From bb3ef8ff4dce26395563b36f1522078ed4d6a9d1 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?=E6=B5=81=E5=B1=BF?= Date: Tue, 24 Mar 2026 10:17:22 +0800 Subject: [PATCH 1/2] feat(qwen-agent): add instrumentation for Qwen-Agent Change-Id: I5ab30c79fea5e6f2070ef182da505084092632b2 Co-developed-by: Cursor --- .github/workflows/loongsuite_lint_0.yml | 19 + .github/workflows/loongsuite_test_0.yml | 190 +++++ .../CHANGELOG.md | 13 + .../README.md | 109 +++ .../pyproject.toml | 65 ++ .../instrumentation/qwen_agent/__init__.py | 191 +++++ .../instrumentation/qwen_agent/package.py | 17 + .../instrumentation/qwen_agent/patch.py | 304 ++++++++ .../instrumentation/qwen_agent/utils.py | 410 ++++++++++ .../instrumentation/qwen_agent/version.py | 15 + .../tests/__init__.py | 0 .../cassettes/test_agent_run_nonstream.yaml | 85 +++ .../test_multi_turn_conversation.yaml | 103 +++ .../tests/cassettes/test_non_stream_chat.yaml | 94 +++ .../cassettes/test_qwen_agent_basic_run.yaml | 105 +++ .../test_qwen_agent_stream_llm_with_ttft.yaml | 85 +++ .../test_qwen_agent_with_tool_call.yaml | 444 +++++++++++ .../cassettes/test_react_multi_round.yaml | 244 ++++++ .../tests/conftest.py | 205 +++++ .../tests/requirements.latest.txt | 37 + .../tests/requirements.oldest.txt | 35 + .../tests/test_instrumentor.py | 169 ++++ .../tests/test_real_api.py | 446 +++++++++++ .../tests/test_spans.py | 722 ++++++++++++++++++ tox-loongsuite.ini | 12 + 25 files changed, 4119 insertions(+) create mode 100644 instrumentation-loongsuite/loongsuite-instrumentation-qwen-agent/CHANGELOG.md create mode 100644 instrumentation-loongsuite/loongsuite-instrumentation-qwen-agent/README.md create mode 100644 instrumentation-loongsuite/loongsuite-instrumentation-qwen-agent/pyproject.toml create mode 100644 instrumentation-loongsuite/loongsuite-instrumentation-qwen-agent/src/opentelemetry/instrumentation/qwen_agent/__init__.py create mode 100644 instrumentation-loongsuite/loongsuite-instrumentation-qwen-agent/src/opentelemetry/instrumentation/qwen_agent/package.py create mode 100644 instrumentation-loongsuite/loongsuite-instrumentation-qwen-agent/src/opentelemetry/instrumentation/qwen_agent/patch.py create mode 100644 instrumentation-loongsuite/loongsuite-instrumentation-qwen-agent/src/opentelemetry/instrumentation/qwen_agent/utils.py create mode 100644 instrumentation-loongsuite/loongsuite-instrumentation-qwen-agent/src/opentelemetry/instrumentation/qwen_agent/version.py create mode 100644 instrumentation-loongsuite/loongsuite-instrumentation-qwen-agent/tests/__init__.py create mode 100644 instrumentation-loongsuite/loongsuite-instrumentation-qwen-agent/tests/cassettes/test_agent_run_nonstream.yaml create mode 100644 instrumentation-loongsuite/loongsuite-instrumentation-qwen-agent/tests/cassettes/test_multi_turn_conversation.yaml create mode 100644 instrumentation-loongsuite/loongsuite-instrumentation-qwen-agent/tests/cassettes/test_non_stream_chat.yaml create mode 100644 instrumentation-loongsuite/loongsuite-instrumentation-qwen-agent/tests/cassettes/test_qwen_agent_basic_run.yaml create mode 100644 instrumentation-loongsuite/loongsuite-instrumentation-qwen-agent/tests/cassettes/test_qwen_agent_stream_llm_with_ttft.yaml create mode 100644 instrumentation-loongsuite/loongsuite-instrumentation-qwen-agent/tests/cassettes/test_qwen_agent_with_tool_call.yaml create mode 100644 instrumentation-loongsuite/loongsuite-instrumentation-qwen-agent/tests/cassettes/test_react_multi_round.yaml create mode 100644 instrumentation-loongsuite/loongsuite-instrumentation-qwen-agent/tests/conftest.py create mode 100644 instrumentation-loongsuite/loongsuite-instrumentation-qwen-agent/tests/requirements.latest.txt create mode 100644 instrumentation-loongsuite/loongsuite-instrumentation-qwen-agent/tests/requirements.oldest.txt create mode 100644 instrumentation-loongsuite/loongsuite-instrumentation-qwen-agent/tests/test_instrumentor.py create mode 100644 instrumentation-loongsuite/loongsuite-instrumentation-qwen-agent/tests/test_real_api.py create mode 100644 instrumentation-loongsuite/loongsuite-instrumentation-qwen-agent/tests/test_spans.py diff --git a/.github/workflows/loongsuite_lint_0.yml b/.github/workflows/loongsuite_lint_0.yml index 083ba861b..03dba5f74 100644 --- a/.github/workflows/loongsuite_lint_0.yml +++ b/.github/workflows/loongsuite_lint_0.yml @@ -146,6 +146,25 @@ jobs: - name: Run tests run: tox -c tox-loongsuite.ini -e lint-loongsuite-instrumentation-langgraph + lint-loongsuite-instrumentation-qwen-agent: + name: LoongSuite loongsuite-instrumentation-qwen-agent + runs-on: ubuntu-latest + timeout-minutes: 30 + steps: + - name: Checkout repo @ SHA - ${{ github.sha }} + uses: actions/checkout@v4 + + - name: Set up Python 3.13 + uses: actions/setup-python@v5 + with: + python-version: "3.13" + + - name: Install tox + run: pip install tox-uv + + - name: Run tests + run: tox -c tox-loongsuite.ini -e lint-loongsuite-instrumentation-qwen-agent + lint-loongsuite-instrumentation-mem0: name: LoongSuite loongsuite-instrumentation-mem0 runs-on: ubuntu-latest diff --git a/.github/workflows/loongsuite_test_0.yml b/.github/workflows/loongsuite_test_0.yml index bfe7c3f3a..59c1dc498 100644 --- a/.github/workflows/loongsuite_test_0.yml +++ b/.github/workflows/loongsuite_test_0.yml @@ -1096,6 +1096,196 @@ jobs: - name: Run tests run: tox -c tox-loongsuite.ini -e py313-test-loongsuite-instrumentation-langgraph-latest -- -ra + py39-test-loongsuite-instrumentation-qwen-agent-oldest_ubuntu-latest: + name: LoongSuite loongsuite-instrumentation-qwen-agent-oldest 3.9 Ubuntu + runs-on: ubuntu-latest + timeout-minutes: 30 + steps: + - name: Checkout repo @ SHA - ${{ github.sha }} + uses: actions/checkout@v4 + + - name: Set up Python 3.9 + uses: actions/setup-python@v5 + with: + python-version: "3.9" + + - name: Install tox + run: pip install tox-uv + + - name: Run tests + run: tox -c tox-loongsuite.ini -e py39-test-loongsuite-instrumentation-qwen-agent-oldest -- -ra + + py39-test-loongsuite-instrumentation-qwen-agent-latest_ubuntu-latest: + name: LoongSuite loongsuite-instrumentation-qwen-agent-latest 3.9 Ubuntu + runs-on: ubuntu-latest + timeout-minutes: 30 + steps: + - name: Checkout repo @ SHA - ${{ github.sha }} + uses: actions/checkout@v4 + + - name: Set up Python 3.9 + uses: actions/setup-python@v5 + with: + python-version: "3.9" + + - name: Install tox + run: pip install tox-uv + + - name: Run tests + run: tox -c tox-loongsuite.ini -e py39-test-loongsuite-instrumentation-qwen-agent-latest -- -ra + + py310-test-loongsuite-instrumentation-qwen-agent-oldest_ubuntu-latest: + name: LoongSuite loongsuite-instrumentation-qwen-agent-oldest 3.10 Ubuntu + runs-on: ubuntu-latest + timeout-minutes: 30 + steps: + - name: Checkout repo @ SHA - ${{ github.sha }} + uses: actions/checkout@v4 + + - name: Set up Python 3.10 + uses: actions/setup-python@v5 + with: + python-version: "3.10" + + - name: Install tox + run: pip install tox-uv + + - name: Run tests + run: tox -c tox-loongsuite.ini -e py310-test-loongsuite-instrumentation-qwen-agent-oldest -- -ra + + py310-test-loongsuite-instrumentation-qwen-agent-latest_ubuntu-latest: + name: LoongSuite loongsuite-instrumentation-qwen-agent-latest 3.10 Ubuntu + runs-on: ubuntu-latest + timeout-minutes: 30 + steps: + - name: Checkout repo @ SHA - ${{ github.sha }} + uses: actions/checkout@v4 + + - name: Set up Python 3.10 + uses: actions/setup-python@v5 + with: + python-version: "3.10" + + - name: Install tox + run: pip install tox-uv + + - name: Run tests + run: tox -c tox-loongsuite.ini -e py310-test-loongsuite-instrumentation-qwen-agent-latest -- -ra + + py311-test-loongsuite-instrumentation-qwen-agent-oldest_ubuntu-latest: + name: LoongSuite loongsuite-instrumentation-qwen-agent-oldest 3.11 Ubuntu + runs-on: ubuntu-latest + timeout-minutes: 30 + steps: + - name: Checkout repo @ SHA - ${{ github.sha }} + uses: actions/checkout@v4 + + - name: Set up Python 3.11 + uses: actions/setup-python@v5 + with: + python-version: "3.11" + + - name: Install tox + run: pip install tox-uv + + - name: Run tests + run: tox -c tox-loongsuite.ini -e py311-test-loongsuite-instrumentation-qwen-agent-oldest -- -ra + + py311-test-loongsuite-instrumentation-qwen-agent-latest_ubuntu-latest: + name: LoongSuite loongsuite-instrumentation-qwen-agent-latest 3.11 Ubuntu + runs-on: ubuntu-latest + timeout-minutes: 30 + steps: + - name: Checkout repo @ SHA - ${{ github.sha }} + uses: actions/checkout@v4 + + - name: Set up Python 3.11 + uses: actions/setup-python@v5 + with: + python-version: "3.11" + + - name: Install tox + run: pip install tox-uv + + - name: Run tests + run: tox -c tox-loongsuite.ini -e py311-test-loongsuite-instrumentation-qwen-agent-latest -- -ra + + py312-test-loongsuite-instrumentation-qwen-agent-oldest_ubuntu-latest: + name: LoongSuite loongsuite-instrumentation-qwen-agent-oldest 3.12 Ubuntu + runs-on: ubuntu-latest + timeout-minutes: 30 + steps: + - name: Checkout repo @ SHA - ${{ github.sha }} + uses: actions/checkout@v4 + + - name: Set up Python 3.12 + uses: actions/setup-python@v5 + with: + python-version: "3.12" + + - name: Install tox + run: pip install tox-uv + + - name: Run tests + run: tox -c tox-loongsuite.ini -e py312-test-loongsuite-instrumentation-qwen-agent-oldest -- -ra + + py312-test-loongsuite-instrumentation-qwen-agent-latest_ubuntu-latest: + name: LoongSuite loongsuite-instrumentation-qwen-agent-latest 3.12 Ubuntu + runs-on: ubuntu-latest + timeout-minutes: 30 + steps: + - name: Checkout repo @ SHA - ${{ github.sha }} + uses: actions/checkout@v4 + + - name: Set up Python 3.12 + uses: actions/setup-python@v5 + with: + python-version: "3.12" + + - name: Install tox + run: pip install tox-uv + + - name: Run tests + run: tox -c tox-loongsuite.ini -e py312-test-loongsuite-instrumentation-qwen-agent-latest -- -ra + + py313-test-loongsuite-instrumentation-qwen-agent-oldest_ubuntu-latest: + name: LoongSuite loongsuite-instrumentation-qwen-agent-oldest 3.13 Ubuntu + runs-on: ubuntu-latest + timeout-minutes: 30 + steps: + - name: Checkout repo @ SHA - ${{ github.sha }} + uses: actions/checkout@v4 + + - name: Set up Python 3.13 + uses: actions/setup-python@v5 + with: + python-version: "3.13" + + - name: Install tox + run: pip install tox-uv + + - name: Run tests + run: tox -c tox-loongsuite.ini -e py313-test-loongsuite-instrumentation-qwen-agent-oldest -- -ra + + py313-test-loongsuite-instrumentation-qwen-agent-latest_ubuntu-latest: + name: LoongSuite loongsuite-instrumentation-qwen-agent-latest 3.13 Ubuntu + runs-on: ubuntu-latest + timeout-minutes: 30 + steps: + - name: Checkout repo @ SHA - ${{ github.sha }} + uses: actions/checkout@v4 + + - name: Set up Python 3.13 + uses: actions/setup-python@v5 + with: + python-version: "3.13" + + - name: Install tox + run: pip install tox-uv + + - name: Run tests + run: tox -c tox-loongsuite.ini -e py313-test-loongsuite-instrumentation-qwen-agent-latest -- -ra + py310-test-loongsuite-instrumentation-mem0-oldest_ubuntu-latest: name: LoongSuite loongsuite-instrumentation-mem0-oldest 3.10 Ubuntu runs-on: ubuntu-latest diff --git a/instrumentation-loongsuite/loongsuite-instrumentation-qwen-agent/CHANGELOG.md b/instrumentation-loongsuite/loongsuite-instrumentation-qwen-agent/CHANGELOG.md new file mode 100644 index 000000000..ea9f2355b --- /dev/null +++ b/instrumentation-loongsuite/loongsuite-instrumentation-qwen-agent/CHANGELOG.md @@ -0,0 +1,13 @@ +# Changelog + +## Unreleased + +### Added + +- Initial release of `loongsuite-instrumentation-qwen-agent` +- Instrumentation for `Agent.run()` (invoke_agent spans; `run_nonstream()` is covered via its internal `run()` call — no duplicate span) +- Instrumentation for `BaseChatModel.chat()` (LLM spans) +- Instrumentation for `Agent._call_tool()` (execute_tool spans) +- Support for streaming and non-streaming LLM responses +- Message conversion from qwen-agent types to GenAI semantic conventions +- Provider detection for DashScope, OpenAI, and Azure backends diff --git a/instrumentation-loongsuite/loongsuite-instrumentation-qwen-agent/README.md b/instrumentation-loongsuite/loongsuite-instrumentation-qwen-agent/README.md new file mode 100644 index 000000000..8452d0b09 --- /dev/null +++ b/instrumentation-loongsuite/loongsuite-instrumentation-qwen-agent/README.md @@ -0,0 +1,109 @@ +# OpenTelemetry Qwen-Agent Instrumentation + +OpenTelemetry instrumentation for the [Qwen-Agent](https://github.com/QwenLM/Qwen-Agent) framework. + +## Installation + +```bash +pip install opentelemetry-distro opentelemetry-exporter-otlp +opentelemetry-bootstrap -a install + +pip install "qwen-agent >= 0.0.20" + +# Install this instrumentation (from the LoongSuite repo) +pip install ./instrumentation-loongsuite/loongsuite-instrumentation-qwen-agent + +# Required: GenAI utilities used by the instrumentation +pip install ./util/opentelemetry-util-genai +``` + +Published package name: + +```bash +pip install loongsuite-instrumentation-qwen-agent +``` + +## Usage + +### Auto-instrumentation + +With `loongsuite-instrumentation-qwen-agent` installed, the `opentelemetry_instrumentor` entry point `qwen_agent` is registered for use with the OpenTelemetry distro. + +```bash +opentelemetry-instrument \ + --traces_exporter console \ + python your_qwen_agent_app.py +``` + +### Manual instrumentation + +```python +from opentelemetry.instrumentation.qwen_agent import QwenAgentInstrumentor +from opentelemetry.sdk.trace import TracerProvider +from opentelemetry.sdk.trace.export import ConsoleSpanExporter, SimpleSpanProcessor +from qwen_agent.agents import Assistant + +provider = TracerProvider() +provider.add_span_processor(SimpleSpanProcessor(ConsoleSpanExporter())) + +QwenAgentInstrumentor().instrument(tracer_provider=provider) + +bot = Assistant( + llm={"model": "qwen-max", "model_type": "qwen_dashscope"}, + name="my-assistant", +) +for _ in bot.run([{"role": "user", "content": "Hello!"}]): + pass + +QwenAgentInstrumentor().uninstrument() +``` + +## Configuration + +### Export to an OTLP backend + +```bash +export OTEL_SERVICE_NAME=my-qwen-agent-app +export OTEL_EXPORTER_OTLP_PROTOCOL=http/protobuf +export OTEL_EXPORTER_OTLP_TRACES_ENDPOINT= +# Optional: metrics / logs if you configure exporters globally +export OTEL_EXPORTER_OTLP_METRICS_ENDPOINT= + +opentelemetry-instrument python your_app.py +``` + +### GenAI semantic conventions and content capture + +```bash +# Enable experimental GenAI semantic conventions (recommended for this instrumentation) +export OTEL_SEMCONV_STABILITY_OPT_IN=gen_ai_latest_experimental + +# Message content capture (same env vars as other GenAI instrumentations in this repo) +export OTEL_INSTRUMENTATION_GENAI_CAPTURE_MESSAGE_CONTENT=SPAN_ONLY +# EVENT_ONLY | SPAN_AND_EVENT | NO_CONTENT +``` + +## Supported components + +| Area | Instrumented API | Span / operation | +|------|------------------|------------------| +| Agent | `Agent.run` | `invoke_agent` | +| LLM | `BaseChatModel.chat` | `chat` | +| ReAct | `Agent._call_llm` | `react step` (agents with tools) | +| Tools | `Agent._call_tool` | `execute_tool` | + +`Agent.run_nonstream()` is not wrapped separately; it calls `run()` internally, so you still get a single `invoke_agent` span per run. + +**Model backends** (inferred from `model_type` / class name): DashScope, OpenAI-compatible APIs, Azure OpenAI, and other Qwen-Agent–supported backends. + +## Visualization + +Export telemetry to: + +- [Alibaba Cloud ARMS / Managed Service for OpenTelemetry](https://www.aliyun.com/product/xtrace) +- [AgentScope Studio](https://github.com/agentscope-ai/agentscope-studio) or any OTLP-compatible collector +- Any OpenTelemetry-compatible backend (Jaeger, Zipkin, etc.) + +## License + +Apache License 2.0 diff --git a/instrumentation-loongsuite/loongsuite-instrumentation-qwen-agent/pyproject.toml b/instrumentation-loongsuite/loongsuite-instrumentation-qwen-agent/pyproject.toml new file mode 100644 index 000000000..aab7ed954 --- /dev/null +++ b/instrumentation-loongsuite/loongsuite-instrumentation-qwen-agent/pyproject.toml @@ -0,0 +1,65 @@ +[build-system] +requires = ["hatchling"] +build-backend = "hatchling.build" + +[project] +name = "loongsuite-instrumentation-qwen-agent" +dynamic = ["version"] +description = "OpenTelemetry Qwen-Agent Instrumentation" +readme = "README.md" +license = "Apache-2.0" +requires-python = ">=3.9" +authors = [ + { name = "LoongSuite Python Agent Authors", email = "qp467389@alibaba-inc.com" }, +] +classifiers = [ + "Development Status :: 4 - Beta", + "Intended Audience :: Developers", + "License :: OSI Approved :: Apache Software License", + "Programming Language :: Python", + "Programming Language :: Python :: 3", + "Programming Language :: Python :: 3.9", + "Programming Language :: Python :: 3.10", + "Programming Language :: Python :: 3.11", + "Programming Language :: Python :: 3.12", + "Programming Language :: Python :: 3.13", +] +dependencies = [ + "opentelemetry-api ~= 1.37", + "opentelemetry-instrumentation >= 0.58b0", + "opentelemetry-semantic-conventions >= 0.58b0", + "opentelemetry-util-genai", + "wrapt", +] + +[project.optional-dependencies] +instruments = [ + "qwen-agent >= 0.0.20", +] + +test = [ + "pytest ~= 8.0", + "pytest-cov ~= 4.1.0", + "qwen-agent >= 0.0.20", + "vcrpy", + "pytest-vcr", +] + +[project.entry-points.opentelemetry_instrumentor] +qwen_agent = "opentelemetry.instrumentation.qwen_agent:QwenAgentInstrumentor" + +[project.urls] +Homepage = "https://github.com/alibaba/loongsuite-python-agent" +Repository = "https://github.com/alibaba/loongsuite-python-agent" + +[tool.hatch.version] +path = "src/opentelemetry/instrumentation/qwen_agent/version.py" + +[tool.hatch.build.targets.sdist] +include = [ + "/src", + "/tests", +] + +[tool.hatch.build.targets.wheel] +packages = ["src/opentelemetry"] diff --git a/instrumentation-loongsuite/loongsuite-instrumentation-qwen-agent/src/opentelemetry/instrumentation/qwen_agent/__init__.py b/instrumentation-loongsuite/loongsuite-instrumentation-qwen-agent/src/opentelemetry/instrumentation/qwen_agent/__init__.py new file mode 100644 index 000000000..2826d19af --- /dev/null +++ b/instrumentation-loongsuite/loongsuite-instrumentation-qwen-agent/src/opentelemetry/instrumentation/qwen_agent/__init__.py @@ -0,0 +1,191 @@ +# Copyright The OpenTelemetry Authors +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +""" +Qwen-Agent instrumentation supporting `qwen-agent >= 0.0.20`. + +Usage +----- +.. code:: python + + from opentelemetry.instrumentation.qwen_agent import QwenAgentInstrumentor + from qwen_agent.agents import Assistant + + QwenAgentInstrumentor().instrument() + + bot = Assistant( + llm={'model': 'qwen-max', 'model_type': 'qwen_dashscope'}, + name='my-assistant', + system_message='You are a helpful assistant.', + ) + + messages = [{'role': 'user', 'content': 'Hello!'}] + for responses in bot.run(messages): + pass + + QwenAgentInstrumentor().uninstrument() + +API +--- +""" + +from __future__ import annotations + +import logging +from typing import Any, Collection + +from wrapt import wrap_function_wrapper + +from opentelemetry.instrumentation.instrumentor import BaseInstrumentor +from opentelemetry.instrumentation.qwen_agent.package import _instruments +from opentelemetry.instrumentation.qwen_agent.patch import ( + wrap_agent_call_llm, + wrap_agent_call_tool, + wrap_agent_run, + wrap_chat_model_chat, +) +from opentelemetry.instrumentation.qwen_agent.version import __version__ +from opentelemetry.instrumentation.utils import unwrap +from opentelemetry.util.genai.extended_handler import ExtendedTelemetryHandler + +logger = logging.getLogger(__name__) + +_AGENT_MODULE = "qwen_agent.agent" +_LLM_MODULE = "qwen_agent.llm.base" + +__all__ = ["QwenAgentInstrumentor", "__version__"] + + +class QwenAgentInstrumentor(BaseInstrumentor): + """OpenTelemetry instrumentor for Qwen-Agent framework. + + Instruments the following components: + - Agent.run(): Agent execution spans (invoke_agent) + (run_nonstream is NOT wrapped separately — it calls run() internally, + so the invoke_agent span is created once by the run() wrapper.) + - Agent._call_llm(): ReAct step spans (only for agents with tools) + - BaseChatModel.chat(): LLM call spans (chat) + - Agent._call_tool(): Tool execution spans (execute_tool) + """ + + def __init__(self): + super().