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ThearchyHelios
ba28dee1f0
- api/copilot.py：event_stream 原样搬成 async generator answer_ops(payload, *, catalog_view=None)，交出的 op dict 不变；开流前的准备（数据源、目录检查器、助手模型、历史、查看服务）用自己的短会话，在第一条操作之前做完。SSE 路由只包一层：先取第一条，开流前的拒绝（模型没配好、限定的数据源都不在）照旧是 HTTP 错误
- catalog_view 一路传给查看服务和自查的 SQL 检查器（目录视图接缝的「生成过程从参数读」）
- providers/usage.py：Meter 是一个 LangChain 回调，和 get_usage_metadata_callback 同一个机制（登记过的上下文变量），按模型累计 tokens、次数，金额按价格目录；估不出的记 unpriced_calls。没直接用 get_usage_metadata_callback：with 块跨 yield 会把变量留在调用方上下文里，调用方随后发起的运行会继承它、被重复计一遍；metered 只在每一步 __anext__ 期间挂上，嵌套时并进外层
- 生成过程读到 done / look / ask 就关模型的流（后面的闲话不要），流末尾才报的用量拿不到：这一次照样计次数和已报的 token，记成估不出，不悄悄少算（遗留：真实接入上建图那几次多半是下限）
- providers/budget.py：BudgetFallback.astream 用 aclosing 包住里面那条流——以前调用方关流时里面那条要等垃圾回收才关，模型那次调用的收尾（用量回调）落在算完账之后；测试去掉它回跑会少计一次
- answer_ops 末尾多一条 {op: usage, by_model, input_tokens, output_tokens, calls, cost_usd, unpriced_calls}；/copilot/review 拆出 review_of_run（问数据页、评测共用），结果带 usage（没调模型时全 0）和 retry_instruction（要不要带着原图重来、说什么，按 chat/turn.py 的决定算；ReviewIn 多一个 attempt）
- 新增 app/chat/turn.py（问数据一轮的决定，复核这边先用上；final.next、对照测试、前端照做在下一个提交）；新增 tests/test_copilot_answer_ops.py（八种结局的 SSE 输出和抽出来之前录下的 fixtures/copilot_answer_ops_baseline.json 逐条相同，末尾多一条 usage；直接迭代和 SSE 同一串；开流前的拒绝仍是 HTTP 错误）、tests/test_usage_meter.py；读 SSE 的十一个测试文件的收流帮手跳过末尾那条 usage
299 lines
14 KiB
Python
299 lines
14 KiB
Python
"""Copilot 没说完就不能按「无需修改」交付。
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2026-09 部署实例上，复杂的改图需求（并行算同比、环比，再加一个单独的 agent）连续两次得到
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「已检查，画布无需修改 · 自查通过」。按同一模型、同一张底图、同一句指令重放：输出额度 8192
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全部用在思考上（finish_reason=length），正文一个字都没有。读流时不看 finish_reason，也不要求
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收到 done，于是自查对着原图报「通过」，final 交回原图，前端比出来没变化就说「无需修改」。
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这里守几件事：
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- 输出被截断（OpenAI 系的 finish_reason=length、Anthropic 的 stop_reason=max_tokens）要报错，
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不跑自查、不交 final；
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- 流正常结束却一个操作都没给、也没有 done（格式跑偏，全被跳过了）同样报错；
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- 模型明确说完了（有 done）但没改任何东西，照旧交付——那才是真的无需修改；
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- 改图的额度要够思考之后还写得下操作；服务方一开口就嫌额度太大时退回 8192 重来。
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"""
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from __future__ import annotations
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import json
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import pytest
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from httpx import ASGITransport, AsyncClient
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from langchain_core.messages import AIMessageChunk
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from app.api import copilot as cp
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from app.api.copilot import _iter_ops
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from app.main import app
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@pytest.fixture
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async def client():
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async with AsyncClient(transport=ASGITransport(app=app), base_url="http://test") as c:
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yield c
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def _node(nid: str, ntype: str, config: dict) -> dict:
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return {"id": nid, "type": ntype, "position": {"x": 0, "y": 0}, "data": {"label": nid, "config": config}}
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#: 一张本来就能过自查的图：截断时自查对着它报「通过」，正是那次的样子
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BASE = {
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"nodes": [
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_node("start", "input", {"fields": [{"name": "question"}]}),
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_node("answer", "llm", {"prompt": "{{ input.question }}", "assign_to": "answer"}),
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_node("out", "output", {"fields": [{"name": "答案", "value": "{{ vars.answer }}"}]}),
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],
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"edges": [{"source": "start", "target": "answer"}, {"source": "answer", "target": "out"}],
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}
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def _line(op: dict) -> AIMessageChunk:
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return AIMessageChunk(content=json.dumps(op, ensure_ascii=False) + "\n")
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def _thinking(text: str) -> AIMessageChunk:
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# OpenAI 兼容系（DeepSeek 经 LiteLLM）的思考走 reasoning_content
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return AIMessageChunk(content="", additional_kwargs={"reasoning_content": text})
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def _openai_cut() -> AIMessageChunk:
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return AIMessageChunk(content="", response_metadata={"finish_reason": "length"})
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def _anthropic_cut() -> AIMessageChunk:
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return AIMessageChunk(content=[], response_metadata={"stop_reason": "max_tokens"})
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class _Scripted:
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"""按剧本吐 chunk 的模型。each 是每次调用吐的那一串；调用次数多于剧本时重复最后一串。"""
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def __init__(self, *each: list[AIMessageChunk], max_tokens: int | None = None) -> None:
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self.each = each
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self.calls = 0
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self.max_tokens = max_tokens
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async def astream(self, messages):
