# 🧠 Rust Logic Graph
> **Reasoning Engine for Distributed Backend & AI Orchestration**
[](https://www.rust-lang.org/)
[](https://opensource.org/licenses/MIT)
[](https://github.com/KSD-CO/rust-logic-graph)
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A high-performance **reasoning engine** for distributed backend systems and AI orchestration. Build complex decision workflows, coordinate multiple services, and create intelligent agent systems with **GRL (Grule Rule Language)** support.
**Not a no-code automation tool** - Rust Logic Graph is an embeddable library for developers building distributed reasoning systems, not a UI-first workflow platform like n8n or Zapier.
---
## 🎯 What is Rust Logic Graph?
Rust Logic Graph is a **reasoning engine library** for building intelligent backend systems:
### Core Capabilities
**🧠 Distributed Reasoning**
- Connect decisions across multiple databases and services
- Build complex decision trees with business rules (GRL)
- Maintain context as data flows through your system
- Explain how decisions were reached
**🤖 AI Agent Orchestration**
- Coordinate multiple LLMs in reasoning chains
- Build RAG (Retrieval-Augmented Generation) pipelines
- Create multi-agent systems with tool calling
- Native support for OpenAI, Claude, Ollama, and custom models
**⚡ High-Performance Execution**
- Sub-millisecond latency (embedded library, not service)
- Automatic parallel execution of independent operations
- Memory-efficient context pooling
- Async/await throughout
**🔧 Production-Ready Patterns**
- Circuit breakers for unstable services
- Retry logic with exponential backoff
- Try/catch error handling
- Saga pattern for distributed transactions
### Example Use Cases
```rust
// Financial risk assessment across multiple data sources
let risk_engine = Graph::new()
.add_node("credit_history", DBNode::postgres(...))
.add_node("transaction_analysis", DBNode::mongodb(...))
.add_node("fraud_check", AINode::openai(...))
.add_node("risk_rules", RuleNode::grl("risk_assessment.grl"))
.add_node("decision", ConditionalNode::new(...));
// Multi-step AI reasoning with tool calling
let ai_agent = Graph::new()
.add_node("understand_query", AINode::claude(...))
.add_node("search_knowledge", SubgraphNode::new(rag_pipeline))
.add_node("reason", AINode::openai_gpt4(...))
.add_node("validate", RuleNode::grl("validation.grl"))
.add_retry("reason", max_attempts: 3);
// Microservice coordination with fault tolerance
let order_flow = Graph::new()
.add_node("inventory", GrpcNode::new("inventory-service"))
.add_node("payment", GrpcNode::new("payment-service"))
.add_node("shipping", GrpcNode::new("shipping-service"))
.add_circuit_breaker("payment", threshold: 5)
.add_saga_compensation(...);
```
---
## ✨ Key Features
- 🔥 **GRL Support** - [rust-rule-engine v0.17](https://crates.io/crates/rust-rule-engine)
- 🔄 **Topological Execution** - Automatic DAG-based node ordering
- ⚡ **Async Runtime** - Built on Tokio for high concurrency
- ⚡ **Parallel Execution** - Automatic parallel execution of independent nodes (v0.5.0)
- �️ **Multi-Database Orchestration** - Parallel queries, correlation, distributed transactions (v0.10.0) 🆕
- �💾 **Caching Layer** - High-performance result caching with TTL, eviction policies, and memory limits (v0.5.0)
- 🧠 **Memory Optimization** - Context pooling and allocation tracking (v0.7.0)
- 🛠️ **CLI Developer Tools** - Graph validation, dry-run, profiling, and visualization (v0.5.0)
- 🎨 **Web Graph Editor** - Next.js visual editor with drag-and-drop interface (v0.8.0)
- 📋 **YAML Configuration** - Declarative graph definitions with external config files (v0.8.5)
- 🎯 **Advanced Control Flow** - Subgraphs, conditionals, loops, error handling (v0.9.0)
- 🚨 **Rich Error Messages** - Unique error codes, actionable suggestions, full context (v0.10.0) 🆕
- 📊 **Multiple Node Types** - RuleNode, DBNode, AINode, ConditionalNode, LoopNode, TryCatchNode, RetryNode, CircuitBreakerNode
- 📝 **JSON/YAML Configuration** - Simple workflow definitions
- 🎯 **98% Drools Compatible** - Easy migration from Java
- 🌊 **Streaming Processing** - Stream-based execution with backpressure (v0.3.0)
- 🗄️ **Database Integrations** - PostgreSQL, MySQL, Redis, MongoDB (v0.2.0)
- 🤖 **AI/LLM Integrations** - OpenAI, Claude, Ollama (v0.2.0)
---
## 🚀 Quick Start
### Installation
```toml
[dependencies]
rust-logic-graph = "0.11.0"
# With specific integrations
rust-logic-graph = { version = "0.11.0", features = ["postgres", "openai"] }
# With all integrations
rust-logic-graph = { version = "0.11.0", features = ["all-integrations"] }
```
## 🏢 Real-World Case Study: Purchasing Flow System
Complete production implementation: **[case_study/](case_study/)** - Purchasing automation with **two architectures** (Monolithic vs Microservices).
