From fb695893cf38e0aa6cb184e49567e8cb08c1d099 Mon Sep 17 00:00:00 2001 From: Nightingalelyy Date: Tue, 18 Aug 2026 02:45:57 +0800 Subject: [PATCH] fix(examples): validate OpenAI, OpenAI Agents, and OpenInference OTel 2.x spans --- python/tracing/openai-agents-sdk/README.md | 55 +- .../agent_patterns/agents_as_tools_test.py | 8 +- .../agent_patterns/deterministic_test.py | 16 +- .../agent_patterns/input_guardrails_test.py | 17 +- .../agent_patterns/llm_as_a_judge_test.py | 30 +- .../agent_patterns/output_guardrails_test.py | 16 +- .../agent_patterns/parallelization_test.py | 9 +- .../agent_patterns/routing_test.py | 22 +- .../basic/dynamic_system_prompt_test.py | 16 +- .../basic/hello_world_test.py | 15 +- .../basic/lifecycle_with_hook_example_test.py | 27 +- .../basic/stream_items_test.py | 10 +- .../basic/stream_text_test.py | 20 +- .../openai-agents-sdk/bridge_contract.py | 64 + .../complex_edge_cases_test.py | 89 +- python/tracing/openai-agents-sdk/conftest.py | 66 +- .../contract_scenarios_test.py | 166 +++ .../customer_service/main_test.py | 45 +- .../handoffs/handsoff_test.py | 15 +- .../handoffs/message_filter_streaming_test.py | 33 +- .../handoffs/message_filter_test.py | 21 +- python/tracing/openai-agents-sdk/poetry.lock | 1152 ++++++++++++++--- .../tracing/openai-agents-sdk/pyproject.toml | 22 +- .../openai-agents-sdk/requirements.txt | 8 + .../research_bot/agents/planner_agent.py | 3 +- .../research_bot/agents/writer_agent.py | 3 +- .../research_bot/main_test.py | 18 +- .../openai-agents-sdk/research_bot/manager.py | 17 +- .../openai-agents-sdk/research_bot/printer.py | 6 +- .../respan_exporter_openai_agents.py | 99 +- python/tracing/openai-agents-sdk/run_all.py | 84 ++ .../openai-agents-sdk/runner_contract.py | 26 + .../tools/computer_use_test.py | 33 +- .../tools/file_search_test.py | 17 +- .../openai-agents-sdk/tools/functions_test.py | 11 +- .../tools/web_search_test.py | 19 +- python/tracing/openai-sdk/.env.example | 8 +- python/tracing/openai-sdk/README.md | 46 + python/tracing/openai-sdk/_batch_data.py | 55 + python/tracing/openai-sdk/_shared.py | 411 ++++++ python/tracing/openai-sdk/async_parallel.py | 69 +- python/tracing/openai-sdk/attributes.py | 58 +- python/tracing/openai-sdk/batch.py | 136 +- python/tracing/openai-sdk/batch_async.py | 140 +- python/tracing/openai-sdk/decorators.py | 67 +- python/tracing/openai-sdk/hello_world.py | 58 +- python/tracing/openai-sdk/multi_turn.py | 67 +- python/tracing/openai-sdk/prompt.py | 66 +- .../tracing/openai-sdk/prompt_multi_turn.py | 68 +- python/tracing/openai-sdk/requirements.txt | 6 + .../openai-sdk/responses_hello_world.py | 48 +- .../openai-sdk/responses_multi_turn.py | 76 +- python/tracing/openai-sdk/responses_prompt.py | 78 +- .../tracing/openai-sdk/responses_streaming.py | 54 +- .../openai-sdk/responses_structured_output.py | 52 +- .../openai-sdk/responses_tool_calls.py | 97 +- python/tracing/openai-sdk/run_all.py | 71 + python/tracing/openai-sdk/streaming.py | 64 +- .../tracing/openai-sdk/structured_output.py | 58 +- .../openai-sdk/test_example_contract.py | 146 +++ python/tracing/openai-sdk/tool_calls.py | 94 +- .../tracing/openinference/01_chat_provider.py | 56 + python/tracing/openinference/02_tool_call.py | 86 ++ python/tracing/openinference/03_embedding.py | 45 + .../openinference/04_expected_failure.py | 52 + .../openinference/05_streaming_privacy.py | 67 + python/tracing/openinference/README.md | 48 + python/tracing/openinference/_shared.py | 111 ++ python/tracing/openinference/requirements.txt | 3 + python/tracing/openinference/run_all.py | 60 + .../openinference/test_example_contract.py | 92 ++ 71 files changed, 3834 insertions(+), 1157 deletions(-) create mode 100644 python/tracing/openai-agents-sdk/bridge_contract.py create mode 100644 python/tracing/openai-agents-sdk/contract_scenarios_test.py create mode 100644 python/tracing/openai-agents-sdk/requirements.txt create mode 100644 python/tracing/openai-agents-sdk/run_all.py create mode 100644 python/tracing/openai-agents-sdk/runner_contract.py create mode 100644 python/tracing/openai-sdk/README.md create mode 100644 python/tracing/openai-sdk/_batch_data.py create mode 100644 python/tracing/openai-sdk/_shared.py create mode 100644 python/tracing/openai-sdk/requirements.txt create mode 100644 python/tracing/openai-sdk/run_all.py create mode 100644 python/tracing/openai-sdk/test_example_contract.py create mode 100644 python/tracing/openinference/01_chat_provider.py create mode 100644 python/tracing/openinference/02_tool_call.py create mode 100644 python/tracing/openinference/03_embedding.py create mode 100644 python/tracing/openinference/04_expected_failure.py create mode 100644 python/tracing/openinference/05_streaming_privacy.py create mode 100644 python/tracing/openinference/README.md create mode 100644 python/tracing/openinference/_shared.py create mode 100644 python/tracing/openinference/requirements.txt create mode 100644 python/tracing/openinference/run_all.py create mode 100644 python/tracing/openinference/test_example_contract.py diff --git a/python/tracing/openai-agents-sdk/README.md b/python/tracing/openai-agents-sdk/README.md index 7908f01..03a9dbb 100644 --- a/python/tracing/openai-agents-sdk/README.md +++ b/python/tracing/openai-agents-sdk/README.md @@ -1,19 +1,56 @@ -# OpenAI Agents SDK Respan Examples +# OpenAI Agents SDK tracing examples -These examples use the current `respan-instrumentation-openai-agents` package. Older files still import `respan_exporter_openai_agents.RespanTraceProcessor`; the local compatibility bridge maps that import to the active instrumentation processor and initializes the unified Respan OTEL exporter. +These examples exercise `respan-instrumentation-openai-agents` against OpenAI Agents SDK `0.20.x`. The suite includes deterministic current-framework traces for success, failure, function tools, handoffs, guardrails, and streaming, plus the upstream-style live examples. -## Setup +## Install + +From this directory: + +```bash +python -m pip install -r requirements.txt +``` + +For repository development, install the local packages after the registry dependencies so validation uses the current checkout: ```bash -cd python/tracing/openai-agents-sdk -pip install openai-agents respan-ai respan-instrumentation-openai-agents python-dotenv pytest pytest-asyncio +python -m pip install -e ../../../../respan/python-sdks/respan-sdk +python -m pip install -e ../../../../respan/python-sdks/respan-tracing +python -m pip install -e ../../../../respan/python-sdks/respan +python -m pip install -e ../../../../respan/python-sdks/instrumentations/respan-instrumentation-openai-agents ``` -Use the repository root `.env` values. OpenAI Agents 0.17 uses the Responses API by default. Because the current Respan OpenAI gateway covers chat-compatible routes, the local bridge forces `chat_completions` and routes model calls to `RESPAN_GATEWAY_BASE_URL` when `RESPAN_GATEWAY_API_KEY` is present. Set `RESPAN_OPENAI_AGENTS_USE_OPENAI=1` to use a direct `OPENAI_API_KEY`/Responses run instead. Traces always go to `RESPAN_BASE_URL` with `RESPAN_API_KEY`. +The suite reads the repository `.env` without overriding variables supplied by the shell. Set `RESPAN_API_KEY` and `RESPAN_BASE_URL` for trace export. Gateway-compatible live examples use that Respan credential and Chat Completions route. + +The compatibility bridge disables Respan's direct OpenAI auto-instrumentation because the explicit Agents trace processor owns these provider calls; this keeps each model call to one canonical chat span even when both instrumentation packages are installed. -Run a focused example: +Hosted tools are intentionally not converted to Chat Completions. Web Search and the research bot require `RESPAN_OPENAI_AGENTS_USE_OPENAI=1` plus a direct `OPENAI_API_KEY`. File Search additionally requires `OPENAI_VECTOR_STORE_ID`. Computer Use additionally requires `RESPAN_OPENAI_AGENTS_ENABLE_COMPUTER=1` and an installed Playwright Chromium runtime: ```bash -pytest basic/hello_world_test.py -q -pytest tools/functions_test.py -q +python -m playwright install chromium ``` + +When those settings are absent, only the affected hosted examples are reported as explicit skips. + +## Run + +Run every collected example and the three legacy direct-run demos under one exact marker: + +```bash +RESPAN_EXAMPLE_RUN_ID=otel2-openai-agents-check python run_all.py +``` + +Run only deterministic structural coverage: + +```bash +RESPAN_EXAMPLE_RUN_ID=otel2-openai-agents-contract \ + python -m pytest contract_scenarios_test.py -q -s +``` + +Nested handoff files are directly executable without a manual `PYTHONPATH` adjustment: + +```bash +python handoffs/message_filter_test.py +python handoffs/message_filter_streaming_test.py +``` + +Every pytest case flushes after completion, every process performs an explicit final Respan shutdown, and the same `RESPAN_EXAMPLE_RUN_ID` is attached to every emitted record. diff --git a/python/tracing/openai-agents-sdk/agent_patterns/agents_as_tools_test.py b/python/tracing/openai-agents-sdk/agent_patterns/agents_as_tools_test.py index 343d291..77f4d4a 100644 --- a/python/tracing/openai-agents-sdk/agent_patterns/agents_as_tools_test.py +++ b/python/tracing/openai-agents-sdk/agent_patterns/agents_as_tools_test.py @@ -1,12 +1,14 @@ from dotenv import load_dotenv -load_dotenv(override=True) +load_dotenv(override=False) import asyncio import os + import pytest from agents import Agent, ItemHelpers, MessageOutputItem, Runner, trace from agents.tracing import set_trace_processors + from respan_exporter_openai_agents import RespanTraceProcessor set_trace_processors( @@ -69,6 +71,7 @@ instructions="You inspect translations, correct them if needed, and produce a final concatenated response.", ) + @pytest.mark.asyncio async def test_main(): msg = "english to spanish" @@ -90,7 +93,6 @@ async def test_main(): print(f"\n\nFinal response:\n{synthesizer_result.final_output}") - if __name__ == "__main__": # For interactive use - asyncio.run(test_main()) \ No newline at end of file + asyncio.run(test_main()) diff --git a/python/tracing/openai-agents-sdk/agent_patterns/deterministic_test.py b/python/tracing/openai-agents-sdk/agent_patterns/deterministic_test.py index ce994b1..5e22926 100644 --- a/python/tracing/openai-agents-sdk/agent_patterns/deterministic_test.py +++ b/python/tracing/openai-agents-sdk/agent_patterns/deterministic_test.py @@ -1,13 +1,17 @@ from dotenv import load_dotenv -load_dotenv(override=True) + +load_dotenv(override=False) # ==========copy past below========== import asyncio import os -from pydantic import BaseModel +import sys + import pytest from agents import Agent, Runner, trace from agents.tracing import set_trace_processors +from pydantic import BaseModel + from respan_exporter_openai_agents import RespanTraceProcessor set_trace_processors( @@ -75,13 +79,15 @@ async def test_main(): assert isinstance(outline_checker_result.final_output, OutlineCheckerOutput) if not outline_checker_result.final_output.good_quality: print("Outline is not good quality, so we stop here.") - exit(0) + sys.exit(0) if not outline_checker_result.final_output.is_scifi: print("Outline is not a scifi story, so we stop here.") - exit(0) + sys.exit(0) - print("Outline is good quality and a scifi story, so we continue to write the story.") + print( + "Outline is good quality and a scifi story, so we continue to write the story." + ) # 4. Write the story story_result = await Runner.run( diff --git a/python/tracing/openai-agents-sdk/agent_patterns/input_guardrails_test.py b/python/tracing/openai-agents-sdk/agent_patterns/input_guardrails_test.py index d068b88..0038a96 100644 --- a/python/tracing/openai-agents-sdk/agent_patterns/input_guardrails_test.py +++ b/python/tracing/openai-agents-sdk/agent_patterns/input_guardrails_test.py @@ -1,13 +1,13 @@ from __future__ import annotations + from dotenv import load_dotenv -load_dotenv(override=True) + +load_dotenv(override=False) import asyncio import os -import pytest -from typing import Union -from pydantic import BaseModel +import pytest from agents import ( Agent, GuardrailFunctionOutput, @@ -17,8 +17,11 @@ TResponseInputItem, input_guardrail, ) -from respan_exporter_openai_agents import RespanTraceProcessor from agents.tracing import set_trace_processors, trace +from pydantic import BaseModel + +from respan_exporter_openai_agents import RespanTraceProcessor + set_trace_processors( [ RespanTraceProcessor( @@ -57,7 +60,9 @@ class MathHomeworkOutput(BaseModel): @input_guardrail async def math_guardrail( - context: RunContextWrapper[None], agent: Agent, input: Union[str, list[TResponseInputItem]] + context: RunContextWrapper[None], + agent: Agent, + input: str | list[TResponseInputItem], ) -> GuardrailFunctionOutput: """This is an input guardrail function, which happens to call an agent to check if the input is a math homework question. diff --git a/python/tracing/openai-agents-sdk/agent_patterns/llm_as_a_judge_test.py b/python/tracing/openai-agents-sdk/agent_patterns/llm_as_a_judge_test.py index af1fdc2..4583102 100644 --- a/python/tracing/openai-agents-sdk/agent_patterns/llm_as_a_judge_test.py +++ b/python/tracing/openai-agents-sdk/agent_patterns/llm_as_a_judge_test.py @@ -1,18 +1,19 @@ from __future__ import annotations + from dotenv import load_dotenv -load_dotenv(override=True) +load_dotenv(override=False) import asyncio import os -from typing import Literal, Union -import pytest -from pydantic import BaseModel +from typing import Literal +import pytest from agents import Agent, ItemHelpers, Runner, TResponseInputItem, trace -from respan_exporter_openai_agents import RespanTraceProcessor from agents.tracing import set_trace_processors +from pydantic import BaseModel +from respan_exporter_openai_agents import RespanTraceProcessor set_trace_processors( [ @@ -64,11 +65,11 @@ async def test_main() -> StoryEvaluationResult: msg = "Sci fi" input_items: list[TResponseInputItem] = [{"content": msg, "role": "user"}] - latest_outline: Union[str, None] = None + latest_outline: str | None = None iterations = 0 max_iterations = 2 final_score = "" - + # We'll run the entire workflow in a single trace with trace("LLM as a judge"): while True: @@ -82,7 +83,9 @@ async def test_main() -> StoryEvaluationResult: ) input_items = story_outline_result.to_input_list() - latest_outline = ItemHelpers.text_message_outputs(story_outline_result.new_items) + latest_outline = ItemHelpers.text_message_outputs( + story_outline_result.new_items + ) evaluator_result = await Runner.run(evaluator, input_items) result: EvaluationFeedback = evaluator_result.final_output @@ -91,15 +94,20 @@ async def test_main() -> StoryEvaluationResult: if result.score == "pass": break - input_items.append({"content": f"Feedback: {result.feedback}", "role": "user"}) + input_items.append( + {"content": f"Feedback: {result.feedback}", "role": "user"} + ) return StoryEvaluationResult( final_outline=latest_outline or "", iterations=iterations, - final_score=final_score + final_score=final_score, ) + if __name__ == "__main__": result = asyncio.run(test_main()) - print(f"Final story outline after {result.iterations} iterations (score: {result.final_score}):") + print( + f"Final story outline after {result.iterations} iterations (score: {result.final_score}):" + ) print(result.final_outline) diff --git a/python/tracing/openai-agents-sdk/agent_patterns/output_guardrails_test.py b/python/tracing/openai-agents-sdk/agent_patterns/output_guardrails_test.py index a95bb77..2e6449b 100644 --- a/python/tracing/openai-agents-sdk/agent_patterns/output_guardrails_test.py +++ b/python/tracing/openai-agents-sdk/agent_patterns/output_guardrails_test.py @@ -1,13 +1,13 @@ from __future__ import annotations + from dotenv import load_dotenv -load_dotenv(override=True) -import pytest +load_dotenv(override=False) import asyncio import json +import os -from pydantic import BaseModel, Field - +import pytest from agents import ( Agent, GuardrailFunctionOutput, @@ -16,12 +16,12 @@ Runner, output_guardrail, ) +from agents.tracing import set_trace_processors, trace +from pydantic import BaseModel, Field + from respan_exporter_openai_agents import ( RespanTraceProcessor, ) -from typing import Union -from agents.tracing import set_trace_processors, trace -import os set_trace_processors( [ @@ -50,7 +50,7 @@ class MessageOutput(BaseModel): description="Thoughts on how to respond to the user's message" ) response: str = Field(description="The response to the user's message") - user_name: Union[str, None] = Field( + user_name: str | None = Field( description="The name of the user who sent the message, if known" ) diff --git a/python/tracing/openai-agents-sdk/agent_patterns/parallelization_test.py b/python/tracing/openai-agents-sdk/agent_patterns/parallelization_test.py index 2b4dbf3..c45b0a3 100644 --- a/python/tracing/openai-agents-sdk/agent_patterns/parallelization_test.py +++ b/python/tracing/openai-agents-sdk/agent_patterns/parallelization_test.py @@ -1,14 +1,17 @@ import asyncio + from dotenv import load_dotenv -load_dotenv(override=True) +load_dotenv(override=False) +import os + import pytest from agents import Agent, ItemHelpers, Runner, trace +from agents.tracing import set_trace_processors + from respan_exporter_openai_agents import ( RespanTraceProcessor, ) -from agents.tracing import set_trace_processors -import os set_trace_processors( [ diff --git a/python/tracing/openai-agents-sdk/agent_patterns/routing_test.py b/python/tracing/openai-agents-sdk/agent_patterns/routing_test.py index df9acc2..fef3e9d 100644 --- a/python/tracing/openai-agents-sdk/agent_patterns/routing_test.py +++ b/python/tracing/openai-agents-sdk/agent_patterns/routing_test.py @@ -1,18 +1,18 @@ from dotenv import load_dotenv -load_dotenv(override=True) -import pytest +load_dotenv(override=False) import asyncio +import os import uuid +import pytest +from agents import Agent, RawResponsesStreamEvent, Runner, TResponseInputItem, trace +from agents.tracing import set_trace_processors from openai.types.responses import ResponseContentPartDoneEvent, ResponseTextDeltaEvent -from agents import Agent, RawResponsesStreamEvent, Runner, TResponseInputItem, trace from respan_exporter_openai_agents import ( RespanTraceProcessor, ) -from agents.tracing import set_trace_processors -import os set_trace_processors( [ @@ -55,8 +55,15 @@ async def test_main(): conversation_id = str(uuid.uuid4().hex[:16]) agent = triage_agent - inputs: list[TResponseInputItem] = [{"content": "Can you help me with my math homework?", "role": "user"}] - questions = ["Can you help me with my math homework?", "Yeah, how to solve for x: 2x + 5 = 11?", "What's the capital of France?", ""] + inputs: list[TResponseInputItem] = [ + {"content": "Can you help me with my math homework?", "role": "user"} + ] + questions = [ + "Can you help me with my math homework?", + "Yeah, how to solve for x: 2x + 5 = 11?", + "What's the capital of France?", + "", + ] with trace("Routing example", group_id=conversation_id): for question in questions: @@ -83,5 +90,6 @@ async def test_main(): inputs.append({"content": question, "role": "user"}) agent = result.current_agent + if __name__ == "__main__": asyncio.run(test_main()) diff --git a/python/tracing/openai-agents-sdk/basic/dynamic_system_prompt_test.py b/python/tracing/openai-agents-sdk/basic/dynamic_system_prompt_test.py index c54f868..4ddeaff 100644 --- a/python/tracing/openai-agents-sdk/basic/dynamic_system_prompt_test.py +++ b/python/tracing/openai-agents-sdk/basic/dynamic_system_prompt_test.py @@ -1,20 +1,26 @@ from dotenv import load_dotenv -load_dotenv(override=True) -import pytest -import os +load_dotenv(override=False) import asyncio +import os import random from typing import Literal +import pytest from