From c1b41691ea58fb9a84c360f6a6e0fbc3567f7be2 Mon Sep 17 00:00:00 2001 From: Hassieb Pakzad <68423100+hassiebp@users.noreply.github.com> Date: Mon, 20 Oct 2025 11:51:11 +0200 Subject: [PATCH 1/5] feat(langchain): add v1 support --- langfuse/_utils/serializer.py | 2 +- langfuse/langchain/CallbackHandler.py | 85 +- poetry.lock | 2574 ++++++++++++------------- pyproject.toml | 6 +- tests/test_datasets.py | 2 +- tests/test_decorators.py | 2 +- tests/test_json.py | 2 +- tests/test_langchain.py | 445 +---- tests/test_langchain_integration.py | 4 +- tests/test_prompt_compilation.py | 2 +- 10 files changed, 1308 insertions(+), 1816 deletions(-) diff --git a/langfuse/_utils/serializer.py b/langfuse/_utils/serializer.py index 289531b23..1350ea00c 100644 --- a/langfuse/_utils/serializer.py +++ b/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 diff --git a/langfuse/langchain/CallbackHandler.py b/langfuse/langchain/CallbackHandler.py index 98ef24680..9e8278e28 100644 --- a/langfuse/langchain/CallbackHandler.py +++ b/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. diff --git a/poetry.lock b/poetry.lock index 4387fe601..c06d82f1c 100644 --- a/poetry.lock +++ b/poetry.lock @@ -1,4 +1,4 @@ -# This file is automatically @generated by Poetry 2.1.1 and should not be changed by hand. +# This file is automatically @generated by Poetry 1.8.4 and should not be changed by hand. [[package]] name = "annotated-types" @@ -6,7 +6,6 @@ version = "0.7.0" description = "Reusable constraint types to use with typing.Annotated" optional = false python-versions = ">=3.8" -groups = ["main", "dev"] files = [ {file = "annotated_types-0.7.0-py3-none-any.whl", hash = "sha256:1f02e8b43a8fbbc3f3e0d4f0f4bfc8131bcb4eebe8849b8e5c773f3a1c582a53"}, {file = "annotated_types-0.7.0.tar.gz", hash = "sha256:aff07c09a53a08bc8cfccb9c85b05f1aa9a2a6f23728d790723543408344ce89"}, @@ -14,14 +13,13 @@ files = [ [[package]] name = "anyio" -version = "4.10.0" +version = "4.11.0" description = "High-level concurrency and networking framework on top of asyncio or Trio" optional = false python-versions = ">=3.9" -groups = ["main", "dev"] files = [ - {file = "anyio-4.10.0-py3-none-any.whl", hash = "sha256:60e474ac86736bbfd6f210f7a61218939c318f43f9972497381f1c5e930ed3d1"}, - {file = "anyio-4.10.0.tar.gz", hash = "sha256:3f3fae35c96039744587aa5b8371e7e8e603c0702999535961dd336026973ba6"}, + {file = "anyio-4.11.0-py3-none-any.whl", hash = "sha256:0287e96f4d26d4149305414d4e3bc32f0dcd0862365a4bddea19d7a1ec38c4fc"}, + {file = "anyio-4.11.0.tar.gz", hash = "sha256:82a8d0b81e318cc5ce71a5f1f8b5c4e63619620b63141ef8c995fa0db95a57c4"}, ] [package.dependencies] @@ -31,48 +29,25 @@ sniffio = ">=1.1" typing_extensions = {version = ">=4.5", markers = "python_version < \"3.13\""} [package.extras] -trio = ["trio (>=0.26.1)"] - -[[package]] -name = "async-timeout" -version = "4.0.3" -description = "Timeout context manager for asyncio programs" -optional = true -python-versions = ">=3.7" -groups = ["main"] -markers = "extra == \"langchain\" and python_version < \"3.11\"" -files = [ - {file = "async-timeout-4.0.3.tar.gz", hash = "sha256:4640d96be84d82d02ed59ea2b7105a0f7b33abe8703703cd0ab0bf87c427522f"}, - {file = "async_timeout-4.0.3-py3-none-any.whl", hash = "sha256:7405140ff1230c310e51dc27b3145b9092d659ce68ff733fb0cefe3ee42be028"}, -] +trio = ["trio (>=0.31.0)"] [[package]] name = "attrs" -version = "25.3.0" +version = "25.4.0" description = "Classes Without Boilerplate" optional = false -python-versions = ">=3.8" -groups = ["dev"] +python-versions = ">=3.9" files = [ - {file = "attrs-25.3.0-py3-none-any.whl", hash = "sha256:427318ce031701fea540783410126f03899a97ffc6f61596ad581ac2e40e3bc3"}, - {file = "attrs-25.3.0.tar.gz", hash = "sha256:75d7cefc7fb576747b2c81b4442d4d4a1ce0900973527c011d1030fd3bf4af1b"}, + {file = "attrs-25.4.0-py3-none-any.whl", hash = "sha256:adcf7e2a1fb3b36ac48d97835bb6d8ade15b8dcce26aba8bf1d14847b57a3373"}, + {file = "attrs-25.4.0.tar.gz", hash = "sha256:16d5969b87f0859ef33a48b35d55ac1be6e42ae49d5e853b597db70c35c57e11"}, ] -[package.extras] -benchmark = ["cloudpickle ; 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--git a/pyproject.toml b/pyproject.toml index dad96000e..a3ac04c3a 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -8,13 +8,12 @@ license = "MIT" readme = "README.md" [tool.poetry.dependencies] -python = ">=3.9,<4.0" +python = ">=3.10,<4.0" httpx = ">=0.15.4,<1.0" pydantic = ">=1.10.7, <3.0" backoff = ">=1.10.0" openai = { version = ">=0.27.8", optional = true } wrapt = "^1.14" -langchain = { version = ">=0.0.309", optional = true } packaging = ">=23.2,<26.0" requests = "^2" opentelemetry-api = "^1.33.1" @@ -31,7 +30,8 @@ pytest-httpserver = "^1.0.8" ruff = ">=0.1.8,<0.13.0" mypy = "^1.0.0" langchain-openai = ">=0.0.5,<0.4" -langgraph = ">=0.2.62,<0.7.0" +langchain = ">=1" +langgraph = ">=1" autoevals = "^0.0.130" [tool.poetry.group.docs.dependencies] diff --git a/tests/test_datasets.py b/tests/test_datasets.py index 7217c0a8d..c64a4adc1 100644 --- a/tests/test_datasets.py +++ b/tests/test_datasets.py @@ -3,7 +3,7 @@ from concurrent.futures import ThreadPoolExecutor from typing import Sequence -from langchain import PromptTemplate +from langchain_core.prompts import PromptTemplate from langchain_openai import OpenAI from langfuse import Langfuse, observe diff --git a/tests/test_decorators.py b/tests/test_decorators.py index 5803d531b..0eac5c617 100644 --- a/tests/test_decorators.py +++ b/tests/test_decorators.py @@ -7,7 +7,7 @@ from typing import Optional import pytest -from langchain.prompts import ChatPromptTemplate +from langchain_core.prompts import ChatPromptTemplate from langchain_openai import ChatOpenAI from opentelemetry import trace diff --git a/tests/test_json.py b/tests/test_json.py index afcacfc76..f231bb97a 100644 --- a/tests/test_json.py +++ b/tests/test_json.py @@ -7,7 +7,7 @@ from unittest.mock import patch import pytest -from langchain.schema.messages import HumanMessage +from langchain.messages import HumanMessage from pydantic import BaseModel import langfuse diff --git a/tests/test_langchain.py b/tests/test_langchain.py index deac5de7d..b4cf828b2 100644 --- a/tests/test_langchain.py +++ b/tests/test_langchain.py @@ -1,23 +1,13 @@ -import os import random import string import time from time import sleep -from typing import Any, Dict, List, Literal, Mapping, Optional +from typing import Any, Dict, Literal import pytest -from langchain.chains import ( - ConversationChain, - LLMChain, - SimpleSequentialChain, -) -from langchain.chains.openai_functions import create_openai_fn_chain -from langchain.memory import ConversationBufferMemory -from langchain.prompts import ChatPromptTemplate, PromptTemplate -from langchain.schema import HumanMessage, SystemMessage -from langchain_core.callbacks.manager import CallbackManagerForLLMRun -from langchain_core.language_models.llms import LLM +from langchain.messages import HumanMessage, SystemMessage from langchain_core.output_parsers import StrOutputParser +from langchain_core.prompts import ChatPromptTemplate, PromptTemplate from langchain_core.runnables.base import RunnableLambda from langchain_core.tools import StructuredTool, tool from langchain_openai import ChatOpenAI, OpenAI @@ -31,59 +21,6 @@ from tests.utils import create_uuid, encode_file_to_base64, get_api -def test_callback_generated_from_trace_chain(): - langfuse = Langfuse() - - with langfuse.start_as_current_span(name="parent") as span: - trace_id = span.trace_id - handler = CallbackHandler() - - llm = OpenAI(openai_api_key=os.environ.get("OPENAI_API_KEY")) - template = """You are a playwright. Given the title of play, it is your job to write a synopsis for that title. - Title: {title} - Playwright: This is a synopsis for the above play:""" - - prompt_template = PromptTemplate(input_variables=["title"], template=template) - synopsis_chain = LLMChain(llm=llm, prompt=prompt_template) - - synopsis_chain.run("Tragedy at sunset on the beach", callbacks=[handler]) - - langfuse.flush() - - trace = get_api().trace.get(trace_id) - - assert trace.input is None - assert trace.output is None - - assert len(trace.observations) == 3 - - langchain_span = list( - filter( - lambda o: o.type == "CHAIN" and o.name == "LLMChain", - trace.observations, - ) - )[0] - - assert langchain_span.input is not None - assert langchain_span.output is not None - - langchain_generation_span = list( - filter( - lambda o: o.type == "GENERATION" and o.name == "OpenAI", - trace.observations, - ) - )[0] - - assert langchain_generation_span.parent_observation_id == langchain_span.id - assert langchain_generation_span.usage_details["input"] > 0 - assert langchain_generation_span.usage_details["output"] > 0 - assert langchain_generation_span.usage_details["total"] > 0 - assert langchain_generation_span.input is not None - assert langchain_generation_span.input != "" - assert langchain_generation_span.output is not None - assert langchain_generation_span.output != "" - - def test_callback_generated_from_trace_chat(): langfuse = Langfuse() @@ -103,7 +40,7 @@ def test_callback_generated_from_trace_chat(): ), ] - chat(messages, callbacks=[handler]) + chat.invoke(messages, config={"callbacks": [handler]}) langfuse.flush() @@ -219,44 +156,6 @@ def test_basic_chat_openai(): assert generation.output is not None -def test_callback_retriever_conversational_with_memory(): - langfuse = Langfuse() - - with langfuse.start_as_current_span( - name="retriever_conversational_with_memory_test" - ) as span: - trace_id = span.trace_id - handler = CallbackHandler() - - llm = OpenAI(openai_api_key=os.environ.get("OPENAI_API_KEY")) - conversation = ConversationChain( - llm=llm, - verbose=True, - memory=ConversationBufferMemory(), - callbacks=[handler], - ) - conversation.predict(input="Hi there!", callbacks=[handler]) - - handler.client.flush() - - trace = get_api().trace.get(trace_id) - - # Add 1 to account for the wrapping span - assert len(trace.observations) == 3 - - generations = list(filter(lambda x: x.type == "GENERATION", trace.observations)) - assert len(generations) == 1 - - for generation in generations: - assert generation.input is not None - assert generation.output is not None - assert generation.input != "" - assert generation.output != "" - assert generation.usage_details["total"] is not None - assert generation.usage_details["input"] is not None - assert generation.usage_details["output"] is not None - - def test_callback_simple_openai(): langfuse = Langfuse() @@ -343,253 +242,6 @@ def test_callback_multiple_invocations_on_different_traces(): assert generation.output != "" -def test_callback_openai_functions_python(): - langfuse = Langfuse() - - with langfuse.start_as_current_span(name="openai_functions_python_test") as span: - trace_id = span.trace_id - handler = CallbackHandler() - - llm = ChatOpenAI(model="gpt-4", temperature=0) - prompt = ChatPromptTemplate.from_messages( - [ - ( - "system", - "You are a world