wehub-resource-sync
67 lines
2.4 KiB
Python
67 lines
2.4 KiB
Python
"""End-to-end test for ``examples/rate_limited_search_agent.yaml``.
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The example wires a :class:`FunctionPolicy` (loaded from
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``tests.resources.examples._shared.search_rate_limit_policy``) that caps tool-call counts
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per turn. The policy runs in the tool-call phase of the agent
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loop — every turn exercises the policy's pre/post-tool hooks
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regardless of whether the cap is actually hit.
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**What breaks if this fails:**
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- Spec parser regresses on ``policies:`` entries with
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``type: function`` + agent-local ``callable:`` paths.
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- The FunctionPolicy tool-call phase hook stops firing on agents
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declared via YAML.
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- The per-agent duplicated helper (``search_rate_limit_policy.py``
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copied into the example dir during unification) stops resolving
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via ``tests.resources.examples._shared.search_rate_limit_policy`` dotted lookup.
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"""
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from __future__ import annotations
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from pathlib import Path
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from tests.e2e.omnigent._example_helpers import (
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assert_completed_one_shot,
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run_one_shot,
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)
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from tests.e2e.omnigent.conftest import configure_mock_llm
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# Low-token summary request so the policy's rate limit stays
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# comfortably unrehced — the goal is to exercise the hook, not
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# to trigger the cap.
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_PROMPT = "Summarize in one sentence: the sky is blue."
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def test_rate_limited_search_agent_one_shot(
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omnigent_python: Path,
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omnigent_repo_root: Path,
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mock_credentials_env: dict[str, str],
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mock_llm_server_url: str,
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) -> None:
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"""
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Run the rate-limited search agent one-shot. The FunctionPolicy
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registers + runs its pre-turn hook before the LLM returns.
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Uses the mock LLM server for deterministic responses.
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:param omnigent_python: Interpreter with omnigent +
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openai-agents installed.
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:param omnigent_repo_root: Repo root for subprocess cwd.
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:param mock_credentials_env: Mock-LLM env vars.
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:param mock_llm_server_url: Mock server URL for configuring
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response queues.
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"""
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configure_mock_llm(
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mock_llm_server_url,
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[{"text": "The sky is blue due to Rayleigh scattering of sunlight."}],
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)
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result = run_one_shot(
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omnigent_python=omnigent_python,
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omnigent_repo_root=omnigent_repo_root,
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omnigent_credentials_env=mock_credentials_env,
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example_name="rate_limited_search_agent",
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prompt=_PROMPT,
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model="mock-model",
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)
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assert_completed_one_shot(result, "rate_limited_search_agent")
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