From 4e607c800d7d51f8493be1e717b7310f788de8ee Mon Sep 17 00:00:00 2001 From: Adam Wright Date: Wed, 9 Sep 2026 18:48:51 +0000 Subject: [PATCH 1/2] Upgrade to LangChain 1.x The upgrade the retriever rewrite existed to unblock. 69 advisories down to 44; the whole LangChain family is now clean. langchain 0.3.30 -> 1.4.0 langchain-core 0.3.86 -> 1.6.2 langchain-openai 0.2.14 -> 1.6.1 langgraph 0.2.76 -> 1.2.11 langgraph-checkpoint 2.1.2 -> 4.2.0 openai 1.109 -> 2.54.0 ragas 0.2.15 -> 0.4.3 Three things did NOT move, each for a reason. chromadb stays below 1.0, and langchain-chroma at 0.2.x with it. langchain-chroma 1.x requires chromadb>=1.3.5, and chromadb 1.x opens a 0.5/0.6 bundle by migrating its sqlite sysdb in place (9 -> 10), which needs write access to the bundle. Installed bundles are root-owned 755, so running as a normal user gives InternalError: error returned from database: (code: 8) attempt to write a readonly database at startup, before a single question. That is a deliberate operational step -- chown every bundle on every host -- not something to slip into a dependency upgrade. The migration itself is sound: chromadb 1.5.9 reads a 0.6-written bundle, and 0.6.3 still reads it afterwards, so a rollback does not strand the data. langchain-chroma 0.2.3 declares langchain-core>=0.3.52 with no upper bound and was verified to run against core 1.6.2 through the full chain. langchain-community stays at 0.3.31. 0.4 drops langchain_community.chat_models.vertexai, which ragas 0.4.3 still imports unconditionally, so 0.4 makes `import ragas` fail and takes ./bin/evaluate with it. ragas declares langchain-community with no version bound, so the resolver cannot see it; only importing can. 0.3.31 accepts langchain-core <2.0.0. torch and transformers stay as they were, per the previous upgrade. Code changes the upgrade forced: - langchain.chains.* moved to langchain-classic, which is their supported home rather than a shim. Rewriting the RAG chain as LCEL is a behaviour change and does not belong here. - langgraph.utils.runnable.RunnableLike is gone, and langgraph 1.0's add_node matches nodes structurally on the parameter name `state`. The node contract is now a Protocol in this repository, and no_search's parameter is named rather than `_`. - EnsembleRetriever now validates len(weights) == len(retrievers), so the empty-ensemble trick used to reach weighted_reciprocal_rank raises. That trick was removed from the pipeline by the rewrite and survived only in the test comparing against it -- the upgrade breaking it is the argument for the rewrite, restated. The vendored RRF still matches LangChain 1.x exactly, over 2000 random inputs. - ragas 0.4 types evaluate() as EvaluationResult | Executor; checked rather than cast, so a future default change says so. Two bugs found while doing it: - AgentGraph.__del__ read self.pool, which does not exist when __init__ raised part way through. A chromadb startup error therefore surfaced as "AttributeError: 'AgentGraph' object has no attribute 'pool'" while the real cause went unprinted. - test_the_vector_side_makes_no_llm_call asserted on the literal string "from langchain.retrievers.self_query". Under 1.x that path is langchain_classic.retrievers.self_query, so the test would have gone green while the thing it guards was reintroduced. It now matches import lines on the module tail. src/evaluation/test_generator.py is deleted. It targeted the ragas 0.1 API -- from_langchain(generator_llm=, critic_llm=), generate_with_langchain_docs(test_size=, distributions=) -- none of which exists in 0.4, its own TODO had said so since 0.2, and nothing imported it. It had not run for three major versions. Measured, not assumed: bin/retrieval_baseline before and after over 20 questions x 4 collections x 2 retrievers shows 2/160 results changed, both adjacent transpositions on the vector side, which is the run-to-run ANN variance the harness already documents (plain vector is byte-identical on 78/80 between two identical runs). BM25 is unchanged. The