class algorithm for extracting information in structured formats.", - ), - ( - "human", - "Use the given format to extract information from the following input: {input}", - ), - ("human", "Tip: Make sure to answer in the correct format"), - ] - ) - - class OptionalFavFood(BaseModel): - """Either a food or null.""" - - food: Optional[str] = Field( - None, - description="Either the name of a food or null. Should be null if the food isn't known.", - ) - - def record_person(name: str, age: int, fav_food: OptionalFavFood) -> str: - """Record some basic identifying information about a person. - - Args: - name: The person's name. - age: The person's age in years. - fav_food: An OptionalFavFood object that either contains the person's favorite food or a null value. - Food should be null if it's not known. - """ - return f"Recording person {name} of age {age} with favorite food {fav_food.food}!" - - def record_dog(name: str, color: str, fav_food: OptionalFavFood) -> str: - """Record some basic identifying information about a dog. - - Args: - name: The dog's name. - color: The dog's color. - fav_food: An OptionalFavFood object that either contains the dog's favorite food or a null value. - Food should be null if it's not known. - """ - return ( - f"Recording dog {name} of color {color} with favorite food {fav_food}!" - ) - - chain = create_openai_fn_chain( - [record_person, record_dog], llm, prompt, callbacks=[handler] - ) - chain.run( - "I can't find my dog Henry anywhere, he's a small brown beagle. Could you send a message about him?", - callbacks=[handler], - ) - - handler.client.flush() - - trace = get_api().trace.get(trace_id) - - # Add 1 to account for the wrapping span - assert len(trace.observations) == 3 - - generations = list(filter(lambda x: x.type == "GENERATION", trace.observations)) - assert len(generations) > 0 - - for generation in generations: - assert generation.input is not None - assert generation.output is not None - assert generation.input == [ - { - "role": "system", - "content": "You are a world class algorithm for extracting information in structured formats.", - }, - { - "role": "user", - "content": "Use the given format to extract information from the following input: I can't find my dog Henry anywhere, he's a small brown beagle. Could you send a message about him?", - }, - { - "role": "user", - "content": "Tip: Make sure to answer in the correct format", - }, - ] - assert generation.output == { - "role": "assistant", - "content": "", - "additional_kwargs": { - "function_call": { - "arguments": '{\n "name": "Henry",\n "color": "brown",\n "fav_food": {\n "food": null\n }\n}', - "name": "record_dog", - }, - "refusal": None, - }, - } - assert generation.usage_details["total"] is not None - assert generation.usage_details["input"] is not None - assert generation.usage_details["output"] is not None - - -def test_agent_executor_chain(): - langfuse = Langfuse() - - with langfuse.start_as_current_span(name="agent_executor_chain_test") as span: - trace_id = span.trace_id - from langchain.agents import AgentExecutor, create_react_agent - from langchain.tools import tool - - prompt = PromptTemplate.from_template(""" - Answer the following questions as best you can. You have access to the following tools: - - {tools} - - Use the following format: - - Question: the input question you must answer - Thought: you should always think about what to do - Action: the action to take, should be one of [{tool_names}] - Action Input: the input to the action - Observation: the result of the action - ... (this Thought/Action/Action Input/Observation can repeat N times) - Thought: I now know the final