feat: bridge Lingma tool events to OpenAI/Anthropic responses
Add structured tool event propagation from Lingma stream/finish metadata and map it to OpenAI tool_calls and Anthropic tool_use/tool_result in both streaming and non-streaming responses. Add focused bridge tests and update docs/design notes to match current behavior. Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
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292
tests/test_tool_call_bridge.py
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292
tests/test_tool_call_bridge.py
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from __future__ import annotations
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import json
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import sys
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import types
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import unittest
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from unittest.mock import AsyncMock, patch
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# app.main imports playwright via auto_login; tests don't exercise that path.
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# Inject a lightweight stub so unit tests run without installing playwright.
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_playwright = types.ModuleType("playwright")
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_playwright_async = types.ModuleType("playwright.async_api")
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class _StubPlaywrightTimeoutError(Exception):
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pass
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async def _stub_async_playwright():
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raise RuntimeError("playwright is stubbed in unit tests")
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_playwright_async.TimeoutError = _StubPlaywrightTimeoutError
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_playwright_async.async_playwright = _stub_async_playwright
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sys.modules.setdefault("playwright", _playwright)
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sys.modules.setdefault("playwright.async_api", _playwright_async)
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from starlette.requests import Request
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from app.anthropic_schema import AnthropicMessagesRequest
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from app.openai_schema import ChatCompletionsRequest
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import app.main as main
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class _FakeTicket:
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def __init__(self) -> None:
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self.released = False
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def release(self) -> None:
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self.released = True
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class _FakeGuard:
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def __init__(self) -> None:
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self.in_flight = 0
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async def try_acquire(self) -> _FakeTicket:
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return _FakeTicket()
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class _FakeClient:
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def __init__(self, *, stream_events: list[dict], complete_result: dict) -> None:
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self._stream_events = stream_events
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self._complete_result = complete_result
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async def query_models(self) -> dict:
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return {
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"chat": [
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{
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"key": "org_auto",
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"displayName": "Auto",
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}
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]
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}
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async def chat_complete(self, *args, **kwargs) -> dict:
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return self._complete_result
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async def chat_stream(self, *args, **kwargs):
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out_meta = kwargs.get("out_meta")
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if isinstance(out_meta, dict):
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out_meta["session_id"] = "sess-stream"
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for event in self._stream_events:
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yield event
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class _FakeInstance:
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def __init__(self, client: _FakeClient) -> None:
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self.name = "inst-test"
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self.client = client
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self.in_flight = 0
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class _FakePool:
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def __init__(self, inst: _FakeInstance) -> None:
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self._inst = inst
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def pick(self, affinity_key: str | None = None) -> _FakeInstance:
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return self._inst
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def _make_request(path: str, headers: dict[str, str] | None = None) -> Request:
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header_pairs = []
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for k, v in (headers or {}).items():
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header_pairs.append((k.lower().encode("latin-1"), v.encode("latin-1")))
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scope = {
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"type": "http",
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"http_version": "1.1",
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"method": "POST",
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"scheme": "http",
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"path": path,
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"raw_path": path.encode("latin-1"),
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"query_string": b"",
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"headers": header_pairs,
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"client": ("testclient", 12345),
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"server": ("testserver", 80),
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"root_path": "",
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}
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return Request(scope)
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async def _collect_stream(response) -> str:
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chunks: list[str] = []
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async for part in response.body_iterator:
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if isinstance(part, bytes):
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chunks.append(part.decode("utf-8"))
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else:
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chunks.append(str(part))
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return "".join(chunks)
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class ToolCallBridgeTests(unittest.IsolatedAsyncioTestCase):
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async def test_openai_non_stream_bridges_tool_calls(self) -> None:
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fake_client = _FakeClient(
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stream_events=[],
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complete_result={
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"text": "done",
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"toolEvents": [
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{
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"id": "call_123",
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"name": "search_docs",
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"input": {"query": "gateway"},
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"result": {"ok": True},
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}
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],
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"sessionId": "sess-1",
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"firstTokenLatencyMs": 12,
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"totalLatencyMs": 34,
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},
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)
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req = ChatCompletionsRequest(
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model="org_auto",
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messages=[{"role": "user", "content": "hi"}],
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stream=False,
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)
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with (
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patch.object(main, "pool", _FakePool(_FakeInstance(fake_client))),
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patch.object(main, "chat_guard", _FakeGuard()),
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patch.object(main, "_ensure_instance_logged_in", AsyncMock(return_value={"id": "u"})),
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patch.object(main.stats_collector, "record_chat", AsyncMock(return_value=None)),
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):
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response = await main.v1_chat_completions(req, _make_request("/v1/chat/completions"))