**Problem**: Automate purchasing decisions across products, warehouses, suppliers.
**Solution**: 15 GRL business rules + rust-logic-graph orchestration.
### Architecture Comparison
| **Performance** | ~10ms (in-process) | ~56ms (gRPC overhead) |
| **Resources** | 50MB RAM, 1 CPU | 500MB RAM, 7 containers |
| **Best For** | <1K req/min, small teams (1-5 devs) | >10K req/min, large teams (15+ devs) |
| **Deployment** | Single binary | Docker Compose / Kubernetes |
| **Scaling** | Vertical only | Horizontal scaling |
| **Complexity** | Simple | Distributed tracing required |
### Quick Start
**Monolithic** (single HTTP service, 4 PostgreSQL DBs):
```bash
cd case_study/monolithic && cargo run --release
curl -X POST http://localhost:8080/purchasing/flow -d '{"product_id": "PROD-001"}'
```
**Microservices** (7 gRPC services):
```bash
cd case_study/microservices && docker compose up -d
curl -X POST http://localhost:8080/api/purchasing/flow -d '{"product_id": "PROD-001"}'
```
### Key Features
**✅ Same Business Logic** - 15 GRL rules shared across both architectures
**✅ YAML Configuration** - Change workflows without recompilation
**✅ Multi-Database** (Monolithic) - 4 separate PostgreSQL databases
**✅ Dynamic Field Mapping** - Zero hardcoded field names
**✅ Graph Executor Pattern** - Declarative node topology
### Architecture Diagrams
**Microservices Communication Flow:**
```
┌─────────────────────────────────────────────────────────────────────┐
│ CLIENT (HTTP REST) │
└────────────────────────────────┬────────────────────────────────────┘
│ POST /api/purchasing/flow
▼
┌────────────────────────────────────────────────────────────┐
│ Orchestrator Service (Port 8080) - main.rs │
│ │
│ HTTP Endpoint → OrchestratorGraphExecutor │
│ │
│ ┌──────────────────────────────────────────────────────┐ │
│ │ rust-logic-graph Graph Executor │ │
│ │ (graph_executor.rs) │ │
│ │ │ │
│ │ Creates Graph with 6 Custom gRPC Nodes: │ │
│ │ ┌────────────────────────────────────────────────┐ │ │
│ │ │ OmsGrpcNode │ │ │
│ │ │ • impl Node trait from rust-logic-graph │ │ │
│ │ │ • async fn run() → gRPC call to :50051 │ │ │
│ │ │ • Returns JSON to Context │ │ │
│ │ └────────────────────────────────────────────────┘ │ │
│ │ ┌────────────────────────────────────────────────┐ │ │
│ │ │ InventoryGrpcNode → gRPC :50052 │ │ │
│ │ │ SupplierGrpcNode → gRPC :50053 │ │ │
│ │ │ UomGrpcNode → gRPC :50054 │ │ │
│ │ │ RuleEngineGrpcNode → gRPC :50056 │ │ │
│ │ │ PoGrpcNode → gRPC :50055 │ │ │
│ │ └────────────────────────────────────────────────┘ │ │
│ │ │ │
│ │ Graph Topology (hardcoded in graph_executor.rs): │ │
│ │ OMS ───────┐ │ │
│ │ Inventory ─┼─→ RuleEngine ──→ PO │ │
│ │ Supplier ──┤ │ │
│ │ UOM ───────┘ │ │
│ │ │ │
│ │ Executor runs in topological order │ │
│ └──────────────────────────────────────────────────────┘ │
└────────┬───────────────────────────────────────────────────┘
│
┌─────────────┼──────────────────┬────────────────┬──────────────┐
│ (Parallel) │ (Parallel) │ (Parallel) │ (Parallel) │
▼ ▼ ▼ ▼ │
┌──────────┐ ┌────────────┐ ┌─────────────┐ ┌───────────┐ │
│OMS :50051│ │Inventory │ │Supplier │ │UOM :50054 │ │
│ (gRPC) │ │:50052 │ │:50053 │ │ (gRPC) │ │
│ │ │ (gRPC) │ │ (gRPC) │ │ │ │
│• History │ │• Levels │ │• Pricing │ │• Convert │ │
│• Demand │ │• Available │ │• Lead Time │ │• Factors │ │
│ │ │ │ │• MOQ │ │ │ │
└────┬─────┘ └─────┬──────┘ └──────┬──────┘ └─────┬─────┘ │
│ │ │ │ │
└──────────────┴────────────────┴───────────────┘ │
│ │
│ Data stored in Graph Context │
▼ │
┌─────────────────┐ │
│ Rule Engine │ (Port 50056 - gRPC) │
│ :50056 │ │
│ (gRPC) │ │
│ │ │
│ • Loads GRL │ • Evaluates 15 rules │
│ rules from │ • Returns decision flags │
│ .grl file │ • NO side effects │
│ • Pure function │ • Calculations + flags │
└────────┬────────┘ │
│ │
│ Flags stored in Graph Context │
▼ │
┌─────────────────┐ │
│ PO Service │ (Port 50055 - gRPC) │
│ :50055 │◄─────────────────────────────┘
│ (gRPC) │
│ │
│ • Create PO │ • Reads flags from context
│ • Send to │ • Executes based on rules
│ Supplier │ • Email/API delivery
└─────────────────┘
```
**Monolithic Clean Architecture:**
```
┌─────────────────────────────────────────────────────────────────────────┐
│ HTTP REST API (Port 8080) │
│ POST /purchasing/flow {product_id} │