chainlit app imports and registers its hooks; the chain answers a real question through both invoke and ainvoke. --- bin/retrieval_baseline | 2 +- poetry.lock | 1401 +++++++++-------- pyproject.toml | 65 +- src/agent/graph.py | 7 +- src/evaluation/README.md | 16 +- src/evaluation/evaluator.py | 12 +- src/evaluation/test_generator.py | 125 -- src/retrievers/plantreactome/metadata_info.py | 2 +- src/retrievers/rag_chain.py | 8 +- src/retrievers/reactome/metadata_info.py | 2 +- src/retrievers/uniprot/metadata_info.py | 2 +- src/tools/external_search/workflow.py | 22 +- tests/agent/test_graph.py | 18 + tests/retrievers/test_hybrid_retriever.py | 16 +- tests/retrievers/test_rrf_equivalence.py | 31 +- 15 files changed, 913 insertions(+), 816 deletions(-) delete mode 100644 src/evaluation/test_generator.py create mode 100644 tests/agent/test_graph.py diff --git a/bin/retrieval_baseline b/bin/retrieval_baseline index 124dbd15..8763dcda 100755 --- a/bin/retrieval_baseline +++ b/bin/retrieval_baseline @@ -30,7 +30,7 @@ from typing import Any import nltk from dotenv import load_dotenv -from langchain.retrievers.self_query.base import SelfQueryRetriever +from langchain_classic.retrievers.self_query.base import SelfQueryRetriever from langchain_chroma.vectorstores import Chroma from langchain_community.document_loaders.csv_loader import CSVLoader from langchain_community.retrievers import BM25Retriever diff --git a/poetry.lock b/poetry.lock index 1ef3a9d1..ebea7dcd 100644 --- a/poetry.lock +++ b/poetry.lock @@ -1149,43 +1149,44 @@ typing-inspect = ">=0.4.0,<1" [[package]] name = "datasets" -version = "3.6.0" +version = "4.8.5" description = "HuggingFace community-driven open-source library of datasets" optional = false -python-versions = ">=3.9.0" +python-versions = ">=3.10.0" files = [ - {file = "datasets-3.6.0-py3-none-any.whl", hash = "sha256:25000c4a2c0873a710df127d08a202a06eab7bf42441a6bc278b499c2f72cd1b"}, - {file = "datasets-3.6.0.tar.gz", hash = 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"sha256:db234eda965dcce15df96bb9709f587cd87d4d52aaf0e80e2f34ec04c7670c57"}, ] [[package]] @@ -8655,4 +8766,4 @@ cffi = ["cffi (>=1.17,<2.0)", "cffi (>=2.0.0b)"] [metadata] lock-version = "2.0" python-versions = ">=3.12, <4" -content-hash = "7c8f16a6f7114ec51772ce180f492d5c3dfe0b5b0f7cffadc3d9e1825f035da3" +content-hash = "23db7f946303db261f877a5d1c34f936275381a999e7632978bf8dec1df052dd" diff --git a/pyproject.toml b/pyproject.toml index 75f8296f..4a07cb9b 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -14,34 +14,50 @@ packages = [ #lark is needed for langchain -> SelfQueryRetriever [tool.poetry.dependencies] python = ">=3.12, <4" -langchain = "^0.3.4" -openai = "^1.12.0" -chromadb = "<1.0" -# Capped, and coupled to the chromadb pin above. chromadb 0.6 calls -# posthog.capture(user_id, name, properties) positionally; posthog 6 changed the -# signature to capture(event, **kwargs), so every telemetry call raises and -# chromadb logs it at ERROR: +langchain = "^1.4.0" +# 2.x, required by langchain-openai 1.x (openai>=2.45). Used directly only by +# bin/probe_model_temperature, for models.list(). +openai = "^2.45.0" +# Held below 1.0, and langchain-chroma below 1.0 with it. chromadb 1.x opens a +# 0.5/0.6 bundle by migrating its sqlite sysdb in place (9 -> 10), which needs +# write access to the bundle directory. Installed bundles here are root-owned +# 755, so every developer running as themselves gets # -# Failed to send telemetry event ClientCreateCollectionEvent: -# capture() takes 1 positional argument but 3 were given +# InternalError: error returned from database: (code: 8) +# attempt to write a readonly database # -# Nothing breaks -- telemetry is off anyway (anonymized_telemetry=False in -# csv_chroma.chroma_settings) -- but it puts several meaningless ERROR lines in -# the log on every startup and every collection open, and an error log nobody -# can act on is one people learn to skip. Lift this with the chromadb 1.x move. +# at startup, before a single question. Migrating