__init__() + self._handler = None + + def instrumentation_dependencies(self) -> Collection[str]: + return _instruments + + def _instrument(self, **kwargs: Any) -> None: + """Enable Qwen-Agent instrumentation.""" + tracer_provider = kwargs.get("tracer_provider") + meter_provider = kwargs.get("meter_provider") + logger_provider = kwargs.get("logger_provider") + + self._handler = ExtendedTelemetryHandler( + tracer_provider=tracer_provider, + meter_provider=meter_provider, + logger_provider=logger_provider, + ) + + # Instrument Agent.run() - agent execution entry point (generator) + try: + wrap_function_wrapper( + module=_AGENT_MODULE, + name="Agent.run", + wrapper=lambda wrapped, instance, args, kwargs: wrap_agent_run( + wrapped, instance, args, kwargs, handler=self._handler + ), + ) + logger.debug("Instrumented Agent.run") + except Exception as e: + logger.warning(f"Failed to instrument Agent.run: {e}") + + # Note: Agent.run_nonstream() is NOT wrapped separately. + # It internally calls self.run(), which is already instrumented above, + # so a single invoke_agent span is created per agent execution. + + # Instrument BaseChatModel.chat() - LLM calls + try: + wrap_function_wrapper( + module=_LLM_MODULE, + name="BaseChatModel.chat", + wrapper=lambda wrapped, instance, args, kwargs: wrap_chat_model_chat( + wrapped, instance, args, kwargs, handler=self._handler + ), + ) + logger.debug("Instrumented BaseChatModel.chat") + except Exception as e: + logger.warning(f"Failed to instrument BaseChatModel.chat: {e}") + + # Instrument Agent._call_llm() - ReAct step tracking (only fires for agents with tools) + try: + wrap_function_wrapper( + module=_AGENT_MODULE, + name="Agent._call_llm", + wrapper=lambda wrapped, instance, args, kwargs: wrap_agent_call_llm( + wrapped, instance, args, kwargs, handler=self._handler + ), + ) + logger.debug("Instrumented Agent._call_llm") + except Exception as e: + logger.warning(f"Failed to instrument Agent._call_llm: {e}") + + # Instrument Agent._call_tool() - tool execution + try: + wrap_function_wrapper( + module=_AGENT_MODULE, + name="Agent._call_tool", + wrapper=lambda wrapped, instance, args, kwargs: wrap_agent_call_tool( + wrapped, instance, args, kwargs, handler=self._handler + ), + ) + logger.debug("Instrumented Agent._call_tool") + except Exception as e: + logger.warning(f"Failed to instrument Agent._call_tool: {e}") + + def _uninstrument(self, **kwargs: Any) -> None: + """Disable Qwen-Agent instrumentation.""" + try: + import qwen_agent.agent # noqa: PLC0415 + + unwrap(qwen_agent.agent.Agent, "run") + logger.debug("Uninstrumented Agent.run") + except Exception as e: + logger.warning(f"Failed to uninstrument Agent.run: {e}") + + try: + import qwen_agent.llm.base # noqa: PLC0415 + + unwrap(qwen_agent.llm.base.BaseChatModel, "chat") + logger.debug("Uninstrumented BaseChatModel.chat") + except Exception as e: + logger.warning(f"Failed to uninstrument BaseChatModel.chat: {e}") + + try: + import qwen_agent.agent # noqa: PLC0415 + + unwrap(qwen_agent.agent.Agent, "_call_llm") + logger.debug("Uninstrumented Agent._call_llm") + except Exception as e: + logger.warning(f"Failed to uninstrument Agent._call_llm: {e}") + + try: + import qwen_agent.agent # noqa: PLC0415 + + unwrap(qwen_agent.agent.Agent, "_call_tool") + logger.debug("Uninstrumented Agent._call_tool") + except Exception as e: + logger.warning(f"Failed to uninstrument Agent._call_tool: {e}") + + self._handler = None diff --git a/instrumentation-loongsuite/loongsuite-instrumentation-qwen-agent/src/opentelemetry/instrumentation/qwen_agent/package.py b/instrumentation-loongsuite/loongsuite-instrumentation-qwen-agent/src/opentelemetry/instrumentation/qwen_agent/package.py new file mode 100644 index 000000000..4f9a13437 --- /dev/null +++ b/instrumentation-loongsuite/loongsuite-instrumentation-qwen-agent/src/opentelemetry/instrumentation/qwen_agent/package.py @@ -0,0 +1,17 @@ +# Copyright The OpenTelemetry Authors +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +_instruments = ("qwen-agent >= 0.0.20",) + +_supports_metrics = False diff --git a/instrumentation-loongsuite/loongsuite-instrumentation-qwen-agent/src/opentelemetry/instrumentation/qwen_agent/patch.py b/instrumentation-loongsuite/loongsuite-instrumentation-qwen-agent/src/opentelemetry/instrumentation/qwen_agent/patch.py new file mode 100644 index 000000000..52e24c36e --- /dev/null +++ b/instrumentation-loongsuite/loongsuite-instrumentation-qwen-agent/src/opentelemetry/instrumentation/qwen_agent/patch.py @@ -0,0 +1,304 @@ +# Copyright The OpenTelemetry Authors +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +"""Patch functions for Qwen-Agent instrumentation. + +Wraps key qwen-agent methods to generate OpenTelemetry spans: +- Agent.run() -> invoke_agent spans + (Agent.run_nonstream() is NOT wrapped separately; it calls self.run() + internally, so a single invoke_agent span is produced by this wrapper.) +- BaseChatModel.chat() -> LLM spans +- Agent._call_tool() -> execute_tool spans +- Agent._call_llm() -> react step spans (only for ReAct agents with tools) +""" + +from __future__ import annotations + +import logging +import timeit +from contextvars import ContextVar +from typing import Any, Iterator, Optional + +from opentelemetry.util.genai._extended_common.common_types import ( + ReactStepInvocation, +) +from opentelemetry.util.genai.extended_handler import ExtendedTelemetryHandler +from opentelemetry.util.genai.types import Error + +from .utils import ( + convert_qwen_messages_to_output_messages, + create_agent_invocation, + create_llm_invocation, + create_tool_invocation, +) + +logger = logging.getLogger(__name__) + +# ContextVar guards for ReAct step tracking. +# _react_mode: True when the current agent run has tools (ReAct-capable). +# _react_step_invocation: the currently active (open) ReactStepInvocation. +# _react_step_counter: 1-based step counter within the current agent run. +_react_mode: ContextVar[bool] = ContextVar("qwen_react_mode", default=False) +_react_step_invocation: ContextVar[Optional[ReactStepInvocation]] = ContextVar( + "qwen_react_step_invocation", default=None +) +_react_step_counter: ContextVar[int] = ContextVar( + "qwen_react_step_counter", default=0 +) + + +def _close_active_react_step(handler: ExtendedTelemetryHandler) -> None: + """Close the currently active react_step span, if any.""" + prev = _react_step_invocation.get() + if prev is not None: + try: + handler.stop_react_step(prev) + except Exception as e: + logger.debug(f"Failed to close react step: {e}") + _react_step_invocation.set(None) + + +def wrap_agent_run(wrapped, instance, args, kwargs, handler: ExtendedTelemetryHandler): + """Wrapper for Agent.run() to create invoke_agent spans. + + Agent.run() is a generator that yields List[Message]. + We wrap it to create an agent span covering the full execution. + + Also sets up the ReAct mode guard: if the agent has tools in its + function_map, _react_mode is set to True so that wrap_agent_call_llm + will create react_step spans for each ReAct iteration. + """ + messages = args[0] if args else kwargs.get("messages", []) + + try: + invocation = create_agent_invocation(instance, messages) + except Exception as e: + logger.debug(f"Failed to create agent invocation: {e}") + yield from wrapped(*args, **kwargs) + return + + # Set up ReAct mode guard: only agents with tools get react_step spans. + is_react = bool(getattr(instance, "function_map", {})) + mode_token = _react_mode.set(is_react) + counter_token = _react_step_counter.set(0) + step_token = _react_step_invocation.set(None) + + handler.start_invoke_agent(invocation) + + try: + last_response = None + for response in wrapped(*args, **kwargs): + last_response = response + yield response + + # Extract output from last yielded response + if last_response: + invocation.output_messages = convert_qwen_messages_to_output_messages( + last_response + ) + + # Close the last react_step span before closing invoke_agent. + _close_active_react_step(handler) + + handler.stop_invoke_agent(invocation) + + except Exception as e: + # Close any open react_step on error path too. + _close_active_react_step(handler) + handler.fail_invoke_agent( + invocation, Error(message=str(e), type=type(e)) + ) + raise + finally: + # Restore ContextVars to pre-run state. + _react_step_counter.reset(counter_token) + _react_step_invocation.reset(step_token) + _react_mode.reset(mode_token) + + +def wrap_chat_model_chat( + wrapped, instance, args, kwargs, handler: ExtendedTelemetryHandler +): + """Wrapper for BaseChatModel.chat() to create LLM spans. + + chat() can return: + - List[Message] (non-stream) + - Iterator[List[Message]] (stream) + """ + messages = args[0] if args else kwargs.get("messages", []) + functions = kwargs.get("functions") if len(args) < 2 else (args[1] if len(args) > 1 else None) + stream = kwargs.get("stream", True) + extra_generate_cfg = kwargs.get("extra_generate_cfg") + + try: + invocation = create_llm_invocation( + instance, messages, functions, stream, extra_generate_cfg + ) + except Exception as e: + logger.debug(f"Failed to create LLM invocation: {e}") + return wrapped(*args, **kwargs) + + handler.start_llm(invocation) + + try: + result = wrapped(*args, **kwargs) + + if stream and hasattr(result, "__iter__") and not isinstance(result, list): + # Streaming: wrap the iterator + return _wrap_streaming_llm_response(result, invocation, handler) + else: + # Non-streaming: result is List[Message] + if result: + invocation.output_messages = convert_qwen_messages_to_output_messages( + result + ) + invocation.response_model_name = invocation.request_model + invocation.finish_reasons = ["stop"] + + # Check for function calls in output + for msg in result: + fc = msg.function_call if hasattr(msg, "function_call") else msg.get("function_call") if isinstance(msg, dict) else None + if fc: + invocation.finish_reasons = ["tool_calls"] + break + + handler.stop_llm(invocation) + return result + + except Exception as e: + handler.fail_llm(invocation, Error(message=str(e), type=type(e))) + raise + + +def _wrap_streaming_llm_response( + response_iter: Iterator, invocation: Any, handler: ExtendedTelemetryHandler +) -> Iterator: + """Wrap a streaming LLM response iterator to capture output on completion.""" + try: + last_response = None + first_token = True + for response in response_iter: + if first_token: + invocation.monotonic_first_token_s = timeit.default_timer() + first_token = False + last_response = response + yield response + + if last_response: + invocation.output_messages = convert_qwen_messages_to_output_messages( + last_response + ) + invocation.response_model_name = invocation.request_model + invocation.finish_reasons = ["stop"] + + # Check for function calls + for msg in last_response: + fc = msg.function_call if hasattr(msg, "function_call") else msg.get("function_call") if isinstance(msg, dict) else None + if fc: + invocation.finish_reasons = ["tool_calls"] + break + + handler.stop_llm(invocation) + + except Exception as e: + handler.fail_llm(invocation, Error(message=str(e), type=type(e))) + raise + + +def wrap_agent_call_llm( + wrapped, instance, args, kwargs, handler: ExtendedTelemetryHandler +): + """Wrapper for Agent._call_llm() to create react_step spans. + + Only creates react_step spans when _react_mode is True (i.e. the + current agent has tools in its function_map). This ensures that + simple agents (no tools) are completely unaffected. + + Each call to _call_llm corresponds to one iteration of the ReAct + while-loop. The react_step span is NOT closed here — it stays + open so that subsequent _call_tool invocations become children of + this react_step. The span is closed either: + - by the next wrap_agent_call_llm call (start of next iteration), or + - by wrap_agent_run when the agent run finishes. + """ + if not _react_mode.get(): + # Not a ReAct agent — transparent pass-through. + return wrapped(*args, **kwargs) + + # Close the previous react_step (if any) before starting a new one. + _close_active_react_step(handler) + + # Increment step counter (1-based). + step_num = _react_step_counter.get() + 1 + _react_step_counter.set(step_num) + + step_invocation = ReactStepInvocation(round=step_num) + + try: + handler.start_react_step(step_invocation) + except Exception as e: + logger.debug(f"Failed to start react step: {e}") + return wrapped(*args, **kwargs) + + _react_step_invocation.set(step_invocation) + + # Call original _call_llm — its return value is a generator (or list). + # The chat span created inside will be a child of this react_step + # because start_react_step attached it to the current context. + return wrapped(*args, **kwargs) + + +def wrap_agent_call_tool( + wrapped, instance, args, kwargs, handler: ExtendedTelemetryHandler +): + """Wrapper for Agent._call_tool() to create execute_tool spans. + + _call_tool(tool_name, tool_args, **kwargs) -> str | List[ContentItem] + """ + tool_name = args[0] if args else kwargs.get("tool_name", "unknown_tool") + tool_args = args[1] if len(args) > 1 else kwargs.get("tool_args", "{}") + + # Get tool instance for description + tool_instance = None + if hasattr(instance, "function_map"): + tool_instance = instance.function_map.get(tool_name) + + try: + invocation = create_tool_invocation(tool_name, tool_args, tool_instance) + except Exception as e: + logger.debug(f"Failed to create tool invocation: {e}") + return wrapped(*args, **kwargs) + + handler.start_execute_tool(invocation) + + try: + result = wrapped(*args, **kwargs) + + # Set tool result + if isinstance(result, str): + invocation.tool_call_result = result + elif isinstance(result, list): + # List[ContentItem] - serialize to string + invocation.tool_call_result = str(result) + else: + invocation.tool_call_result = str(result) if result else None + + handler.stop_execute_tool(invocation) + return result + + except Exception as e: + handler.fail_execute_tool( + invocation, Error(message=str(e), type=type(e)) + ) + raise diff --git a/instrumentation-loongsuite/loongsuite-instrumentation-qwen-agent/src/opentelemetry/instrumentation/qwen_agent/utils.py b/instrumentation-loongsuite/loongsuite-instrumentation-qwen-agent/src/opentelemetry/instrumentation/qwen_agent/utils.py new file mode 100644 index 000000000..036cf75ac --- /dev/null +++ b/instrumentation-loongsuite/loongsuite-instrumentation-qwen-agent/src/opentelemetry/instrumentation/qwen_agent/utils.py @@ -0,0 +1,410 @@ +# Copyright The OpenTelemetry Authors +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +"""Utility functions for Qwen-Agent instrumentation. + +Handles conversion between qwen-agent Message types and +OpenTelemetry GenAI semantic convention types. +""" + +from __future__ import annotations + +import json +import logging +from enum import Enum +from typing import Any, Dict, List, Optional + +from opentelemetry.semconv._incubating.attributes import ( + gen_ai_attributes as GenAIAttributes, +) +from opentelemetry.util.genai.extended_types import ( + ExecuteToolInvocation, + InvokeAgentInvocation, +) +from opentelemetry.util.genai.types import ( + FunctionToolDefinition, + InputMessage, + LLMInvocation, + OutputMessage, + Text, + ToolCall, + ToolCallResponse, +) + +logger = logging.getLogger(__name__) + + +class QwenAgentProviderName(str, Enum): + """Provider names for qwen-agent LLM backends.""" + + DASHSCOPE = "dashscope" + QWEN = "qwen" + + +# Map qwen-agent model_type to provider name +_MODEL_TYPE_PROVIDER_MAP = { + "qwen_dashscope": QwenAgentProviderName.DASHSCOPE.value, + "qwenvl_dashscope": QwenAgentProviderName.DASHSCOPE.value, + "qwenaudio_dashscope": QwenAgentProviderName.DASHSCOPE.value, + "oai": GenAIAttributes.GenAiProviderNameValues.OPENAI.value, + "azure": GenAIAttributes.GenAiProviderNameValues.OPENAI.value, + "qwenvl_oai": GenAIAttributes.GenAiProviderNameValues.OPENAI.value, + "qwenomni_oai": GenAIAttributes.GenAiProviderNameValues.OPENAI.value, +} + + +def get_provider_name(llm_instance: Any) -> str: + """Extract provider name from a qwen-agent LLM instance. + + Args: + llm_instance: A BaseChatModel instance from qwen-agent. + + Returns: + Provider name string. + """ + model_type = getattr(llm_instance, "model_type", "") + if model_type in _MODEL_TYPE_PROVIDER_MAP: + return _MODEL_TYPE_PROVIDER_MAP[model_type] + + # Fallback: infer from class name + class_name = type(llm_instance).