From 29fc4af7c1f350a30cd1d45b8ead4b3c9494aec4 Mon Sep 17 00:00:00 2001 From: xumaple <45406854+xumaple@users.noreply.github.com> Date: Wed, 15 Apr 2026 13:29:05 -0400 Subject: [PATCH 1/5] AI-18: Move set_tracing_disabled from workflow to worker startup (#288) * AI-18: Move set_tracing_disabled from workflow to worker startup set_tracing_disabled is a global side effect that shouldn't be called inside deterministic workflow code. Move it to the top of main() in the worker files where it runs once at process startup. Co-Authored-By: Claude Opus 4.6 (1M context) * AI-18: Add comment explaining why tracing is disabled at worker startup Co-Authored-By: Claude Opus 4.6 (1M context) * linting --------- Co-authored-by: Claude Opus 4.6 (1M context) --- openai_agents/model_providers/run_gpt_oss_worker.py | 12 +++++++++++- .../model_providers/run_litellm_provider_worker.py | 6 ++++++ .../model_providers/workflows/gpt_oss_workflow.py | 4 +--- .../workflows/litellm_auto_workflow.py | 4 +--- 4 files changed, 19 insertions(+), 7 deletions(-) diff --git a/openai_agents/model_providers/run_gpt_oss_worker.py b/openai_agents/model_providers/run_gpt_oss_worker.py index 88c85fca..59798a1d 100644 --- a/openai_agents/model_providers/run_gpt_oss_worker.py +++ b/openai_agents/model_providers/run_gpt_oss_worker.py @@ -3,7 +3,12 @@ from datetime import timedelta from typing import Optional -from agents import Model, ModelProvider, OpenAIChatCompletionsModel +from agents import ( + Model, + ModelProvider, + OpenAIChatCompletionsModel, + set_tracing_disabled, +) from openai import AsyncOpenAI from temporalio.client import Client from temporalio.contrib.openai_agents import ModelActivityParameters, OpenAIAgentsPlugin @@ -27,6 +32,11 @@ def get_model(self, model_name: Optional[str]) -> Model: async def main(): + # Disable Agents SDK tracing — the default exporter sends traces to OpenAI's + # backend, which requires an OpenAI API key not available in these samples. + # Call here rather than in the workflow because it's a global side effect. + set_tracing_disabled(disabled=True) + # Configure logging to show workflow debug messages logging.basicConfig(level=logging.WARNING) logging.getLogger("temporalio.workflow").setLevel(logging.DEBUG) diff --git a/openai_agents/model_providers/run_litellm_provider_worker.py b/openai_agents/model_providers/run_litellm_provider_worker.py index 5eb8b8b2..3441013c 100644 --- a/openai_agents/model_providers/run_litellm_provider_worker.py +++ b/openai_agents/model_providers/run_litellm_provider_worker.py @@ -1,6 +1,7 @@ import asyncio from datetime import timedelta +from agents import set_tracing_disabled from agents.extensions.models.litellm_provider import LitellmProvider from temporalio.client import Client from temporalio.contrib.openai_agents import ModelActivityParameters, OpenAIAgentsPlugin @@ -12,6 +13,11 @@ async def main(): + # Disable Agents SDK tracing — the default exporter sends traces to OpenAI's + # backend, which requires an OpenAI API key not available in these samples. + # Call here rather than in the workflow because it's a global side effect. + set_tracing_disabled(disabled=True) + # Create client connected to server at the given address client = await Client.connect( "localhost:7233", diff --git a/openai_agents/model_providers/workflows/gpt_oss_workflow.py b/openai_agents/model_providers/workflows/gpt_oss_workflow.py index d7ed8021..821844b3 100644 --- a/openai_agents/model_providers/workflows/gpt_oss_workflow.py +++ b/openai_agents/model_providers/workflows/gpt_oss_workflow.py @@ -1,6 +1,6 @@ from __future__ import annotations -from agents import Agent, Runner, function_tool, set_tracing_disabled +from agents import Agent, Runner, function_tool from temporalio import workflow @@ -8,8 +8,6 @@ class GptOssWorkflow: @workflow.run async def run(self, prompt: str) -> str: - set_tracing_disabled(disabled=True) - @function_tool def get_weather(city: str): workflow.logger.debug(f"Getting weather for {city}") diff --git a/openai_agents/model_providers/workflows/litellm_auto_workflow.py b/openai_agents/model_providers/workflows/litellm_auto_workflow.py index 4a67ded4..9fe3d40b 100644 --- a/openai_agents/model_providers/workflows/litellm_auto_workflow.py +++ b/openai_agents/model_providers/workflows/litellm_auto_workflow.py @@ -1,6 +1,6 @@ from __future__ import annotations -from agents import Agent, Runner, function_tool, set_tracing_disabled +from agents import Agent, Runner, function_tool from temporalio import workflow @@ -8,8 +8,6 @@ class LitellmAutoWorkflow: @workflow.run async def run(self, prompt: str) -> str: - set_tracing_disabled(disabled=True) - @function_tool def get_weather(city: str): return f"The weather in {city} is sunny." From 26c124480446d50a516855956680171b0fb1b378 Mon Sep 17 00:00:00 2001 From: tconley1428 Date: Fri, 17 Apr 2026 14:01:00 -0700 Subject: [PATCH 2/5] Update dependency version for temporalio 1.26.0 (#291) * Update dependency version for temporalio 1.26.0 * Fix CI: bump pandas to 2.3.3 for Python 3.14, add opentelemetry extra for openai-agents * cleanup types in openai agents samples --------- Co-authored-by: Jason Steving --- .../financial_research_manager.py | 4 +- .../workflows/image_generator_workflow.py | 3 +- pyproject.toml | 16 +- uv.lock | 989 ++++++++++++------ 4 files changed, 660 insertions(+), 352 deletions(-) diff --git a/openai_agents/financial_research_agent/financial_research_manager.py b/openai_agents/financial_research_agent/financial_research_manager.py index 9a437a45..6f2050b2 100644 --- a/openai_agents/financial_research_agent/financial_research_manager.py +++ b/openai_agents/financial_research_agent/financial_research_manager.py @@ -3,7 +3,7 @@ import asyncio from collections.abc import Sequence -from agents import RunConfig, Runner, RunResult, custom_span, trace +from agents import RunConfig, Runner, RunResult, RunResultStreaming, custom_span, trace from temporalio import workflow from openai_agents.financial_research_agent.agents.financials_agent import ( @@ -26,7 +26,7 @@ ) -async def _summary_extractor(run_result: RunResult) -> str: +async def _summary_extractor(run_result: RunResult | RunResultStreaming) -> str: """Custom output extractor for sub-agents that return an AnalysisSummary.""" # The financial/risk analyst agents emit an AnalysisSummary with a `summary` field. # We want the tool call to return just that summary text so the writer can drop it inline. diff --git a/openai_agents/tools/workflows/image_generator_workflow.py b/openai_agents/tools/workflows/image_generator_workflow.py index 7c58091b..20234125 100644 --- a/openai_agents/tools/workflows/image_generator_workflow.py +++ b/openai_agents/tools/workflows/image_generator_workflow.py @@ -4,6 +4,7 @@ from typing import Optional from agents import Agent, ImageGenerationTool, Runner +from openai.types.responses.response_output_item import ImageGenerationCall from temporalio import workflow @@ -34,7 +35,7 @@ async def run(self, prompt: str) -> ImageGenerationResult: for item in result.new_items: if ( item.type == "tool_call_item" - and item.raw_item.type == "image_generation_call" + and isinstance(item.raw_item, ImageGenerationCall) and (img_result := item.raw_item.result) ): image_data = img_result diff --git a/pyproject.toml b/pyproject.toml index caae123c..f65ff1c2 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -6,7 +6,7 @@ authors = [{ name = "Temporal Technologies Inc", email = "sdk@temporal.io" }] requires-python = ">=3.10" readme = "README.md" license = "MIT" -dependencies = ["temporalio>=1.23.0,<2"] +dependencies = ["temporalio>=1.26.0,<2"] [project.urls] Homepage = 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Watkins-Harvey Date: Fri, 17 Apr 2026 20:48:17 -0400 Subject: [PATCH 3/5] Update and pin all GHA actions (#293) --- .github/workflows/ci.yml | 8 ++++---- 1 file changed, 4 insertions(+), 4 deletions(-) diff --git a/.github/workflows/ci.yml b/.github/workflows/ci.yml index 4443cbdd..4a101818 100644 --- a/.github/workflows/ci.yml +++ b/.github/workflows/ci.yml @@ -24,13 +24,13 @@ jobs: runsOn: macos-latest runs-on: ${{ matrix.runsOn || matrix.os }} steps: - - uses: astral-sh/setup-uv@v5 + - uses: astral-sh/setup-uv@cec208311dfd045dd5311c1add060b2062131d57 # v8 - name: Print build information run: "echo head_ref: ${{ github.head_ref }}, ref: ${{ github.ref }}, os: ${{ matrix.os }}, python: ${{ matrix.python }}" - - uses: actions/checkout@v4 + - uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6 with: submodules: recursive - - uses: actions/setup-python@v5 + - uses: actions/setup-python@a309ff8b426b58ec0e2a45f0f869d46889d02405 # v6 with: python-version: ${{ matrix.python }} - run: uv tool install poethepoet @@ -56,7 +56,7 @@ jobs: uv run gevent_async/test/run_combined.py - name: Upload junit-xml artifacts - uses: actions/upload-artifact@v4 + uses: actions/upload-artifact@bbbca2ddaa5d8feaa63e36b76fdaad77386f024f # v7 if: always() with: name: junit-xml--${{github.run_id}}--${{github.run_attempt}}--${{ matrix.python }}--${{ matrix.os }} From b199e50726ee6df1dd2c596e52131526a9e78a58 Mon Sep 17 00:00:00 2001 From: xumaple <45406854+xumaple@users.noreply.github.com> Date: Wed, 22 Apr 2026 14:04:34 -0400 Subject: [PATCH 4/5] Add LangSmith tracing sample (#292) MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit * Add LangSmith tracing sample with basic and chatbot examples Demonstrates the LangSmithPlugin for automatic LangSmith tracing in Temporal workflows. Includes