c0aa06f300
PR #3566 intentionally routes suppressed content to stream_delta_callback when tool calls are present, so reasoning tag extraction can fire during streaming. The test was still asserting the old behavior where content after tool calls was fully suppressed from the callback. Updated the assertion to match: content IS delivered to the callback (for tag extraction), with display-level suppression handled by the CLI's _stream_delta.
785 lines
28 KiB
Python
785 lines
28 KiB
Python
"""Tests for streaming token delivery infrastructure.
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Tests the unified streaming API call, delta callbacks, tool-call
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suppression, provider fallback, and CLI streaming display.
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"""
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import json
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import threading
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import uuid
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from types import SimpleNamespace
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from unittest.mock import MagicMock, patch, PropertyMock
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import pytest
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# ── Helpers ──────────────────────────────────────────────────────────────
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def _make_stream_chunk(
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content=None, tool_calls=None, finish_reason=None,
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model=None, reasoning_content=None, usage=None,
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):
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"""Build a mock streaming chunk matching OpenAI's ChatCompletionChunk shape."""
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delta = SimpleNamespace(
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content=content,
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tool_calls=tool_calls,
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reasoning_content=reasoning_content,
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reasoning=None,
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)
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choice = SimpleNamespace(
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index=0,
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delta=delta,
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finish_reason=finish_reason,
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)
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chunk = SimpleNamespace(
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choices=[choice],
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model=model,
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usage=usage,
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)
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return chunk
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def _make_tool_call_delta(index=0, tc_id=None, name=None, arguments=None, extra_content=None, model_extra=None):
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"""Build a mock tool call delta."""
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func = SimpleNamespace(name=name, arguments=arguments)
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delta = SimpleNamespace(index=index, id=tc_id, function=func)
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if extra_content is not None:
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delta.extra_content = extra_content
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if model_extra is not None:
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delta.model_extra = model_extra
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return delta
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def _make_empty_chunk(model=None, usage=None):
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"""Build a chunk with no choices (usage-only final chunk)."""
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return SimpleNamespace(choices=[], model=model, usage=usage)
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# ── Test: Streaming Accumulator ──────────────────────────────────────────
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class TestStreamingAccumulator:
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"""Verify that _interruptible_streaming_api_call accumulates content
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and tool calls into a response matching the non-streaming shape."""
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@patch("run_agent.AIAgent._create_request_openai_client")
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@patch("run_agent.AIAgent._close_request_openai_client")
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def test_text_only_response(self, mock_close, mock_create):
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"""Text-only stream produces correct response shape."""
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from run_agent import AIAgent
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chunks = [
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_make_stream_chunk(content="Hello"),
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_make_stream_chunk(content=" world"),
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_make_stream_chunk(content="!", finish_reason="stop", model="test-model"),
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_make_empty_chunk(usage=SimpleNamespace(prompt_tokens=10, completion_tokens=3)),
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]
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mock_client = MagicMock()
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mock_client.chat.completions.create.return_value = iter(chunks)
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mock_create.return_value = mock_client
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agent = AIAgent(
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model="test/model",
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quiet_mode=True,
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skip_context_files=True,
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skip_memory=True,
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)
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agent.api_mode = "chat_completions"
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agent._interrupt_requested = False
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response = agent._interruptible_streaming_api_call({})
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assert response.choices[0].message.content == "Hello world!"
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assert response.choices[0].message.tool_calls is None
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assert response.choices[0].finish_reason == "stop"
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assert response.usage is not None
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assert response.usage.completion_tokens == 3
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@patch("run_agent.AIAgent._create_request_openai_client")
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@patch("run_agent.AIAgent._close_request_openai_client")
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def test_tool_call_response(self, mock_close, mock_create):
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"""Tool call stream accumulates ID, name, and arguments."""