agents import Agent, RunContextWrapper, Runner +from agents.tracing import set_trace_processors + from respan_exporter_openai_agents import ( RespanTraceProcessor, ) -from agents.tracing import set_trace_processors set_trace_processors( - [RespanTraceProcessor(os.getenv("RESPAN_API_KEY"), endpoint=os.getenv("RESPAN_OAIA_TRACING_ENDPOINT"))] + [ + RespanTraceProcessor( + os.getenv("RESPAN_API_KEY"), + endpoint=os.getenv("RESPAN_OAIA_TRACING_ENDPOINT"), + ) + ] ) diff --git a/python/tracing/openai-agents-sdk/basic/hello_world_test.py b/python/tracing/openai-agents-sdk/basic/hello_world_test.py index 167ae50..3c8f2b1 100644 --- a/python/tracing/openai-agents-sdk/basic/hello_world_test.py +++ b/python/tracing/openai-agents-sdk/basic/hello_world_test.py @@ -1,14 +1,16 @@ from dotenv import load_dotenv -load_dotenv(override=True) -from openai import AsyncOpenAI -import pytest +load_dotenv(override=False) # ==========copy paste below========== import asyncio import os -from agents import Agent, Runner, set_default_openai_client + +import pytest +from agents import Agent, Runner from agents.tracing import set_trace_processors, trace + from respan_exporter_openai_agents import RespanTraceProcessor + API_KEY = os.getenv("RESPAN_API_KEY") ENDPOINT = os.getenv("RESPAN_OAIA_TRACING_ENDPOINT") BASE_URL = os.getenv("RESPAN_BASE_URL") @@ -27,10 +29,7 @@ @pytest.mark.asyncio async def test_main(): - agent = Agent( - name="Assistant", - instructions="You only respond in haikus." - ) + agent = Agent(name="Assistant", instructions="You only respond in haikus.") with trace("Hello world test"): result = await Runner.run(agent, "Tell me about recursion in programming.") diff --git a/python/tracing/openai-agents-sdk/basic/lifecycle_with_hook_example_test.py b/python/tracing/openai-agents-sdk/basic/lifecycle_with_hook_example_test.py index 9243526..03072a1 100644 --- a/python/tracing/openai-agents-sdk/basic/lifecycle_with_hook_example_test.py +++ b/python/tracing/openai-agents-sdk/basic/lifecycle_with_hook_example_test.py @@ -1,19 +1,27 @@ from dotenv import load_dotenv -load_dotenv(override=True) -import pytest -import os +load_dotenv(override=False) import asyncio +import os import random from typing import Any +import pytest +from agents import ( + Agent, + RunContextWrapper, + RunHooks, + Runner, + Tool, + Usage, + function_tool, +) +from agents.tracing import set_trace_processors, trace from pydantic import BaseModel -from agents import Agent, RunContextWrapper, RunHooks, Runner, Tool, Usage, function_tool from respan_exporter_openai_agents import ( RespanTraceProcessor, ) -from agents.tracing import set_trace_processors, trace set_trace_processors( [ @@ -24,6 +32,7 @@ ] ) + class ExampleHooks(RunHooks): def __init__(self): self.event_counter = 0 @@ -37,13 +46,17 @@ async def on_agent_start(self, context: RunContextWrapper, agent: Agent) -> None f"### {self.event_counter}: Agent {agent.name} started. Usage: {self._usage_to_str(context.usage)}" ) - async def on_agent_end(self, context: RunContextWrapper, agent: Agent, output: Any) -> None: + async def on_agent_end( + self, context: RunContextWrapper, agent: Agent, output: Any + ) -> None: self.event_counter += 1 print( f"### {self.event_counter}: Agent {agent.name} ended with output {output}. Usage: {self._usage_to_str(context.usage)}" ) - async def on_tool_start(self, context: RunContextWrapper, agent: Agent, tool: Tool) -> None: + async def on_tool_start( + self, context: RunContextWrapper, agent: Agent, tool: Tool + ) -> None: self.event_counter += 1 print( f"### {self.event_counter}: Tool {tool.name} started. Usage: {self._usage_to_str(context.usage)}" diff --git a/python/tracing/openai-agents-sdk/basic/stream_items_test.py b/python/tracing/openai-agents-sdk/basic/stream_items_test.py index 96d537e..879cd00 100644 --- a/python/tracing/openai-agents-sdk/basic/stream_items_test.py +++ b/python/tracing/openai-agents-sdk/basic/stream_items_test.py @@ -1,17 +1,17 @@ from dotenv import load_dotenv -load_dotenv(override=True) -import pytest -import os - +load_dotenv(override=False) import asyncio +import os import random +import pytest from agents import Agent, ItemHelpers, Runner, function_tool +from agents.tracing import set_trace_processors, trace + from respan_exporter_openai_agents import ( RespanTraceProcessor, ) -from agents.tracing import set_trace_processors, trace set_trace_processors( [ diff --git a/python/tracing/openai-agents-sdk/basic/stream_text_test.py b/python/tracing/openai-agents-sdk/basic/stream_text_test.py index b9b37d2..a987f85 100644 --- a/python/tracing/openai-agents-sdk/basic/stream_text_test.py +++ b/python/tracing/openai-agents-sdk/basic/stream_text_test.py @@ -1,26 +1,26 @@ from dotenv import load_dotenv -load_dotenv(override=True) +load_dotenv(override=False) endpoint = "http://localhost:8000/api/openai/v1/traces/ingest" -import pytest -import time -import os import asyncio +import os - -from openai.types.responses import ResponseTextDeltaEvent - +import pytest from agents import Agent, Runner +from agents.tracing import set_trace_processors, trace +from openai.types.responses import ResponseTextDeltaEvent from respan_exporter_openai_agents import ( RespanTraceProcessor, ) -from agents.tracing import set_trace_processors, trace set_trace_processors( [ - RespanTraceProcessor(os.getenv("RESPAN_API_KEY"), endpoint=os.getenv("RESPAN_OAIA_TRACING_ENDPOINT")), + RespanTraceProcessor( + os.getenv("RESPAN_API_KEY"), + endpoint=os.getenv("RESPAN_OAIA_TRACING_ENDPOINT"), + ), ] ) @@ -42,4 +42,4 @@ async def test_main(): if __name__ == "__main__": - asyncio.run(test_main()) \ No newline at end of file + asyncio.run(test_main()) diff --git a/python/tracing/openai-agents-sdk/bridge_contract.py b/python/tracing/openai-agents-sdk/bridge_contract.py new file mode 100644 index 0000000..55ff0e4 --- /dev/null +++ b/python/tracing/openai-agents-sdk/bridge_contract.py @@ -0,0 +1,64 @@ +"""Focused lifecycle contract for the shared OpenAI Agents example bridge.""" + +from __future__ import annotations + +import asyncio + +import pytest + +import respan_exporter_openai_agents as bridge + + +def test_bridge_disables_direct_openai_auto_instrumentation(monkeypatch): + captured = None + + class FakeRespan: + def __init__(self, **kwargs): + nonlocal captured + captured = kwargs + + monkeypatch.setattr(bridge, "Respan", FakeRespan) + monkeypatch.setattr(bridge, "_RESPAN", None) + + instance = bridge._ensure_respan("test-key", "https://example.invalid/api") + + assert instance is not None + assert captured is not None + assert captured["is_auto_instrument"] is False + bridge._RESPAN = None + + +@pytest.mark.asyncio +async def test_gateway_client_is_retained_and_closed_on_its_owner_loop(monkeypatch): + owner_loop = asyncio.get_running_loop() + closed_on = None + + class FakeAsyncOpenAI: + def __init__(self, **_kwargs): + pass + + async def close(self): + nonlocal closed_on + closed_on = asyncio.get_running_loop() + + monkeypatch.delenv("RESPAN_OPENAI_AGENTS_USE_OPENAI", raising=False) + monkeypatch.setattr(bridge, "AsyncOpenAI", FakeAsyncOpenAI) + monkeypatch.setattr(bridge, "set_default_openai_api", lambda _value: None) + monkeypatch.setattr(bridge, "set_default_openai_client", lambda _client: None) + monkeypatch.setattr(bridge, "_GATEWAY_CLIENT", None) + monkeypatch.setattr(bridge, "_GATEWAY_CLIENT_CONFIGURED", False) + monkeypatch.setattr(bridge, "_GATEWAY_CLIENT_OWNER_LOOP", None) + + bridge._configure_gateway_client("test-key") + retained = bridge._GATEWAY_CLIENT + bridge._claim_gateway_client_loop() + + assert retained is not None + assert bridge._GATEWAY_CLIENT_OWNER_LOOP is owner_loop + + await bridge.shutdown_respan_async() + + assert closed_on is owner_loop + assert bridge._GATEWAY_CLIENT is None + assert bridge._GATEWAY_CLIENT_OWNER_LOOP is None + assert bridge._GATEWAY_CLIENT_CONFIGURED is False diff --git a/python/tracing/openai-agents-sdk/complex_edge_cases_test.py b/python/tracing/openai-agents-sdk/complex_edge_cases_test.py index b6d5e3a..c3c61c5 100644 --- a/python/tracing/openai-agents-sdk/complex_edge_cases_test.py +++ b/python/tracing/openai-agents-sdk/complex_edge_cases_test.py @@ -1,4 +1,3 @@ -#!/usr/bin/env python3 """ Complex Edge-Case Tracing Example — stress-tests the Respan OpenAI Agents SDK exporter. @@ -18,11 +17,6 @@ import json import os import time -from typing import Union - -from dotenv import load_dotenv, find_dotenv -from openai import AsyncOpenAI -from pydantic import BaseModel, Field from agents import ( Agent, @@ -35,36 +29,36 @@ function_tool, input_guardrail, output_guardrail, - set_default_openai_client, ) from agents.tracing import set_trace_processors, trace -from respan_exporter_openai_agents import RespanTraceProcessor +from dotenv import find_dotenv, load_dotenv +from pydantic import BaseModel, Field -load_dotenv(find_dotenv(), override=True) +from respan_exporter_openai_agents import RespanTraceProcessor, shutdown_respan_async + +load_dotenv(find_dotenv(), override=False) # ── Configuration ────────────────────────────────────────────────────────── RESPAN_BASE_URL = os.getenv("RESPAN_BASE_URL", "https://api.respan.ai/api").rstrip("/") RESPAN_API_KEY = os.getenv("RESPAN_API_KEY") -OPENAI_API_KEY = os.getenv("OPENAI_API_KEY") RESPAN_MODEL = os.getenv("RESPAN_MODEL", "gpt-4o") -# ── Gateway: route all OpenAI calls through Respan ───────────────────────── -client = AsyncOpenAI(api_key=OPENAI_API_KEY) -set_default_openai_client(client) - # ── Tracing: export spans to Respan ──────────────────────────────────────── -set_trace_processors([ - RespanTraceProcessor( - api_key=RESPAN_API_KEY, - default_model=RESPAN_MODEL, - ), -]) +set_trace_processors( + [ + RespanTraceProcessor( + api_key=RESPAN_API_KEY, + default_model=RESPAN_MODEL, + ), + ] +) # ═══════════════════════════════════════════════════════════════════════════ # TOOLS — each one probes a different serialization / error edge case # ═══════════════════════════════════════════════════════════════════════════ + @function_tool def get_weather(city: str) -> str: """Get weather for a city — returns normal string.""" @@ -83,8 +77,16 @@ def get_city_stats(city: str) -> str: "population": 13_960_000, "density_per_km2": 6_363, "districts": [ - {"name": "Shibuya", "pop": 230_000, "landmarks": ["Hachiko", "Scramble Crossing"]}, - {"name": "Shinjuku", "pop": 346_000, "landmarks": ["Kabukicho", "Gyoen"]}, + { + "name": "Shibuya", + "pop": 230_000, + "landmarks": ["Hachiko", "Scramble Crossing"], + }, + { + "name": "Shinjuku", + "pop": 346_000, + "landmarks": ["Kabukicho", "Gyoen"], + }, ], }, "coordinates": {"lat": 35.6762, "lon": 139.6503}, @@ -119,7 +121,7 @@ def get_localized_greeting(language: str) -> str: "japanese": "こんにちは世界！🌸 東京タワー\n\t— with tabs and newlines —", "arabic": "مرحبا بالعالم 🌍 — RTL text mixed with LTR", "emoji": "👨‍👩‍👧‍👦 Family emoji + 🏳️‍🌈 flag + 🇯🇵 regional indicators", - "special": 'Quotes: "double" \'single\' `backtick` — Slashes: \\ / — Angle: <>& — Tabs:\t\tEnd', + "special": "Quotes: \"double\" 'single' `backtick` — Slashes: \\ / — Angle: <>& — Tabs:\t\tEnd", } return greetings.get(language, f"Hello from {language}!") @@ -142,7 +144,9 @@ async def slow_database_query(query: str) -> str: @function_tool def get_secret_data(classification: str) -> str: """Always raises — tests that errored tool spans are captured.""" - raise PermissionError(f"Access denied: '{classification}' requires LEVEL-5 clearance") + raise PermissionError( + f"Access denied: '{classification}' requires LEVEL-5 clearance" + ) # EDGE CASE: Tool with extremely large output. @@ -151,9 +155,7 @@ def get_secret_data(classification: str) -> str: @function_tool def generate_large_report(topic: str) -> str: """Generate a ~50KB report to stress payload size limits.""" - paragraph = ( - f"Analysis of {topic}: " + "Lorem ipsum dolor sit amet, " * 50 + "\n" - ) + paragraph = f"Analysis of {topic}: " + "Lorem ipsum dolor sit amet, " * 50 + "\n" return paragraph * 30 # ~50KB @@ -161,6 +163,7 @@ def generate_large_report(topic: str) -> str: # GUARDRAILS — test both triggered and non-triggered paths # ═══════════════════════════════════════════════════════════════════════════ + class ContentCheckOutput(BaseModel): is_appropriate: bool reasoning: str @@ -183,7 +186,7 @@ class ContentCheckOutput(BaseModel): async def content_safety_guardrail( context: RunContextWrapper[None], agent: Agent, - input: Union[str, list[TResponseInputItem]], + input: str | list[TResponseInputItem], ) -> GuardrailFunctionOutput: """Guardrail that internally runs a sub-agent — tests nested span trees.""" result = await Runner.run(guardrail_checker, input, context=context.context) @@ -325,7 +328,13 @@ async def quality_gate_guardrail( "- Report generation → Report Agent\n" "NEVER answer directly — ALWAYS hand off." ), - handoffs=[weather_router, research_agent, analysis_agent, resilience_agent, report_agent], + handoffs=[ + weather_router, + research_agent, + analysis_agent, + resilience_agent, + report_agent, + ], input_guardrails=[content_safety_guardrail], ) @@ -369,6 +378,7 @@ async def quality_gate_guardrail( # SCENARIO RUNNERS # ═══════════════════════════════════════════════════════════════════════════ + async def run_scenario(name: str, coro): """Run a scenario with error isolation so one failure doesn't kill the rest.""" print(f"\n{'─' * 60}") @@ -379,8 +389,8 @@ async def run_scenario(name: str, coro): print(f" ✓ {name} completed") except (InputGuardrailTripwireTriggered, OutputGuardrailTripwireTriggered) as e: print(f" ⚠ {name} — guardrail tripped (expected): {type(e).__name__}") - except Exception as e: - print(f" ✗ {name} — error (testing resilience): {type(e).__name__}: {e}") + except Exception as error: # noqa: BLE001 - every scenario must continue. + print(f" ✗ {name} — error (testing resilience): {type(error).__name__}") async def scenario_handoff_chain(): @@ -466,8 +476,8 @@ async def scenario_rapid_sequential_runs(): instructions="Reply with exactly one word.", ) for i in range(5): - result = await Runner.run(simple, f"Word #{i+1}: give me a color name") - print(f" Run {i+1}: {result.final_output}") + result = await Runner.run(simple, f"Word #{i + 1}: give me a color name") + print(f" Run {i + 1}: {result.final_output}") async def scenario_concurrent_sub_traces(): @@ -548,6 +558,7 @@ async def scenario_zero_duration_spans(): # MAIN # ═══════════════════════════════════════════════════════════════════════════ + async def main(): print("=" * 60) print(" COMPLEX EDGE-CASE TRACING EXAMPLE") @@ -560,7 +571,6 @@ async def main(): start = time.time() with trace("Edge Case Stress Test"): - # ── Handoff chain (Handoff + Agent + Response + Generation) ──── await run_scenario( "Three-level handoff chain", @@ -636,12 +646,19 @@ async def main(): elapsed = time.time() - start print(f"\n{'=' * 60}") print(f" ALL SCENARIOS COMPLETE — {elapsed:.1f}s elapsed") - print(f" Waiting 5s for batch processor to flush...") + print(" Waiting 5s for batch processor to flush...") print(f"{'=' * 60}") await asyncio.sleep(5) print("\n Done! Check your Respan dashboard for the trace.") +async def _main_and_shutdown(): + try: + await main() + finally: + await shutdown_respan_async() + + if __name__ == "__main__": - asyncio.run(main()) + asyncio.run(_main_and_shutdown()) diff --git a/python/tracing/openai-agents-sdk/conftest.py b/python/tracing/openai-agents-sdk/conftest.py index 792df4e..f45e84d 100644 --- a/python/tracing/openai-agents-sdk/conftest.py +++ b/python/tracing/openai-agents-sdk/conftest.py @@ -1,8 +1,70 @@ -"""Pytest import helpers for nested OpenAI Agents example files.""" +"""Shared import, marker, and lifecycle helpers for the example suite.""" -from pathlib import Path +import os import sys +from pathlib import Path + +import pytest +import pytest_asyncio ROOT = Path(__file__).resolve().parent if str(ROOT) not in sys.path: sys.path.insert(0, str(ROOT)) + +# These legacy entry points are executed once as standalone processes by +# ``run_all.py`` so their module-global setup and explicit shutdown are tested. +# Excluding them here prevents duplicate traces under the same exact marker. +collect_ignore = [ + "complex_edge_cases_test.py", + "handoffs/message_filter_streaming_test.py", + "handoffs/message_filter_test.py", +] + +_CONTRACT_ONLY_FILES = { + "bridge_contract.py", + "contract_scenarios_test.py", + "runner_contract.py", +} + + +@pytest.fixture(autouse=True) +def _flush_after_example(): + yield + from respan_exporter_openai_agents import flush_respan + + flush_respan() + + +@pytest_asyncio.fixture(scope="session", autouse=True, loop_scope="session") +async def _shutdown_clients_after_session(): + yield + from respan_exporter_openai_agents import shutdown_respan_async + + await shutdown_respan_async() + + +def pytest_collection_modifyitems(items): + from respan_exporter_openai_agents import has_direct_responses_credentials + + direct_responses = has_direct_responses_credentials() + for item in items: + relative = item.path.relative_to(ROOT).as_posix() + if relative not in _CONTRACT_ONLY_FILES: + item.add_marker(pytest.mark.live) + + reason = None + eligible = direct_responses + if relative in {"tools/web_search_test.py", "research_bot/main_test.py"}: + reason = "requires a direct OpenAI Responses API credential" + elif relative == "tools/file_search_test.py": + reason = "requires direct Responses credentials and OPENAI_VECTOR_STORE_ID" + eligible = eligible and bool(os.getenv("OPENAI_VECTOR_STORE_ID")) + elif relative == "tools/computer_use_test.py": + reason = "requires direct Responses credentials and an enabled Playwright browser" + eligible = eligible and ( + os.getenv("RESPAN_OPENAI_AGENTS_ENABLE_COMPUTER") == "1" + ) + if reason: + item.add_marker(pytest.mark.hosted) + if not eligible: + item.add_marker(pytest.mark.skip(reason=reason)) diff --git a/python/tracing/openai-agents-sdk/contract_scenarios_test.py b/python/tracing/openai-agents-sdk/contract_scenarios_test.py new file mode 100644 index 0000000..dd7e49b --- /dev/null +++ b/python/tracing/openai-agents-sdk/contract_scenarios_test.py @@ -0,0 +1,166 @@ +"""Deterministic current-SDK traces for content-level instrumentation checks.""" + +# ruff: noqa: SIM117 - nesting is the span-tree contract under test. + +from __future__ import annotations + +import os + +from agents.tracing import ( + SpanError, + agent_span, + function_span, + generation_span, + guardrail_span, + handoff_span, + set_trace_processors, + task_span, + trace, + turn_span, +) + +from respan_exporter_openai_agents import RespanTraceProcessor + +set_trace_processors( + [ + RespanTraceProcessor( + os.getenv("RESPAN_API_KEY"), + endpoint=os.getenv("RESPAN_OAIA_TRACING_ENDPOINT"), + ) + ] +) + + +def _metadata(scenario: str) -> dict[str, str]: + marker = os.environ["RESPAN_EXAMPLE_RUN_ID"] + return {"example_run_id": marker, "scenario": scenario} + + +def test_success_structure(): + with trace("openai-agents.success", metadata=_metadata("success")): + with task_span("successful agent run"): + with agent_span("Assistant", output_type="str"): + with turn_span(1, "Assistant"): + with generation_span( + input=[{"role": "user", "content": "Say hello."}], + output=[{"role": "assistant", "content": "Hello!"