two examples: - basic/: one-shot LLM workflow (prompt → OpenAI → result) - chatbot/: conversational loop with save_note/read_note tools, signals, queries, and dynamic trace names Co-Authored-By: Claude Opus 4.6 (1M context) * Enrich LangSmith tracing usage across basic and chatbot samples - Add @traceable with metadata, tags, and run_type variety to workflows - Add client-side @traceable on starters for end-to-end trace linking - Add --temporal-runs flag to workers and starters for add_temporal_runs toggle - Use run_type="llm" for OpenAI calls, "tool" for save_note, "chain" for orchestration - Add trace tree diagrams to README showing both add_temporal_runs modes - Add "Three Layers of Tracing" section to README (wrap_openai, @traceable, Temporal plugin) - Skip all tests when temporalio.contrib.langsmith is unavailable (pending SDK release) Co-Authored-By: Claude Opus 4.6 (1M context) * Address review feedback: READMEs, comments, activity conventions - Split top-level README into per-sample READMEs (basic/ and chatbot/) with detailed trace structure diagrams and screenshot placeholders - Add replay safety comment on @workflow.run methods explaining why @traceable must wrap an inner function - Make read_note a proper activity for LangSmith trace visibility - Change save_note/read_note to use NoteRequest dataclass (single arg) - Fix misplaced comments in activities (wrap_openai, run_type docs) - Add links to LangSmith docs and Temporal SDK plugin docs - Add add_temporal_runs explanation section to top-level README Co-Authored-By: Claude Opus 4.6 (1M context) * Address audit findings: types, comments, tests, consistency Audit findings addressed: - Remove max_cached_workflows=0 (debugging leftover, not needed) - Expand replay safety comment to explain why (I/O on replay) - Tighten type annotations: str|list[dict[str,Any]], dict[str,Any] - Clarify read_note docstring (passthrough for tracing visibility) - Clarify activity docstrings (retries handled by Temporal, not OpenAI) - Make trace tree annotations consistent across basic/chatbot READMEs - Extract shared test helpers (make_text_response, poll_last_response) - Add TimeoutError on poll failure instead of silent assertion - Fix "simplest possible" wording to "very simple" Co-Authored-By: Claude Opus 4.6 (1M context) * Rewrite replay safety comment to focus on outcome Changed from explaining internals (I/O on replay) to describing what the user would see: duplicate or orphaned traces. Also swept all other comments for outcome-focus — no further changes needed. Co-Authored-By: Claude Opus 4.6 (1M context) * Move save_note/read_note from activities to workflow methods - save_note and read_note are now @traceable methods on ChatbotWorkflow, not activities. Notes live in workflow state (durable via event history). - Remove NoteRequest dataclass and activity registrations - Fix wrap_openai comment placement (describes child span, not parent) - Remove retry policy from basic workflow (unnecessary for simple example) - Add comment highlighting that non-@workflow.run methods can use @traceable - Update chatbot README trace trees to reflect workflow methods vs activities Co-Authored-By: Claude Opus 4.6 (1M context) * Remove screenshot placeholders, rename flag to --add-temporal-runs Co-Authored-By: Claude Opus 4.6 (1M context) * Clean up tests, naming, and dependencies - Remove skip markers from tests — CI should fail loudly if deps missing - Pin temporalio[pydantic,langsmith]>=1.26.0 (plugin is released) - Rename kwargs to response_args in chatbot activity - Remove notes CLI command from chatbot starter - Update chatbot README trace trees for accuracy - Change input prompt from "You: " to "> " Co-Authored-By: Claude Opus 4.6 (1M context) * Fix README trace trees to match actual integration test hierarchies - StartWorkflow/RunWorkflow are siblings, not parent-child - StartActivity/RunActivity are siblings under RunWorkflow - @traceable activity spans nest under RunActivity - Signal/query traces are separate roots (or under client @traceable) - Merge client-side and worker-side into unified trees - add_temporal_runs=False: only @traceable spans, all under client root Co-Authored-By: Claude Opus 4.6 (1M context) * Add openai-agents to conflicting groups for langsmith-tracing temporalio>=1.26.0 requires openai-agents>=0.14.0 but the openai-agents group pins ==0.3.2, causing a resolution failure. Co-Authored-By: Claude Opus 4.6 (1M context) * Fix run commands to include --group langsmith-tracing Without the group flag, uv resolves the base temporalio dep (1.23.0) which doesn't have contrib.langsmith. Co-Authored-By: Claude Opus 4.6 (1M context) * fix tracing project * Address PR review comments and refine chatbot architecture - Simplify basic/worker.py to use asyncio.run(main()) pattern - Basic activity now returns str instead of Response (drops pydantic dep) - Remove pydantic_data_converter from basic worker/starter - Replace chatbot signal+poll with update handler (message_from_user) - Wrap update handler body in @traceable for input/output capture - Inline RetryPolicy in chatbot workflow (no separate RETRY constant) - Add comment about alternative traceable() function-call style - Make PROJECT_NAME a shared constant in starters, pass to client-side @traceable so traces go to the right LangSmith project - Update READMEs with correct trace hierarchies based on real output - Fix wrap_openai span name (ChatOpenAI, not openai.responses.create) - Simplify tests (mocks match new str return type, use execute_update) - Remove poll_last_response helper Co-Authored-By: Claude Opus 4.7 (1M context) * Remove langchain sample, fix CI by relaxing openai version pin The langchain sample's langsmith<0.4 pin conflicts with langsmith-tracing's langsmith>=0.7.0. The langchain sample uses an older custom-interceptor approach that's superseded by the new LangSmithPlugin demonstrated in langsmith_tracing/. Removing it eliminates the dep conflict and the related [tool.uv] conflicts declaration. Also relax openai pin from <2 to no upper bound so it resolves alongside the openai-agents group (which now requires openai>=2.26.0). Add inline comment on max_retries=0 explaining Temporal handles retries. Co-Authored-By: Claude Opus 4.7 (1M context) --------- Co-authored-by: Claude Opus 4.6 (1M context) --- langchain/README.md | 30 -- langchain/activities.py | 34 -- langchain/langchain_interceptor.py | 181 ------- langchain/starter.py | 47 -- langchain/worker.py | 44 -- langchain/workflow.py | 53 -- langsmith_tracing/README.md | 49 ++ langsmith_tracing/__init__.py | 0 langsmith_tracing/basic/README.md | 50 ++ langsmith_tracing/basic/__init__.py | 0 langsmith_tracing/basic/activities.py | 33 ++ langsmith_tracing/basic/starter.py | 54 ++ langsmith_tracing/basic/worker.py | 49 ++ langsmith_tracing/basic/workflows.py | 33 ++ langsmith_tracing/chatbot/README.md | 81 +++ langsmith_tracing/chatbot/__init__.py | 0 langsmith_tracing/chatbot/activities.py | 45 ++ langsmith_tracing/chatbot/starter.py | 76 +++ langsmith_tracing/chatbot/worker.py | 49 ++ langsmith_tracing/chatbot/workflows.py | 178 +++++++ pyproject.toml | 14 +- tests/langsmith_tracing/__init__.py | 0 tests/langsmith_tracing/helpers.py | 33 ++ tests/langsmith_tracing/test_basic.py | 34 ++ tests/langsmith_tracing/test_chatbot.py | 132 +++++ uv.lock | 671 +++++------------------- 26 files changed, 1046 insertions(+), 924 deletions(-) delete mode 100644 langchain/README.md delete mode 100644 langchain/activities.py delete mode 100644 langchain/langchain_interceptor.py delete mode 100644 langchain/starter.py delete mode 100644 langchain/worker.py delete mode 100644 langchain/workflow.py create mode 100644 langsmith_tracing/README.md create mode 100644 langsmith_tracing/__init__.py create mode 100644 langsmith_tracing/basic/README.md create mode 100644 langsmith_tracing/basic/__init__.py create mode 100644 langsmith_tracing/basic/activities.py create mode 100644 langsmith_tracing/basic/starter.py create mode 100644 langsmith_tracing/basic/worker.py create mode 100644 langsmith_tracing/basic/workflows.py create mode 100644 langsmith_tracing/chatbot/README.md create mode 100644 langsmith_tracing/chatbot/__init__.py create mode 100644 langsmith_tracing/chatbot/activities.py create mode 100644 langsmith_tracing/chatbot/starter.py create mode 100644 langsmith_tracing/chatbot/worker.py create mode 100644 langsmith_tracing/chatbot/workflows.py create mode 100644 tests/langsmith_tracing/__init__.py create mode 100644 tests/langsmith_tracing/helpers.py create mode 100644 tests/langsmith_tracing/test_basic.py create mode 100644 tests/langsmith_tracing/test_chatbot.py diff --git a/langchain/README.md b/langchain/README.md deleted file mode 100644 index 506a379d..00000000 --- a/langchain/README.md +++ /dev/null @@ -1,30 +0,0 @@ -# LangChain Sample - -This sample shows you how you can use Temporal to orchestrate workflows for [LangChain](https://www.langchain.com). It includes an interceptor that makes LangSmith traces work seamlessly across Temporal clients, workflows and activities. - -For this sample, the optional `langchain` dependency group must be included. To include, run: - - uv sync --group langchain - -Export your [OpenAI API key](https://platform.openai.com/api-keys) as an environment variable. Replace `YOUR_API_KEY` with your actual OpenAI API key. - - export OPENAI_API_KEY='...' - -To run, first see [README.md](../README.md) for prerequisites. Then, run the following