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from run_agent import AIAgent
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chunks = [
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_make_stream_chunk(tool_calls=[
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_make_tool_call_delta(index=0, tc_id="call_123", name="terminal")
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]),
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_make_stream_chunk(tool_calls=[
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_make_tool_call_delta(index=0, arguments='{"command":')
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]),
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_make_stream_chunk(tool_calls=[
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_make_tool_call_delta(index=0, arguments=' "ls"}')
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]),
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_make_stream_chunk(finish_reason="tool_calls"),
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]
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mock_client = MagicMock()
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mock_client.chat.completions.create.return_value = iter(chunks)
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mock_create.return_value = mock_client
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agent = AIAgent(
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model="test/model",
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quiet_mode=True,
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skip_context_files=True,
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skip_memory=True,
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)
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agent.api_mode = "chat_completions"
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agent._interrupt_requested = False
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response = agent._interruptible_streaming_api_call({})
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tc = response.choices[0].message.tool_calls
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assert tc is not None
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assert len(tc) == 1
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assert tc[0].id == "call_123"
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assert tc[0].function.name == "terminal"
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assert tc[0].function.arguments == '{"command": "ls"}'
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@patch("run_agent.AIAgent._create_request_openai_client")
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@patch("run_agent.AIAgent._close_request_openai_client")
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def test_tool_call_extra_content_preserved(self, mock_close, mock_create):
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"""Streamed tool calls preserve provider-specific extra_content metadata."""
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from run_agent import AIAgent
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chunks = [
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_make_stream_chunk(tool_calls=[
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_make_tool_call_delta(
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index=0,
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tc_id="call_gemini",
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name="cronjob",
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model_extra={
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"extra_content": {
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"google": {"thought_signature": "sig-123"}
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}
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},
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)
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]),
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_make_stream_chunk(tool_calls=[
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_make_tool_call_delta(index=0, arguments='{"task": "deep index on ."}')
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]),
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_make_stream_chunk(finish_reason="tool_calls"),
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]
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mock_client = MagicMock()
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mock_client.chat.completions.create.return_value = iter(chunks)
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mock_create.return_value = mock_client
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agent = AIAgent(
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model="test/model",
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quiet_mode=True,
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skip_context_files=True,
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skip_memory=True,
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)
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agent.api_mode = "chat_completions"
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agent._interrupt_requested = False
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response = agent._interruptible_streaming_api_call({})
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tc = response.choices[0].message.tool_calls
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assert tc is not None
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assert tc[0].extra_content == {
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"google": {"thought_signature": "sig-123"}
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}
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@patch("run_agent.AIAgent._create_request_openai_client")
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@patch("run_agent.AIAgent._close_request_openai_client")
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def test_mixed_content_and_tool_calls(self, mock_close, mock_create):
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"""Stream with both text and tool calls accumulates both."""
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from run_agent import AIAgent
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chunks = [
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_make_stream_chunk(content="Let me check"),
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_make_stream_chunk(tool_calls=[
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_make_tool_call_delta(index=0, tc_id="call_456", name="web_search")
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]),
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_make_stream_chunk(tool_calls=[
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_make_tool_call_delta(index=0, arguments='{"query": "test"}')
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]),
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_make_stream_chunk(finish_reason="tool_calls"),
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]
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mock_client = MagicMock()
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mock_client.chat.completions.create.return_value = iter(chunks)
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mock_create.return_value = mock_client
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agent = AIAgent(
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model="test/model",
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quiet_mode=True,
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skip_context_files=True,
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skip_memory=True,
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)
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agent.api_mode = "chat_completions"
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agent._interrupt_requested = False
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response = agent._interruptible_streaming_api_call({})
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assert response.choices[0].message.content == "Let me check"
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assert len(response.choices[0].message.tool_calls) == 1
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# ── Test: Streaming Callbacks ────────────────────────────────────────────
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class TestStreamingCallbacks:
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"""Verify that delta callbacks fire correctly."""
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@patch("run_agent.AIAgent._create_request_openai_client")
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@patch("run_agent.AIAgent._close_request_openai_client")
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def test_deltas_fire_in_order(self, mock_close, mock_create):
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"""Callbacks receive text deltas in order."""