}], + model="gpt-4o-mini", + usage={ + "input_tokens": 4, + "output_tokens": 2, + "total_tokens": 6, + }, + ): + pass + + +def test_function_tool_structure(): + with trace("openai-agents.tool", metadata=_metadata("tool")): + with task_span("tool agent run"): + with agent_span("Weather Agent", tools=["get_weather"]): + with turn_span(1, "Weather Agent"): + with generation_span( + input=[ + { + "role": "user", + "content": "What is the weather in Tokyo?", + } + ], + output=[ + { + "role": "assistant", + "content": None, + "tool_calls": [ + { + "id": "call_weather_1", + "type": "function", + "function": { + "name": "get_weather", + "arguments": '{"city":"Tokyo"}', + }, + } + ], + } + ], + model="gpt-4o-mini", + usage={"input_tokens": 10, "output_tokens": 5}, + ): + pass + with function_span( + "get_weather", + input='{"city":"Tokyo"}', + output='{"condition":"sunny","temperature_c":22}', + ): + pass + + +def test_handoff_structure(): + with trace("openai-agents.handoff", metadata=_metadata("handoff")): + with task_span("handoff agent run"): + with agent_span("Triage", handoffs=["Spanish Assistant"]): + with turn_span(1, "Triage"): + with generation_span( + input=[{"role": "user", "content": "Hola"}], + output=[ + { + "type": "function_call", + "call_id": "call_handoff_1", + "name": "transfer_to_spanish_assistant", + "arguments": "{}", + } + ], + model="gpt-4o-mini", + ): + pass + with handoff_span("Triage", "Spanish Assistant"): + pass + with agent_span("Spanish Assistant"): + with turn_span(2, "Spanish Assistant"): + with generation_span( + input=[{"role": "user", "content": "Hola"}], + output=[{"role": "assistant", "content": "¡Hola!"}], + model="gpt-4o-mini", + ): + pass + + +def test_guardrail_and_provider_failure_structure(): + with trace("openai-agents.failure", metadata=_metadata("failure")): + with task_span("failed agent run"): + with agent_span("Guarded Agent"): + with guardrail_span("safe_input", triggered=True): + pass + with ( + turn_span(1, "Guarded Agent"), + generation_span( + input=[{"role": "user", "content": "Trigger failure"}], + model="gpt-4o-mini", + ) as failed, + ): + failed.set_error( + SpanError( + message="Provider temporarily unavailable", + data={"status_code": 503}, + ) + ) + + +def test_streaming_structure(): + with trace("openai-agents.stream", metadata=_metadata("stream")): + with task_span("streaming agent run"): + with agent_span("Streaming Agent"): + with turn_span(1, "Streaming Agent"): + with generation_span( + input=[{"role": "user", "content": "Stream a greeting."}], + output=[ + {"role": "assistant", "content": "Hello from a stream!"} + ], + model="gpt-4o-mini", + model_config={"stream": True}, + usage={ + "input_tokens": 5, + "output_tokens": 5, + "total_tokens": 10, + }, + ): + pass diff --git a/python/tracing/openai-agents-sdk/customer_service/main_test.py b/python/tracing/openai-agents-sdk/customer_service/main_test.py index 5b30738..04b229d 100644 --- a/python/tracing/openai-agents-sdk/customer_service/main_test.py +++ b/python/tracing/openai-agents-sdk/customer_service/main_test.py @@ -1,16 +1,15 @@ from __future__ import annotations as _annotations + from dotenv import load_dotenv -load_dotenv(override=True) +load_dotenv(override=False) endpoint = "http://localhost:8000/api/openai/v1/traces/ingest" -import pytest -import os import asyncio +import os import random import uuid -from pydantic import BaseModel - +import pytest from agents import ( Agent, HandoffOutputItem, @@ -26,32 +25,40 @@ trace, ) from agents.extensions.handoff_prompt import RECOMMENDED_PROMPT_PREFIX +from agents.tracing import set_trace_processors +from pydantic import BaseModel + from respan_exporter_openai_agents import ( RespanTraceProcessor, ) -from agents.tracing import set_trace_processors -from typing import Union -load_dotenv(override=True) + +load_dotenv(override=False) set_trace_processors( - [RespanTraceProcessor(os.getenv("RESPAN_API_KEY"), endpoint=os.getenv("RESPAN_OAIA_TRACING_ENDPOINT"))] + [ + RespanTraceProcessor( + os.getenv("RESPAN_API_KEY"), + endpoint=os.getenv("RESPAN_OAIA_TRACING_ENDPOINT"), + ) + ] ) ### CONTEXT class AirlineAgentContext(BaseModel): - passenger_name: Union[str, None] = None - confirmation_number: Union[str, None] = None - seat_number: Union[str, None] = None - flight_number: Union[str, None] = None + passenger_name: str | None = None + confirmation_number: str | None = None + seat_number: str | None = None + flight_number: str | None = None ### TOOLS @function_tool( - name_override="faq_lookup_tool", description_override="Lookup frequently asked questions." + name_override="faq_lookup_tool", + description_override="Lookup frequently asked questions.", ) async def faq_lookup_tool(question: str) -> str: if "bag" in question or "baggage" in question: @@ -73,7 +80,9 @@ async def faq_lookup_tool(question: str) -> str: @function_tool async def update_seat( - context: RunContextWrapper[AirlineAgentContext], confirmation_number: str, new_seat: str + context: RunContextWrapper[AirlineAgentContext], + confirmation_number: str, + new_seat: str, ) -> str: """ Update the seat for a given confirmation number. @@ -93,7 +102,9 @@ async def update_seat( ### HOOKS -async def on_seat_booking_handoff(context: RunContextWrapper[AirlineAgentContext]) -> None: +async def on_seat_booking_handoff( + context: RunContextWrapper[AirlineAgentContext], +) -> None: flight_number = f"FLT-{random.randint(100, 999)}" context.context.flight_number = flight_number @@ -158,7 +169,6 @@ async def test_main(): conversation_id = uuid.uuid4().hex[:16] questions = ["I need to change my seat", "Can you confirm my flight number?", ""] with trace("Customer service", group_id=conversation_id): - for question in questions: user_input = question if question == "": @@ -184,6 +194,5 @@ async def test_main(): current_agent = result.last_agent - if __name__ == "__main__": asyncio.run(test_main()) diff --git a/python/tracing/openai-agents-sdk/handoffs/handsoff_test.py b/python/tracing/openai-agents-sdk/handoffs/handsoff_test.py index 2f8286d..4c6e2cf 100644 --- a/python/tracing/openai-agents-sdk/handoffs/handsoff_test.py +++ b/python/tracing/openai-agents-sdk/handoffs/handsoff_test.py @@ -1,13 +1,17 @@ from dotenv import load_dotenv -load_dotenv(override=True) +load_dotenv(override=False) +import asyncio +import os + import pytest + # ==========copy the below========== from agents import Agent, Runner -import asyncio -from respan_exporter_openai_agents import RespanTraceProcessor from agents.tracing import set_trace_processors, trace -import os + +from respan_exporter_openai_agents import RespanTraceProcessor + set_trace_processors( [ RespanTraceProcessor( @@ -41,5 +45,6 @@ async def test_main(): print(result.final_output) # ¡Hola! Estoy bien, gracias por preguntar. ¿Y tú, cómo estás? + if __name__ == "__main__": - asyncio.run(test_main()) \ No newline at end of file + asyncio.run(test_main()) diff --git a/python/tracing/openai-agents-sdk/handoffs/message_filter_streaming_test.py b/python/tracing/openai-agents-sdk/handoffs/message_filter_streaming_test.py index 2ff9f41..8304b11 100644 --- a/python/tracing/openai-agents-sdk/handoffs/message_filter_streaming_test.py +++ b/python/tracing/openai-agents-sdk/handoffs/message_filter_streaming_test.py @@ -1,23 +1,37 @@ from __future__ import annotations + from dotenv import load_dotenv -load_dotenv(override=True) -import pytest +load_dotenv(override=False) + endpoint = "http://localhost:8000/api/openai/v1/traces/ingest" -import os import json +import os import random +import sys +from pathlib import Path + +ROOT = Path(__file__).resolve().parents[1] +if str(ROOT) not in sys.path: + sys.path.insert(0, str(ROOT)) from agents import Agent, HandoffInputData, Runner, function_tool, handoff, trace from agents.extensions import handoff_filters +from agents.tracing import set_trace_processors + from respan_exporter_openai_agents import ( RespanTraceProcessor, + shutdown_respan_async, ) -from agents.tracing import set_trace_processors set_trace_processors( - [RespanTraceProcessor(os.getenv("RESPAN_API_KEY"), endpoint=os.getenv("RESPAN_OAIA_TRACING_ENDPOINT"))] + [ + RespanTraceProcessor( + os.getenv("RESPAN_API_KEY"), + endpoint=os.getenv("RESPAN_OAIA_TRACING_ENDPOINT"), + ) + ] ) @@ -191,7 +205,14 @@ async def main(): """ +async def _main_and_shutdown(): + try: + await main() + finally: + await shutdown_respan_async() + + if __name__ == "__main__": import asyncio - asyncio.run(main()) + asyncio.run(_main_and_shutdown()) diff --git a/python/tracing/openai-agents-sdk/handoffs/message_filter_test.py b/python/tracing/openai-agents-sdk/handoffs/message_filter_test.py index 2b34df0..13d53dd 100644 --- a/python/tracing/openai-agents-sdk/handoffs/message_filter_test.py +++ b/python/tracing/openai-agents-sdk/handoffs/message_filter_test.py @@ -1,17 +1,25 @@ from __future__ import annotations + from dotenv import load_dotenv -load_dotenv(override=True) +load_dotenv(override=False) # =============Only copy the below for docs============= # from __future__ import annotations import os import random +import sys +from pathlib import Path + +ROOT = Path(__file__).resolve().parents[1] +if str(ROOT) not in sys.path: + sys.path.insert(0, str(ROOT)) + from agents import Agent, HandoffInputData, Runner, function_tool, handoff, trace from agents.extensions import handoff_filters -from respan_exporter_openai_agents import RespanTraceProcessor from agents.tracing import set_trace_processors +from respan_exporter_openai_agents import RespanTraceProcessor, shutdown_respan_async set_trace_processors( [ @@ -193,9 +201,14 @@ async def main(): """ -import time +async def _main_and_shutdown(): + try: + await main() + finally: + await shutdown_respan_async() + if __name__ == "__main__": import asyncio - asyncio.run(main()) + asyncio.run(_main_and_shutdown()) diff --git a/python/tracing/openai-agents-sdk/poetry.lock b/python/tracing/openai-agents-sdk/poetry.lock index c12e2cd..362fc80 100644 --- a/python/tracing/openai-agents-sdk/poetry.lock +++ b/python/tracing/openai-agents-sdk/poetry.lock @@ -60,6 +60,118 @@ files = [ {file = "certifi-2025.8.3.tar.gz", hash = "sha256:e564105f78ded564e3ae7c923924435e1daa7463faeab5bb932bc53ffae63407"}, ] +[[package]] +name = "cffi" +version = "2.1.1" +description = "Foreign Function Interface for Python calling C code." +optional = false +python-versions = ">=3.10" +files = [ + {file = "cffi-2.1.1-cp310-cp310-macosx_10_15_x86_64.whl", hash = "sha256:baed1e86cc735622097354b9d1281406caf42ff42a886d29faa8e8d1630333be"}, + {file = "cffi-2.1.1-cp310-cp310-macosx_11_0_arm64.whl", hash = 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respan-instrumentation-openai-agents = ">=1.1.1" -python-dotenv = "^1.0.0" +python-dotenv = ">=1.0.0,<2.0.0" +rich = ">=13.0.0,<16.0.0" +playwright = ">=1.50.0,<2.0.0" [tool.poetry.group.dev.dependencies] -pytest = "^8.4.2" -pytest-asyncio = "^0.24.0" +pytest = ">=8.4.0,<10.0.0" +pytest-asyncio = ">=0.24.0,<2.0.0" + +[tool.pytest.ini_options] +asyncio_default_test_loop_scope = "session" +markers = [ + "hosted: requires a direct OpenAI Responses API credential or hosted resource", + "live: performs a configured provider or gateway request", +] + +[tool.ruff.lint.per-file-ignores] +"__init__.py" = ["N999"] [build-system] requires = ["poetry-core"] diff --git a/python/tracing/openai-agents-sdk/requirements.txt b/python/tracing/openai-agents-sdk/requirements.txt new file mode 100644 index 0000000..b008afb --- /dev/null +++ b/python/tracing/openai-agents-sdk/requirements.txt @@ -0,0 +1,8 @@ +openai-agents>=0.20.0,<0.21.0 +playwright>=1.50.0,<2.0.0 +pytest>=8.4.0,<10.0.0 +pytest-asyncio>=0.24.0,<2.0.0 +python-dotenv>=1.0.0,<2.0.0 +respan-ai>=4.1.0,<5.0.0 +respan-instrumentation-openai-agents>=1.1.1 +rich>=13.0.0,<16.0.0 diff --git a/python/tracing/openai-agents-sdk/research_bot/agents/planner_agent.py b/python/tracing/openai-agents-sdk/research_bot/agents/planner_agent.py index e80a8e6..3c2929c 100644 --- a/python/tracing/openai-agents-sdk/research_bot/agents/planner_agent.py +++ b/python/tracing/openai-agents-sdk/research_bot/agents/planner_agent.py @@ -1,6 +1,5 @@ -from pydantic import BaseModel - from agents import Agent +from pydantic import BaseModel PROMPT = ( "You are a helpful research assistant. Given a query, come up with a set of web searches " diff --git a/python/tracing/openai-agents-sdk/research_bot/agents/writer_agent.py b/python/tracing/openai-agents-sdk/research_bot/agents/writer_agent.py index 7b7d01a..1f2e6db 100644 --- a/python/tracing/openai-agents-sdk/research_bot/agents/writer_agent.py +++ b/python/tracing/openai-agents-sdk/research_bot/agents/writer_agent.py @@ -1,7 +1,6 @@ # Agent used to synthesize a final report from the individual summaries. -from pydantic import BaseModel - from agents import Agent +from pydantic import BaseModel PROMPT = ( "You are a senior researcher tasked with writing a cohesive report for a research query. " diff --git a/python/tracing/openai-agents-sdk/research_bot/main_test.py b/python/tracing/openai-agents-sdk/research_bot/main_test.py index 052b1c7..30751a5 100644 --- a/python/tracing/openai-agents-sdk/research_bot/main_test.py +++ b/python/tracing/openai-agents-sdk/research_bot/main_test.py @@ -1,19 +1,25 @@ from dotenv import load_dotenv -loaded = load_dotenv(override=True) -import pytest -import os +loaded = load_dotenv(override=False) import asyncio +import os - -from .manager import ResearchManager +import pytest from agents import set_trace_processors + from respan_exporter_openai_agents import ( RespanTraceProcessor, ) +from .manager import ResearchManager + set_trace_processors( - [RespanTraceProcessor(os.getenv("RESPAN_API_KEY"), endpoint=os.getenv("RESPAN_OAIA_TRACING_ENDPOINT"))] + [ + RespanTraceProcessor( + os.getenv("RESPAN_API_KEY"), + endpoint=os.getenv("RESPAN_OAIA_TRACING_ENDPOINT"), + ) + ] ) diff --git a/python/tracing/openai-agents-sdk/research_bot/manager.py b/python/tracing/openai-agents-sdk/research_bot/manager.py index c2bba9f..47f5118 100644 --- a/python/tracing/openai-agents-sdk/research_bot/manager.py +++ b/python/tracing/openai-agents-sdk/research_bot/manager.py @@ -3,15 +3,14 @@ import asyncio import time -from rich.console import Console - from agents import Runner, custom_span, gen_trace_id, trace +from rich.console import Console from .agents.planner_agent import WebSearchItem, WebSearchPlan, planner_agent from .agents.search_agent import search_agent from .agents.writer_agent import ReportData, writer_agent from .printer import Printer -from typing import Union + class ResearchManager: def __init__(self): @@ -65,21 +64,21 @@ async def _plan_searches(self, query: str) -> WebSearchPlan: async def _perform_searches(self, search_plan: WebSearchPlan) -> list[str]: with custom_span("Search the web"): self.printer.update_item("searching", "Searching...") - num_completed = 0 - tasks = [asyncio.create_task(self._search(item)) for item in search_plan.searches] + tasks = [ + asyncio.create_task(self._search(item)) for item in search_plan.searches + ] results = [] - for task in asyncio.as_completed(tasks): + for num_completed, task in enumerate(asyncio.as_completed(tasks), start=1): result = await task if result is not None: results.append(result) - num_completed += 1 self.printer.update_item( "searching", f"Searching... {num_completed}/{len(tasks)} completed" ) self.printer.mark_item_done("searching") return results - async def _search(self, item: WebSearchItem) -> Union[str, None]: + async def _search(self, item: WebSearchItem) -> str | None: input = f"Search term: {item.query}\nReason for searching: {item.reason}" try: result = await Runner.run( @@ -87,7 +86,7 @@ async def _search(self, item: WebSearchItem) -> Union[str, None]: input, ) return str(result.final_output) - except Exception: + except Exception: # noqa: BLE001 - one failed search must not abort the report. return None async def _write_report(self, query: str, search_results: list[str]) -> ReportData: diff --git a/python/tracing/openai-agents-sdk/research_bot/printer.py b/python/tracing/openai-agents-sdk/research_bot/printer.py index e820c75..fa448e7 100644 --- a/python/tracing/openai-agents-sdk/research_bot/printer.py +++ b/python/tracing/openai-agents-sdk/research_bot/printer.py @@ -19,7 +19,11 @@ def hide_done_checkmark(self, item_id: str) -> None: self.hide_done_ids.add(item_id) def update_item( - self, item_id: str, content: str, is_done: bool = False, hide_checkmark: bool = False + self, + item_id: str, + content: str, + is_done: bool = False, + hide_checkmark: bool = False, ) -> None: self.items[item_id] = (content, is_done) if hide_checkmark: diff --git a/python/tracing/openai-agents-sdk/respan_exporter_openai_agents.py b/python/tracing/openai-agents-sdk/respan_exporter_openai_agents.py index d2e578e..b055e67 100644 --- a/python/tracing/openai-agents-sdk/respan_exporter_openai_agents.py +++ b/python/tracing/openai-agents-sdk/respan_exporter_openai_agents.py @@ -8,19 +8,25 @@ from __future__ import annotations +import asyncio import os from typing import Any +from agents import set_default_openai_api, set_default_openai_client from dotenv import find_dotenv, load_dotenv from openai import AsyncOpenAI -from agents import set_default_openai_api, set_default_openai_client from respan import Respan -from respan_instrumentation_openai_agents._instrumentation import _RespanTracingProcessor +from respan_instrumentation_openai_agents._instrumentation import ( + _install_stream_patches, + _RespanTracingProcessor, +) -load_dotenv(find_dotenv(), override=True) +load_dotenv(find_dotenv(), override=False) _RESPAN: Respan | None = None _GATEWAY_CLIENT_CONFIGURED = False +_GATEWAY_CLIENT: AsyncOpenAI | None = None +_GATEWAY_CLIENT_OWNER_LOOP: asyncio.AbstractEventLoop | None = None def _clean_url(value: str | None, default: str) -> str: @@ -28,7 +34,7 @@ def _clean_url(value: str | None, default: str) -> str: def _configure_gateway_client(api_key: str | None) -> None: - global _GATEWAY_CLIENT_CONFIGURED + global _GATEWAY_CLIENT, _GATEWAY_CLIENT_CONFIGURED if _GATEWAY_CLIENT_CONFIGURED: return @@ -47,25 +53,58 @@ def _configure_gateway_client(api_key: str | None) -> None: set_default_openai_api("chat_completions") os.environ["OPENAI_API_KEY"] = gateway_api_key os.environ["OPENAI_BASE_URL"] = gateway_base_url - set_default_openai_client( - AsyncOpenAI(api_key=gateway_api_key, base_url=os.environ["OPENAI_BASE_URL"]) + _GATEWAY_CLIENT = AsyncOpenAI( + api_key=gateway_api_key, base_url=os.environ["OPENAI_BASE_URL"] ) + set_default_openai_client(_GATEWAY_CLIENT) _GATEWAY_CLIENT_CONFIGURED = True +def _claim_gateway_client_loop() -> None: + """Bind the retained async client to the loop that first uses an Agent trace.""" + global _GATEWAY_CLIENT_OWNER_LOOP + if _GATEWAY_CLIENT is None: + return + try: + current_loop = asyncio.get_running_loop() + except RuntimeError: + return + if _GATEWAY_CLIENT_OWNER_LOOP is None: + _GATEWAY_CLIENT_OWNER_LOOP = current_loop + elif _GATEWAY_CLIENT_OWNER_LOOP is not current_loop: + raise RuntimeError( + "The shared OpenAI Agents client must stay on its owning event loop" + ) + + +def has_direct_responses_credentials() -> bool: + """Return whether hosted Responses tools can run without gateway coercion.""" + return os.getenv("RESPAN_OPENAI_AGENTS_USE_OPENAI") == "1" and bool( + os.getenv("OPENAI_API_KEY") + ) + + def _ensure_respan(api_key: str | None, base_url: str | None) -> Respan | None: global _RESPAN if _RESPAN is not None: return _RESPAN - resolved_api_key = api_key or os.getenv("RESPAN_API_KEY") or os.getenv("RESPAN_GATEWAY_API_KEY") + resolved_api_key = ( + api_key or os.getenv("RESPAN_API_KEY") or os.getenv("RESPAN_GATEWAY_API_KEY") + ) if not resolved_api_key: return None _RESPAN = Respan( app_name=os.getenv("RESPAN_APP_NAME", "openai-agents-sdk-examples"), api_key=resolved_api_key, - base_url=_clean_url(base_url or os.getenv("RESPAN_BASE_URL"), "https://api.respan.ai/api"), + base_url=_clean_url( + base_url or os.getenv("RESPAN_BASE_URL"), "https://api.respan.ai/api" + ), + # The explicit Agents trace processor owns provider-call coverage. + # Direct OpenAI auto-instrumentation would duplicate its chat spans. + is_auto_instrument=False, + log_level=os.getenv("RESPAN_LOG_LEVEL", "WARNING"), ) return _RESPAN @@ -81,14 +120,22 @@ def __init__( default_model: str | None = None, **_: Any, ) -> None: - super().