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https://github.com/tiennm99/DocsGPT.git
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arc53-machine
ab3dbfa1be
chunks is a total per request, split across the attached sources, so an agent with two sources and the default of 2 got a single chunk from each, and its answers changed with whichever chunk won. 6 gives three per source for about 4-5k more input tokens per retrieval turn. Every literal default moves from 2 to 6: the request default, the retrievers, the internal search tool, workflow agent nodes, scheduled and headless runs, agent create/update/import, the source retrieval config and the frontend forms. Existing agents and sources keep what they store; a source saved with chunks=2 now counts as configured at 2, which is pinned by a test. Headless runs also read chunks=0 as unset (`or 2`), so an agent with retrieval switched off retrieved anyway on scheduled runs; 0 now stays 0.
69 lines
2.5 KiB
Python
69 lines
2.5 KiB
Python
"""``run_agent_headless`` passes the agent's ``chunks`` to the retriever.
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``chunks=0`` switches retrieval off, but ``int(... or 2)`` read it as unset,
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so a scheduled run of an agent with retrieval off retrieved anyway.
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"""
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from __future__ import annotations
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from unittest.mock import MagicMock, patch
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import pytest
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def _retriever_chunks(agent_config, monkeypatch):
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"""The ``chunks`` a headless run hands to the retriever."""
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from docsgpt.agents import headless_runner as hr
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agent = MagicMock(name="agent")
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agent.gen.return_value = iter([{"answer": "ok"}])
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agent.llm.token_usage = {"prompt_tokens": 1, "generated_tokens": 1}
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retriever = MagicMock(name="retriever")
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retriever.search.return_value = []
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created = {}
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def create_retriever(cls, *args, **kwargs):
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created.update(kwargs)
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return retriever
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tool_executor = MagicMock(name="tool_executor")
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tool_executor.headless_denials = []
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monkeypatch.setattr(hr, "get_prompt", lambda _pid: "system prompt")
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monkeypatch.setattr(
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hr.RetrieverCreator, "create_retriever", classmethod(create_retriever),
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)
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monkeypatch.setattr(hr, "ToolExecutor", lambda *a, **kw: tool_executor)
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monkeypatch.setattr(
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hr.AgentCreator, "create_agent",
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classmethod(lambda cls, *a, **kw: agent),
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)
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config = {"user_id": "u1", "id": "agent-1", "default_model_id": "m", **agent_config}
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with patch("docsgpt.core.model_utils.validate_model_id", return_value=True), \
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patch("docsgpt.core.model_utils.get_default_model_id", return_value="m"), \
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patch(
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"docsgpt.core.model_utils.get_provider_from_model_id",
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return_value="openai",
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), \
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patch("docsgpt.core.model_utils.get_api_key_for_provider", return_value="k"), \
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patch("docsgpt.utils.calculate_doc_token_budget", return_value=1000):
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hr.run_agent_headless(config, "do the thing")
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return created["chunks"]
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@pytest.mark.unit
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class TestHeadlessRunnerChunks:
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def test_unset_chunks_uses_the_default(self, monkeypatch):
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assert _retriever_chunks({}, monkeypatch) == 6
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def test_null_chunks_uses_the_default(self, monkeypatch):
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assert _retriever_chunks({"chunks": None}, monkeypatch) == 6
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def test_zero_chunks_keeps_retrieval_off(self, monkeypatch):
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assert _retriever_chunks({"chunks": 0}, monkeypatch) == 0
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def test_explicit_chunks_is_kept(self, monkeypatch):
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assert _retriever_chunks({"chunks": 4}, monkeypatch) == 4
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