Show HN: Arise – 실패 시 런타임에 자체 도구를 생성하는 에이전트

Your agent works great on the tasks you planned for. ARISE handles the ones you didn't. ARISE is a framework-agnostic middleware that gives LLM agents the ability to create their own tools at runtime. When your agent fails at a task, ARISE detects the capability gap, synthesizes a Python tool, validates it in a sandbox, and promotes it to the active library — no human intervention required. Documentation | Quick Start | PyPI pip install arise-ai from arise import ARISE from arise.rewards import task_success arise = ARISE( agent_fn=my_agent, # any (task, tools) -> str function reward_fn=task_success, model="gpt-4o-mini", # cheap model for tool synthesis ) result = arise.run("Fetch all users from the paginated API") # Agent fails → ARISE synthesizes fetch_all_paginated tool → agent succeeds Episode 1 | FAIL | reward=0.00 | skills=2 Task: "Fetch paginated users with auth" Episode 2 | FAIL | reward=0.00 | skills=2 Episode 3 | FAIL | reward=0.00 | skills=2 [Evolution triggered — 3 failures on API tasks] → Synthesizing 'parse_json_response'... 3/3 tests passed ✓ → Synthesizing 'fetch_all_paginated'... sandbox fail → refine → 1/1 passed ✓ Episode 4 | OK | reward=1.00 | skills=4 Agent now has the tools it needs - Self-evolving tool library — fail → detect gap → synthesize → sandbox test → promote - Framework-agnostic — any (task, tools) -> str function, Strands, LangGraph, CrewAI - Sandboxed validation — subprocess or Docker, adversarial testing, import restrictions - Distributed mode — S3 + SQS for stateless deployments (Lambda, ECS, AgentCore) - Skill registry — share evolved tools across projects - Version control + rollback — SQLite checkpoints, arise rollback - A/B testing — refined skills tested against originals before promotion - Web Console — create agents, watch evolution live, inspect evolved code ( arise console ) - Dashboard — terminal TUI and web UI for monitoring | Model | Condition | AcmeCorp (SRE) | DataCorp (Data Eng) | |---|---|---|---| | Claude Sonnet | ARISE | 78% | — | | Claude Sonnet | No tools | 63% | — | | GPT-4o-mini | ARISE | 57% | 92% | | GPT-4o-mini | No tools | 48% | 50% | ARISE improves task success by +9–42 percentage points across models and domains. See the full benchmark results. A web UI for creating agents, watching evolution live, and inspecting evolved tools: arise console # Opens http://localhost:8080 - Create agents — pick model, set system prompt, choose reward function - Live terminal feed — watch episodes and evolution in real-time via WebSocket - Skill inspector — syntax-highlighted code, test suite, performance metrics - Editable config — change reward function, system prompt, failure threshold on the fly - All Skills / Evolution Log — global views across all agents Full documentation at arise-ai.dev: - Installation — install and configure - Quick Start — complete evolution loop walkthrough - How It Works — the 5-step evolution pipeline - Reward Functions — built-in and custom reward functions - Safety & Validation — sandbox, adversarial testing, production recommendations - Distributed Mode — S3 + SQS for stateless deployments - Framework Adapters — Strands, LangGraph, CrewAI, raw OpenAI/Anthropic - CLI Reference — all CLI commands - API Reference — ARISE class, config, types | Example | Description | |---|---| quickstart_evolution.py | Full evolution loop: agent fails → ARISE evolves tool → agent succeeds | quickstart.py | Math agent evolves statistics tools | api_agent.py | HTTP agent evolves auth + pagination (mock server) | devops_agent.py | DevOps agent evolves log analysis tools | strands_agent.py | Strands integration with Bedrock | demo/agentcore/ | AgentCore deployment with A2A protocol | pip install arise-ai # core (just pydantic) pip install arise-ai[aws] # + boto3 for distributed mode pip install arise-ai[litellm] # + litellm for multi-provider LLM pip install arise-ai[docker] # + docker sandbox backend pip install arise-ai[dashboard] # + rich, fastapi for dashboard pip install arise-ai[otel] # + opentelemetry for tracing pip install arise-ai[all] # everything ARISE builds on ideas from LATM, VOYAGER, CREATOR, ADAS, and CRAFT. ARISE adds the production layer: framework-agnostic integration, sandboxed validation, adversarial testing, version control, distributed deployment, and A/B testing. MIT