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from run_agent import AIAgent
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chunks = [
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_make_stream_chunk(content="a"),
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_make_stream_chunk(content="b"),
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_make_stream_chunk(content="c"),
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_make_stream_chunk(finish_reason="stop"),
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]
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deltas = []
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mock_client = MagicMock()
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mock_client.chat.completions.create.return_value = iter(chunks)
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mock_create.return_value = mock_client
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agent = AIAgent(
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model="test/model",
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quiet_mode=True,
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skip_context_files=True,
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skip_memory=True,
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stream_delta_callback=lambda t: deltas.append(t),
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)
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agent.api_mode = "chat_completions"
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agent._interrupt_requested = False
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agent._interruptible_streaming_api_call({})
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assert deltas == ["a", "b", "c"]
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@patch("run_agent.AIAgent._create_request_openai_client")
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@patch("run_agent.AIAgent._close_request_openai_client")
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def test_on_first_delta_fires_once(self, mock_close, mock_create):
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"""on_first_delta callback fires exactly once."""
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from run_agent import AIAgent
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chunks = [
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_make_stream_chunk(content="a"),
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_make_stream_chunk(content="b"),
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_make_stream_chunk(finish_reason="stop"),
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]
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first_delta_calls = []
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mock_client = MagicMock()
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mock_client.chat.completions.create.return_value = iter(chunks)
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mock_create.return_value = mock_client
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agent = AIAgent(
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model="test/model",
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quiet_mode=True,
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skip_context_files=True,
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skip_memory=True,
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)
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agent.api_mode = "chat_completions"
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agent._interrupt_requested = False
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agent._interruptible_streaming_api_call(
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{}, on_first_delta=lambda: first_delta_calls.append(True)
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)
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assert len(first_delta_calls) == 1
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@patch("run_agent.AIAgent._create_request_openai_client")
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@patch("run_agent.AIAgent._close_request_openai_client")
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def test_tool_only_does_not_fire_callback(self, mock_close, mock_create):
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"""Tool-call-only stream does not fire the delta callback."""
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from run_agent import AIAgent
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chunks = [
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_make_stream_chunk(tool_calls=[
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_make_tool_call_delta(index=0, tc_id="call_789", name="terminal")
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]),
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_make_stream_chunk(tool_calls=[
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_make_tool_call_delta(index=0, arguments='{"command": "ls"}')
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]),
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_make_stream_chunk(finish_reason="tool_calls"),
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]
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deltas = []
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mock_client = MagicMock()
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mock_client.chat.completions.create.return_value = iter(chunks)
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mock_create.return_value = mock_client
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agent = AIAgent(
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model="test/model",
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quiet_mode=True,
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skip_context_files=True,
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skip_memory=True,
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stream_delta_callback=lambda t: deltas.append(t),
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)
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agent.api_mode = "chat_completions"
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agent._interrupt_requested = False
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agent._interruptible_streaming_api_call({})
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assert deltas == []
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@patch("run_agent.AIAgent._create_request_openai_client")
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@patch("run_agent.AIAgent._close_request_openai_client")
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def test_text_suppressed_when_tool_calls_present(self, mock_close, mock_create):
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"""Text deltas are suppressed when tool calls are also in the stream."""
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from run_agent import AIAgent
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chunks = [
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_make_stream_chunk(content="thinking..."),
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_make_stream_chunk(tool_calls=[
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_make_tool_call_delta(index=0, tc_id="call_abc", name="read_file")
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]),
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_make_stream_chunk(content=" more text"),
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_make_stream_chunk(finish_reason="tool_calls"),
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]
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deltas = []
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mock_client = MagicMock()
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mock_client.chat.completions.create.return_value = iter(chunks)
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mock_create.return_value = mock_client
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agent = AIAgent(
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model="test/model",
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quiet_mode=True,
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skip_context_files=True,
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skip_memory=True,
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stream_delta_callback=lambda t: deltas.append(t),
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)
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agent.api_mode = "chat_completions"
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agent._interrupt_requested = False
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response = agent._interruptible_streaming_api_call({})
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# Text before tool call IS fired (we don't know yet it will have tools)
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assert "thinking..." in deltas
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# Text after tool call IS still routed to stream_delta_callback so that
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# reasoning tag extraction can fire (PR #3566). Display-level suppression
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# of non-reasoning text happens in the CLI's _stream_delta, not here.