is a deliberate operational +# step -- chown every bundle on every host -- not something to slip into a +# dependency upgrade. (The migration itself is sound: verified that chromadb +# 1.5.9 reads a 0.6-written bundle and that 0.6.3 still reads it afterwards, so +# a rollback does not strand the data.) +chromadb = "<1.0" +# chromadb 0.6 calls posthog.capture() positionally; posthog 6 changed the +# signature, so every telemetry call fails and chromadb logs it at ERROR. +# Telemetry is off anyway; this is purely to keep the log readable. posthog = "<6" pandas = "^2.2.1" pyasn1 = "^0.6.4" -langchain-openai = "^0.2.3" +langchain-openai = "^1.6.1" neo4j = "4.3.6" python-dotenv = "^1.0.1" pyfiglet = "^1.0.2" chainlit = "^2.0.3" asyncpg = "^0.30.0" sqlalchemy = "^2.0.30" -langchain-community = "^0.3.3" -langchain-core = "^0.3.13" -langchain-huggingface = "^0.1.0" +# Held at 0.3 deliberately. 0.4 requires langchain-classic and drops +# langchain_community.chat_models.vertexai -- which ragas 0.4.3 still imports +# unconditionally at ragas/llms/base.py:12, so langchain-community 0.4 makes +# `import ragas` a ModuleNotFoundError and takes ./bin/evaluate with it. ragas +# declares langchain-community with no version bound, so the resolver cannot +# see the conflict; only importing it does. +# +# 0.3.31 accepts langchain-core <2.0.0,>=0.3.78, so it runs against core 1.x. +# The app uses it for BM25Retriever, the CSV/directory loaders and +# OpenAICallbackHandler. Lift when ragas stops importing the vertexai module. +langchain-community = "^0.3.31" +langchain-core = "^1.6.2" +langchain-huggingface = "^1.2.2" # Capped, and coupled to the torch pin below. transformers 5 requires torch>=2.5 # and, finding 2.4.1, disables PyTorch entirely rather than failing: # @@ -59,11 +75,14 @@ torch = [ { version = "2.4.1+cpu", markers = "sys_platform == 'linux' and platform_machine == 'x86_64'", source = "pytorch_cpu" }, { version = "2.2.*", markers = "sys_platform != 'linux' or platform_machine != 'x86_64'", source = "PyPI" }, ] -langchain-chroma = "0.2.3" -langchain-ollama = "^0.2.0" +# 0.2.x, because 1.x requires chromadb>=1.3.5 -- see the chromadb note above. +# 0.2.3 declares langchain-core>=0.3.52 with no upper bound, so it runs against +# core 1.x. +langchain-chroma = "^0.2.3" +langchain-ollama = "^1.1.0" lark = "^1.2.2" -langgraph = "^0.2.39" -langgraph-checkpoint-postgres = "^2.0.2" +langgraph = "^1.2.11" +langgraph-checkpoint-postgres = "^3.1.2" rank-bm25 = "^0.2.2" psycopg = {extras = ["binary"], version = "^3.2.3"} pydantic = "^2.10.5" @@ -92,8 +111,8 @@ mypy = "^1.13.0" pandas-stubs = "^2.2.3.241009" types-requests = "^2.32.0.20241016" types-pyyaml = "^6.0.12.20241230" -datasets = "^3.2.0" -ragas = "^0.2.11" +datasets = "^4.0.0" +ragas = "^0.4.3" [[tool.poetry.source]] name = "PyPI" diff --git a/src/agent/graph.py b/src/agent/graph.py index 59e94da0..7716f539 100644 --- a/src/agent/graph.py +++ b/src/agent/graph.py @@ -186,7 +186,12 @@ def __del__(self) -> None: there is. The real fix is an explicit lifecycle -- close the pool from the application's shutdown hook -- which belongs with the agent-API work. """ - if self.pool is None: + # getattr, not self.pool: __del__ runs even when __init__ raised part + # way through, and then the attribute does not exist yet. That turned a + # readable startup error into "AttributeError: 'AgentGraph' object has no + # attribute 'pool'" printed from __del__, which is where the real cause + # went missing. + if getattr(self, "pool", None) is None: return try: asyncio.get_running_loop() diff --git a/src/evaluation/README.md b/src/evaluation/README.md index cf8097e9..d34abc64 100644 --- a/src/evaluation/README.md +++ b/src/evaluation/README.md @@ -5,10 +5,18 @@ Scores the answers the chatbot actually gives. - `evaluator.py` (run it as `./bin/evaluate`) asks the **shipping RAG chain** a set of questions and scores the answers with ragas: faithfulness, answer relevancy, context utilization, and context recall when reference answers are