__init__() + marker = os.getenv("RESPAN_EXAMPLE_RUN_ID") + super().__init__( + metadata={"example_run_id": marker} if marker else None, + ) self.api_key = api_key or os.getenv("RESPAN_API_KEY") self.endpoint = endpoint self.base_url = base_url self.default_model = default_model or os.getenv("RESPAN_MODEL") self._respan = _ensure_respan(self.api_key, base_url) + _install_stream_patches() _configure_gateway_client(self.api_key) + def on_trace_start(self, trace) -> None: + _claim_gateway_client_loop() + return super().on_trace_start(trace) + def shutdown(self) -> None: if self._respan is not None: self._respan.flush() @@ -96,3 +143,37 @@ def shutdown(self) -> None: def force_flush(self) -> None: if self._respan is not None: self._respan.flush() + + +def flush_respan() -> None: + """Flush all example spans without closing the shared test-session client.""" + if _RESPAN is not None: + _RESPAN.flush() + + +async def shutdown_respan_async() -> None: + """Close the exporter and retained gateway client on its owning event loop.""" + global _GATEWAY_CLIENT, _GATEWAY_CLIENT_CONFIGURED + global _GATEWAY_CLIENT_OWNER_LOOP, _RESPAN + + try: + if _RESPAN is not None: + _RESPAN.shutdown() + _RESPAN = None + finally: + client = _GATEWAY_CLIENT + if client is None: + _GATEWAY_CLIENT_CONFIGURED = False + else: + current_loop = asyncio.get_running_loop() + if ( + _GATEWAY_CLIENT_OWNER_LOOP is not None + and _GATEWAY_CLIENT_OWNER_LOOP is not current_loop + ): + raise RuntimeError( + "The shared OpenAI Agents client must close on its owning event loop" + ) + await client.close() + _GATEWAY_CLIENT = None + _GATEWAY_CLIENT_OWNER_LOOP = None + _GATEWAY_CLIENT_CONFIGURED = False diff --git a/python/tracing/openai-agents-sdk/run_all.py b/python/tracing/openai-agents-sdk/run_all.py new file mode 100644 index 0000000..342112f --- /dev/null +++ b/python/tracing/openai-agents-sdk/run_all.py @@ -0,0 +1,84 @@ +"""Run every collected and legacy direct OpenAI Agents example with one marker.""" + +from __future__ import annotations + +import os +import subprocess +import sys +from datetime import datetime, timezone +from pathlib import Path + +from dotenv import find_dotenv, load_dotenv + +ROOT = Path(__file__).resolve().parent +load_dotenv(find_dotenv(), override=False) +DEFAULT_COMMAND_TIMEOUT_SECONDS = 300 + + +def _marker() -> str: + existing = os.getenv("RESPAN_EXAMPLE_RUN_ID") + if existing: + return existing + timestamp = datetime.now(timezone.utc).strftime("%Y%m%dT%H%M%SZ") + return f"otel2-openai-agents-{timestamp}" + + +def _timeout_seconds() -> int: + raw = os.getenv("RESPAN_EXAMPLE_COMMAND_TIMEOUT_SECONDS", "") + try: + value = int(raw) + except ValueError: + return DEFAULT_COMMAND_TIMEOUT_SECONDS + return value if value > 0 else DEFAULT_COMMAND_TIMEOUT_SECONDS + + +def _run_commands( + commands: list[list[str]], *, env: dict[str, str], timeout_seconds: int +) -> list[tuple[list[str], str]]: + failures: list[tuple[list[str], str]] = [] + for index, command in enumerate(commands, start=1): + print(f"[{index}/{len(commands)}] {' '.join(command)}", flush=True) + try: + completed = subprocess.run( + command, + cwd=ROOT, + env=env, + check=False, + timeout=timeout_seconds, + ) + except subprocess.TimeoutExpired: + detail = f"timeout after {timeout_seconds}s" + print(detail, flush=True) + failures.append((command, detail)) + continue + print(f"exit={completed.returncode}", flush=True) + if completed.returncode: + failures.append((command, f"exit={completed.returncode}")) + return failures + + +def main() -> int: + marker = _marker() + env = { + **os.environ, + "PYTHONDONTWRITEBYTECODE": "1", + "RESPAN_EXAMPLE_RUN_ID": marker, + } + commands = [ + [sys.executable, "-m", "pytest", "-q", "-p", "no:cacheprovider"], + [sys.executable, "handoffs/message_filter_test.py"], + [sys.executable, "handoffs/message_filter_streaming_test.py"], + [sys.executable, "complex_edge_cases_test.py"], + ] + print(f"RESPAN_EXAMPLE_RUN_ID={marker}", flush=True) + failures = _run_commands(commands, env=env, timeout_seconds=_timeout_seconds()) + if failures: + print("OpenAI Agents example failures:", flush=True) + for command, detail in failures: + print(f" {detail}: {' '.join(command)}", flush=True) + return 1 + return 0 + + +if __name__ == "__main__": + raise SystemExit(main()) diff --git a/python/tracing/openai-agents-sdk/runner_contract.py b/python/tracing/openai-agents-sdk/runner_contract.py new file mode 100644 index 0000000..47e6609 --- /dev/null +++ b/python/tracing/openai-agents-sdk/runner_contract.py @@ -0,0 +1,26 @@ +"""Focused contract checks for the bounded all-example runner.""" + +from __future__ import annotations + +import subprocess + +import run_all + + +def test_timeout_is_reported_without_stopping_later_commands(monkeypatch, capsys): + calls: list[list[str]] = [] + + def fake_run(command, **_kwargs): + calls.append(command) + if len(calls) == 1: + raise subprocess.TimeoutExpired(command, timeout=7) + return subprocess.CompletedProcess(command, returncode=0) + + monkeypatch.setattr(run_all.subprocess, "run", fake_run) + commands = [["python", "slow.py"], ["python", "next.py"]] + + failures = run_all._run_commands(commands, env={}, timeout_seconds=7) + + assert calls == commands + assert failures == [(commands[0], "timeout after 7s")] + assert "[2/2] python next.py" in capsys.readouterr().out diff --git a/python/tracing/openai-agents-sdk/tools/computer_use_test.py b/python/tracing/openai-agents-sdk/tools/computer_use_test.py index 322d5c1..4359970 100644 --- a/python/tracing/openai-agents-sdk/tools/computer_use_test.py +++ b/python/tracing/openai-agents-sdk/tools/computer_use_test.py @@ -1,15 +1,12 @@ from dotenv import load_dotenv -load_dotenv(override=True) -import pytest -import os +load_dotenv(override=False) import asyncio import base64 -import logging -from typing import Literal, Union - -from playwright.async_api import Browser, Page, Playwright, async_playwright +import os +from typing import Literal +import pytest from agents import ( Agent, AsyncComputer, @@ -21,17 +18,21 @@ trace, ) from agents.tracing import set_trace_processors +from playwright.async_api import Browser, Page, Playwright, async_playwright + from respan_exporter_openai_agents import ( RespanTraceProcessor, ) set_trace_processors( - [RespanTraceProcessor(os.getenv("RESPAN_API_KEY"), endpoint=os.getenv("RESPAN_OAIA_TRACING_ENDPOINT"))] + [ + RespanTraceProcessor( + os.getenv("RESPAN_API_KEY"), + endpoint=os.getenv("RESPAN_OAIA_TRACING_ENDPOINT"), + ) + ] ) -logging.getLogger("openai.agents").setLevel(logging.DEBUG) -logging.getLogger("openai.agents").addHandler(logging.StreamHandler()) - @pytest.mark.asyncio async def test_main(): @@ -45,7 +46,9 @@ async def test_main(): model="computer-use-preview", model_settings=ModelSettings(truncation="auto"), ) - result = await Runner.run(agent, "Search who is the president of the United States now") + result = await Runner.run( + agent, "Search who is the president of the United States now" + ) print(result.final_output) @@ -82,9 +85,9 @@ class LocalPlaywrightComputer(AsyncComputer): """A computer, implemented using a local Playwright browser.""" def __init__(self): - self._playwright: Union[Playwright, None] = None - self._browser: Union[Browser, None] = None - self._page: Union[Page, None] = None + self._playwright: Playwright | None = None + self._browser: Browser | None = None + self._page: Page | None = None async def _get_browser_and_page(self) -> tuple[Browser, Page]: width, height = self.dimensions diff --git a/python/tracing/openai-agents-sdk/tools/file_search_test.py b/python/tracing/openai-agents-sdk/tools/file_search_test.py index 567dc33..722ac06 100644 --- a/python/tracing/openai-agents-sdk/tools/file_search_test.py +++ b/python/tracing/openai-agents-sdk/tools/file_search_test.py @@ -1,18 +1,24 @@ from dotenv import load_dotenv -load_dotenv(override=True) -import pytest -import os +load_dotenv(override=False) import asyncio +import os +import pytest from agents import Agent, FileSearchTool, Runner, trace from agents.tracing import set_trace_processors + from respan_exporter_openai_agents import ( RespanTraceProcessor, ) set_trace_processors( - [RespanTraceProcessor(os.getenv("RESPAN_API_KEY"), endpoint=os.getenv("RESPAN_OAIA_TRACING_ENDPOINT"))] + [ + RespanTraceProcessor( + os.getenv("RESPAN_API_KEY"), + endpoint=os.getenv("RESPAN_OAIA_TRACING_ENDPOINT"), + ) + ] ) @@ -24,7 +30,7 @@ async def test_main(): tools=[ FileSearchTool( max_num_results=3, - vector_store_ids=["vs_67d3bdd0c8888191adfa890a9e829480"], + vector_store_ids=[os.environ["OPENAI_VECTOR_STORE_ID"]], include_search_results=True, ) ], @@ -45,5 +51,6 @@ async def test_main(): {"id":"...", "queries":["Arrakis"], "results":[...]} """ + if __name__ == "__main__": asyncio.run(test_main()) diff --git a/python/tracing/openai-agents-sdk/tools/functions_test.py b/python/tracing/openai-agents-sdk/tools/functions_test.py index 9a4c25c..10b8285 100644 --- a/python/tracing/openai-agents-sdk/tools/functions_test.py +++ b/python/tracing/openai-agents-sdk/tools/functions_test.py @@ -1,15 +1,17 @@ from dotenv import load_dotenv -load_dotenv(override=True) -import pytest +load_dotenv(override=False) # ==========copy the below========== import asyncio +import os + +import pytest from agents import Agent, Runner, function_tool +from agents.tracing import set_trace_processors + from respan_exporter_openai_agents import ( RespanTraceProcessor, ) -from agents.tracing import set_trace_processors -import os set_trace_processors( [ @@ -39,5 +41,6 @@ async def test_main(): print(result.final_output) # The weather in Tokyo is sunny. + if __name__ == "__main__": asyncio.run(test_main()) diff --git a/python/tracing/openai-agents-sdk/tools/web_search_test.py b/python/tracing/openai-agents-sdk/tools/web_search_test.py index 48d25c4..de3a905 100644 --- a/python/tracing/openai-agents-sdk/tools/web_search_test.py +++ b/python/tracing/openai-agents-sdk/tools/web_search_test.py @@ -1,19 +1,25 @@ from dotenv import load_dotenv -load_dotenv(override=True) +load_dotenv(override=False) -import os import asyncio -import pytest +import os +import pytest from agents import Agent, Runner, WebSearchTool, trace from agents.tracing import set_trace_processors + from respan_exporter_openai_agents import ( RespanTraceProcessor, ) set_trace_processors( - [RespanTraceProcessor(os.getenv("RESPAN_API_KEY"), endpoint=os.getenv("RESPAN_OAIA_TRACING_ENDPOINT"))] + [ + RespanTraceProcessor( + os.getenv("RESPAN_API_KEY"), + endpoint=os.getenv("RESPAN_OAIA_TRACING_ENDPOINT"), + ) + ] ) @@ -22,7 +28,9 @@ async def test_main(): agent = Agent( name="Web searcher", instructions="You are a helpful agent.", - tools=[WebSearchTool(user_location={"type": "approximate", "city": "New York"})], + tools=[ + WebSearchTool(user_location={"type": "approximate", "city": "New York"}) + ], ) with trace("Web search example"): @@ -33,5 +41,6 @@ async def test_main(): print(result.final_output) # The New York Giants are reportedly pursuing quarterback Aaron Rodgers after his ... + if __name__ == "__main__": asyncio.run(test_main()) diff --git a/python/tracing/openai-sdk/.env.example b/python/tracing/openai-sdk/.env.example index 1f3d605..8895857 100644 --- a/python/tracing/openai-sdk/.env.example +++ b/python/tracing/openai-sdk/.env.example @@ -2,6 +2,8 @@ RESPAN_API_KEY=your-api-key-here RESPAN_BASE_URL=https://api.respan.ai/api -# OpenAI — direct API key (NOT the Respan gateway key) -# Required for Batch API, file uploads, and other direct OpenAI endpoints -OPENAI_API_KEY=your-api-key-here +# Optional live-provider mode. The default examples are deterministic. +RESPAN_OPENAI_LIVE=0 +# OPENAI_API_KEY=your-direct-openai-key +# OPENAI_BASE_URL=https://api.openai.com/v1 +# RESPAN_PROMPT_ID=your-managed-prompt-id diff --git a/python/tracing/openai-sdk/README.md b/python/tracing/openai-sdk/README.md new file mode 100644 index 0000000..c0d5d53 --- /dev/null +++ b/python/tracing/openai-sdk/README.md @@ -0,0 +1,46 @@ +# OpenAI SDK tracing examples + +These 18 scripts exercise the real OpenAI 3.x sync and async client surfaces +while exporting traces through the local editable Respan packages. The default +mode is deterministic: an in-process `httpx2.MockTransport` supplies valid +OpenAI response payloads, so no provider credential or managed prompt is +required. Requests still pass through the official OpenAI resource, streaming, +SSE, Pydantic parse, and error classes. + +The examples cover Chat and Responses calls, sync/async structured parsing, +streaming, two-turn tools, embeddings, precise 401 handling, propagated +attributes, decorators, prompt-shaped requests, and deterministic batch result +logging. + +## Run + +From this directory, link the checked-out packages and run the full set with +one exact marker: + +```bash +python -m pip install -e ../../../../respan/python-sdks/respan-sdk \ + -e ../../../../respan/python-sdks/respan-tracing \ + -e ../../../../respan/python-sdks/instrumentations/respan-instrumentation-openai \ + -e ../../../../respan/python-sdks/respan +RESPAN_EXAMPLE_RUN_ID=openai-check-001 python run_all.py +``` + +`run_all.py` preserves a shell-supplied marker, runs every script independently, +and reports all failures after the set finishes. Every script flushes and shuts +down Respan explicitly. + +## Optional live provider + +Set the following only when you want to replace deterministic transport with a +real OpenAI-compatible endpoint: + +```bash +RESPAN_OPENAI_LIVE=1 +OPENAI_API_KEY=... +# Optional: +OPENAI_BASE_URL=https://api.openai.com/v1 +``` + +Managed-prompt-shaped examples use `RESPAN_PROMPT_ID` when supplied. Batch +examples intentionally use deterministic result payloads because provider-side +file upload and polling are independent of this instrumentation package. diff --git a/python/tracing/openai-sdk/_batch_data.py b/python/tracing/openai-sdk/_batch_data.py new file mode 100644 index 0000000..3a221b1 --- /dev/null +++ b/python/tracing/openai-sdk/_batch_data.py @@ -0,0 +1,55 @@ +from __future__ import annotations + +from typing import Any + +from _shared import model_name + + +def batch_requests() -> list[dict[str, Any]]: + return [ + { + "custom_id": f"topic-{index}", + "method": "POST", + "url": "/v1/chat/completions", + "body": { + "model": model_name(), + "messages": [{"role": "user", "content": f"Summarize {topic}."}], + }, + } + for index, topic in enumerate( + ("quantum computing", "blockchain", "edge computing") + ) + ] + + +def batch_results(requests: list[dict[str, Any]]) -> list[dict[str, Any]]: + return [ + { + "custom_id": request["custom_id"], + "response": { + "status_code": 200, + "body": { + "id": f"chat_{request['custom_id']}", + "object": "chat.completion", + "created": 1_786_972_800 + index, + "model": model_name(), + "choices": [ + { + "index": 0, + "message": { + "role": "assistant", + "content": f"Deterministic summary {index + 1}.", + }, + "finish_reason": "stop", + } + ], + "usage": { + "prompt_tokens": 5 + index, + "completion_tokens": 3, + "total_tokens": 8 + index, + }, + }, + }, + } + for index, request in enumerate(requests) + ] diff --git a/python/tracing/openai-sdk/_shared.py b/python/tracing/openai-sdk/_shared.py new file mode 100644 index 0000000..ca0388e --- /dev/null +++ b/python/tracing/openai-sdk/_shared.py @@ -0,0 +1,411 @@ +from __future__ import annotations + +import json +import os +from contextlib import contextmanager +from pathlib import Path +from typing import Any +from uuid import uuid4 + +import httpx2 +from dotenv import load_dotenv +from openai import AsyncOpenAI, OpenAI +from respan import Respan, propagate_attributes +from respan_instrumentation_openai import OpenAIInstrumentor + +PROJECT_ROOT = Path(__file__).resolve().parents[3] +DEFAULT_RESPAN_BASE_URL = "https://api.respan.ai/api" +DEFAULT_MODEL = "gpt-4.1-nano" +FAILURE_SENTINEL = "RESPAN_EXPECTED_401" + + +def load_root_env() -> None: + # A shell-supplied group marker must win over values in the repository file. + load_dotenv(PROJECT_ROOT / ".env", override=False) + + +def require_respan_api_key() -> str: + load_root_env() + api_key = os.getenv("RESPAN_API_KEY") + if not api_key: + raise RuntimeError("RESPAN_API_KEY must be set in the repository .env") + return api_key + + +def respan_base_url() -> str: + return os.getenv("RESPAN_BASE_URL", DEFAULT_RESPAN_BASE_URL).rstrip("/") + + +def model_name() -> str: + return os.getenv("RESPAN_OPENAI_MODEL", DEFAULT_MODEL) + + +def run_id() -> str: + marker = os.getenv("RESPAN_EXAMPLE_RUN_ID") + if marker: + return marker + marker = f"openai-sdk-{uuid4().hex[:12]}" + os.environ["RESPAN_EXAMPLE_RUN_ID"] = marker + return marker + + +def workflow_name(example_name: str) -> str: + return f"openai_{example_name.replace('-', '_')}" + + +def make_respan(example_name: str) -> Respan: + marker = run_id() + return Respan( + api_key=require_respan_api_key(), + base_url=respan_base_url(), + app_name="openai-sdk-examples", + environment=os.getenv("RESPAN_ENVIRONMENT", "example"), + instrumentations=[OpenAIInstrumentor()], + metadata={ + "integration": "openai", + "example": example_name, + "example_run_id": marker, + }, + ) + + +@contextmanager +def example_attributes(example_name: str): + marker = run_id() + current_workflow = workflow_name(example_name) + with propagate_attributes( + custom_identifier=f"{marker}:{example_name}", + trace_group_identifier=current_workflow, + metadata={ + "integration": "openai", + "example": example_name, + "example_run_id": marker, + "workflow_name": current_workflow, + }, + ): + yield marker + + +def live_enabled() -> bool: + return os.getenv("RESPAN_OPENAI_LIVE", "").lower() in {"1", "true", "yes"} + + +def client_mode() -> str: + return "live-openai" if live_enabled() else "deterministic-openai-transport" + + +def _live_client_kwargs() -> dict[str, Any]: + api_key = os.getenv("OPENAI_API_KEY") + if not api_key: + raise RuntimeError("RESPAN_OPENAI_LIVE=1 requires OPENAI_API_KEY") + kwargs: dict[str, Any] = {"api_key": api_key, "max_retries": 0} + base_url = os.getenv("OPENAI_BASE_URL") + if base_url: + kwargs["base_url"] = base_url + return kwargs + + +def make_sync_client() -> OpenAI: + load_root_env() + if live_enabled(): + return OpenAI(**_live_client_kwargs()) + return OpenAI( + api_key="deterministic-test-key", + base_url="https://openai.example.invalid/v1", + max_retries=0, + http_client=httpx2.Client(transport=httpx2.MockTransport(_sync_handler)), + ) + + +def make_async_client() -> AsyncOpenAI: + load_root_env() + if live_enabled(): + return AsyncOpenAI(**_live_client_kwargs()) + return AsyncOpenAI( + api_key="deterministic-test-key", + base_url="https://openai.example.invalid/v1", + max_retries=0, + http_client=httpx2.AsyncClient(transport=httpx2.MockTransport(_async_handler)), + ) + + +def finish_respan(respan: Respan) -> None: + try: + respan.flush() + finally: + respan.shutdown() + + +def print_result(example_name: str, text: str) -> None: + print(f"example={example_name}") + print(f"example_run_id={run_id()}") + print(f"workflow_name={workflow_name(example_name)}") + print(f"client_mode={client_mode()}") + print(text.strip()) + + +def _request_body(request: httpx2.Request) -> dict[str, Any]: + return json.loads(request.content or b"{}") + + +def _contains_failure(value: Any) -> bool: + return FAILURE_SENTINEL in json.dumps(value, default=str) + + +def _chat_response(body: dict[str, Any]) -> dict[str, Any]: + messages = body.get("messages") or [] + structured = bool(body.get("response_format")) + if structured: + content = json.dumps( + { + "title": "The Matrix", + "rating": 9, + "summary": "A deterministic science-fiction classic.", + "pros": ["visuals", "ideas"], + "cons": ["dense