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chunks = self.each[min(self.calls, len(self.each) - 1)]
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self.calls += 1
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for chunk in chunks:
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yield chunk
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async def _events(client, monkeypatch, model, base: dict | None = BASE) -> list[dict]:
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async def _model(*_a, **_k):
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return model, "mock-fast"
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monkeypatch.setattr(cp, "get_chat_model", _model)
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out: list[dict] = []
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async with client.stream("POST", "/api/copilot/generate-stream",
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json={"instruction": "并行算同比和环比", "base_graph": base}) as r:
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async for line in r.aiter_lines():
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# 末尾那条 usage 是这一轮助手的用量（answer_ops），不是生成的操作
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if line.startswith("data: ") and not line.startswith('data: {"op": "usage"'):
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out.append(json.loads(line[6:]))
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return out
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def _kinds(events: list[dict]) -> list[str]:
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return [e["op"] for e in events if e["op"] not in ("thinking", "heartbeat", "model")]
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# ---------------------------------------------------------------------------
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# 读流这一层
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# ---------------------------------------------------------------------------
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@pytest.mark.parametrize("cut", [_openai_cut, _anthropic_cut], ids=["finish_reason", "stop_reason"])
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async def test_a_cut_off_stream_raises(cut):
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model = _Scripted([_thinking("先想想怎么拆成并行分支……"), _line({"op": "plan", "summary": "拆成三支"}),
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AIMessageChunk(content='{"op":"add_node","node":{"id":"yo'), cut()])
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got: list[dict] = []
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with pytest.raises(cp.CopilotIncomplete) as info:
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async for op in _iter_ops(model, []):
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got.append(op)
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assert [o["op"] for o in got] == ["thinking", "plan"], "截断之前的操作照常转出去"
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assert "长度上限" in str(info.value)
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assert info.value.hint
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async def test_done_that_lands_exactly_at_the_limit_is_complete():
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"""最后一行 done 刚好写完（没来得及换行）就到了上限：模型已经说完了，不算截断。"""
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model = _Scripted([_line({"op": "plan", "summary": "x"}),
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AIMessageChunk(content='{"op":"done","explanation":"好了"}'), _openai_cut()])
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ops = [o async for o in _iter_ops(model, [])]
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assert [o["op"] for o in ops] == ["plan", "done"]
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async def test_a_normal_finish_is_not_a_cut():
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model = _Scripted([_line({"op": "plan", "summary": "x"}), _line({"op": "done", "explanation": "y"}),
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AIMessageChunk(content="", response_metadata={"finish_reason": "stop"})])
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ops = [o async for o in _iter_ops(model, [])]
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assert [o["op"] for o in ops] == ["plan", "done"]
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# ---------------------------------------------------------------------------
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# 画布改图：截断和空手而归都不能冒充「无需修改」
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# ---------------------------------------------------------------------------
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async def test_thinking_that_eats_the_whole_budget_is_an_error_not_unchanged(client, monkeypatch):
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"""就是截图里那一轮：只有思考、没有正文，额度用完。"""
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model = _Scripted([_thinking("Let me design the modification. "), _thinking("report_ans has 4 incoming edges."),
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_openai_cut()], max_tokens=8192)
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events = await _events(client, monkeypatch, model)
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kinds = _kinds(events)
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assert "final" not in kinds, "没说完的一轮不能把原图当成结果交回去"
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assert "check" not in kinds, "自查对着原图报「通过」，是在替一个没发生的修改作证"
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[err] = [e for e in events if e["op"] == "error"]
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assert err["message"].startswith("助手本轮未完成：") and "长度上限" in err["message"]
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assert "画布未修改" in err["hint"]
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assert "length" in err["detail"] and "8192" in err["detail"]
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async def test_a_cut_in_the_middle_of_the_ops_is_not_delivered_as_done(client, monkeypatch):