answer - Final Answer: the final answer to the original input question - - Begin! - - Question: {input} - Thought:{agent_scratchpad} - """) - - callback = CallbackHandler() - llm = OpenAI(temperature=0) - - @tool - def get_word_length(word: str) -> int: - """Returns the length of a word.""" - return len(word) - - tools = [get_word_length] - agent = create_react_agent(llm, tools, prompt) - agent_executor = AgentExecutor( - agent=agent, tools=tools, handle_parsing_errors=True - ) - - agent_executor.invoke( - {"input": "what is the length of the word LangFuse?"}, - config={"callbacks": [callback]}, - ) - - callback.client.flush() - - trace = get_api().trace.get(trace_id) - - generations = list(filter(lambda x: x.type == "GENERATION", trace.observations)) - assert len(generations) > 0 - - for generation in generations: - assert generation.input is not None - assert generation.output is not None - assert generation.input != "" - assert generation.output != "" - assert generation.usage_details["total"] is not None - assert generation.usage_details["input"] is not None - assert generation.usage_details["output"] is not None - - -def test_unimplemented_model(): - langfuse = Langfuse() - - with langfuse.start_as_current_span(name="unimplemented_model_test") as span: - trace_id = span.trace_id - callback = CallbackHandler() - - class CustomLLM(LLM): - n: int - - @property - def _llm_type(self) -> str: - return "custom" - - def _call( - self, - prompt: str, - stop: Optional[List[str]] = None, - run_manager: Optional[CallbackManagerForLLMRun] = None, - **kwargs: Any, - ) -> str: - if stop is not None: - raise ValueError("stop kwargs are not permitted.") - return "This is a great text, which i can take characters from "[ - : self.n - ] - - @property - def _identifying_params(self) -> Mapping[str, Any]: - """Get the identifying parameters.""" - return {"n": self.n} - - custom_llm = CustomLLM(n=10) - - llm = OpenAI(openai_api_key=os.environ.get("OPENAI_API_KEY")) - template = """You are a playwright. Given the title of play, it is your job to write a synopsis for that title. - Title: {title} - Playwright: This is a synopsis for the above play:""" - - prompt_template = PromptTemplate(input_variables=["title"], template=template) - synopsis_chain = LLMChain(llm=llm, prompt=prompt_template) - - template = """You are a play critic from the New York Times. - Given the synopsis of play, it is your job to write a review for that play. - - Play Synopsis: - {synopsis} - Review from a New York Times play critic of the above play:""" - prompt_template = PromptTemplate( - input_variables=["synopsis"], template=template - ) - custom_llm_chain = LLMChain(llm=custom_llm, prompt=prompt_template) - - sequential_chain = SimpleSequentialChain( - chains=[custom_llm_chain, synopsis_chain] - ) - sequential_chain.run("This is a foobar thing", callbacks=[callback]) - - callback.client.flush() - - trace = get_api().trace.get(trace_id) - - # Add 1 to account for the wrapping span - assert len(trace.observations) == 6 - - custom_generation = list( - filter( - lambda x: x.type == "GENERATION" and x.name == "CustomLLM", - trace.observations, - ) - )[0] - - assert custom_generation.output == "This is a" - assert custom_generation.model is None - - def test_openai_instruct_usage(): langfuse = Langfuse() @@ -1343,92 +995,3 @@ def test_cached_token_usage(): ) < 0.0001 ) - - -def test_langchain_automatic_observation_types(): - """Test that LangChain components automatically get correct observation types: - AGENT, TOOL, GENERATION, RETRIEVER, CHAIN - """ - langfuse = Langfuse() - - with langfuse.start_as_current_span(name="observation_types_test_agent") as