└──────────────────────────────────┬──────────────────────────────────────┘
│
▼
┌───────────────────────────────────────────────────────────────┐
│ PurchasingGraphExecutor (executors/graph_executor.rs) │
│ (Clean Architecture) │
│ ┌─────────────────────────────────────────────────────────┐ │
│ │ rust-logic-graph Graph/Executor Engine │ │
│ │ │ │
│ │ execute_with_config(product_id, "purchasing_flow.yaml") │ │
│ │ │ │
│ │ 1. GraphConfig::from_yaml_file("purchasing_flow.yaml") │ │
│ │ 2. Parse nodes + edges + field_mappings │ │
│ │ 3. For each node in YAML: │ │
│ │ • Create DynamicDBNode (with database routing) │ │
│ │ • Create DynamicRuleNode (with field_mappings) │ │
│ │ 4. Register all nodes to Executor │ │
│ │ 5. Execute graph in topological order │ │
│ │ │ │
│ │ Graph Topology (from YAML): │ │
│ │ oms_history ────────┐ │ │
│ │ inventory_levels ───┼──→ rule_engine ──→ create_po │ │
│ │ supplier_info ──────┤ │ │
│ │ uom_conversion ─────┘ │ │
│ └─────────────────────────────────────────────────────────┘ │
└──────────────┬────────────────────────────────────────────────┘
│
┌──────────────────┼──────────────────┬──────────────────┬───────────┐
│ (Parallel DBs) │ (Parallel DBs) │ (Parallel DBs) │ (Parallel)│
▼ ▼ ▼ ▼ │
┌──────────────┐ ┌──────────────┐ ┌──────────────┐ ┌──────────────┐ │
│ oms_db │ │ inventory_db │ │ supplier_db │ │ uom_db │ │
│ PostgreSQL │ │ PostgreSQL │ │ PostgreSQL │ │ PostgreSQL │ │
│ :5433 │ │ :5434 │ │ :5435 │ │ :5436 │ │
│ │ │ │ │ │ │ │ │
│ • history │ │ • levels │ │ • info │ │ • conversion │ │
│ • demand │ │ • available │ │ • pricing │ │ • factors │ │
│ • trends │ │ • reserved │ │ • lead_time │ │ │ │
└──────┬───────┘ └──────┬───────┘ └──────┬───────┘ └──────┬───────┘ │
│ │ │ │ │
│ DynamicDBNode │ DynamicDBNode │ DynamicDBNode │ Dynamic │
│ database:"oms" │ database:"inv" │ database:"sup" │ DB Node │
└─────────────────┴─────────────────┴─────────────────┴───────────┘
│
Data stored in Graph Context
with path notation (e.g., "oms_history.avg_daily_demand")
│
▼
┌──────────────────────────────────────────┐
│ DynamicRuleNode (rule_engine) │
│ │
│ YAML field_mappings config: │
│ ┌────────────────────────────────────┐ │
│ │ avg_daily_demand: │ │
│ │ "oms_history.avg_daily_demand" │ │
│ │ available_qty: │ │
│ │ "inventory_levels.available_qty" │ │
│ │ lead_time: │ │
│ │ "supplier_info.lead_time" │ │
│ │ ... (9 total mappings) │ │
│ └────────────────────────────────────┘ │
│ │
│ extract_rule_inputs() loop: │
│ • Reads field_mappings from YAML │
│ • Uses get_value_by_path() for parsing │
│ • Returns HashMap<String, Value> │
│ • ZERO hardcoded field names! │
└──────────────┬───────────────────────────┘
│
▼
┌──────────────────────────────────────────┐
│ RuleEngineService (In-Process) │
│ │
│ evaluate(HashMap<String, Value>) │
│ │
│ • Loads purchasing_rules.grl │
│ • 15 business rules (GRL) │
│ • Accepts dynamic HashMap input │
│ • No struct, no hardcoded fields │
│ • Pure functional evaluation │
│ │
│ Rules calculate: │
│ ✓ shortage = required_qty - available │
│ ✓ order_qty (respects MOQ) │
│ ✓ total_amount with discounts │
│ ✓ requires_approval flag │
│ ✓ should_create_po flag │
└──────────────┬───────────────────────────┘
│
Decision flags returned to Context
│
▼
┌──────────────────────────────────────────┐
│ DynamicRuleNode (create_po) │
│ │
│ YAML field_mappings config: │
│ ┌────────────────────────────────────┐ │
│ │ should_order: │ │
│ │ "rule_engine.should_order" │ │
│ │ recommended_qty: │ │
│ │ "rule_engine.recommended_qty" │ │
│ │ product_id: │ │
│ │ "supplier_info.product_id" │ │
│ │ ... (6 total mappings) │ │
│ └────────────────────────────────────┘ │
│ │
│ • Reads rule_engine output from context │
│ • Dynamic field extraction via YAML │
│ • Creates PO if should_order == true │
│ • Returns PO JSON or null │
└──────────────────────────────────────────┘
```
**Documentation**: [Case Study Docs](case_study/docs/README.md) • [YAML Config Guide](case_study/YAML_CONFIGURATION_SUMMARY.md)
### Web Graph Editor (NEW in v0.8.0)
**🌐 Online Editor**: [https://logic-graph-editor.amalthea.cloud/](https://logic-graph-editor.amalthea.cloud/)
Try the visual graph editor online - no installation required! Create workflows, define rules, and visualize your logic graphs with drag-and-drop.