exposition"], + } + ) + finish_reason = "stop" + message: dict[str, Any] = {"role": "assistant", "content": content} + elif body.get("tools") and not any( + message.get("role") == "tool" + for message in messages + if isinstance(message, dict) + ): + finish_reason = "tool_calls" + message = { + "role": "assistant", + "content": None, + "tool_calls": [ + { + "id": "call_weather", + "type": "function", + "function": { + "name": "get_weather", + "arguments": '{"city":"Paris"}', + }, + } + ], + } + elif body.get("tools"): + finish_reason = "stop" + message = { + "role": "assistant", + "content": "The deterministic tool reports sunny weather in Paris.", + } + elif not messages: + finish_reason = "stop" + message = { + "role": "assistant", + "content": "Milestone plan: design, implement, validate.", + } + else: + finish_reason = "stop" + message = { + "role": "assistant", + "content": "Deterministic OpenAI chat response.", + } + return { + "id": "chat_deterministic", + "object": "chat.completion", + "created": 1_786_972_800, + "model": body.get("model") or model_name(), + "choices": [ + { + "index": 0, + "message": message, + "finish_reason": finish_reason, + } + ], + "usage": {"prompt_tokens": 13, "completion_tokens": 7, "total_tokens": 20}, + } + + +def _responses_response(body: dict[str, Any]) -> dict[str, Any]: + structured = bool(body.get("text", {}).get("format")) + input_value = body.get("input") + has_tool_result = False + if isinstance(input_value, list): + has_tool_result = any( + isinstance(item, dict) and item.get("type") == "function_call_output" + for item in input_value + ) + if structured: + text = json.dumps( + { + "title": "The Matrix", + "rating": 9, + "summary": "A deterministic science-fiction classic.", + "pros": ["visuals", "ideas"], + "cons": ["dense exposition"], + } + ) + output = [_response_message(text)] + elif body.get("tools") and not has_tool_result: + output = [ + { + "id": "fc_weather", + "type": "function_call", + "call_id": "call_weather", + "name": "get_weather", + "arguments": '{"city":"Paris"}', + "status": "completed", + } + ] + else: + text = ( + "The deterministic tool reports sunny weather in Paris." + if has_tool_result + else "Deterministic OpenAI Responses output." + ) + output = [_response_message(text)] + return { + "id": "resp_deterministic", + "object": "response", + "created_at": 1_786_972_800, + "status": "completed", + "model": body.get("model") or model_name(), + "output": output, + "parallel_tool_calls": True, + "tool_choice": "auto", + "tools": [], + "temperature": 1, + "top_p": 1, + "usage": {"input_tokens": 11, "output_tokens": 6, "total_tokens": 17}, + "error": None, + "incomplete_details": None, + "instructions": body.get("instructions"), + "metadata": {}, + } + + +def _response_message(text: str) -> dict[str, Any]: + return { + "id": "msg_deterministic", + "type": "message", + "status": "completed", + "role": "assistant", + "content": [{"type": "output_text", "text": text, "annotations": []}], + } + + +def _sync_handler(request: httpx2.Request) -> httpx2.Response: + body = _request_body(request) + if _contains_failure(body): + return httpx2.Response( + 401, + json={ + "error": { + "message": "deterministic OpenAI credential rejected", + "type": "authentication_error", + } + }, + ) + if request.url.path.endswith("/chat/completions"): + if body.get("stream"): + return _chat_stream_response(body) + return httpx2.Response(200, json=_chat_response(body)) + if request.url.path.endswith("/responses"): + if body.get("stream"): + return _responses_stream_response(body) + return httpx2.Response(200, json=_responses_response(body)) + if request.url.path.endswith("/embeddings"): + return httpx2.Response( + 200, + json={ + "object": "list", + "model": body.get("model") or "text-embedding-3-small", + "data": [ + {"object": "embedding", "index": 0, "embedding": [0.1, 0.2, 0.3]} + ], + "usage": {"prompt_tokens": 4, "total_tokens": 4}, + }, + ) + raise AssertionError(f"unhandled deterministic endpoint: {request.url.path}") + + +async def _async_handler(request: httpx2.Request) -> httpx2.Response: + return _sync_handler(request) + + +def _chat_stream_response(body: dict[str, Any]) -> httpx2.Response: + chunks = [ + { + "id": "chat_stream", + "object": "chat.completion.chunk", + "created": 1_786_972_800, + "model": body.get("model") or model_name(), + "choices": [ + { + "index": 0, + "delta": {"role": "assistant", "content": "Streaming "}, + "finish_reason": None, + } + ], + }, + { + "id": "chat_stream", + "object": "chat.completion.chunk", + "created": 1_786_972_800, + "model": body.get("model") or model_name(), + "choices": [ + { + "index": 0, + "delta": {"content": "OpenAI response."}, + "finish_reason": "stop", + } + ], + }, + { + "id": "chat_stream", + "object": "chat.completion.chunk", + "created": 1_786_972_800, + "model": body.get("model") or model_name(), + "choices": [], + "usage": {"prompt_tokens": 9, "completion_tokens": 4, "total_tokens": 13}, + }, + ] + payload = "".join(f"data: {json.dumps(chunk)}\n\n" for chunk in chunks) + payload += "data: [DONE]\n\n" + return httpx2.Response( + 200, + headers={"content-type": "text/event-stream"}, + content=payload.encode(), + ) + + +def _responses_stream_response(body: dict[str, Any]) -> httpx2.Response: + final_response = _responses_response(body) + final_response["output"] = [_response_message("Streaming Responses output.")] + events = [ + { + "type": "response.output_text.delta", + "sequence_number": 0, + "item_id": "msg_deterministic", + "output_index": 0, + "content_index": 0, + "delta": "Streaming ", + }, + { + "type": "response.output_text.delta", + "sequence_number": 1, + "item_id": "msg_deterministic", + "output_index": 0, + "content_index": 0, + "delta": "Responses output.", + }, + { + "type": "response.completed", + "sequence_number": 2, + "response": final_response, + }, + ] + payload = "".join( + f"event: {event['type']}\ndata: {json.dumps(event)}\n\n" for event in events + ) + payload += "data: [DONE]\n\n" + return httpx2.Response( + 200, + headers={"content-type": "text/event-stream"}, + content=payload.encode(), + ) diff --git a/python/tracing/openai-sdk/async_parallel.py b/python/tracing/openai-sdk/async_parallel.py index 7ce0958..2ebc311 100644 --- a/python/tracing/openai-sdk/async_parallel.py +++ b/python/tracing/openai-sdk/async_parallel.py @@ -1,42 +1,61 @@ -"""Async Parallel — Run multiple OpenAI calls concurrently, all auto-traced.""" +"""Concurrent async Chat calls plus async Responses structured parsing.""" -import os import asyncio -from dotenv import load_dotenv -load_dotenv(override=True) +from pydantic import BaseModel +from respan import task, workflow -from openai import AsyncOpenAI -from respan import Respan, workflow, task -from respan_instrumentation_openai import OpenAIInstrumentor +from _shared import ( + example_attributes, + finish_respan, + make_async_client, + make_respan, + model_name, + print_result, +) -respan = Respan(instrumentations=[OpenAIInstrumentor()]) +EXAMPLE = "async-parallel" +respan = make_respan(EXAMPLE) -client = AsyncOpenAI( - api_key=os.getenv("RESPAN_API_KEY"), - base_url=os.getenv("RESPAN_BASE_URL", "https://api.respan.ai/api"), -) + +class Review(BaseModel): + title: str + rating: int + summary: str + pros: list[str] + cons: list[str] @task(name="summarize") async def summarize(topic: str) -> str: response = await client.chat.completions.create( - model="gpt-4.1-nano", - messages=[ - {"role": "system", "content": "Summarize in one sentence."}, - {"role": "user", "content": f"What is {topic}?"}, - ], - + model=model_name(), + messages=[{"role": "user", "content": f"Summarize {topic}."}], ) - return response.choices[0].message.content + return response.choices[0].message.content or "" -@workflow(name="parallel_summaries") -async def run(): +@workflow(name="openai_async_parallel") +async def run() -> str: topics = ["quantum computing", "blockchain", "edge computing"] - results = await asyncio.gather(*[summarize(t) for t in topics]) - for topic, summary in zip(topics, results): - print(f"{topic}: {summary}\n") + summaries = await asyncio.gather(*(summarize(topic) for topic in topics)) + parsed = await client.responses.parse( + model=model_name(), input="Review The Matrix", text_format=Review + ) + return f"summaries={len(summaries)} parsed_rating={parsed.output_parsed.rating}" + + +async def main() -> None: + try: + global client + client = make_async_client() + try: + with example_attributes(EXAMPLE): + print_result(EXAMPLE, await run()) + finally: + await client.close() + finally: + finish_respan(respan) -asyncio.run(run()) +asyncio.run(main()) diff --git a/python/tracing/openai-sdk/attributes.py b/python/tracing/openai-sdk/attributes.py index 1fe372e..7e68084 100644 --- a/python/tracing/openai-sdk/attributes.py +++ b/python/tracing/openai-sdk/attributes.py @@ -1,39 +1,41 @@ -"""Attributes — Attach customer info and metadata to traces.""" +"""Customer, thread, and metadata propagation across OpenAI calls.""" -import os -from dotenv import load_dotenv +from respan import propagate_attributes, workflow -load_dotenv(override=True) - -from openai import OpenAI -from respan import Respan, workflow, propagate_attributes -from respan_instrumentation_openai import OpenAIInstrumentor - -respan = Respan( - instrumentations=[OpenAIInstrumentor()], - metadata={"service": "chat-api", "version": "1.0.0"}, +from _shared import ( + example_attributes, + finish_respan, + make_respan, + make_sync_client, + model_name, + print_result, ) -client = OpenAI( - api_key=os.getenv("RESPAN_API_KEY"), - base_url=os.getenv("RESPAN_BASE_URL", "https://api.respan.ai/api"), -) +EXAMPLE = "attributes" +respan = make_respan(EXAMPLE) -@workflow(name="handle_request") -def handle_request(user_id: str, question: str): +@workflow(name="openai_handle_request") +def handle_request(user_id: str, question: str) -> str: with propagate_attributes( customer_identifier=user_id, - thread_identifier="conv_001", - metadata={"plan": "pro"}, # merged with default metadata + thread_identifier="openai-conversation-001", + metadata={"plan": "pro"}, ): response = client.chat.completions.create( - model="gpt-4.1-nano", - messages=[{"role": "user", "content": question}], - + model=model_name(), messages=[{"role": "user", "content": question}] ) - print(f"[{user_id}] {response.choices[0].message.content}") - - -handle_request("user_alice", "What is an API gateway?") -handle_request("user_bob", "Explain rate limiting.") + return response.choices[0].message.content or "" + + +try: + client = make_sync_client() + try: + with example_attributes(EXAMPLE): + first = handle_request("user_alice", "What is an API gateway?") + second = handle_request("user_bob", "Explain rate limiting.") + print_result(EXAMPLE, f"first={first} second={second}") + finally: + client.close() +finally: + finish_respan(respan) diff --git a/python/tracing/openai-sdk/batch.py b/python/tracing/openai-sdk/batch.py index 6c9ad4f..0cc1096 100644 --- a/python/tracing/openai-sdk/batch.py +++ b/python/tracing/openai-sdk/batch.py @@ -1,127 +1,29 @@ -"""Batch API — Submit multiple requests for async processing at 50% cost. +"""Deterministic OpenAI Batch result logging without provider-side polling.""" -The Batch API uses OpenAI's file and batch endpoints directly. -Respan decorators trace the batch workflow for observability. +from respan import task, workflow -Set OPENAI_API_KEY (direct OpenAI key) and RESPAN_API_KEY in .env: +from _batch_data import batch_requests, batch_results +from _shared import example_attributes, finish_respan, make_respan, print_result - RESPAN_API_KEY=your-respan-key - OPENAI_API_KEY=sk-proj-... -""" +EXAMPLE = "batch" +respan = make_respan(EXAMPLE) -import os -import json -import time -from dotenv import load_dotenv - -load_dotenv() - -from openai import OpenAI -from respan import Respan, workflow, task -from respan_instrumentation_openai import OpenAIInstrumentor - -respan = Respan(instrumentations=[OpenAIInstrumentor()]) - -# Batch API requires direct OpenAI access (not gateway). -# The .env has a direct OPENAI_API_KEY (not the Respan gateway key). -client = OpenAI( - api_key=os.getenv("OPENAI_API_KEY"), -) - -TOPICS = [ - "quantum computing", - "blockchain", - "edge computing", - "reinforcement learning", - "zero-knowledge proofs", -] - - -@task(name="create_batch_file") -def create_batch_file() -> str: - """Create a JSONL file with batch requests.""" - tasks = [] - for i, topic in enumerate(TOPICS): - tasks.append({ - "custom_id": f"topic-{i}", - "method": "POST", - "url": "/v1/chat/completions", - "body": { - "model": "gpt-4.1-nano", - "messages": [ - {"role": "system", "content": "Explain in one sentence."}, - {"role": "user", "content": f"What is {topic}?"}, - ], - }, - }) - - file_path = "/tmp/respan_batch_input.jsonl" - with open(file_path, "w") as f: - for t in tasks: - f.write(json.dumps(t) + "\n") - - print(f"Created {len(tasks)} tasks in {file_path}") - return file_path - - -@task(name="upload_and_submit") -def upload_and_submit(file_path: str) -> str: - """Upload the JSONL file and create a batch job.""" - batch_file = client.files.create( - file=open(file_path, "rb"), - purpose="batch", - ) - print(f"Uploaded file: {batch_file.id}") - - batch = client.batches.create( - input_file_id=batch_file.id, - endpoint="/v1/chat/completions", - completion_window="24h", - ) - print(f"Batch created: {batch.id} (status: {batch.status})") - return batch.id - - -@task(name="poll_batch") -def poll_batch(batch_id: str) -> str: - """Poll until the batch completes.""" - while True: - batch = client.batches.retrieve(batch_id) - print(f"Status: {batch.status} ({batch.request_counts.completed}/{batch.request_counts.total} done)") - - if batch.status == "completed": - return batch.output_file_id - elif batch.status in ("failed", "expired", "cancelled"): - raise RuntimeError(f"Batch {batch.status}: {batch.errors}") - - time.sleep(5) - - -@task(name="download_results") -def download_results(output_file_id: str): - """Download batch results and log each completion as a traced span.""" - content = client.files.content(output_file_id).content - results = [json.loads(line) for line in content.decode().strip().split("\n")] - - with open("/tmp/respan_batch_input.jsonl") as f: - requests = [json.loads(line) for line in f] - - # Log each batch result as an individual chat completion span +@task(name="log_batch_results") +def log_results() -> int: + requests = batch_requests() + results = batch_results(requests) respan.log_batch_results(requests, results) - - for r in results: - idx = int(r["custom_id"].split("-")[1]) - message = r["response"]["body"]["choices"][0]["message"]["content"] - print(f"{TOPICS[idx]}: {message}") + return len(results) -@workflow(name="batch_pipeline") -def run(): - file_path = create_batch_file() - batch_id = upload_and_submit(file_path) - output_file_id = poll_batch(batch_id) - download_results(output_file_id) +@workflow(name="openai_batch_pipeline") +def run() -> str: + return f"logged_results={log_results()}" -run() +try: + with example_attributes(EXAMPLE): + print_result(EXAMPLE, run()) +finally: + finish_respan(respan) diff --git a/python/tracing/openai-sdk/batch_async.py b/python/tracing/openai-sdk/batch_async.py index 7f7809d..9360896 100644 --- a/python/tracing/openai-sdk/batch_async.py +++ b/python/tracing/openai-sdk/batch_async.py @@ -1,129 +1,33 @@ -"""Async Batch — Submit a batch, come back later, log results into the original trace. +"""Log deterministic batch results after the submission workflow completes.""" -Simulates the real-world pattern where batch submission and result retrieval -happen at different times (or in different processes). +from respan import get_client, task, workflow - RESPAN_API_KEY=your-respan-key - OPENAI_API_KEY=sk-proj-... -""" +from _batch_data import batch_requests, batch_results +from _shared import example_attributes, finish_respan, make_respan, print_result -import os -import json -import time +EXAMPLE = "batch-async" +respan = make_respan(EXAMPLE) -from dotenv import load_dotenv - -load_dotenv() - -from openai import OpenAI -from respan import Respan, workflow, task, get_client -from respan_instrumentation_openai import OpenAIInstrumentor - -respan = Respan(instrumentations=[OpenAIInstrumentor()]) -client = OpenAI(api_key=os.getenv("OPENAI_API_KEY")) - -TOPICS = [ - "quantum computing", - "blockchain", - "edge computing", -] - - -# ── Phase 1: Submit ────────────────────────────────────────────────── -# In production this would be an API endpoint, a CLI command, etc. - -@task(name="create_and_submit") -def create_and_submit() -> dict: - """Build requests, upload, submit batch, return handles for later.""" - requests = [] - for i, topic in enumerate(TOPICS): - requests.append({ - "custom_id": f"topic-{i}", - "method": "POST", - "url": "/v1/chat/completions", - "body": { - "model": "gpt-4.1-nano", - "messages": [ - {"role": "system", "content": "Explain in one sentence."}, - {"role": "user", "content": f"What is {topic}?"}, - ], - }, - }) - - # Write + upload + submit - file_path = "/tmp/respan_batch_async.jsonl" - with open(file_path, "w") as f: - for r in requests: - f.write(json.dumps(r) + "\n") - - batch_file = client.files.create(file=open(file_path, "rb"), purpose="batch") - batch = client.batches.create( - input_file_id=batch_file.id, - endpoint="/v1/chat/completions", - completion_window="24h", - ) - print(f"Batch submitted: {batch.id} (status: {batch.status})") - - # Capture trace context — in production, save this to DB - rc = get_client() - trace_id = rc.get_current_trace_id() - print(f"Trace ID saved: {trace_id}") +@task(name="submit_batch") +def submit_batch() -> dict[str, str]: return { - "batch_id": batch.id, - "trace_id": trace_id, - "input_file": file_path, + "batch_id": "batch_deterministic", + "trace_id": get_client().get_current_trace_id(), } -@workflow(name="batch_submit") -def submit(): - return create_and_submit() - - -# ── Phase 2: Retrieve (simulates a separate job) ──────────────────── -# In production this would be a cron job, webhook handler, queue worker, etc. - -def retrieve_and_log(saved: dict): - """Check batch status, download results, log into original trace.""" - batch_id = saved["batch_id"] - trace_id = saved["trace_id"] - input_file = saved["input_file"] - - # Poll until done - while True: - batch = client.batches.retrieve(batch_id) - print(f"Status: {batch.status} ({batch.request_counts.completed}/{batch.request_counts.total} done)") - if batch.status == "completed": - break - elif batch.status in ("failed", "expired", "cancelled"): - raise RuntimeError(f"Batch {batch.status}: {batch.errors}") - time.sleep(5) - - # Download results - content = client.files.content(batch.output_file_id).content - results = [json.loads(line) for line in content.decode().strip().split("\n")] - - # Load original requests - with open(input_file) as f: - requests = [json.loads(line) for line in f] - - # Log completions back into the ORIGINAL trace - respan.log_batch_results(requests, results, trace_id=trace_id) - - for r in results: - idx = int(r["custom_id"].split("-")[1]) - message = r["response"]["body"]["choices"][0]["message"]["content"] - print(f"{TOPICS[idx]}: {message}") - - -# ── Run both phases ────────────────────────────────────────────────── +@workflow(name="openai_batch_submit") +def submit() -> dict[str, str]: + return submit_batch() -# Phase 1: submit -saved = submit() -print(f"\n--- Batch submitted. Waiting for results... ---\n") -# Phase 2: come back later and retrieve -# (In production, this would be a completely separate process/job) -retrieve_and_log(saved) -print("\nDone — check the trace in Respan!") +try: + with example_attributes(EXAMPLE): + saved = submit() + requests = batch_requests() + results = batch_results(requests) + respan.log_batch_results(requests, results, trace_id=saved["trace_id"]) + print_result(EXAMPLE, f"batch_id={saved['batch_id']} logged={len(results)}") +finally: + finish_respan(respan) diff --git a/python/tracing/openai-sdk/decorators.py b/python/tracing/openai-sdk/decorators.py index e84eaab..602371b 100644 --- a/python/tracing/openai-sdk/decorators.py +++ b/python/tracing/openai-sdk/decorators.py @@ -1,56 +1,47 @@ -"""Decorators — Use @workflow and @task to structure traces.""" +"""A two-step content workflow around traced OpenAI Chat calls.""" -import os -from dotenv import load_dotenv +from respan import task, workflow -load_dotenv(override=True) - -from openai import OpenAI -from respan import Respan, workflow, task -from respan_instrumentation_openai import OpenAIInstrumentor - -respan = Respan(instrumentations=[OpenAIInstrumentor()]) - -client = OpenAI( - api_key=os.getenv("RESPAN_API_KEY"), - base_url=os.getenv("RESPAN_BASE_URL", "https://api.respan.ai/api"), +from _shared import ( + example_attributes, + finish_respan, + make_respan, + make_sync_client, + model_name, + print_result, ) +EXAMPLE = "decorators" +respan = make_respan(EXAMPLE) + @task(name="generate_outline") def generate_outline(topic: str) -> str: response = client.chat.completions.create( - model="gpt-4.1-nano", - messages=[ - {"role": "system", "content": "Generate a 3-point outline. Be concise."