Lango¶
A high-performance AI agent framework built with Go.
Single binary. Multi-provider AI. Self-learning knowledge system.
Experimental
Lango is under active development. APIs and configuration formats may change between releases. Use in production at your own risk.
Quick Install¶
git clone https://github.com/langowarny/lango.git
cd lango
make build
./bin/lango onboard
See the Installation Guide for detailed instructions.
Features¶
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Fast
Single binary, <100ms startup, <250MB memory footprint. Built with Go for maximum performance.
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Multi-Provider AI
OpenAI, Anthropic, Gemini, and Ollama with a unified interface. Switch providers without changing code.
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Multi-Channel
Connect to Telegram, Discord, and Slack. Manage conversations across channels from a single agent.
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Rich Tools
Shell execution, file system operations, browser automation, crypto and secrets management tools.
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Self-Learning
Knowledge store, learning engine, skill system, observational memory, and a proactive librarian that grows smarter over time.
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Knowledge Graph & Graph RAG
BoltDB-backed triple store with hybrid vector + graph retrieval for deep contextual understanding.
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Multi-Agent Orchestration
Hierarchical sub-agents (Executor, Researcher, Planner, Memory Manager) working together on complex tasks.
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A2A Protocol
Agent-to-Agent protocol for remote agent discovery and inter-agent communication.
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Blockchain Payments
USDC payments on Base L2 with X402 V2 auto-pay protocol support.
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Cron Scheduling
Persistent cron jobs with Ent ORM storage and multi-channel delivery.
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Background Execution
Async task manager with concurrency control for long-running operations.
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Workflow Engine
DAG-based YAML workflows with parallel step execution and dependency management.
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Secure
AES-256-GCM encryption, key registry, secret management, and PII redaction.
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Persistent
Ent ORM with encrypted SQLite storage for sessions, configuration, and knowledge.
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Gateway
WebSocket and HTTP server with real-time streaming support.
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Auth
OIDC authentication and OAuth login flow for secure access control.
Next Steps¶
- Getting Started -- Install, configure, and run your first agent
- Architecture -- Understand the system design
- CLI Reference -- Complete command documentation