fix: set langchain template variables as dict (#193)

python/instrumentation/openinference-instrumentation-langchain/examples/chain_metadata.py

@@ -1,20 +1,17 @@
 from langchain.chains import LLMChain
-from langchain_community.llms import OpenAI
 from langchain_core.prompts import PromptTemplate
+from langchain_openai import OpenAI
 from openinference.instrumentation.langchain import LangChainInstrumentor
 from opentelemetry import trace as trace_api
 from opentelemetry.exporter.otlp.proto.http.trace_exporter import OTLPSpanExporter
 from opentelemetry.sdk import trace as trace_sdk
-from opentelemetry.sdk.resources import Resource
 from opentelemetry.sdk.trace.export import ConsoleSpanExporter, SimpleSpanProcessor
 
-resource = Resource(attributes={})
-tracer_provider = trace_sdk.TracerProvider(resource=resource)
-trace_api.set_tracer_provider(tracer_provider=tracer_provider)
-span_otlp_exporter = OTLPSpanExporter(endpoint="http://127.0.0.1:6006/v1/traces")
-tracer_provider.add_span_processor(SimpleSpanProcessor(span_exporter=span_otlp_exporter))
-span_console_exporter = ConsoleSpanExporter()
-tracer_provider.add_span_processor(SimpleSpanProcessor(span_exporter=span_console_exporter))
+endpoint = "http://127.0.0.1:6006/v1/traces"
+tracer_provider = trace_sdk.TracerProvider()
+trace_api.set_tracer_provider(tracer_provider)
+tracer_provider.add_span_processor(SimpleSpanProcessor(OTLPSpanExporter(endpoint=endpoint)))
+tracer_provider.add_span_processor(SimpleSpanProcessor(ConsoleSpanExporter()))
 
 LangChainInstrumentor().instrument()
 

python/instrumentation/openinference-instrumentation-langchain/examples/openai_chat_stream.py

@@ -3,16 +3,13 @@
 from opentelemetry import trace as trace_api
 from opentelemetry.exporter.otlp.proto.http.trace_exporter import OTLPSpanExporter
 from opentelemetry.sdk import trace as trace_sdk
-from opentelemetry.sdk.resources import Resource
 from opentelemetry.sdk.trace.export import ConsoleSpanExporter, SimpleSpanProcessor
 
-resource = Resource(attributes={})
-tracer_provider = trace_sdk.TracerProvider(resource=resource)
-trace_api.set_tracer_provider(tracer_provider=tracer_provider)
-span_otlp_exporter = OTLPSpanExporter(endpoint="http://127.0.0.1:6006/v1/traces")
-tracer_provider.add_span_processor(SimpleSpanProcessor(span_exporter=span_otlp_exporter))
-span_console_exporter = ConsoleSpanExporter()
-tracer_provider.add_span_processor(SimpleSpanProcessor(span_exporter=span_console_exporter))
+endpoint = "http://127.0.0.1:6006/v1/traces"
+tracer_provider = trace_sdk.TracerProvider()
+trace_api.set_tracer_provider(tracer_provider)
+tracer_provider.add_span_processor(SimpleSpanProcessor(OTLPSpanExporter(endpoint=endpoint)))
+tracer_provider.add_span_processor(SimpleSpanProcessor(ConsoleSpanExporter()))
 
 LangChainInstrumentor().instrument()
 

python/instrumentation/openinference-instrumentation-langchain/src/openinference/instrumentation/langchain/_tracer.py

@@ -140,7 +140,7 @@ def _update_span(span: trace_api.Span, run: Run) -> None:
                     _prompts(run.inputs),
                     _input_messages(run.inputs),
                     _output_messages(run.outputs),
-                    _prompt_template(run.serialized),
+                    _prompt_template(run),
                     _invocation_parameters(run),
                     _model_name(run.extra),
                     _token_counts(run.outputs),
@@ -353,11 +353,12 @@ def _get_tool_call(tool_call: Optional[Mapping[str, Any]]) -> Iterator[Tuple[str
 
 
 @stop_on_exception
-def _prompt_template(serialized: Optional[Mapping[str, Any]]) -> Iterator[Tuple[str, Any]]:
+def _prompt_template(run: Run) -> Iterator[Tuple[str, Any]]:
     """
     A best-effort attempt to locate the PromptTemplate object among the
     keyword arguments of a serialized object, e.g. an LLMChain object.
     """
+    serialized: Optional[Mapping[str, Any]] = run.serialized
     if not serialized:
         return
     assert hasattr(serialized, "get"), f"expected Mapping, found {type(serialized)}"
@@ -383,7 +384,12 @@ def _prompt_template(serialized: Optional[Mapping[str, Any]]) -> Iterator[Tuple[
                 assert isinstance(
                     input_variables, list
                 ), f"expected list, found {type(input_variables)}"
-                yield LLM_PROMPT_TEMPLATE_VARIABLES, input_variables
+                template_variables = {}
+                for variable in input_variables:
+                    if value := run.inputs.get(variable):
+                        template_variables[variable] = value
+                if template_variables:
+                    yield LLM_PROMPT_TEMPLATE_VARIABLES, json.dumps(template_variables)
             break
 
 

python/instrumentation/openinference-instrumentation-langchain/tests/openinference/instrumentation/langchain/test_instrumentor.py

@@ -1,4 +1,5 @@
 import asyncio
+import json
 import logging
 import random
 from contextlib import suppress
@@ -27,7 +28,6 @@
 )
 from opentelemetry import trace as trace_api
 from opentelemetry.sdk import trace as trace_sdk
-from opentelemetry.sdk.resources import Resource
 from opentelemetry.sdk.trace.export import SimpleSpanProcessor
 from opentelemetry.sdk.trace.export.in_memory_span_exporter import InMemorySpanExporter
 from opentelemetry.semconv.trace import SpanAttributes as OTELSpanAttributes
@@ -55,6 +55,8 @@ def test_callback_llm(
     completion_usage: Dict[str, Any],
 ) -> None:
     question = randstr()
+    template = "{context}{question}"
+    prompt = PromptTemplate(input_variables=["context", "question"], template=template)
     output_messages: List[Dict[str, Any]] = (
         chat_completion_mock_stream[1] if is_stream else [{"role": randstr(), "content": randstr()}]
     )
@@ -82,7 +84,11 @@ def test_callback_llm(
         texts=documents,
         embeddings=FakeEmbeddings(size=2),
     )
-    rqa = RetrievalQA.from_chain_type(llm=chat_model, retriever=retriever)
+    rqa = RetrievalQA.from_chain_type(
+        llm=chat_model,
+        retriever=retriever,
+        chain_type_kwargs={"prompt": prompt},
+    )
     with suppress(openai.BadRequestError):
         if is_async:
             asyncio.run(rqa.ainvoke({"query": question}))
@@ -150,6 +156,15 @@ def test_callback_llm(
     assert llm_attributes.pop(OPENINFERENCE_SPAN_KIND, None) == CHAIN.value
     assert llm_attributes.pop(INPUT_VALUE, None) is not None
     assert llm_attributes.pop(INPUT_MIME_TYPE, None) == JSON.value
+    assert llm_attributes.pop(LLM_PROMPT_TEMPLATE, None) == template
+    assert isinstance(
+        template_variables_json_string := llm_attributes.pop(LLM_PROMPT_TEMPLATE_VARIABLES, None),
+        str,
+    )
+    assert json.loads(template_variables_json_string) == {
+        "context": "\n\n".join(documents),
+        "question": question,
+    }
     if status_code == 200:
         assert llm_attributes.pop(OUTPUT_VALUE, None) == output_messages[0]["content"]
     elif status_code == 400:
@@ -275,10 +290,8 @@ def in_memory_span_exporter() -> InMemorySpanExporter:
 
 @pytest.fixture(scope="module")
 def tracer_provider(in_memory_span_exporter: InMemorySpanExporter) -> trace_api.TracerProvider:
-    resource = Resource(attributes={})
-    tracer_provider = trace_sdk.TracerProvider(resource=resource)
-    span_processor = SimpleSpanProcessor(span_exporter=in_memory_span_exporter)
-    tracer_provider.add_span_processor(span_processor=span_processor)
+    tracer_provider = trace_sdk.TracerProvider()
+    tracer_provider.add_span_processor(SimpleSpanProcessor(in_memory_span_exporter))
     return tracer_provider
 
 
@@ -362,6 +375,8 @@ async def __aiter__(self) -> AsyncIterator[bytes]:
 LLM_MODEL_NAME = SpanAttributes.LLM_MODEL_NAME
 LLM_OUTPUT_MESSAGES = SpanAttributes.LLM_OUTPUT_MESSAGES
 LLM_PROMPTS = SpanAttributes.LLM_PROMPTS
+LLM_PROMPT_TEMPLATE = SpanAttributes.LLM_PROMPT_TEMPLATE
+LLM_PROMPT_TEMPLATE_VARIABLES = SpanAttributes.LLM_PROMPT_TEMPLATE_VARIABLES
 LLM_TOKEN_COUNT_COMPLETION = SpanAttributes.LLM_TOKEN_COUNT_COMPLETION
 LLM_TOKEN_COUNT_PROMPT = SpanAttributes.LLM_TOKEN_COUNT_PROMPT
 LLM_TOKEN_COUNT_TOTAL = SpanAttributes.LLM_TOKEN_COUNT_TOTAL