}, - {"role": "user", "content": topic}, - ], - + model=model_name(), messages=[{"role": "user", "content": topic}] ) - return response.choices[0].message.content + return response.choices[0].message.content or "" @task(name="write_draft") def write_draft(outline: str) -> str: response = client.chat.completions.create( - model="gpt-4.1-nano", - messages=[ - {"role": "system", "content": "Write a short paragraph from this outline."}, - {"role": "user", "content": outline}, - ], - + model=model_name(), messages=[{"role": "user", "content": outline}] ) - return response.choices[0].message.content + return response.choices[0].message.content or "" -@workflow(name="content_pipeline") +@workflow(name="openai_content_pipeline") def run(topic: str) -> str: - outline = generate_outline(topic) - print(f"Outline:\n{outline}\n") - - draft = write_draft(outline) - print(f"Draft:\n{draft}") - return draft - - -run("Benefits of open-source software") + return write_draft(generate_outline(topic)) + + +try: + client = make_sync_client() + try: + with example_attributes(EXAMPLE): + print_result(EXAMPLE, run("Benefits of open-source software")) + finally: + client.close() +finally: + finish_respan(respan) diff --git a/python/tracing/openai-sdk/hello_world.py b/python/tracing/openai-sdk/hello_world.py index bd2a8e0..e352370 100644 --- a/python/tracing/openai-sdk/hello_world.py +++ b/python/tracing/openai-sdk/hello_world.py @@ -1,24 +1,48 @@ -"""Hello World — Simplest possible: one OpenAI call, auto-traced.""" +"""Chat, embedding, and precise provider-error tracing with the OpenAI SDK.""" -import os -from dotenv import load_dotenv +from openai import AuthenticationError +from respan import workflow -load_dotenv(override=True) +from _shared import ( + FAILURE_SENTINEL, + example_attributes, + finish_respan, + make_respan, + make_sync_client, + model_name, + print_result, +) -from openai import OpenAI -from respan import Respan -from respan_instrumentation_openai import OpenAIInstrumentor +EXAMPLE = "hello-world" +respan = make_respan(EXAMPLE) -respan = Respan(instrumentations=[OpenAIInstrumentor()]) -client = OpenAI( - api_key=os.getenv("RESPAN_API_KEY"), - base_url=os.getenv("RESPAN_BASE_URL", "https://api.respan.ai/api"), -) +@workflow(name="openai_hello_world") +def run() -> str: + response = client.chat.completions.create( + model=model_name(), + messages=[{"role": "user", "content": "Say hello in three languages."}], + ) + embedding = client.embeddings.create( + model="text-embedding-3-small", input="observable OpenAI request" + ) + try: + client.chat.completions.create( + model=model_name(), + messages=[{"role": "user", "content": FAILURE_SENTINEL}], + ) + except AuthenticationError as exc: + if exc.status_code != 401: + raise + return f"{response.choices[0].message.content} embedding_dim={len(embedding.data[0].embedding)}" -response = client.chat.completions.create( - model="gpt-4.1-nano", - messages=[{"role": "user", "content": "Say hello in three languages."}], -) -print(response.choices[0].message.content) +try: + client = make_sync_client() + try: + with example_attributes(EXAMPLE): + print_result(EXAMPLE, run()) + finally: + client.close() +finally: + finish_respan(respan) diff --git a/python/tracing/openai-sdk/multi_turn.py b/python/tracing/openai-sdk/multi_turn.py index ed876a8..1843978 100644 --- a/python/tracing/openai-sdk/multi_turn.py +++ b/python/tracing/openai-sdk/multi_turn.py @@ -1,44 +1,43 @@ -"""Multi-Turn — Conversational chat with message history, auto-traced.""" +"""Three-turn Chat history with each provider call auto-traced.""" -import os -from dotenv import load_dotenv +from respan import workflow -load_dotenv(override=True) - -from openai import OpenAI -from respan import Respan, workflow -from respan_instrumentation_openai import OpenAIInstrumentor - -respan = Respan(instrumentations=[OpenAIInstrumentor()]) - -client = OpenAI( - api_key=os.getenv("RESPAN_API_KEY"), - base_url=os.getenv("RESPAN_BASE_URL", "https://api.respan.ai/api"), +from _shared import ( + example_attributes, + finish_respan, + make_respan, + make_sync_client, + model_name, + print_result, ) +EXAMPLE = "multi-turn" +respan = make_respan(EXAMPLE) -@workflow(name="conversation") -def chat(): - messages = [ + +@workflow(name="openai_conversation") +def run() -> str: + messages: list[dict[str, str]] = [ {"role": "system", "content": "You are a concise cooking assistant."} ] - questions = [ + for question in ( "What can I make with eggs and cheese?", - "How long does the omelette take?", - "Any tips to make it fluffy?", - ] - - for question in questions: + "How long does it take?", + "How can I make it fluffy?", + ): messages.append({"role": "user", "content": question}) - response = client.chat.completions.create( - model="gpt-4.1-nano", - messages=messages, - - ) - answer = response.choices[0].message.content + response = client.chat.completions.create(model=model_name(), messages=messages) + answer = response.choices[0].message.content or "" messages.append({"role": "assistant", "content": answer}) - print(f"User: {question}") - print(f"Bot: {answer}\n") - - -chat() + return messages[-1]["content"] + + +try: + client = make_sync_client() + try: + with example_attributes(EXAMPLE): + print_result(EXAMPLE, run()) + finally: + client.close() +finally: + finish_respan(respan) diff --git a/python/tracing/openai-sdk/prompt.py b/python/tracing/openai-sdk/prompt.py index 990c1cb..5a9fda5 100644 --- a/python/tracing/openai-sdk/prompt.py +++ b/python/tracing/openai-sdk/prompt.py @@ -1,35 +1,43 @@ -"""Prompt — Use a Respan-managed prompt template with variables.""" +"""A managed-prompt-shaped Chat request using a configurable prompt ID.""" import os -from dotenv import load_dotenv -load_dotenv(override=True) +from respan import workflow -from openai import OpenAI -from respan import Respan -from respan_instrumentation_openai import OpenAIInstrumentor - -respan = Respan(instrumentations=[OpenAIInstrumentor()]) - -client = OpenAI( - api_key=os.getenv("RESPAN_API_KEY"), - base_url=os.getenv("RESPAN_BASE_URL", "https://api.respan.ai/api"), -) - -PROMPT_ID = "d767498c1cbb4951bb122eef423b5f76" - -response = client.chat.completions.create( - model="placeholder", # model is defined in the prompt config - messages=[], # messages are defined in the prompt template - extra_body={ - "prompt": { - "prompt_id": PROMPT_ID, - "schema_version": 2, - "variables": { - "feature_request": "Add a real-time notification system for order status updates", - }, - } - }, +from _shared import ( + example_attributes, + finish_respan, + make_respan, + make_sync_client, + print_result, ) -print(response.choices[0].message.content) +EXAMPLE = "prompt" +respan = make_respan(EXAMPLE) + + +@workflow(name="openai_managed_prompt") +def run() -> str: + response = client.chat.completions.create( + model="placeholder", + messages=[], + extra_body={ + "prompt": { + "prompt_id": os.getenv("RESPAN_PROMPT_ID", "deterministic-prompt"), + "schema_version": 2, + "variables": {"feature_request": "Add order notifications"}, + } + }, + ) + return response.choices[0].message.content or "" + + +try: + client = make_sync_client() + try: + with example_attributes(EXAMPLE): + print_result(EXAMPLE, run()) + finally: + client.close() +finally: + finish_respan(respan) diff --git a/python/tracing/openai-sdk/prompt_multi_turn.py b/python/tracing/openai-sdk/prompt_multi_turn.py index 2f608fe..15b3cc4 100644 --- a/python/tracing/openai-sdk/prompt_multi_turn.py +++ b/python/tracing/openai-sdk/prompt_multi_turn.py @@ -1,56 +1,52 @@ -"""Prompt Multi-Turn — Continue a conversation using a managed prompt.""" +"""Managed-prompt-shaped first turn followed by a normal Chat turn.""" import os -from dotenv import load_dotenv -load_dotenv(override=True) +from respan import workflow -from openai import OpenAI -from respan import Respan, workflow -from respan_instrumentation_openai import OpenAIInstrumentor - -respan = Respan(instrumentations=[OpenAIInstrumentor()]) - -client = OpenAI( - api_key=os.getenv("RESPAN_API_KEY"), - base_url=os.getenv("RESPAN_BASE_URL", "https://api.respan.ai/api"), +from _shared import ( + example_attributes, + finish_respan, + make_respan, + make_sync_client, + model_name, + print_result, ) -PROMPT_ID = "d767498c1cbb4951bb122eef423b5f76" +EXAMPLE = "prompt-multi-turn" +respan = make_respan(EXAMPLE) -@workflow(name="prompt_conversation") -def chat(): - # Turn 1: Initial request using the prompt template - response = client.chat.completions.create( +@workflow(name="openai_prompt_conversation") +def run() -> str: + first = client.chat.completions.create( model="placeholder", messages=[], extra_body={ "prompt": { - "prompt_id": PROMPT_ID, + "prompt_id": os.getenv("RESPAN_PROMPT_ID", "deterministic-prompt"), "schema_version": 2, - "variables": { - "feature_request": "Add dark mode support to the dashboard", - }, + "variables": {"feature_request": "Add dark mode"}, } }, ) - plan = response.choices[0].message.content - print(f"=== Initial Plan ===\n{plan}\n") - - # Turn 2: Follow-up without the prompt template (regular chat) - follow_up = client.chat.completions.create( - model="gpt-4.1-nano", + plan = first.choices[0].message.content or "" + second = client.chat.completions.create( + model=model_name(), messages=[ - {"role": "system", "content": "You are a Lead Product Engineer."}, {"role": "assistant", "content": plan}, - { - "role": "user", - "content": "Can you estimate the effort for each milestone in story points?", - }, + {"role": "user", "content": "Estimate effort."}, ], ) - print(f"=== Follow-up ===\n{follow_up.choices[0].message.content}") - - -chat() + return second.choices[0].message.content or "" + + +try: + client = make_sync_client() + try: + with example_attributes(EXAMPLE): + print_result(EXAMPLE, run()) + finally: + client.close() +finally: + finish_respan(respan) diff --git a/python/tracing/openai-sdk/requirements.txt b/python/tracing/openai-sdk/requirements.txt new file mode 100644 index 0000000..9b26ad2 --- /dev/null +++ b/python/tracing/openai-sdk/requirements.txt @@ -0,0 +1,6 @@ +httpx2>=2.10.0,<3.0.0 +openai>=3.0.0,<4.0.0 +pydantic>=2.12.0,<3.0.0 +python-dotenv>=1.0.0,<2.0.0 +respan-ai>=4.1.0,<5.0.0 +respan-instrumentation-openai>=1.2.0,<2.0.0 diff --git a/python/tracing/openai-sdk/responses_hello_world.py b/python/tracing/openai-sdk/responses_hello_world.py index e0e2f3d..a16493e 100644 --- a/python/tracing/openai-sdk/responses_hello_world.py +++ b/python/tracing/openai-sdk/responses_hello_world.py @@ -1,24 +1,36 @@ -"""Responses API — Simplest possible: one call, auto-traced.""" +"""One successful Responses API call inside a workflow.""" -import os -from dotenv import load_dotenv +from respan import workflow -load_dotenv(override=True) +from _shared import ( + example_attributes, + finish_respan, + make_respan, + make_sync_client, + model_name, + print_result, +) -from openai import OpenAI -from respan import Respan -from respan_instrumentation_openai import OpenAIInstrumentor +EXAMPLE = "responses-hello-world" +respan = make_respan(EXAMPLE) -respan = Respan(instrumentations=[OpenAIInstrumentor()]) -client = OpenAI( - api_key=os.getenv("RESPAN_API_KEY"), - base_url=os.getenv("RESPAN_BASE_URL", "https://api.respan.ai/api"), -) +@workflow(name="openai_responses_hello_world") +def run() -> str: + response = client.responses.create( + model=model_name(), + instructions="You are a helpful assistant.", + input="Say hello in three languages.", + ) + return response.output_text -response = client.responses.create( - model="gpt-4.1-nano", - instructions="You are a helpful assistant.", - input="Say hello in three languages.", -) -print(response.output_text) + +try: + client = make_sync_client() + try: + with example_attributes(EXAMPLE): + print_result(EXAMPLE, run()) + finally: + client.close() +finally: + finish_respan(respan) diff --git a/python/tracing/openai-sdk/responses_multi_turn.py b/python/tracing/openai-sdk/responses_multi_turn.py index d4ce8ad..4a2c50c 100644 --- a/python/tracing/openai-sdk/responses_multi_turn.py +++ b/python/tracing/openai-sdk/responses_multi_turn.py @@ -1,50 +1,46 @@ -"""Responses API Multi-Turn — Continue a conversation using previous_response_id.""" +"""Three Responses calls linked by previous_response_id.""" -import os -from dotenv import load_dotenv +from respan import workflow -load_dotenv(override=True) - -from openai import OpenAI -from respan import Respan, workflow -from respan_instrumentation_openai import OpenAIInstrumentor - -respan = Respan(instrumentations=[OpenAIInstrumentor()]) - -client = OpenAI( - api_key=os.getenv("RESPAN_API_KEY"), - base_url=os.getenv("RESPAN_BASE_URL", "https://api.respan.ai/api"), +from _shared import ( + example_attributes, + finish_respan, + make_respan, + make_sync_client, + model_name, + print_result, ) +EXAMPLE = "responses-multi-turn" +respan = make_respan(EXAMPLE) -@workflow(name="conversation") -def chat(): - # Turn 1 - r1 = client.responses.create( - model="gpt-4.1-nano", - instructions="You are a helpful assistant. Be concise.", - input="What is the capital of France?", - store=True, - ) - print(f"Turn 1: {r1.output_text}\n") - # Turn 2 — uses previous_response_id to chain context - r2 = client.responses.create( - model="gpt-4.1-nano", - input="And what is its population?", - previous_response_id=r1.id, +@workflow(name="openai_responses_conversation") +def run() -> str: + first = client.responses.create( + model=model_name(), input="Capital of France?", store=True + ) + second = client.responses.create( + model=model_name(), + input="Population?", + previous_response_id=first.id, store=True, ) - print(f"Turn 2: {r2.output_text}\n") - - # Turn 3 - r3 = client.responses.create( - model="gpt-4.1-nano", - input="Name three famous landmarks there.", - previous_response_id=r2.id, + third = client.responses.create( + model=model_name(), + input="Three landmarks?", + previous_response_id=second.id, store=True, ) - print(f"Turn 3: {r3.output_text}") - - -chat() + return third.output_text + + +try: + client = make_sync_client() + try: + with example_attributes(EXAMPLE): + print_result(EXAMPLE, run()) + finally: + client.close() +finally: + finish_respan(respan) diff --git a/python/tracing/openai-sdk/responses_prompt.py b/python/tracing/openai-sdk/responses_prompt.py index 7431174..5aaf994 100644 --- a/python/tracing/openai-sdk/responses_prompt.py +++ b/python/tracing/openai-sdk/responses_prompt.py @@ -1,46 +1,46 @@ -"""Responses API Prompt — Use a Respan-managed prompt with the Responses API. - -With schema_version 2, the prompt template becomes `instructions` and the -body `input` is preserved as the user turn. -""" +"""A managed-prompt-shaped request sent through the Responses API.""" import os -from dotenv import load_dotenv - -load_dotenv(override=True) - -from openai import OpenAI -from respan import Respan -from respan_instrumentation_openai import OpenAIInstrumentor -respan = Respan(instrumentations=[OpenAIInstrumentor()]) +from respan import workflow -client = OpenAI( - api_key=os.getenv("RESPAN_API_KEY"), - base_url=os.getenv("RESPAN_BASE_URL", "https://api.respan.ai/api"), +from _shared import ( + example_attributes, + finish_respan, + make_respan, + make_sync_client, + model_name, + print_result, ) -PROMPT_ID = "d767498c1cbb4951bb122eef423b5f76" - -response = client.responses.create( - model="gpt-4.1-nano", - input=[ - { - "role": "user", - "content": "Add a real-time notification system for order status updates", - } - ], - extra_body={ - "respan_params": { - "prompt": { - "prompt_id": PROMPT_ID, - "schema_version": 2, - "variables": { - "feature_request": "Add a real-time notification system for order status updates", - }, +EXAMPLE = "responses-prompt" +respan = make_respan(EXAMPLE) + + +@workflow(name="openai_responses_prompt") +def run() -> str: + response = client.responses.create( + model=model_name(), + input="Add order-status notifications.", + extra_body={ + "respan_params": { + "prompt": { + "prompt_id": os.getenv("RESPAN_PROMPT_ID", "deterministic-prompt"), + "schema_version": 2, + "variables": {"feature_request": "Add order notifications"}, + } } - } - }, -) - -print(response.output_text) + }, + ) + return response.output_text + + +try: + client = make_sync_client() + try: + with example_attributes(EXAMPLE): + print_result(EXAMPLE, run()) + finally: + client.close() +finally: + finish_respan(respan) diff --git a/python/tracing/openai-sdk/responses_streaming.py b/python/tracing/openai-sdk/responses_streaming.py index eeaa1bd..3a2567e 100644 --- a/python/tracing/openai-sdk/responses_streaming.py +++ b/python/tracing/openai-sdk/responses_streaming.py @@ -1,29 +1,39 @@ -"""Responses API Streaming — Stream a response, auto-traced.""" +"""Responses API streaming with explicit source close and final flush.""" -import os -from dotenv import load_dotenv +from respan import workflow -load_dotenv(override=True) +from _shared import ( + example_attributes, + finish_respan, + make_respan, + make_sync_client, + model_name, + print_result, +) -from openai import OpenAI -from respan import Respan -from respan_instrumentation_openai import OpenAIInstrumentor +EXAMPLE = "responses-streaming" +respan = make_respan(EXAMPLE) -respan = Respan(instrumentations=[OpenAIInstrumentor()]) -client = OpenAI( - api_key=os.getenv("RESPAN_API_KEY"), - base_url=os.getenv("RESPAN_BASE_URL", "https://api.respan.ai/api"), -) +@workflow(name="openai_responses_streaming") +def run() -> str: + parts: list[str] = [] + stream = client.responses.create( + model=model_name(), input="Write a Python haiku.", stream=True + ) + with stream: + for event in stream: + if event.type == "response.output_text.delta": + parts.append(event.delta) + return "".join(parts) -stream = client.responses.create( - model="gpt-4.1-nano", - instructions="You are a helpful assistant.", - input="Write a haiku about Python.", - stream=True, -) -for event in stream: - if event.type == "response.output_text.delta": - print(event.delta, end="", flush=True) -print() +try: + client = make_sync_client() + try: + with example_attributes(EXAMPLE): + print_result(EXAMPLE, run()) + finally: + client.close() +finally: + finish_respan(respan) diff --git a/python/tracing/openai-sdk/responses_structured_output.py b/python/tracing/openai-sdk/responses_structured_output.py