supplied. -- `test_generator.py` synthesizes question/answer sets from the example corpora. - **It targets the ragas 0.1 API and does not run against the pinned 0.2** — see - the TODO in the file. `tests/golden/questions.txt` is what the evaluator uses by - default and needs no generation. +`test_generator.py` used to sit beside it and was **deleted** in the LangChain 1.x +upgrade. It targeted the ragas 0.1 API — `from_langchain(generator_llm=, +critic_llm=)`, `generate_with_langchain_docs(test_size=, distributions=)` — none +of which exists in the pinned 0.4, and its own TODO had said so since 0.2. It was +not a port away from working; it had not run for three major versions, and +nothing imported it. `git log -- src/evaluation/test_generator.py` has it. + +Generating reference answers is still worth having — it is what would let +`context_recall` run. Rebuilding it against the current ragas synthesizer API is +a real piece of work, not a rename, and belongs with whoever wants that metric. +`tests/golden/questions.txt` is what the evaluator uses by default and needs no +generation. ## What changed, and why the old flags are gone diff --git a/src/evaluation/evaluator.py b/src/evaluation/evaluator.py index 4cd7ce30..876c779e 100644 --- a/src/evaluation/evaluator.py +++ b/src/evaluation/evaluator.py @@ -38,6 +38,7 @@ from dotenv import load_dotenv from langchain_core.language_models.chat_models import BaseChatModel from ragas import EvaluationDataset, SingleTurnSample, evaluate +from ragas.dataset_schema import EvaluationResult, MultiTurnSample from ragas.embeddings import LangchainEmbeddingsWrapper from ragas.llms import LangchainLLMWrapper from ragas.metrics import ( @@ -174,7 +175,7 @@ def score( ) ) - samples = [ + samples: list[SingleTurnSample | MultiTurnSample] = [ SingleTurnSample( user_input=q, response=a, @@ -200,6 +201,15 @@ def score( llm=judge_llm, embeddings=judge_embeddings, ) + # ragas 0.4 types evaluate() as EvaluationResult | Executor; it returns an + # Executor only when asked to run asynchronously, which this does not do. + # Checked rather than cast, so a future ragas that changes the default says + # so here instead of failing on the next line with an AttributeError. + if not isinstance(result, EvaluationResult): + raise TypeError( + f"ragas returned {type(result).__name__}, not EvaluationResult. " + "evaluate() now defers by default; this tool expects a completed run." + ) # result.scores is a public field holding one dict of metric -> score per # sample. The aggregate used to come from result._repr_dict, which is private # and would break on a ragas upgrade without warning -- in a file whose whole diff --git a/src/evaluation/test_generator.py b/src/evaluation/test_generator.py deleted file mode 100644 index bd954eca..00000000 --- a/src/evaluation/test_generator.py +++ /dev/null @@ -1,125 +0,0 @@ -import argparse -import os -from typing import Any - -import pandas as pd -from dotenv import load_dotenv -from langchain_community.document_loaders import DirectoryLoader -from langchain_openai import ChatOpenAI, OpenAIEmbeddings -from ragas.testset.synthesizers.generate import TestsetGenerator - - -def parse_arguments() -> argparse.Namespace: - parser = argparse.ArgumentParser( - description="Generate a test set based on given documents and distributions." - ) - parser.add_argument( - "--path", - type=str, - required=True, - help="Path to the directory containing example files", - ) - parser.add_argument( - "--model", - type=str, - default="gpt-4-turbo", - help="Language model to use (default: gpt-4-turbo)", - ) - parser.add_argument( - "--temperature", - type=float, - default=0.3, - help="Temperature setting for the language model (default: 0.3)", - ) - parser.add_argument( - "--test_size", - type=int, - default=4, - help="Number of tests to generate (default: 4)", - ) - parser.add_argument( - "--distributions", - type=str, - nargs="+", - help="Distributions of test types (e.g., simple=0.25 reasoning=0.25 multi_context=0.25 conditional=0.25)", - ) - - return