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payload = json.loads(response.body)
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message = payload["choices"][0]["message"]
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self.assertEqual(message["content"], "done")
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self.assertIsInstance(message["tool_calls"], list)
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self.assertEqual(message["tool_calls"][0]["function"]["name"], "search_docs")
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self.assertEqual(
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json.loads(message["tool_calls"][0]["function"]["arguments"]),
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{"query": "gateway"},
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)
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async def test_openai_stream_bridges_tool_and_text_events(self) -> None:
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fake_client = _FakeClient(
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stream_events=[
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{
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"type": "tool",
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"tool": {
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"id": "call_stream_1",
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"name": "read_file",
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"input": {"path": "README.md"},
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},
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},
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{"type": "text", "text": "hello"},
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],
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complete_result={},
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)
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req = ChatCompletionsRequest(
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model="org_auto",
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messages=[{"role": "user", "content": "hi"}],
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stream=True,
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stream_options={"include_usage": True},
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)
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with (
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patch.object(main, "pool", _FakePool(_FakeInstance(fake_client))),
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patch.object(main, "chat_guard", _FakeGuard()),
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patch.object(main, "_ensure_instance_logged_in", AsyncMock(return_value={"id": "u"})),
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patch.object(main.stats_collector, "record_chat", AsyncMock(return_value=None)),
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):
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response = await main.v1_chat_completions(req, _make_request("/v1/chat/completions"))
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body = await _collect_stream(response)
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self.assertIn('"tool_calls"', body)
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self.assertIn('"content": "hello"', body)
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self.assertIn('"usage"', body)
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self.assertIn("data: [DONE]", body)
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async def test_anthropic_non_stream_bridges_tool_blocks(self) -> None:
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fake_client = _FakeClient(
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stream_events=[],
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complete_result={
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"text": "ok",
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"toolEvents": [
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{
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"id": "toolu_1",
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"name": "lookup",
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"input": {"k": "v"},
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"result": {"value": 1},
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}
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],
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"sessionId": "sess-2",
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},
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)
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req = AnthropicMessagesRequest(
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model="claude-3-5-sonnet-20241022",
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max_tokens=256,
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messages=[{"role": "user", "content": "hi"}],
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stream=False,
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)
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with (
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patch.object(main, "pool", _FakePool(_FakeInstance(fake_client))),
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patch.object(main, "chat_guard", _FakeGuard()),
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patch.object(main, "_ensure_instance_logged_in", AsyncMock(return_value={"id": "u"})),
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patch.object(main.stats_collector, "record_chat", AsyncMock(return_value=None)),
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patch.object(main.settings, "api_keys", ["test-key"]),
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):
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response = await main.v1_messages(
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req,
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_make_request(
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"/v1/messages",
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headers={"x-api-key": "test-key", "anthropic-version": "2023-06-01"},
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),
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)
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payload = json.loads(response.body)
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types = [item["type"] for item in payload["content"]]
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self.assertEqual(types, ["text", "tool_use", "tool_result"])
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self.assertEqual(payload["content"][1]["name"], "lookup")
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self.assertEqual(payload["content"][2]["tool_use_id"], "toolu_1")
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async def test_anthropic_stream_bridges_tool_and_text_events(self) -> None:
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fake_client = _FakeClient(
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stream_events=[
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{
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"type": "tool",
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"tool": {
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"id": "toolu_stream_1",
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"name": "read",
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"input": {"file": "a.txt"},
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"result": "done",
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},
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},
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{"type": "text", "text": "world"},
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],
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complete_result={},
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)
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req = AnthropicMessagesRequest(
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model="claude-3-5-sonnet-20241022",
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max_tokens=256,
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messages=[{"role": "user", "content": "hi"}],
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stream=True,
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)
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with (
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patch.object(main, "pool", _FakePool(_FakeInstance(fake_client))),
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patch.object(main, "chat_guard", _FakeGuard()),
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patch.object(main, "_ensure_instance_logged_in", AsyncMock(return_value={"id": "u"})),
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patch.object(main.stats_collector, "record_chat", AsyncMock(return_value=None)),
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patch.object(main.settings, "api_keys", ["test-key"]),
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):
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response = await main.v1_messages(
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req,
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_make_request(
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"/v1/messages",
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headers={"x-api-key": "test-key", "anthropic-version": "2023-06-01"},
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),
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)
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body = await _collect_stream(response)
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self.assertIn("event: message_start", body)
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self.assertIn('"type": "tool_use"', body)
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self.assertIn('"type": "tool_result"', body)
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self.assertIn('"type": "text_delta"', body)
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self.assertIn("event: message_stop", body)
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if __name__ == "__main__":
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unittest.main()
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