span: - trace_id = span.trace_id - handler = CallbackHandler() - - from langchain.agents import AgentExecutor, create_react_agent - from langchain.tools import tool - - # for type TOOL - @tool - def test_tool(x: str) -> str: - """Process input string.""" - return f"processed {x}" - - # for type GENERATION - llm = ChatOpenAI(temperature=0) - tools = [test_tool] - - prompt = PromptTemplate.from_template(""" - Answer: {input} - - Tools: {tools} - Tool names: {tool_names} - - Question: {input} - {agent_scratchpad} - """) - - # for type AGENT - agent = create_react_agent(llm, tools, prompt) - agent_executor = AgentExecutor( - agent=agent, tools=tools, handle_parsing_errors=True, max_iterations=1 - ) - - try: - agent_executor.invoke({"input": "hello"}, {"callbacks": [handler]}) - except Exception: - pass - - try: - test_tool.invoke("simple input", {"callbacks": [handler]}) - except Exception: - pass - - from langchain_core.prompts import PromptTemplate as CorePromptTemplate - - # for type CHAIN - chain_prompt = CorePromptTemplate.from_template("Answer: {question}") - simple_chain = chain_prompt | llm - - try: - simple_chain.invoke({"question": "hi"}, {"callbacks": [handler]}) - except Exception: - pass - - # for type RETRIEVER - from langchain_core.documents import Document - from langchain_core.retrievers import BaseRetriever - - class SimpleRetriever(BaseRetriever): - def _get_relevant_documents(self, query: str, *, run_manager): - return [Document(page_content="test doc")] - - try: - SimpleRetriever().invoke("query", {"callbacks": [handler]}) - except Exception: - pass - - handler.client.flush() - trace = get_api().trace.get(trace_id) - - # Validate all expected observation types are created - types_found = {obs.type for obs in trace.observations} - expected_types = {"AGENT", "TOOL", "CHAIN", "RETRIEVER", "GENERATION"} - - for obs_type in expected_types: - obs_count = len([obs for obs in trace.observations if obs.type == obs_type]) - assert obs_count > 0, f"Expected {obs_type} observations, found {obs_count}" - - assert expected_types.issubset( - types_found - ), f"Missing types: {expected_types - types_found}" diff --git a/tests/test_langchain_integration.py b/tests/test_langchain_integration.py index c45ec98e0..599860b50 100644 --- a/tests/test_langchain_integration.py +++ b/tests/test_langchain_integration.py @@ -1,8 +1,8 @@ import types import pytest -from langchain.prompts import ChatPromptTemplate, PromptTemplate -from langchain.schema import StrOutputParser +from langchain_core.output_parsers import StrOutputParser +from langchain_core.prompts import ChatPromptTemplate, PromptTemplate from langchain_openai import ChatOpenAI, OpenAI from langfuse import Langfuse diff --git a/tests/test_prompt_compilation.py b/tests/test_prompt_compilation.py index 10a4cd990..039556c5d 100644 --- a/tests/test_prompt_compilation.py +++ b/tests/test_prompt_compilation.py @@ -1,5 +1,5 @@ import pytest -from langchain.prompts import ChatPromptTemplate, PromptTemplate +from langchain_core.prompts import ChatPromptTemplate, PromptTemplate from langfuse.api.resources.prompts import ChatMessage, Prompt_Chat from langfuse.model import ( From d6a54b1db33ada09c16c663cbea94b9380368f57 Mon Sep 17 00:00:00 2001 From: Hassieb Pakzad <68423100+hassiebp@users.noreply.github.com> Date: Mon, 20 Oct 2025 15:12:39 +0200 Subject: [PATCH 2/5] push --- tests/test_json.py | 3 ++- 1 file changed, 2 insertions(+), 1 deletion(-) diff --git a/tests/test_json.py b/tests/test_json.py index f231bb97a..26b6919fa 100644 --- a/tests/test_json.py +++ b/tests/test_json.py @@ -31,8 +31,9 @@ def test_json_encoder(): } result = json.dumps(obj, cls=EventSerializer) + print(result) assert ( - '{"foo": "bar", "bar": "2021-01-01T00:00:00Z", "date": "2024-01-01", "messages": [{"content": "I love programming!", "additional_kwargs": {}, "response_metadata": {}, "type": "human", "name": null, "id": null, "example": false}]}' + '{"foo": "bar", "bar": "2021-01-01T00:00:00Z", "date": "2024-01-01", "messages": [{"content": "I love programming!", "additional_kwargs": {}, "response_metadata": {}, "type": "human", "name": null, "id": null}]}' in result ) From bc26f7cdd0db4404f859f846c0b0da7681bb95d0 Mon Sep 17 00:00:00 2001 From: Hassieb Pakzad <68423100+hassiebp@users.noreply.github.com> Date: Mon, 20 Oct 2025 15:17:21 +0200 Subject: [PATCH 3/5] push --- .pre-commit-config.yaml | 2 +- langfuse/_client/client.py | 4 +--- 2 files changed, 2 insertions(+), 4 deletions(-) diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml index 45f88c352..59073b603 100644 --- a/.pre-commit-config.yaml +++ b/.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: diff --git a/langfuse/_client/client.py b/langfuse/_client/client.py index d0f946547..09610567d 100644 --- a/langfuse/_client/client.py +++ b/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) ) From 85d411bf1132cb84e4990990aa5e28ea451a355a Mon Sep 17 00:00:00 2001 From: Hassieb Pakzad <68423100+hassiebp@users.noreply.github.com> Date: Mon, 20 Oct 2025 15:20:21 +0200 Subject: [PATCH 4/5] push --- .github/workflows/ci.yml | 5 +++-- pyproject.toml | 4 ---- 2 files changed, 3 insertions(+), 6 deletions(-) diff --git a/.github/workflows/ci.yml b/.github/workflows/ci.yml index 1e1ae37f7..1b8e0a83e 100644 --- a/.github/workflows/ci.yml +++ b/.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: diff --git a/pyproject.toml b/pyproject.toml index a3ac04c3a..2f622a5d1 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -37,10 +37,6 @@ autoevals = "^0.0.130" [tool.poetry.group.docs.dependencies] pdoc = "^15.0.4" -[tool.poetry.extras] -openai = ["openai"] -langchain = ["langchain"] - [build-system] requires = ["poetry-core>=1.0.0"] build-backend = "poetry.core.masonry.api" From abe7f70d2e422a3410b7474f822d3bc385e8fe3d Mon Sep 17 00:00:00 2001 From: Hassieb Pakzad <68423100+hassiebp@users.noreply.github.com> Date: Mon, 20 Oct 2025 15:35:18 +0200 Subject: [PATCH 5/5] push --- poetry.lock | 12 ++++-------- 1 file changed, 4 insertions(+), 8 deletions(-) diff --git a/poetry.lock b/poetry.lock index c06d82f1c..51f812200 100644 --- a/poetry.lock +++ b/poetry.lock @@ -642,13 +642,13 @@ referencing = ">=0.31.0" [[package]] name = "langchain" -version = "1.0.0" +version = "1.0.1" description = "Building applications with LLMs through composability" optional = false python-versions = "<4.0.0,>=3.10.0" files = [ - {file = "langchain-1.0.0-py3-none-any.whl", hash = "sha256:8c95e41250fc86d09a978fbdf999f86c18d50a28a2addc5da88546af00a1ad15"}, - {file = "langchain-1.0.0.tar.gz", hash = "sha256:56bf90d935ac1dda864519372d195ca58757b755dd4c44b87840b67d069085b7"}, + {file = "langchain-1.0.1-py3-none-any.whl", hash = "sha256:48fd616413fee4843f12cad49e8b74ad6fc159640142ca885d03bd925cd24503"}, + {file = "langchain-1.0.1.tar.gz", hash = "sha256:8bf60e096ca9c06626d9161a46651405ef1d12b5863f7679283666f83f760dc5"}, ] [package.dependencies] @@ -2752,11 +2752,7 @@ files = [ [package.extras] cffi = ["cffi (>=1.17,<2.0)", "cffi (>=2.0.0b)"] -[extras] -langchain = [] -openai = ["openai"] - [metadata] lock-version = "2.0" python-versions = ">=3.10,<4.0" -content-hash = "0022ae33f0a583a079753fb6ebc93c3178a44bcc7d9ba8e73397fbc8be2bafed" +content-hash = "cfda3b10ea654d3aa01a0d4292631380b85dcaa982e726b6e6f575f15d9a22da"