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assert " more text" in deltas
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# Content is still accumulated in the response
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assert response.choices[0].message.content == "thinking... more text"
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# ── Test: Streaming Fallback ────────────────────────────────────────────
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class TestStreamingFallback:
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"""Verify fallback to non-streaming on ANY streaming error."""
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@patch("run_agent.AIAgent._interruptible_api_call")
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@patch("run_agent.AIAgent._create_request_openai_client")
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@patch("run_agent.AIAgent._close_request_openai_client")
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def test_stream_error_falls_back(self, mock_close, mock_create, mock_non_stream):
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"""'not supported' error triggers fallback to non-streaming."""
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from run_agent import AIAgent
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mock_client = MagicMock()
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mock_client.chat.completions.create.side_effect = Exception(
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"Streaming is not supported for this model"
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)
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mock_create.return_value = mock_client
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fallback_response = SimpleNamespace(
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id="fallback",
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model="test",
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choices=[SimpleNamespace(
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index=0,
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message=SimpleNamespace(
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role="assistant",
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content="fallback response",
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tool_calls=None,
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reasoning_content=None,
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),
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finish_reason="stop",
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)],
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usage=None,
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)
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mock_non_stream.return_value = fallback_response
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agent = AIAgent(
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model="test/model",
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quiet_mode=True,
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skip_context_files=True,
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skip_memory=True,
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)
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agent.api_mode = "chat_completions"
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agent._interrupt_requested = False
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response = agent._interruptible_streaming_api_call({})
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assert response.choices[0].message.content == "fallback response"
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mock_non_stream.assert_called_once()
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@patch("run_agent.AIAgent._interruptible_api_call")
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@patch("run_agent.AIAgent._create_request_openai_client")
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@patch("run_agent.AIAgent._close_request_openai_client")
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def test_any_stream_error_falls_back(self, mock_close, mock_create, mock_non_stream):
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"""ANY streaming error triggers fallback — not just specific messages."""
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from run_agent import AIAgent
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mock_client = MagicMock()
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mock_client.chat.completions.create.side_effect = Exception(
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"Connection reset by peer"
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)
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mock_create.return_value = mock_client
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fallback_response = SimpleNamespace(
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id="fallback",
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model="test",
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choices=[SimpleNamespace(
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index=0,
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message=SimpleNamespace(
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role="assistant",
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content="fallback after connection error",
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tool_calls=None,
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reasoning_content=None,
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),
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finish_reason="stop",
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)],
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usage=None,
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)
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mock_non_stream.return_value = fallback_response
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agent = AIAgent(
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model="test/model",
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quiet_mode=True,
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skip_context_files=True,
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skip_memory=True,
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)
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agent.api_mode = "chat_completions"
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agent._interrupt_requested = False
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response = agent._interruptible_streaming_api_call({})
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assert response.choices[0].message.content == "fallback after connection error"
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mock_non_stream.assert_called_once()
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@patch("run_agent.AIAgent._interruptible_api_call")
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@patch("run_agent.AIAgent._create_request_openai_client")
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@patch("run_agent.AIAgent._close_request_openai_client")
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def test_fallback_error_propagates(self, mock_close, mock_create, mock_non_stream):
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"""When both streaming AND fallback fail, the fallback error propagates."""