parser.parse_args() - - -def save_testset(testset: Any, filename: str) -> None: - output_dir = "testsets" - os.makedirs(output_dir, exist_ok=True) - output_path = os.path.join(output_dir, f"{filename}_testset.xlsx") - - # Convert testset to DataFrame for filtering - df = pd.DataFrame(testset) - - # Filter out rows where "ground_truth" is "The answer to given question is not present in context" - filtered_df = df[ - df["ground_truth"] != "The answer to given question is not present in context" - ] - - # Save the filtered DataFrame to an Excel file - filtered_df.to_excel(output_path, index=False) - - print(f"Filtered testset saved to {output_path}") - - -def main() -> None: - try: - # Load environment variables - load_dotenv() - - # Parse command line arguments - args = parse_arguments() - - # Setup document loader - loader = DirectoryLoader(args.path) - documents = loader.load() - - # Initialize Language Models and Embeddings - llm = ChatOpenAI(model=args.model, temperature=args.temperature) - embeddings = OpenAIEmbeddings() - - # Parse test type distributions - # TODO: this targets the ragas 0.1 API. `distributions` took evolution - # objects (simple, reasoning, multi_context, conditional) imported from - # ragas.testset.evolutions, which 0.2 replaced with synthesizers, and the - # generate_with_langchain_docs keyword changed too. The names were - # previously resolved with eval() on argv -- removed here because that - # executes arbitrary input, and because those names are not imported, so - # it raised NameError rather than working. Porting this to 0.2 needs the - # current ragas API. - distributions: dict[str, float] = {} - for dist in args.distributions: - key, sep, value = dist.partition("=") - if not sep: - raise SystemExit( - f"Malformed --distributions entry {dist!r}; use name=weight" - ) - distributions[key] = float(value) - - # Setup and run test set generator - generator = TestsetGenerator.from_langchain( - generator_llm=llm, critic_llm=llm, embeddings=embeddings - ) - testset = generator.generate_with_langchain_docs( - documents, test_size=args.test_size, distributions=distributions - ) - - # Save the output - base_filename = os.path.basename(args.path).split(".")[ - 0 - ] # Assumes files have an extension - output_dir = f"{base_filename}_testset" - save_testset(testset, output_dir) - except Exception as e: - print(f"An error occurred: {e}") - - -if __name__ == "__main__": - main() - - -## python your_script.py --path "/evaluation/example_files/" --model "gpt-4-turbo" --temperature 0.3 --test_size 4 --distributions simple=0.25 reasoning=0.25 multi_context=0.25 conditional=0.25 diff --git a/src/retrievers/plantreactome/metadata_info.py b/src/retrievers/plantreactome/metadata_info.py index 3ff6b246..330fdeee 100644 --- a/src/retrievers/plantreactome/metadata_info.py +++ b/src/retrievers/plantreactome/metadata_info.py @@ -1,4 +1,4 @@ -from langchain.chains.query_constructor.base import AttributeInfo +from langchain_classic.chains.query_constructor.schema import AttributeInfo pathway_id_description = "A Plant Reactome Identifier unique to each pathway. A pathway name may appear multiple times in the dataset\ This ID allows for the specific identification and exploration of each pathway's details within the Plant Reactome Database." diff --git a/src/retrievers/rag_chain.py b/src/retrievers/rag_chain.py index 11c00518..091e6864 100644 --- a/src/retrievers/rag_chain.py +++ b/src/retrievers/rag_chain.py @@ -1,5 +1,9 @@ -from langchain.chains.combine_documents import create_stuff_documents_chain -from langchain.chains.retrieval import create_retrieval_chain +# langchain_classic, not langchain: LangChain 1.0 moved the pre-LCEL chain +# builders out of the core package into langchain-classic, which is their +# supported home rather than a deprecation shim. Rewriting this as LCEL is a +# behaviour change and does not belong in a dependency upgrade. +from langchain_classic.chains.combine_documents import create_stuff_documents_chain +from langchain_classic.chains.retrieval