from the root directory to start the -worker: - - uv run langchain/worker.py - -This will start the worker. Then, in another terminal, run the following to execute a workflow: - - uv run langchain/starter.py - -Then, in another terminal, run the following command to translate a phrase: - - curl -X POST "http://localhost:8000/translate?phrase=hello%20world&language1=Spanish&language2=French&language3=Russian" - -Which should produce some output like: - - {"translations":{"French":"Bonjour tout le monde","Russian":"Привет, мир","Spanish":"Hola mundo"}} - -Check [LangSmith](https://smith.langchain.com/) for the corresponding trace. \ No newline at end of file diff --git a/langchain/activities.py b/langchain/activities.py deleted file mode 100644 index a9dec70c..00000000 --- a/langchain/activities.py +++ /dev/null @@ -1,34 +0,0 @@ -from dataclasses import dataclass - -from langchain_openai import ChatOpenAI -from temporalio import activity - -from langchain.prompts import ChatPromptTemplate - - -@dataclass -class TranslateParams: - phrase: str - language: str - - -@activity.defn -async def translate_phrase(params: TranslateParams) -> str: - # LangChain setup - template = """You are a helpful assistant who translates between languages. - Translate the following phrase into the specified language: {phrase} - Language: {language}""" - chat_prompt = ChatPromptTemplate.from_messages( - [ - ("system", template), - ("human", "Translate"), - ] - ) - chain = chat_prompt | ChatOpenAI() - # Use the asynchronous invoke method - return ( - dict( - await chain.ainvoke({"phrase": params.phrase, "language": params.language}) - ).get("content") - or "" - ) diff --git a/langchain/langchain_interceptor.py b/langchain/langchain_interceptor.py deleted file mode 100644 index bb230b6b..00000000 --- a/langchain/langchain_interceptor.py +++ /dev/null @@ -1,181 +0,0 @@ -from __future__ import annotations - -from typing import Any, Mapping, Protocol, Type - -from temporalio import activity, api, client, converter, worker, workflow - -with workflow.unsafe.imports_passed_through(): - from contextlib import contextmanager - - from langsmith import trace, tracing_context - from langsmith.run_helpers import get_current_run_tree - -# Header key for LangChain context -LANGCHAIN_CONTEXT_KEY = "langchain-context" - - -class _InputWithHeaders(Protocol): - headers: Mapping[str, api.common.v1.Payload] - - -def set_header_from_context( - input: _InputWithHeaders, payload_converter: converter.PayloadConverter -) -> None: - # Get current LangChain run tree - run_tree = get_current_run_tree() - if run_tree: - headers = run_tree.to_headers() - input.headers = { - **input.headers, - LANGCHAIN_CONTEXT_KEY: payload_converter.to_payload(headers), - } - - -@contextmanager -def context_from_header( - input: _InputWithHeaders, payload_converter: converter.PayloadConverter -): - payload = input.headers.get(LANGCHAIN_CONTEXT_KEY) - if payload: - run_tree = payload_converter.from_payload(payload, dict) - # Set the run tree in the current context - with tracing_context(parent=run_tree): - yield - else: - yield - - -class LangChainContextPropagationInterceptor(client.Interceptor, worker.Interceptor): - """Interceptor that propagates LangChain context through Temporal.""" - - def __init__( - self, - payload_converter: converter.PayloadConverter = converter.default().payload_converter, - ) -> None: - self._payload_converter = payload_converter - - def intercept_client( - self, next: client.OutboundInterceptor - ) -> client.OutboundInterceptor: - return _LangChainContextPropagationClientOutboundInterceptor( - next, self._payload_converter - ) - - def intercept_activity( - self, next: worker.ActivityInboundInterceptor - ) -> worker.ActivityInboundInterceptor: - return _LangChainContextPropagationActivityInboundInterceptor(next) - - def workflow_interceptor_class( - self, input: worker.WorkflowInterceptorClassInput - ) -> Type[_LangChainContextPropagationWorkflowInboundInterceptor]: - return _LangChainContextPropagationWorkflowInboundInterceptor - - -class _LangChainContextPropagationClientOutboundInterceptor(client.OutboundInterceptor): - def __init__( - self, - next: client.OutboundInterceptor, - payload_converter: converter.PayloadConverter, - ) -> None: - super().__init__(next) - self._payload_converter = payload_converter - - async def start_workflow( - self, input: client.StartWorkflowInput - ) -> client.WorkflowHandle[Any, Any]: - with trace(name=f"start_workflow:{input.workflow}"): - set_header_from_context(input, self._payload_converter) - return await super().start_workflow(input) - - -class _LangChainContextPropagationActivityInboundInterceptor( - worker.ActivityInboundInterceptor -): - async def execute_activity(self, input: worker.ExecuteActivityInput) -> Any: - if isinstance(input.fn, str): - name = input.fn - elif callable(input.fn): - defn = activity._Definition.from_callable(input.fn) - name = ( - defn.name if defn is not None and defn.name is not None else "unknown" - ) - else: - name = "unknown" - - with context_from_header(input, activity.payload_converter()): - with trace(name=f"execute_activity:{name}"): - return await self.next.execute_activity(input) - - -class _LangChainContextPropagationWorkflowInboundInterceptor( - worker.WorkflowInboundInterceptor -): - def init(self, outbound: worker.WorkflowOutboundInterceptor) -> None: - self.next.init( - _LangChainContextPropagationWorkflowOutboundInterceptor(outbound) - ) - - async def execute_workflow(self, input: worker.ExecuteWorkflowInput) -> Any: - if isinstance(input.run_fn, str): - name = input.run_fn - elif callable(input.run_fn): - defn = workflow._Definition.from_run_fn(input.run_fn) - name = ( - defn.name if defn is not None and defn.name is not None else "unknown" - ) - else: - name = "unknown" - - with context_from_header(input, workflow.payload_converter()): - # This is a sandbox friendly way to write - # with trace(...): - # return await self.next.execute_workflow(input) - with workflow.unsafe.sandbox_unrestricted(): - t = trace( - name=f"execute_workflow:{name}", run_id=workflow.info().run_id - ) - with workflow.unsafe.imports_passed_through(): - t.__enter__() - try: - return await self.next.execute_workflow(input) - finally: - with workflow.unsafe.sandbox_unrestricted(): - # Cannot use __aexit__ because it's internally uses - # loop.run_in_executor which is not available in the sandbox - t.__exit__() - - -class _LangChainContextPropagationWorkflowOutboundInterceptor( - worker.WorkflowOutboundInterceptor -): - def start_activity( - self, input: worker.StartActivityInput - ) -> workflow.ActivityHandle: - with workflow.unsafe.sandbox_unrestricted(): - t = trace(name=f"start_activity:{input.activity}", run_id=workflow.uuid4()) - with workflow.unsafe.imports_passed_through(): - t.__enter__() - try: - set_header_from_context(input, workflow.payload_converter()) - return self.next.start_activity(input) - finally: - with workflow.unsafe.sandbox_unrestricted(): - t.__exit__() - - async def start_child_workflow( - self, input: worker.StartChildWorkflowInput - ) -> workflow.ChildWorkflowHandle: - with workflow.unsafe.sandbox_unrestricted(): - t = trace( - name=f"start_child_workflow:{input.workflow}", run_id=workflow.uuid4() - ) - with workflow.unsafe.imports_passed_through(): - t.__enter__() - - try: - set_header_from_context(input, workflow.payload_converter()) - return await self.next.start_child_workflow(input) - finally: - with workflow.unsafe.sandbox_unrestricted(): - t.__exit__() diff --git a/langchain/starter.py b/langchain/starter.py deleted file mode 100644 index 6d9e00c2..00000000 --- a/langchain/starter.py +++ /dev/null @@ -1,47 +0,0 @@ -from contextlib import asynccontextmanager -from typing import List -from uuid import uuid4 - -import uvicorn -from activities import TranslateParams -from fastapi import FastAPI, HTTPException -from langchain_interceptor import LangChainContextPropagationInterceptor -from temporalio.client import Client -from temporalio.envconfig import ClientConfig -from workflow import LangChainWorkflow, TranslateWorkflowParams - - -@asynccontextmanager -async def lifespan(app: FastAPI): - config = ClientConfig.load_client_connect_config() - config.setdefault("target_host", "localhost:7233") - - client = await Client.connect( - **config, - interceptors=[LangChainContextPropagationInterceptor()], - ) - yield - - -app = FastAPI(lifespan=lifespan) - - -@app.post("/translate") -async def translate(phrase: str, language1: str, language2: str, language3: str): - languages = [language1, language2, language3] - client = app.state.temporal_client - try: - result = await client.execute_workflow( - LangChainWorkflow.run, - TranslateWorkflowParams(phrase, languages), - id=f"langchain-translation-{uuid4()}", - task_queue="langchain-task-queue", - ) - except Exception as e: - raise HTTPException(status_code=500, detail=str(e)) - - return {"translations": result} - - -if __name__ == "__main__": - uvicorn.run(app, host="localhost", port=8000) diff --git a/langchain/worker.py b/langchain/worker.py deleted file mode 100644 index b7fb7741..00000000 --- a/langchain/worker.py +++ /dev/null @@ -1,44 +0,0 @@ -import asyncio - -from activities import translate_phrase -from langchain_interceptor import LangChainContextPropagationInterceptor -from temporalio.client import Client -from temporalio.envconfig import ClientConfig -from temporalio.worker import Worker -from workflow import LangChainChildWorkflow, LangChainWorkflow - -interrupt_event = asyncio.Event() - - -async def main(): - config = ClientConfig.load_client_connect_config() - config.setdefault("target_host", "localhost:7233") - client = await Client.connect(**config) - - worker = Worker( - client, - task_queue="langchain-task-queue", - workflows=[LangChainWorkflow, LangChainChildWorkflow], - activities=[translate_phrase], - interceptors=[LangChainContextPropagationInterceptor()], - ) - - print("\nWorker started, ctrl+c to exit\n") - await worker.run() - try: - # Wait indefinitely until the interrupt event is set - await interrupt_event.wait() - finally: - # The worker will be shutdown gracefully due to the async context manager - print("\nShutting down the worker\n") - - -if __name__ == "__main__": - loop = asyncio.new_event_loop() - asyncio.set_event_loop(loop) - try: - loop.run_until_complete(main()) - except KeyboardInterrupt: - print("\nInterrupt received, shutting down...