feat: preserve governed OpenAI tool messages in 1.4.0
Add faithful single-choice chat results, tool stream activity, error-frame retries, and isolated protocol caching. Reject empty cached completions with the same value predicate as transport, add regression coverage, and adopt Apache-2.0.
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"""协议聚合器的分片、防御与快照契约。"""
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import copy
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import json
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import pytest
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from polygateway.errors import TransientError
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from polygateway.transports._openai_completion import (
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ChatCompletionAccumulator,
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parse_chat_completion,
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)
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def chunk(delta, **extra):
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"""构造单 choice 协议帧。"""
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return (
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"data: "
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+ json.dumps({"id": "upstream-1", "choices": [{"index": 0, "delta": delta, **extra}]})
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+ "\n\n"
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)
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def tool_frames():
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"""两个交错分片工具，保留空白及 Unicode。"""
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return [
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chunk({"role": "assistant", "content": None}),
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chunk(
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{
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"tool_calls": [
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{
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"index": 1,
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"id": "b",
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"type": "function",
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"function": {"name": "echo", "arguments": '{"v":'},
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},
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{
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"index": 0,
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"id": "a",
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"type": "function",
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"function": {"name": "echo", "arguments": "{"},
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},
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]
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}
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),
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chunk(
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{
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"tool_calls": [
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{"index": 0, "function": {"arguments": '"v": "中" }'}},
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{"index": 1, "function": {"arguments": "2}"}},
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]
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},
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finish_reason="tool_calls",
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),
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]
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def accumulate():
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"""复用双工具网关帧样本。"""
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state = ChatCompletionAccumulator(response_mode="openai")
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for frame in tool_frames():
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state.add_chunk(json.loads(frame.removeprefix("data: ")))
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return state
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@pytest.mark.parametrize("role", [None, "user", "tool"])
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def test_role_is_required_everywhere(role):
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"""缺角色不能被协议成功掩盖。"""
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state = accumulate()
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state.message.pop("role")
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if role:
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state.message["role"] = role
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with pytest.raises(TransientError, match="role"):
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state.finish()
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with pytest.raises(TransientError, match="role"):
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parse_chat_completion({"choices": [{"message": state.message}]})
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@pytest.mark.parametrize(
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"change",
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[
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lambda t: t.pop("id"),
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lambda t: t.update(type="custom"),
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lambda t: t["function"].pop("name"),
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lambda t: t["function"].pop("arguments"),
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lambda t: t["function"].update(arguments=12),
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],
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)
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def test_incomplete_tool_is_not_success(change):
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"""工具必需字段不能靠正文兜底。"""
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state = accumulate()
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state.message["content"] = "text"
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change(state.tools[0])
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with pytest.raises(TransientError):
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state.finish()
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@pytest.mark.parametrize(
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"delta",
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[
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[],
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{"audio": {}},
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{"tool_calls": {}},
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{"content": []},
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{"tool_calls": [{"index": True}]},
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{"tool_calls": [{"index": -1}]},
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{"tool_calls": [{"index": 0, "extra": 1}]},
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{"tool_calls": [{"index": 0, "function": {"arguments": None}}]},
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],
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)
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def test_invalid_delta_is_domain_error(delta):
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"""畸形输入不泄漏裸类型错误。"""
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state = ChatCompletionAccumulator(response_mode="openai")
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with pytest.raises(TransientError):
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state.add_chunk({"choices": [{"index": 0, "delta": delta}]})
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def test_identity_repeat_does_not_refresh_progress():
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"""身份只初次生效算进展；同值重复不能续命。"""
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state = accumulate()
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repeated = {
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"choices": [
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{"index": 0, "delta": {"tool_calls": [{"index": 0, "id": "a", "type": "function"}]}}
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]
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}
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assert not state.add_chunk(repeated).progress
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repeated["choices"][0]["delta"]["tool_calls"][0]["id"] = "other"
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with pytest.raises(TransientError, match="冲突"):
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state.add_chunk(repeated)
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@pytest.mark.parametrize("delta", [{"role": "assistant"}, {}, {"content": ""}])
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def test_metadata_not_progress(delta):
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"""空帧和角色不算 token。"""
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state = ChatCompletionAccumulator(response_mode="openai")
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assert not state.add_chunk({"choices": [{"index": 0, "delta": delta}]}).progress
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def test_nonstream_snapshot_and_length_preserved():
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"""非流式扩展字段与参数原文独立保存，不修复 length 产物。"""
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message = accumulate().finish().message
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message["extension"] = {"nested": [1]}
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message["tool_calls"][0]["function"]["arguments"] = '{"unfinished":'
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original = copy.deepcopy(message)
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result = parse_chat_completion(
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{
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"id": "id",
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"choices": [{"message": message, "finish_reason": "length"}],
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"usage": {"extra": 3},
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}
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)
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message["extension"]["nested"].append(2)
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assert result.message == original
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assert result.finish_reason == "length" and result.usage == {"extra": 3}
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@pytest.mark.parametrize("choices", [[], [{"index": 1, "message": {}}], [{}, {}]])
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def test_nonstream_single_choice(choices):
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"""不会静默取第一个 choice。"""
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with pytest.raises(TransientError):
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parse_chat_completion({"choices": choices})
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def test_explicit_empty_tools_remains_present():
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"""显式空工具列表与缺省不同，不删除已接收字段。"""
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state = ChatCompletionAccumulator(response_mode="openai")
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state.add_chunk(
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{
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"choices": [
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{"index": 0, "delta": {"role": "assistant", "content": "ok", "tool_calls": []}}
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]
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}
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)
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assert state.finish().message["tool_calls"] == []
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def test_fragmented_name_and_arguments_with_usage():
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"""名称/参数分片逐字拼接，usage 扩展原样快照。"""
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state = ChatCompletionAccumulator(response_mode="openai")
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state.add_chunk(
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{
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"id": "response",
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"choices": [
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{
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"index": 0,
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"delta": {
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"role": "assistant",
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"tool_calls": [
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{
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"index": 3,
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"id": "call",
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"type": "function",
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"function": {"name": "ec", "arguments": " "},
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}
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],
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},
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}
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],
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}
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)
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progress = state.add_chunk(
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{
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"choices": [
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{
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"index": 0,
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"delta": {
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"content": "text",
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"reasoning_content": "reason",
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"tool_calls": [
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{"index": 3, "function": {"name": "ho", "arguments": "{} "}}
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],
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},
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"finish_reason": "length",
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}
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]
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}
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)
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assert (
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progress.content == "text" and progress.reasoning_content == "reason" and progress.progress
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)
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usage = {"prompt_tokens": 7, "completion_tokens": 2, "extra": {"nested": 9}}
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assert not state.add_chunk({"choices": [], "usage": usage}).progress
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result = state.finish()
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usage["extra"]["nested"] = 10
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assert result.message["tool_calls"][0]["function"] == {"name": "echo", "arguments": " {} "}
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assert result.usage["extra"]["nested"] == 9
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assert result.finish_reason == "length"
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