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4c275525e9
Workflow Input Structure:
├─ question: User content for reasoning
├─ project: Project ID for scoping
├─ operations: Flags for link_entities, infer_facts, reason_query, summarize
└─ llm_activity: Configuration for LLMInferenceActivity
├─ model: Selected based on complexity (reasoning|ornith:35b|qwen2.5:3b)
├─ system_prompt: Task-specific instruction (Zep-backed)
├─ user_prompt: Content to process
├─ temperature: 0.7 (reasoning) or 0.5 (validation)
└─ max_tokens: 2048 (reasoning) or 512 (validation)
Model Selection:
├─ reason_query=true, summarize=true → reasoning (DeepSeek-R1, complex)
├─ reason_query=true, summarize=false → ornith:35b (medium)
└─ reason_query=false → qwen2.5:3b (fast, <100ms)
System Prompts (handlers/llm_prompts.rs):
├─ entity_extraction_system_prompt(): Extract entities + relationships + facts
├─ reasoning_system_prompt(): Step-by-step reasoning + answers
├─ agent_capability_validation_prompt(): Validate agent capabilities
└─ fact_validation_system_prompt(): Detect contradictions
Workflow Activity Execution:
├─ Temporal receives workflow input with llm_activity config
├─ ReasoningWorkflow orchestrates:
│ ├─ Activity 1: RetrieveMemory (optional context)
│ ├─ Activity 2: LLMInferenceActivity (calls /v1/chat/completions via gateway)
│ │ └─ Retries: 3× with backoff (2s, 4s, 8s)
│ │ └─ Timeout: 120s
│ │ └─ JWT propagation: Authorization: Bearer header
│ ├─ Activity 3: PersistResults (save to memory_entity/memory_edge)
│ └─ Activity 4: SummarizeFindings (return results)
├─ Memory handler polls DESCRIBE_WORKFLOW (30× with 100ms delay, 3s timeout)
└─ Returns ReasoningResult with answers, confidence, reasoning_steps
Changes:
├─ execute_reasoning_workflow(): Build llm_activity config with model selection
├─ select_llm_model(): Choose model based on operation complexity
├─ build_system_prompt(): Use Zep-inspired prompts for reasoning
├─ handlers/llm_prompts.rs: Centralized prompt templates (5 system + 4 user builders)
├─ AgentInitialization: Include llm_activity for capability validation
└─ Fixed duplicate extract_jwt_token call in agent_handler.rs
Activity Contract:
├─ Workflow input includes llm_activity block
├─ Temporal passes to LLMInferenceActivity
├─ Activity substitutes {{ previous_output }} template variables
├─ Activity calls POST /v1/chat/completions with JWT header
├─ Activity returns { response, model, stop_reason, tokens_used }
├─ PersistResults activity stores results to DB
└─ Workflow returns: question, answers[], confidence, reasoning_steps[]
Tests Added:
+ 14 new tests in llm_prompts.rs (prompt validation, user prompt builders)
Compilation: ✅
Poimen Memory System
Production-grade knowledge graph RAG system with semantic search, temporal filtering, community detection, path finding, and faceted search.
Quick Start
# Build
cargo build --release
# Run
cargo run --release -- --config config/default.toml
API Documentation
See API.md for complete endpoint specifications, request/response formats, and usage examples.
Core Endpoints
- POST
/memory/query/semantic/entities— Semantic search with optional community detection, path finding, facet discovery - POST
/memory/query/semantic/edges— Relation search with temporal and facet filters - POST
/memory/query/hybrid— Combined semantic + lexical search (RRF fusion)
Optional Features (via query parameters)
- Temporal Filtering:
start_time,end_time(ISO 8601 datetime) - Community Detection:
detect_communities=true,min_community_size=N - Path Finding:
find_paths=true,target_entity_id=<id>,max_path_depth=N,k_hops=N - Faceted Search:
discover_facets=true,facet_filters={...}
Architecture
crates/mem-cli/src/
├── query/
│ ├── semantic_retriever.rs (vector + lexical search)
│ ├── community_detector.rs (Louvain algorithm)
│ ├── path_finder.rs (BFS/DFS graph traversal)
│ └── faceted_search.rs (multi-dimension filtering)
├── handlers/
│ └── semantic.rs (HTTP endpoints)
└── http_server.rs (Actix-web server)
crates/mem-core/src/
├── domain.rs (data structures)
├── entity.rs, edge.rs (graph entities)
└── scoring.rs (relevance metrics)
crates/mem-store/src/
└── *_repo.rs (database persistence)
Testing
# Run all tests
cargo test --lib
# Run specific test suite
cargo test --lib query::semantic
cargo test --lib handlers::semantic
# With output
cargo test --lib -- --nocapture
Configuration
See config/default.toml for:
- Database connection strings
- JWT authentication settings
- Rate limiting thresholds
- Embeddings model configuration
Production Deployment
- Build release binary:
cargo build --release - Set environment:
JWT_SECRET,DATABASE_URL,OPENAI_API_KEY - Run:
./target/release/mem-cli - Health check:
GET http://localhost:8080/health
Development
Quality Standards:
- CRAP score < 3.2 (low complexity)
- DRY > 98% (minimal duplication)
- SOLID 5.0/5 (excellent design)
- 230+ comprehensive tests (100% pass rate)
- Performance: P50 latency < 500ms
Adding New Features:
- Create core module in
crates/mem-cli/src/query/ - Add optional parameters to request struct
- Extend response with optional field (use
skip_serializing_if) - Add handler logic (delegate to core module)
- Write 25-35 tests (unit + integration)
- Document in API.md
See CLAUDE.md for project context and constraints.