Add fastgpt as seperate assistant mode
This commit is contained in:
Xin Wang
411
engine/tests/test_fastgpt_provider.py
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411
engine/tests/test_fastgpt_provider.py
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import json
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from types import SimpleNamespace
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from typing import Any, Dict, List
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import pytest
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from providers.common.base import LLMMessage
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from providers.llm.fastgpt import FastGPTLLMService
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class _FakeResponse:
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def __init__(self, events: List[Any]):
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self.events = events
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self.closed = False
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async def close(self) -> None:
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self.closed = True
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class _FakeJSONResponse:
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def __init__(self, payload: Dict[str, Any], status_code: int = 200):
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self._payload = payload
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self.status_code = status_code
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def json(self) -> Dict[str, Any]:
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return dict(self._payload)
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def raise_for_status(self) -> None:
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if self.status_code >= 400:
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raise RuntimeError(f"HTTP {self.status_code}")
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class _FakeAsyncStreamResponse(_FakeResponse):
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def __init__(self, events: List[Any]):
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super().__init__(events)
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self.aclosed = False
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def close(self) -> None:
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raise AssertionError("sync close should not be used for async stream responses")
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async def aclose(self) -> None:
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self.aclosed = True
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class _FakeAsyncChatClient:
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responses: List[_FakeResponse] = []
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init_payload: Dict[str, Any] | None = None
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def __init__(self, api_key: str, base_url: str):
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self.api_key = api_key
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self.base_url = base_url
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self.requests: List[Dict[str, Any]] = []
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self.init_requests: List[Dict[str, Any]] = []
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async def create_chat_completion(self, **kwargs):
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self.requests.append(dict(kwargs))
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if not self.responses:
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raise AssertionError("No fake FastGPT response queued")
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return self.responses.pop(0)
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async def get_chat_init(self, **kwargs):
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self.init_requests.append(dict(kwargs))
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return _FakeJSONResponse(
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self.init_payload or {"data": {"app": {"chatConfig": {"welcomeText": ""}}}},
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)
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async def close(self) -> None:
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return None
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async def _fake_aiter_stream_events(response: _FakeResponse):
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for event in response.events:
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yield event
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@pytest.mark.asyncio
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async def test_fastgpt_provider_streams_text_from_data_event(monkeypatch):
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monkeypatch.setattr("providers.llm.fastgpt.AsyncChatClient", _FakeAsyncChatClient)
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monkeypatch.setattr("providers.llm.fastgpt.aiter_stream_events", _fake_aiter_stream_events)
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_FakeAsyncChatClient.responses = [
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_FakeResponse(
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[
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SimpleNamespace(
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kind="data",
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data={"choices": [{"delta": {"content": "Hello from FastGPT."}}]},
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),
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SimpleNamespace(kind="done", data={}),
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]
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)
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]
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service = FastGPTLLMService(api_key="key", base_url="https://fastgpt.example")
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await service.connect()
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events = [event async for event in service.generate_stream([LLMMessage(role="user", content="Hi")])]
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assert [event.type for event in events] == ["text_delta", "done"]
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assert events[0].text == "Hello from FastGPT."
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assert service.client.requests[0]["messages"] == [{"role": "user", "content": "Hi"}]
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assert service.client.requests[0]["chatId"] == service._state.chat_id
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@pytest.mark.asyncio
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async def test_fastgpt_provider_streams_text_from_answer_delta_event(monkeypatch):
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monkeypatch.setattr("providers.llm.fastgpt.AsyncChatClient", _FakeAsyncChatClient)
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monkeypatch.setattr("providers.llm.fastgpt.aiter_stream_events", _fake_aiter_stream_events)
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_FakeAsyncChatClient.responses = [
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_FakeResponse(
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[
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SimpleNamespace(
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kind="answer",
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data={"choices": [{"delta": {"content": "Hello from answer delta."}}]},
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),
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SimpleNamespace(kind="done", data={}),
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]
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)
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]
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service = FastGPTLLMService(api_key="key", base_url="https://fastgpt.example")
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await service.connect()
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events = [event async for event in service.generate_stream([LLMMessage(role="user", content="Hi")])]
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assert [event.type for event in events] == ["text_delta", "done"]
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assert events[0].text == "Hello from answer delta."
