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Why a Graph

Business workflows are rarely linear. Hive models execution as a directed graph so agents can branch, retry, loop, and escalate.

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Nodes

Nodes are units of work that read from shared memory, perform logic, and write outputs. Core node types:
  • event_loop: multi-turn LLM + tools loop (primary autonomous workhorse)
  • function: deterministic Python logic
  • router: rule-based or model-assisted path selection
  • human_input: pause for supervised input
  • llm_tool_use and llm_generate: simpler one-shot LLM nodes

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Self-Correction in event_loop

Each iteration can end with:
  • Accept
  • Retry
  • Escalate
This reflexive loop improves within-session reliability without restarting the full run.

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Edges

Edges define control flow:
  • On success
  • On failure
  • Conditional
  • LLM-decided
Edges can also map outputs to downstream inputs and enable parallel branches.

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Shared Memory

Shared memory is session-scoped state used for cross-node communication.
  • Nodes declare read/write contracts
  • Execution remains traceable and structured
  • Final state represents run output and side effects

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Human-in-the-Loop

HITL nodes pause execution and preserve session state until a human responds. Use HITL for high-impact actions (financial operations, outbound communications, approvals).

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Graph Shape Example

intake -> research -> draft -> [human review] -> send -> done
              ^                                     |
              +------------ on failure -------------+