__name__.lower() + if "dashscope" in class_name: + return QwenAgentProviderName.DASHSCOPE.value + if "openai" in class_name or "oai" in class_name or "azure" in class_name: + return GenAIAttributes.GenAiProviderNameValues.OPENAI.value + + return "qwen_agent" + + +def _extract_content_text(content: Any) -> str: + """Extract text from qwen-agent Message content field. + + Content can be str or List[ContentItem]. + """ + if isinstance(content, str): + return content + if isinstance(content, list): + texts = [] + for item in content: + if hasattr(item, "text") and item.text is not None: + texts.append(item.text) + elif hasattr(item, "get_type_and_value"): + t, v = item.get_type_and_value() + if t == "text": + texts.append(v) + return "\n".join(texts) + return str(content) if content else "" + + +def convert_qwen_messages_to_input_messages( + messages: Any, +) -> List[InputMessage]: + """Convert qwen-agent Message list to GenAI InputMessage format. + + Args: + messages: List of qwen-agent Message objects or dicts. + + Returns: + List of InputMessage objects for ExtendedTelemetryHandler. + """ + if not messages: + return [] + + if not isinstance(messages, list): + messages = [messages] + + input_messages = [] + for msg in messages: + try: + role = msg.role if hasattr(msg, "role") else msg.get("role", "user") + content = msg.content if hasattr(msg, "content") else msg.get("content", "") + function_call = ( + msg.function_call if hasattr(msg, "function_call") else msg.get("function_call") + ) + name = msg.name if hasattr(msg, "name") else msg.get("name") + + parts = [] + + # Handle function_call (tool call from assistant) + if function_call: + fc_name = ( + function_call.name + if hasattr(function_call, "name") + else function_call.get("name", "") + ) + fc_args = ( + function_call.arguments + if hasattr(function_call, "arguments") + else function_call.get("arguments", "{}") + ) + # Parse arguments if string + if isinstance(fc_args, str): + try: + fc_args = json.loads(fc_args) + except (json.JSONDecodeError, ValueError): + pass + parts.append(ToolCall(name=fc_name, arguments=fc_args, id=None)) + + # Handle function role (tool response) + if role == "function" and content: + text = _extract_content_text(content) + parts.append( + ToolCallResponse( + id=name or "", + response=text, + ) + ) + elif content: + text = _extract_content_text(content) + if text: + parts.append(Text(content=text)) + + if parts: + input_messages.append(InputMessage(role=role, parts=parts)) + + except Exception as e: + logger.debug(f"Error converting message: {e}") + continue + + return input_messages + + +def convert_qwen_messages_to_output_messages( + messages: Any, +) -> List[OutputMessage]: + """Convert qwen-agent response messages to GenAI OutputMessage format. + + Args: + messages: List of qwen-agent Message objects (LLM output). + + Returns: + List of OutputMessage objects. + """ + if not messages: + return [] + + if not isinstance(messages, list): + messages = [messages] + + output_messages = [] + for msg in messages: + try: + content = msg.content if hasattr(msg, "content") else msg.get("content", "") + function_call = ( + msg.function_call if hasattr(msg, "function_call") else msg.get("function_call") + ) + + parts = [] + finish_reason = "stop" + + if function_call: + fc_name = ( + function_call.name + if hasattr(function_call, "name") + else function_call.get("name", "") + ) + fc_args = ( + function_call.arguments + if hasattr(function_call, "arguments") + else function_call.get("arguments", "{}") + ) + if isinstance(fc_args, str): + try: + fc_args = json.loads(fc_args) + except (json.JSONDecodeError, ValueError): + pass + parts.append(ToolCall(name=fc_name, arguments=fc_args, id=None)) + finish_reason = "tool_calls" + + if content: + text = _extract_content_text(content) + if text: + parts.append(Text(content=text)) + + if not parts: + parts.append(Text(content="")) + + output_messages.append( + OutputMessage( + role="assistant", + parts=parts, + finish_reason=finish_reason, + ) + ) + + except Exception as e: + logger.debug(f"Error converting output message: {e}") + continue + + return output_messages + + +def get_tool_definitions(functions: Optional[List[Dict]]) -> Optional[List[FunctionToolDefinition]]: + """Extract tool definitions for tracing as FunctionToolDefinition objects. + + Args: + functions: List of function dicts in qwen-agent format + (each with 'name', 'description', 'parameters'). + + Returns: + List of FunctionToolDefinition objects, or None. + """ + if not functions: + return None + + try: + tool_defs = [] + for func in functions: + if not isinstance(func, dict): + continue + name = func.get("name") + if not name: + continue + tool_defs.append( + FunctionToolDefinition( + name=name, + description=func.get("description"), + parameters=func.get("parameters"), + ) + ) + if tool_defs: + return tool_defs + except Exception: + pass + + return None + + +def create_llm_invocation( + llm_instance: Any, + messages: Any, + functions: Optional[List[Dict]] = None, + stream: bool = True, + extra_generate_cfg: Optional[Dict] = None, +) -> LLMInvocation: + """Create LLMInvocation from qwen-agent BaseChatModel.chat() parameters. + + Args: + llm_instance: The BaseChatModel instance. + messages: Input messages. + functions: Tool function definitions. + stream: Whether streaming. + extra_generate_cfg: Extra generation config. + + Returns: + LLMInvocation for ExtendedTelemetryHandler. + """ + provider_name = get_provider_name(llm_instance) + request_model = getattr(llm_instance, "model", "unknown_model") + + input_messages = convert_qwen_messages_to_input_messages(messages) + + invocation = LLMInvocation( + request_model=request_model, + provider=provider_name, + input_messages=input_messages, + ) + + # Set generation parameters + if extra_generate_cfg: + if extra_generate_cfg.get("max_tokens"): + invocation.max_tokens = extra_generate_cfg["max_tokens"] + if extra_generate_cfg.get("temperature"): + invocation.temperature = extra_generate_cfg["temperature"] + if extra_generate_cfg.get("top_p"): + invocation.top_p = extra_generate_cfg["top_p"] + + # Set tool definitions + tool_definitions = get_tool_definitions(functions) + if tool_definitions: + invocation.tool_definitions = tool_definitions + + return invocation + + +def create_agent_invocation( + agent_instance: Any, + messages: Any, +) -> InvokeAgentInvocation: + """Create InvokeAgentInvocation from qwen-agent Agent.run() parameters. + + Args: + agent_instance: The Agent instance. + messages: Input messages. + + Returns: + InvokeAgentInvocation for ExtendedTelemetryHandler. + """ + # Get provider and model from agent's LLM + provider_name = None + request_model = None + if hasattr(agent_instance, "llm") and agent_instance.llm: + provider_name = get_provider_name(agent_instance.llm) + request_model = getattr(agent_instance.llm, "model", None) + + input_messages = convert_qwen_messages_to_input_messages(messages) + + agent_name = getattr(agent_instance, "name", None) or type(agent_instance).__name__ + agent_description = getattr(agent_instance, "description", None) or "" + + invocation = InvokeAgentInvocation( + provider=provider_name, + agent_name=agent_name, + agent_description=agent_description, + request_model=request_model, + input_messages=input_messages, + ) + + # Set system instruction if available + if hasattr(agent_instance, "system_message") and agent_instance.system_message: + invocation.system_instruction = [Text(content=agent_instance.system_message)] + + return invocation + + +def create_tool_invocation( + tool_name: str, + tool_args: Any = None, + tool_instance: Any = None, +) -> ExecuteToolInvocation: + """Create ExecuteToolInvocation from qwen-agent tool call parameters. + + Args: + tool_name: Name of the tool. + tool_args: Tool arguments (str or dict). + tool_instance: The BaseTool instance, if available. + + Returns: + ExecuteToolInvocation for ExtendedTelemetryHandler. + """ + # Parse tool_args + if isinstance(tool_args, str): + try: + parsed_args = json.loads(tool_args) + except (json.JSONDecodeError, ValueError): + parsed_args = {"raw_args": tool_args} + elif isinstance(tool_args, dict): + parsed_args = tool_args + else: + parsed_args = {} + + tool_description = None + if tool_instance: + tool_description = getattr(tool_instance, "description", None) + + return ExecuteToolInvocation( + tool_name=tool_name, + tool_call_arguments=parsed_args, + tool_description=tool_description, + ) diff --git a/instrumentation-loongsuite/loongsuite-instrumentation-qwen-agent/src/opentelemetry/instrumentation/qwen_agent/version.py b/instrumentation-loongsuite/loongsuite-instrumentation-qwen-agent/src/opentelemetry/instrumentation/qwen_agent/version.py new file mode 100644 index 000000000..5fd301e2e --- /dev/null +++ b/instrumentation-loongsuite/loongsuite-instrumentation-qwen-agent/src/opentelemetry/instrumentation/qwen_agent/version.py @@ -0,0 +1,15 @@ +# Copyright The OpenTelemetry Authors +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +__version__ = "0.1.0" diff --git a/instrumentation-loongsuite/loongsuite-instrumentation-qwen-agent/tests/__init__.py b/instrumentation-loongsuite/loongsuite-instrumentation-qwen-agent/tests/__init__.py new file mode 100644 index 000000000..e69de29bb diff --git a/instrumentation-loongsuite/loongsuite-instrumentation-qwen-agent/tests/cassettes/test_agent_run_nonstream.yaml b/instrumentation-loongsuite/loongsuite-instrumentation-qwen-agent/tests/cassettes/test_agent_run_nonstream.yaml new file mode 100644 index 000000000..2fbba30a9 --- /dev/null +++ b/instrumentation-loongsuite/loongsuite-instrumentation-qwen-agent/tests/cassettes/test_agent_run_nonstream.yaml @@ -0,0 +1,85 @@ +interactions: +- request: + body: |- + { + "model": "qwen-max", + "parameters": { + "result_format": "message", + "incremental_output": true, + "seed": 993050835 + }, + "input": { + "messages": [ + { + "role": "user", + "content": "Say 'OK' and nothing else." + } + ] + } + } + headers: + Accept: + - text/event-stream + Accept-Encoding: + - gzip, deflate, br + Connection: + - keep-alive + Content-Length: + - '196' + Content-Type: + - application/json + X-Accel-Buffering: + - 'no' + X-DashScope-SSE: + - enable + authorization: + - Bearer test_dashscope_api_key + user-agent: + - dashscope/1.25.2; python/3.12.10; platform/macOS-15.1.1-arm64-arm-64bit; processor/arm; + incremental_to_full/0 + method: POST + uri: https://dashscope.aliyuncs.com/api/v1/services/aigc/text-generation/generation + response: + body: + string: |+ + id:1 + event:result + :HTTP_STATUS/200 + data:{"output":{"choices":[{"message":{"content":"OK","role":"assistant"},"finish_reason":"null"}]},"usage":{"total_tokens":17,"output_tokens":1,"input_tokens":16,"prompt_tokens_details":{"cached_tokens":0}},"request_id":"81fdbf28-1e5f-4c23-964c-0568e8684665"} + + id:2 + event:result + :HTTP_STATUS/200 + data:{"output":{"choices":[{"message":{"content":"","role":"assistant"},"finish_reason":"stop"}]},"usage":{"total_tokens":17,"output_tokens":1,"input_tokens":16,"prompt_tokens_details":{"cached_tokens":0}},"request_id":"81fdbf28-1e5f-4c23-964c-0568e8684665"} + + headers: + content-type: + - text/event-stream;charset=UTF-8 + date: + - Fri, 20 Mar 2026 02:22:37 GMT + req-arrive-time: + - '1773973357553' + req-cost-time: + - '523' + resp-start-time: + - '1773973358076' + server: + - istio-envoy + transfer-encoding: + - chunked + vary: + - Origin,Access-Control-Request-Method,Access-Control-Request-Headers + x-dashscope-call-gateway: + - 'true' + x-dashscope-finished: + - 'false' + x-dashscope-timeout: + - '298' + x-envoy-upstream-service-time: + - '515' + x-request-id: + - 81fdbf28-1e5f-4c23-964c-0568e8684665 + status: + code: 200 + message: OK +version: 1 diff --git a/instrumentation-loongsuite/loongsuite-instrumentation-qwen-agent/tests/cassettes/test_multi_turn_conversation.yaml b/instrumentation-loongsuite/loongsuite-instrumentation-qwen-agent/tests/cassettes/test_multi_turn_conversation.yaml new file mode 100644 index 000000000..1edec8ee8 --- /dev/null +++ b/instrumentation-loongsuite/loongsuite-instrumentation-qwen-agent/tests/cassettes/test_multi_turn_conversation.yaml @@ -0,0 +1,103 @@ +interactions: +- request: + body: |- + { + "model": "qwen-max", + "parameters": { + "result_format": "message", + "incremental_output": true, + "seed": 260755724 + }, + "input": { + "messages": [ + { + "role": "user", + "content": "My name is Alice." + }, + { + "role": "assistant", + "content": "Nice to meet you, Alice!" + }, + { + "role": "user", + "content": "What is my name?" + } + ] + } + } + headers: + Accept: + - text/event-stream + Accept-Encoding: + - gzip, deflate, br + Connection: + - keep-alive + Content-Length: + - '298' + Content-Type: + - application/json + X-Accel-Buffering: + - 'no' + X-DashScope-SSE: + - enable + authorization: + - Bearer test_dashscope_api_key + user-agent: + - dashscope/1.25.2; python/3.12.10; platform/macOS-15.1.1-arm64-arm-64bit; processor/arm; + incremental_to_full/0 + method: POST + uri: https://dashscope.aliyuncs.com/api/v1/services/aigc/text-generation/generation + response: + body: + string: |+ + id:1 + event:result + :HTTP_STATUS/200 + data:{"output":{"choices":[{"message":{"content":"Your","role":"assistant"},"finish_reason":"null"}]},"usage":{"total_tokens":36,"output_tokens":1,"input_tokens":35,"prompt_tokens_details":{"cached_tokens":0}},"request_id":"fd5a3067-858a-4604-ab8e-8b9e40796e99"} + + id:2 + event:result + :HTTP_STATUS/200 + data:{"output":{"choices":[{"message":{"content":" name is Alice","role":"assistant"},"finish_reason":"null"}]},"usage":{"total_tokens":39,"output_tokens":4,"input_tokens":35,"prompt_tokens_details":{"cached_tokens":0}},"request_id":"fd5a3067-858a-4604-ab8e-8b9e40796e99"} + + id:3 + event:result + :HTTP_STATUS/200 + data:{"output":{"choices":[{"message":{"content":".","role":"assistant"},"finish_reason":"null"}]},"usage":{"total_tokens":40,"output_tokens":5,"input_tokens":35,"prompt_tokens_details":{"cached_tokens":0}},"request_id":"fd5a3067-858a-4604-ab8e-8b9e40796e99"} + + id:4 + event:result + :HTTP_STATUS/200 + data:{"output":{"choices":[{"message":{"content":"","role":"assistant"},"finish_reason":"stop"}]},"usage":{"total_tokens":40,"output_tokens":5,"input_tokens":35,"prompt_tokens_details":{"cached_tokens":0}},"request_id":"fd5a3067-858a-4604-ab8e-8b9e40796e99"} + + headers: + content-type: + - text/event-stream;charset=UTF-8 + date: + - Fri, 20 Mar 2026 02:22:38 GMT + req-arrive-time: + - '1773973358381' + req-cost-time: + - '260' + resp-start-time: + - '1773973358642' + server: + - istio-envoy + transfer-encoding: + - chunked + vary: + - Origin,Access-Control-Request-Method,Access-Control-Request-Headers + x-dashscope-call-gateway: + - 'true' + x-dashscope-finished: + - 'false' + x-dashscope-timeout: + - '298' + x-envoy-upstream-service-time: + - '254' + x-request-id: + - fd5a3067-858a-4604-ab8e-8b9e40796e99 + status: + code: 200 + message: OK +version: 1 diff --git a/instrumentation-loongsuite/loongsuite-instrumentation-qwen-agent/tests/cassettes/test_non_stream_chat.yaml b/instrumentation-loongsuite/loongsuite-instrumentation-qwen-agent/tests/cassettes/test_non_stream_chat.yaml new file mode 100644 index 000000000..b0d43f704 --- /dev/null +++ b/instrumentation-loongsuite/loongsuite-instrumentation-qwen-agent/tests/cassettes/test_non_stream_chat.yaml @@ -0,0 +1,94 @@ +interactions: +- request: + body: |- + { + "model": "qwen-max", + "parameters": { + "result_format": "message", + "seed": 935360180 + }, + "input": { + "messages": [ + { + "role": "user", + "content": "What is 2+2? Answer with just the number." + } + ] + } + } + headers: + Accept: + - application/json + Accept-Encoding: + - gzip, deflate, br + Connection: + - keep-alive + Content-Length: + - '183' + Content-Type: + - application/json + authorization: + - Bearer test_dashscope_api_key + user-agent: + - dashscope/1.25.2; python/3.12.10; platform/macOS-15.1.1-arm64-arm-64bit; processor/arm; + incremental_to_full/0 + method: POST + uri: https://dashscope.aliyuncs.com/api/v1/services/aigc/text-generation/generation + response: + body: + string: |- + { + "output": { + "choices": [ + { + "finish_reason": "stop", + "message": { + "content": "4", + "role": "assistant" + } + } + ] + }, + "usage": { + "input_tokens": 21, + "output_tokens": 1, + "prompt_tokens_details": { + "cached_tokens": 0 + }, + "total_tokens": 22 + }, + "request_id": "c5f380ae-1f7e-423b-803a-9d38fe7f448c" + } + headers: + content-length: + - '254' + content-type: + - application/json + date: + - Fri, 20 Mar 2026 02:31:41 GMT + req-arrive-time: + - '1773973901239' + req-cost-time: + - '679' + resp-start-time: + - '1773973901919' + server: + - istio-envoy + transfer-encoding: + - chunked + vary: + - Origin,Access-Control-Request-Method,Access-Control-Request-Headers, Accept-Encoding + x-dashscope-call-gateway: + - 'true' + x-dashscope-finished: + - 'true' + x-dashscope-timeout: + - '298' + x-envoy-upstream-service-time: + - '673' + x-request-id: + - c5f380ae-1f7e-423b-803a-9d38fe7f448c + status: + code: 200 + message: OK +version: 1 diff --git a/instrumentation-loongsuite/loongsuite-instrumentation-qwen-agent/tests/cassettes/test_qwen_agent_basic_run.yaml b/instrumentation-loongsuite/loongsuite-instrumentation-qwen-agent/tests/cassettes/test_qwen_agent_basic_run.yaml new file mode 100644 index 000000000..4fbdd0095 --- /dev/null +++ b/instrumentation-loongsuite/loongsuite-instrumentation-qwen-agent/tests/cassettes/test_qwen_agent_basic_run.yaml @@ -0,0 +1,105 @@ +interactions: +- request: + body: |- + { + "model": "qwen-max", + "parameters": { + "result_format": "message", + "incremental_output": true, + "seed": 289569634 + }, + "input": { + "messages": [ + { + "role": "user", + "content": "Hello, what is 1+1?" + } + ] + } + } + headers: + Accept: + - text/event-stream + Accept-Encoding: + - gzip, deflate, br + Connection: + - keep-alive + Content-Length: + - '189' + Content-Type: + - application/json + X-Accel-Buffering: + - 'no' + X-DashScope-SSE: + - enable + authorization: + - Bearer test_dashscope_api_key + user-agent: + - dashscope/1.25.2; python/3.12.10; platform/macOS-15.1.1-arm64-arm-64bit; processor/arm; + incremental_to_full/0 + method: POST + uri: https://dashscope.aliyuncs.com/api/v1/services/aigc/text-generation/generation + response: + body: + string: |+ + id:1 + event:result + :HTTP_STATUS/200 + data:{"output":{"choices":[{"message":{"content":"Hello","role":"assistant"},"finish_reason":"null"}]},"usage":{"total_tokens":18,"output_tokens":1,"input_tokens":17,"prompt_tokens_details":{"cached_tokens":0}},"request_id":"f0a08fc8-84cd-4884-a742-f8f94d014c2a"} + + id:2 + event:result + :HTTP_STATUS/200 + data:{"output":{"choices":[{"message":{"content":"! ","role":"assistant"},"finish_reason":"null"}]},"usage":{"total_tokens":20,"output_tokens":3,"input_tokens":17,"prompt_tokens_details":{"cached_tokens":0}},"request_id":"f0a08fc8-84cd-4884-a742-f8f94d014c2a"} + + id:3 + event:result + :HTTP_STATUS/200 + data:{"output":{"choices":[{"message":{"content":"1+1","role":"assistant"},"finish_reason":"null"}]},"usage":{"total_tokens":23,"output_tokens":6,"input_tokens":17,"prompt_tokens_details":{"cached_tokens":0}},"request_id":"f0a08fc8-84cd-4884-a742-f8f94d014c2a"} + + id:4 + event:result + :HTTP_STATUS/200 + data:{"output":{"choices":[{"message":{"content":" equals 2","role":"assistant"},"finish_reason":"null"}]},"usage":{"total_tokens":26,"output_tokens":9,"input_tokens":17,"prompt_tokens_details":{"cached_tokens":0}},"request_id":"f0a08fc8-84cd-4884-a742-f8f94d014c2a"} + + id:5 + event:result + :HTTP_STATUS/200 + data:{"output":{"choices":[{"message":{"content":".","role":"assistant"},"finish_reason":"null"}]},"usage":{"total_tokens":27,"output_tokens":10,"input_tokens":17,"prompt_tokens_details":{"cached_tokens":0}},"request_id":"f0a08fc8-84cd-4884-a742-f8f94d014c2a"} + + id:6 + event:result + :HTTP_STATUS/200 + data:{"output":{"choices":[{"message":{"content":"","role":"assistant"},"finish_reason":"stop"}]},"usage":{"total_tokens":27,"output_tokens":10,"input_tokens":17,"prompt_tokens_details":{"cached_tokens":0}},"request_id":"f0a08fc8-84cd-4884-a742-f8f94d014c2a"} + + headers: + content-type: + - text/event-stream;charset=UTF-8 + date: + - Thu, 19 Mar 2026 08:14:35 GMT + req-arrive-time: + - '1773908075696' + req-cost-time: + - '235' + resp-start-time: + - '1773908075932' + server: + - istio-envoy + transfer-encoding: + - chunked + vary: + - Origin,Access-Control-Request-Method,Access-Control-Request-Headers + x-dashscope-call-gateway: + - 'true' + x-dashscope-finished: + - 'false' + x-dashscope-timeout: + - '298' + x-envoy-upstream-service-time: + - '228' + x-request-id: + - f0a08fc8-84cd-4884-a742-f8f94d014c2a + status: + code: 200 + message: OK +version: 1 diff --git a/instrumentation-loongsuite/loongsuite-instrumentation-qwen-agent/tests/cassettes/test_qwen_agent_stream_llm_with_ttft.yaml b/instrumentation-loongsuite/loongsuite-instrumentation-qwen-agent/tests/cassettes/test_qwen_agent_stream_llm_with_ttft.yaml new file mode 100644 index 000000000..47c5d84ac --- /dev/null +++ b/instrumentation-loongsuite/loongsuite-instrumentation-qwen-agent/tests/cassettes/test_qwen_agent_stream_llm_with_ttft.yaml @@ -0,0 +1,85 @@ +interactions: +- request: + body: |- + { + "model": "qwen-max", + "parameters": { + "result_format": "message", + "incremental_output": true, + "seed": 200802247 + }, + "input": { + "messages": [ + { + "role": "user", + "content": "Say hello in one word." + } + ] + } + } + headers: + Accept: + - text/event-stream + Accept-Encoding: + - gzip, deflate, br + Connection: + - keep-alive + Content-Length: + - '192' + Content-Type: + - application/json + X-Accel-Buffering: + - 'no' + X-DashScope-SSE: + - enable + authorization: + - Bearer test_dashscope_api_key + user-agent: + - dashscope/1.25.2; python/3.12.10; platform/macOS-15.1.1-arm64-arm-64bit; processor/arm; + incremental_to_full/0 + method: POST + uri: https://dashscope.aliyuncs.com/api/v1/services/aigc/text-generation/generation + response: + body: + string: |+ + id:1 + event:result + :HTTP_STATUS/200 + data:{"output":{"choices":[{"message":{"content":"Hello","role":"assistant"},"finish_reason":"null"}]},"usage":{"total_tokens":15,"output_tokens":1,"input_tokens":14,"prompt_tokens_details":{"cached_tokens":0}},"request_id":"280f9f0f-6f8b-4d48-b646-aceda50fe87c"} + + id:2 + event:result + :HTTP_STATUS/200 + data:{"output":{"choices":[{"message":{"content":"","role":"assistant"},"finish_reason":"stop"}]},"usage":{"total_tokens":15,"output_tokens":1,"input_tokens":14,"prompt_tokens_details":{"cached_tokens":0}},"request_id":"280f9f0f-6f8b-4d48-b646-aceda50fe87c"} + + headers: + content-type: + - text/event-stream;charset=UTF-8 + date: + - Thu, 19 Mar 2026 08:14:36 GMT + req-arrive-time: + - '1773908076883' + req-cost-time: + - '264' + resp-start-time: + - '1773908077147' + server: + - istio-envoy + transfer-encoding: + - chunked + vary: + - Origin,Access-Control-Request-Method,Access-Control-Request-Headers + x-dashscope-call-gateway: + - 'true' + x-dashscope-finished: + - 'false' + x-dashscope-timeout: + - '298' + x-envoy-upstream-service-time: + - '259' + x-request-id: + - 280f9f0f-6f8b-4d48-b646-aceda50fe87c + status: + code: 200 + message: OK +version: 1 diff --git a/instrumentation-loongsuite/loongsuite-instrumentation-qwen-agent/tests/cassettes/test_qwen_agent_with_tool_call.yaml b/instrumentation-loongsuite/loongsuite-instrumentation-qwen-agent/tests/cassettes/test_qwen_agent_with_tool_call.yaml new file mode 100644 index 000000000..f6daee186 --- /dev/null +++ b/instrumentation-loongsuite/loongsuite-instrumentation-qwen-agent/tests/cassettes/test_qwen_agent_with_tool_call.yaml @@ -0,0 +1,444 @@ +interactions: +- request: + body: |- + { + "model": "qwen-max", + "parameters": { + "result_format": "message", + "incremental_output": true, + "seed": 1031217577, + "tools": [ + { + "type": "function", + "function": { + "name": "get_current_weather_test", + "description": "Get the current weather for a given city.", + "parameters": [ + { + "name": "city", + "type": "string", + "description": "The city name to get weather for.", + "required": true + } + ] + } + } + ] + }, + "input": { + "messages": [ + { + "role": "user", + "content": "What is the weather in Beijing right now?" + } + ] + } + } + headers: + Accept: + - text/event-stream + Accept-Encoding: + - gzip, deflate, br + Connection: + - keep-alive + Content-Length: + - '477' + Content-Type: + - application/json + X-Accel-Buffering: + - 'no' + X-DashScope-SSE: + - enable + authorization: + - Bearer test_dashscope_api_key + user-agent: + - dashscope/1.25.2; 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Let's try again.", + "tool_calls": [ + { + "id": "call_cbd8e5262b69466a8f8fdc", + "type": "function", + "function": { + "name": "get_current_weather_test", + "arguments": "{\"city\": \"Beijing\"}" + } + } + ] + }, + { + "role": "tool", + "content": "An error occurred when calling tool `get_current_weather_test`:\nAttributeError: 'str' object has no attribute 'get'\nTraceback:\n File \"/Users/sipercai/miniforge3/lib/python3.12/site-packages/qwen_agent/agent.py\", line 192, in _call_tool\n tool_result = tool.call(tool_args, **kwargs)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/Users/sipercai/project/pyins/team-work/loongsuite-python-agent/instrumentation-loongsuite/loongsuite-instrumentation-qwen-agent/tests/test_real_api.py\", line 204, in call\n city = params.get(\"city\", \"unknown\")\n ^^^^^^^^^^\n", + "name": "get_current_weather_test", + "extra": { + "function_id": "call_cbd8e5262b69466a8f8fdc" + }, + "id": "call_cbd8e5262b69466a8f8fdc" + } + ] + } + } + headers: + Accept: + - text/event-stream + Accept-Encoding: + - gzip, deflate, br + Connection: + - keep-alive + Content-Length: + - '2471' + Content-Type: + - application/json + X-Accel-Buffering: + - 'no' + X-DashScope-SSE: + - enable + authorization: + - Bearer test_dashscope_api_key + user-agent: + - dashscope/1.25.2; python/3.12.10; platform/macOS-15.1.1-arm64-arm-64bit; processor/arm; + incremental_to_full/0 + method: POST + uri: https://dashscope.aliyuncs.com/api/v1/services/aigc/text-generation/generation + response: + body: + string: |+ + id:1 + event:result + :HTTP_STATUS/200 + data:{"output":{"choices":[{"message":{"content":"I","role":"assistant"},"index":0,"finish_reason":"null"}]},"usage":{"total_tokens":637,"output_tokens":2,"input_tokens":635,"prompt_tokens_details":{"cached_tokens":0}},"request_id":"f5412765-6e4e-457a-abe6-ef0eca865a38"} + + id:2 + event:result + :HTTP_STATUS/200 + data:{"output":{"choices":[{"message":{"content":"'m encountering","role":"assistant"},"index":0,"finish_reason":"null"}]},"usage":{"total_tokens":639,"output_tokens":4,"input_tokens":635,"prompt_tokens_details":{"cached_tokens":0}},"request_id":"f5412765-6e4e-457a-abe6-ef0eca865a38"} + + id:3 + event:result + :HTTP_STATUS/200 + data:{"output":{"choices":[{"message":{"content":" a","role":"assistant"},"index":0,"finish_reason":"null"}]},"usage":{"total_tokens":640,"output_tokens":5,"input_tokens":635,"prompt_tokens_details":{"cached_tokens":0}},"request_id":"f5412765-6e4e-457a-abe6-ef0eca865a38"} + + id:4 + event:result + :HTTP_STATUS/200 + data:{"output":{"choices":[{"message":{"content":" technical issue while trying","role":"assistant"},"index":0,"finish_reason":"null"}]},"usage":{"total_tokens":644,"output_tokens":9,"input_tokens":635,"prompt_tokens_details":{"cached_tokens":0}},"request_id":"f5412765-6e4e-457a-abe6-ef0eca865a38"} + + id:5 + event:result + :HTTP_STATUS/200 + data:{"output":{"choices":[{"message":{"content":" to fetch the current weather","role":"assistant"},"index":0,"finish_reason":"null"}]},"usage":{"total_tokens":649,"output_tokens":14,"input_tokens":635,"prompt_tokens_details":{"cached_tokens":0}},"request_id":"f5412765-6e4e-457a-abe6-ef0eca865a38"} + + id:6 + event:result + :HTTP_STATUS/200 + data:{"output":{"choices":[{"message":{"content":" for Beijing. 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42.","role":"assistant"},"index":0,"finish_reason":"null"}]},"usage":{"total_tokens":310,"output_tokens":15,"input_tokens":295,"prompt_tokens_details":{"cached_tokens":0}},"request_id":"144bde91-158f-46e9-ac9c-49249e330cbc"} + + id:5 + event:result + :HTTP_STATUS/200 + data:{"output":{"choices":[{"message":{"content":"","role":"assistant"},"index":0,"finish_reason":"stop"}]},"usage":{"total_tokens":310,"output_tokens":15,"input_tokens":295,"prompt_tokens_details":{"cached_tokens":0}},"request_id":"144bde91-158f-46e9-ac9c-49249e330cbc"} + + headers: + content-type: + - text/event-stream;charset=UTF-8 + date: + - Fri, 20 Mar 2026 02:22:41 GMT + req-arrive-time: + - '1773973360868' + req-cost-time: + - '447' + resp-start-time: + - '1773973361315' + server: + - istio-envoy + transfer-encoding: + - chunked + vary: + - Origin,Access-Control-Request-Method,Access-Control-Request-Headers + x-dashscope-call-gateway: + - 'true' + x-dashscope-finished: + - 'false' + x-dashscope-timeout: + - '298' + x-envoy-upstream-service-time: + - '439' + x-request-id: + - 144bde91-158f-46e9-ac9c-49249e330cbc + status: + code: 200 + message: OK +version: 1 diff --git a/instrumentation-loongsuite/loongsuite-instrumentation-qwen-agent/tests/conftest.py b/instrumentation-loongsuite/loongsuite-instrumentation-qwen-agent/tests/conftest.py new file mode 100644 index 000000000..ec0f10810 --- /dev/null +++ b/instrumentation-loongsuite/loongsuite-instrumentation-qwen-agent/tests/conftest.py @@ -0,0 +1,205 @@ +# Copyright The OpenTelemetry Authors +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +"""Test configuration for Qwen-Agent instrumentation tests.""" + +import json +import os + +import pytest +import yaml +from vcr.stubs import VCRHTTPResponse + +# Set DASHSCOPE_API_KEY before any dashscope/qwen-agent imports +# dashscope SDK reads environment variables at module import time +if "DASHSCOPE_API_KEY" not in os.environ: + os.environ["DASHSCOPE_API_KEY"] = "test_dashscope_api_key" + +from opentelemetry.instrumentation.qwen_agent import QwenAgentInstrumentor +from opentelemetry.sdk._logs import LoggerProvider +from opentelemetry.sdk._logs.export import ( + InMemoryLogExporter, + SimpleLogRecordProcessor, +) +from opentelemetry.sdk.metrics import MeterProvider +from opentelemetry.sdk.metrics.export import InMemoryMetricReader +from opentelemetry.sdk.trace import TracerProvider +from opentelemetry.sdk.trace.export import SimpleSpanProcessor +from opentelemetry.sdk.trace.export.in_memory_span_exporter import ( + InMemorySpanExporter, +) + + +def pytest_configure(config: pytest.Config): + os.environ["OTEL_SEMCONV_STABILITY_OPT_IN"] = "gen_ai_latest_experimental" + + +# ==================== Exporters ==================== + + +@pytest.fixture(scope="function", name="span_exporter") +def fixture_span_exporter(): + exporter = InMemorySpanExporter() + yield exporter + + +@pytest.fixture(scope="function", name="log_exporter") +def fixture_log_exporter(): + exporter = InMemoryLogExporter() + yield exporter + + +@pytest.fixture(scope="function", name="metric_reader") +def fixture_metric_reader(): + reader = InMemoryMetricReader() + yield reader + + +# ==================== Providers ==================== + + +@pytest.fixture(scope="function", name="tracer_provider") +def fixture_tracer_provider(span_exporter): + provider = TracerProvider() + provider.add_span_processor(SimpleSpanProcessor(span_exporter)) + return provider + + +@pytest.fixture(scope="function", name="logger_provider") +def fixture_logger_provider(log_exporter): + provider = LoggerProvider() + provider.add_log_record_processor(SimpleLogRecordProcessor(log_exporter)) + return provider + + +@pytest.fixture(scope="function", name="meter_provider") +def fixture_meter_provider(metric_reader): + meter_provider = MeterProvider( + metric_readers=[metric_reader], + ) + return meter_provider + + +# ==================== Instrumentation ==================== + + +@pytest.fixture(scope="function") +def instrument(tracer_provider, logger_provider, meter_provider): + instrumentor = QwenAgentInstrumentor() + instrumentor.instrument( + tracer_provider=tracer_provider, + logger_provider=logger_provider, + meter_provider=meter_provider, + skip_dep_check=True, + ) + yield instrumentor + instrumentor.uninstrument() + + +# ==================== VCR Support ==================== + + +def _patch_vcr_response(): + """Patch VCRHTTPResponse to add missing version_string attribute. + + Newer urllib3 requires version_string on HTTP responses, but VCR.py's + VCRHTTPResponse stub does not set it, causing AttributeError when dashscope + SDK streams SSE responses. + """ + if not hasattr(VCRHTTPResponse, "version_string"): + VCRHTTPResponse.version_string = "HTTP/1.1" + + +_patch_vcr_response() + + +class LiteralBlockScalar(str): + """Formats the string as a literal block scalar.""" + + +def literal_block_scalar_presenter(dumper, data): + """Represents a scalar string as a literal block.""" + return dumper.represent_scalar("tag:yaml.org,2002:str", data, style="|") + + +yaml.add_representer(LiteralBlockScalar, literal_block_scalar_presenter) + + +def process_string_value(string_value): + """Pretty-prints JSON or returns long strings as a LiteralBlockScalar.""" + try: + json_data = json.loads(string_value) + return LiteralBlockScalar(json.dumps(json_data, indent=2)) + except (ValueError, TypeError): + if len(string_value) > 80: + return LiteralBlockScalar(string_value) + return string_value + + +def convert_body_to_literal(data): + """Searches the data for body strings, attempting to pretty-print JSON.""" + if isinstance(data, dict): + for key, value in data.items(): + if key == "body" and isinstance(value, dict) and "string" in value: + value["string"] = process_string_value(value["string"]) + elif key == "body" and isinstance(value, str): + data[key] = process_string_value(value) + else: + convert_body_to_literal(value) + elif isinstance(data, list): + for idx, choice in enumerate(data): + data[idx] = convert_body_to_literal(choice) + return data + + +class PrettyPrintJSONBody: + """Makes request and response body recordings more readable.""" + + @staticmethod + def serialize(cassette_dict): + cassette_dict = convert_body_to_literal(cassette_dict) + return yaml.dump( + cassette_dict, default_flow_style=False, allow_unicode=True + ) + + @staticmethod + def deserialize(cassette_string): + return yaml.load(cassette_string, Loader=yaml.Loader) + + +def scrub_response_headers(response): + """Scrubs sensitive response headers.""" + if "x-dashscope-request-id" in response.get("headers", {}): + response["headers"]["x-dashscope-request-id"] = "test_request_id" + return response + + +@pytest.fixture(scope="module") +def vcr_config(): + """Configure VCR for recording/replaying HTTP interactions.""" + return { + "filter_headers": [ + ("authorization", "Bearer test_dashscope_api_key"), + ("x-dashscope-api-key", "test_dashscope_api_key"), + ], + "decode_compressed_response": True, + "before_record_response": scrub_response_headers, + } + + +@pytest.fixture(scope="module", autouse=True) +def fixture_vcr(vcr): + """Register custom VCR serializer.""" + vcr.register_serializer("yaml", PrettyPrintJSONBody) + return vcr diff --git a/instrumentation-loongsuite/loongsuite-instrumentation-qwen-agent/tests/requirements.latest.txt b/instrumentation-loongsuite/loongsuite-instrumentation-qwen-agent/tests/requirements.latest.txt new file mode 100644 index 000000000..3458eb436 --- /dev/null +++ b/instrumentation-loongsuite/loongsuite-instrumentation-qwen-agent/tests/requirements.latest.txt @@ -0,0 +1,37 @@ +# Copyright The OpenTelemetry Authors +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# ******************************** +# WARNING: NOT HERMETIC !!!!!!!!!! +# ******************************** +# +# Installed together with {[testenv]test_deps} from tox-loongsuite.ini +# (opentelemetry-api/sdk/semantic-conventions from CORE_REPO). + +# Newest supported versions of external dependencies for qwen-agent tests. +# numpy / soundfile / python-dateutil: see requirements.oldest.txt + +qwen-agent>=0.0.20 +numpy>=1.24.0 +soundfile>=0.12.0 +python-dateutil>=2.8.0 +pytest==7.4.4 +pytest-vcr==1.0.2 +vcrpy>=4.2.0 +pyyaml>=6.0 +wrapt==1.17.3 + +-e opentelemetry-instrumentation +-e instrumentation-loongsuite/loongsuite-instrumentation-qwen-agent +-e util/opentelemetry-util-genai diff --git a/instrumentation-loongsuite/loongsuite-instrumentation-qwen-agent/tests/requirements.oldest.txt b/instrumentation-loongsuite/loongsuite-instrumentation-qwen-agent/tests/requirements.oldest.txt new file mode 100644 index 000000000..9a4ebd320 --- /dev/null +++ b/instrumentation-loongsuite/loongsuite-instrumentation-qwen-agent/tests/requirements.oldest.txt @@ -0,0 +1,35 @@ +# Copyright The OpenTelemetry Authors +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# You may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# Oldest supported versions for loongsuite-instrumentation-qwen-agent tests. +# numpy / soundfile / python-dateutil: not always declared by qwen-agent but +# required at import time by current qwen_agent modules used in tests. + +qwen-agent>=0.0.20 +numpy>=1.24.0 +soundfile>=0.12.0 +python-dateutil>=2.8.0 +pytest==7.4.4 +pytest-vcr==1.0.2 +vcrpy>=4.2.0 +pyyaml>=6.0 +wrapt==1.17.3 +opentelemetry-exporter-otlp-proto-http~=1.30 +opentelemetry-api==1.37 +opentelemetry-sdk==1.37 +opentelemetry-semantic-conventions==0.58b0 +opentelemetry-instrumentation==0.58b0 + +-e instrumentation-loongsuite/loongsuite-instrumentation-qwen-agent +-e util/opentelemetry-util-genai diff --git a/instrumentation-loongsuite/loongsuite-instrumentation-qwen-agent/tests/test_instrumentor.py b/instrumentation-loongsuite/loongsuite-instrumentation-qwen-agent/tests/test_instrumentor.py new file mode 100644 index 000000000..135b739b6 --- /dev/null +++ b/instrumentation-loongsuite/loongsuite-instrumentation-qwen-agent/tests/test_instrumentor.py @@ -0,0 +1,169 @@ +# Copyright The OpenTelemetry Authors +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +"""Tests for QwenAgentInstrumentor.""" + +from unittest.mock import MagicMock + +from qwen_agent.llm.schema import ContentItem, FunctionCall, Message + +from opentelemetry.instrumentation.qwen_agent import QwenAgentInstrumentor +from opentelemetry.instrumentation.qwen_agent.utils import ( + convert_qwen_messages_to_input_messages, + convert_qwen_messages_to_output_messages, + create_llm_invocation, + get_provider_name, +) +from opentelemetry.util.genai.types import ToolCall + + +class TestQwenAgentInstrumentor: + """Test the instrumentor lifecycle.""" + + def test_instrument_and_uninstrument(self, tracer_provider, logger_provider, meter_provider): + """Test that instrument/uninstrument works without errors.""" + instrumentor = QwenAgentInstrumentor() + instrumentor.instrument( + tracer_provider=tracer_provider, + logger_provider=logger_provider, + meter_provider=meter_provider, + skip_dep_check=True, + ) + assert instrumentor._handler is not None + instrumentor.uninstrument() + assert instrumentor._handler is None + + def test_instrumentation_dependencies(self): + """Test that dependencies are correctly specified.""" + instrumentor = QwenAgentInstrumentor() + deps = instrumentor.instrumentation_dependencies() + assert ("qwen-agent >= 0.0.20",) == deps + + +class TestProviderName: + """Test provider name detection.""" + + def test_dashscope_model_type(self): + llm = MagicMock() + llm.model_type = "qwen_dashscope" + assert get_provider_name(llm) == "dashscope" + + def test_oai_model_type(self): + llm = MagicMock() + llm.model_type = "oai" + assert get_provider_name(llm) == "openai" + + def test_unknown_model_type(self): + llm = MagicMock() + llm.model_type = "unknown_custom" + type(llm).__name__ = "CustomModel" + assert get_provider_name(llm) == "qwen_agent" + + def test_class_name_fallback_dashscope(self): + llm = MagicMock() + llm.model_type = "custom" + type(llm).