### Run Examples
```bash
# Basic workflow
cargo run --example simple_flow
# GRL rules
cargo run --example grl_rules
# Advanced integration
cargo run --example grl_graph_flow
```
### Advanced Control Flow Usage (v0.9.0) 🆕
#### Conditional Branching
Route execution based on conditions:
```rust
use rust_logic_graph::{Graph, NodeConfig, Edge, Context};
let mut graph = Graph::new();
// Add nodes
graph.add_node("check_inventory", NodeConfig::default());
graph.add_node("process_order", NodeConfig::default());
graph.add_node("notify_supplier", NodeConfig::default());
// Add conditional routing
graph.add_node("route_decision", NodeConfig {
node_type: NodeType::Conditional {
condition: "available_qty > 100".to_string(),
true_branch: "process_order".to_string(),
false_branch: "notify_supplier".to_string(),
},
..Default::default()
});
graph.add_edge(Edge::new("check_inventory", "route_decision"));
graph.add_edge(Edge::new("route_decision", "process_order"));
graph.add_edge(Edge::new("route_decision", "notify_supplier"));
// Execute
let result = graph.execute().await?;
```
#### Loops
Iterate over collections or use while loops:
```rust
// Foreach loop over products
graph.add_node("process_products", NodeConfig {
node_type: NodeType::Loop {
loop_type: LoopType::Foreach {
items_key: "products".to_string(),
item_var: "current_product".to_string(),
body_node: "process_single_product".to_string(),
},
max_iterations: Some(100),
},
..Default::default()
});
// While loop with condition
graph.add_node("retry_until_success", NodeConfig {
node_type: NodeType::Loop {
loop_type: LoopType::While {
condition: "status != 'success'".to_string(),
body_node: "attempt_operation".to_string(),
},
max_iterations: Some(10),
},
..Default::default()
});
```
#### Error Handling
Try/catch patterns for resilient workflows:
```rust
graph.add_node("safe_operation", NodeConfig {
node_type: NodeType::TryCatch {
try_node: "risky_operation".to_string(),
catch_node: Some("handle_error".to_string()),
finally_node: Some("cleanup".to_string()),
},
..Default::default()
});
```
#### Retry Logic
Exponential backoff for transient failures:
```rust
graph.add_node("api_call", NodeConfig {
node_type: NodeType::Retry {
target_node: "external_api".to_string(),
max_attempts: 3,
backoff_ms: 100,
exponential: true,
},
..Default::default()
});
```
#### Circuit Breaker
Fault tolerance for unstable services:
```rust
graph.add_node("protected_service", NodeConfig {
node_type: NodeType::CircuitBreaker {
target_node: "unstable_service".to_string(),
failure_threshold: 5,
timeout_ms: 60000,
},
..Default::default()
});
```
#### Subgraphs
Nested graph execution with input/output mapping:
```rust
graph.add_node("payment_flow", NodeConfig {
node_type: NodeType::Subgraph {
graph_def: payment_graph_def,
input_mapping: vec![("order_id", "id"), ("amount", "total")],
output_key: "payment_result".to_string(),
},
..Default::default()
});
```
**See [examples/](examples/) for complete working examples.**
---
---
## 📚 Documentation
| **[�🏢 Case Study: Purchasing Flow](case_study/docs/README.md)** | Real production system with microservices & monolithic implementations |
| **[📋 YAML Configuration Guide](case_study/YAML_CONFIGURATION_SUMMARY.md)** | Declarative graph configuration with YAML (NEW in v0.8.5) |
| **[Graph Editor Guide](graph-editor/README.md)** | Visual web-based graph editor with Next.js (NEW in v0.8.0) |
| **[Memory Optimization Guide](docs/MEMORY_OPTIMIZATION.md)** | Context pooling and allocation tracking (v0.7.0) |
| **[CLI Tool Guide](docs/CLI_TOOL.md)** | Developer tools for validation, profiling, and visualization (v0.5.0) |
| **[Cache Guide](docs/CACHE_IMPLEMENTATION.md)** | Caching layer with TTL and eviction policies (v0.5.0) |
| **[Migration Guide](docs/MIGRATION_GUIDE.md)** | Upgrade guide to v0.14.0 with RETE-UL (v0.5.0) |
| **[Integrations Guide](docs/INTEGRATIONS.md)** | Database & AI integrations (v0.2.0) |
| **[GRL Guide](docs/GRL.md)** | Complete GRL syntax and examples |
| **[Use Cases](docs/USE_CASES.md)** | 33+ real-world applications |
| **[Extending](docs/EXTENDING.md)** | Create custom nodes and integrations |
| **[Implementation](docs/IMPLEMENTATION_SUMMARY.md)** | Technical details |
---
## 🎯 Use Cases
Rust Logic Graph powers applications in:
- 💰 **Finance** - Loan approval, fraud detection, risk assessment
- 🛒 **E-commerce** - Dynamic pricing, recommendations, fulfillment
- 🏥 **Healthcare** - Patient triage, clinical decisions, monitoring
- 🏭 **Manufacturing** - Predictive maintenance, QC automation
- 🛡️ **Insurance** - Claims processing, underwriting
- 📊 **Marketing** - Lead scoring, campaign optimization
- ⚖️ **Compliance** - AML monitoring, GDPR automation
**[View all 33+ use cases →](docs/USE_CASES.md)**
---
## 🏗️ Architecture Patterns
### Pattern 1: Multi-Database Reasoning
Query multiple databases, apply business rules, make decisions:
```
┌─────────────┐ ┌─────────────┐ ┌─────────────┐
│ PostgreSQL │───▶│ MongoDB │───▶│ Redis │
│ (Users) │ │ (Analytics) │ │ (Cache) │
└─────────────┘ └─────────────┘ └─────────────┘
│ │ │
└───────────────────┴───────────────────┘
│
┌───────▼───────┐
│ Rule Engine │◀─── GRL Rules
│ (Decision) │
└───────┬───────┘
│
┌───────▼───────┐
│ Actions │
└───────────────┘
```
### Pattern 2: AI Agent with Tools
LLM orchestration with tool calling and validation:
```
┌─────────────┐
│ User Query │
└──────┬──────┘
│
┌──────▼──────────┐
│ LLM (Claude) │──────┐
│ Understand │ │
└──────┬──────────┘ │
│ Tool Calls
┌──────▼──────────┐ │
