Build a fast, deterministic local test loop for LangChain 1.0 / LangGraph 1.0
— FakeListChatModel fixtures, pytest config, VCR cassettes with key redaction,
warning-filter policy. Use when adding tests to a new chain, fixing a flaky
test, or making integration tests reproducible.
Trigger with "langchain pytest", "FakeListChatModel", "VCR langchain",
"langchain test fixtures", "langchain integration test".
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Build a fast, deterministic local test loop for LangChain 1.0 / LangGraph 1.0
— FakeListChatModel fixtures, pytest config, VCR cassettes with key redaction,
warning-filter policy. Use when adding tests to a new chain, fixing a flaky
test, or making integration tests reproducible.
Trigger with "langchain pytest", "FakeListChatModel", "VCR langchain",
"langchain test fixtures", "langchain integration test".
An engineer writes the most natural assertion possible:
deftest_summarize():
out = chain.invoke({"text": "..."})
assert out.content == "expected summary"
It passes locally against Claude at temperature=0. It fails in CI on the third
run with a one-token delta in the output. That is P05: Anthropic's temperature=0
is not greedy — it still samples. Tests against live Claude are not deterministic,
period.
So the engineer swaps in FakeListChatModel(responses=["expected summary"]) and
the assertion passes. Then the downstream callback that logs cost blows up in CI
with KeyError: 'token_usage' — because FakeListChatModel does not emit
response_metadata["token_usage"] (P43). Production code reads that key, so
either the fake has to synthesize it or the test has to skip the callback.
Meanwhile, the first integration test under VCR records a cassette that ships
Authorization: Bearer sk-ant-api03-... in the repo (P44). PR review catches it;
the reviewer revokes the key; the dev loop is hosed for an afternoon.
And none of this matters if pytest cannot even collect the suite because
import langchain_community emits a DeprecationWarning that -W error promotes
to failure (P45).
This skill installs the four layers that make the whole loop fast and safe:
FakeListChatModel / FakeListLLM with a metadata-emitting subclass (fixes P43);
VCR with filter_headers plus a pre-commit hook (fixes P44); pytest
filterwarnings policy in pyproject.toml (fixes P45); and an env-var-gated
integration marker so the default pytest run never touches live APIs.
Speed targets: unit tests with FakeListChatModel run in < 100ms per
test; VCR-replayed integration tests run in 500ms – 2s per test; live
integration tests (the RUN_INTEGRATION=1 gate) run only in nightly or
manual workflows.
For integration tests: at least one provider key (ANTHROPIC_API_KEY, etc.)
Project uses pyproject.toml (PEP 621) for pytest config
Instructions
Step 1 — Deterministic unit tests with FakeListChatModel
Use FakeListChatModel from langchain_core.language_models.fake for chat
chains and FakeListLLM for legacy completion LLMs. Responses cycle through
the list.
from langchain_core.language_models.fake import FakeListChatModel
from langchain_core.prompts import ChatPromptTemplate
deftest_classifier_picks_positive():
fake = FakeListChatModel(responses=["positive"])
prompt = ChatPromptTemplate.from_messages([("user", "Classify: {text}")])
chain = prompt | fake
out = chain.invoke({"text": "I love it"})
assert out.content == "positive"
This is deterministic, runs in single-digit milliseconds, and has zero provider
dependency. Use it for every chain assertion that does not specifically require
real model behavior.
Step 2 — Subclass FakeListChatModel to emit response_metadata (P43 fix)
The stock fake emits no response_metadata["token_usage"]. If your chain has a
callback that records cost, the callback crashes under the fake. Subclass and
synthesize the metadata instead of mocking around the callback:
from langchain_core.language_models.fake import FakeListChatModel
from langchain_core.outputs import ChatGeneration, ChatResult
from langchain_core.messages import AIMessage
classFakeChatWithUsage(FakeListChatModel):
"""FakeListChatModel that emits response_metadata['token_usage'] so
downstream callbacks reading token usage do not crash under test."""def_generate(self, messages, stop=None, run_manager=None, **kwargs):
response = self.responses[self.i % len(self.responses)]
self.i += 1
message = AIMessage(
content=response,
response_metadata={
"token_usage": {
"input_tokens": 10,
"output_tokens": len(response.split()),
"total_tokens": 10 + len(response.split()),
},
"model_name": "fake-chat",
},
usage_metadata={
"input_tokens": 10,
"output_tokens": len(response.split()),
"total_tokens": 10 + len(response.split()),
},
)
return ChatResult(generations=[ChatGeneration(message=message)])
Use FakeChatWithUsage whenever a chain's observability / cost path is in the
assertion surface. See Fake Model Fixtures
for agent, retriever, and embedder fakes.