\n") - interrupt_event.set() - loop.run_until_complete(loop.shutdown_asyncgens()) diff --git a/langchain/workflow.py b/langchain/workflow.py deleted file mode 100644 index 31861c07..00000000 --- a/langchain/workflow.py +++ /dev/null @@ -1,53 +0,0 @@ -import asyncio -from dataclasses import dataclass -from datetime import timedelta -from typing import List - -from temporalio import workflow - -with workflow.unsafe.imports_passed_through(): - from activities import TranslateParams, translate_phrase - - -@workflow.defn -class LangChainChildWorkflow: - @workflow.run - async def run(self, params: TranslateParams) -> str: - return await workflow.execute_activity( - translate_phrase, - params, - schedule_to_close_timeout=timedelta(seconds=30), - ) - - -@dataclass -class TranslateWorkflowParams: - phrase: str - languages: List[str] - - -@workflow.defn -class LangChainWorkflow: - @workflow.run - async def run(self, params: TranslateWorkflowParams) -> dict: - result1, result2, result3 = await asyncio.gather( - workflow.execute_activity( - translate_phrase, - TranslateParams(params.phrase, params.languages[0]), - schedule_to_close_timeout=timedelta(seconds=30), - ), - workflow.execute_activity( - translate_phrase, - TranslateParams(params.phrase, params.languages[1]), - schedule_to_close_timeout=timedelta(seconds=30), - ), - workflow.execute_child_workflow( - LangChainChildWorkflow.run, - TranslateParams(params.phrase, params.languages[2]), - ), - ) - return { - params.languages[0]: result1, - params.languages[1]: result2, - params.languages[2]: result3, - } diff --git a/langsmith_tracing/README.md b/langsmith_tracing/README.md new file mode 100644 index 00000000..127a8059 --- /dev/null +++ b/langsmith_tracing/README.md @@ -0,0 +1,49 @@ +# LangSmith Tracing + +This sample demonstrates [LangSmith](https://smith.langchain.com/) tracing integration with Temporal workflows using the [`LangSmithPlugin`](https://python.temporal.io/temporalio.contrib.langsmith.html). + +Two examples are included: + +- **[basic/](basic/)** — A one-shot LLM workflow that sends a prompt to OpenAI and returns the response. +- **[chatbot/](chatbot/)** — A long-running conversational workflow with tool calls (save/read notes) and update handlers. + +## Prerequisites + +Install dependencies: + +```bash +uv sync --group langsmith-tracing +``` + +Set environment variables: + +```bash +export OPENAI_API_KEY="sk-..." +export LANGSMITH_API_KEY="lsv2_..." +export LANGCHAIN_TRACING_V2=true +``` + +A local Temporal server must be running (`temporal server start-dev`). + +## Three Layers of Tracing + +This sample shows three complementary ways LangSmith captures trace data: + +1. **Automatic (`wrap_openai`)** — Wrapping the OpenAI client with `wrap_openai()` automatically creates a child span for every LLM call, capturing model parameters, token usage, and latency. No extra code needed. + +2. **Explicit (`@traceable`)** — Decorating functions with `@traceable` creates named spans for your business logic. You control the name, tags, metadata, and `run_type` (chain, llm, tool, retriever). This is how you structure traces to tell a story about what your application is doing. + +3. **Temporal (`add_temporal_runs=True`)** — The `LangSmithPlugin` can optionally create LangSmith runs for each Temporal workflow execution and activity execution, giving visibility into the orchestration layer alongside your LLM calls. + +## `add_temporal_runs` + +By default, `LangSmithPlugin(add_temporal_runs=False)` only propagates LangSmith context so that `@traceable` and `wrap_openai` calls nest correctly. + +Set `add_temporal_runs=True` to also create LangSmith runs for Temporal operations (workflow executions, activity executions, signals, etc.), giving full visibility into the orchestration layer. Both examples support a `--add-temporal-runs` CLI flag to toggle this. + +## Further Reading + +- [LangSmith documentation](https://docs.smith.langchain.com/) +- [Temporal Python SDK LangSmith plugin](https://python.temporal.io/temporalio.contrib.langsmith.html) +- [LangSmith `@traceable` guide](https://docs.smith.langchain.com/observability/how-to/annotate-code) +- [LangSmith `wrap_openai` guide](https://docs.smith.langchain.com/observability/how-to/trace-with-openai) diff --git a/langsmith_tracing/__init__.py b/langsmith_tracing/__init__.py new file mode 100644 index 00000000..e69de29b diff --git a/langsmith_tracing/basic/README.md b/langsmith_tracing/basic/README.md new file mode 100644 index 00000000..839312e8 --- /dev/null +++ b/langsmith_tracing/basic/README.md @@ -0,0 +1,50 @@ +# Basic LLM Workflow + +A one-shot workflow that sends a prompt to OpenAI and returns the response. A very simple example of LangSmith tracing with Temporal. + +See the [parent README](../README.md) for prerequisites. + +## Running + +```bash +# Terminal 1 — start the worker +uv run --group langsmith-tracing python -m langsmith_tracing.basic.worker + +# Terminal 2 — run the workflow +uv run --group langsmith-tracing python -m langsmith_tracing.basic.starter +``` + +## Trace Structure + +### `add_temporal_runs=False` (default) + +Only `@traceable` and `wrap_openai` spans appear. The client-side `@traceable` is the root, and workflow/activity traces nest under it via context propagation. + +``` +Basic LLM Request (@traceable, client-side) +└── Ask: What is Temporal? (@traceable, workflow) + └── Call OpenAI (@traceable, activity) + └── ChatOpenAI (automatic via wrap_openai) +``` + +### `add_temporal_runs=True` + +Pass `--add-temporal-runs` to both the worker and starter: + +```bash +uv run --group langsmith-tracing python -m langsmith_tracing.basic.worker --add-temporal-runs +uv run --group langsmith-tracing python -m langsmith_tracing.basic.starter --add-temporal-runs +``` + +Temporal operation spans are added. `StartWorkflow`/`RunWorkflow` and `StartActivity`/`RunActivity` appear as sibling pairs: + +``` +Basic LLM Request (@traceable, client-side) +├── StartWorkflow:BasicLLMWorkflow (automatic, Temporal plugin) +└── RunWorkflow:BasicLLMWorkflow (automatic, Temporal plugin) + └── Ask: What is Temporal? (@traceable, workflow) + ├── StartActivity:call_openai (automatic, Temporal plugin) + └── RunActivity:call_openai (automatic, Temporal plugin) + └── Call OpenAI (@traceable, activity) + └── ChatOpenAI (automatic via wrap_openai) +``` diff --git a/langsmith_tracing/basic/__init__.py b/langsmith_tracing/basic/__init__.py new file mode 100644 index 00000000..e69de29b diff --git a/langsmith_tracing/basic/activities.py b/langsmith_tracing/basic/activities.py new file mode 100644 index 00000000..e04e1711 --- /dev/null +++ b/langsmith_tracing/basic/activities.py @@ -0,0 +1,33 @@ +"""Basic LLM activity with LangSmith tracing.""" + +from dataclasses import dataclass + +from langsmith import traceable +from langsmith.wrappers import wrap_openai +from openai import AsyncOpenAI +from temporalio import activity + + +@dataclass +class OpenAIRequest: + model: str + input: str + instructions: str = "You are a helpful assistant." + + +@traceable(name="Call OpenAI", run_type="llm") +@activity.defn +async def call_openai(request: OpenAIRequest) -> str: + """Call OpenAI Responses API. Retries handled by Temporal, not the OpenAI client.""" + # wrap_openai patches the client so each API call (e.g. responses.create) + # creates its own child span with model parameters and token usage. + # max_retries=0 disables OpenAI's built-in retries — Temporal's activity + # retry policy handles retries instead, with full visibility in the UI. + client = wrap_openai(AsyncOpenAI(max_retries=0)) + response = await client.responses.create( + model=request.model, + instructions=request.instructions, + input=request.input, + timeout=30, + ) + return response.output_text diff --git a/langsmith_tracing/basic/starter.py b/langsmith_tracing/basic/starter.py new file mode 100644 index 00000000..901ae9b5 --- /dev/null +++ b/langsmith_tracing/basic/starter.py @@ -0,0 +1,54 @@ +"""Starter for the basic LangSmith sample.""" + +import asyncio +import sys + +from langsmith import traceable +from temporalio.client import Client +from temporalio.contrib.langsmith import LangSmithPlugin +from temporalio.envconfig import ClientConfig + +from langsmith_tracing.basic.workflows import BasicLLMWorkflow + +PROJECT_NAME = "langsmith-basic" + + +async def main(): + add_temporal_runs = "--add-temporal-runs" in sys.argv + + config = ClientConfig.load_client_connect_config() + config.setdefault("target_host", "localhost:7233") + + plugin = LangSmithPlugin( + project_name=PROJECT_NAME, + add_temporal_runs=add_temporal_runs, + ) + + client = await Client.connect( + **config, + plugins=[plugin], + ) + + @traceable( + name="Basic LLM Request", + run_type="chain", + # CRITICAL: Client-side @traceable runs outside the LangSmithPlugin's scope. + # Make sure client-side traces use the same project_name as what is given to + # # the plugin. + project_name=PROJECT_NAME, + tags=["client-side"], + ) + async def run_workflow(prompt: str) -> str: + return await client.execute_workflow( + BasicLLMWorkflow.run, + prompt, + id="langsmith-basic-workflow-id", + task_queue="langsmith-basic-task-queue", + ) + + result = await run_workflow("What is Temporal?") + print(f"Workflow result: {result}") + + +if __name__ == "__main__": + asyncio.run(main()) diff --git a/langsmith_tracing/basic/worker.py b/langsmith_tracing/basic/worker.py new file mode 100644 index 00000000..140c87da --- /dev/null +++ b/langsmith_tracing/basic/worker.py @@ -0,0 +1,49 @@ +"""Worker for the basic LangSmith sample.""" + +import asyncio +import logging +import sys + +from temporalio.client import Client +from temporalio.contrib.langsmith import LangSmithPlugin +from temporalio.envconfig import ClientConfig +from temporalio.worker import Worker + +from langsmith_tracing.basic.activities import call_openai +from langsmith_tracing.basic.workflows import BasicLLMWorkflow + + +async def main(): + logging.basicConfig(level=logging.INFO) + + # add_temporal_runs=True creates LangSmith runs for each Temporal + # workflow/activity execution. False (default) only propagates context. + add_temporal_runs = "--add-temporal-runs" in sys.argv + + config = ClientConfig.load_client_connect_config() + config.setdefault("target_host", "localhost:7233") + + plugin = LangSmithPlugin( + project_name="langsmith-basic", + add_temporal_runs=add_temporal_runs, + ) + + client = await Client.connect( + **config, + plugins=[plugin], + ) + + worker = Worker( + client, + task_queue="langsmith-basic-task-queue", + workflows=[BasicLLMWorkflow], + activities=[call_openai], + ) + + label = "with" if add_temporal_runs else "without" + print(f"Worker started ({label} Temporal runs in traces), ctrl+c to exit") + await worker.run() + + +if __name__ == "__main__": + asyncio.run(main()) diff --git a/langsmith_tracing/basic/workflows.py b/langsmith_tracing/basic/workflows.py new file mode 100644 index 00000000..c6cc14b2 --- /dev/null +++ b/langsmith_tracing/basic/workflows.py @@ -0,0 +1,33 @@ +"""Basic one-shot LLM workflow with LangSmith tracing.""" + +from datetime import timedelta + +from temporalio import workflow + +with workflow.unsafe.imports_passed_through(): + from langsmith import traceable + + from langsmith_tracing.basic.activities import OpenAIRequest, call_openai + + +@workflow.defn +class BasicLLMWorkflow: + # Do not decorate @workflow.run with @traceable — it would violate + # replay safety and produce duplicate or orphaned traces. Instead, + # wrap an inner function. + @workflow.run + async def run(self, prompt: str) -> str: + @traceable( + name=f"Ask: {prompt[:60]}", + run_type="chain", + metadata={"workflow_id": workflow.info().workflow_id}, + tags=["basic-llm"], + ) + async def _run() -> str: + return await workflow.execute_activity( + call_openai, + OpenAIRequest(model="gpt-4o-mini", input=prompt), + start_to_close_timeout=timedelta(seconds=60), + ) + + return await _run() diff --git a/langsmith_tracing/chatbot/README.md b/langsmith_tracing/chatbot/README.md new file mode 100644 index 00000000..b9784989 --- /dev/null +++ b/langsmith_tracing/chatbot/README.md @@ -0,0 +1,81 @@ +# Chatbot with Tool Calls + +A long-running conversational workflow with tool calls and update handlers. Demonstrates how LangSmith traces an agentic loop where the model calls tools across multiple turns. + +See the [parent README](../README.md) for prerequisites. + +## Running + +```bash +# Terminal 1 — start the worker +uv run --group langsmith-tracing python -m langsmith_tracing.chatbot.worker + +# Terminal 2 — interactive CLI +uv run --group langsmith-tracing python -m langsmith_tracing.chatbot.starter +``` + +Commands in the CLI: +- Type a message and press Enter to chat +- `exit` — end the session + +## Tools + +The model has two tools, both implemented as `@traceable` methods on the workflow class: + +- **`save_note(name, content)`** — Stores a note in the workflow's in-memory dict. The note is durable because workflow state survives crashes and restarts via Temporal's event history. +- **`read_note(name)`** — Reads a note from the workflow's in-memory dict. + +## Architecture + +The main `@workflow.run` method runs a loop that processes user messages (calls `_query_openai`, which handles the tool-call loop). The `message_from_user` update handler coordinates: it hands the message to the main loop via a shared `_pending_message` field, then waits for the response. + +This means: +- Activity calls and the tool loop happen inside the main workflow run +- The update handler's trace just shows the input/output of the coordination step + +## Trace Structure + +### `add_temporal_runs=False` (default) + +Only `@traceable` and `wrap_openai` spans appear. The client-side `@traceable` wraps `start_workflow` and each `execute_update`, so both workflow and update traces nest under it via context propagation. + +``` +Chatbot Session a1b2c3d4 (@traceable, client-side) +├── Session Apr 17 10:30 (@traceable, workflow main loop) +│ ├── Request: hello (@traceable, per-message in main loop) +│ │ └── Call OpenAI (@traceable, activity) +│ │ └── ChatOpenAI (automatic via wrap_openai) +│ └── Request: save that as note 15 (@traceable, per-message in main loop) +│ ├── Call OpenAI → function_call: save_note +│ ├── Save Note (@traceable, workflow method) +│ └── Call OpenAI → text response +├── Update: hello (@traceable, update handler) +└── Update: save that as note 15 (@traceable, update handler) +``` + +### `add_temporal_runs=True` + +With `--add-temporal-runs`, Temporal operation spans are added. `StartWorkflow`/`RunWorkflow` and `StartActivity`/`RunActivity` appear as sibling pairs. + +``` +Chatbot Session a1b2c3d4 (@traceable, client-side) +├── StartWorkflow:ChatbotWorkflow (automatic, Temporal plugin) +├── RunWorkflow:ChatbotWorkflow (automatic, Temporal plugin) +│ └── Session Apr 17 10:30 (@traceable, workflow main loop) +│ └── Request: save that as note 15 (@traceable, per-message) +│ ├── StartActivity:call_openai (automatic, Temporal plugin) +│ ├── RunActivity:call_openai (automatic, Temporal plugin) +│ │ └── Call OpenAI (@traceable, activity) +│ │ └── ChatOpenAI (automatic via wrap_openai) +│ ├── Save Note (@traceable, workflow method) +│ ├── StartActivity:call_openai (automatic, Temporal plugin) +│ └── RunActivity:call_openai (automatic, Temporal plugin) +│ └── Call OpenAI (@traceable, activity) +│ └── ChatOpenAI (automatic via wrap_openai) +├── StartWorkflowUpdate:message_from_user (automatic, Temporal plugin) +│ └── HandleUpdate:message_from_user (automatic, Temporal plugin) +│ └── Update: save that as note 15 (@traceable, update handler) +└── ... +``` + +Note that the `Request:` chain (with activity calls) lives under `RunWorkflow` (the main loop), while the `Update:` span lives under `HandleUpdate` (the update handler). They're connected by the shared workflow state but appear as separate subtrees. diff --git a/langsmith_tracing/chatbot/__init__.py b/langsmith_tracing/chatbot/__init__.py new file mode 100644 index 00000000..e69de29b diff --git a/langsmith_tracing/chatbot/activities.py b/langsmith_tracing/chatbot/activities.py new file mode 100644 index 00000000..1994f792 --- /dev/null +++ b/langsmith_tracing/chatbot/activities.py @@ -0,0 +1,45 @@ +"""Chatbot activities with LangSmith tracing.""" + +from dataclasses import dataclass +from typing import Any + +from langsmith import traceable +from langsmith.wrappers import wrap_openai +from openai import AsyncOpenAI +from openai.types.responses import Response +from temporalio import activity + + +@dataclass +class OpenAIRequest: + model: str + # str for the initial user prompt, list for tool call results fed back + input: str | list[dict[str, Any]] + instructions: str = ( + "You are a helpful assistant with note-taking abilities. " + "Use save_note to remember things and read_note to recall them." + ) + tools: list[dict[str, Any]] | None = None + previous_response_id: str | None = None + + +@traceable(name="Call OpenAI", run_type="llm") +@activity.defn +async def call_openai(request: OpenAIRequest) -> Response: + """Call OpenAI Responses API. Retries handled by Temporal, not the OpenAI client.""" + # wrap_openai patches the client so each API call (e.g. responses.create) + # creates its own child span with model parameters and token usage. + # max_retries=0 disables OpenAI's built-in retries — Temporal's activity + # retry policy handles retries instead, with full visibility in the UI. + client = wrap_openai(AsyncOpenAI(max_retries=0)) + response_args: dict[str, Any] = { + "model": request.model, + "instructions": request.instructions, + "input": request.input, + "timeout": 30, + } + if request.tools: + response_args["tools"] = request.tools + if request.previous_response_id: + response_args["previous_response_id"] = request.previous_response_id + return await client.responses.create(**response_args) diff --git a/langsmith_tracing/chatbot/starter.py b/langsmith_tracing/chatbot/starter.py new file mode 100644 index 