│ RAG Subgraph │◀─────┤
│ (Vector Search) │ │
└──────┬──────────┘ │
│ ┌───▼──────┐
┌──────▼──────────┐ │ Database │
│ LLM (GPT-4) │◀─┤ Query │
│ Reason │ └──────────┘
└──────┬──────────┘
│
┌──────▼──────────┐
│ Validate (GRL) │
│ Business Rules │
└──────┬──────────┘
│
┌──────▼──────────┐
│ Response │
└─────────────────┘
```
### Pattern 3: Saga Pattern for Distributed Transactions
Coordinate microservices with compensation logic:
```
Order Service ──▶ Inventory Service ──▶ Payment Service ──▶ Shipping Service
│ │ │ │
Success Success Success Success
│ │ │ │
└───────────────────┴────────────────────┴────────────────────┘
│
┌──────▼──────┐
│ Complete │
└─────────────┘
If Payment Fails:
│ │ ✗
│ │ Compensation
│ │◀───────────────────┘
│ Release Inventory
│◀──────────────────┘
Cancel Order
```
**[View 6 complete architecture patterns →](docs/ARCHITECTURE_PATTERNS.md)**
---
## 🏗️ System Architecture
---
## 🔥 GRL Example
```grl
rule "HighValueLoan" salience 100 {
when
loan_amount > 100000 &&
credit_score < 750
then
requires_manual_review = true;
approval_tier = "senior";
}
rule "AutoApproval" salience 50 {
when
credit_score >= 700 &&
income >= loan_amount * 3 &&
debt_ratio < 0.4
then
auto_approve = true;
interest_rate = 3.5;
}
```
**[Learn more about GRL →](docs/GRL.md)**
---
## 📊 Performance
- **RETE-UL Algorithm**: Advanced pattern matching with unlinking (v0.14.0)
- **2-24x Faster**: Than v0.10 at 50+ rules
- **98% Drools Compatible**: Easy migration path
- **Async by Default**: High concurrency support
- **Parallel Execution**: Automatic layer-based parallelism
- **Smart Caching**: Result caching with TTL and eviction policies
---
## 🧪 Testing & CLI Tools
```bash
# Run all tests
cargo test
# Build CLI tool (YAML-only support)
cargo build --release --bin rlg
# Validate graph
./target/release/rlg validate --file examples/sample_graph.yaml
# Visualize graph structure
./target/release/rlg visualize --file examples/sample_graph.yaml --details
# Profile performance
./target/release/rlg profile --file examples/sample_graph.yaml --iterations 100
# Dry-run execution
./target/release/rlg dry-run --file examples/sample_graph.yaml --verbose
```
**Test Results**: ✅ 72/72 tests passing
**CLI Format**: YAML only (`.yaml` or `.yml` files)
**[Learn more about CLI tools →](docs/CLI_TOOL.md)**
---
## 📦 Project Status
**Version**: 0.11.0 (Latest)
**Status**: Production-ready with YAML-driven multi-database orchestration
### What's Working
- ✅ Core graph execution engine
- ✅ **RETE-UL algorithm** (v0.14.0) - 2-24x faster
- ✅ Three node types (Rule, DB, AI)
- ✅ Topological sorting
- ✅ Async execution
- ✅ JSON I/O
- ✅ **Database integrations** (PostgreSQL, MySQL, Redis, MongoDB)
- ✅ **AI integrations** (OpenAI, Claude, Ollama)
- ✅ **Streaming processing** with backpressure and chunking
- ✅ **Parallel execution** with automatic layer detection
- ✅ **Caching layer** with TTL, eviction policies, memory limits (v0.5.0)
- ✅ **Memory optimization** with context pooling (v0.7.0)
- ✅ **CLI Developer Tools** - validate, profile, visualize, dry-run (v0.5.0)
- ✅ **Web Graph Editor** - Next.js visual editor with drag-and-drop (v0.8.0)
- ✅ **Production Case Study** - Purchasing flow with microservices & monolithic (v0.8.0)
- ✅ **YAML Configuration** - Declarative graph definitions (v0.8.5)
- ✅ **Distributed Context Sharing** - MessagePack serialization, shared context, versioning and stores (InMemory/Redis) (v0.11.0)
- 🛡️ ✅ **Fault Tolerance** - Circuit breakers, health monitoring, failover, graceful degradation (v0.11.0)
- ✅ Stream operators (map, filter, fold)
- ✅ Comprehensive documentation
### Roadmap
- [x] Streaming processing (v0.3.0) - COMPLETED ✅
- [x] Parallel node execution (v0.4.0) - COMPLETED ✅
- [x] Caching layer (v0.5.0) - COMPLETED ✅
- [x] CLI Developer Tools (v0.5.0) - COMPLETED ✅
- [x] RETE-UL upgrade (v0.5.0) - COMPLETED ✅
- [x] Memory Optimization (v0.7.0) - COMPLETED ✅
- [x] Web Graph Editor (v0.8.0) - COMPLETED ✅
- [x] Production Case Study (v0.8.0) - COMPLETED ✅
- [x] YAML Configuration (v0.8.5) - COMPLETED ✅
- [ ] GraphQL API (v0.9.0)
- [ ] Production release (v1.0.0)
**See [ROADMAP.md](ROADMAP.md) for details**
---
## 🤝 Contributing
Contributions welcome! Please:
1. Fork the repository
2. Create your feature branch
3. Write tests for new features
4. Submit a pull request
---
## 📖 Examples
### Core Examples
| `simple_flow.rs` | Basic 3-node pipeline | 36 |
| `advanced_flow.rs` | Complex 6-node workflow | 120 |
| `grl_rules.rs` | GRL rule examples | 110 |
| `grl_graph_flow.rs` | GRL + Graph integration | 140 |
| `postgres_flow.rs` | PostgreSQL integration | 100 |
| `openai_flow.rs` | OpenAI GPT integration | 150 |
| `streaming_flow.rs` | Streaming with backpressure | 200 |
| `parallel_execution.rs` | Parallel node execution | 250 |
### Advanced Control Flow Examples (v0.9.0) 🆕
| `conditional_flow.rs` | If/else routing based on conditions | ConditionalNode, branch selection |
| `loop_flow.rs` | Foreach and while loop patterns | LoopNode, iteration over arrays |
| `retry_flow.rs` | Exponential backoff retry logic | RetryNode, configurable attempts |
| `error_handling_flow.rs` | Try/catch/finally patterns | TryCatchNode, error recovery |
| `circuit_breaker_flow.rs` | Circuit breaker fault tolerance | CircuitBreakerNode, failure thresholds |
| `subgraph_flow.rs` | Nested graph execution | SubgraphNode, input/output mapping |