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"""写到一半被截断：半张图不能当成品交付，更不能自动开跑。"""
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model = _Scripted([
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_line({"op": "plan", "summary": "加一支"}),
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_line({"op": "add_node", "node": {"id": "yoy", "type": "llm", "label": "同比",
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"config": {"prompt": "算同比", "assign_to": "yoy"}}}),
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_anthropic_cut(),
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])
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events = await _events(client, monkeypatch, model)
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kinds = _kinds(events)
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assert "final" not in kinds
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assert kinds[-1] == "error"
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async def test_output_that_parses_to_nothing_is_an_error(client, monkeypatch):
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"""格式跑偏（整段放进 markdown 围栏、JSON 分了行），每一行都被跳过：一个操作都没有，也没有 done。"""
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pretty = "```json\n" + json.dumps({"op": "add_node", "node": {"id": "yoy", "type": "llm"}}, indent=2) + "\n```\n"
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model = _Scripted([AIMessageChunk(content=pretty),
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AIMessageChunk(content="", response_metadata={"finish_reason": "stop"})])
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events = await _events(client, monkeypatch, model)
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kinds = _kinds(events)
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assert "final" not in kinds
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[err] = [e for e in events if e["op"] == "error"]
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assert err["message"].startswith("助手本轮未完成：") and "画布未修改" in err["hint"]
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async def test_a_model_that_says_done_without_changes_is_still_unchanged(client, monkeypatch):
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"""模型看过、明确收尾、一处不改：这才是真的「无需修改」，照旧交付。"""
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model = _Scripted([_line({"op": "plan", "summary": "现有的图已经满足"}),
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_line({"op": "done", "explanation": "不需要改"})])
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events = await _events(client, monkeypatch, model)
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final = events[-1]
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assert final["op"] == "final" and final["explanation"] == "不需要改"
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assert {n["id"] for n in final["graph"]["nodes"]} == {"start", "answer", "out"}
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assert "error" not in _kinds(events)
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async def test_a_cut_in_the_repair_round_is_reported(client, monkeypatch):
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"""自查交回去修的那一轮被截断：要说修正没完成，不能说「自查通过」。"""
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broken = [
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_line({"op": "plan", "summary": "加个循环"}),
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_line({"op": "add_node", "node": {"id": "lp", "type": "loop", "label": "循环",
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"config": {"mode": "while", "condition": "foo(vars.x)",
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"max_iterations": 2}}}),
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_line({"op": "add_edge", "edge": {"source": "answer", "target": "lp"}}),
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_line({"op": "add_edge", "edge": {"source": "lp", "target": "out", "sourceHandle": "done"}}),
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_line({"op": "done", "explanation": "加好了"}),
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]
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model = _Scripted(broken, [_thinking("修一下条件"), _openai_cut()])
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events = await _events(client, monkeypatch, model)
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checks = [e for e in events if e["op"] == "check"]
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assert checks[0]["status"] == "repairing"
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assert any(c["status"] == "error" and "长度上限" in c["message"] for c in checks), checks
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assert not any(c["status"] == "passed" for c in checks)
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# ---------------------------------------------------------------------------
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# 额度
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# ---------------------------------------------------------------------------
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async def test_the_stream_asks_for_a_budget_that_leaves_room_after_thinking(client, monkeypatch):
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asked: list[int | None] = []
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async def _model(_session, spec):
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asked.append(spec.max_tokens)
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return _Scripted([_line({"op": "plan", "summary": "x"}), _line({"op": "done", "explanation": "y"})]), "m"
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monkeypatch.setattr(cp, "get_chat_model", _model)
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async with client.stream("POST", "/api/copilot/generate-stream",
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json={"instruction": "改一下", "base_graph": BASE}) as r:
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[line async for line in r.aiter_lines()]