__name__ = "QwenDashScopeChat" + assert get_provider_name(llm) == "dashscope" + + +class TestMessageConversion: + """Test qwen-agent message to GenAI type conversion.""" + + def test_convert_simple_user_message(self): + """Test converting a simple user text message.""" + messages = [Message(role="user", content="Hello")] + result = convert_qwen_messages_to_input_messages(messages) + assert len(result) == 1 + assert result[0].role == "user" + assert len(result[0].parts) == 1 + assert result[0].parts[0].content == "Hello" + + def test_convert_function_call_message(self): + """Test converting a message with function_call.""" + msg = Message( + role="assistant", + content="", + function_call=FunctionCall( + name="get_weather", + arguments='{"city": "Beijing"}', + ), + ) + result = convert_qwen_messages_to_output_messages([msg]) + assert len(result) == 1 + assert result[0].finish_reason == "tool_calls" + # Should have a ToolCall part + tool_calls = [p for p in result[0].parts if isinstance(p, ToolCall)] + assert len(tool_calls) == 1 + assert tool_calls[0].name == "get_weather" + + def test_convert_function_response_message(self): + """Test converting a function role message (tool result).""" + msg = Message(role="function", name="get_weather", content="Sunny, 25°C") + result = convert_qwen_messages_to_input_messages([msg]) + assert len(result) == 1 + assert result[0].role == "function" + + def test_convert_empty_messages(self): + """Test converting empty message list.""" + result = convert_qwen_messages_to_input_messages([]) + assert result == [] + + def test_convert_multimodal_content(self): + """Test converting message with ContentItem list.""" + msg = Message( + role="user", + content=[ContentItem(text="Describe this image")], + ) + result = convert_qwen_messages_to_input_messages([msg]) + assert len(result) == 1 + assert result[0].parts[0].content == "Describe this image" + + +class TestLLMInvocation: + """Test LLM invocation creation.""" + + def test_create_basic_invocation(self): + """Test creating a basic LLM invocation.""" + llm = MagicMock() + llm.model = "qwen-max" + llm.model_type = "qwen_dashscope" + + messages = [Message(role="user", content="Hi")] + invocation = create_llm_invocation(llm, messages) + + assert invocation.request_model == "qwen-max" + assert invocation.provider == "dashscope" + assert len(invocation.input_messages) == 1 + + def test_create_invocation_with_functions(self): + """Test creating invocation with tool definitions.""" + llm = MagicMock() + llm.model = "qwen-max" + llm.model_type = "qwen_dashscope" + + messages = [Message(role="user", content="What's the weather?")] + functions = [ + { + "name": "get_weather", + "description": "Get weather info", + "parameters": {"type": "object", "properties": {}}, + } + ] + invocation = create_llm_invocation(llm, messages, functions=functions) + + # P1 fix: tool_definitions are now FunctionToolDefinition objects on invocation.tool_definitions + assert len(invocation.tool_definitions) == 1 + tool_def = invocation.tool_definitions[0] + assert tool_def.name == "get_weather" + assert tool_def.description == "Get weather info" diff --git a/instrumentation-loongsuite/loongsuite-instrumentation-qwen-agent/tests/test_real_api.py b/instrumentation-loongsuite/loongsuite-instrumentation-qwen-agent/tests/test_real_api.py new file mode 100644 index 000000000..fb67ac4bc --- /dev/null +++ b/instrumentation-loongsuite/loongsuite-instrumentation-qwen-agent/tests/test_real_api.py @@ -0,0 +1,446 @@ +# Copyright The OpenTelemetry Authors +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +"""Integration tests for Qwen-Agent instrumentation using VCR cassettes. + +These tests use real qwen-agent calls that are recorded via VCR so subsequent +runs replay the HTTP interactions without hitting the real API. +""" + +import json +import os + +import pytest +from qwen_agent.agents import Assistant +from qwen_agent.llm import get_chat_model +from qwen_agent.tools.base import BaseTool, register_tool + +from opentelemetry.instrumentation.qwen_agent import QwenAgentInstrumentor +from opentelemetry.sdk._logs import LoggerProvider +from opentelemetry.sdk._logs.export import ( + InMemoryLogExporter, + SimpleLogRecordProcessor, +) +from opentelemetry.sdk.metrics import MeterProvider +from opentelemetry.sdk.metrics.export import InMemoryMetricReader +from opentelemetry.sdk.trace import TracerProvider +from opentelemetry.sdk.trace.export import SimpleSpanProcessor +from opentelemetry.sdk.trace.export.in_memory_span_exporter import ( + InMemorySpanExporter, +) +from opentelemetry.semconv._incubating.attributes import ( + gen_ai_attributes as GenAIAttributes, +) + +# cassette directory for this test module +VCR_CASSETTE_DIR = os.path.join(os.path.dirname(__file__), "cassettes") + + +def _make_providers(): + """Create fresh OTel providers for each test.""" + span_exporter = InMemorySpanExporter() + tracer_provider = TracerProvider() + tracer_provider.add_span_processor(SimpleSpanProcessor(span_exporter)) + + log_exporter = InMemoryLogExporter() + logger_provider = LoggerProvider() + logger_provider.add_log_record_processor( + SimpleLogRecordProcessor(log_exporter) + ) + + metric_reader = InMemoryMetricReader() + meter_provider = MeterProvider(metric_readers=[metric_reader]) + + return tracer_provider, span_exporter, logger_provider, log_exporter, meter_provider + + +@pytest.mark.vcr() +def test_qwen_agent_basic_run(): + """Test basic qwen-agent Assistant conversation. + + Verifies that: + - An invoke_agent span is produced + - A chat (LLM) span is produced as a child + - Both spans have the expected gen_ai.* attributes + """ + tracer_provider, span_exporter, logger_provider, log_exporter, meter_provider = _make_providers() + + instrumentor = QwenAgentInstrumentor() + instrumentor.instrument( + tracer_provider=tracer_provider, + logger_provider=logger_provider, + meter_provider=meter_provider, + skip_dep_check=True, + ) + + try: + bot = Assistant( + llm={"model": "qwen-max", "model_type": "qwen_dashscope"}, + name="TestAssistant", + ) + messages = [{"role": "user", "content": "Hello, what is 1+1?"}] + # Consume the generator to trigger all spans + list(bot.run(messages)) + finally: + instrumentor.uninstrument() + + spans = span_exporter.get_finished_spans() + assert len(spans) >= 2, f"Expected at least 2 spans, got {len(spans)}: {[s.name for s in spans]}" + + # Find invoke_agent span + agent_spans = [s for s in spans if "invoke_agent" in s.name] + assert len(agent_spans) >= 1, f"No invoke_agent span found in: {[s.name for s in spans]}" + agent_span = agent_spans[0] + assert agent_span.attributes.get(GenAIAttributes.GEN_AI_OPERATION_NAME) == "invoke_agent" + + # Find chat/LLM span + chat_spans = [s for s in spans if s.name.startswith("chat ")] + assert len(chat_spans) >= 1, f"No chat span found in: {[s.name for s in spans]}" + chat_span = chat_spans[0] + + # Verify key span attributes on the chat span + assert chat_span.attributes.get(GenAIAttributes.GEN_AI_OPERATION_NAME) == "chat" + assert chat_span.attributes.get(GenAIAttributes.GEN_AI_PROVIDER_NAME) == "dashscope" + assert chat_span.attributes.get(GenAIAttributes.GEN_AI_REQUEST_MODEL) == "qwen-max" + + # response_model_name fix: GEN_AI_RESPONSE_MODEL should now be populated + response_model = chat_span.attributes.get(GenAIAttributes.GEN_AI_RESPONSE_MODEL) + assert response_model is not None, "gen_ai.response.model should be set (P0 fix)" + + # finish_reasons fix: GEN_AI_RESPONSE_FINISH_REASONS should be populated + finish_reasons = chat_span.attributes.get(GenAIAttributes.GEN_AI_RESPONSE_FINISH_REASONS) + assert finish_reasons is not None, "gen_ai.response.finish_reasons should be set (P0 fix)" + + +@pytest.mark.vcr() +def test_qwen_agent_stream_llm_with_ttft(): + """Test streaming LLM call and verify TTFT (Time-to-First-Token) is recorded. + + Verifies that P2 fix (monotonic_first_token_s) is working: + - gen_ai.response.time_to_first_token attribute is recorded when available + """ + tracer_provider, span_exporter, logger_provider, log_exporter, meter_provider = _make_providers() + + instrumentor = QwenAgentInstrumentor() + instrumentor.instrument( + tracer_provider=tracer_provider, + logger_provider=logger_provider, + meter_provider=meter_provider, + skip_dep_check=True, + ) + + try: + llm = get_chat_model({"model": "qwen-max", "model_type": "qwen_dashscope"}) + messages = [{"role": "user", "content": "Say hello in one word."}] + # stream=True is the default; consume the iterator + list(llm.chat(messages=messages, stream=True)) + finally: + instrumentor.uninstrument() + + spans = span_exporter.get_finished_spans() + chat_spans = [s for s in spans if s.name.startswith("chat ")] + assert len(chat_spans) >= 1, f"No chat span found in: {[s.name for s in spans]}" + chat_span = chat_spans[0] + + # Verify basic span attributes + assert chat_span.attributes.get(GenAIAttributes.GEN_AI_OPERATION_NAME) == "chat" + assert chat_span.attributes.get(GenAIAttributes.GEN_AI_PROVIDER_NAME) == "dashscope" + assert chat_span.attributes.get(GenAIAttributes.GEN_AI_REQUEST_MODEL) == "qwen-max" + + # TTFT (gen_ai.response.time_to_first_token) may be None during cassette replay; + # we assert finish_reasons to ensure the P2 code path ran. + finish_reasons = chat_span.attributes.get(GenAIAttributes.GEN_AI_RESPONSE_FINISH_REASONS) + assert finish_reasons is not None, "gen_ai.response.finish_reasons should be set (P0 fix)" + + +@pytest.mark.vcr() +def test_non_stream_chat(): + """Test non-streaming LLM chat call (stream=False code path). + + Verifies the else-branch in wrap_chat_model_chat: + - chat span is produced + - response_model and finish_reasons are set (P0 fix) + - no streaming wrapper is used + """ + tracer_provider, span_exporter, logger_provider, log_exporter, meter_provider = _make_providers() + + instrumentor = QwenAgentInstrumentor() + instrumentor.instrument( + tracer_provider=tracer_provider, + logger_provider=logger_provider, + meter_provider=meter_provider, + skip_dep_check=True, + ) + + try: + # use_raw_api=False forces the non-streaming code path; newer qwen-agent + # versions default use_raw_api=True for qwen_dashscope which only supports stream=True. + llm = get_chat_model({ + "model": "qwen-max", + "model_type": "qwen_dashscope", + "generate_cfg": {"use_raw_api": False}, + }) + messages = [{"role": "user", "content": "What is 2+2? Answer with just the number."}] + list(llm.chat(messages=messages, stream=False)) + finally: + instrumentor.uninstrument() + + spans = span_exporter.get_finished_spans() + chat_spans = [s for s in spans if s.name.startswith("chat ")] + assert len(chat_spans) >= 1, f"Expected at least 1 chat span, got: {[s.name for s in spans]}" + chat_span = chat_spans[0] + + assert chat_span.attributes.get(GenAIAttributes.GEN_AI_OPERATION_NAME) == "chat" + assert chat_span.attributes.get(GenAIAttributes.GEN_AI_PROVIDER_NAME) == "dashscope" + assert chat_span.attributes.get(GenAIAttributes.GEN_AI_REQUEST_MODEL) == "qwen-max" + + response_model = chat_span.attributes.get(GenAIAttributes.GEN_AI_RESPONSE_MODEL) + assert response_model is not None, "gen_ai.response.model should be set for non-stream (P0 fix)" + + finish_reasons = chat_span.attributes.get(GenAIAttributes.GEN_AI_RESPONSE_FINISH_REASONS) + assert finish_reasons is not None, "gen_ai.response.finish_reasons should be set for non-stream (P0 fix)" + + +@pytest.mark.vcr() +def test_agent_run_nonstream(): + """Test Agent.run_nonstream() produces a single invoke_agent span. + + run_nonstream() is not wrapped separately — it calls self.run() internally, + so the invoke_agent span is created once by the run() wrapper. + Verifies there is no span duplication when using the non-streaming entry point. + """ + tracer_provider, span_exporter, logger_provider, log_exporter, meter_provider = _make_providers() + + instrumentor = QwenAgentInstrumentor() + instrumentor.instrument( + tracer_provider=tracer_provider, + logger_provider=logger_provider, + meter_provider=meter_provider, + skip_dep_check=True, + ) + + try: + bot = Assistant( + llm={"model": "qwen-max", "model_type": "qwen_dashscope"}, + name="NonStreamAssistant", + ) + messages = [{"role": "user", "content": "Say 'OK' and nothing else."}] + bot.run_nonstream(messages) + finally: + instrumentor.uninstrument() + + spans = span_exporter.get_finished_spans() + # Assistant may spawn a Memory sub-agent producing extra invoke_agent spans; + # filter to the target agent by name. + agent_spans = [s for s in spans if s.name == "invoke_agent NonStreamAssistant"] + assert len(agent_spans) >= 1, f"Expected invoke_agent NonStreamAssistant span, got: {[s.name for s in spans]}" + agent_span = agent_spans[0] + assert agent_span.attributes.get(GenAIAttributes.GEN_AI_OPERATION_NAME) == "invoke_agent" + + chat_spans = [s for s in spans if s.name.startswith("chat ")] + assert len(chat_spans) >= 1, f"No chat span found in: {[s.name for s in spans]}" + + +@pytest.mark.vcr() +def test_multi_turn_conversation(): + """Test multi-turn conversation with history messages. + + Verifies that all input messages (user + assistant history) are correctly + captured in the span event log, not just the last message. + """ + tracer_provider, span_exporter, logger_provider, log_exporter, meter_provider = _make_providers() + + instrumentor = QwenAgentInstrumentor() + instrumentor.instrument( + tracer_provider=tracer_provider, + logger_provider=logger_provider, + meter_provider=meter_provider, + skip_dep_check=True, + ) + + try: + bot = Assistant( + llm={"model": "qwen-max", "model_type": "qwen_dashscope"}, + name="MultiTurnAssistant", + ) + # Simulate a 2-turn conversation by including history + messages = [ + {"role": "user", "content": "My name is Alice."}, + {"role": "assistant", "content": "Nice to meet you, Alice!"}, + {"role": "user", "content": "What is my name?"}, + ] + list(bot.run(messages)) + finally: + instrumentor.uninstrument() + + spans = span_exporter.get_finished_spans() + # Filter to our specific agent; Assistant may produce extra Memory sub-agent spans. + agent_spans = [s for s in spans if s.name == "invoke_agent MultiTurnAssistant"] + assert len(agent_spans) >= 1, f"Expected invoke_agent MultiTurnAssistant span in: {[s.name for s in spans]}" + + chat_spans = [s for s in spans if s.name.startswith("chat ")] + assert len(chat_spans) >= 1, f"No chat span found in: {[s.name for s in spans]}" + chat_span = chat_spans[0] + + assert chat_span.attributes.get(GenAIAttributes.GEN_AI_REQUEST_MODEL) == "qwen-max" + finish_reasons = chat_span.attributes.get(GenAIAttributes.GEN_AI_RESPONSE_FINISH_REASONS) + assert finish_reasons is not None, "gen_ai.response.finish_reasons should be set" + + +@pytest.mark.vcr() +def test_react_multi_round(): + """Test ReAct agent completing a multi-round task via tool calls. + + Verifies the react_step span introduced for ReAct tracking: + - react_step spans appear when the agent has tools + - gen_ai.react.round attribute increments per iteration + - chat and execute_tool spans are nested inside react_step + """ + tracer_provider, span_exporter, logger_provider, log_exporter, meter_provider = _make_providers() + + instrumentor = QwenAgentInstrumentor() + instrumentor.instrument( + tracer_provider=tracer_provider, + logger_provider=logger_provider, + meter_provider=meter_provider, + skip_dep_check=True, + ) + + try: + @register_tool("calculator_react_test") + class CalculatorTool(BaseTool): + description = "Evaluate a simple arithmetic expression and return the numeric result." + parameters = [ + { + "name": "expression", + "type": "string", + "description": "The arithmetic expression to evaluate, e.g. '3 * 7'.", + "required": True, + } + ] + + def call(self, params, **kwargs): + if isinstance(params, str): + try: + params = json.loads(params) + except Exception: + params = {"expression": params} + expr = params.get("expression", "0") + try: + return str(eval(expr, {"__builtins__": {}}, {})) # noqa: S307 + except Exception as e: + return f"Error: {e}" + + bot = Assistant( + llm={"model": "qwen-max", "model_type": "qwen_dashscope"}, + name="ReactAgent", + function_list=["calculator_react_test"], + ) + messages = [{"role": "user", "content": "What is 6 multiplied by 7?"}] + list(bot.run(messages)) + finally: + instrumentor.uninstrument() + + spans = span_exporter.get_finished_spans() + span_names = [s.name for s in spans] + + # Filter to our specific agent; Assistant may produce extra Memory sub-agent spans. + agent_spans = [s for s in spans if s.name == "invoke_agent ReactAgent"] + assert len(agent_spans) >= 1, f"Expected invoke_agent ReactAgent span in: {span_names}" + + # "react step" spans must appear (agent has tools → ReAct mode) + react_spans = [s for s in spans if s.name == "react step"] + assert len(react_spans) >= 1, ( + f"Expected 'react step' spans for a tool-enabled agent, got none. All spans: {span_names}" + ) + + # gen_ai.react.round attribute must be set and start at 1 + rounds = [s.attributes.get("gen_ai.react.round") for s in react_spans] + assert 1 in rounds, f"Expected gen_ai.react.round=1 in react step spans, got rounds={rounds}" + + # chat spans must exist inside react step (nested via OTel context) + chat_spans = [s for s in spans if s.name.startswith("chat ")] + assert len(chat_spans) >= 1, f"No chat span in: {span_names}" + + +@pytest.mark.vcr() +def test_qwen_agent_with_tool_call(): + """Test qwen-agent with tools, verify execute_tool span is produced. + + Uses a custom BaseTool subclass (can be passed directly to Assistant + without TOOL_REGISTRY registration) to exercise the tool_definitions P1 fix + and verify execute_tool spans are generated when the model calls a tool. + """ + tracer_provider, span_exporter, logger_provider, log_exporter, meter_provider = _make_providers() + + instrumentor = QwenAgentInstrumentor() + instrumentor.instrument( + tracer_provider=tracer_provider, + logger_provider=logger_provider, + meter_provider=meter_provider, + skip_dep_check=True, + ) + + try: + @register_tool("get_current_weather_test") + class GetCurrentWeatherTool(BaseTool): + description = "Get the current weather for a given city." + parameters = [ + { + "name": "city", + "type": "string", + "description": "The city name to get weather for.", + "required": True, + } + ] + + def call(self, params, **kwargs): + if isinstance(params, str): + try: + params = json.loads(params) + except Exception: + params = {"city": params} + city = params.get("city", "unknown") if isinstance(params, dict) else "unknown" + return f"The weather in {city} is sunny and 22 degrees Celsius." + + bot = Assistant( + llm={"model": "qwen-max", "model_type": "qwen_dashscope"}, + name="WeatherAgent", + function_list=["get_current_weather_test"], + ) + messages = [{"role": "user", "content": "What is the weather in Beijing right now?"}] + list(bot.run(messages)) + finally: + instrumentor.uninstrument() + + spans = span_exporter.get_finished_spans() + span_names = [s.name for s in spans] + + # Verify we got invoke_agent and chat spans + agent_spans = [s for s in spans if "invoke_agent" in s.name] + assert len(agent_spans) >= 1, f"No invoke_agent span in: {span_names}" + + chat_spans = [s for s in spans if s.name.startswith("chat ")] + assert len(chat_spans) >= 1, f"No chat span in: {span_names}" + + # Verify chat span attributes + chat_span = chat_spans[0] + assert chat_span.attributes.get(GenAIAttributes.GEN_AI_OPERATION_NAME) == "chat" + assert chat_span.attributes.get(GenAIAttributes.GEN_AI_PROVIDER_NAME) == "dashscope" + + # If the model called the tool, there should be an execute_tool span + tool_spans = [s for s in spans if "execute_tool" in s.name] + # Tool call is model-dependent; only assert if tool spans exist + for tool_span in tool_spans: + assert tool_span.attributes.get(GenAIAttributes.GEN_AI_OPERATION_NAME) == "execute_tool" diff --git a/instrumentation-loongsuite/loongsuite-instrumentation-qwen-agent/tests/test_spans.py b/instrumentation-loongsuite/loongsuite-instrumentation-qwen-agent/tests/test_spans.py new file mode 100644 index 000000000..8230efd4f --- /dev/null +++ b/instrumentation-loongsuite/loongsuite-instrumentation-qwen-agent/tests/test_spans.py @@ -0,0 +1,722 @@ +# Copyright The OpenTelemetry Authors +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +"""Integration tests for span generation from the qwen-agent instrumentation plugin. + +Tests verify that the instrumented methods produce correct OpenTelemetry spans +with the expected names, kinds, and attributes. +""" + +from unittest.mock import MagicMock, patch + +import pytest +from qwen_agent.agent import Agent +from qwen_agent.llm.base import BaseChatModel +from qwen_agent.llm.schema import ContentItem, FunctionCall, Message + +from opentelemetry.semconv._incubating.attributes import ( + gen_ai_attributes as GenAIAttributes, +) +from opentelemetry.trace import SpanKind, StatusCode + +# --------------------------------------------------------------------------- +# Helpers: minimal concrete subclasses of the abstract qwen-agent classes +# --------------------------------------------------------------------------- + + +class _StubChatModel(BaseChatModel): + """A minimal BaseChatModel subclass for testing. + + The real BaseChatModel.__init__ reads from a cfg dict; we bypass most of + that logic by calling super().__init__ with a minimal config and then + overriding the attributes we care about. + """ + + def __init__(self, model="test-model", model_type="qwen_dashscope"): + cfg = {"model": model, "model_type": model_type} + super().