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ThearchyHelios
76cb4d2845
验收时盲算、反方审稿的模型把 table 写成 '["orders", "stores"]'（一个字符串），工具只按逗号拆，回「中没有 ["orders"」 「中没有 "stores"]」，两张表明明都在，模型重试几轮才改成不传 table。表名参数的解析抽成 _schema_tables：元素都是 字符串的 JSON 数组（整个作为一个字符串传进来，或者数组里的一项）按数组认，其余照旧按逗号拆；不是 JSON 的 （[orders]、单引号）、元素不是字符串的照旧。只动 db_schema 这一段，查询工具不动。
388 lines
16 KiB
Python
388 lines
16 KiB
Python
"""工具参数的校验、纠错，以及 agent 一轮只跑一个工具。
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起因是一条谁也看不懂的报错：
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工具 db_query__shop 执行失败：
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_make_query_tool.<locals>._run() got an unexpected keyword argument 'query'
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参数名写成了 query（它叫 sql），而动态工具那条调用路径当时是裸 `**args` 展开的，
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于是 pydantic 的"缺少 sql 字段"漏成了一个只剩内部闭包名的 TypeError —— 既指不到
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是哪个工具，也说不出该填什么，人和模型都只能接着猜。
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"""
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from __future__ import annotations
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import sqlite3
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from types import SimpleNamespace
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import pytest
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from langchain_core.messages import ToolMessage
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from pydantic import BaseModel, Field
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from app.engine.nodes.llm import split_tool_calls
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from app.tools.datasource import _make_query_tool, _make_schema_tool
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from app.tools.registry import (
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ToolArgsError,
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ToolContext,
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args_model_of,
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describe_args,
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prepare_args,
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)
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class _QueryLike(BaseModel):
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"""和 datasource 的查询参数同形：一个必填 + 一个可选。"""
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sql: str = Field(description="要执行的 SQL，一次一条")
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limit: int | None = Field(default=None, description="最多返回多少行，默认 1000")
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class _AllOptional(BaseModel):
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table: str | None = Field(default=None, description="表名；留空则列出所有表")
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@pytest.fixture
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def source(tmp_path):
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path = tmp_path / "shop.db"
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db = sqlite3.connect(path)
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db.executescript("CREATE TABLE orders (id INTEGER PRIMARY KEY, amount REAL NOT NULL);")
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db.executemany("INSERT INTO orders(id,amount) VALUES(?,?)", [(i, i * 1.5) for i in range(1, 6)])
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db.commit()
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db.close()
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return SimpleNamespace(
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# id 必须和别的测试文件不同：engine 按 source.id 缓存连接池
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# （app/data/engine.py:121），撞了 id 就会连到人家那个库上——
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# 默认的文件顺序下碰巧不冲突，单跑一个文件或换个顺序就串了
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id="tool-args-src", name="shop", kind="sqlite", database=str(path),
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host=None, port=None, username=None, password=None, options={},
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readonly=True, description="测试库", schema_cache={},
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)
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# --------------------------------------------------------------------------
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# prepare_args
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# --------------------------------------------------------------------------
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def test_unique_candidate_is_corrected() -> None:
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"""多出来一个 query、少了一个必填的 sql —— 候选唯一，改名就是了。"""
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payload, note = prepare_args(_QueryLike, {"query": "SELECT 1"})
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assert payload["sql"] == "SELECT 1"
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assert note and "query" in note and "sql" in note
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def test_correct_args_pass_through_without_a_note() -> None:
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"""本来就对的不该被说成"纠正过"，否则轨迹里全是没用的黄条。"""
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payload, note = prepare_args(_QueryLike, {"sql": "SELECT 1", "limit": 10})
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assert (payload["sql"], payload["limit"]) == ("SELECT 1", 10)
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assert note is None
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def test_ambiguous_names_are_not_guessed() -> None:
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"""两个都不认识时改名就是碰运气，不如把参数表摊开。"""
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with pytest.raises(ToolArgsError) as e:
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prepare_args(_QueryLike, {"foo": "SELECT 1", "bar": 3})
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text = str(e.value)
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assert "sql" in text and "limit" in text
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assert "foo" in text and "bar" in text
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def test_typo_on_all_optional_schema_is_not_silently_dropped() -> None:
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"""全可选的 schema 上，pydantic 默认会把认不出的键悄悄丢掉。
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真丢了的话 {"tabel": "orders"} 会"成功"执行一次什么都没查的调用 ——
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这种静默失败比报错难查得多。这里必须要么纠正、要么报错。
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"""
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payload, note = prepare_args(_AllOptional, {"tabel": "orders"})
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assert payload["table"] == "orders"
