{"id":34582237,"url":"https://github.com/agenisea/agentic-mathematical-engine","last_synced_at":"2025-12-24T10:10:43.894Z","repository":{"id":328551129,"uuid":"1115612363","full_name":"agenisea/agentic-mathematical-engine","owner":"agenisea","description":"An intelligent Julia agent for scientific computing with natural language queries and multi-domain mathematical reasoning.","archived":false,"fork":false,"pushed_at":"2025-12-14T01:53:12.000Z","size":156,"stargazers_count":2,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-12-15T18:57:56.176Z","etag":null,"topics":["agentic","deepseek-r1","julia","julia-language","julialang","multi-agent-system","reasoning-agent","scientific"],"latest_commit_sha":null,"homepage":"","language":"Julia","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"mit","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/agenisea.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":"CONTRIBUTING.md","funding":null,"license":"LICENSE","code_of_conduct":"CODE_OF_CONDUCT.md","threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":"SECURITY.md","support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null,"zenodo":null,"notice":null,"maintainers":null,"copyright":null,"agents":null,"dco":null,"cla":null}},"created_at":"2025-12-13T07:33:55.000Z","updated_at":"2025-12-15T10:06:46.000Z","dependencies_parsed_at":null,"dependency_job_id":null,"html_url":"https://github.com/agenisea/agentic-mathematical-engine","commit_stats":null,"previous_names":["agenisea/agentic-mathematical-engine"],"tags_count":1,"template":false,"template_full_name":null,"purl":"pkg:github/agenisea/agentic-mathematical-engine","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/agenisea%2Fagentic-mathematical-engine","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/agenisea%2Fagentic-mathematical-engine/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/agenisea%2Fagentic-mathematical-engine/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/agenisea%2Fagentic-mathematical-engine/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/agenisea","download_url":"https://codeload.github.com/agenisea/agentic-mathematical-engine/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/agenisea%2Fagentic-mathematical-engine/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":28000523,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","status":"online","status_checked_at":"2025-12-24T02:00:07.193Z","response_time":83,"last_error":null,"robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":true,"can_crawl_api":true,"host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["agentic","deepseek-r1","julia","julia-language","julialang","multi-agent-system","reasoning-agent","scientific"],"created_at":"2025-12-24T10:10:43.233Z","updated_at":"2025-12-24T10:10:43.882Z","avatar_url":"https://github.com/agenisea.png","language":"Julia","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Amy - Agentic Mathematical Engine\n\n**An intelligent computational reasoning system for scientific research**\n\n[![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT)\n\n\u003e **Note:** This project is an experiment and a work in progress. All contributions are welcome!\n\n## The Problem\n\nScientists and engineers face a gap between **what they want to compute** and **how to compute it**:\n\n- Traditional tools require specifying exact operations: \"Differentiate x² + 2x\"\n- But researchers think in goals: \"Find where this function has extrema\"\n- Complex problems require chaining multiple tools across domains\n- Manual verification is tedious and error-prone\n- Results lack reasoning traces for reproducibility\n\n## The Solution\n\n**Agentic Mathematical Engine** bridges this gap with an intelligent agent that:\n\n- **Understands** natural language mathematical queries\n- **Plans** multi-step solutions automatically\n- **Executes** computations across seven mathematical domains\n- **Verifies** results for correctness and physical validity\n- **Explains** reasoning traces for full transparency\n\n## How It Works\n\n1. **Describe your goal** in natural language\n2. **Agent decomposes** the problem into sub-goals\n3. **Tools execute** the required computations\n4. **Verification** ensures correctness\n5. **Explanation** provides reasoning