feat(langchain): add v1 support

.github/workflows/ci.yml

@@ -30,7 +30,7 @@ jobs:
       - name: Set up Python
         uses: actions/setup-python@v4
         with:
-          python-version: "3.12"
+          python-version: "3.13"
       - name: Install poetry
         uses: abatilo/actions-poetry@v2
       - name: Setup a local virtual environment
@@ -69,9 +69,10 @@ jobs:
       fail-fast: false
       matrix:
         python-version:
-          - "3.9"
           - "3.10"
           - "3.11"
+          - "3.12"
+          - "3.13"
 
     name: Test on Python version ${{ matrix.python-version }}
     steps:

.pre-commit-config.yaml

@@ -12,7 +12,7 @@ repos:
         types_or: [python, pyi, jupyter]
 
   - repo: https://github.com/pre-commit/mirrors-mypy
-    rev: v1.8.0
+    rev: v1.18.2
     hooks:
       - id: mypy
         additional_dependencies:

langfuse/_client/client.py

@@ -211,9 +211,7 @@ def __init__(
         additional_headers: Optional[Dict[str, str]] = None,
         tracer_provider: Optional[TracerProvider] = None,
     ):
-        self._host = host or cast(
-            str, os.environ.get(LANGFUSE_HOST, "https://cloud.langfuse.com")
-        )
+        self._host = host or os.environ.get(LANGFUSE_HOST, "https://cloud.langfuse.com")
         self._environment = environment or cast(
             str, os.environ.get(LANGFUSE_TRACING_ENVIRONMENT)
         )

langfuse/_utils/serializer.py

@@ -19,7 +19,7 @@
 
 # Attempt to import Serializable
 try:
-    from langchain.load.serializable import Serializable
+    from langchain_core.load.serializable import Serializable
 except ImportError:
     # If Serializable is not available, set it to a placeholder type
     class Serializable:  # type: ignore

langfuse/langchain/CallbackHandler.py

@@ -1,5 +1,17 @@
-import typing
 from contextvars import Token
+from typing import (
+    Any,
+    Dict,
+    List,
+    Literal,
+    Optional,
+    Sequence,
+    Set,
+    Type,
+    Union,
+    cast,
+)
+from uuid import UUID
 
 import pydantic
 from opentelemetry import context, trace
@@ -16,41 +28,52 @@
     LangfuseSpan,
     LangfuseTool,
 )
+from langfuse._utils import _get_timestamp
+from langfuse.langchain.utils import _extract_model_name
 from langfuse.logger import langfuse_logger
 
 try:
-    import langchain  # noqa
-
-except ImportError as e:
-    langfuse_logger.error(
-        f"Could not import langchain. The langchain integration will not work. {e}"
-    )
+    import langchain
 
-from typing import Any, Dict, List, Literal, Optional, Sequence, Set, Type, Union, cast
-from uuid import UUID
+    if langchain.__version__.startswith("1"):
+        # Langchain v1
+        from langchain_core.agents import AgentAction, AgentFinish
+        from langchain_core.callbacks import (
+            BaseCallbackHandler as LangchainBaseCallbackHandler,
+        )
+        from langchain_core.documents import Document
+        from langchain_core.messages import (
+            AIMessage,
+            BaseMessage,
+            ChatMessage,
+            FunctionMessage,
+            HumanMessage,
+            SystemMessage,
+            ToolMessage,
+        )
+        from langchain_core.outputs import ChatGeneration, LLMResult
 
-from langfuse._utils import _get_timestamp
-from langfuse.langchain.utils import _extract_model_name
+    else:
+        # Langchain v0
+        from langchain.callbacks.base import (  # type: ignore
+            BaseCallbackHandler as LangchainBaseCallbackHandler,
+        )
+        from langchain.schema.agent import AgentAction, AgentFinish  # type: ignore
+        from langchain.schema.document import Document  # type: ignore
+        from langchain_core.messages import (
+            AIMessage,
+            BaseMessage,
+            ChatMessage,
+            FunctionMessage,
+            HumanMessage,
+            SystemMessage,
+            ToolMessage,
+        )
+        from langchain_core.outputs import (
+            ChatGeneration,
+            LLMResult,
+        )
 
-try:
-    from langchain.callbacks.base import (
-        BaseCallbackHandler as LangchainBaseCallbackHandler,
-    )
-    from langchain.schema.agent import AgentAction, AgentFinish
-    from langchain.schema.document import Document
-    from langchain_core.messages import (
-        AIMessage,
-        BaseMessage,
-        ChatMessage,
-        FunctionMessage,
-        HumanMessage,
-        SystemMessage,
-        ToolMessage,
-    )
-    from langchain_core.outputs import (
-        ChatGeneration,
-        LLMResult,
-    )
 except ImportError:
     raise ModuleNotFoundError(
         "Please install langchain to use the Langfuse langchain integration: 'pip install langchain'"
@@ -1011,7 +1034,7 @@ def _flatten_comprehension(matrix: Any) -> Any:
     return [item for row in matrix for item in row]
 
 
-def _parse_usage_model(usage: typing.Union[pydantic.BaseModel, dict]) -> Any:
+def _parse_usage_model(usage: Union[pydantic.BaseModel, dict]) -> Any:
     # maintains a list of key translations. For each key, the usage model is checked
     # and a new object will be created with the new key if the key exists in the usage model
     # All non matched keys will remain on the object.