__init__(cfg) + # Disable raw_api mode which requires stream-only and API key + self.use_raw_api = False + + # Abstract methods required by BaseChatModel + def _chat_no_stream(self, messages, **kwargs): + raise NotImplementedError + + def _chat_stream(self, messages, **kwargs): + raise NotImplementedError + + def _chat_with_functions(self, messages, functions, **kwargs): + raise NotImplementedError + + +class _StubAgent(Agent): + """A minimal Agent subclass for testing. + + Agent.__init__ normally requires complex setup; we use ``__new__`` and + manually assign the attributes the instrumentation reads so that we can + test the wrapped methods without triggering real agent initialization. + """ + + @classmethod + def create(cls, name="TestAgent", llm=None): + """Factory that skips the heavy __init__.""" + obj = cls.__new__(cls) + obj.name = name + obj.description = "A test agent" + obj.system_message = "You are a helpful assistant." + obj.llm = llm + obj.function_map = {} + obj.extra_generate_cfg = {} + return obj + + # Abstract method required by Agent + def _run(self, messages, **kwargs): + raise NotImplementedError + + +# --------------------------------------------------------------------------- +# LLM chat span tests +# --------------------------------------------------------------------------- + + +class TestLLMChatSpan: + """Verify that BaseChatModel.chat() produces a correct LLM (chat) span.""" + + def test_non_stream_chat_creates_span(self, span_exporter, instrument): + """Non-streaming chat() should create a single chat span with model info.""" + model = _StubChatModel(model="qwen-max", model_type="qwen_dashscope") + + fake_response = [Message(role="assistant", content="Hello there!")] + + with patch.object( + _StubChatModel, + "_chat_no_stream", + return_value=fake_response, + ): + result = model.chat( + messages=[Message(role="user", content="Hi")], + stream=False, + ) + + assert result is not None + + spans = span_exporter.get_finished_spans() + chat_spans = [s for s in spans if s.name.startswith("chat")] + assert len(chat_spans) >= 1, f"Expected a chat span, got: {[s.name for s in spans]}" + + span = chat_spans[0] + assert span.name == "chat qwen-max" + assert span.kind == SpanKind.CLIENT + attrs = dict(span.attributes or {}) + assert attrs.get(GenAIAttributes.GEN_AI_REQUEST_MODEL) == "qwen-max" + # Provider name is stored as "gen_ai.provider.name" in newer semconv + provider = attrs.get("gen_ai.provider.name") or attrs.get(GenAIAttributes.GEN_AI_SYSTEM) + assert provider == "dashscope", f"Expected 'dashscope', got attrs: {attrs}" + + def test_stream_chat_creates_span(self, span_exporter, instrument): + """Streaming chat() should create a chat span after the iterator is consumed.""" + model = _StubChatModel(model="qwen-turbo", model_type="qwen_dashscope") + + chunk1 = [Message(role="assistant", content="Hello")] + chunk2 = [Message(role="assistant", content="Hello world")] + + def fake_stream(messages, **kwargs): + yield chunk1 + yield chunk2 + + with patch.object( + _StubChatModel, + "_chat_stream", + side_effect=fake_stream, + ): + response_iter = model.chat( + messages=[Message(role="user", content="Hi")], + stream=True, + ) + # Consume the iterator to trigger span completion + responses = list(response_iter) + + assert len(responses) == 2 + + spans = span_exporter.get_finished_spans() + chat_spans = [s for s in spans if s.name.startswith("chat")] + assert len(chat_spans) >= 1 + span = chat_spans[0] + assert span.name == "chat qwen-turbo" + assert span.kind == SpanKind.CLIENT + + def test_chat_with_function_call_response(self, span_exporter, instrument): + """Chat response containing a function_call should still produce a valid span.""" + model = _StubChatModel(model="qwen-max", model_type="qwen_dashscope") + + fake_response = [ + Message( + role="assistant", + content="", + function_call=FunctionCall( + name="get_weather", + arguments='{"city": "Beijing"}', + ), + ) + ] + + with patch.object( + _StubChatModel, + "_chat_no_stream", + return_value=fake_response, + ): + model.chat( + messages=[Message(role="user", content="What is the weather?")], + stream=False, + ) + + spans = span_exporter.get_finished_spans() + chat_spans = [s for s in spans if s.name.startswith("chat")] + assert len(chat_spans) >= 1 + + def test_chat_error_creates_error_span(self, span_exporter, instrument): + """An exception during chat() should still produce a span with error status.""" + model = _StubChatModel(model="qwen-max", model_type="qwen_dashscope") + + with patch.object( + _StubChatModel, + "_chat_no_stream", + side_effect=RuntimeError("API timeout"), + ): + with pytest.raises(RuntimeError, match="API timeout"): + model.chat( + messages=[Message(role="user", content="Hi")], + stream=False, + ) + + spans = span_exporter.get_finished_spans() + chat_spans = [s for s in spans if s.name.startswith("chat")] + assert len(chat_spans) >= 1 + span = chat_spans[0] + assert span.status.status_code == StatusCode.ERROR + + +# --------------------------------------------------------------------------- +# Agent run span tests +# --------------------------------------------------------------------------- + + +class TestAgentRunSpan: + """Verify that Agent.run() and run_nonstream() produce invoke_agent spans.""" + + def test_agent_run_creates_invoke_agent_span(self, span_exporter, instrument): + """Agent.run() (generator) should create an invoke_agent span.""" + llm = MagicMock() + llm.model = "qwen-max" + llm.model_type = "qwen_dashscope" + + agent = _StubAgent.create(name="WeatherBot", llm=llm) + + response_msgs = [Message(role="assistant", content="It is sunny.")] + + def fake_run(messages, **kwargs): + yield response_msgs + + with patch.object(_StubAgent, "_run", side_effect=fake_run): + results = list(agent.run([Message(role="user", content="Weather?")])) + + assert len(results) >= 1 + + spans = span_exporter.get_finished_spans() + agent_spans = [s for s in spans if "invoke_agent" in s.name] + assert len(agent_spans) >= 1, f"Expected invoke_agent span, got: {[s.name for s in spans]}" + + span = agent_spans[0] + assert span.name == "invoke_agent WeatherBot" + assert span.kind == SpanKind.INTERNAL + + def test_agent_run_nonstream_creates_invoke_agent_span( + self, span_exporter, instrument + ): + """Agent.run_nonstream() should produce exactly one invoke_agent span. + + run_nonstream is NOT wrapped separately — it calls self.run() internally, + so the single invoke_agent span comes from the run() wrapper. + """ + llm = MagicMock() + llm.model = "qwen-max" + llm.model_type = "qwen_dashscope" + + agent = _StubAgent.create(name="ChatBot", llm=llm) + + response_msgs = [Message(role="assistant", content="Hello!")] + + def fake_run(messages, **kwargs): + yield response_msgs + + with patch.object(_StubAgent, "_run", side_effect=fake_run): + result = agent.run_nonstream([Message(role="user", content="Hi")]) + + assert result is not None + + spans = span_exporter.get_finished_spans() + agent_spans = [s for s in spans if "invoke_agent" in s.name] + # run_nonstream is not wrapped; only run() creates the invoke_agent span. + # Exactly one span should be produced (no duplication). + assert len(agent_spans) == 1 + span_names = [s.name for s in agent_spans] + assert any("ChatBot" in n for n in span_names) + + def test_agent_run_error_creates_error_span(self, span_exporter, instrument): + """An exception during Agent.run() should produce an error invoke_agent span.""" + llm = MagicMock() + llm.model = "qwen-max" + llm.model_type = "qwen_dashscope" + + agent = _StubAgent.create(name="FailBot", llm=llm) + + def fake_run(messages, **kwargs): + if False: + yield # make it a generator + raise ValueError("Agent processing failed") + + with patch.object(_StubAgent, "_run", side_effect=fake_run): + with pytest.raises(ValueError, match="Agent processing failed"): + list(agent.run([Message(role="user", content="Go")])) + + spans = span_exporter.get_finished_spans() + agent_spans = [s for s in spans if "invoke_agent" in s.name] + assert len(agent_spans) >= 1 + span = agent_spans[0] + assert span.status.status_code == StatusCode.ERROR + + def test_agent_run_multiple_yields(self, span_exporter, instrument): + """Agent.run() yielding multiple times should produce one invoke_agent span.""" + llm = MagicMock() + llm.model = "qwen-max" + llm.model_type = "qwen_dashscope" + + agent = _StubAgent.create(name="MultiYieldBot", llm=llm) + + def fake_run(messages, **kwargs): + yield [Message(role="assistant", content="Thinking...")] + yield [Message(role="assistant", content="Done!")] + + with patch.object(_StubAgent, "_run", side_effect=fake_run): + results = list(agent.run([Message(role="user", content="Go")])) + + assert len(results) == 2 + + spans = span_exporter.get_finished_spans() + agent_spans = [s for s in spans if "invoke_agent" in s.name] + # The wrapper should produce exactly one span per run() call + assert len(agent_spans) == 1 + + +# --------------------------------------------------------------------------- +# Tool call span tests +# --------------------------------------------------------------------------- + + +class TestToolCallSpan: + """Verify that Agent._call_tool() produces an execute_tool span.""" + + def _make_agent_with_tool(self, tool_name="get_weather"): + """Create a stub agent with a tool in its function_map.""" + agent = _StubAgent.create(name="ToolAgent") + + mock_tool = MagicMock() + mock_tool.description = "Get weather information" + mock_tool.call = MagicMock(return_value="Sunny, 25 degrees") + agent.function_map = {tool_name: mock_tool} + return agent, mock_tool + + def test_call_tool_creates_execute_tool_span(self, span_exporter, instrument): + """_call_tool() should create an execute_tool span with tool name.""" + agent, mock_tool = self._make_agent_with_tool("get_weather") + + result = agent._call_tool("get_weather", '{"city": "Beijing"}') + + assert result == "Sunny, 25 degrees" + + spans = span_exporter.get_finished_spans() + tool_spans = [s for s in spans if "execute_tool" in s.name] + assert len(tool_spans) >= 1, f"Expected execute_tool span, got: {[s.name for s in spans]}" + + span = tool_spans[0] + assert span.name == "execute_tool get_weather" + assert span.kind == SpanKind.INTERNAL + + def test_call_tool_with_dict_args(self, span_exporter, instrument): + """_call_tool() should handle dict arguments.""" + agent, mock_tool = self._make_agent_with_tool("search") + mock_tool.call = MagicMock(return_value="Found 3 results") + + result = agent._call_tool("search", {"query": "OpenTelemetry"}) + + assert result == "Found 3 results" + + spans = span_exporter.get_finished_spans() + tool_spans = [s for s in spans if "execute_tool" in s.name] + assert len(tool_spans) >= 1 + assert tool_spans[0].name == "execute_tool search" + + def test_call_tool_error_creates_span(self, span_exporter, instrument): + """An exception in _call_tool() should still produce an execute_tool span. + + Note: qwen-agent's Agent._call_tool() catches tool exceptions internally + and returns an error string rather than re-raising. + """ + agent, mock_tool = self._make_agent_with_tool("broken_tool") + mock_tool.call = MagicMock(side_effect=RuntimeError("Tool crashed")) + + # qwen-agent catches the exception and returns an error string + result = agent._call_tool("broken_tool", "{}") + assert isinstance(result, str) + + spans = span_exporter.get_finished_spans() + tool_spans = [s for s in spans if "execute_tool" in s.name] + assert len(tool_spans) >= 1 + assert tool_spans[0].name == "execute_tool broken_tool" + + def test_call_tool_returns_content_items(self, span_exporter, instrument): + """_call_tool() returning List[ContentItem] should still create a valid span.""" + agent, mock_tool = self._make_agent_with_tool("image_gen") + mock_tool.call = MagicMock( + return_value=[ContentItem(text="Generated image description")] + ) + + result = agent._call_tool("image_gen", '{"prompt": "a cat"}') + + assert isinstance(result, list) + + spans = span_exporter.get_finished_spans() + tool_spans = [s for s in spans if "execute_tool" in s.name] + assert len(tool_spans) >= 1 + assert tool_spans[0].name == "execute_tool image_gen" + + def test_call_unknown_tool_no_crash(self, span_exporter, instrument): + """Calling a tool not in function_map should still produce a span without crashing.""" + agent = _StubAgent.create(name="ToolAgent") + agent.function_map = {} + + # The real Agent._call_tool returns an error string for unknown tools + result = agent._call_tool("nonexistent", "{}") + + assert "does not exist" in result.lower() or isinstance(result, str) + + spans = span_exporter.get_finished_spans() + tool_spans = [s for s in spans if "execute_tool" in s.name] + assert len(tool_spans) >= 1 + + +# --------------------------------------------------------------------------- +# Span hierarchy / parent-child tests +# --------------------------------------------------------------------------- + + +class TestSpanHierarchy: + """Verify that spans are correctly nested when operations are composed.""" + + def test_agent_run_with_llm_call_produces_nested_spans( + self, span_exporter, instrument + ): + """When an agent run internally calls LLM chat, spans should be nested.""" + model = _StubChatModel(model="qwen-max", model_type="qwen_dashscope") + agent = _StubAgent.create(name="NestBot", llm=model) + + llm_response = [Message(role="assistant", content="The answer is 42.")] + + def fake_run(messages, **kwargs): + # Simulate the agent calling LLM internally + with patch.object( + _StubChatModel, + "_chat_no_stream", + return_value=llm_response, + ): + agent.llm.chat(messages=messages, stream=False) + yield [Message(role="assistant", content="The answer is 42.")] + + with patch.object(_StubAgent, "_run", side_effect=fake_run): + list(agent.run([Message(role="user", content="What is 6*7?")])) + + spans = span_exporter.get_finished_spans() + agent_spans = [s for s in spans if "invoke_agent" in s.name] + chat_spans = [s for s in spans if s.name.startswith("chat")] + + assert len(agent_spans) >= 1 + assert len(chat_spans) >= 1 + + # The chat span should be a child of the agent span + agent_span = agent_spans[0] + chat_span = chat_spans[0] + assert chat_span.context.trace_id == agent_span.context.trace_id + assert chat_span.parent is not None + assert chat_span.parent.span_id == agent_span.context.span_id + + def test_agent_run_with_tool_call_produces_nested_spans( + self, span_exporter, instrument + ): + """When an agent run internally calls a tool, spans should be nested.""" + agent = _StubAgent.create(name="ToolNestBot") + + mock_tool = MagicMock() + mock_tool.description = "Calculator tool" + mock_tool.call = MagicMock(return_value="42") + agent.function_map = {"calculator": mock_tool} + + def fake_run(messages, **kwargs): + # Simulate the agent calling a tool internally + agent._call_tool("calculator", '{"expr": "6*7"}') + yield [Message(role="assistant", content="The result is 42.")] + + with patch.object(_StubAgent, "_run", side_effect=fake_run): + list(agent.run([Message(role="user", content="Calculate 6*7")])) + + spans = span_exporter.get_finished_spans() + agent_spans = [s for s in spans if "invoke_agent" in s.name] + tool_spans = [s for s in spans if "execute_tool" in s.name] + + assert len(agent_spans) >= 1 + assert len(tool_spans) >= 1 + + agent_span = agent_spans[0] + tool_span = tool_spans[0] + assert tool_span.context.trace_id == agent_span.context.trace_id + assert tool_span.parent is not None + assert tool_span.parent.span_id == agent_span.context.span_id + + +# --------------------------------------------------------------------------- +# ReAct Step span tests +# --------------------------------------------------------------------------- + + +class TestReactStepSpan: + """Verify that react_step spans are created for ReAct agents with tools, + and NOT created for agents without tools.""" + + def test_react_agent_with_tools_creates_react_step_spans( + self, span_exporter, instrument + ): + """FnCallAgent-like agent with tools: each _call_llm round should + produce a react_step span.""" + model = _StubChatModel(model="qwen-max", model_type="qwen_dashscope") + agent = _StubAgent.create(name="ReactBot", llm=model) + + # Give the agent a tool -> react mode ON + mock_tool = MagicMock() + mock_tool.description = "Calculator" + mock_tool.call = MagicMock(return_value="42") + agent.function_map = {"calculator": mock_tool} + + # Simulate 2-round ReAct: LLM -> tool -> LLM -> done + call_count = [0] + + def fake_run(messages, **kwargs): + # Round 1: LLM decides to call tool + call_count[0] += 1 + with patch.object( + _StubChatModel, + "_chat_no_stream", + return_value=[ + Message( + role="assistant", + content="", + function_call=FunctionCall( + name="calculator", + arguments='{"expr": "6*7"}', + ), + ) + ], + ): + # This calls _call_llm internally -> react_step 1 + agent._call_llm(messages=messages, functions=[], stream=False) + + # Tool call (inside react_step 1 context) + agent._call_tool("calculator", '{"expr": "6*7"}') + + # Round 2: LLM summarizes (react_step 2) + call_count[0] += 1 + with patch.object( + _StubChatModel, + "_chat_no_stream", + return_value=[ + Message(role="assistant", content="The result is 42.") + ], + ): + agent._call_llm(messages=messages, functions=[], stream=False) + + yield [Message(role="assistant", content="The result is 42.")] + + with patch.object(_StubAgent, "_run", side_effect=fake_run): + list(agent.run([Message(role="user", content="Calculate 6*7")])) + + spans = span_exporter.get_finished_spans() + react_spans = [s for s in spans if "react step" in s.name] + agent_spans = [s for s in spans if "invoke_agent" in s.name] + chat_spans = [s for s in spans if s.name.startswith("chat")] + tool_spans = [s for s in spans if "execute_tool" in s.name] + + # Should have exactly 2 react_step spans + assert len(react_spans) == 2, ( + f"Expected 2 react_step spans, got {len(react_spans)}: " + f"{[s.name for s in spans]}" + ) + + # react_step spans should be children of invoke_agent + agent_span = agent_spans[0] + for rs in react_spans: + assert rs.parent is not None + assert rs.parent.span_id == agent_span.context.span_id + + # chat spans should be children of react_step (not directly of invoke_agent) + for cs in chat_spans: + assert cs.parent is not None + parent_is_react = any( + cs.parent.span_id == rs.context.span_id for rs in react_spans + ) + assert parent_is_react, ( + f"chat span parent should be a react_step, " + f"not {cs.parent.span_id}" + ) + + # tool span should be child of react_step 1 (the first one) + assert len(tool_spans) >= 1 + tool_span = tool_spans[0] + assert tool_span.parent is not None + assert tool_span.parent.span_id == react_spans[0].context.span_id + + def test_agent_without_tools_no_react_step_spans( + self, span_exporter, instrument + ): + """Agent WITHOUT tools: no react_step spans should be created, + even though _call_llm is wrapped.""" + model = _StubChatModel(model="qwen-max", model_type="qwen_dashscope") + agent = _StubAgent.create(name="SimpleBot", llm=model) + agent.function_map = {} # No tools -> react mode OFF + + def fake_run(messages, **kwargs): + with patch.object( + _StubChatModel, + "_chat_no_stream", + return_value=[ + Message(role="assistant", content="Hello!") + ], + ): + agent._call_llm(messages=messages, stream=False) + yield [Message(role="assistant", content="Hello!")] + + with patch.object(_StubAgent, "_run", side_effect=fake_run): + list(agent.run([Message(role="user", content="Hi")])) + + spans = span_exporter.get_finished_spans() + react_spans = [s for s in spans if "react step" in s.name] + agent_spans = [s for s in spans if "invoke_agent" in s.name] + chat_spans = [s for s in spans if s.name.startswith("chat")] + + # NO react_step spans + assert len(react_spans) == 0, ( + f"Expected 0 react_step spans for no-tool agent, " + f"got {len(react_spans)}: {[s.name for s in spans]}" + ) + + # invoke_agent and chat should still work normally + assert len(agent_spans) >= 1 + assert len(chat_spans) >= 1 + + # chat should be direct child of invoke_agent (no react_step in between) + chat_span = chat_spans[0] + assert chat_span.parent is not None + assert chat_span.parent.span_id == agent_spans[0].context.span_id + + def test_single_round_react_agent_creates_one_step( + self, span_exporter, instrument + ): + """Agent WITH tools but LLM answers directly (no tool call): + should create exactly 1 react_step span (step=1).""" + model = _StubChatModel(model="qwen-max", model_type="qwen_dashscope") + agent = _StubAgent.create(name="DirectBot", llm=model) + + mock_tool = MagicMock() + mock_tool.description = "Unused tool" + agent.function_map = {"unused_tool": mock_tool} + + def fake_run(messages, **kwargs): + # LLM answers directly, no tool call + with patch.object( + _StubChatModel, + "_chat_no_stream", + return_value=[ + Message(role="assistant", content="I know the answer: 42.") + ], + ): + agent._call_llm(messages=messages, functions=[], stream=False) + yield [Message(role="assistant", content="I know the answer: 42.")] + + with patch.object(_StubAgent, "_run", side_effect=fake_run): + list(agent.run([Message(role="user", content="What is 42?")])) + + spans = span_exporter.get_finished_spans() + react_spans = [s for s in spans if "react step" in s.name] + + # Exactly 1 react_step (agent had tools, so react mode was on) + assert len(react_spans) == 1 + + def test_react_step_does_not_leak_across_runs( + self, span_exporter, instrument + ): + """Running an agent WITH tools, then an agent WITHOUT tools: + the second run should NOT have react_step spans.""" + model = _StubChatModel(model="qwen-max", model_type="qwen_dashscope") + + # Run 1: agent with tools + agent1 = _StubAgent.create(name="ToolBot", llm=model) + mock_tool = MagicMock() + mock_tool.description = "Tool" + mock_tool.call = MagicMock(return_value="ok") + agent1.function_map = {"tool1": mock_tool} + + def fake_run_1(messages, **kwargs): + with patch.object( + _StubChatModel, + "_chat_no_stream", + return_value=[Message(role="assistant", content="Done")], + ): + agent1._call_llm(messages=messages, functions=[], stream=False) + yield [Message(role="assistant", content="Done")] + + with patch.object(_StubAgent, "_run", side_effect=fake_run_1): + list(agent1.run([Message(role="user", content="Go")])) + + spans_after_run1 = span_exporter.get_finished_spans() + react_spans_1 = [s for s in spans_after_run1 if "react step" in s.name] + assert len(react_spans_1) == 1 # Tool agent had react_step + + span_exporter.clear() + + # Run 2: agent WITHOUT tools + agent2 = _StubAgent.create(name="PlainBot", llm=model) + agent2.function_map = {} + + def fake_run_2(messages, **kwargs): + with patch.object( + _StubChatModel, + "_chat_no_stream", + return_value=[Message(role="assistant", content="Hi")], + ): + agent2._call_llm(messages=messages, stream=False) + yield [Message(role="assistant", content="Hi")] + + with patch.object(_StubAgent, "_run", side_effect=fake_run_2): + list(agent2.run([Message(role="user", content="Hello")])) + + spans_after_run2 = span_exporter.get_finished_spans() + react_spans_2 = [s for s in spans_after_run2 if "react step" in s.name] + assert len(react_spans_2) == 0 # No tool -> no react_step diff --git a/tox-loongsuite.ini b/tox-loongsuite.ini index d146667fe..f83a1ec33 100644 --- a/tox-loongsuite.ini +++ b/tox-loongsuite.ini @@ -44,6 +44,10 @@ envlist = py3{9,10,11,12,13}-test-loongsuite-instrumentation-langgraph-{oldest,latest} lint-loongsuite-instrumentation-langgraph + ; loongsuite-instrumentation-qwen-agent + py3{9,10,11,12,13}-test-loongsuite-instrumentation-qwen-agent-{oldest,latest} + lint-loongsuite-instrumentation-qwen-agent + ; ; loongsuite-instrumentation-mcp ; py3{9,10,11,12,13}-test-loongsuite-instrumentation-mcp ; lint-loongsuite-instrumentation-mcp @@ -118,6 +122,11 @@ deps = langgraph-latest: -r {toxinidir}/instrumentation-loongsuite/loongsuite-instrumentation-langgraph/tests/requirements.latest.txt lint-loongsuite-instrumentation-langgraph: -r {toxinidir}/instrumentation-loongsuite/loongsuite-instrumentation-langgraph/tests/requirements.oldest.txt + qwen-agent-oldest: -r {toxinidir}/instrumentation-loongsuite/loongsuite-instrumentation-qwen-agent/tests/requirements.oldest.txt + qwen-agent-latest: {[testenv]test_deps} + qwen-agent-latest: -r {toxinidir}/instrumentation-loongsuite/loongsuite-instrumentation-qwen-agent/tests/requirements.latest.txt + lint-loongsuite-instrumentation-qwen-agent: -r {toxinidir}/instrumentation-loongsuite/loongsuite-instrumentation-qwen-agent/tests/requirements.oldest.txt + loongsuite-mcp: {[testenv]test_deps} loongsuite-mcp: -r {toxinidir}/instrumentation-loongsuite/loongsuite-instrumentation-mcp/test-requirements.txt @@ -178,6 +187,9 @@ commands = test-loongsuite-instrumentation-langgraph: pytest {toxinidir}/instrumentation-loongsuite/loongsuite-instrumentation-langgraph/tests {posargs} lint-loongsuite-instrumentation-langgraph: python -m ruff check {toxinidir}/instrumentation-loongsuite/loongsuite-instrumentation-langgraph + test-loongsuite-instrumentation-qwen-agent: pytest {toxinidir}/instrumentation-loongsuite/loongsuite-instrumentation-qwen-agent/tests {posargs} + lint-loongsuite-instrumentation-qwen-agent: python -m ruff check {toxinidir}/instrumentation-loongsuite/loongsuite-instrumentation-qwen-agent + test-loongsuite-instrumentation-mcp: pytest {toxinidir}/instrumentation-loongsuite/loongsuite-instrumentation-mcp/tests {posargs} lint-loongsuite-instrumentation-mcp: python -m ruff check {toxinidir}/instrumentation-loongsuite/loongsuite-instrumentation-mcp From 77567923e01ec56da2b7ce460e8bcb22fb536c9e Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?=E6=B5=81=E5=B1=BF?= Date: Tue, 24 Mar 2026 10:36:26 +0800 Subject: [PATCH 2/2] fix: add license and run precommit Change-Id: I6e70c5771f05d4915546bf6c2d4b96dc50582ce7 Co-developed-by: Cursor --- .../instrumentation/qwen_agent/__init__.py | 18 +- .../instrumentation/qwen_agent/patch.py | 48 ++- .../instrumentation/qwen_agent/utils.py | 49 ++- .../tests/__init__.py | 13 + .../tests/test_instrumentor.py | 8 +- .../tests/test_real_api.py | 281 ++++++++++++++---- .../tests/test_spans.py | 44 ++- 7 files changed, 359 insertions(+), 102 deletions(-) diff --git a/instrumentation-loongsuite/loongsuite-instrumentation-qwen-agent/src/opentelemetry/instrumentation/qwen_agent/__init__.py b/instrumentation-loongsuite/loongsuite-instrumentation-qwen-agent/src/opentelemetry/instrumentation/qwen_agent/__init__.py index 2826d19af..8e3e22625 100644 --- a/instrumentation-loongsuite/loongsuite-instrumentation-qwen-agent/src/opentelemetry/instrumentation/qwen_agent/__init__.py +++ b/instrumentation-loongsuite/loongsuite-instrumentation-qwen-agent/src/opentelemetry/instrumentation/qwen_agent/__init__.py @@ -120,8 +120,10 @@ def _instrument(self, **kwargs: Any) -> None: wrap_function_wrapper( module=_LLM_MODULE, name="BaseChatModel.chat", - wrapper=lambda wrapped, instance, args, kwargs: wrap_chat_model_chat( - wrapped, instance, args, kwargs, handler=self._handler + wrapper=lambda wrapped, instance, args, kwargs: ( + wrap_chat_model_chat( + wrapped, instance, args, kwargs, handler=self._handler + ) ), ) logger.debug("Instrumented BaseChatModel.chat") @@ -133,8 +135,10 @@ def _instrument(self, **kwargs: Any) -> None: wrap_function_wrapper( module=_AGENT_MODULE, name="Agent._call_llm", - wrapper=lambda wrapped, instance, args, kwargs: wrap_agent_call_llm( - wrapped, instance, args, kwargs, handler=self._handler + wrapper=lambda wrapped, instance, args, kwargs: ( + wrap_agent_call_llm( + wrapped, instance, args, kwargs, handler=self._handler + ) ), ) logger.debug("Instrumented Agent._call_llm") @@ -146,8 +150,10 @@ def _instrument(self, **kwargs: Any) -> None: wrap_function_wrapper( module=_AGENT_MODULE, name="Agent._call_tool", - wrapper=lambda wrapped, instance, args, kwargs: wrap_agent_call_tool( - wrapped, instance, args, kwargs, handler=self._handler + wrapper=lambda wrapped, instance, args, kwargs: ( + wrap_agent_call_tool( + wrapped, instance, args, kwargs, handler=self._handler + ) ), ) logger.debug("Instrumented Agent._call_tool") diff --git a/instrumentation-loongsuite/loongsuite-instrumentation-qwen-agent/src/opentelemetry/instrumentation/qwen_agent/patch.py b/instrumentation-loongsuite/loongsuite-instrumentation-qwen-agent/src/opentelemetry/instrumentation/qwen_agent/patch.py index 52e24c36e..c069c7506 100644 --- a/instrumentation-loongsuite/loongsuite-instrumentation-qwen-agent/src/opentelemetry/instrumentation/qwen_agent/patch.py +++ b/instrumentation-loongsuite/loongsuite-instrumentation-qwen-agent/src/opentelemetry/instrumentation/qwen_agent/patch.py @@ -69,7 +69,9 @@ def _close_active_react_step(handler: ExtendedTelemetryHandler) -> None: _react_step_invocation.set(None) -def wrap_agent_run(wrapped, instance, args, kwargs, handler: ExtendedTelemetryHandler): +def wrap_agent_run( + wrapped, instance, args, kwargs, handler: ExtendedTelemetryHandler +): """Wrapper for Agent.run() to create invoke_agent spans. Agent.run() is a generator that yields List[Message]. @@ -104,8 +106,8 @@ def wrap_agent_run(wrapped, instance, args, kwargs, handler: ExtendedTelemetryHa # Extract output from last yielded response if last_response: - invocation.output_messages = convert_qwen_messages_to_output_messages( - last_response + invocation.output_messages = ( + convert_qwen_messages_to_output_messages(last_response) ) # Close the last react_step span before closing invoke_agent. @@ -137,7 +139,11 @@ def wrap_chat_model_chat( - Iterator[List[Message]] (stream) """ messages = args[0] if args else kwargs.get("messages", []) - functions = kwargs.get("functions") if len(args) < 2 else (args[1] if len(args) > 1 else None) + functions = ( + kwargs.get("functions") + if len(args) < 2 + else (args[1] if len(args) > 1 else None) + ) stream = kwargs.get("stream", True) extra_generate_cfg = kwargs.get("extra_generate_cfg") @@ -154,21 +160,31 @@ def wrap_chat_model_chat( try: result = wrapped(*args, **kwargs) - if stream and hasattr(result, "__iter__") and not isinstance(result, list): + if ( + stream + and hasattr(result, "__iter__") + and not isinstance(result, list) + ): # Streaming: wrap the iterator return _wrap_streaming_llm_response(result, invocation, handler) else: # Non-streaming: result is List[Message] if result: - invocation.output_messages = convert_qwen_messages_to_output_messages( - result + invocation.output_messages = ( + convert_qwen_messages_to_output_messages(result) ) invocation.response_model_name = invocation.request_model invocation.finish_reasons = ["stop"] # Check for function calls in output for msg in result: - fc = msg.function_call if hasattr(msg, "function_call") else msg.get("function_call") if isinstance(msg, dict) else None + fc = ( + msg.function_call + if hasattr(msg, "function_call") + else msg.get("function_call") + if isinstance(msg, dict) + else None + ) if fc: invocation.finish_reasons = ["tool_calls"] break @@ -196,15 +212,21 @@ def _wrap_streaming_llm_response( yield response if last_response: - invocation.output_messages = convert_qwen_messages_to_output_messages( - last_response + invocation.output_messages = ( + convert_qwen_messages_to_output_messages(last_response) ) invocation.response_model_name = invocation.request_model invocation.finish_reasons = ["stop"] # Check for function calls for msg in last_response: - fc = msg.function_call if hasattr(msg, "function_call") else msg.get("function_call") if isinstance(msg, dict) else None + fc = ( + msg.function_call + if hasattr(msg, "function_call") + else msg.get("function_call") + if isinstance(msg, dict) + else None + ) if fc: invocation.finish_reasons = ["tool_calls"] break @@ -275,7 +297,9 @@ def wrap_agent_call_tool( tool_instance = instance.function_map.get(tool_name) try: - invocation = create_tool_invocation(tool_name, tool_args, tool_instance) + invocation = create_tool_invocation( + tool_name, tool_args, tool_instance + ) except Exception as e: logger.debug(f"Failed to create tool invocation: {e}") return wrapped(*args, **kwargs) diff --git a/instrumentation-loongsuite/loongsuite-instrumentation-qwen-agent/src/opentelemetry/instrumentation/qwen_agent/utils.py b/instrumentation-loongsuite/loongsuite-instrumentation-qwen-agent/src/opentelemetry/instrumentation/qwen_agent/utils.py index 036cf75ac..d836cc895 100644 --- a/instrumentation-loongsuite/loongsuite-instrumentation-qwen-agent/src/opentelemetry/instrumentation/qwen_agent/utils.py +++ b/instrumentation-loongsuite/loongsuite-instrumentation-qwen-agent/src/opentelemetry/instrumentation/qwen_agent/utils.py @@ -127,10 +127,18 @@ def convert_qwen_messages_to_input_messages( input_messages = [] for msg in messages: try: - role = msg.role if hasattr(msg, "role") else msg.get("role", "user") - content = msg.content if hasattr(msg, "content") else msg.get("content", "") + role = ( + msg.role if hasattr(msg, "role") else msg.get("role", "user") + ) + content = ( + msg.content + if hasattr(msg, "content") + else msg.get("content", "") + ) function_call = ( - msg.function_call if hasattr(msg, "function_call") else msg.get("function_call") + msg.function_call + if hasattr(msg, "function_call") + else msg.get("function_call") ) name = msg.name if hasattr(msg, "name") else msg.get("name") @@ -154,7 +162,9 @@ def convert_qwen_messages_to_input_messages( fc_args = json.loads(fc_args) except (json.JSONDecodeError, ValueError): pass - parts.append(ToolCall(name=fc_name, arguments=fc_args, id=None)) + parts.append( + ToolCall(name=fc_name, arguments=fc_args, id=None) + ) # Handle function role (tool response) if role == "function" and content: @@ -200,9 +210,15 @@ def convert_qwen_messages_to_output_messages( output_messages = [] for msg in messages: try: - content = msg.content if hasattr(msg, "content") else msg.get("content", "") + content = ( + msg.content + if hasattr(msg, "content") + else msg.get("content", "") + ) function_call = ( - msg.function_call if hasattr(msg, "function_call") else msg.get("function_call") + msg.function_call + if hasattr(msg, "function_call") + else msg.get("function_call") ) parts = [] @@ -224,7 +240,9 @@ def convert_qwen_messages_to_output_messages( fc_args = json.loads(fc_args) except (json.JSONDecodeError, ValueError): pass - parts.append(ToolCall(name=fc_name, arguments=fc_args, id=None)) + parts.append( + ToolCall(name=fc_name, arguments=fc_args, id=None) + ) finish_reason = "tool_calls" if content: @@ -250,7 +268,9 @@ def convert_qwen_messages_to_output_messages( return output_messages -def get_tool_definitions(functions: Optional[List[Dict]]) -> Optional[List[FunctionToolDefinition]]: +def get_tool_definitions( + functions: Optional[List[Dict]], +) -> Optional[List[FunctionToolDefinition]]: """Extract tool definitions for tracing as FunctionToolDefinition objects. Args: @@ -355,7 +375,9 @@ def create_agent_invocation( input_messages = convert_qwen_messages_to_input_messages(messages) - agent_name = getattr(agent_instance, "name", None) or type(agent_instance).__name__ + agent_name = ( + getattr(agent_instance, "name", None) or type(agent_instance).__name__ + ) agent_description = getattr(agent_instance, "description", None) or "" invocation = InvokeAgentInvocation( @@ -367,8 +389,13 @@ def create_agent_invocation( ) # Set system instruction if available - if hasattr(agent_instance, "system_message") and agent_instance.system_message: - invocation.system_instruction = [Text(content=agent_instance.system_message)] + if ( + hasattr(agent_instance, "system_message") + and agent_instance.system_message + ): + invocation.system_instruction = [ + Text(content=agent_instance.system_message) + ] return invocation diff --git a/instrumentation-loongsuite/loongsuite-instrumentation-qwen-agent/tests/__init__.py b/instrumentation-loongsuite/loongsuite-instrumentation-qwen-agent/tests/__init__.py index e69de29bb..b0a6f4284 100644 --- a/instrumentation-loongsuite/loongsuite-instrumentation-qwen-agent/tests/__init__.py +++ b/instrumentation-loongsuite/loongsuite-instrumentation-qwen-agent/tests/__init__.py @@ -0,0 +1,13 @@ +# Copyright The OpenTelemetry Authors +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. diff --git a/instrumentation-loongsuite/loongsuite-instrumentation-qwen-agent/tests/test_instrumentor.py b/instrumentation-loongsuite/loongsuite-instrumentation-qwen-agent/tests/test_instrumentor.py index 135b739b6..81d2cfca0 100644 --- a/instrumentation-loongsuite/loongsuite-instrumentation-qwen-agent/tests/test_instrumentor.py +++ b/instrumentation-loongsuite/loongsuite-instrumentation-qwen-agent/tests/test_instrumentor.py @@ -31,7 +31,9 @@ class TestQwenAgentInstrumentor: """Test the instrumentor lifecycle.""" - def test_instrument_and_uninstrument(self, tracer_provider, logger_provider, meter_provider): + def test_instrument_and_uninstrument( + self, tracer_provider, logger_provider, meter_provider + ): """Test that instrument/uninstrument works without errors.""" instrumentor = QwenAgentInstrumentor() instrumentor.instrument( @@ -109,7 +111,9 @@ def test_convert_function_call_message(self): def test_convert_function_response_message(self): """Test converting a function role message (tool result).""" - msg = Message(role="function", name="get_weather", content="Sunny, 25°C") + msg = Message( + role="function", name="get_weather", content="Sunny, 25°C" + ) result = convert_qwen_messages_to_input_messages([msg]) assert len(result) == 1 assert result[0].role == "function" diff --git a/instrumentation-loongsuite/loongsuite-instrumentation-qwen-agent/tests/test_real_api.py b/instrumentation-loongsuite/loongsuite-instrumentation-qwen-agent/tests/test_real_api.py index fb67ac4bc..a2f92b2e0 100644 --- a/instrumentation-loongsuite/loongsuite-instrumentation-qwen-agent/tests/test_real_api.py +++ b/instrumentation-loongsuite/loongsuite-instrumentation-qwen-agent/tests/test_real_api.py @@ -62,7 +62,13 @@ def _make_providers(): metric_reader = InMemoryMetricReader() meter_provider = MeterProvider(metric_readers=[metric_reader]) - return tracer_provider, span_exporter, logger_provider, log_exporter, meter_provider + return ( + tracer_provider, + span_exporter, + logger_provider, + log_exporter, + meter_provider, + ) @pytest.mark.vcr() @@ -74,7 +80,13 @@ def test_qwen_agent_basic_run(): - A chat (LLM) span is produced as a child - Both spans have the expected gen_ai.