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assert note is not None
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def test_wrong_type_names_the_field_and_the_expected_type() -> None:
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"""名字对但类型不对，不是"写错名字"，别顺手改名把错误盖掉。"""
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with pytest.raises(ToolArgsError) as e:
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prepare_args(_QueryLike, {"sql": "SELECT 1", "limit": "很多"})
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assert "limit 的值不合法，应为整数" in str(e.value)
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def test_missing_required_says_what_is_required() -> None:
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with pytest.raises(ToolArgsError) as e:
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prepare_args(_QueryLike, {})
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assert "缺少必填参数 sql" in str(e.value)
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def test_every_problem_is_reported_at_once() -> None:
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"""改对了名字再回来撞一次类型错误，等于让人分两趟改。"""
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with pytest.raises(ToolArgsError) as e:
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prepare_args(_QueryLike, {"query": "SELECT 1", "limit": "很多"})
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text = str(e.value)
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assert "query 不是该工具的参数" in text
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assert "limit 的值不合法" in text
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def test_the_message_is_a_whole_sentence() -> None:
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"""调用方会把它直接拼在工具名后面（"工具 X：…"），不能缺主语。"""
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for args in ({}, {"foo": 1, "bar": 2}, {"sql": "SELECT 1", "limit": "很多"}):
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with pytest.raises(ToolArgsError) as e:
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prepare_args(_QueryLike, args)
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assert str(e.value).startswith("参数有误：")
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# --------------------------------------------------------------------------
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# describe_args —— 这段话是模型下一步改对的唯一依据
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# --------------------------------------------------------------------------
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def test_description_carries_the_field_help_text() -> None:
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text = describe_args(_QueryLike, {"query": "SELECT 1"})
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assert "要执行的 SQL" in text # Field(description=...) 要搬进来
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assert "必填" in text and "可选" in text
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assert "字符串" in text and "整数" in text # 可选字段是 anyOf[int, null]，要摊开
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assert "query" in text # 说清楚"你传的是什么"
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# --------------------------------------------------------------------------
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# 真实的数据源工具：复现开头那条报错
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# --------------------------------------------------------------------------
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async def test_the_original_query_typo_now_runs(source) -> None:
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tool = _make_query_tool(source, ToolContext())
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schema = args_model_of(tool)
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assert schema is not None
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payload, note = prepare_args(schema, {"query": "SELECT COUNT(*) AS c FROM orders"})
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assert note is not None
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result = await tool.coroutine(**payload)
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assert '"c"' in result or "c" in result
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async def test_raw_expansion_is_what_used_to_explode(source) -> None:
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"""记录一下被修掉的是什么：绕开校验直接展开，抛的就是那句天书。"""
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tool = _make_query_tool(source, ToolContext())
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with pytest.raises(TypeError) as e:
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await tool.coroutine(query="SELECT 1")
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assert "unexpected keyword argument" in str(e.value)
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async def test_schema_tool_args_are_validated_too(source) -> None:
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tool = _make_schema_tool(source)
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schema = args_model_of(tool)
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payload, note = prepare_args(schema, {"tabel": "orders"})
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assert payload["table"] == "orders" and note is not None
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def test_tools_without_a_pydantic_schema_are_let_through() -> None:
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"""MCP 这类工具的 args_schema 可能是一份 JSON Schema dict，校验不了就放行。"""
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assert args_model_of(SimpleNamespace(args_schema={"type": "object"})) is None
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assert args_model_of(SimpleNamespace(args_schema=None)) is None
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# --------------------------------------------------------------------------
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# agent 一轮只跑一个工具
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# --------------------------------------------------------------------------
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def _calls() -> list[dict]:
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return [
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{"name": "db_schema__shop", "args": {}, "id": "c1"},
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{"name": "db_query__shop", "args": {"sql": "SELECT 1"}, "id": "c2"},
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{"name": "db_query__shop", "args": {"sql": "SELECT 2"}, "id": "c3"},
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]
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def test_serial_runs_only_the_first() -> None:
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run_calls, deferred = split_tool_calls(_calls(), parallel=False)