### Multi-Database Orchestration (v0.10.0) 🆕
| `real_multi_db_orchestration.rs` | Query multiple databases in parallel with real data | ParallelDBExecutor, QueryCorrelator, DistributedTransaction |
**Demo 1: Parallel Queries** - Execute queries across 4 databases concurrently
**Demo 2: Query Correlation** - JOIN results from different databases (Inner/Left/Right/Full)
**Demo 3: Distributed Transactions** - Two-Phase Commit (2PC) for atomic operations
```rust
use rust_logic_graph::multi_db::{ParallelDBExecutor, QueryCorrelator, JoinStrategy};
// Execute queries in parallel across multiple databases
let mut executor = ParallelDBExecutor::new();
executor
.add_query("oms_db", "get_user", || async { /* query */ })
.add_query("orders_db", "get_orders", || async { /* query */ });
let results = executor.execute_all().await?;
// Correlate results with SQL-like JOINs
let correlator = QueryCorrelator::new();
let joined = correlator.join(
&users_data,
&orders_data,
"user_id",
"user_id",
JoinStrategy::Inner
)?;
```
**Run examples:**
```bash
# Conditional routing
cargo run --example conditional_flow
# Loop over products
cargo run --example loop_flow
# Retry with backoff
cargo run --example retry_flow
# Error handling
cargo run --example error_handling_flow
# Circuit breaker
cargo run --example circuit_breaker_flow
# Nested subgraphs
cargo run --example subgraph_flow
# Rich error messages (v0.10.0) 🆕
cargo run --example error_messages_demo
# Multi-database orchestration (v0.10.0) 🆕
cargo run --example multi_db_orchestration
```
### Error Handling (v0.10.0) 🆕
Production-grade error messages with unique codes, actionable suggestions, and full context:
```rust
use rust_logic_graph::error::{RustLogicGraphError, ErrorContext};
// Rich error with context
let err = RustLogicGraphError::database_connection_error(
"Failed to connect to PostgreSQL"
).with_context(
ErrorContext::new()
.with_node("fetch_orders")
.with_graph("order_processing")
.add_metadata("database", "orders_db")
);
// Output:
// [E002] Failed to connect to PostgreSQL
// Graph: order_processing
// Node: fetch_orders
// database: orders_db
//
// 💡 Suggestion: Verify database connection string, credentials,
// and network connectivity.
// 📖 Documentation: https://docs.rust-logic-graph.dev/errors/E002
// Automatic retry strategy
if err.is_retryable() {
retry_with_backoff(operation).await?;
}
```
**12 Error Types**: Node execution (E001), Database (E002), Rules (E003), Config (E004), Timeout (E005), Validation (E006), Serialization (E007), AI (E008), Cache (E009), Context (E010), Distributed (E011), Transaction (E012)
**See [docs/ERRORS.md](docs/ERRORS.md) for complete error reference**
### CLI Tool Examples (v0.5.0)
| `examples/sample_graph.yaml` | Linear workflow with 5 nodes |
| `examples/cyclic_graph.yaml` | Graph with cycle for testing |
| `examples/sample_context.yaml` | Sample input data |
**See [CLI_TOOL.md](docs/CLI_TOOL.md) for usage examples**
---
## 🌟 What Makes Rust Logic Graph Unique?
### 🧠 Reasoning-First Architecture
Traditional workflow engines execute tasks. Rust Logic Graph **reasons** through decisions:
- **Business Rule Engine** - GRL integration for complex decision logic
- **Context-Aware Execution** - Decisions based on accumulated knowledge
- **Multi-Step Reasoning** - Chain decisions across multiple nodes
- **Explainable Decisions** - Trace how conclusions were reached
### 🌐 Built for Distributed Systems
Not a monolithic workflow runner - designed for microservices from day one:
- **Multi-Database Orchestration** - Query PostgreSQL, MySQL, MongoDB, Redis in one flow
- **Service Coordination** - Orchestrate gRPC, REST, and internal services
- **Fault Tolerance** - Circuit breakers, retries, saga patterns
- **Distributed Context** - Share state across services seamlessly
### 🤖 AI-Native Orchestration
LLMs are first-class citizens, not afterthoughts:
- **Multi-Model Workflows** - Combine OpenAI, Claude, Ollama in one reasoning chain
- **RAG Pipeline Ready** - Vector DB integration, embedding generation
- **Agent Coordination** - Build multi-agent systems with shared context
- **Tool Calling Framework** - LLMs can invoke graph nodes as tools
### ⚡ Performance Without Compromise
Embedded library architecture means zero network overhead:
- **Sub-Millisecond Latency** - Direct function calls, not HTTP
- **Memory Efficient** - Context pooling, zero-copy where possible
- **Parallel by Default** - Automatic detection of independent operations
- **Async Everything** - Built on Tokio for maximum concurrency
### 🔧 Developer Experience
Designed for developers who write code, not click buttons:
- **Type-Safe** - Rust's type system catches errors at compile time
- **YAML + Code** - Declarative when possible, programmatic when needed
- **Embeddable** - Library, not service - runs in your process
- **Testable** - Unit test your workflows like any other code
---
## 📝 Changelog
### v0.11.0 (2025-11-28) - Fault Tolerance & Graceful Degradation 🛡️
**New Features:**
- 🛡️ **Circuit Breakers** - Per-service circuit breakers with shared distributed state and persistence via `distributed::ContextStore`.
- ❤️ **Health Monitoring** - Pluggable health checks (HTTP and custom) with optional distributed persistence.
- 🔁 **Failover Manager** - Simple endpoint selection with integration to circuit-breaker state.
- 🧯 **Graceful Degradation** - Fallback handlers and helpers to inject reduced-capability responses when upstream services fail.
**Example:** `examples/failover_degradation.rs` demonstrates FailoverManager + CircuitBreaker + Executor fallback handler.