* attributes """ - tracer_provider, span_exporter, logger_provider, log_exporter, meter_provider = _make_providers() + ( + tracer_provider, + span_exporter, + logger_provider, + log_exporter, + meter_provider, + ) = _make_providers() instrumentor = QwenAgentInstrumentor() instrumentor.instrument( @@ -96,31 +108,57 @@ def test_qwen_agent_basic_run(): instrumentor.uninstrument() spans = span_exporter.get_finished_spans() - assert len(spans) >= 2, f"Expected at least 2 spans, got {len(spans)}: {[s.name for s in spans]}" + assert len(spans) >= 2, ( + f"Expected at least 2 spans, got {len(spans)}: {[s.name for s in spans]}" + ) # Find invoke_agent span agent_spans = [s for s in spans if "invoke_agent" in s.name] - assert len(agent_spans) >= 1, f"No invoke_agent span found in: {[s.name for s in spans]}" + assert len(agent_spans) >= 1, ( + f"No invoke_agent span found in: {[s.name for s in spans]}" + ) agent_span = agent_spans[0] - assert agent_span.attributes.get(GenAIAttributes.GEN_AI_OPERATION_NAME) == "invoke_agent" + assert ( + agent_span.attributes.get(GenAIAttributes.GEN_AI_OPERATION_NAME) + == "invoke_agent" + ) # Find chat/LLM span chat_spans = [s for s in spans if s.name.startswith("chat ")] - assert len(chat_spans) >= 1, f"No chat span found in: {[s.name for s in spans]}" + assert len(chat_spans) >= 1, ( + f"No chat span found in: {[s.name for s in spans]}" + ) chat_span = chat_spans[0] # Verify key span attributes on the chat span - assert chat_span.attributes.get(GenAIAttributes.GEN_AI_OPERATION_NAME) == "chat" - assert chat_span.attributes.get(GenAIAttributes.GEN_AI_PROVIDER_NAME) == "dashscope" - assert chat_span.attributes.get(GenAIAttributes.GEN_AI_REQUEST_MODEL) == "qwen-max" + assert ( + chat_span.attributes.get(GenAIAttributes.GEN_AI_OPERATION_NAME) + == "chat" + ) + assert ( + chat_span.attributes.get(GenAIAttributes.GEN_AI_PROVIDER_NAME) + == "dashscope" + ) + assert ( + chat_span.attributes.get(GenAIAttributes.GEN_AI_REQUEST_MODEL) + == "qwen-max" + ) # response_model_name fix: GEN_AI_RESPONSE_MODEL should now be populated - response_model = chat_span.attributes.get(GenAIAttributes.GEN_AI_RESPONSE_MODEL) - assert response_model is not None, "gen_ai.response.model should be set (P0 fix)" + response_model = chat_span.attributes.get( + GenAIAttributes.GEN_AI_RESPONSE_MODEL + ) + assert response_model is not None, ( + "gen_ai.response.model should be set (P0 fix)" + ) # finish_reasons fix: GEN_AI_RESPONSE_FINISH_REASONS should be populated - finish_reasons = chat_span.attributes.get(GenAIAttributes.GEN_AI_RESPONSE_FINISH_REASONS) - assert finish_reasons is not None, "gen_ai.response.finish_reasons should be set (P0 fix)" + finish_reasons = chat_span.attributes.get( + GenAIAttributes.GEN_AI_RESPONSE_FINISH_REASONS + ) + assert finish_reasons is not None, ( + "gen_ai.response.finish_reasons should be set (P0 fix)" + ) @pytest.mark.vcr() @@ -130,7 +168,13 @@ def test_qwen_agent_stream_llm_with_ttft(): Verifies that P2 fix (monotonic_first_token_s) is working: - gen_ai.response.time_to_first_token attribute is recorded when available """ - tracer_provider, span_exporter, logger_provider, log_exporter, meter_provider = _make_providers() + ( + tracer_provider, + span_exporter, + logger_provider, + log_exporter, + meter_provider, + ) = _make_providers() instrumentor = QwenAgentInstrumentor() instrumentor.instrument( @@ -141,7 +185,9 @@ def test_qwen_agent_stream_llm_with_ttft(): ) try: - llm = get_chat_model({"model": "qwen-max", "model_type": "qwen_dashscope"}) + llm = get_chat_model( + {"model": "qwen-max", "model_type": "qwen_dashscope"} + ) messages = [{"role": "user", "content": "Say hello in one word."}] # stream=True is the default; consume the iterator list(llm.chat(messages=messages, stream=True)) @@ -150,18 +196,33 @@ def test_qwen_agent_stream_llm_with_ttft(): spans = span_exporter.get_finished_spans() chat_spans = [s for s in spans if s.name.startswith("chat ")] - assert len(chat_spans) >= 1, f"No chat span found in: {[s.name for s in spans]}" + assert len(chat_spans) >= 1, ( + f"No chat span found in: {[s.name for s in spans]}" + ) chat_span = chat_spans[0] # Verify basic span attributes - assert chat_span.attributes.get(GenAIAttributes.GEN_AI_OPERATION_NAME) == "chat" - assert chat_span.attributes.get(GenAIAttributes.GEN_AI_PROVIDER_NAME) == "dashscope" - assert chat_span.attributes.get(GenAIAttributes.GEN_AI_REQUEST_MODEL) == "qwen-max" + assert ( + chat_span.attributes.get(GenAIAttributes.GEN_AI_OPERATION_NAME) + == "chat" + ) + assert ( + chat_span.attributes.get(GenAIAttributes.GEN_AI_PROVIDER_NAME) + == "dashscope" + ) + assert ( + chat_span.attributes.get(GenAIAttributes.GEN_AI_REQUEST_MODEL) + == "qwen-max" + ) # TTFT (gen_ai.response.time_to_first_token) may be None during cassette replay; # we assert finish_reasons to ensure the P2 code path ran. - finish_reasons = chat_span.attributes.get(GenAIAttributes.GEN_AI_RESPONSE_FINISH_REASONS) - assert finish_reasons is not None, "gen_ai.response.finish_reasons should be set (P0 fix)" + finish_reasons = chat_span.attributes.get( + GenAIAttributes.GEN_AI_RESPONSE_FINISH_REASONS + ) + assert finish_reasons is not None, ( + "gen_ai.response.finish_reasons should be set (P0 fix)" + ) @pytest.mark.vcr() @@ -173,7 +234,13 @@ def test_non_stream_chat(): - response_model and finish_reasons are set (P0 fix) - no streaming wrapper is used """ - tracer_provider, span_exporter, logger_provider, log_exporter, meter_provider = _make_providers() + ( + tracer_provider, + span_exporter, + logger_provider, + log_exporter, + meter_provider, + ) = _make_providers() instrumentor = QwenAgentInstrumentor() instrumentor.instrument( @@ -186,30 +253,56 @@ def test_non_stream_chat(): try: # use_raw_api=False forces the non-streaming code path; newer qwen-agent # versions default use_raw_api=True for qwen_dashscope which only supports stream=True. - llm = get_chat_model({ - "model": "qwen-max", - "model_type": "qwen_dashscope", - "generate_cfg": {"use_raw_api": False}, - }) - messages = [{"role": "user", "content": "What is 2+2? Answer with just the number."}] + llm = get_chat_model( + { + "model": "qwen-max", + "model_type": "qwen_dashscope", + "generate_cfg": {"use_raw_api": False}, + } + ) + messages = [ + { + "role": "user", + "content": "What is 2+2? Answer with just the number.", + } + ] list(llm.chat(messages=messages, stream=False)) finally: instrumentor.uninstrument() spans = span_exporter.get_finished_spans() chat_spans = [s for s in spans if s.name.startswith("chat ")] - assert len(chat_spans) >= 1, f"Expected at least 1 chat span, got: {[s.name for s in spans]}" + assert len(chat_spans) >= 1, ( + f"Expected at least 1 chat span, got: {[s.name for s in spans]}" + ) chat_span = chat_spans[0] - assert chat_span.attributes.get(GenAIAttributes.GEN_AI_OPERATION_NAME) == "chat" - assert chat_span.attributes.get(GenAIAttributes.GEN_AI_PROVIDER_NAME) == "dashscope" - assert chat_span.attributes.get(GenAIAttributes.GEN_AI_REQUEST_MODEL) == "qwen-max" + assert ( + chat_span.attributes.get(GenAIAttributes.GEN_AI_OPERATION_NAME) + == "chat" + ) + assert ( + chat_span.attributes.get(GenAIAttributes.GEN_AI_PROVIDER_NAME) + == "dashscope" + ) + assert ( + chat_span.attributes.get(GenAIAttributes.GEN_AI_REQUEST_MODEL) + == "qwen-max" + ) - response_model = chat_span.attributes.get(GenAIAttributes.GEN_AI_RESPONSE_MODEL) - assert response_model is not None, "gen_ai.response.model should be set for non-stream (P0 fix)" + response_model = chat_span.attributes.get( + GenAIAttributes.GEN_AI_RESPONSE_MODEL + ) + assert response_model is not None, ( + "gen_ai.response.model should be set for non-stream (P0 fix)" + ) - finish_reasons = chat_span.attributes.get(GenAIAttributes.GEN_AI_RESPONSE_FINISH_REASONS) - assert finish_reasons is not None, "gen_ai.response.finish_reasons should be set for non-stream (P0 fix)" + finish_reasons = chat_span.attributes.get( + GenAIAttributes.GEN_AI_RESPONSE_FINISH_REASONS + ) + assert finish_reasons is not None, ( + "gen_ai.response.finish_reasons should be set for non-stream (P0 fix)" + ) @pytest.mark.vcr() @@ -220,7 +313,13 @@ def test_agent_run_nonstream(): so the invoke_agent span is created once by the run() wrapper. Verifies there is no span duplication when using the non-streaming entry point. """ - tracer_provider, span_exporter, logger_provider, log_exporter, meter_provider = _make_providers() + ( + tracer_provider, + span_exporter, + logger_provider, + log_exporter, + meter_provider, + ) = _make_providers() instrumentor = QwenAgentInstrumentor() instrumentor.instrument( @@ -243,13 +342,22 @@ def test_agent_run_nonstream(): spans = span_exporter.get_finished_spans() # Assistant may spawn a Memory sub-agent producing extra invoke_agent spans; # filter to the target agent by name. - agent_spans = [s for s in spans if s.name == "invoke_agent NonStreamAssistant"] - assert len(agent_spans) >= 1, f"Expected invoke_agent NonStreamAssistant span, got: {[s.name for s in spans]}" + agent_spans = [ + s for s in spans if s.name == "invoke_agent NonStreamAssistant" + ] + assert len(agent_spans) >= 1, ( + f"Expected invoke_agent NonStreamAssistant span, got: {[s.name for s in spans]}" + ) agent_span = agent_spans[0] - assert agent_span.attributes.get(GenAIAttributes.GEN_AI_OPERATION_NAME) == "invoke_agent" + assert ( + agent_span.attributes.get(GenAIAttributes.GEN_AI_OPERATION_NAME) + == "invoke_agent" + ) chat_spans = [s for s in spans if s.name.startswith("chat ")] - assert len(chat_spans) >= 1, f"No chat span found in: {[s.name for s in spans]}" + assert len(chat_spans) >= 1, ( + f"No chat span found in: {[s.name for s in spans]}" + ) @pytest.mark.vcr() @@ -259,7 +367,13 @@ def test_multi_turn_conversation(): Verifies that all input messages (user + assistant history) are correctly captured in the span event log, not just the last message. """ - tracer_provider, span_exporter, logger_provider, log_exporter, meter_provider = _make_providers() + ( + tracer_provider, + span_exporter, + logger_provider, + log_exporter, + meter_provider, + ) = _make_providers() instrumentor = QwenAgentInstrumentor() instrumentor.instrument( @@ -286,16 +400,29 @@ def test_multi_turn_conversation(): spans = span_exporter.get_finished_spans() # Filter to our specific agent; Assistant may produce extra Memory sub-agent spans. - agent_spans = [s for s in spans if s.name == "invoke_agent MultiTurnAssistant"] - assert len(agent_spans) >= 1, f"Expected invoke_agent MultiTurnAssistant span in: {[s.name for s in spans]}" + agent_spans = [ + s for s in spans if s.name == "invoke_agent MultiTurnAssistant" + ] + assert len(agent_spans) >= 1, ( + f"Expected invoke_agent MultiTurnAssistant span in: {[s.name for s in spans]}" + ) chat_spans = [s for s in spans if s.name.startswith("chat ")] - assert len(chat_spans) >= 1, f"No chat span found in: {[s.name for s in spans]}" + assert len(chat_spans) >= 1, ( + f"No chat span found in: {[s.name for s in spans]}" + ) chat_span = chat_spans[0] - assert chat_span.attributes.get(GenAIAttributes.GEN_AI_REQUEST_MODEL) == "qwen-max" - finish_reasons = chat_span.attributes.get(GenAIAttributes.GEN_AI_RESPONSE_FINISH_REASONS) - assert finish_reasons is not None, "gen_ai.response.finish_reasons should be set" + assert ( + chat_span.attributes.get(GenAIAttributes.GEN_AI_REQUEST_MODEL) + == "qwen-max" + ) + finish_reasons = chat_span.attributes.get( + GenAIAttributes.GEN_AI_RESPONSE_FINISH_REASONS + ) + assert finish_reasons is not None, ( + "gen_ai.response.finish_reasons should be set" + ) @pytest.mark.vcr() @@ -307,7 +434,13 @@ def test_react_multi_round(): - gen_ai.react.round attribute increments per iteration - chat and execute_tool spans are nested inside react_step """ - tracer_provider, span_exporter, logger_provider, log_exporter, meter_provider = _make_providers() + ( + tracer_provider, + span_exporter, + logger_provider, + log_exporter, + meter_provider, + ) = _make_providers() instrumentor = QwenAgentInstrumentor() instrumentor.instrument( @@ -318,6 +451,7 @@ def test_react_multi_round(): ) try: + @register_tool("calculator_react_test") class CalculatorTool(BaseTool): description = "Evaluate a simple arithmetic expression and return the numeric result." @@ -357,7 +491,9 @@ def call(self, params, **kwargs): # Filter to our specific agent; Assistant may produce extra Memory sub-agent spans. agent_spans = [s for s in spans if s.name == "invoke_agent ReactAgent"] - assert len(agent_spans) >= 1, f"Expected invoke_agent ReactAgent span in: {span_names}" + assert len(agent_spans) >= 1, ( + f"Expected invoke_agent ReactAgent span in: {span_names}" + ) # "react step" spans must appear (agent has tools → ReAct mode) react_spans = [s for s in spans if s.name == "react step"] @@ -367,7 +503,9 @@ def call(self, params, **kwargs): # gen_ai.react.round attribute must be set and start at 1 rounds = [s.attributes.get("gen_ai.react.round") for s in react_spans] - assert 1 in rounds, f"Expected gen_ai.react.round=1 in react step spans, got rounds={rounds}" + assert 1 in rounds, ( + f"Expected gen_ai.react.round=1 in react step spans, got rounds={rounds}" + ) # chat spans must exist inside react step (nested via OTel context) chat_spans = [s for s in spans if s.name.startswith("chat ")] @@ -382,7 +520,13 @@ def test_qwen_agent_with_tool_call(): without TOOL_REGISTRY registration) to exercise the tool_definitions P1 fix and verify execute_tool spans are generated when the model calls a tool. """ - tracer_provider, span_exporter, logger_provider, log_exporter, meter_provider = _make_providers() + ( + tracer_provider, + span_exporter, + logger_provider, + log_exporter, + meter_provider, + ) = _make_providers() instrumentor = QwenAgentInstrumentor() instrumentor.instrument( @@ -393,6 +537,7 @@ def test_qwen_agent_with_tool_call(): ) try: + @register_tool("get_current_weather_test") class GetCurrentWeatherTool(BaseTool): description = "Get the current weather for a given city." @@ -411,15 +556,26 @@ def call(self, params, **kwargs): params = json.loads(params) except Exception: params = {"city": params} - city = params.get("city", "unknown") if isinstance(params, dict) else "unknown" - return f"The weather in {city} is sunny and 22 degrees Celsius." + city = ( + params.get("city", "unknown") + if isinstance(params, dict) + else "unknown" + ) + return ( + f"The weather in {city} is sunny and 22 degrees Celsius." + ) bot = Assistant( llm={"model": "qwen-max", "model_type": "qwen_dashscope"}, name="WeatherAgent", function_list=["get_current_weather_test"], ) - messages = [{"role": "user", "content": "What is the weather in Beijing right now?"}] + messages = [ + { + "role": "user", + "content": "What is the weather in Beijing right now?", + } + ] list(bot.run(messages)) finally: instrumentor.uninstrument() @@ -436,11 +592,20 @@ def call(self, params, **kwargs): # Verify chat span attributes chat_span = chat_spans[0] - assert chat_span.attributes.get(GenAIAttributes.GEN_AI_OPERATION_NAME) == "chat" - assert chat_span.attributes.get(GenAIAttributes.GEN_AI_PROVIDER_NAME) == "dashscope" + assert ( + chat_span.attributes.get(GenAIAttributes.GEN_AI_OPERATION_NAME) + == "chat" + ) + assert ( + chat_span.attributes.get(GenAIAttributes.GEN_AI_PROVIDER_NAME) + == "dashscope" + ) # If the model called the tool, there should be an execute_tool span tool_spans = [s for s in spans if "execute_tool" in s.name] # Tool call is model-dependent; only assert if tool spans exist for tool_span in tool_spans: - assert tool_span.attributes.get(GenAIAttributes.GEN_AI_OPERATION_NAME) == "execute_tool" + assert ( + tool_span.attributes.get(GenAIAttributes.GEN_AI_OPERATION_NAME) + == "execute_tool" + ) diff --git a/instrumentation-loongsuite/loongsuite-instrumentation-qwen-agent/tests/test_spans.py b/instrumentation-loongsuite/loongsuite-instrumentation-qwen-agent/tests/test_spans.py index 8230efd4f..dd42670cb 100644 --- a/instrumentation-loongsuite/loongsuite-instrumentation-qwen-agent/tests/test_spans.py +++ b/instrumentation-loongsuite/loongsuite-instrumentation-qwen-agent/tests/test_spans.py @@ -113,7 +113,9 @@ def test_non_stream_chat_creates_span(self, span_exporter, instrument): spans = span_exporter.get_finished_spans() chat_spans = [s for s in spans if s.name.startswith("chat")] - assert len(chat_spans) >= 1, f"Expected a chat span, got: {[s.name for s in spans]}" + assert len(chat_spans) >= 1, ( + f"Expected a chat span, got: {[s.name for s in spans]}" + ) span = chat_spans[0] assert span.name == "chat qwen-max" @@ -121,8 +123,12 @@ def test_non_stream_chat_creates_span(self, span_exporter, instrument): attrs = dict(span.attributes or {}) assert attrs.get(GenAIAttributes.GEN_AI_REQUEST_MODEL) == "qwen-max" # Provider name is stored as "gen_ai.provider.name" in newer semconv - provider = attrs.get("gen_ai.provider.name") or attrs.get(GenAIAttributes.GEN_AI_SYSTEM) - assert provider == "dashscope", f"Expected 'dashscope', got attrs: {attrs}" + provider = attrs.get("gen_ai.provider.name") or attrs.get( + GenAIAttributes.GEN_AI_SYSTEM + ) + assert provider == "dashscope", ( + f"Expected 'dashscope', got attrs: {attrs}" + ) def test_stream_chat_creates_span(self, span_exporter, instrument): """Streaming chat() should create a chat span after the iterator is consumed.""" @@ -177,7 +183,9 @@ def test_chat_with_function_call_response(self, span_exporter, instrument): return_value=fake_response, ): model.chat( - messages=[Message(role="user", content="What is the weather?")], + messages=[ + Message(role="user", content="What is the weather?") + ], stream=False, ) @@ -215,7 +223,9 @@ def test_chat_error_creates_error_span(self, span_exporter, instrument): class TestAgentRunSpan: """Verify that Agent.run() and run_nonstream() produce invoke_agent spans.""" - def test_agent_run_creates_invoke_agent_span(self, span_exporter, instrument): + def test_agent_run_creates_invoke_agent_span( + self, span_exporter, instrument + ): """Agent.run() (generator) should create an invoke_agent span.""" llm = MagicMock() llm.model = "qwen-max" @@ -229,13 +239,17 @@ def fake_run(messages, **kwargs): yield response_msgs with patch.object(_StubAgent, "_run", side_effect=fake_run): - results = list(agent.run([Message(role="user", content="Weather?")])) + results = list( + agent.run([Message(role="user", content="Weather?")]) + ) assert len(results) >= 1 spans = span_exporter.get_finished_spans() agent_spans = [s for s in spans if "invoke_agent" in s.name] - assert len(agent_spans) >= 1, f"Expected invoke_agent span, got: {[s.name for s in spans]}" + assert len(agent_spans) >= 1, ( + f"Expected invoke_agent span, got: {[s.name for s in spans]}" + ) span = agent_spans[0] assert span.name == "invoke_agent WeatherBot" @@ -273,7 +287,9 @@ def fake_run(messages, **kwargs): span_names = [s.name for s in agent_spans] assert any("ChatBot" in n for n in span_names) - def test_agent_run_error_creates_error_span(self, span_exporter, instrument): + def test_agent_run_error_creates_error_span( + self, span_exporter, instrument + ): """An exception during Agent.run() should produce an error invoke_agent span.""" llm = MagicMock() llm.model = "qwen-max" @@ -337,7 +353,9 @@ def _make_agent_with_tool(self, tool_name="get_weather"): agent.function_map = {tool_name: mock_tool} return agent, mock_tool - def test_call_tool_creates_execute_tool_span(self, span_exporter, instrument): + def test_call_tool_creates_execute_tool_span( + self, span_exporter, instrument + ): """_call_tool() should create an execute_tool span with tool name.""" agent, mock_tool = self._make_agent_with_tool("get_weather") @@ -347,7 +365,9 @@ def test_call_tool_creates_execute_tool_span(self, span_exporter, instrument): spans = span_exporter.get_finished_spans() tool_spans = [s for s in spans if "execute_tool" in s.name] - assert len(tool_spans) >= 1, f"Expected execute_tool span, got: {[s.name for s in spans]}" + assert len(tool_spans) >= 1, ( + f"Expected execute_tool span, got: {[s.name for s in spans]}" + ) span = tool_spans[0] assert span.name == "execute_tool get_weather" @@ -606,9 +626,7 @@ def fake_run(messages, **kwargs): with patch.object( _StubChatModel, "_chat_no_stream", - return_value=[ - Message(role="assistant", content="Hello!") - ], + return_value=[Message(role="assistant", content="Hello!")], ): agent._call_llm(messages=messages, stream=False) yield [Message(role="assistant", content="Hello!")]