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assert [c["id"] for c in run_calls] == ["c1"]
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assert [c["id"] for c, _ in deferred] == ["c2", "c3"]
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def test_every_deferred_call_still_gets_a_result() -> None:
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"""两家 API 都要求每个 tool_use 有一条配对的 tool_result，少一条下次调用就是 400。"""
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calls = _calls()
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run_calls, deferred = split_tool_calls(calls, parallel=False)
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answered = {c["id"] for c in run_calls} | {m.tool_call_id for _, m in deferred}
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assert answered == {c["id"] for c in calls}
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assert all(isinstance(m, ToolMessage) and m.content for _, m in deferred)
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def test_parallel_keeps_every_call() -> None:
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run_calls, deferred = split_tool_calls(_calls(), parallel=True)
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assert len(run_calls) == 3 and deferred == []
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def test_single_call_is_never_deferred() -> None:
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run_calls, deferred = split_tool_calls(_calls()[:1], parallel=False)
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assert len(run_calls) == 1 and deferred == []
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# --------------------------------------------------------------------------
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# 串行也要告诉模型，省得它白发一堆调用
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# --------------------------------------------------------------------------
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def _one_tool():
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from app.tools.registry import all_specs, build_tool
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return [build_tool(next(iter(all_specs().values())), ToolContext())]
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def test_anthropic_gets_disable_parallel_tool_use() -> None:
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"""ChatAnthropic 把它翻成 tool_choice，不是原样的 parallel_tool_calls。
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type 必须是 auto：强制某个工具（any/tool）和 thinking 不能并存，
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而 agent 节点默认是开着 thinking 的。
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"""
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from langchain_anthropic import ChatAnthropic
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from app.providers.factory import bind_tools_safely
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model = ChatAnthropic(model="claude-opus-5", api_key="x",
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thinking={"type": "adaptive", "display": "summarized"})
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choice = bind_tools_safely(model, _one_tool(), parallel=False).kwargs["tool_choice"]
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assert choice == {"type": "auto", "disable_parallel_tool_use": True}
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assert "tool_choice" not in bind_tools_safely(model, _one_tool(), parallel=True).kwargs
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def test_openai_gets_parallel_tool_calls() -> None:
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from langchain_openai import ChatOpenAI
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from app.providers.factory import bind_tools_safely
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model = ChatOpenAI(model="gpt-4o", api_key="x")
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assert bind_tools_safely(model, _one_tool(), parallel=False).kwargs["parallel_tool_calls"] is False
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assert "parallel_tool_calls" not in bind_tools_safely(model, _one_tool(), parallel=True).kwargs
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def test_binding_survives_models_that_ignore_the_flag() -> None:
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"""mock 和各种兼容网关不认这个参数也不能炸——串行本来就有编排层兜底。"""
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from app.providers.factory import bind_tools_safely
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from app.providers.mock_model import MockChatModel
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model = MockChatModel(model_name="mock-fast")
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assert bind_tools_safely(model, _one_tool(), parallel=False) is not None
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# 没有工具时原样返回，不该凭空包一层
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assert bind_tools_safely(model, [], parallel=False) is model
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# --------------------------------------------------------------------------
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# 步数用完时的收尾
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# --------------------------------------------------------------------------
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def test_the_skip_note_never_becomes_the_answer() -> None:
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"""真出过事：run dd9927e6 交给用户的"答案"是一句内部管道文案。
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本轮只执行了第一个工具。看到它的结果之后，再决定这一个还要不要调…
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步数用完时，收尾取的是 messages[-1]——而串行模式下那很可能是一条给模型看的
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ToolMessage。用户看到的不是"没跑完"，是一句冒充结论的管道说明。
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"""
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from langchain_core.messages import AIMessage, HumanMessage
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from app.engine.nodes.llm import SKIPPED_NOTE
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messages = [
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HumanMessage(content="Shop 有几个管理员？"),
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AIMessage(content="我先看看表结构。"),
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ToolMessage(content="表 user …", tool_call_id="c1"),
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ToolMessage(content=SKIPPED_NOTE, tool_call_id="c2"),
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]
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# 收尾该取的是模型自己说过的最后一句，不是消息数组的最后一条
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picked = next(
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(t for m in reversed(messages)
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if isinstance(m, AIMessage) and (t := m.content.strip())),
