nihalashetty
ae67bff5a3
Self-hosted platform for building, testing, and shipping LangChain/LangGraph agents. Deep-agent sub-agents on the canvas, a live tracing/observability timeline, auto-provisioned built-in tools with import/export, per-environment tool variables, streamed evaluations, and per-user auth token forwarding.
38 lines
1.6 KiB
Python
38 lines
1.6 KiB
Python
"""Error-workflow fallback: an erroring run returns the on_error message gracefully."""
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from __future__ import annotations
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from langgraph.checkpoint.memory import InMemorySaver
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from forge.db.base import SessionLocal
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from forge.models import Workflow
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from forge.services.dispatch import dispatch_message
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from forge.services.runs import RunService
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# agent with an unknown middleware type -> compile_workflow raises (deterministic, offline).
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# run_to_completion compiles inside its try block, so the on_error fallback covers it.
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_ERR_WF = {
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"id": "wf_err", "version": 1,
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"state": {"messages": {"type": "list[message]", "reducer": "add_messages"}},
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"entry_node": "agent",
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"on_error": {"message": "Sorry - something went wrong. A teammate will follow up."},
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"nodes": [
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{"id": "agent", "type": "agent", "config": {"flavor": "agent", "model": "fake:hi", "middleware": [{"type": "___nonexistent___", "enabled": True}]}},
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{"id": "end", "type": "end", "config": {}},
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],
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"edges": [{"source": "agent", "target": "end"}],
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}
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async def test_errored_run_returns_on_error_message():
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async with SessionLocal() as s:
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wf = Workflow(tenant_id="t_err", project_id="p_err", name="Err", executable=_ERR_WF, status="active")
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s.add(wf)
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await s.commit()
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await s.refresh(wf)
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rs = RunService(checkpointer=InMemorySaver())
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result = await dispatch_message(rs, tenant_id="t_err", project_id="p_err", workflow_id=wf.id, text="hi")
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assert result.get("error") # the run did fail
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assert result.get("error_handled") is True
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assert result.get("answer") == "Sorry - something went wrong. A teammate will follow up."
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