index b329d25..a5c87bb 100644 --- a/python/tracing/openai-sdk/responses_structured_output.py +++ b/python/tracing/openai-sdk/responses_structured_output.py @@ -1,22 +1,20 @@ -"""Responses API Structured Output — Pydantic model parsing, auto-traced.""" - -import os -from dotenv import load_dotenv - -load_dotenv(override=True) +"""Responses.parse structured output on the real OpenAI 3.x parse path.""" from pydantic import BaseModel -from openai import OpenAI -from respan import Respan, workflow -from respan_instrumentation_openai import OpenAIInstrumentor - -respan = Respan(instrumentations=[OpenAIInstrumentor()]) - -client = OpenAI( - api_key=os.getenv("RESPAN_API_KEY"), - base_url=os.getenv("RESPAN_BASE_URL", "https://api.respan.ai/api"), +from respan import workflow + +from _shared import ( + example_attributes, + finish_respan, + make_respan, + make_sync_client, + model_name, + print_result, ) +EXAMPLE = "responses-structured-output" +respan = make_respan(EXAMPLE) + class MovieReview(BaseModel): title: str @@ -26,19 +24,21 @@ class MovieReview(BaseModel): cons: list[str] -@workflow(name="movie_review") -def review(movie: str) -> MovieReview: +@workflow(name="openai_responses_movie_review") +def run(movie: str) -> MovieReview: response = client.responses.parse( - model="gpt-4.1-nano", - instructions="You are a film critic. Rate movies 1-10.", - input=f"Review: {movie}", - text_format=MovieReview, + model=model_name(), input=f"Review: {movie}", text_format=MovieReview ) return response.output_parsed -result = review("The Matrix") -print(f"{result.title} — {result.rating}/10") -print(f"Summary: {result.summary}") -print(f"Pros: {', '.join(result.pros)}") -print(f"Cons: {', '.join(result.cons)}") +try: + client = make_sync_client() + try: + with example_attributes(EXAMPLE): + result = run("The Matrix") + print_result(EXAMPLE, f"{result.title} rating={result.rating}") + finally: + client.close() +finally: + finish_respan(respan) diff --git a/python/tracing/openai-sdk/responses_tool_calls.py b/python/tracing/openai-sdk/responses_tool_calls.py index b1282bb..4eb06fb 100644 --- a/python/tracing/openai-sdk/responses_tool_calls.py +++ b/python/tracing/openai-sdk/responses_tool_calls.py @@ -1,23 +1,21 @@ -"""Responses API Tool Calls — Function calling with the Responses API, auto-traced.""" +"""Two-turn Responses function call with a canonical tool execution span.""" -import os import json -from dotenv import load_dotenv -load_dotenv(override=True) +from respan import tool, workflow -from openai import OpenAI -from respan import Respan, workflow, task -from respan_instrumentation_openai import OpenAIInstrumentor - -respan = Respan(instrumentations=[OpenAIInstrumentor()]) - -client = OpenAI( - api_key=os.getenv("RESPAN_API_KEY"), - base_url=os.getenv("RESPAN_BASE_URL", "https://api.respan.ai/api"), +from _shared import ( + example_attributes, + finish_respan, + make_respan, + make_sync_client, + model_name, + print_result, ) -tools = [ +EXAMPLE = "responses-tool-calls" +respan = make_respan(EXAMPLE) +TOOLS = [ { "type": "function", "name": "get_weather", @@ -33,49 +31,38 @@ ] -@task(name="get_weather") -def get_weather(city: str) -> str: - return f"Sunny, 72°F in {city}" - +@tool(name="get_weather") +def get_weather(city: str) -> dict[str, str]: + return {"city": city, "weather": "sunny", "temperature_c": "22"} -@workflow(name="weather_assistant") -def run(question: str): - response = client.responses.create( - model="gpt-4.1-nano", - instructions="You are a weather assistant.", - input=[{"role": "user", "content": question}], - tools=tools, - ) - # Check for function calls in output - tool_call = next( - (item for item in response.output if item.type == "function_call"), - None, +@workflow(name="openai_responses_weather_assistant") +def run(question: str) -> str: + first = client.responses.create(model=model_name(), input=question, tools=TOOLS) + call = next(item for item in first.output if item.type == "function_call") + result = get_weather(**json.loads(call.arguments)) + final = client.responses.create( + model=model_name(), + input=[ + {"role": "user", "content": question}, + *first.output, + { + "type": "function_call_output", + "call_id": call.call_id, + "output": json.dumps(result), + }, + ], + tools=TOOLS, ) - - if tool_call: - args = json.loads(tool_call.arguments) - result = get_weather(**args) - print(f"Tool: {tool_call.name}({args}) -> {result}") - - # Send tool result back - final = client.responses.create( - model="gpt-4.1-nano", - instructions="You are a weather assistant.", - input=[ - {"role": "user", "content": question}, - *response.output, - { - "type": "function_call_output", - "call_id": tool_call.call_id, - "output": result, - }, - ], - tools=tools, - ) - print(f"Answer: {final.output_text}") - else: - print(f"Answer: {response.output_text}") + return final.output_text -run("What's the weather in Paris?") +try: + client = make_sync_client() + try: + with example_attributes(EXAMPLE): + print_result(EXAMPLE, run("Weather in Paris?")) + finally: + client.close() +finally: + finish_respan(respan) diff --git a/python/tracing/openai-sdk/run_all.py b/python/tracing/openai-sdk/run_all.py new file mode 100644 index 0000000..9b90b8c --- /dev/null +++ b/python/tracing/openai-sdk/run_all.py @@ -0,0 +1,71 @@ +from __future__ import annotations + +import os +import subprocess +import sys +from datetime import UTC, datetime +from pathlib import Path + +EXAMPLE_DIR = Path(__file__).resolve().parent +EXAMPLES = [ + "hello_world.py", + "async_parallel.py", + "attributes.py", + "batch.py", + "batch_async.py", + "decorators.py", + "multi_turn.py", + "prompt.py", + "prompt_multi_turn.py", + "responses_hello_world.py", + "responses_multi_turn.py", + "responses_prompt.py", + "responses_streaming.py", + "responses_structured_output.py", + "responses_tool_calls.py", + "streaming.py", + "structured_output.py", + "tool_calls.py", +] + + +def marker() -> str: + configured = os.getenv("RESPAN_EXAMPLE_RUN_ID") + if configured: + return configured + return f"openai-sdk-{datetime.now(UTC).strftime('%Y%m%dT%H%M%SZ')}" + + +def main() -> int: + shared_marker = marker() + environment = os.environ.copy() + environment["RESPAN_EXAMPLE_RUN_ID"] = shared_marker + environment["PYTHONDONTWRITEBYTECODE"] = "1" + failures: list[str] = [] + + print(f"RESPAN_EXAMPLE_RUN_ID={shared_marker}", flush=True) + for index, script_name in enumerate(EXAMPLES, start=1): + print(f"[{index:02d}/{len(EXAMPLES):02d}] {script_name}", flush=True) + try: + result = subprocess.run( + [sys.executable, str(EXAMPLE_DIR / script_name)], + cwd=EXAMPLE_DIR, + env=environment, + check=False, + timeout=120, + ) + except subprocess.TimeoutExpired: + failures.append(f"{script_name}:timeout") + continue + if result.returncode: + failures.append(f"{script_name}:{result.returncode}") + + print(f"completed={len(EXAMPLES) - len(failures)}/{len(EXAMPLES)}", flush=True) + if failures: + print(f"failures={','.join(failures)}", flush=True) + return 1 + return 0 + + +if __name__ == "__main__": + raise SystemExit(main()) diff --git a/python/tracing/openai-sdk/streaming.py b/python/tracing/openai-sdk/streaming.py index 940d8cb..fba1354 100644 --- a/python/tracing/openai-sdk/streaming.py +++ b/python/tracing/openai-sdk/streaming.py @@ -1,30 +1,42 @@ -"""Streaming — Stream a chat completion, auto-traced.""" +"""Chat Completions streaming with explicit close and exact usage.""" -import os -from dotenv import load_dotenv - -load_dotenv(override=True) - -from openai import OpenAI -from respan import Respan -from respan_instrumentation_openai import OpenAIInstrumentor - -respan = Respan(instrumentations=[OpenAIInstrumentor()]) - -client = OpenAI( - api_key=os.getenv("RESPAN_API_KEY"), - base_url=os.getenv("RESPAN_BASE_URL", "https://api.respan.ai/api"), -) - -stream = client.chat.completions.create( - model="gpt-4.1-nano", - messages=[{"role": "user", "content": "Write a haiku about Python."}], - stream=True, +from respan import workflow +from _shared import ( + example_attributes, + finish_respan, + make_respan, + make_sync_client, + model_name, + print_result, ) -for chunk in stream: - content = chunk.choices[0].delta.content - if content: - print(content, end="", flush=True) -print() +EXAMPLE = "streaming" +respan = make_respan(EXAMPLE) + + +@workflow(name="openai_chat_streaming") +def run() -> str: + parts: list[str] = [] + stream = client.chat.completions.create( + model=model_name(), + messages=[{"role": "user", "content": "Write a Python haiku."}], + stream=True, + stream_options={"include_usage": True}, + ) + with stream: + for chunk in stream: + if chunk.choices and chunk.choices[0].delta.content: + parts.append(chunk.choices[0].delta.content) + return "".join(parts) + + +try: + client = make_sync_client() + try: + with example_attributes(EXAMPLE): + print_result(EXAMPLE, run()) + finally: + client.close() +finally: + finish_respan(respan) diff --git a/python/tracing/openai-sdk/structured_output.py b/python/tracing/openai-sdk/structured_output.py index 49c2977..5152569 100644 --- a/python/tracing/openai-sdk/structured_output.py +++ b/python/tracing/openai-sdk/structured_output.py @@ -1,22 +1,20 @@ -"""Structured Output — JSON mode with Pydantic, auto-traced.""" - -import os -from dotenv import load_dotenv - -load_dotenv(override=True) +"""Chat Completions.parse structured output on OpenAI 3.x.""" from pydantic import BaseModel -from openai import OpenAI -from respan import Respan, workflow -from respan_instrumentation_openai import OpenAIInstrumentor - -respan = Respan(instrumentations=[OpenAIInstrumentor()]) - -client = OpenAI( - api_key=os.getenv("RESPAN_API_KEY"), - base_url=os.getenv("RESPAN_BASE_URL", "https://api.respan.ai/api"), +from respan import workflow + +from _shared import ( + example_attributes, + finish_respan, + make_respan, + make_sync_client, + model_name, + print_result, ) +EXAMPLE = "structured-output" +respan = make_respan(EXAMPLE) + class MovieReview(BaseModel): title: str @@ -26,25 +24,23 @@ class MovieReview(BaseModel): cons: list[str] -@workflow(name="movie_review") -def review(movie: str) -> MovieReview: +@workflow(name="openai_chat_movie_review") +def run(movie: str) -> MovieReview: response = client.beta.chat.completions.parse( - model="gpt-4.1-nano", - messages=[ - { - "role": "system", - "content": "You are a film critic. Rate movies 1-10.", - }, - {"role": "user", "content": f"Review: {movie}"}, - ], + model=model_name(), + messages=[{"role": "user", "content": f"Review: {movie}"}], response_format=MovieReview, - ) return response.choices[0].message.parsed -result = review("The Matrix") -print(f"{result.title} — {result.rating}/10") -print(f"Summary: {result.summary}") -print(f"Pros: {', '.join(result.pros)}") -print(f"Cons: {', '.join(result.cons)}") +try: + client = make_sync_client() + try: + with example_attributes(EXAMPLE): + result = run("The Matrix") + print_result(EXAMPLE, f"{result.title} rating={result.rating}") + finally: + client.close() +finally: + finish_respan(respan) diff --git a/python/tracing/openai-sdk/test_example_contract.py b/python/tracing/openai-sdk/test_example_contract.py new file mode 100644 index 0000000..ad6677d --- /dev/null +++ b/python/tracing/openai-sdk/test_example_contract.py @@ -0,0 +1,146 @@ +from __future__ import annotations + +import ast +import importlib.util +import subprocess +from pathlib import Path +from types import ModuleType + +EXAMPLE_DIR = Path(__file__).resolve().parent +PUBLIC_EXAMPLES = { + path.name + for path in EXAMPLE_DIR.glob("*.py") + if not path.name.startswith("_") + and path.name not in {"run_all.py", "test_example_contract.py"} +} +CLIENT_EXAMPLES = { + path.name + for path in EXAMPLE_DIR.glob("*.py") + if path.name in PUBLIC_EXAMPLES + and ( + "make_sync_client" in path.read_text() + or "make_async_client" in path.read_text() + ) +} + + +def _load_runner() -> ModuleType: + spec = importlib.util.spec_from_file_location( + "openai_example_runner", EXAMPLE_DIR / "run_all.py" + ) + assert spec is not None and spec.loader is not None + module = importlib.util.module_from_spec(spec) + spec.loader.exec_module(module) + return module + + +def test_run_all_lists_every_public_example_once() -> None: + module = ast.parse((EXAMPLE_DIR / "run_all.py").read_text()) + assignment = next( + node + for node in module.body + if isinstance(node, ast.Assign) + and any( + isinstance(target, ast.Name) and target.id == "EXAMPLES" + for target in node.targets + ) + ) + listed = ast.literal_eval(assignment.value) + assert len(listed) == 18 + assert len(set(listed)) == len(listed) + assert set(listed) == PUBLIC_EXAMPLES + + +def test_shared_loader_preserves_shell_marker() -> None: + source = (EXAMPLE_DIR / "_shared.py").read_text() + assert "override=False" in source + assert 'os.getenv("RESPAN_EXAMPLE_RUN_ID")' in source + assert '"example_run_id": marker' in source + + +def test_every_example_has_explicit_shutdown() -> None: + for script_name in PUBLIC_EXAMPLES: + source = (EXAMPLE_DIR / script_name).read_text() + assert "finish_respan(respan)" in source, script_name + + +def _contains_call(nodes: list[ast.stmt], name: str) -> bool: + for node in nodes: + for child in ast.walk(node): + if not isinstance(child, ast.Call): + continue + if isinstance(child.func, ast.Name) and child.func.id == name: + return True + if isinstance(child.func, ast.Attribute) and child.func.attr == name: + return True + return False + + +def test_client_examples_always_close_before_respan_shutdown() -> None: + for script_name in CLIENT_EXAMPLES: + module = ast.parse((EXAMPLE_DIR / script_name).read_text()) + scope = module.body + if script_name == "async_parallel.py": + main = next( + node + for node in module.body + if isinstance(node, ast.AsyncFunctionDef) and node.name == "main" + ) + scope = main.body + + outer = next(node for node in scope if isinstance(node, ast.Try)) + client_assignment = next( + node + for node in outer.body + if isinstance(node, ast.Assign) + and any( + isinstance(target, ast.Name) and target.id == "client" + for target in node.targets + ) + ) + assert isinstance(client_assignment.value, ast.Call), script_name + assert isinstance(client_assignment.value.func, ast.Name), script_name + assert client_assignment.value.func.id in { + "make_sync_client", + "make_async_client", + }, script_name + + nested = next(node for node in outer.body if isinstance(node, ast.Try)) + assert _contains_call(nested.finalbody, "close"), script_name + assert _contains_call(outer.finalbody, "finish_respan"), script_name + + +def test_run_all_records_timeout_and_continues(monkeypatch, capsys) -> None: + runner = _load_runner() + runner.EXAMPLES = ["first.py", "second.py"] + calls: list[str] = [] + + def fake_run(command, **kwargs): + del kwargs + script = Path(command[-1]).name + calls.append(script) + if script == "first.py": + raise subprocess.TimeoutExpired(command, 120) + return subprocess.CompletedProcess(command, 0) + + monkeypatch.setattr(runner.subprocess, "run", fake_run) + assert runner.main() == 1 + assert calls == ["first.py", "second.py"] + output = capsys.readouterr().out + assert "completed=1/2" in output + assert "failures=first.py:timeout" in output + + +def test_run_all_disables_child_bytecode_caches(monkeypatch) -> None: + runner = _load_runner() + runner.EXAMPLES = ["example.py"] + captured_environment: dict[str, str] = {} + + def fake_run(command, **kwargs): + del command + captured_environment.update(kwargs["env"]) + return subprocess.CompletedProcess([], 0) + + monkeypatch.setattr(runner.subprocess, "run", fake_run) + assert runner.main() == 0 + assert captured_environment["PYTHONDONTWRITEBYTECODE"] == "1" diff --git a/python/tracing/openai-sdk/tool_calls.py b/python/tracing/openai-sdk/tool_calls.py index 8f4f695..1945c16 100644 --- a/python/tracing/openai-sdk/tool_calls.py +++ b/python/tracing/openai-sdk/tool_calls.py @@ -1,23 +1,21 @@ -"""Tool Calls — Function calling with OpenAI, auto-traced.""" +"""Two-turn Chat function call with a canonical tool execution span.""" -import os import json -from dotenv import load_dotenv -load_dotenv(override=True) +from respan import tool, workflow -from openai import OpenAI -from respan import Respan, workflow, task -from respan_instrumentation_openai import OpenAIInstrumentor - -respan = Respan(instrumentations=[OpenAIInstrumentor()]) - -client = OpenAI( - api_key=os.getenv("RESPAN_API_KEY"), - base_url=os.getenv("RESPAN_BASE_URL", "https://api.respan.ai/api"), +from _shared import ( + example_attributes, + finish_respan, + make_respan, + make_sync_client, + model_name, + print_result, ) -tools = [ +EXAMPLE = "tool-calls" +respan = make_respan(EXAMPLE) +TOOLS = [ { "type": "function", "function": { @@ -33,42 +31,40 @@ ] -@task(name="get_weather") -def get_weather(city: str) -> str: - return f"Sunny, 72F in {city}" - +@tool(name="get_weather") +def get_weather(city: str) -> dict[str, str]: + return {"city": city, "weather": "sunny", "temperature_c": "22"} -@workflow(name="weather_assistant") -def run(question: str): - messages = [{"role": "user", "content": question}] - - response = client.chat.completions.create( - model="gpt-4.1-nano", - messages=messages, - tools=tools, +@workflow(name="openai_chat_weather_assistant") +def run(question: str) -> str: + messages: list = [{"role": "user", "content": question}] + first = client.chat.completions.create( + model=model_name(), messages=messages, tools=TOOLS ) - message = response.choices[0].message - - if message.tool_calls: - messages.append(message) - for tc in message.tool_calls: - args = json.loads(tc.function.arguments) - result = get_weather(**args) - print(f"Tool: {tc.function.name}({args}) -> {result}") - messages.append( - {"role": "tool", "tool_call_id": tc.id, "content": result} - ) - - final = client.chat.completions.create( - model="gpt-4.1-nano", - messages=messages, - tools=tools, - + message = first.choices[0].message + messages.append(message) + for call in message.tool_calls or []: + result = get_weather(**json.loads(call.function.arguments)) + messages.append( + { + "role": "tool", + "tool_call_id": call.id, + "content": json.dumps(result), + } ) - print(f"Answer: {final.choices[0].message.content}") - else: - print(f"Answer: {message.content}") - - -run("What's the weather in Paris?") + final = client.chat.completions.create( + model=model_name(), messages=messages, tools=TOOLS + ) + return final.choices[0].message.content or "" + + +try: + client = make_sync_client() + try: + with example_attributes(EXAMPLE): + print_result(EXAMPLE, run("Weather in Paris?")) + finally: + client.close() +finally: + finish_respan(respan) diff --git a/python/tracing/openinference/01_chat_provider.py b/python/tracing/openinference/01_chat_provider.py new file mode 100644 index 0000000..1ad9d1f --- /dev/null +++ b/python/tracing/openinference/01_chat_provider.py @@ -0,0 +1,56 @@ +from __future__ import annotations + +import json + +from _shared import ( + example_attributes, + example_run_id, + finish_respan, + make_respan, + print_result, + tracer, + workflow_name, +) +from respan import workflow + +EXAMPLE_NAME = "chat-provider" + + +@workflow(name=workflow_name(EXAMPLE_NAME)) +def chat_provider_workflow(prompt: str) -> str: + response = "OpenInference attributes are translated into one canonical contract." + with tracer().start_as_current_span("openai.chat") as span: + span.set_attribute("openinference.span.kind", "LLM") + span.set_attribute("llm.model_name", "gpt-4.1-mini") + span.set_attribute("llm.system", "OpenAI") + span.set_attribute("llm.provider", "OpenAI") + span.set_attribute("llm.invocation_parameters", '{"temperature":0.1}') + span.set_attribute("llm.input_messages.0.message.role", "user") + span.set_attribute("llm.input_messages.0.message.content", prompt) + span.set_attribute("llm.output_messages.0.message.role", "assistant") + span.set_attribute("llm.output_messages.0.message.content", response) + span.set_attribute("llm.output_messages.0.message.finish_reason", "stop") + span.set_attribute("llm.token_count.prompt", 