Add LangChain integration to main package with auto_instrument() support

integrations/langchain-py/src/braintrust_langchain/__init__.py

@@ -1,4 +1,4 @@
 from .callbacks import BraintrustCallbackHandler
-from .context import set_global_handler
+from .context import clear_global_handler, set_global_handler
 
-__all__ = ["BraintrustCallbackHandler", "set_global_handler"]
+__all__ = ["BraintrustCallbackHandler", "set_global_handler", "clear_global_handler"]

py/Makefile

@@ -55,7 +55,8 @@ install-dev: install-build-deps
 	python -m uv pip install -r requirements-dev.txt
 
 install-optional:
-	python -m uv pip install anthropic openai pydantic_ai litellm agno google-genai dspy langsmith
+	python -m uv pip install anthropic openai pydantic_ai litellm agno google-genai dspy langsmith \
+		langchain langchain-openai tenacity
 	python -m uv pip install -e .[temporal,otel]
 
 .DEFAULT_GOAL := help

py/examples/auto_instrument.py

@@ -13,6 +13,7 @@
 - Agno
 - Claude Agent SDK
 - DSPy
+- LangChain
 """
 
 import braintrust

py/examples/langchain/auto.py

@@ -0,0 +1,35 @@
+"""
+Example: LangChain with auto_instrument()
+
+This example demonstrates automatic tracing of LangChain operations
+using braintrust.auto_instrument().
+
+Run with: python examples/langchain/auto.py
+"""
+
+import braintrust
+
+# One-line instrumentation - call this BEFORE importing LangChain
+results = braintrust.auto_instrument()
+print(f"LangChain instrumented: {results.get('langchain', False)}")
+
+# Initialize logging
+logger = braintrust.init_logger(project="langchain-auto-example")
+
+# Now import LangChain - all operations are automatically traced
+from langchain_core.prompts import ChatPromptTemplate
+from langchain_openai import ChatOpenAI
+
+# Create a simple chain
+prompt = ChatPromptTemplate.from_template("What is {number} + {number}?")
+model = ChatOpenAI(model="gpt-4o-mini")
+chain = prompt | model
+
+# Wrap in a span to get a link
+with braintrust.start_span(name="langchain_auto_example") as span:
+    print("Running LangChain chain...")
+    result = chain.invoke({"number": "5"})
+    print(f"Result: {result.content}")
+    span.log(output=result.content)
+
+print(f"\nView trace: {span.link()}")

py/examples/langchain/manual.py

@@ -0,0 +1,62 @@
+"""
+Example: LangChain with manual setup
+
+This example demonstrates using setup_langchain() for global handler registration
+and BraintrustCallbackHandler for per-call tracing.
+
+Run with: python examples/langchain/manual.py
+"""
+
+import braintrust
+from braintrust.wrappers.langchain import (
+    BraintrustCallbackHandler,
+    set_global_handler,
+    setup_langchain,
+)
+
+# Initialize logging
+logger = braintrust.init_logger(project="langchain-manual-example")
+
+# Method 1: Global handler via setup_langchain()
+# This registers a handler that traces ALL LangChain operations automatically
+print("Method 1: Global handler")
+setup_langchain()
+
+from langchain_core.prompts import ChatPromptTemplate
+from langchain_openai import ChatOpenAI
+
+prompt = ChatPromptTemplate.from_template("What is the capital of {country}?")
+model = ChatOpenAI(model="gpt-4o-mini")
+chain = prompt | model
+
+# All operations are traced automatically
+result = chain.invoke({"country": "France"})
+print(f"  Capital: {result.content}\n")
+
+
+# Method 2: Per-call handler
+# This is useful when you want more control over which calls are traced
+print("Method 2: Per-call handler")
+
+# Create a handler with a specific logger
+handler = BraintrustCallbackHandler(logger=logger)
+
+# Pass the handler explicitly to chain.invoke()
+result = chain.invoke(
+    {"country": "Japan"},
+    config={"callbacks": [handler]}
+)
+print(f"  Capital: {result.content}\n")
+
+
+# Method 3: Global handler with custom handler instance
+print("Method 3: Custom global handler")
+
+# Create a custom handler and set it globally
+custom_handler = BraintrustCallbackHandler(logger=logger)
+set_global_handler(custom_handler)
+
+result = chain.invoke({"country": "Brazil"})
+print(f"  Capital: {result.content}\n")
+
+print("Check Braintrust dashboard for traces!")