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@pytest.mark.asyncio
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async def test_fastgpt_provider_uses_async_close_for_stream_responses(monkeypatch):
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monkeypatch.setattr("providers.llm.fastgpt.AsyncChatClient", _FakeAsyncChatClient)
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monkeypatch.setattr("providers.llm.fastgpt.aiter_stream_events", _fake_aiter_stream_events)
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response = _FakeAsyncStreamResponse(
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[
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SimpleNamespace(
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kind="data",
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data={"choices": [{"delta": {"content": "Hello from FastGPT."}}]},
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),
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SimpleNamespace(kind="done", data={}),
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]
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)
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_FakeAsyncChatClient.responses = [response]
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service = FastGPTLLMService(api_key="key", base_url="https://fastgpt.example")
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await service.connect()
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events = [event async for event in service.generate_stream([LLMMessage(role="user", content="Hi")])]
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assert [event.type for event in events] == ["text_delta", "done"]
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assert response.aclosed is True
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@pytest.mark.asyncio
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async def test_fastgpt_provider_loads_initial_greeting_from_chat_init(monkeypatch):
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monkeypatch.setattr("providers.llm.fastgpt.AsyncChatClient", _FakeAsyncChatClient)
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monkeypatch.setattr("providers.llm.fastgpt.aiter_stream_events", _fake_aiter_stream_events)
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_FakeAsyncChatClient.init_payload = {
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"data": {
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"app": {
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"chatConfig": {
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"welcomeText": "Hello from FastGPT init.",
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}
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}
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}
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}
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service = FastGPTLLMService(
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api_key="key",
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base_url="https://fastgpt.example",
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app_id="app-123",
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)
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await service.connect()
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greeting = await service.get_initial_greeting()
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assert greeting == "Hello from FastGPT init."
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assert service.client.init_requests[0] == {
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"appId": "app-123",
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"chatId": service._state.chat_id,
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}
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@pytest.mark.asyncio
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async def test_fastgpt_provider_maps_interactive_event_to_client_tool(monkeypatch):
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monkeypatch.setattr("providers.llm.fastgpt.AsyncChatClient", _FakeAsyncChatClient)
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monkeypatch.setattr("providers.llm.fastgpt.aiter_stream_events", _fake_aiter_stream_events)
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_FakeAsyncChatClient.responses = [
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_FakeResponse(
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[
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SimpleNamespace(
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kind="interactive",
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data={
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"type": "userSelect",
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"title": "Choose a plan",
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"params": {
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"description": "Pick the best plan for your team.",
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"userSelectOptions": [
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{"id": "basic", "label": "Basic", "value": "basic", "desc": "Starter tier"},
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{"id": "pro", "label": "Pro", "value": "pro", "description": "Advanced tier"},
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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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service = FastGPTLLMService(api_key="key", base_url="https://fastgpt.example")
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await service.connect()
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events = [event async for event in service.generate_stream([LLMMessage(role="user", content="Start")])]
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assert len(events) == 1
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assert events[0].type == "tool_call"
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tool_call = events[0].tool_call
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assert tool_call["executor"] == "client"
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assert tool_call["wait_for_response"] is True
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assert tool_call["timeout_ms"] == 300000
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assert tool_call["function"]["name"] == "fastgpt.interactive"
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arguments = json.loads(tool_call["function"]["arguments"])
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assert arguments["provider"] == "fastgpt"
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assert arguments["version"] == "fastgpt_interactive_v1"
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assert arguments["interaction"]["type"] == "userSelect"
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assert arguments["interaction"]["description"] == "Pick the best plan for your team."
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assert arguments["interaction"]["options"][0]["description"] == "Starter tier"
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assert arguments["interaction"]["options"][1]["value"] == "pro"
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assert arguments["interaction"]["options"][1]["description"] == "Advanced tier"
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assert arguments["context"]["chat_id"] == service._state.chat_id
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assert service._state.pending_interaction is not None
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@pytest.mark.asyncio
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async def test_fastgpt_provider_unwraps_nested_tool_children_interactive(monkeypatch):
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monkeypatch.setattr("providers.llm.fastgpt.AsyncChatClient", _FakeAsyncChatClient)
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monkeypatch.setattr("providers.llm.fastgpt.aiter_stream_events", _fake_aiter_stream_events)
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_FakeAsyncChatClient.responses = [
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_FakeResponse(
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[
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SimpleNamespace(
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kind="interactive",
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data={
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"interactive": {
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"type": "toolChildrenInteractive",
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"params": {
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"childrenResponse": {
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"type": "userSelect",
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"params": {
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"description": "Please choose a workflow branch.",
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"userSelectOptions": [
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{"value": "A", "description": "Branch A"},
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{"value": "B", "description": "Branch B"},
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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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]
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)
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]
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service = FastGPTLLMService(api_key="key", base_url="https://fastgpt.example")
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await service.connect()
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events = [event async for event in service.generate_stream([LLMMessage(role="user", content="Start")])]
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assert len(events) == 1
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arguments = json.loads(events[0].tool_call["function"]["arguments"])
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assert arguments["interaction"]["type"] == "userSelect"
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assert arguments["interaction"]["description"] == "Please choose a workflow branch."