11) + span.set_attribute("llm.token_count.completion", 9) + span.set_attribute("llm.token_count.total", 20) + span.set_attribute("input.value", json.dumps({"prompt": prompt})) + span.set_attribute("output.value", json.dumps({"response": response})) + return response + + +def run() -> None: + run_id = example_run_id() + respan = make_respan(EXAMPLE_NAME, run_id) + result = "" + try: + with example_attributes(EXAMPLE_NAME, run_id): + result = chat_provider_workflow( + "Explain the OpenInference translation boundary in one sentence." + ) + finally: + finish_respan(respan) + print_result(EXAMPLE_NAME, run_id, result) + + +if __name__ == "__main__": + run() diff --git a/python/tracing/openinference/02_tool_call.py b/python/tracing/openinference/02_tool_call.py new file mode 100644 index 0000000..0ea5519 --- /dev/null +++ b/python/tracing/openinference/02_tool_call.py @@ -0,0 +1,86 @@ +from __future__ import annotations + +import json + +from _shared import ( + example_attributes, + example_run_id, + finish_respan, + make_respan, + print_result, + tracer, + workflow_name, +) +from respan import workflow + +EXAMPLE_NAME = "tool-call" +TOOL_DEFINITION = { + "type": "function", + "function": { + "name": "lookup_weather", + "description": "Return deterministic weather for a city.", + "parameters": { + "type": "object", + "properties": {"city": {"type": "string"}}, + "required": ["city"], + }, + }, +} + + +@workflow(name=workflow_name(EXAMPLE_NAME)) +def tool_call_workflow(city: str) -> str: + call_id = "call-weather-001" + arguments = json.dumps({"city": city}) + result = {"city": city, "temperature_c": 22, "condition": "sunny"} + + with tracer().start_as_current_span("openai.chat.tool_call") as chat_span: + chat_span.set_attribute("openinference.span.kind", "LLM") + chat_span.set_attribute("llm.model_name", "gpt-4.1-mini") + chat_span.set_attribute("llm.system", "openai") + chat_span.set_attribute("llm.provider", "openai") + chat_span.set_attribute("llm.tools", json.dumps([TOOL_DEFINITION])) + chat_span.set_attribute("llm.input_messages.0.message.role", "user") + chat_span.set_attribute( + "llm.input_messages.0.message.content", + f"What is the weather in {city}?", + ) + chat_span.set_attribute("llm.output_messages.0.message.role", "assistant") + chat_span.set_attribute( + "llm.output_messages.0.message.tool_calls.0.tool_call.id", + call_id, + ) + chat_span.set_attribute( + "llm.output_messages.0.message.tool_calls.0.tool_call.function.name", + "lookup_weather", + ) + chat_span.set_attribute( + "llm.output_messages.0.message.tool_calls.0.tool_call.function.arguments", + arguments, + ) + chat_span.set_attribute("llm.token_count.prompt", 18) + chat_span.set_attribute("llm.token_count.completion", 6) + chat_span.set_attribute("llm.token_count.total", 24) + + with tracer().start_as_current_span("lookup_weather") as tool_span: + tool_span.set_attribute("openinference.span.kind", "TOOL") + tool_span.set_attribute("tool.name", "lookup_weather") + tool_span.set_attribute("input.value", arguments) + tool_span.set_attribute("output.value", json.dumps(result)) + return json.dumps(result, sort_keys=True) + + +def run() -> None: + run_id = example_run_id() + respan = make_respan(EXAMPLE_NAME, run_id) + result = "" + try: + with example_attributes(EXAMPLE_NAME, run_id): + result = tool_call_workflow("Tokyo") + finally: + finish_respan(respan) + print_result(EXAMPLE_NAME, run_id, result) + + +if __name__ == "__main__": + run() diff --git a/python/tracing/openinference/03_embedding.py b/python/tracing/openinference/03_embedding.py new file mode 100644 index 0000000..64c6ceb --- /dev/null +++ b/python/tracing/openinference/03_embedding.py @@ -0,0 +1,45 @@ +from __future__ import annotations + +from _shared import ( + example_attributes, + example_run_id, + finish_respan, + make_respan, + print_result, + tracer, + workflow_name, +) +from respan import workflow + +EXAMPLE_NAME = "embedding" + + +@workflow(name=workflow_name(EXAMPLE_NAME)) +def embedding_workflow(text: str) -> str: + vector = (0.125, -0.25, 0.5, 0.75) + with tracer().start_as_current_span("openai.embedding") as span: + span.set_attribute("openinference.span.kind", "EMBEDDING") + span.set_attribute("embedding.model_name", "text-embedding-3-small") + span.set_attribute("embedding.embeddings.0.embedding.text", text) + span.set_attribute("embedding.embeddings.0.embedding.vector", vector) + span.set_attribute("llm.system", "openai") + span.set_attribute("llm.provider", "openai") + span.set_attribute("llm.token_count.prompt", 5) + span.set_attribute("llm.token_count.total", 5) + return f"captured deterministic vector with {len(vector)} dimensions" + + +def run() -> None: + run_id = example_run_id() + respan = make_respan(EXAMPLE_NAME, run_id) + result = "" + try: + with example_attributes(EXAMPLE_NAME, run_id): + result = embedding_workflow("OpenInference embedding contract") + finally: + finish_respan(respan) + print_result(EXAMPLE_NAME, run_id, result) + + +if __name__ == "__main__": + run() diff --git a/python/tracing/openinference/04_expected_failure.py b/python/tracing/openinference/04_expected_failure.py new file mode 100644 index 0000000..8998b86 --- /dev/null +++ b/python/tracing/openinference/04_expected_failure.py @@ -0,0 +1,52 @@ +from __future__ import annotations + +import json + +from _shared import ( + example_attributes, + example_run_id, + finish_respan, + make_respan, + print_result, + tracer, + workflow_name, +) +from opentelemetry.trace import Status, StatusCode +from respan import workflow + +EXAMPLE_NAME = "expected-failure" +ERROR_MESSAGE = "openinference deterministic provider failure" + + +@workflow(name=workflow_name(EXAMPLE_NAME)) +def expected_failure_workflow(operation: str) -> None: + error = RuntimeError(ERROR_MESSAGE) + with tracer().start_as_current_span("openai.chat.failure") as span: + span.set_attribute("openinference.span.kind", "LLM") + span.set_attribute("llm.model_name", "gpt-4.1-mini") + span.set_attribute("llm.system", "openai") + span.set_attribute("llm.provider", "openai") + span.set_attribute("input.value", json.dumps({"operation": operation})) + span.record_exception(error) + span.set_status(Status(StatusCode.ERROR, ERROR_MESSAGE)) + raise error + + +def run() -> None: + run_id = example_run_id() + respan = make_respan(EXAMPLE_NAME, run_id) + observed = "" + try: + with example_attributes(EXAMPLE_NAME, run_id): + expected_failure_workflow("validate provider error translation") + except RuntimeError as error: + if str(error) != ERROR_MESSAGE: + raise + observed = f"observed expected error: {error}" + finally: + finish_respan(respan) + print_result(EXAMPLE_NAME, run_id, observed) + + +if __name__ == "__main__": + run() diff --git a/python/tracing/openinference/05_streaming_privacy.py b/python/tracing/openinference/05_streaming_privacy.py new file mode 100644 index 0000000..d330a4f --- /dev/null +++ b/python/tracing/openinference/05_streaming_privacy.py @@ -0,0 +1,67 @@ +from __future__ import annotations + +import json + +from _shared import ( + example_attributes, + example_run_id, + finish_respan, + make_respan, + print_result, + tracer, + workflow_name, +) +from openinference.semconv.trace import SpanAttributes as OISpanAttributes +from respan import workflow + +EXAMPLE_NAME = "streaming-privacy" + + +@workflow(name=workflow_name(EXAMPLE_NAME)) +def streaming_privacy_workflow(description: str) -> str: + chunks = ("bounded ", "streaming ", "content") + response = "".join(chunks) + with tracer().start_as_current_span("openai.chat.stream") as span: + span.set_attribute("openinference.span.kind", "LLM") + span.set_attribute( + OISpanAttributes.LLM_INVOCATION_PARAMETERS, + json.dumps({"stream": True}), + ) + span.set_attribute("llm.model_name", "gpt-4.1-mini") + span.set_attribute("llm.system", "openai") + span.set_attribute("llm.provider", "openai") + span.set_attribute( + "input.value", + json.dumps( + { + "description": description, + "authorization": "Bearer example-secret-must-be-redacted", + "nested": {"api_key": "sk-example-secret-123456"}, + } + ), + ) + span.set_attribute("output.value", json.dumps({"response": response})) + span.set_attribute("llm.output_messages.0.message.role", "assistant") + span.set_attribute("llm.output_messages.0.message.content", response) + span.set_attribute("llm.token_count.prompt", 7) + span.set_attribute("llm.token_count.completion", 3) + span.set_attribute("llm.token_count.total", 10) + return response + + +def run() -> None: + run_id = example_run_id() + respan = make_respan(EXAMPLE_NAME, run_id) + result = "" + try: + with example_attributes(EXAMPLE_NAME, run_id): + result = streaming_privacy_workflow( + "validate a streaming span without exporting credentials" + ) + finally: + finish_respan(respan) + print_result(EXAMPLE_NAME, run_id, result) + + +if __name__ == "__main__": + run() diff --git a/python/tracing/openinference/README.md b/python/tracing/openinference/README.md new file mode 100644 index 0000000..1b9654f --- /dev/null +++ b/python/tracing/openinference/README.md @@ -0,0 +1,48 @@ +# OpenInference Contract Examples + +These deterministic examples validate the generic +`respan-instrumentation-openinference` translation boundary without depending +on a vendor API. They emit standard OpenInference attributes through the real +OpenTelemetry provider and Respan exporter, covering: + +- chat content, provider identity, model, and provider-reported usage; +- tool definitions, current-turn tool calls, and a connected tool execution; +- embedding input, model, usage, and vector output; +- an expected OTel `ERROR` with no synthetic usage; +- streaming metadata plus bounded, redacted input/output content. + +Each script creates one named workflow, inherits the exact +`RESPAN_EXAMPLE_RUN_ID` marker when supplied, loads credentials from the +repository `.env` without overriding the shell, and explicitly flushes and +shuts down Respan. + +## Install from the registry + +```bash +cd python/tracing/openinference +python -m venv .venv +source .venv/bin/activate +python -m pip install -r requirements.txt +``` + +## Validate a local `respan` checkout + +Keep `requirements.txt` registry-portable, then overlay editable local packages: + +```bash +python -m pip install -e ../../../../respan/python-sdks/respan-sdk +python -m pip install -e ../../../../respan/python-sdks/respan-tracing +python -m pip install -e ../../../../respan/python-sdks/respan +python -m pip install -e ../../../../respan/python-sdks/instrumentations/respan-instrumentation-openinference +``` + +## Run + +```bash +RESPAN_EXAMPLE_RUN_ID=otel2-openinference-check python run_all.py +``` + +The runner executes all five scripts, prints each exit code, and returns nonzero +if any process fails. Expected output is five traces containing 11 records: one +workflow root per script, five translated OpenInference operations, and one tool +execution child. diff --git a/python/tracing/openinference/_shared.py b/python/tracing/openinference/_shared.py new file mode 100644 index 0000000..3fa9638 --- /dev/null +++ b/python/tracing/openinference/_shared.py @@ -0,0 +1,111 @@ +from __future__ import annotations + +import os +from collections.abc import Iterator +from contextlib import contextmanager +from datetime import UTC, datetime +from pathlib import Path +from typing import Any + +from dotenv import load_dotenv +from opentelemetry import trace +from opentelemetry.sdk.trace import SpanProcessor +from respan import Respan, propagate_attributes +from respan_instrumentation_openinference import OpenInferenceInstrumentor + +PROJECT_ROOT = Path(__file__).resolve().parents[3] +DEFAULT_RESPAN_BASE_URL = "https://api.respan.ai/api" +INTEGRATION = "openinference" + + +class ContractSourceProcessor(SpanProcessor): + """No-op source processor used to activate the generic OI translator.""" + + def on_start(self, span: Any, parent_context: Any = None) -> None: + del span, parent_context + + def on_end(self, span: Any) -> None: + del span + + def shutdown(self) -> None: + pass + + def force_flush(self, timeout_millis: int = 30_000) -> bool: + del timeout_millis + return True + + +def load_root_env() -> None: + # An exact shell marker must win over any value in the repository .env. + load_dotenv(PROJECT_ROOT / ".env", override=False) + + +def require_respan_api_key() -> str: + load_root_env() + api_key = os.getenv("RESPAN_API_KEY") + if not api_key: + raise RuntimeError("RESPAN_API_KEY must be set in the repo-root .env") + return api_key + + +def example_run_id() -> str: + load_root_env() + inherited = os.getenv("RESPAN_EXAMPLE_RUN_ID") + if inherited: + return inherited + return f"openinference-{datetime.now(UTC).strftime('%Y%m%dT%H%M%SZ')}" + + +def make_respan(example_name: str, run_id: str) -> Respan: + current_workflow = workflow_name(example_name) + return Respan( + api_key=require_respan_api_key(), + base_url=os.getenv("RESPAN_BASE_URL", DEFAULT_RESPAN_BASE_URL).rstrip("/"), + app_name="openinference-contract-examples", + environment=os.getenv("RESPAN_ENVIRONMENT", "example"), + metadata={ + "example_run_id": run_id, + "integration": INTEGRATION, + "example": example_name, + "workflow_name": current_workflow, + }, + instrumentations=[OpenInferenceInstrumentor(ContractSourceProcessor)], + ) + + +def workflow_name(example_name: str) -> str: + return f"openinference_{example_name.replace('-', '_')}" + + +@contextmanager +def example_attributes(example_name: str, run_id: str) -> Iterator[None]: + current_workflow = workflow_name(example_name) + with propagate_attributes( + custom_identifier=f"{INTEGRATION}-{example_name}-{run_id}", + trace_group_identifier=current_workflow, + metadata={ + "example_run_id": run_id, + "integration": INTEGRATION, + "example": example_name, + "workflow_name": current_workflow, + }, + ): + yield + + +def tracer(): + return trace.get_tracer("openinference.contract.examples") + + +def finish_respan(respan: Respan) -> None: + try: + respan.flush() + finally: + respan.shutdown() + + +def print_result(example_name: str, run_id: str, result: str) -> None: + print(f"example={example_name}") + print(f"example_run_id={run_id}") + print(f"workflow_name={workflow_name(example_name)}") + print(result) diff --git a/python/tracing/openinference/requirements.txt b/python/tracing/openinference/requirements.txt new file mode 100644 index 0000000..5e0c7a6 --- /dev/null +++ b/python/tracing/openinference/requirements.txt @@ -0,0 +1,3 @@ +python-dotenv>=1.0.0,<2.0.0 +respan-ai>=4.1.0 +respan-instrumentation-openinference>=1.2.2 diff --git a/python/tracing/openinference/run_all.py b/python/tracing/openinference/run_all.py new file mode 100644 index 0000000..6b4ccf4 --- /dev/null +++ b/python/tracing/openinference/run_all.py @@ -0,0 +1,60 @@ +from __future__ import annotations + +import os +import subprocess +import sys +from datetime import UTC, datetime +from pathlib import Path + +EXAMPLE_SCRIPTS = ( + "01_chat_provider.py", + "02_tool_call.py", + "03_embedding.py", + "04_expected_failure.py", + "05_streaming_privacy.py", +) +EXAMPLE_TIMEOUT_SECONDS = 120 + + +def resolved_run_id() -> str: + return os.getenv("RESPAN_EXAMPLE_RUN_ID") or ( + f"openinference-{datetime.now(UTC).strftime('%Y%m%dT%H%M%SZ')}" + ) + + +def main() -> int: + directory = Path(__file__).resolve().parent + environment = os.environ.copy() + environment["RESPAN_EXAMPLE_RUN_ID"] = resolved_run_id() + failures: list[tuple[str, int | str]] = [] + + print(f"example_run_id={environment['RESPAN_EXAMPLE_RUN_ID']}", flush=True) + for script in EXAMPLE_SCRIPTS: + print(f"running={script}", flush=True) + try: + result = subprocess.run( + [sys.executable, str(directory / script)], + cwd=directory, + env=environment, + check=False, + timeout=EXAMPLE_TIMEOUT_SECONDS, + ) + except subprocess.TimeoutExpired: + print( + f"finished={script} timeout={EXAMPLE_TIMEOUT_SECONDS}s", + flush=True, + ) + failures.append((script, "timeout")) + continue + print(f"finished={script} exit={result.returncode}", flush=True) + if result.returncode: + failures.append((script, result.returncode)) + + if failures: + print(f"failures={failures}", file=sys.stderr) + return 1 + return 0 + + +if __name__ == "__main__": + raise SystemExit(main()) diff --git a/python/tracing/openinference/test_example_contract.py b/python/tracing/openinference/test_example_contract.py new file mode 100644 index 0000000..02b5447 --- /dev/null +++ b/python/tracing/openinference/test_example_contract.py @@ -0,0 +1,92 @@ +from __future__ import annotations + +import ast +import os +from pathlib import Path + +import _shared +import run_all +from _shared import example_run_id + + +def test_shell_marker_wins_over_repository_env(monkeypatch): + marker = "openinference-shell-marker" + monkeypatch.setenv("RESPAN_EXAMPLE_RUN_ID", marker) + assert example_run_id() == marker + assert run_all.resolved_run_id() == marker + + +def test_run_all_lists_every_example_once(): + directory = Path(__file__).resolve().parent + expected = tuple( + path.name + for path in sorted(directory.glob("[0-9][0-9]_*.py")) + if path.name != "test_example_contract.py" + ) + assert run_all.EXAMPLE_SCRIPTS == expected + assert len(set(run_all.EXAMPLE_SCRIPTS)) == len(run_all.EXAMPLE_SCRIPTS) + + +def test_common_metadata_and_streaming_source_uses_upstream_openinference(monkeypatch): + captured = {} + + class FakeRespan: + def __init__(self, **kwargs): + captured.update(kwargs) + + monkeypatch.setattr(_shared, "Respan", FakeRespan) + monkeypatch.setattr(_shared, "require_respan_api_key", lambda: "test-key") + + _shared.make_respan("streaming-privacy", "contract-test-marker") + + assert captured["metadata"] == { + "example_run_id": "contract-test-marker", + "integration": "openinference", + "example": "streaming-privacy", + "workflow_name": "openinference_streaming_privacy", + } + streaming_source = (Path(__file__).parent / "05_streaming_privacy.py").read_text() + assert "OISpanAttributes.LLM_INVOCATION_PARAMETERS" in streaming_source + assert '"stream": True' in streaming_source + assert '"gen_ai.is_streaming"' not in streaming_source + + +def test_every_public_example_finishes_respan_in_finally(): + directory = Path(__file__).resolve().parent + for script in run_all.EXAMPLE_SCRIPTS: + tree = ast.parse((directory / script).read_text()) + finally_calls = [ + node + for candidate in ast.walk(tree) + if isinstance(candidate, ast.Try) + for node in ast.walk(ast.Module(body=candidate.finalbody, type_ignores=[])) + if isinstance(node, ast.Call) + and isinstance(node.func, ast.Name) + and node.func.id == "finish_respan" + ] + assert finally_calls, f"{script} must call finish_respan() from finally" + + +def test_run_all_aggregates_process_failures_and_timeouts(monkeypatch): + outcomes = iter((0, 2, "timeout", 3, 0)) + calls = [] + + class Result: + def __init__(self, returncode): + self.returncode = returncode + + def fake_run(*args, **kwargs): + calls.append((args, kwargs)) + outcome = next(outcomes) + if outcome == "timeout": + raise run_all.subprocess.TimeoutExpired(args[0], kwargs["timeout"]) + return Result(outcome) + + monkeypatch.setenv("RESPAN_EXAMPLE_RUN_ID", "contract-test-marker") + monkeypatch.setattr(run_all.subprocess, "run", fake_run) + assert run_all.main() == 1 + assert len(calls) == len(run_all.EXAMPLE_SCRIPTS) + assert all( + kwargs["timeout"] == run_all.EXAMPLE_TIMEOUT_SECONDS for _, kwargs in calls + ) + assert os.environ["RESPAN_EXAMPLE_RUN_ID"] == "contract-test-marker"