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from run_agent import AIAgent
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mock_client = MagicMock()
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mock_client.chat.completions.create.side_effect = Exception("stream broke")
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mock_create.return_value = mock_client
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mock_non_stream.side_effect = Exception("Rate limit exceeded")
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agent = AIAgent(
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model="test/model",
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quiet_mode=True,
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skip_context_files=True,
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skip_memory=True,
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)
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agent.api_mode = "chat_completions"
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agent._interrupt_requested = False
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with pytest.raises(Exception, match="Rate limit exceeded"):
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agent._interruptible_streaming_api_call({})
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@patch("run_agent.AIAgent._interruptible_api_call")
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@patch("run_agent.AIAgent._create_request_openai_client")
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@patch("run_agent.AIAgent._close_request_openai_client")
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def test_exhausted_transient_stream_error_falls_back(self, mock_close, mock_create, mock_non_stream):
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"""Transient stream errors retry first, then fall back after retries are exhausted."""
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from run_agent import AIAgent
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import httpx
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mock_client = MagicMock()
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mock_client.chat.completions.create.side_effect = httpx.ConnectError("socket closed")
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|
mock_create.return_value = mock_client
|
|
|
|
fallback_response = SimpleNamespace(
|
|
id="fallback",
|
|
model="test",
|
|
choices=[SimpleNamespace(
|
|
index=0,
|
|
message=SimpleNamespace(
|
|
role="assistant",
|
|
content="fallback after retries exhausted",
|
|
tool_calls=None,
|
|
reasoning_content=None,
|
|
),
|
|
finish_reason="stop",
|
|
)],
|
|
usage=None,
|
|
)
|
|
mock_non_stream.return_value = fallback_response
|
|
|
|
agent = AIAgent(
|
|
model="test/model",
|
|
quiet_mode=True,
|
|
skip_context_files=True,
|
|
skip_memory=True,
|
|
)
|
|
agent.api_mode = "chat_completions"
|
|
agent._interrupt_requested = False
|
|
|
|
response = agent._interruptible_streaming_api_call({})
|
|
|
|
assert response.choices[0].message.content == "fallback after retries exhausted"
|
|
assert mock_client.chat.completions.create.call_count == 3
|
|
mock_non_stream.assert_called_once()
|
|
assert mock_close.call_count >= 1
|
|
|
|
@patch("run_agent.AIAgent._interruptible_api_call")
|
|
@patch("run_agent.AIAgent._create_request_openai_client")
|
|
@patch("run_agent.AIAgent._close_request_openai_client")
|
|
def test_sse_connection_lost_retried_as_transient(self, mock_close, mock_create, mock_non_stream):
|
|
"""SSE 'Network connection lost' (APIError w/ no status_code) retries like httpx errors.
|
|
|
|
OpenRouter sends {"error":{"message":"Network connection lost."}} as an SSE
|
|
event when the upstream stream drops. The OpenAI SDK raises APIError from
|
|
this. It should be retried at the streaming level, same as httpx connection
|
|
errors, before falling back to non-streaming.
|
|
"""