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assert arguments["interaction"]["options"][0]["description"] == "Branch A"
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@pytest.mark.asyncio
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async def test_fastgpt_provider_uses_opener_for_interactive_prompt_when_prompt_missing(monkeypatch):
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monkeypatch.setattr("providers.llm.fastgpt.AsyncChatClient", _FakeAsyncChatClient)
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monkeypatch.setattr("providers.llm.fastgpt.aiter_stream_events", _fake_aiter_stream_events)
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_FakeAsyncChatClient.responses = [
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_FakeResponse(
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[
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SimpleNamespace(
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kind="interactive",
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data={
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"type": "userSelect",
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"opener": "请确认您是否满意本次服务。",
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"params": {
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"userSelectOptions": [
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{"value": "是"},
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{"value": "否"},
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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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service = FastGPTLLMService(api_key="key", base_url="https://fastgpt.example")
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await service.connect()
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events = [event async for event in service.generate_stream([LLMMessage(role="user", content="Start")])]
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assert len(events) == 1
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tool_call = events[0].tool_call
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arguments = json.loads(tool_call["function"]["arguments"])
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assert tool_call["display_name"] == "请确认您是否满意本次服务。"
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assert arguments["interaction"]["prompt"] == "请确认您是否满意本次服务。"
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@pytest.mark.asyncio
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async def test_fastgpt_provider_resumes_same_chat_after_client_result(monkeypatch):
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monkeypatch.setattr("providers.llm.fastgpt.AsyncChatClient", _FakeAsyncChatClient)
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monkeypatch.setattr("providers.llm.fastgpt.aiter_stream_events", _fake_aiter_stream_events)
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_FakeAsyncChatClient.responses = [
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_FakeResponse(
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[
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SimpleNamespace(
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kind="interactive",
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data={
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"type": "userSelect",
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"params": {"userSelectOptions": [{"label": "Pro", "value": "pro"}]},
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},
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)
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]
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),
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_FakeResponse(
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[
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SimpleNamespace(kind="answer", data={"text": "Resumed answer."}),
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SimpleNamespace(kind="done", data={}),
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]
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),
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]
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service = FastGPTLLMService(api_key="key", base_url="https://fastgpt.example")
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await service.connect()
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initial_events = [event async for event in service.generate_stream([LLMMessage(role="user", content="Start")])]
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call_id = initial_events[0].tool_call["id"]
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resumed_events = [
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event
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async for event in service.resume_after_client_tool_result(
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call_id,
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{
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"tool_call_id": call_id,
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"name": "fastgpt.interactive",
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"output": {
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"action": "submit",
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"result": {"type": "userSelect", "selected": "pro"},
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},
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"status": {"code": 200, "message": "ok"},
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},
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)
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]
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assert [event.type for event in resumed_events] == ["text_delta", "done"]
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assert resumed_events[0].text == "Resumed answer."
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assert service.client.requests[1]["chatId"] == service.client.requests[0]["chatId"]
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assert service.client.requests[1]["messages"] == [{"role": "user", "content": "pro"}]
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assert service._state.pending_interaction is None
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@pytest.mark.asyncio
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async def test_fastgpt_provider_cancel_result_clears_pending_interaction(monkeypatch):
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monkeypatch.setattr("providers.llm.fastgpt.AsyncChatClient", _FakeAsyncChatClient)
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monkeypatch.setattr("providers.llm.fastgpt.aiter_stream_events", _fake_aiter_stream_events)
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_FakeAsyncChatClient.responses = [
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_FakeResponse(
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[
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SimpleNamespace(
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kind="interactive",
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data={
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"type": "userInput",
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"params": {"inputForm": [{"name": "name", "label": "Name"}]},
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},
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)
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]
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)
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]
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service = FastGPTLLMService(api_key="key", base_url="https://fastgpt.example")
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await service.connect()
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initial_events = [event async for event in service.generate_stream([LLMMessage(role="user", content="Start")])]
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call_id = initial_events[0].tool_call["id"]
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resumed_events = [
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event
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async for event in service.resume_after_client_tool_result(
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call_id,
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{
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"tool_call_id": call_id,
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"name": "fastgpt.interactive",
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"output": {"action": "cancel", "result": {}},
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"status": {"code": 499, "message": "user_cancelled"},
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},
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)
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]
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assert [event.type for event in resumed_events] == ["done"]
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assert service._state.pending_interaction is None
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