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"",
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)
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assert picked == "我先看看表结构。"
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assert SKIPPED_NOTE not in picked
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# --------------------------------------------------------------------------
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# 查表结构可以一次问好几张
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# --------------------------------------------------------------------------
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async def test_schema_tool_takes_several_tables_at_once(source) -> None:
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"""一次调用就是一步。逐张问 6 张表就是 6 步，一次 8 步的预算直接见底。"""
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from app.data import introspect
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source.schema_cache = await introspect.introspect(source)
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tool = _make_schema_tool(source)
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one = await tool.coroutine(table="orders")
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assert "orders" in one
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many = await tool.coroutine(table=["orders", "orders"])
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assert many.count("表 orders") == 2 # 两张都描述了，不是只认第一张
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async def test_schema_tool_accepts_a_comma_separated_string(source) -> None:
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"""模型两种写法都会用。为此拒掉一次调用，白白浪费一步。"""
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from app.data import introspect
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source.schema_cache = await introspect.introspect(source)
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out = await _make_schema_tool(source).coroutine(table="orders, orders")
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assert out.count("表 orders") == 2
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async def test_schema_tool_still_lists_everything_when_asked_for_nothing(source) -> None:
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from app.data import introspect
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source.schema_cache = await introspect.introspect(source)
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out = await _make_schema_tool(source).coroutine()
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assert "张表" in out and "orders" in out
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@pytest.fixture
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async def depots(tmp_path):
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"""两张表的库（虚构的仓储）：parcels、depots，结构已探查。"""
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from app.data import introspect
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path = tmp_path / "depots.db"
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db = sqlite3.connect(path)
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db.executescript("CREATE TABLE parcels (id INTEGER PRIMARY KEY, depot_id INTEGER, fee REAL);"
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"CREATE TABLE depots (id INTEGER PRIMARY KEY, zone TEXT);")
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db.commit()
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db.close()
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src = SimpleNamespace(id="tool-args-depots-src", name="depots", kind="sqlite", database=str(path), host=None,
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port=None, username=None, password=None, options={}, readonly=True, description="测试库",
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schema_cache={})
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src.schema_cache = await introspect.introspect(src)
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return src
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@pytest.mark.parametrize("written", ['["parcels", "depots"]', '["parcels","depots"]', ' [ "parcels" , "depots" ] ',
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['["parcels", "depots"]'], ['["parcels"]', "depots"]])
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async def test_schema_tool_reads_a_json_array_written_as_one_string(depots, written) -> None:
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"""2026-10 验收：模型把 table 写成一整个字符串 '["orders", "stores"]'（参数说明里的 ["user","roles"] 引得它这么写），
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只按逗号拆就成了「没有 ["orders"」「没有 "stores"]」——两张都在，模型却白白多调了几轮。写成字符串的 JSON 数组
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和逗号分隔一样认。"""
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out = await _make_schema_tool(depots).coroutine(table=written)
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assert out.count("表 parcels") == 1 and out.count("表 depots") == 1, out
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assert "没有" not in out
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async def test_schema_tool_reads_a_one_table_json_array(depots) -> None:
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out = await _make_schema_tool(depots).coroutine(table='["parcels"]')
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assert out.startswith("表 parcels") and "depots" not in out and "没有" not in out
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# 空数组和不传一样：列出所有表
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assert "共 2 张表" in await _make_schema_tool(depots).coroutine(table="[]")
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@pytest.mark.parametrize("written,missing", [
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("[parcels]", "[parcels]"), # 不是 JSON（名字没加引号）：照旧整个当表名
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("['parcels']", "['parcels']"), # 单引号也不是 JSON
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("[1, 2]", "[1"), # 数组里不是表名：照旧按逗号拆
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])
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async def test_schema_tool_leaves_other_bracketed_text_as_before(depots, written, missing) -> None:
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out = await _make_schema_tool(depots).coroutine(table=written)
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assert f"中没有 {missing}。" in out
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def test_copilot_is_told_not_to_pin_max_steps() -> None:
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"""Copilot 把 max_steps: 8 写进了生成的图，后端默认值根本轮不上。"""
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from app.api.copilot import NODE_REFERENCE
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assert "不要写 max_steps" in NODE_REFERENCE
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