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"sk-1234567890abcdef1234567890abcdef") - llm = ChatOpenAI( - model_name="gpt-3.5-turbo", openai_api_key=api_key, temperature=0.0 - ) + llm = ChatOpenAI(model_name="gpt-4o-mini", openai_api_key=api_key, temperature=0.0) prompt = PromptTemplate.from_template("1 + {number} = ") long_str = ( "really_massive_name_that_is_longer_than_max_characters_which_would_be_crazy" @@ -94,9 +92,7 @@ async def test_simple_chain_ainvoke( api_key = os.environ.get("OPENAI_API_KEY", "sk-1234567890abcdef1234567890abcdef") - llm = ChatOpenAI( - model_name="gpt-3.5-turbo", openai_api_key=api_key, temperature=0.0 - ) + llm = ChatOpenAI(model_name="gpt-4o-mini", openai_api_key=api_key, temperature=0.0) prompt = PromptTemplate.from_template("1 + {number} = ") llm_chain = prompt | llm @@ -120,9 +116,7 @@ def test_simple_chain_stream( api_key = os.environ.get("OPENAI_API_KEY", "sk-1234567890abcdef1234567890abcdef") - llm = ChatOpenAI( - model_name="gpt-3.5-turbo", openai_api_key=api_key, temperature=0.0 - ) + llm = ChatOpenAI(model_name="gpt-4o-mini", openai_api_key=api_key, temperature=0.0) prompt = PromptTemplate.from_template("1 + {number} = ") llm_chain = prompt | llm @@ -149,9 +143,7 @@ async def test_simple_chain_astream( api_key = os.environ.get("OPENAI_API_KEY", "sk-1234567890abcdef1234567890abcdef") - llm = ChatOpenAI( - model_name="gpt-3.5-turbo", openai_api_key=api_key, temperature=0.0 - ) + llm = ChatOpenAI(model_name="gpt-4o-mini", openai_api_key=api_key, temperature=0.0) prompt = PromptTemplate.from_template("1 + {number} = ") llm_chain = prompt | llm @@ -197,9 +189,7 @@ def test_simple_chain_batch( api_key = os.environ.get("OPENAI_API_KEY", "sk-1234567890abcdef1234567890abcdef") - llm = ChatOpenAI( - model_name="gpt-3.5-turbo", openai_api_key=api_key, temperature=0.0 - ) + llm = ChatOpenAI(model_name="gpt-4o-mini", openai_api_key=api_key, temperature=0.0) prompt = PromptTemplate.from_template("1 + {number} = ") llm_chain = prompt | llm @@ -225,9 +215,7 @@ async def test_simple_chain_abatch( api_key = os.environ.get("OPENAI_API_KEY", "sk-1234567890abcdef1234567890abcdef") - llm = ChatOpenAI( - model_name="gpt-3.5-turbo", openai_api_key=api_key, temperature=0.0 - ) + llm = ChatOpenAI(model_name="gpt-4o-mini", openai_api_key=api_key, temperature=0.0) prompt = PromptTemplate.from_template("1 + {number} = ") llm_chain = prompt | llm @@ -274,9 +262,7 @@ def test_simple_chain_batch_inside_op( api_key = os.environ.get("OPENAI_API_KEY", "sk-1234567890abcdef1234567890abcdef") - llm = ChatOpenAI( - model_name="gpt-3.5-turbo", openai_api_key=api_key, temperature=0.0 - ) + llm = ChatOpenAI(model_name="gpt-4o-mini", openai_api_key=api_key, temperature=0.0) prompt = PromptTemplate.from_template("1 + {number} = ") llm_chain = prompt | llm @@ -391,9 +377,7 @@ def test_simple_rag_chain(client: WeaveClient, fix_chroma_ci: None) -> None: "Question: {question}\nContext: {context}\nAnswer:" ) - llm = ChatOpenAI( - model_name="gpt-3.5-turbo", openai_api_key=api_key, temperature=0.0 - ) + llm = ChatOpenAI(model_name="gpt-4o-mini", openai_api_key=api_key, temperature=0.0) def format_docs(documents: list[Document]) -> str: return "\n\n".join(doc.page_content for doc in documents) @@ -473,9 +457,7 @@ def multiply(a: int, b: int) -> int: api_key = os.environ.get("OPENAI_API_KEY", "sk-1234567890abcdef1234567890abcdef") - llm = ChatOpenAI( - model_name="gpt-3.5-turbo", openai_api_key=api_key, temperature=0.0 - ) + llm = ChatOpenAI(model_name="gpt-4o-mini", openai_api_key=api_key, temperature=0.0) tools = [calculator] functions = [convert_to_openai_tool(t) for t in tools] @@ -591,9 +573,7 @@ def multiply(a: int, b: int) -> int: api_key = os.environ.get("OPENAI_API_KEY", "sk-1234567890abcdef1234567890abcdef") - llm = ChatOpenAI( - model_name="gpt-3.5-turbo", openai_api_key=api_key, temperature=0.0 - ) + llm = ChatOpenAI(model_name="gpt-4o-mini", openai_api_key=api_key, temperature=0.0) tools = [calculator] functions = [convert_to_openai_function(t) for t in tools] @@ -647,3 +627,31 @@ class AgentInput(BaseModel): ) calls = list(client.calls(filter=tsi.CallsFilter(trace_roots_only=True))) assert_correct_calls_for_agent_with_function_call(calls) + + +@pytest.mark.skip_clickhouse_client +@pytest.mark.vcr( + filter_headers=["authorization", "x-api-key"], + allowed_hosts=["api.wandb.ai", "localhost", "trace.wandb.ai"], + before_record_request=filter_body, +) +def test_weave_attributes_in_call(client: WeaveClient) -> None: + from langchain_core.prompts import PromptTemplate + from langchain_openai import ChatOpenAI + + api_key = os.environ.get("OPENAI_API_KEY", "sk-1234567890abcdef1234567890abcdef") + + llm = ChatOpenAI(model_name="gpt-4o-mini", openai_api_key=api_key, temperature=0.0) + prompt = PromptTemplate.from_template("1 + {number} = ") + + llm_chain = prompt | llm + with weave.attributes({"call_attr": 1}): + _ = llm_chain.invoke({"number": 2}) + + calls = list(client.calls(filter=tsi.CallsFilter(trace_roots_only=True))) + assert len(calls) > 0 + call_attrs = calls[0].attributes + assert call_attrs["call_attr"] == 1 + assert "lc_id" in call_attrs + assert "parent_run_id" in call_attrs + assert "lc_name" in call_attrs diff --git a/weave/integrations/langchain/langchain.py b/weave/integrations/langchain/langchain.py index 4695e8823410..759e7a604add 100644 --- a/weave/integrations/langchain/langchain.py +++ b/weave/integrations/langchain/langchain.py @@ -161,7 +161,7 @@ def _persist_run_single(self, run: Run) -> None: # First, there needs to be something on the stack. if wv_current_run is not None: - attrs = wv_current_run.attributes or {} + attrs = call_context.call_attributes.get() # Now, the major condition: if ( # 1. Both runs must be of type `RunnableSequence` @@ -190,16 +190,20 @@ def _persist_run_single(self, run: Run) -> None: fn_name = make_pythonic_function_name(run.name) complete_op_name = f"langchain.{run.run_type.capitalize()}.{fn_name}" complete_op_name = truncate_op_name(complete_op_name) + call_attrs = call_context.call_attributes.get() + call_attrs.update( + { + "lc_id": str(run.id), + "parent_run_id": lc_parent_run_id, + "lc_name": run.name, + } + ) call = self.gc.create_call( # Make sure to add the run name once the UI issue is figured out complete_op_name, inputs=run_dict.get("inputs", {}), parent=parent_run, - attributes={ - "lc_id": str(run.id), - "parent_run_id": lc_parent_run_id, - "lc_name": run.name, - }, + attributes=call_attrs, display_name=f"langchain.{run.run_type.capitalize()}.{run.name}", use_stack=use_stack, )