ed
9ddfa98133
The follow-up track's tool-loop refactor moved 'from src.openai_compatible import send_openai_compatible, OpenAICompatibleRequest, NormalizedResponse' to MODULE level in src/ai_client.py. This violates the startup_speedup_20260606 invariant: heavy SDKs must not be loaded at module level because ai_client.py is on the main thread's import chain. src/openai_compatible.py line 5 does 'from openai import OpenAIError, ...', so any import from it triggers the openai SDK to load. test_ai_client_does_not_import_openai_at_module_level guards this invariant and was failing. Fix: move the imports back to local scope inside the function bodies that need them: - _default_send closure inside run_with_tool_loop (imports send_openai_compatible) - _send_grok (imports OpenAICompatibleRequest) - _send_minimax (imports OpenAICompatibleRequest) - _send_llama (imports OpenAICompatibleRequest) - _send_gemini_cli (imports OpenAICompatibleRequest + NormalizedResponse) Test patches: tests that previously patched 'src.ai_client.send_openai_compatible' now patch 'src.openai_compatible.send_openai_compatible' (the actual import source). _execute_tool_calls_concurrently patches unchanged (it's defined in src/ai_client.py itself). Green confirmed: 62 vendor + tool + import-isolation tests pass. 0 regressions.
42 lines
1.9 KiB
Python
42 lines
1.9 KiB
Python
"""Verify run_with_tool_loop supports a per-round request_builder callback.
|
|
|
|
Vendors that mutate their history list (e.g. MiniMax) need to rebuild
|
|
the messages on each round so the API sees the latest tool results.
|
|
run_with_tool_loop accepts a callable as the 2nd arg to enable this.
|
|
"""
|
|
from __future__ import annotations
|
|
from typing import Any
|
|
from unittest.mock import MagicMock, patch
|
|
from src.openai_compatible import NormalizedResponse, OpenAICompatibleRequest
|
|
from src.ai_client import run_with_tool_loop
|
|
from src.vendor_capabilities import VendorCapabilities
|
|
|
|
def _make_normalized_response(text: str = "ok", tool_calls: list[dict[str, Any]] | None = None) -> NormalizedResponse:
|
|
return NormalizedResponse(
|
|
text=text, tool_calls=tool_calls or [],
|
|
usage_input_tokens=10, usage_output_tokens=5,
|
|
usage_cache_read_tokens=0, usage_cache_creation_tokens=0,
|
|
raw_response=None,
|
|
)
|
|
|
|
def test_run_with_tool_loop_calls_request_builder_each_round() -> None:
|
|
caps = VendorCapabilities(vendor="test", model="test-model", tool_calling=True, context_window=8192)
|
|
client = MagicMock()
|
|
tool_response = _make_normalized_response(
|
|
"first", tool_calls=[{"id": "c1", "type": "function", "function": {"name": "noop", "arguments": "{}"}}]
|
|
)
|
|
final = _make_normalized_response("done")
|
|
builder_calls: list[int] = []
|
|
def builder(round_idx: int) -> OpenAICompatibleRequest:
|
|
builder_calls.append(round_idx)
|
|
return OpenAICompatibleRequest(messages=[{"role": "user", "content": f"round={round_idx}"}], model="m")
|
|
with patch("src.openai_compatible.send_openai_compatible", side_effect=[tool_response, final]), \
|
|
patch("src.ai_client._execute_tool_calls_concurrently", return_value=[("noop", "c1", "r", "")]):
|
|
result = run_with_tool_loop(
|
|
client, builder, capabilities=caps,
|
|
pre_tool_callback=None, qa_callback=None, patch_callback=None,
|
|
base_dir=".", vendor_name="test", history_lock=None, history=None,
|
|
)
|
|
assert result == "done"
|
|
assert len(builder_calls) >= 2
|