|
|
from run_agent import AIAgent
|
|
import httpx
|
|
|
|
# Create an APIError that mimics what the OpenAI SDK raises from SSE error events.
|
|
# Key: no status_code attribute (unlike APIStatusError which has one).
|
|
from openai import APIError as OAIAPIError
|
|
sse_error = OAIAPIError(
|
|
message="Network connection lost.",
|
|
request=httpx.Request("POST", "https://openrouter.ai/api/v1/chat/completions"),
|
|
body={"message": "Network connection lost."},
|
|
)
|
|
|
|
mock_client = MagicMock()
|
|
mock_client.chat.completions.create.side_effect = sse_error
|
|
mock_create.return_value = mock_client
|
|
|
|
fallback_response = SimpleNamespace(
|
|
id="fallback",
|
|
model="test",
|
|
choices=[SimpleNamespace(
|
|
index=0,
|
|
message=SimpleNamespace(
|
|
role="assistant",
|
|
content="fallback after SSE retries",
|
|
tool_calls=None,
|
|
reasoning_content=None,
|
|
),
|
|
finish_reason="stop",
|
|
)],
|
|
usage=None,
|
|
)
|
|
mock_non_stream.return_value = fallback_response
|
|
|
|
agent = AIAgent(
|
|
model="test/model",
|
|
quiet_mode=True,
|
|
skip_context_files=True,
|
|
skip_memory=True,
|
|
)
|
|
agent.api_mode = "chat_completions"
|
|
agent._interrupt_requested = False
|
|
|
|
response = agent._interruptible_streaming_api_call({})
|
|
|
|
assert response.choices[0].message.content == "fallback after SSE retries"
|
|
# Should retry 3 times (default HERMES_STREAM_RETRIES=2 → 3 attempts)
|
|
# before falling back to non-streaming
|
|
assert mock_client.chat.completions.create.call_count == 3
|
|
mock_non_stream.assert_called_once()
|
|
# Connection cleanup should happen for each failed retry
|
|
assert mock_close.call_count >= 2
|
|
|
|
@patch("run_agent.AIAgent._interruptible_api_call")
|
|
@patch("run_agent.AIAgent._create_request_openai_client")
|
|
@patch("run_agent.AIAgent._close_request_openai_client")
|
|
def test_sse_non_connection_error_falls_back_immediately(self, mock_close, mock_create, mock_non_stream):
|
|
"""SSE errors that aren't connection-related still fall back immediately (no stream retry)."""
|
|
from run_agent import AIAgent
|
|
import httpx
|
|
|
|
from openai import APIError as OAIAPIError
|
|
sse_error = OAIAPIError(
|
|
message="Invalid model configuration.",
|
|
request=httpx.Request("POST", "https://openrouter.ai/api/v1/chat/completions"),
|
|
body={"message": "Invalid model configuration."},
|
|
)
|
|
|
|
mock_client = MagicMock()
|
|
mock_client.chat.completions.create.side_effect = sse_error
|
|
mock_create.return_value = mock_client
|
|
|
|
fallback_response = SimpleNamespace(
|
|
id="fallback",
|
|
model="test",
|
|
choices=[SimpleNamespace(
|
|
index=0,
|
|
message=SimpleNamespace(
|
|
role="assistant",
|
|
content="fallback no retry",
|
|
tool_calls=None,
|
|
reasoning_content=None,
|
|
),
|
|
finish_reason="stop",
|
|
)],
|
|
usage=None,
|
|
)
|
|
mock_non_stream.return_value = fallback_response
|
|
|
|
agent = AIAgent(
|
|
model="test/model",
|
|
quiet_mode=True,
|
|
skip_context_files=True,
|
|
skip_memory=True,
|
|
)
|
|
agent.api_mode = "chat_completions"
|
|
agent._interrupt_requested = False
|
|
|
|
response = agent._interruptible_streaming_api_call({})
|
|
|
|
assert response.choices[0].message.content == "fallback no retry"
|
|
# Should NOT retry — goes straight to non-streaming fallback
|
|
assert mock_client.chat.completions.create.call_count == 1
|
|
mock_non_stream.assert_called_once()
|
|
|
|
|
|
# ── Test: Reasoning Streaming ────────────────────────────────────────────
|
|
|
|
|
|
class TestReasoningStreaming:
|
|
"""Verify reasoning content is accumulated and callback fires."""
|
|
|
|
@patch("run_agent.AIAgent._create_request_openai_client")
|
|
@patch("run_agent.AIAgent._close_request_openai_client")
|
|
def test_reasoning_callback_fires(self, mock_close, mock_create):
|
|
"""Reasoning deltas fire the reasoning_callback."""
