tekton-builder
namespace: poimen
---
# ClusterRole: Database access for migrations
apiVersion: rbac.authorization.k8s.io/v1
kind: ClusterRole
metadata:
name: tekton-builder-db-access
rules:
- apiGroups: [""]
resources: ["pods"]
verbs: ["get", "list"]
- apiGroups: [""]
resources: ["pods/exec"]
verbs: ["create"]
- apiGroups: [""]
resources: ["secrets"]
resourceNames: ["memory-db-app"]
verbs: ["get"]
- apiGroups: [""]
resources: ["services"]
verbs: ["get", "list"]

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