trace\n\n```julia\nusing AgenticMathematicalEngine\n\n# Natural language query\nresponse = solve(\"Design a Hohmann transfer from Earth to Mars with minimum fuel\")\n\n# Get results with full explanation\nprintln(response.result)       # Δv = 5.59 km/s, transfer time = 259 days\nprintln(response.explanation)  # Step-by-step reasoning\nprintln(response.confidence)   # 0.95\n```\n\n## Features\n\n### Seven Mathematical Domains\n\n| Domain | Capabilities |\n|--------|-------------|\n| **Symbolic** | Algebra, calculus, equation solving, simplification |\n| **Numerical** | ODEs, PDEs, integration, optimization, N-body simulation |\n| **Tensor** | General relativity, differential geometry, index manipulation |\n| **Coordinate** | Reference frames, orbital mechanics, unit conversion |\n| **Propulsion** | Rocket equations, delta-v budgets, trajectory optimization |\n| **Linear Algebra** | Eigenanalysis, decompositions, matrix calculus |\n| **Physics** | Electromagnetism, thermodynamics, fluids, quantum mechanics |\n\n### Intelligent Agent Capabilities\n\n- **Dynamic Planning** — Automatically decomposes complex problems\n- **Tool Selection** — Chooses appropriate methods for each sub-goal\n- **Verification** — Checks units, conservation laws, physical bounds\n- **Replanning** — Adapts when approaches fail\n- **Explanation** — Generates reasoning traces for reproducibility\n\n### Built-in Knowledge\n\n- Solar system body data (planets, moons)\n- Physical constants with units\n- Material properties\n- Reference values for verification\n\n## Installation\n\n### Prerequisites\n\n- Julia 1.9 or higher\n- ~2GB disk space for dependencies\n\n### Install from Source\n\n```bash\ngit clone https://github.com/agenisea/agentic-mathematical-engine.git\ncd agentic-mathematical-engine\njulia --project=. -e 'using Pkg; Pkg.instantiate()'\n```\n\n### LLM Configuration\n\nAmy uses Ollama with DeepSeek-R1 for LLM-powered reasoning. Ensure Ollama is running locally:\n\n```bash\n# Install Ollama (macOS)\nbrew install ollama\n\n# Pull the DeepSeek-R1 model\nollama pull deepseek-r1:latest\n\n# Start Ollama server (runs on localhost:11434 by default)\nollama serve\n```\n\n## Usage\n\n### Basic Usage\n\n```julia\nusing AgenticMathematicalEngine\n\n# Simple query\nresponse = solve(\"What is the derivative of x³ + 2x²?\")\nprintln(response.result)  # 3x² + 4x\n\n# Trajectory design\nresponse = solve(\"Design a Hohmann transfer from LEO (400km) to GEO\")\nprintln(response.result.delta_v_total)  # ~3.9 km/s\n\n# Stability analysis\nresponse = solve(\"Is the L4 Lagrange point stable for the Sun-Earth system?\")\nprintln(response.result)  # STABLE (with eigenvalue analysis)\n```\n\n### Multi-turn Conversations\n\n```julia\nagent = Agent()\n\nresponse1 = agent(\"Set up a simple harmonic oscillator with ω = 5 rad/s\")\nresponse2 = agent(\"Now add damping with ζ = 0.3\")\nresponse3 = agent(\"Find the damped natural frequency\")\n```\n\n### Configuration\n\n```julia\nconfig = AgentConfig(\n    max_tool_calls = 50,\n    verification_level = :thorough,  # :minimal, :standard, :thorough\n    explanation_detail = :verbose,   # :brief, :standard, :verbose\n    timeout_seconds = 300,\n)\n\nresponse = solve(\"Complex multi-step problem...\", config=config)\n```\n\n## Examples\n\nThe `examples/` directory contains comprehensive demonstrations:\n\n| Example | Description |\n|---------|-------------|\n| `llm_demo.jl` | **Interactive LLM demo** with real-time event streaming |\n| `trajectory_design.jl` | Orbital mechanics, mission design, gravity assists |\n| `stability_analysis.jl` | Eigenvalue analysis, Lagrange points, control systems |\n| `physics_simulation.jl` | Heat transfer, E\u0026M, quantum mechanics, N-body |\n| `symbolic_derivation.jl` | Calculus, series expansions, tensor calculus |\n\nRun an example:\n\n```bash\njulia --project=. examples/trajectory_design.jl\n```\n\n## Architecture\n\n```\n┌─────────────────────────────────────────────────────────────────┐\n│                         USER QUERY                              │\n│  \"Design a Hohmann transfer from Earth to Mars\"                 │\n└─────────────────────────────────────────────────────────────────┘\n                                │\n                                ▼\n┌─────────────────────────────────────────────────────────────────┐\n│                      