import create_retrieval_chain from langchain_core.language_models.chat_models import BaseChatModel from langchain_core.prompts import BasePromptTemplate, ChatPromptTemplate from langchain_core.retrievers import BaseRetriever diff --git a/src/retrievers/reactome/metadata_info.py b/src/retrievers/reactome/metadata_info.py index b9fd2516..fff4783e 100644 --- a/src/retrievers/reactome/metadata_info.py +++ b/src/retrievers/reactome/metadata_info.py @@ -1,4 +1,4 @@ -from langchain.chains.query_constructor.base import AttributeInfo +from langchain_classic.chains.query_constructor.schema import AttributeInfo pathway_id_description = "A Reactome Identifier unique to each pathway. A pathway name may appear multiple times in the dataset\ This ID allows for the specific identification and exploration of each pathway's details within the Reactome Database." diff --git a/src/retrievers/uniprot/metadata_info.py b/src/retrievers/uniprot/metadata_info.py index 0b7aa755..b35e8de5 100644 --- a/src/retrievers/uniprot/metadata_info.py +++ b/src/retrievers/uniprot/metadata_info.py @@ -1,4 +1,4 @@ -from langchain.chains.query_constructor.base import AttributeInfo +from langchain_classic.chains.query_constructor.schema import AttributeInfo uniprot_descriptions_info = { "uniprot_data": "Contains detailed protein information about gene names, protein names, subcellular localizations, family classifications, biological pathway associations, domains, motifs, disease associations, and functional descriptions. ", diff --git a/src/tools/external_search/workflow.py b/src/tools/external_search/workflow.py index 038a44d8..62703f9f 100644 --- a/src/tools/external_search/workflow.py +++ b/src/tools/external_search/workflow.py @@ -1,10 +1,9 @@ -from typing import Literal +from typing import Any, Literal, Protocol from langchain_core.language_models.chat_models import BaseChatModel from langchain_core.runnables import Runnable, RunnableConfig from langgraph.graph import StateGraph from langgraph.graph.state import CompiledStateGraph -from langgraph.utils.runnable import RunnableLike from agent.tasks.completeness_grader import ( CompletenessGrade, @@ -20,11 +19,26 @@ def decide_next_steps(state: SearchState) -> Literal["perform_web_search", "no_s return "no_search" -def no_search(_: SearchState) -> SearchState: +def no_search(state: SearchState) -> SearchState: return SearchState(search_results=[]) -def run_completeness_grader(grader: Runnable) -> RunnableLike: +class SearchNode(Protocol): + """The shape langgraph 1.0 requires of a graph node taking a config. + + Spelled out rather than imported. This was + `langgraph.utils.runnable.RunnableLike` -- a private module, and a union too + wide for langgraph 1.0's stricter `add_node`. + + It has to be a Protocol and not a Callable alias: langgraph matches nodes + structurally on the *parameter name* `state`, which a Callable alias cannot + express. That is also why `no_search` below takes `state` rather than `_`. + """ + + def __call__(self, state: SearchState, config: RunnableConfig) -> Any: ... + + +def run_completeness_grader(grader: Runnable) -> SearchNode: async def _run_completeness_grader( state: SearchState, config: RunnableConfig ) -> SearchState: diff --git a/tests/agent/test_graph.py b/tests/agent/test_graph.py new file mode 100644 index 00000000..3c91e157 --- /dev/null +++ b/tests/agent/test_graph.py @@ -0,0 +1,18 @@ +"""AgentGraph construction and teardown.""" + +import pytest + +pytest.importorskip("langgraph", reason="agent stack not installed") + +from agent.graph import AgentGraph # noqa: E402 + + +def test_agent_graph_del_survives_a_failed_init() -> None: + """__del__ must not raise when __init__ never finished. + + A chromadb error during __init__ left `pool` unset, and __del__ then raised + `AttributeError: 'AgentGraph' object has no attribute 'pool'` -- which is + what got printed, while the error that actually stopped startup did not. + """ + orphan = AgentGraph.__new__(AgentGraph) # __init__ deliberately not run + orphan.