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assert asked and asked[0] >= 32768, asked
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class _BudgetTooLarge(Exception):
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"""仿 openai / anthropic SDK 的 400：一发请求就被拒，还没吐出任何东西。"""
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status_code = 400
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class _Rejects:
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def __init__(self, message: str) -> None:
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self.message = message
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self.calls = 0
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async def astream(self, messages):
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self.calls += 1
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raise _BudgetTooLarge(self.message)
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yield # pragma: no cover - 让它成为异步生成器
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@pytest.mark.parametrize("message", [
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"Invalid max_tokens value, the valid range of max_tokens is [1, 8192]",
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"max_tokens: 32768 > 8192, which is the maximum allowed number of output tokens",
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"This model's maximum context length is 32768 tokens. However, you requested 40369 tokens "
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"(7601 in the messages, 32768 in the completion).",
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])
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async def test_a_rejected_budget_falls_back_to_the_old_one(client, monkeypatch, message):
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big = _Rejects(message)
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small = _Scripted([_line({"op": "plan", "summary": "x"}),
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_line({"op": "add_node", "node": {"id": "yoy", "type": "llm", "label": "同比",
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"config": {"prompt": "算同比", "assign_to": "yoy"}}}),
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_line({"op": "add_edge", "edge": {"source": "answer", "target": "yoy"}}),
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_line({"op": "add_edge", "edge": {"source": "yoy", "target": "out"}}),
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_line({"op": "done", "explanation": "加好了"})])
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asked: list[int | None] = []
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async def _model(_session, spec):
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asked.append(spec.max_tokens)
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return (big if spec.max_tokens and spec.max_tokens > 8192 else small), "m"
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monkeypatch.setattr(cp, "get_chat_model", _model)
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events: list[dict] = []
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async with client.stream("POST", "/api/copilot/generate-stream",
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json={"instruction": "加一支同比", "base_graph": BASE}) as r:
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async for line in r.aiter_lines():
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# 末尾那条 usage 是这一轮助手的用量（answer_ops），不是生成的操作
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if line.startswith("data: ") and not line.startswith('data: {"op": "usage"'):
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events.append(json.loads(line[6:]))
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assert 8192 in asked
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assert big.calls == 1 and small.calls == 1
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final = events[-1]
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assert final["op"] == "final" and "yoy" in {n["id"] for n in final["graph"]["nodes"]}
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async def test_other_rejections_are_not_retried(client, monkeypatch):
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"""别的 400（模型名写错之类）照实报错，不拿小额度再撞一次。"""
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big = _Rejects("model 'no-such-model' does not exist")
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small = _Scripted([_line({"op": "done", "explanation": "不该到这里"})])
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async def _model(_session, spec):
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return (big if spec.max_tokens and spec.max_tokens > 8192 else small), "m"
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monkeypatch.setattr(cp, "get_chat_model", _model)
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events: list[dict] = []
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async with client.stream("POST", "/api/copilot/generate-stream",
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json={"instruction": "改一下", "base_graph": BASE}) as r:
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async for line in r.aiter_lines():
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# 末尾那条 usage 是这一轮助手的用量（answer_ops），不是生成的操作
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if line.startswith("data: ") and not line.startswith('data: {"op": "usage"'):
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events.append(json.loads(line[6:]))
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assert small.calls == 0
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assert events[-1]["op"] == "error"
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def test_the_protocol_asks_not_to_draft_the_json_while_thinking():
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"""思考里把整段 JSON 先写一遍，额度就去了一半：那一轮重放时思考的结尾正在逐字写口径卡的表达式。"""
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assert "思考" in cp._STREAM_PROTOCOL and "不要在思考里" in cp._STREAM_PROTOCOL
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