py/noxfile.py

@@ -43,6 +43,7 @@
     "openai",
     "openai-agents",
     # pydantic_ai is NOT included here - it has dedicated test sessions with version-specific handling
+    # langchain is NOT included here - it has dedicated test sessions with version-specific handling
     "autoevals",
     "braintrust_core",
     "litellm",
@@ -73,6 +74,8 @@
 DSPY_VERSIONS = (LATEST,)
 # temporalio 1.19.0+ requires Python >= 3.10; skip Python 3.9 entirely
 TEMPORAL_VERSIONS = (LATEST, "1.20.0", "1.19.0")
+# langchain requires Python >= 3.10
+LANGCHAIN_VERSIONS = (LATEST, "0.3.27")
 
 
 @nox.session()
@@ -193,6 +196,20 @@ def test_dspy(session, version):
     _run_tests(session, f"{WRAPPER_DIR}/test_dspy.py")
 
 
+@nox.session()
+@nox.parametrize("version", LANGCHAIN_VERSIONS, ids=LANGCHAIN_VERSIONS)
+def test_langchain(session, version):
+    """Test LangChain integration."""
+    # langchain requires Python >= 3.10
+    if sys.version_info < (3, 10):
+        session.skip("langchain tests require Python >= 3.10")
+    _install_test_deps(session)
+    _install(session, "langchain", version)
+    session.install("langchain-openai", "langchain-anthropic", "langgraph")
+    _run_tests(session, f"{WRAPPER_DIR}/test_langchain.py")
+    _run_core_tests(session)
+
+
 @nox.session()
 @nox.parametrize("version", AUTOEVALS_VERSIONS, ids=AUTOEVALS_VERSIONS)
 def test_autoevals(session, version):
@@ -267,6 +284,8 @@ def pylint(session):
     session.install("opentelemetry.instrumentation.openai")
     # langsmith is needed for the wrapper module but not in VENDOR_PACKAGES
     session.install("langsmith")
+    # langchain dependencies for the langchain wrapper
+    session.install("langchain", "langchain-openai", "langchain-anthropic", "langgraph")
 
     result = session.run("git", "ls-files", "**/*.py", silent=True, log=False)
     files = result.strip().splitlines()

py/src/braintrust/auto.py

@@ -35,6 +35,7 @@ def auto_instrument(
     agno: bool = True,
     claude_agent_sdk: bool = True,
     dspy: bool = True,
+    langchain: bool = True,
 ) -> dict[str, bool]:
     """
     Auto-instrument supported AI/ML libraries for Braintrust tracing.
@@ -54,6 +55,7 @@ def auto_instrument(
         agno: Enable Agno instrumentation (default: True)
         claude_agent_sdk: Enable Claude Agent SDK instrumentation (default: True)
         dspy: Enable DSPy instrumentation (default: True)
+        langchain: Enable LangChain instrumentation (default: True)
 
     Returns:
         Dict mapping integration name to whether it was successfully instrumented.
@@ -91,6 +93,11 @@ def auto_instrument(
         from google.genai import Client
         client = Client()
         client.models.generate_content(model="gemini-2.0-flash", contents="Hello!")
+
+        # LangChain
+        from langchain_openai import ChatOpenAI
+        model = ChatOpenAI(model="gpt-4o-mini")
+        model.invoke("Hello!")
         ```
     """
     results = {}
@@ -111,6 +118,8 @@ def auto_instrument(
         results["claude_agent_sdk"] = _instrument_claude_agent_sdk()
     if dspy:
         results["dspy"] = _instrument_dspy()
+    if langchain:
+        results["langchain"] = _instrument_langchain()
 
     return results
 
@@ -177,3 +186,11 @@ def _instrument_dspy() -> bool:
 
         return patch_dspy()
     return False
+
+
+def _instrument_langchain() -> bool:
+    with _try_patch():
+        from braintrust.wrappers.langchain import setup_langchain
+
+        return setup_langchain()
+    return False