__del__() # must not raise diff --git a/tests/retrievers/test_hybrid_retriever.py b/tests/retrievers/test_hybrid_retriever.py index e5586aa9..b90a000f 100644 --- a/tests/retrievers/test_hybrid_retriever.py +++ b/tests/retrievers/test_hybrid_retriever.py @@ -216,11 +216,21 @@ def test_the_vector_side_makes_no_llm_call() -> None: would pass just as well against a cached or mocked LLM. """ source = Path(csv_chroma.__file__).read_text() - # Checks the import, not the word: the name still appears in a comment + # Checks imports, not the word: the name still appears in a comment # explaining what was replaced, and that comment is worth keeping. + # + # Matched on the module tail rather than the full path. LangChain 1.0 moved + # this to langchain_classic.retrievers.self_query, and a test pinned to + # "from langchain.retrievers.self_query" would have gone quietly green + # against the new path while claiming the vector side was still LLM-free. + imports = [ + line + for line in source.splitlines() + if line.startswith(("import ", "from ")) and "retrievers.self_query" in line + ] assert ( - "from langchain.retrievers.self_query" not in source - ), "the vector side must not reintroduce an LLM-backed retriever" + not imports + ), f"the vector side must not reintroduce an LLM-backed retriever: {imports}" assert "as_retriever(" in source, "plain similarity search is expected" diff --git a/tests/retrievers/test_rrf_equivalence.py b/tests/retrievers/test_rrf_equivalence.py index 0b5ebc75..3d45f90e 100644 --- a/tests/retrievers/test_rrf_equivalence.py +++ b/tests/retrievers/test_rrf_equivalence.py @@ -20,14 +20,37 @@ pytest.importorskip("langchain", reason="retrieval stack not installed") -from langchain.retrievers import EnsembleRetriever # noqa: E402 +from langchain_classic.retrievers import EnsembleRetriever # noqa: E402 +from langchain_core.retrievers import BaseRetriever # noqa: E402 pytestmark = pytest.mark.requires_retrieval_stack +class _NoopRetriever(BaseRetriever): + """Never invoked; it exists only to satisfy a length check. + + LangChain 1.0 made EnsembleRetriever validate that len(weights) equals + len(retrievers), so `EnsembleRetriever(retrievers=[], weights=[...])` -- the + empty-ensemble trick this repository used to reach `weighted_reciprocal_rank` + -- now raises. That trick was removed from the pipeline by the retriever + rewrite; it survived only here, in the test that compares against it. + + The upgrade breaking it is the argument for the rewrite, restated: the method + is public, but every route to it is not. + """ + + def _get_relevant_documents(self, query: str, **kwargs: object) -> list[Document]: + return [] + + +def _ensemble(n: int) -> EnsembleRetriever: + return EnsembleRetriever( + retrievers=[_NoopRetriever() for _ in range(n)], weights=[1 / n] * n + ) + + def _langchain_rrf(doc_lists: list[list[Document]]) -> list[str]: - n = len(doc_lists) - ensemble = EnsembleRetriever(retrievers=[], weights=[1 / n] * n) + ensemble = _ensemble(len(doc_lists)) return [d.page_content for d in ensemble.weighted_reciprocal_rank(doc_lists)] @@ -36,7 +59,7 @@ def _ours(doc_lists: list[list[Document]]) -> list[str]: def test_the_constant_matches_the_source_it_was_copied_from() -> None: - assert EnsembleRetriever(retrievers=[], weights=[1.0]).c == RRF_K + assert _ensemble(1).c == RRF_K @pytest.mark.parametrize("seed", range(25)) From 36c89e17e31504df1cae1e20885699ab308e5e66 Mon Sep 17 00:00:00 2001 From: Adam Wright Date: Wed, 9 Sep 2026 19:11:44 +0000 Subject: [PATCH 2/2] Declare langchain-classic and langchain-text-splitters CI could not import langchain_classic; locally everything passed. The package was in my virtualenv as a leftover from langchain-community 0.4, which was installed for a few minutes while working out that ragas could not tolerate it. `poetry install` does not prune, so it stayed -- and made code that imports langchain_classic directly look fine against a lock that never contained it. Both packages are imported by name here (rag_chain and the