|
|
from run_agent import AIAgent
|
|
|
|
chunks = [
|
|
_make_stream_chunk(reasoning_content="Let me think"),
|
|
_make_stream_chunk(reasoning_content=" about this"),
|
|
_make_stream_chunk(content="The answer is 42"),
|
|
_make_stream_chunk(finish_reason="stop"),
|
|
]
|
|
|
|
reasoning_deltas = []
|
|
text_deltas = []
|
|
|
|
mock_client = MagicMock()
|
|
mock_client.chat.completions.create.return_value = iter(chunks)
|
|
mock_create.return_value = mock_client
|
|
|
|
agent = AIAgent(
|
|
model="test/model",
|
|
quiet_mode=True,
|
|
skip_context_files=True,
|
|
skip_memory=True,
|
|
stream_delta_callback=lambda t: text_deltas.append(t),
|
|
reasoning_callback=lambda t: reasoning_deltas.append(t),
|
|
)
|
|
agent.api_mode = "chat_completions"
|
|
agent._interrupt_requested = False
|
|
|
|
response = agent._interruptible_streaming_api_call({})
|
|
|
|
assert reasoning_deltas == ["Let me think", " about this"]
|
|
assert text_deltas == ["The answer is 42"]
|
|
assert response.choices[0].message.reasoning_content == "Let me think about this"
|
|
assert response.choices[0].message.content == "The answer is 42"
|
|
|
|
|
|
# ── Test: _has_stream_consumers ──────────────────────────────────────────
|
|
|
|
|
|
class TestHasStreamConsumers:
|
|
"""Verify _has_stream_consumers() detects registered callbacks."""
|
|
|
|
def test_no_consumers(self):
|
|
from run_agent import AIAgent
|
|
agent = AIAgent(
|
|
model="test/model",
|
|
quiet_mode=True,
|
|
skip_context_files=True,
|
|
skip_memory=True,
|
|
)
|
|
assert agent._has_stream_consumers() is False
|
|
|
|
def test_delta_callback_set(self):
|
|
from run_agent import AIAgent
|
|
agent = AIAgent(
|
|
model="test/model",
|
|
quiet_mode=True,
|
|
skip_context_files=True,
|
|
skip_memory=True,
|
|
stream_delta_callback=lambda t: None,
|
|
)
|
|
assert agent._has_stream_consumers() is True
|
|
|
|
def test_stream_callback_set(self):
|
|
from run_agent import AIAgent
|
|
agent = AIAgent(
|
|
model="test/model",
|
|
quiet_mode=True,
|
|
skip_context_files=True,
|
|
skip_memory=True,
|
|
)
|
|
agent._stream_callback = lambda t: None
|
|
assert agent._has_stream_consumers() is True
|
|
|
|
|
|
# ── Test: Codex stream fires callbacks ────────────────────────────────
|
|
|
|
|
|
class TestCodexStreamCallbacks:
|
|
"""Verify _run_codex_stream fires delta callbacks."""
|
|
|
|
def test_codex_text_delta_fires_callback(self):
|
|
from run_agent import AIAgent
|
|
|
|
deltas = []
|
|
|
|
agent = AIAgent(
|
|
model="test/model",
|
|
quiet_mode=True,
|
|
skip_context_files=True,
|
|
skip_memory=True,
|
|
stream_delta_callback=lambda t: deltas.append(t),
|
|
)
|
|
agent.api_mode = "codex_responses"
|
|
agent._interrupt_requested = False
|
|
|
|
# Mock the stream context manager
|
|
mock_event_text = SimpleNamespace(
|
|
type="response.output_text.delta",
|
|
delta="Hello from Codex!",
|
|
)
|
|
mock_event_done = SimpleNamespace(
|
|
type="response.completed",
|
|
delta="",
|
|
)
|
|
|
|
mock_stream = MagicMock()
|
|
mock_stream.__enter__ = MagicMock(return_value=mock_stream)
|
|
mock_stream.__exit__ = MagicMock(return_value=False)
|
|
mock_stream.__iter__ = MagicMock(return_value=iter([mock_event_text, mock_event_done]))
|
|
mock_stream.get_final_response.return_value = SimpleNamespace(
|
|
output=[SimpleNamespace(
|
|
type="message",
|
|
content=[SimpleNamespace(type="output_text", text="Hello from Codex!")],
|
|
)],
|
|
status="completed",
|
|
)
|
|
|
|
mock_client = MagicMock()
|
|
mock_client.responses.stream.return_value = mock_stream
|
|
|
|
response = agent._run_codex_stream({}, client=mock_client)
|
|
assert "Hello from Codex!" in deltas
|