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> Hive uses a `uv` workspace layout and is not installed with `pip install`.
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> Running `pip install -e .` from the repository root will create a placeholder package and Hive will not function correctly.
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> Please use the quickstart script below to set up the environment.
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# Or run directly
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hive run exports/your_agent_name --input '{"key": "value"}'
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```
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## Coding Agent Support
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## Coding Agent Support
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### Codex CLI
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Hive includes native support for [OpenAI Codex CLI](https://github.com/openai/codex) (v0.101.0+).
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1.**Config:**`.codex/config.toml` with `agent-builder` MCP server (tracked in git)
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2.**Skills:**`.agents/skills/` symlinks to Hive skills (tracked in git)
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3.**Launch:** Run `codex` in the repo root, then type `use hive`
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Example:
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```
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codex> use hive
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```
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### Opencode
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### Opencode
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Hive includes native support for [Opencode](https://github.com/opencode-ai/opencode).
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1.**Setup:** Run the quickstart script
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1.**Setup:** Run the quickstart script
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2.**Launch:** Open Opencode in the project root.
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3.**Activate:** Type `/hive` in the chat to switch to the Hive Agent.
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4.**Verify:** Ask the agent *"List your tools"* to confirm the connection.
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4.**Verify:** Ask the agent _"List your tools"_ to confirm the connection.
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The agent has access to all Hive skills and can scaffold agents, add tools, and debug workflows directly from the chat.
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@@ -180,7 +185,6 @@ Hive is built to be model-agnostic and system-agnostic.
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-**LLM flexibility** - Hive Framework is designed to support various types of LLMs, including hosted and local models through LiteLLM-compatible providers.
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-**Business system connectivity** - Hive Framework is designed to connect to all kinds of business systems as tools, such as CRM, support, messaging, data, file, and internal APIs via MCP.
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## Why Aden
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Hive focuses on generating agents that run real business processes rather than generic agents. Instead of requiring you to manually design workflows, define agent interactions, and handle failures reactively, Hive flips the paradigm: **you describe outcomes, and the system builds itself**—delivering an outcome-driven, adaptive experience with an easy-to-use set of tools and integrations.
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Aden Hive Agent Framework aims to help developers build outcome-oriented, self-adaptive agents. See [roadmap.md](docs/roadmap.md) for details.
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```mermaid
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flowchart TD
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subgraph Foundation
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direction LR
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subgraph arch["Architecture"]
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a1["Node-Based Architecture"]:::done
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a2["Python SDK"]:::done
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a3["LLM Integration"]:::done
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a4["Communication Protocol"]:::done
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end
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subgraph ca["Coding Agent"]
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b1["Goal Creation Session"]:::done
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b2["Worker Agent Creation"]
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b3["MCP Tools"]:::done
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end
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subgraph wa["Worker Agent"]
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c1["Human-in-the-Loop"]:::done
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c2["Callback Handlers"]:::done
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c3["Intervention Points"]:::done
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c4["Streaming Interface"]
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end
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subgraph cred["Credentials"]
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d1["Setup Process"]:::done
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d2["Pluggable Sources"]:::done
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d3["Enterprise Secrets"]
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d4["Integration Tools"]:::done
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flowchart TB
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%% Main Entity
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User([User])
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%% =========================================
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%% EXTERNAL EVENT SOURCES
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%% =========================================
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subgraph ExtEventSource [External Event Source]
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E_Sch["Schedulers"]
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E_WH["Webhook"]
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E_SSE["SSE"]
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end
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subgraph tools["Tools"]
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e1["File Use"]:::done
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e2["Memory STM/LTM"]:::done
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e3["Web Search/Scraper"]:::done
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e4["CSV/PDF"]:::done
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e5["Excel/Email"]
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end
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subgraph core["Core"]
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f1["Eval System"]
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f2["Pydantic Validation"]:::done
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f3["Documentation"]:::done
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f4["Adaptiveness"]
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f5["Sample Agents"]
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end
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end
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subgraph Expansion
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direction LR
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subgraph intel["Intelligence"]
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g1["Guardrails"]
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g2["Streaming Mode"]
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g3["Image Generation"]
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g4["Semantic Search"]
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end
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subgraph mem["Memory Iteration"]
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h1["Message Model & Sessions"]
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h2["Storage Migration"]
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h3["Context Building"]
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h4["Proactive Compaction"]
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h5["Token Tracking"]
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end
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subgraph evt["Event System"]
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i1["Event Bus for Nodes"]
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%% =========================================
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%% SYSTEM NODES
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%% =========================================
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subgraph WorkerBees [Worker Bees]
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WB_C["Conversation"]
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WB_SP["System prompt"]
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subgraph Graph [Graph]
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direction TB
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N1["Node"] --> N2["Node"] --> N3["Node"]
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N1 -.-> AN["Active Node"]
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N2 -.-> AN
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N3 -.-> AN
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%% Nested Event Loop Node
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subgraph EventLoopNode [Event Loop Node]
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ELN_L["listener"]
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ELN_SP["System Prompt<br/>(Task)"]
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ELN_EL["Event loop"]
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ELN_C["Conversation"]
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end
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end
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end
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subgraph cas["Coding Agent Support"]
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j1["Claude Code"]
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j2["Cursor"]
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j3["Opencode"]
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j4["Antigravity"]
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j5["Codex CLI"]
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subgraph JudgeNode [Judge]
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J_C["Criteria"]
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J_P["Principles"]
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J_EL["Event loop"] <--> J_S["Scheduler"]
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end
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subgraph plat["Platform"]
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k1["JavaScript/TypeScript SDK"]
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k2["Custom Tool Integrator"]
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k3["Windows Support"]
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subgraph QueenBee [Queen Bee]
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QB_SP["System prompt"]
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QB_EL["Event loop"]
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QB_C["Conversation"]
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end
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subgraph dep["Deployment"]
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l1["Self-Hosted"]
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l2["Cloud Services"]
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l3["CI/CD Pipeline"]
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subgraph Infra [Infra]
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SA["Sub Agent"]
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TR["Tool Registry"]
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WTM["Write through Conversation Memory<br/>(Logs/RAM/Harddrive)"]
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