00000000..4d67e794 --- /dev/null +++ b/langsmith_tracing/chatbot/starter.py @@ -0,0 +1,76 @@ +"""Interactive CLI starter for the chatbot LangSmith sample.""" + +import asyncio +import readline # noqa: F401 — enables input() line editing +import sys +import uuid + +from langsmith import traceable +from temporalio.client import Client +from temporalio.contrib.langsmith import LangSmithPlugin +from temporalio.contrib.pydantic import pydantic_data_converter +from temporalio.envconfig import ClientConfig + +from langsmith_tracing.chatbot.workflows import ChatbotWorkflow + +PROJECT_NAME = "langsmith-chatbot" + + +async def main(): + add_temporal_runs = "--add-temporal-runs" in sys.argv + + config = ClientConfig.load_client_connect_config() + config.setdefault("target_host", "localhost:7233") + + plugin = LangSmithPlugin( + project_name=PROJECT_NAME, + add_temporal_runs=add_temporal_runs, + ) + + client = await Client.connect( + **config, + data_converter=pydantic_data_converter, + plugins=[plugin], + ) + + wf_id = f"langsmith-chatbot-{uuid.uuid4().hex[:8]}" + + @traceable( + name=f"Chatbot Session {wf_id[-8:]}", + run_type="chain", + # CRITICAL: Client-side @traceable runs outside the LangSmithPlugin's scope. + # Make sure client-side traces use the same project_name as what is given to + # the plugin. + project_name=PROJECT_NAME, + tags=["client-side", "chatbot"], + ) + async def run_session(): + wf_handle = await client.start_workflow( + ChatbotWorkflow.run, + id=wf_id, + task_queue="langsmith-chatbot-task-queue", + ) + print(f"Started workflow: {wf_handle.id}") + print('Type a message or "exit" to quit.\n') + + while True: + user_input = input("> ").strip() + if not user_input: + continue + + if user_input.lower() == "exit": + await wf_handle.signal(ChatbotWorkflow.exit) + result = await wf_handle.result() + print(f"\nWorkflow finished: {result}") + return + + response = await wf_handle.execute_update( + ChatbotWorkflow.message_from_user, user_input + ) + print(f"Bot: {response}\n") + + await run_session() + + +if __name__ == "__main__": + asyncio.run(main()) diff --git a/langsmith_tracing/chatbot/worker.py b/langsmith_tracing/chatbot/worker.py new file mode 100644 index 00000000..0f43e7c9 --- /dev/null +++ b/langsmith_tracing/chatbot/worker.py @@ -0,0 +1,49 @@ +"""Worker for the chatbot LangSmith sample.""" + +import asyncio +import logging +import sys + +from temporalio.client import Client +from temporalio.contrib.langsmith import LangSmithPlugin +from temporalio.contrib.pydantic import pydantic_data_converter +from temporalio.envconfig import ClientConfig +from temporalio.worker import Worker + +from langsmith_tracing.chatbot.activities import call_openai +from langsmith_tracing.chatbot.workflows import ChatbotWorkflow + + +async def main(): + logging.basicConfig(level=logging.INFO) + + add_temporal_runs = "--add-temporal-runs" in sys.argv + + config = ClientConfig.load_client_connect_config() + config.setdefault("target_host", "localhost:7233") + + client = await Client.connect( + **config, + data_converter=pydantic_data_converter, + plugins=[ + LangSmithPlugin( + project_name="langsmith-chatbot", + add_temporal_runs=add_temporal_runs, + ) + ], + ) + + worker = Worker( + client, + task_queue="langsmith-chatbot-task-queue", + workflows=[ChatbotWorkflow], + activities=[call_openai], + ) + + label = "with" if add_temporal_runs else "without" + print(f"Worker started ({label} Temporal runs in traces), ctrl+c to exit") + await worker.run() + + +if __name__ == "__main__": + asyncio.run(main()) diff --git a/langsmith_tracing/chatbot/workflows.py b/langsmith_tracing/chatbot/workflows.py new file mode 100644 index 00000000..4b25df50 --- /dev/null +++ b/langsmith_tracing/chatbot/workflows.py @@ -0,0 +1,178 @@ +"""Conversational chatbot workflow with tool loop and LangSmith tracing.""" + +import json +from datetime import timedelta + +from temporalio import workflow +from temporalio.common import RetryPolicy + +with workflow.unsafe.imports_passed_through(): + from langsmith import traceable + + from langsmith_tracing.chatbot.activities import OpenAIRequest, call_openai + +TOOLS = [ + { + "type": "function", + "name": "save_note", + "description": "Save or update a note.", + "parameters": { + "type": "object", + "properties": { + "name": {"type": "string", "description": "Name/key for the note."}, + "content": { + "type": "string", + "description": "Content of the note.", + }, + }, + "required": ["name", "content"], + }, + }, + { + "type": "function", + "name": "read_note", + "description": "Read a previously saved note.", + "parameters": { + "type": "object", + "properties": { + "name": { + "type": "string", + "description": "Name/key of the note to read.", + }, + }, + "required": ["name"], + }, + }, +] + + +@workflow.defn +class ChatbotWorkflow: + def __init__(self): + self._pending_message: str | None = None + self._last_response: str = "" + self._previous_response_id: str | None = None + self._notes: dict[str, str] = {} + self._done = False + + @workflow.signal + async def exit(self) -> None: + self._done = True + + @workflow.query + def notes(self) -> dict[str, str]: + return dict(self._notes) + + @workflow.update + async def message_from_user(self, message: str) -> str: + """Hand the message to the main loop and wait for its response.""" + + # Inner @traceable captures the message as input and response as output. + @traceable(name=f"Update: {message[:60]}", run_type="chain") + async def _traced(msg: str) -> str: + # Wait until any previous message has finished processing + await workflow.wait_condition(lambda: self._pending_message is None) + self._pending_message = msg + # Main loop sets _last_response, then clears _pending_message to signal done + await workflow.wait_condition(lambda: self._pending_message is None) + return self._last_response + + return await _traced(message) + + # Do not decorate @workflow.run with @traceable — it would violate + # replay safety and produce duplicate or orphaned traces. Instead, + # wrap an inner function, eg. self._run_inner() in this case. + @workflow.run + async def run(self) -> str: + # Alternative to @traceable decorator: call traceable() as a function + # for dynamic trace names that depend on runtime values. + now = workflow.now().strftime("%b %d %H:%M") + return await traceable( + name=f"Session {now}", + run_type="chain", + metadata={"workflow_id": workflow.info().workflow_id}, + tags=["chatbot-session"], + )(self._run_inner)() + + async def _run_inner(self) -> str: + while not self._done: + await workflow.wait_condition( + lambda: self._pending_message is not None or self._done + ) + if self._done: + break + assert self._pending_message is not None + message = self._pending_message + self._last_response = await self._query_openai(message) + # Clear pending_message AFTER setting the response so the update + # handler reads the correct response when its wait_condition fires. + self._pending_message = None + + return "Session ended." + + # Unlike @workflow.run, other workflow methods can be decorated with + # @traceable directly — they run inside the plugin-managed context + # where trace I/O is handled safely during replay. + @traceable(name="Save Note", run_type="tool") + def _save_note(self, name: str, content: str) -> str: + self._notes[name] = content + return f"Saved note '{name}'." + + @traceable(name="Read Note", run_type="tool") + def _read_note(self, name: str) -> str: + return self._notes.get(name, "Note not found.") + + async def _query_openai(self, message: str) -> str: + @traceable( + name=f"Request: {message[:60]}", + run_type="chain", + tags=["user-message"], + ) + async def _traced(): + input_for_next: str | list = message + while True: + response = await workflow.execute_activity( + call_openai, + OpenAIRequest( + model="gpt-4o-mini", + input=input_for_next, + tools=TOOLS, + previous_response_id=self._previous_response_id, + ), + start_to_close_timeout=timedelta(seconds=60), + retry_policy=RetryPolicy( + initial_interval=timedelta(seconds=2), maximum_attempts=3 + ), + ) + self._previous_response_id = response.id + + tool_results = [] + for item in response.output: + if item.type != "function_call": + continue + args = json.loads(item.arguments) + if item.name == "save_note": + result = self._save_note(args["name"], args["content"]) + tool_results.append( + { + "type": "function_call_output", + "call_id": item.call_id, + "output": result, + } + ) + elif item.name == "read_note": + result = self._read_note(args["name"]) + tool_results.append( + { + "type": "function_call_output", + "call_id": item.call_id, + "output": result, + } + ) + + if not tool_results: + return response.output_text or "Done." + + input_for_next = tool_results + + return await _traced() diff --git a/pyproject.toml b/pyproject.toml index f65ff1c2..0927eea3 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -30,14 +30,10 @@ bedrock = ["boto3>=1.34.92,<2"] dsl = ["pyyaml>=6.0.1,<7", "types-pyyaml>=6.0.12,<7", "dacite>=1.8.1,<2"] encryption = ["cryptography>=38.0.1,<39", "aiohttp>=3.8.1,<4"] gevent = ["gevent>=25.4.2 ; python_version >= '3.8'"] -langchain = [ - "langchain>=1.2.15,<2 ; python_version >= '3.8.1' and python_version < '4.0'", - "langchain-openai>=1.1.13,<2 ; python_version >= '3.8.1' and python_version < '4.0'", - "langsmith>=0.3.45,<0.4 ; python_version >= '3.8.1' and python_version < '4.0'", - "openai>=2.0.0,<3", - "fastapi>=0.115.12", - "tqdm>=4.62.0,<5", - "uvicorn[standard]>=0.31.0,<0.32.0", +langsmith-tracing = [ + "openai>=1.4.0", + "langsmith>=0.7.0", + "temporalio[pydantic,langsmith]>=1.26.0", ] nexus = ["nexus-rpc>=1.1.0,<2"] open-telemetry = [ @@ -79,7 +75,7 @@ packages = [ "encryption", "gevent_async", "hello", - "langchain", + "langsmith_tracing", "message_passing", "nexus", "open_telemetry", diff --git a/tests/langsmith_tracing/__init__.py b/tests/langsmith_tracing/__init__.py new file mode 100644 index 00000000..e69de29b diff --git a/tests/langsmith_tracing/helpers.py b/tests/langsmith_tracing/helpers.py new file mode 100644 index 00000000..6742a60f --- /dev/null +++ b/tests/langsmith_tracing/helpers.py @@ -0,0 +1,33 @@ +"""Shared test helpers for LangSmith tracing tests.""" + +from openai.types.responses import Response +from openai.types.responses.response_output_message import ResponseOutputMessage +from openai.types.responses.response_output_text import ResponseOutputText + + +def make_text_response(text: str) -> Response: + """Build a minimal OpenAI Response with a text output.""" + return Response.model_construct( + id="resp_mock", + created_at=0.0, + model="gpt-4o-mini", + object="response", + output=[ + ResponseOutputMessage.model_construct( + id="msg_mock", + type="message", + role="assistant", + status="completed", + content=[ + ResponseOutputText.model_construct( + type="output_text", + text=text, + annotations=[], + ) + ], + ) + ], + parallel_tool_calls=False, + tool_choice="auto", + tools=[], + ) diff --git a/tests/langsmith_tracing/test_basic.py b/tests/langsmith_tracing/test_basic.py new file mode 100644 index 00000000..b5be2f35 --- /dev/null +++ b/tests/langsmith_tracing/test_basic.py @@ -0,0 +1,34 @@ +import uuid + +from temporalio import activity +from temporalio.client import Client +from temporalio.contrib.langsmith import LangSmithPlugin +from temporalio.testing import WorkflowEnvironment +from temporalio.worker import Worker + +from langsmith_tracing.basic.activities import OpenAIRequest +from langsmith_tracing.basic.workflows import BasicLLMWorkflow + + +async def test_basic_workflow(client: Client, env: WorkflowEnvironment): + expected_text = "Temporal is a durable execution platform." + + @activity.defn(name="call_openai") + async def mock_call_openai(request: OpenAIRequest) -> str: + return expected_text + + async with Worker( + client, + task_queue="test-langsmith-basic", + workflows=[BasicLLMWorkflow], + activities=[mock_call_openai], + plugins=[LangSmithPlugin()], + ): + result = await client.execute_workflow( + BasicLLMWorkflow.run, + "What is Temporal?", + id=f"test-basic-{uuid.uuid4().hex[:8]}", + task_queue="test-langsmith-basic", + ) + + assert result == expected_text diff --git a/tests/langsmith_tracing/test_chatbot.py b/tests/langsmith_tracing/test_chatbot.py new file mode 100644 index 00000000..f7845217 --- /dev/null +++ b/tests/langsmith_tracing/test_chatbot.py @@ -0,0 +1,132 @@ +import json +import uuid + +from openai.types.responses import Response +from openai.types.responses.response_function_tool_call import ( + ResponseFunctionToolCall, +) +from temporalio import activity +from temporalio.client import Client +from temporalio.contrib.langsmith import LangSmithPlugin +from temporalio.testing import WorkflowEnvironment +from temporalio.worker import Worker + +from langsmith_tracing.chatbot.activities import OpenAIRequest +from langsmith_tracing.chatbot.workflows import ChatbotWorkflow +from tests.langsmith_tracing.helpers import make_text_response + + +def _make_function_call_response( + name: str, arguments: dict, call_id: str = "call_123" +) -> Response: + return Response.model_construct( + id="resp_tool", + created_at=0.0, + model="gpt-4o-mini", + object="response", + output=[ + ResponseFunctionToolCall.model_construct( + id="fc_mock", + type="function_call", + name=name, + arguments=json.dumps(arguments), + call_id=call_id, + status="completed", + ) + ], + parallel_tool_calls=False, + tool_choice="auto", + tools=[], + ) + + +async def test_chatbot_save_note(client: Client, env: WorkflowEnvironment): + """Test save_note tool call loop — save_note runs as a workflow method.""" + call_count = 0 + + @activity.defn(name="call_openai") + async def mock_call_openai(request: OpenAIRequest) -> Response: + nonlocal call_count + call_count += 1 + if call_count == 1: + return _make_function_call_response( + name="save_note", + arguments={"name": "greeting", "content": "Hello world"}, + ) + return make_text_response("Note saved successfully!") + + async with Worker( + client, + task_queue="test-langsmith-chatbot", + workflows=[ChatbotWorkflow], + activities=[mock_call_openai], + plugins=[LangSmithPlugin()], + ): + wf_handle = await client.start_workflow( + ChatbotWorkflow.run, + id=f"test-chatbot-{uuid.uuid4().hex[:8]}", + task_queue="test-langsmith-chatbot", + ) + + response = await wf_handle.execute_update( + ChatbotWorkflow.message_from_user, "Save a note" + ) + assert response == "Note saved successfully!" + + notes = await wf_handle.query(ChatbotWorkflow.notes) + assert notes == {"greeting": "Hello world"} + + await wf_handle.signal(ChatbotWorkflow.exit) + result = await wf_handle.result() + assert result == "Session ended." + + +async def test_chatbot_read_note(client: Client, env: WorkflowEnvironment): + """Test read_note tool call loop — read_note runs as a workflow method.""" + call_count = 0 + + @activity.defn(name="call_openai") + async def mock_call_openai(request: OpenAIRequest) -> Response: + nonlocal call_count + call_count += 1 + if call_count == 1: + return _make_function_call_response( + name="save_note", + arguments={"name": "todo", "content": "Buy milk"}, + call_id="call_save", + ) + if call_count == 2: + return make_text_response("Saved your todo!") + if call_count == 3: + return _make_function_call_response( + name="read_note", + arguments={"name": "todo"}, + call_id="call_read", + ) + return make_text_response("Your todo says: Buy milk") + + async with Worker( + client, + task_queue="test-langsmith-chatbot-read", + workflows=[ChatbotWorkflow], + activities=[mock_call_openai], + plugins=[LangSmithPlugin()], + ): + wf_handle = await client.start_workflow( + ChatbotWorkflow.run, + id=f"test-chatbot-read-{uuid.uuid4().hex[:8]}", + task_queue="test-langsmith-chatbot-read", + ) + + response = await wf_handle.execute_update( + ChatbotWorkflow.message_from_user, "Save my todo" + ) + assert response == "Saved your todo!" + + response = await wf_handle.execute_update( + ChatbotWorkflow.message_from_user, "Read my todo" + ) + assert response == "Your todo says: Buy milk" + + await wf_handle.signal(ChatbotWorkflow.exit) + await wf_handle.result() diff --git a/uv.lock b/uv.lock index 4a22edea..3c9990eb 100644 --- a/uv.lock +++ b/uv.lock @@ -3,8 +3,7 @@ revision = 3 requires-python = ">=3.10" resolution-markers = [ "python_full_version >= '3.13'", - "python_full_version >= '3.12.4' and python_full_version < '3.13'", - "python_full_version >= '3.12' and python_full_version < '3.12.4'", + "python_full_version == '3.12.*'", "python_full_version == '3.11.*'", "python_full_version < '3.11'", ] @@ -388,20 +387,6 @@ wheels = [ { url = "https://files.pythonhosted.org/packages/36/f4/c6e662dade71f56cd2f3735141b265c3c79293c109549c1e6933b0651ffc/exceptiongroup-1.3.0-py3-none-any.whl", hash = "sha256:4d111e6e0c13d0644cad6ddaa7ed0261a0b36971f6d23e7ec9b4b9097da78a10", size = 16674, upload-time = 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upload-time = "2025-09-14T22:18:19.088Z" }, ] From ba9e9a1147dce9ce20da4c2b398577057d37ec3b Mon Sep 17 00:00:00 2001 From: xumaple <45406854+xumaple@users.noreply.github.com> Date: Thu, 23 Apr 2026 12:11:57 -0400 Subject: [PATCH 5/5] LangSmith sample: starter cleanup, plugin on Worker, chatbot Response decoupling (#295) * Clean up LangSmith sample per PR #292 review - basic/starter.py: move `@traceable` decorator directly onto `main`, removing the nested `run_workflow` closure (addresses reviewer comment) - basic/worker.py, chatbot/worker.py: move `LangSmithPlugin` from the `Client` to the `Worker`, matching our recommended pattern (plugin on the worker in worker code; on the client in client code) * Return workflow result from basic starter's main @traceable captures the decorated function's return value as the LangSmith trace output, so implicitly returning None left the trace's output field empty. Return `result` (and annotate the return type) so the trace shows the workflow response. * Return minimal ChatResponse from chatbot call_openai activity The activity previously returned `openai.types.responses.Response` directly. The OpenAI API currently returns `"prompt_cache_retention": "in_memory"` (underscore), but openai SDK v2.32.0 declares that field as `Literal["in-memory", "24h"]`. The openai client parses laxly so the activity succeeds, but Temporal's `pydantic_data_converter` uses strict `TypeAdapter(Response).validate_json` on the way into the workflow and rejects the underscore value, failing every workflow task. Define minimal `ChatResponse` and `ToolCall` pydantic models in `activities.py` exposing only the fields the workflow uses (id, output_text, tool_calls). The activity projects the openai Response down to this shape so the sample is no longer coupled to SDK drift in fields it doesn't use. Update the workflow loop to iterate `response.tool_calls` directly and the test mocks/helpers to build `ChatResponse` instead of constructing openai Response objects. --- langsmith_tracing/basic/starter.py | 34 ++++++++++++------------- langsmith_tracing/basic/worker.py | 6 ++--- langsmith_tracing/chatbot/activities.py | 27 +++++++++++++++++--- langsmith_tracing/chatbot/worker.py | 12 ++++----- langsmith_tracing/chatbot/workflows.py | 14 +++++----- tests/langsmith_tracing/helpers.py | 33 +++--------------------- tests/langsmith_tracing/test_chatbot.py | 29 ++++++--------------- 7 files changed, 66 insertions(+), 89 deletions(-) diff --git a/langsmith_tracing/basic/starter.py b/langsmith_tracing/basic/starter.py index 901ae9b5..4a2a103a 100644 --- a/langsmith_tracing/basic/starter.py +++ b/langsmith_tracing/basic/starter.py @@ -13,7 +13,16 @@ PROJECT_NAME = "langsmith-basic" -async def main(): +@traceable( + name="Basic LLM Request", + run_type="chain", + # CRITICAL: Client-side @traceable runs outside the LangSmithPlugin's scope. + # Make sure client-side traces use the same project_name as what is given to + # the plugin. + project_name=PROJECT_NAME, + tags=["client-side"], +) +async def main() -> str: add_temporal_runs = "--add-temporal-runs" in sys.argv config = ClientConfig.load_client_connect_config() @@ -29,25 +38,14 @@ async def main(): plugins=[plugin], ) - @traceable( - name="Basic LLM Request", - run_type="chain", - # CRITICAL: Client-side @traceable runs outside the LangSmithPlugin's scope. - # Make sure client-side traces use the same project_name as what is given to - # # the plugin. - project_name=PROJECT_NAME, - tags=["client-side"], + result = await client.execute_workflow( + BasicLLMWorkflow.run, + "What is Temporal?", + id="langsmith-basic-workflow-id", + task_queue="langsmith-basic-task-queue", ) - async def run_workflow(prompt: str) -> str: - return await client.execute_workflow( - BasicLLMWorkflow.run, - prompt, - id="langsmith-basic-workflow-id", - task_queue="langsmith-basic-task-queue", - ) - - result = await run_workflow("What is Temporal?") print(f"Workflow result: {result}") + return result if __name__ == "__main__": diff --git a/langsmith_tracing/basic/worker.py b/langsmith_tracing/basic/worker.py index 140c87da..941b28c5 100644 --- a/langsmith_tracing/basic/worker.py +++ b/langsmith_tracing/basic/worker.py @@ -28,16 +28,14 @@ async def main(): add_temporal_runs=add_temporal_runs, ) - client = await Client.connect( - **config, - plugins=[plugin], - ) + client = await Client.connect(**config) worker = Worker( client, task_queue="langsmith-basic-task-queue", workflows=[BasicLLMWorkflow], activities=[call_openai], + plugins=[plugin], ) label = "with" if add_temporal_runs else "without" diff --git a/langsmith_tracing/chatbot/activities.py b/langsmith_tracing/chatbot/activities.py index 1994f792..5e979320 100644 --- a/langsmith_tracing/chatbot/activities.py +++ b/langsmith_tracing/chatbot/activities.py @@ -6,10 +6,22 @@ from langsmith import traceable from langsmith.wrappers import wrap_openai from openai import AsyncOpenAI -from openai.types.responses import Response +from pydantic import BaseModel, Field from temporalio import activity +class ToolCall(BaseModel): + call_id: str + name: str + arguments: str + + +class ChatResponse(BaseModel): + id: str + output_text: str = "" + tool_calls: list[ToolCall] = Field(default_factory=list) + + @dataclass class OpenAIRequest: model: str @@ -25,7 +37,7 @@ class OpenAIRequest: @traceable(name="Call OpenAI", run_type="llm") @activity.defn -async def call_openai(request: OpenAIRequest) -> Response: +async def call_openai(request: OpenAIRequest) -> ChatResponse: """Call OpenAI Responses API. Retries handled by Temporal, not the OpenAI client.""" # wrap_openai patches the client so each API call (e.g. responses.create) # creates its own child span with model parameters and token usage. @@ -42,4 +54,13 @@ async def call_openai(request: OpenAIRequest) -> Response: response_args["tools"] = request.tools if request.previous_response_id: response_args["previous_response_id"] = request.previous_response_id - return await client.responses.create(**response_args) + response = await client.responses.create(**response_args) + return ChatResponse( + id=response.id, + output_text=response.output_text or "", + tool_calls=[ + ToolCall(call_id=item.call_id, name=item.name, arguments=item.arguments) + for item in response.output + if item.type == "function_call" + ], + ) diff --git a/langsmith_tracing/chatbot/worker.py b/langsmith_tracing/chatbot/worker.py index 0f43e7c9..b2bd2c98 100644 --- a/langsmith_tracing/chatbot/worker.py +++ b/langsmith_tracing/chatbot/worker.py @@ -22,15 +22,14 @@ async def main(): config = ClientConfig.load_client_connect_config() config.setdefault("target_host", "localhost:7233") + plugin = LangSmithPlugin( + project_name="langsmith-chatbot", + add_temporal_runs=add_temporal_runs, + ) + client = await Client.connect( **config, data_converter=pydantic_data_converter, - plugins=[ - LangSmithPlugin( - project_name="langsmith-chatbot", - add_temporal_runs=add_temporal_runs, - ) - ], ) worker = Worker( @@ -38,6 +37,7 @@ async def main(): task_queue="langsmith-chatbot-task-queue", workflows=[ChatbotWorkflow], activities=[call_openai], + plugins=[plugin], ) label = "with" if add_temporal_runs else "without" diff --git a/langsmith_tracing/chatbot/workflows.py b/langsmith_tracing/chatbot/workflows.py index 4b25df50..47205611 100644 --- a/langsmith_tracing/chatbot/workflows.py +++ b/langsmith_tracing/chatbot/workflows.py @@ -147,25 +147,23 @@ async def _traced(): self._previous_response_id = response.id tool_results = [] - for item in response.output: - if item.type != "function_call": - continue - args = json.loads(item.arguments) - if item.name == "save_note": + for tc in response.tool_calls: + args = json.loads(tc.arguments) + if tc.name == "save_note": result = self._save_note(args["name"], args["content"]) tool_results.append( { "type": "function_call_output", - "call_id": item.call_id, + "call_id": tc.call_id, "output": result, } ) - elif item.name == "read_note": + elif tc.name == "read_note": result = self._read_note(args["name"]) tool_results.append( { "type": "function_call_output", - "call_id": item.call_id, + "call_id": tc.call_id, "output": result, } ) diff --git a/tests/langsmith_tracing/helpers.py b/tests/langsmith_tracing/helpers.py index 6742a60f..afd3d1c4 100644 --- a/tests/langsmith_tracing/helpers.py +++ b/tests/langsmith_tracing/helpers.py @@ -1,33 +1,8 @@ """Shared test helpers for LangSmith tracing tests.""" -from openai.types.responses import Response -from openai.types.responses.response_output_message import ResponseOutputMessage -from openai.types.responses.response_output_text import ResponseOutputText +from langsmith_tracing.chatbot.activities import ChatResponse -def make_text_response(text: str) -> Response: - """Build a minimal OpenAI Response with a text output.""" - return Response.model_construct( - id="resp_mock", - created_at=0.0, - model="gpt-4o-mini", - object="response", - output=[ - ResponseOutputMessage.model_construct( - id="msg_mock", - type="message", - role="assistant", - status="completed", - content=[ - ResponseOutputText.model_construct( - type="output_text", - text=text, - annotations=[], - ) - ], - ) - ], - parallel_tool_calls=False, - tool_choice="auto", - tools=[], - ) +def make_text_response(text: str) -> ChatResponse: + """Build a minimal ChatResponse with a text output.""" + return ChatResponse(id="resp_mock", output_text=text) diff --git a/tests/langsmith_tracing/test_chatbot.py b/tests/langsmith_tracing/test_chatbot.py index f7845217..2febb654 100644 --- a/tests/langsmith_tracing/test_chatbot.py +++ b/tests/langsmith_tracing/test_chatbot.py @@ -1,42 +1,29 @@ import json import uuid -from openai.types.responses import Response -from openai.types.responses.response_function_tool_call import ( - ResponseFunctionToolCall, -) from temporalio import activity from temporalio.client import Client from temporalio.contrib.langsmith import LangSmithPlugin from temporalio.testing import WorkflowEnvironment from temporalio.worker import Worker -from langsmith_tracing.chatbot.activities import OpenAIRequest +from langsmith_tracing.chatbot.activities import ChatResponse, OpenAIRequest, ToolCall from langsmith_tracing.chatbot.workflows import ChatbotWorkflow from tests.langsmith_tracing.helpers import make_text_response def _make_function_call_response( name: str, arguments: dict, call_id: str = "call_123" -) -> Response: - return Response.model_construct( +) -> ChatResponse: + return ChatResponse( id="resp_tool", - created_at=0.0, - model="gpt-4o-mini", - object="response", - output=[ - ResponseFunctionToolCall.model_construct( - id="fc_mock", - type="function_call", + tool_calls=[ + ToolCall( + call_id=call_id, name=name, arguments=json.dumps(arguments), - call_id=call_id, - status="completed", ) ], - parallel_tool_calls=False, - tool_choice="auto", - tools=[], ) @@ -45,7 +32,7 @@ async def test_chatbot_save_note(client: Client, env: WorkflowEnvironment): call_count = 0 @activity.defn(name="call_openai") - async def mock_call_openai(request: OpenAIRequest) -> Response: + async def mock_call_openai(request: OpenAIRequest) -> ChatResponse: nonlocal call_count call_count += 1 if call_count == 1: @@ -86,7 +73,7 @@ async def test_chatbot_read_note(client: Client, env: WorkflowEnvironment): call_count = 0 @activity.defn(name="call_openai") - async def mock_call_openai(request: OpenAIRequest) -> Response: + async def mock_call_openai(request: OpenAIRequest) -> ChatResponse: nonlocal call_count call_count += 1 if call_count == 1: