Add langchain instrumentation

CHANGELOG.md

@@ -4,6 +4,8 @@
 
 ### Features Added
 
+- Add langchain instrumentation 
+  ([#26](https://github.com/microsoft/opentelemetry-distro-python/pull/26))
 - Add Microsoft Opentelemetry Distro Configuration
   ([#9](https://github.com/microsoft/opentelemetry-distro-python/pull/9))
 - Add langchain samples

pyproject.toml

@@ -24,6 +24,9 @@ dependencies = [
     "opentelemetry-instrumentation-urllib3==0.61b0",
     "opentelemetry-instrumentation-logging==0.61b0",
     "opentelemetry-resource-detector-azure<1.0.0,>=0.1.5",
+    "langchain-core>=0.2.0",
+    "wrapt>=1.0",
+    "opentelemetry-util-genai>=0.3b0",
 ]
 
 [project.optional-dependencies]
@@ -40,6 +43,9 @@ dev = [
     "pytest-cov>=5.0",
 ]
 
+[project.entry-points.opentelemetry_instrumentor]
+langchain = "microsoft.genai._langchain._tracer_instrumentor:LangChainInstrumentor"
+
 [tool.setuptools]
 package-dir = {"" = "src"}
 

samples/langchain/sample_langchain_instrumentation.py

@@ -0,0 +1,87 @@
+# Copyright (c) Microsoft Corporation.
+# Licensed under the MIT License.
+
+from microsoft.opentelemetry._distro import use_microsoft_opentelemetry
+from langchain_core.messages import HumanMessage, SystemMessage
+from langchain_core.tools import tool
+from langchain_openai import ChatOpenAI
+from langchain.agents import create_agent
+
+
+endpoint = "<AZURE_OPENAI_ENDPOINT>"
+model_name = "gpt-4.1"
+deployment_name = "gpt-4.1"
+
+api_key = "<AZURE_OPENAI_API_KEY>"
+
+use_microsoft_opentelemetry(
+    sampling_ratio=1.0,
+    instrumentation_options={
+        "langchain": {"enabled": True},
+    }
+)
+
+def main():
+
+    # ChatOpenAI
+    llm = ChatOpenAI(
+        model="gpt-4.1",
+        temperature=0.1,
+        max_tokens=100,
+        top_p=0.9,
+        frequency_penalty=0.5,
+        presence_penalty=0.5,
+        stop_sequences=["\n", "Human:", "AI:"],
+        seed=100,
+        api_key=api_key, # Do not include api_key and base_url if using the OPENAI_API_KEY environment variable
+        base_url=endpoint,
+    )
+
+    messages = [
+        SystemMessage(content="You are a helpful assistant!"),
+        HumanMessage(content="What is the capital of France?"),
+    ]
+
+    result = llm.invoke(messages)
+    print("LLM output:\n", result)
+
+    @tool
+    def get_population(city: str) -> str:
+        """Get the population of a city."""
+        populations = {
+            "paris": "2.1 million",
+            "london": "8.9 million",
+            "tokyo": "14 million",
+            "new york": "8.3 million",
+        }
+        return populations.get(city.lower(), f"Population data not available for {city}.")
+
+    @tool
+    def get_famous_landmark(city: str) -> str:
+        """Get the most famous landmark in a city."""
+        landmarks = {
+            "paris": "Eiffel Tower",
+            "london": "Big Ben",
+            "tokyo": "Tokyo Tower",
+            "new york": "Statue of Liberty",
+        }
+        return landmarks.get(city.lower(), f"No landmark info for {city}.")
+
+    agent = create_agent(
+        llm,
+        tools=[get_population, get_famous_landmark],
+        system_prompt="You are a helpful travel assistant. Use the tools to answer questions about cities.",
+        name="Travel_Assistant"
+    )
+
+    print("\n--- Agent run ---")
+    user_input = "What is the population of Paris and what is its most famous landmark?"
+    agent_result = agent.invoke({"messages": [("human", user_input)]})
+    output = agent_result["messages"][-1].content
+    print("Agent output:\n", output)
+
+
+
+
+if __name__ == "__main__":
+    main()

src/microsoft/genai/__init__.py

@@ -0,0 +1,2 @@
+# Copyright (c) Microsoft Corporation.
+# Licensed under the MIT License.

src/microsoft/genai/_langchain/__init__.py

@@ -0,0 +1,6 @@
+# Copyright (c) Microsoft Corporation.
+# Licensed under the MIT License.
+
+from microsoft.genai._langchain._tracer_instrumentor import LangChainInstrumentor
+
+__all__ = ["LangChainInstrumentor"]