halo-format-langgraph 0.4.0

Halo host adapter for LangChain agents and LangGraph graphs (Python): a wrap_tool_call encode middleware plus a halo_fetch navigation tool. install_halo() wires it in one call.

halo-format-langgraph

Halo host adapter for LangChain agents and LangGraph graphs (Python). install_halo() wires it in one call:

• a wrap_tool_call encode middleware — the deterministic wrap-the-tool-call hook, LangChain's analog of the Claude SDK's PostToolUse — that replaces a large tool result with a halo shape map (root kind + one line per field: ref, kind, and a bounded preview), so the payload stays out of the model's context while it still sees what's there. The full envelope rides in the ToolMessage artifact (kept in graph state, never sent to the model) for audit/replay;
• a single plain LangChain halo_fetch tool the model uses to pull back only the leaves it needs, verified on read — a ref that lands on a branch returns that branch's sub-refs, so one batch API both pulls and expands (there is no separate halo_walk).

from langchain.agents import create_agent
from halo_format_langgraph import install_halo

result = install_halo(tools=my_tools)
agent = create_agent(model, tools=result.tools, middleware=result.middleware)
# result.session holds the shared store for audit/inspection

For hand-built StateGraphs, use halo_tool_node(tools=...) instead — it returns a ToolNode with the same wrapper attached as wrap_tool_call / awrap_tool_call, plus the tools list (to bind to your model) and the session.

The middleware is deterministic plumbing (it always fires, for every tool); the Halo Skill (or prompt-mode guidance) is the navigation behavior. Pass store=FileStore(dir) for the heavy/persistent deployment. The core engine is halo-format; this package is only the shim.