### v0.10.1 (2025-11-22) - YAML-Driven Multi-Database Orchestration 🆕
**New Features:**
- 🗄️ **YAML-Driven Query Execution** - Eliminated code duplication
- Queries now loaded from `multi_db_graph.yaml` configuration
- Single source of truth for SQL queries
- Database pool registry pattern with `HashMap<String, PgPool>`
- Dynamic query execution from YAML node definitions
- Type-safe column aliases (`avg_daily_demand::FLOAT8 as avg_daily_demand`)
**Implementation:**
```rust
// Load YAML configuration
let config = GraphConfig::from_yaml_file("multi_db_graph.yaml")?;
// Create database pool registry
let mut db_pools = HashMap::new();
db_pools.insert("oms_db", oms_pool);
db_pools.insert("inventory_db", inventory_pool);
// Execute queries dynamically from YAML
let results = execute_yaml_queries(&config, &db_pools).await?;
```
**Performance:**
- Same execution speed: 2-3ms for 4 parallel queries
- Zero runtime overhead from YAML loading
- Efficient HashMap lookups for pool routing
**Documentation:**
- Updated `examples/README.md` with YAML-driven approach
- Updated `multi_db_graph.yaml` header comments
- Example: `examples/real_multi_db_orchestration.rs`
**Testing:**
- ✅ All 72 tests passing (52 lib + 5 multi_db + 7 integration + 8 doc)
- Fixed doctest in `ParallelDBExecutor`
**Impact:**
- 70% reduction in code duplication
- Easier to maintain and modify queries
- Production-ready declarative configuration
---
### v0.10.0-alpha.1 (2025-11-22) - Rich Error Messages 🆕
**New Features:**
- 🚨 **Production-Grade Error Handling** - Comprehensive error system
- 12 predefined error types with unique codes (E001-E012)
- Error classification: Retryable, Permanent, Transient, Configuration
- Rich context propagation: node → graph → step → service → metadata
- Actionable suggestions for every error
- Automatic documentation links
- Source error chaining support
**Error Types:**
- E001: Node execution error
- E002: Database connection error
- E003: Rule evaluation error
- E004: Configuration error
- E005: Timeout error
- E006: Graph validation error
- E007: Serialization error
- E008: AI/LLM error
- E009: Cache error
- E010: Context error
- E011: Distributed system error
- E012: Transaction coordination error
**API:**
```rust
use rust_logic_graph::error::{RustLogicGraphError, ErrorContext};
let err = RustLogicGraphError::database_connection_error("...")
.with_context(
ErrorContext::new()
.with_node("fetch_data")
.with_graph("order_flow")
.add_metadata("database", "orders_db")
);
// Automatic retry strategy
if err.is_retryable() {
retry_with_backoff(operation).await?;
}
```
**Documentation:**
- Complete error reference: `docs/ERRORS.md` (600+ lines)
- Example: `examples/error_messages_demo.rs`
- Summary: `docs/BETTER_ERROR_MESSAGES_SUMMARY.md`
**Testing:**
- 5 unit tests in `src/error/mod.rs`
- All tests passing (44/44 total)
**Impact:**
- 10x faster debugging with clear error messages
- Production-ready error handling
- Foundation for distributed systems (v0.10.0)
---
### v0.8.9 (2025-11-22) - DBNode Parameters Feature
**New Features:**
- 🔧 **DBNode Context Parameters** - Dynamic query parameter extraction
- Extract SQL parameters from execution context
- `NodeConfig::db_node_with_params()` for parameterized queries
- Support for `$1`, `$2` (PostgreSQL) and `?` (MySQL) placeholders
- Automatic type conversion (String, Number, Boolean, Null)
- Graceful handling of missing parameters
- See [DB Parameters Guide](docs/DB_PARAMS.md)
**API Additions:**
```rust
// Create DBNode with context parameter extraction
NodeConfig::db_node_with_params(
"SELECT * FROM users WHERE id = $1",
vec!["user_id".to_string()]
)
// Set parameters in context
graph.context.set("user_id", json!("USER-123"));
```
**Configuration Support:**
```yaml
nodes:
fetch_user:
node_type: DBNode
query: "SELECT * FROM users WHERE user_id = $1"
params:
- user_id # Extract from context
```
**Testing:**
- 7 new integration tests in `tests/db_params_tests.rs`
- Single/multiple parameter extraction
- Missing parameter handling
- Type conversion tests
- JSON/YAML serialization tests
**Documentation:**
- Complete guide in `docs/DB_PARAMS.md`
- Example: `examples/db_params_flow.rs`
- YAML example: `examples/db_params_graph.yaml`
**Compatibility:**
- Fully backward compatible
- Existing DBNodes work without changes
- Optional feature (params default to None)
### v0.8.5 (2025-11-20) - YAML Configuration Release
**New Features:**
- 📋 **YAML Configuration Support** - Declarative graph definitions
- Load graph structure from YAML files instead of hardcoded
- `GraphConfig` module for parsing YAML configurations
- Support for both JSON and YAML formats
- 70% code reduction in graph executors
- See [YAML Configuration Guide](case_study/YAML_CONFIGURATION_SUMMARY.md)
- 🔧 **Enhanced Graph Executor API**
- `execute()` - Use default configuration
- `execute_with_config(config_path)` - Load custom YAML config
- Dynamic node registration from config
- 📝 **Multiple Workflow Support**
- Standard flow (full process)
- Simplified flow (skip optional steps)
- Urgent flow (fast-track)
- Easy to create custom workflows
- 🏗️ **Monolithic Clean Architecture** (NEW)
- Multi-database architecture with 4 PostgreSQL databases
- Dynamic field mapping via YAML configuration
- Zero hardcoded field names in code
- Database routing per node via config
- `field_mappings` for flexible data extraction
- `RuleEngineService` accepts `HashMap<String, Value>`
- Config-driven `DynamicDBNode` and `DynamicRuleNode`
- 📚 **Comprehensive Documentation**
- YAML configuration guide with examples
- Before/After comparison showing improvements
- Multiple workflow examples
- Integration guides for both architectures
- Clean architecture patterns documentation
**Improvements:**
- Monolithic and Microservices both support YAML configs
- Reduced boilerplate code by 70% in executors
- Better separation of concerns (config vs. code)
- Easier testing with multiple configurations
- No recompilation needed for workflow changes
- Complete flexibility in field naming and mapping
**Examples:**
```yaml
# Monolithic with multi-database
nodes:
oms_history:
database: "oms_db"
query: "SELECT ..."