REASONING AGENT                            │\n│  ┌────────────┐  ┌────────────┐  ┌────────────┐  ┌───────────┐  │\n│  │ UNDERSTAND │→ │   PLAN     │→ │  EXECUTE   │→ │  VERIFY   │  │\n│  │            │  │            │  │            │  │           │  │\n│  │ Parse      │  │ Decompose  │  │ Run tools  │  │ Check     │  │\n│  │ intent     │  │ into goals │  │ Get results│  │ results   │  │\n│  └────────────┘  └────────────┘  └────────────┘  └───────────┘  │\n│                                                                 │\n│  ┌──────────────────────────────────────────────────────────┐   │\n│  │                    WORKING MEMORY                        │   │\n│  │  • Goal stack  • Intermediate results  • Confidence      │   │\n│  └──────────────────────────────────────────────────────────┘   │\n└─────────────────────────────────────────────────────────────────┘\n                                │\n                                ▼\n┌────────────────────────────────────────────────────────────────┐\n│                        TOOL SUITE                              │\n│  ┌─────────┐ ┌─────────┐ ┌─────────┐ ┌─────────┐ ┌──────────┐  │\n│  │SYMBOLIC │ │NUMERICAL│ │ TENSOR  │ │COORD    │ │PROPULSION│  │\n│  │         │ │         │ │         │ │         │ │          │  │\n│  │simplify │ │solve_ode│ │riemann  │ │kepler   │ │hohmann   │  │\n│  │diff     │ │optimize │ │geodesic │ │ephemeris│ │lambert   │  │\n│  │integrate│ │nbody    │ │contract │ │transform│ │delta_v   │  │\n│  └─────────┘ └─────────┘ └─────────┘ └─────────┘ └──────────┘  │\n│  ┌─────────┐ ┌─────────┐ ┌────────────────────────────────┐    │\n│  │ MATRIX  │ │ PHYSICS │ │         VERIFICATION           │    │\n│  │         │ │         │ │                                │    │\n│  │eigen    │ │maxwell  │ │ check_units  check_conservation│    │\n│  │decompose│ │heat     │ │ check_bounds numerical_verify  │    │\n│  │jacobian │ │quantum  │ │                                │    │\n│  └─────────┘ └─────────┘ └────────────────────────────────┘    │\n└────────────────────────────────────────────────────────────────┘\n                                │\n                                ▼\n┌─────────────────────────────────────────────────────────────────┐\n│                          OUTPUT                                 │\n│  Result: Δv_total = 5.59 km/s, Transfer time = 259 days         │\n│  Reasoning: Decomposed into orbital parameters, vis-viva...     │\n│  Confidence: 0.95 (verified against reference data)             │\n└─────────────────────────────────────────────────────────────────┘\n```\n\n### Multi-Agent LLM Pipeline\n\nAmy uses 5 specialized LLM agents orchestrated by a supervisor:\n\n```\n┌─────────────────────────────────────────────────────────────────────────────┐\n│                           LLM AGENT PIPELINE                                │\n├─────────────────────────────────────────────────────────────────────────────┤\n│                                                                             │\n│  ┌─────────────┐    ┌─────────────┐    ┌─────────────┐                      │\n│  │ INTERPRETER │───▶│   PLANNER   │───▶│  EXECUTOR   │                      │\n│  │             │    │             │    │             │                      │\n│  │ Parse query │    │ Decompose   │    │ Map goals   │                      │\n│  │ Extract     │    │ into goal   │    │ to tools    │                      │\n│  │ intent      │    │ DAG         │    │ Execute     │                      │\n│  └─────────────┘    └─────────────┘    └──────┬──────┘                      │\n│                                               │                             │\n│                      ┌────────────────────────┴────────────────────┐        │\n│                      │                                             │        │\n│                      ▼                                             ▼        │\n│               ┌─────────────┐                              ┌─────────────┐  │\n│               │  VERIFIER   │                              │  EXPLAINER  │  │\n│               │             │                              │             │  │\n│               │ Validate    │                              │ Generate    │  │\n│               │ results     │                              │ natural     │  │\n│               │ Check units │                              │ language    │  │\n│               │ \u0026 bounds    │                              │ explanation │  │\n│               └─────────────┘                              └─────────────┘  │\n│                                                                             │\n└─────────────────────────────────────────────────────────────────────────────┘\n```\n\n| Agent | Role | Output Format |\n|-------|------|---------------|\n| **INTERPRETER** | Parse natural language, extract intent \u0026 entities | Structured JSON intent |\n| **PLANNER** | Decompose problem into goal DAG | Goal nodes with dependencies |\n| **EXECUTOR** | Map goals to tools, prepare parameters | Tool call specifications |\n| **VERIFIER** | Validate results against physical laws | Pass/Warn/Fail verdict |\n| **EXPLAINER** | Generate human-readable explanations | Summary with LaTeX equations |\n\n### Parallel Execution Architecture (Fan-Out/Fan-In)\n\nAmy uses a DAG-based parallel execution model to maximize throughput when goals are independent:\n\n```\n                         ┌─────────────────────────────────────┐\n                         │           PLANNER                   │\n                         │   Creates Goal DAG with deps        │\n                         └──────────────┬──────────────────────┘\n                                        │\n                                        ▼\n                    ┌───────────────────────────────────────────┐\n                    │          PARALLEL SCHEDULER               │\n                    │   Identifies independent goals            │\n                    │   Groups into execution batches           │\n                    └───────────────────┬───────────────────────┘\n                                        │\n          ┌─────────────────────────────┼─────────────────────────────┐\n          │                             │                             │\n          ▼                             ▼                             ▼\n   ══════════════════════════════════════════════════════════════════════\n                              FAN-OUT PHASE\n   ══════════════════════════════════════════════════════════════════════\n          │                             │                             │\n          ▼                             ▼                             ▼\n   ┌─────────────┐               ┌─────────────┐               ┌─────────────┐\n   │   GOAL 1    │               │   GOAL 2    │               │   GOAL 3    │\n   │   (no deps) │               │   (no deps) │               │   (no deps) │\n   │             │               │             │               │             │\n   │  Execute    │               │  Execute    │               │  Execute    │\n   │  Tool A     │               │  Tool B     │               │  Tool C     │\n   └──────┬──────┘               └──────┬──────┘               └──────┬──────┘\n          │                             │                             │\n          ▼                             ▼                             ▼\n   ┌─────────────┐               ┌─────────────┐               ┌─────────────┐\n   │  VERIFIER   │               │  VERIFIER   │               │  VERIFIER   │\n   │  (parallel) │               │  (parallel) │               │  (parallel) │\n   └──────┬──────┘               └──────┬──────┘               └──────┬──────┘\n          │                             │                             │\n          └─────────────────────────────┼─────────────────────────────┘\n                                        │\n   ══════════════════════════════════════════════════════════════════════\n                               FAN-IN PHASE\n   ══════════════════════════════════════════════════════════════════════\n                                        │\n                                        ▼\n                         ┌─────────────────────────────────────┐\n                         │       THREAD-SAFE MEMORY            │\n                         │   Collects results from all goals   │\n                         │   Tracks verification status        │\n                         └──────────────┬──────────────────────┘\n                                        │\n                                        ▼\n                         ┌─────────────────────────────────────┐\n                         │          NEXT BATCH                 │\n                         │   Goals with satisfied deps         │\n                         └──────────────┬──────────────────────┘\n                                        │\n          ┌─────────────────────────────┼─────────────────────────────┐\n          │                             │                             │\n          ▼                             ▼                             ▼\n   ┌─────────────┐               ┌─────────────┐               ┌─────────────┐\n   │   GOAL 4    │               │   GOAL 5    │               │   GOAL 6    │\n   │ (deps: 1,2) │               │ (deps: 2,3) │               │ (deps: 1)   │\n   └─────────────┘               └─────────────┘               └─────────────┘\n                                        │\n                                        ▼\n                         ┌─────────────────────────────────────┐\n                         │          EXPLAINER                  │\n                         │   Generates unified explanation     │\n                         └─────────────────────────────────────┘\n```\n\n#### Key Features of Parallel Execution\n\n| Feature | Description |\n|---------|-------------|\n| **DAG Scheduling** | Goals form a directed acyclic graph; independent goals run concurrently |\n| **Batch Execution** | Goals grouped into batches based on dependency satisfaction |\n| **Thread-Safe Memory** | Concurrent writes protected with ReentrantLock |\n| **Parallel Verification** | Each goal verified independently, can run alongside next batch |\n| **Automatic Fallback** | Falls back to sequential execution for single-goal plans |\n| **Budget Management** | Token budgets tracked per-agent with atomic counters |\n\n#### Execution Modes\n\n```julia\n# Automatic mode selection based on goal count and dependencies\nconfig = PipelineConfig(\n    enable_parallel_execution = true,   # Enable parallel when beneficial\n    max_concurrent_goals = 4,           # Max parallel goals\n    enable_parallel_verification = true # Verify concurrently\n)\n```\n\n**When Parallel Execution is Used:**\n- Plan has 2+ goals\n- Goals have independent dependencies (can run in parallel batches)\n- Budget permits concurrent LLM calls\n\n**When Sequential Execution is Used:**\n- Single goal plans\n- Strictly linear dependencies (each goal depends on previous)\n- Fallback mode (budget/circuit breaker constraints)\n\n## Project Structure\n\n```\nagentic-mathematical-engine/\n├── Project.toml              # Julia package manifest\n├── Manifest.toml             # Dependency lock file\n├── README.md                 # This file\n├── CONTRIBUTING.md           # Contribution guidelines\n├── CODE_OF_CONDUCT.md        # Community standards\n├── SECURITY.md               # Security policy\n│\n├── src/\n│   ├── AgenticMathematicalEngine.jl  # Main module\n│   │\n│   ├── types/                # Core type definitions\n│   │   ├── goals.jl          # Goal \u0026 GoalStatus\n│   │   ├── plans.jl          # Plan \u0026 PlanStatus\n│   │   ├── memory.jl         # WorkingMemory\n│   │   ├── tools.jl          # ToolDefinition\n│   │   └── results.jl        # AgentResponse, Explanation\n│   │\n│   ├── agent/                # Agent components\n│   │   ├── core.jl           # Main agent loop\n│   │   ├── understanding.jl  # Intent parsing\n│   │   ├── planning.jl       # Problem decomposition\n│   │   ├── execution.jl      # Tool invocation\n│   │   ├── verification.jl   # Result checking\n│   │   └── explanation.jl    # Reasoning traces\n│   │\n│   ├── tools/                # Mathematical tools\n│   │   ├── registry.jl       # Tool registry\n│   │   ├── symbolic.jl       # Symbolic math\n│   │   ├── numerical.jl      # Numerical methods\n│   │   ├── tensor.jl         # Tensor algebra\n│   │   ├── coordinate.jl     # Coordinate systems\n│   │   ├── propulsion.jl     # Propulsion tools\n│   │   ├── matrix.jl         # Linear algebra\n│   │   ├── physics.jl        # Physics tools\n│   │   └── verification.jl   # Verification tools\n│   │\n│   ├── strategies/           # Problem-solving strategies\n│   │   ├── base.jl           # Strategy interface\n│   │   ├── trajectory.jl     # Trajectory design\n│   │   ├── stability.jl      # Stability analysis\n│   │   ├── derivation.jl     # Mathematical derivation\n│   │   ├── simulation.jl     # Physics simulation\n│   │   └── optimization.jl   # Optimization problems\n│   │\n│   ├── knowledge/            # Built-in knowledge\n│   │   ├── constants.jl      # Physical constants\n│   │   ├── bodies.jl         # Celestial body data\n│   │   ├── materials.jl      # Material properties\n│   │   └── references.jl     # Reference values\n│   │\n│   ├── util/                 # Utilities\n│   │   ├── units.jl          # Unit handling\n│   │   ├── latex.jl          # LaTeX generation\n│   │   └── logging.jl        # Logging utilities\n│   │\n│   ├── llm/                  # LLM Integration Layer\n│   │   ├── client.jl         # Ollama client\n│   │   ├── events.jl         # Event streaming\n│   │   ├── parser.jl         # Response parsing\n│   │   ├── prompts.jl        # Agent prompts\n│   │   └── fallback.jl       # Fallback handlers\n│   │\n│   ├── orchestration/        # Multi-Agent Orchestration\n│   │   ├── supervisor.jl     # Pipeline supervisor\n│   │   ├── parallel.jl       # Parallel execution\n│   │   ├── budget.jl         # Token budget management\n│   │   └── resilience.jl     # Circuit breakers\n│   │\n│   └── prompts/              # Agent System Prompts\n│       ├── interpreter.md    # Intent parsing prompt\n│       ├── planner.md        # Goal decomposition prompt\n│       ├── executor.md       # Tool invocation prompt\n│       ├── verifier.md       # Result validation prompt\n│       └── explainer.md      # Explanation generation prompt\n│\n├── examples/                 # Example scripts\n│   ├── trajectory_design.jl\n│   ├── stability_analysis.jl\n│   ├── physics_simulation.jl\n│   └── symbolic_derivation.jl\n│\n└── test/                     # Test suite\n    ├── runtests.jl\n    ├── unit/\n    ├── integration/\n    └── validation/\n```\n\n## Tech Stack\n\n- **Julia 1.9+** — High-performance scientific computing\n- **Symbolics.jl** — Computer algebra system\n- **DifferentialEquations.jl** — ODE/PDE solvers\n- **Unitful.jl** — Physical units with type safety\n- **Optim.jl** — Optimization algorithms\n- **LinearAlgebra** — Matrix operations\n- **ForwardDiff.jl** — Automatic differentiation\n\n## Design Artifacts\n\nThis repo includes the original planning and agent-design docs used to architect the system—shared intentionally for transparency and reuse. These documents are optional; the engine runs independently of them.\n\n- [`docs/blueprompt.md`](docs/blueprompt.md) — App design spec ([blueprompt.app](https://blueprompt.app))\n- [`docs/agenisea.md`](docs/agenisea.md) — Multi-agent architecture spec\n\n## Roadmap\n\n- [x] Core agent architecture\n- [x] Seven mathematical domains\n- [x] Verification system\n- [x] Comprehensive examples\n- [x] LLM integration (Ollama/DeepSeek-R1)\n- [x] Multi-agent orchestration (5 specialized agents)\n- [x] Parallel execution with fan-out/fan-in\n- [x] Token budget management\n- [x] Circuit breaker resilience\n- [ ] Web interface\n- [ ] Jupyter notebook integration\n- [ ] GPU acceleration for N-body\n- [ ] More physics domains (plasma, relativity)\n\n## Contributing\n\nWe welcome contributions! See [CONTRIBUTING.md](CONTRIBUTING.md) for guidelines.\n\n### Quick Start for Contributors\n\n```bash\n# Clone and setup\ngit clone https://github.com/agenisea/agentic-mathematical-engine.git\ncd agentic-mathematical-engine\njulia --project=. -e 'using Pkg; Pkg.instantiate()'\n\n# Run tests\njulia --project=. -e 'using Pkg; Pkg.test()'\n\n# Run examples\njulia --project=. examples/trajectory_design.jl\n```\n\n## License\n\nMIT License - see [LICENSE](LICENSE) for details.\n\n## Support\n\n- **Issues**: [GitHub Issues](https://github.com/agenisea/agentic-mathematical-engine/issues)\n- **Discussions**: [GitHub Discussions](https://github.com/agenisea/agentic-mathematical-engine/discussions)\n\n---\n\n\u003cp align=\"center\"\u003e\n  Built by \u003ca href=\"https://agenisea.ai\"\u003eAgenisea™\u003c/a\u003e 🪼\n\u003c/p\u003e\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fagenisea%2Fagentic-mathematical-engine","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fagenisea%2Fagentic-mathematical-engine","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fagenisea%2Fagentic-mathematical-engine/lists"}