metadata_info modules; RecursiveCharacterTextSplitter in data_generation), so both are now direct dependencies. Declaring what you import is right regardless of how it used to arrive. Verified against a virtualenv synced to the lock with --sync, which removed twelve stale packages, including the two this commit adds back deliberately. Gates, the CI import check and the real chain all pass on that clean tree. --- poetry.lock | 55 +++++++++++++++++++++++++++++++++++++++++++++++++- pyproject.toml | 8 ++++++++ 2 files changed, 62 insertions(+), 1 deletion(-) diff --git a/poetry.lock b/poetry.lock index ebea7dcd..f7b92589 100644 --- a/poetry.lock +++ b/poetry.lock @@ -2392,6 +2392,45 @@ numpy = [ {version = ">=2.1.0", markers = "python_version >= \"3.13\""}, ] +[[package]] +name = "langchain-classic" +version = "1.0.8" +description = "Building applications with LLMs through composability" +optional = false +python-versions = "<4.0.0,>=3.10.0" +files = [ + {file = "langchain_classic-1.0.8-py3-none-any.whl", hash = "sha256:1a11ea7fbe630c4f2af2f3873d27718ceac9488cf32d0821030be7cf039a6213"}, + {file = "langchain_classic-1.0.8.tar.gz", hash = "sha256:ada0cc341a8a5b80fb24d73bdfaaeb849056ee2d8a41cc468355163fd3667484"}, +] + +[package.dependencies] +langchain-core = ">=1.4.4,<2.0.0" +langchain-text-splitters = ">=1.1.2,<2.0.0" +langsmith = ">=0.1.17,<1.0.0" +pydantic = ">=2.7.4,<3.0.0" +pyyaml = ">=5.3.0,<7.0.0" +requests = ">=2.0.0,<3.0.0" +sqlalchemy = ">=1.4.0,<3.0.0" + +[package.extras] +anthropic = ["langchain-anthropic"] +aws = ["langchain-aws"] +azure-ai = ["langchain-azure-ai"] +cohere = ["langchain-cohere"] +community = ["langchain-community"] +deepseek = ["langchain-deepseek"] +fireworks = ["langchain-fireworks"] +google-genai = ["langchain-google-genai"] +google-vertexai = ["langchain-google-vertexai"] +groq = ["langchain-groq"] +huggingface = ["langchain-huggingface"] +mistralai = ["langchain-mistralai"] +ollama = ["langchain-ollama"] +openai = ["langchain-openai"] +perplexity = ["langchain-perplexity"] +together = ["langchain-together"] +xai = ["langchain-xai"] + [[package]] name = "langchain-community" version = "0.3.31" @@ -2508,6 +2547,20 @@ files = [ [package.dependencies] typing-extensions = ">=4.13.0,<5.0.0" +[[package]] +name = "langchain-text-splitters" +version = "1.1.2" +description = "LangChain text splitting utilities" +optional = false +python-versions = "<4.0.0,>=3.10.0" +files = [ + {file = "langchain_text_splitters-1.1.2-py3-none-any.whl", hash = "sha256:a2de0d799ff31886429fd6e2e0032df275b60ec817c19059a7b46181cc1c2f10"}, + {file = "langchain_text_splitters-1.1.2.tar.gz", hash = "sha256:782a723db0a4746ac91e251c7c1d57fd23636e4f38ed733074e28d7a86f41627"}, +] + +[package.dependencies] +langchain-core = ">=1.2.31,<2.0.0" + [[package]] name = "langgraph" version = "1.2.11" @@ -8766,4 +8819,4 @@ cffi = ["cffi (>=1.17,<2.0)", "cffi (>=2.0.0b)"] [metadata] lock-version = "2.0" python-versions = ">=3.12, <4" -content-hash = "23db7f946303db261f877a5d1c34f936275381a999e7632978bf8dec1df052dd" +content-hash = "bea6f436e269885b6a20cba9e71881d67aef8df2b70e68416a71ede7eba71d6b" diff --git a/pyproject.toml b/pyproject.toml index 4a07cb9b..d7af2f5c 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -15,6 +15,14 @@ packages = [ [tool.poetry.dependencies] python = ">=3.12, <4" langchain = "^1.4.0" +# Declared, not inherited. LangChain 1.0 moved the pre-LCEL chain builders here +# (retrievers/rag_chain.py, the metadata_info modules), so this repository +# imports langchain_classic directly and must depend on it directly. It arrived +# transitively while langchain-community 0.4 was briefly installed, which is +# exactly why a stale virtualenv made the code look fine locally and CI did not. +langchain-classic = "^1.0.8" +# Same: data_generation imports RecursiveCharacterTextSplitter from it. +langchain-text-splitters = "^1.1.2" # 2.x, required by langchain-openai 1.x (openai>=2.45). Used directly only by # bin/probe_model_temperature, for models.list(). openai = "^2.45.0"