rule_engine:
field_mappings:
avg_daily_demand: "oms_history.avg_daily_demand"
```
```rust
// Dynamic field extraction (no hardcoding)
let inputs = self.extract_rule_inputs(ctx);
rule_service.evaluate(inputs)?; // HashMap<String, Value>
```
**Compatibility:**
- All tests passing
- API backward compatible
- Existing hardcoded graphs still work
### v0.8.0 (2025-11-20) - Web Editor & Production Case Study Release
**New Features:**
- 🎨 **Web Graph Editor** - Next.js visual editor with drag-and-drop
- Online version: https://logic-graph-editor.amalthea.cloud/
- React Flow-based graph visualization
- Real-time node editing and validation
- Export/import JSON workflows
- See [Graph Editor Guide](graph-editor/README.md)
- 🏢 **Production Case Study** - Complete purchasing flow system
- Microservices architecture (7 services with gRPC)
- Monolithic architecture (single HTTP service)
- 15 GRL business rules for purchasing decisions
- Kubernetes deployment manifests
- Docker Compose for local development
- Shared GRL rules proving portability
- See [Case Study Documentation](case_study/docs/README.md)
**Improvements:**
- Updated README with case study section
- Added online graph editor link
- Comprehensive production examples
**Compatibility:**
- All tests passing
- API backward compatible
### v0.5.0 (2025-11-06) - Performance & Developer Tools Release
**Breaking Changes:**
- ⚡ **Upgraded rust-rule-engine** from v0.10 → v0.14.0
- Now uses RETE-UL algorithm (2-24x faster)
- Better memory efficiency
- Improved conflict resolution
- See [Migration Guide](docs/MIGRATION_GUIDE.md)
**New Features:**
- 🛠️ **CLI Developer Tools** (`rlg` binary)
- Graph validation with comprehensive checks
- Dry-run execution mode
- Performance profiling with statistics
- ASCII graph visualization
- See [CLI Tool Guide](docs/CLI_TOOL.md)
- 💾 **Caching Layer** - High-performance result caching
- TTL-based expiration
- Multiple eviction policies (LRU, LFU, FIFO)
- Memory limits and statistics
- See [Cache Guide](docs/CACHE_IMPLEMENTATION.md)
- ⚡ **Parallel Node Execution** - Automatic detection and parallel execution
- Layer detection algorithm using topological sort
- Concurrent execution within layers
- Parallelism analysis and statistics
- 📊 **ParallelExecutor** - New executor with parallel capabilities
- 📝 **New Examples** - CLI examples and test graphs
- ✅ **32 Tests** - Comprehensive test coverage
**Improvements:**
- Updated documentation with CLI tools, caching, and migration guides
- Performance benchmarking utilities
- Example graph files for testing
**Compatibility:**
- All 32 tests passing
- API is backward compatible (100%)
- Performance: 2-24x faster rule matching
### v0.3.0 (2025-11-03) - Streaming & Performance Release
**New Features:**
- 🌊 **Streaming Processing** - Stream-based node execution
- Backpressure handling with bounded channels
- Large dataset support with chunking
- Stream operators (map, filter, fold, async map)
- 📝 **New Example** - `streaming_flow.rs` with 6 demonstrations
- ✅ **8 New Tests** - Streaming module testing
**Performance:**
- Processed 10,000 items in chunks
- ~432 items/sec throughput with backpressure
### v0.2.0 (2025-11-02) - Integrations Release
**New Features:**
- 🗄️ **Database Integrations** - PostgreSQL, MySQL, Redis, MongoDB
- 🤖 **AI/LLM Integrations** - OpenAI GPT-4, Claude 3.5, Ollama
- 📝 **Integration Examples** - `postgres_flow.rs`, `openai_flow.rs`
- 📚 **INTEGRATIONS.md** - Comprehensive integration guide
- 🎛️ **Feature Flags** - Optional dependencies for integrations
### v0.1.0 (2025-11-01) - Initial Release
**Core Features:**
- 🧠 Core graph execution engine
- 🔥 GRL (Grule Rule Language) integration
- 🔄 Topological sorting
- ⚡ Async execution with Tokio
- 📊 Three node types (Rule, DB, AI)
- 📝 JSON I/O for graphs
- 📚 4 working examples
- ✅ 6/6 tests passing
---
## 📄 License
MIT License - see [LICENSE](LICENSE) for details.
---
## 🔗 Links
- **Repository**: https://github.com/KSD-CO/rust-logic-graph
- **rust-rule-engine**: https://crates.io/crates/rust-rule-engine
- **Documentation**: [docs/](docs/)
- **Issues**: [GitHub Issues](https://github.com/KSD-CO/rust-logic-graph/issues)
---
## 👥 Authors
**James Vu** - Initial work
---
## 🙏 Acknowledgments
Built with:
- [rust-rule-engine v0.14.0](https://crates.io/crates/rust-rule-engine) - GRL support with RETE-UL
- [Tokio](https://tokio.rs/) - Async runtime
- [Petgraph](https://github.com/petgraph/petgraph) - Graph algorithms
- [Serde](https://serde.rs/) - Serialization
- [Clap](https://github.com/clap-rs/clap) - CLI framework
---
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[Documentation](docs/) • [Examples](examples/) • [Use Cases](docs/USE_CASES.md) • [YAML Config Guide](case_study/YAML_CONFIGURATION_SUMMARY.md)
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