Step 3 — pytest fixtures that wire the fake into chains
Put fixtures in tests/conftest.py so they are shared across the suite:
# tests/conftest.pyimport pytest
from langchain_core.prompts import ChatPromptTemplate
from tests.fakes import FakeChatWithUsage
@pytest.fixturedeffake_chat():
"""Reusable fake chat model. Override responses per-test via
monkeypatch.setattr(fake_chat, 'responses', [...])."""return FakeChatWithUsage(responses=["ok"])
@pytest.fixturedefsummarize_chain(fake_chat):
prompt = ChatPromptTemplate.from_messages([
("system", "Summarize the user's text in one line."),
("user", "{text}"),
])
return prompt | fake_chat
Step 4 — VCR cassettes for integration tests with key redaction (P44 fix)
Unit tests should never touch the network. Integration tests do, exactly once —
to record a cassette — and every subsequent run replays from the cassette file.
vcrpy records headers by default, which means Authorization: Bearer sk-...
lands in the fixture unless you filter it.
import pytest
@pytest.mark.vcr # cassette at tests/cassettes/<test_name>.yaml@pytest.mark.integrationdeftest_live_claude_short_answer():
from langchain_anthropic import ChatAnthropic
chat = ChatAnthropic(model="claude-sonnet-4-6", temperature=0, timeout=30)
out = chat.invoke("Say 'ok' and nothing else.")
assert"ok"in out.content.lower()
To record (once, locally, with a real key): pytest --record-mode=once tests/.
Every other run replays — cassettes are committed, real API is never hit again.
Pre-commit hook to block key leaks:
# .git/hooks/pre-commit or .pre-commit-config.yaml entry#!/usr/bin/env bashset -e
if git diff --cached --name-only | grep -q '^tests/cassettes/'; thenif git diff --cached -U0 -- 'tests/cassettes/' | \
grep -E '(sk-ant-[a-zA-Z0-9_-]+|sk-[a-zA-Z0-9]{20,}|Bearer\s+[a-zA-Z0-9_-]{20,})'; thenecho"ERROR: API key pattern found in staged cassette." >&2
exit 1
fifi
See VCR Cassette Hygiene for the full
pre-commit config, record-new-episodes flow, shared-cassette patterns, and the
PR review checklist.
langchain_community and some provider SDKs emit DeprecationWarning at import
time. If the suite runs -W error, collection fails before any test does. Set
the policy once in pyproject.toml:
[tool.pytest.ini_options]minversion = "8.0"testpaths = ["tests"]
addopts = [
"-ra",
"--strict-markers",
"--strict-config",
"-W", "error",
]
markers = [
"integration: hits real APIs or replays VCR cassettes (set RUN_INTEGRATION=1)",
"slow: takes > 1s per test",
"smoke: minimal healthcheck run in CI",
]
filterwarnings = [
"error",
"ignore::DeprecationWarning:langchain_community.*",
"ignore::DeprecationWarning:pydantic.*",
"ignore::PendingDeprecationWarning:langchain_core.*",
]
See Pytest Config for the full skeleton
including coverage config and parallel execution notes.
Step 6 — Integration-test gating via env var
Default pytest must never hit real APIs. Gate on RUN_INTEGRATION=1:
# tests/conftest.py (continued)import os
import pytest
defpytest_collection_modifyitems(config, items):
if os.getenv("RUN_INTEGRATION") == "1":
return
skip_integration = pytest.mark.skip(reason="set RUN_INTEGRATION=1 to run")
for item in items:
if"integration"in item.keywords:
item.add_marker(skip_integration)
Step 7 — LangGraph tests: per-test thread_id + state assertions
LangGraph state is scoped to a thread_id. Tests that share a thread_id leak
state between each other. Give every test a fresh thread_id and a fresh
MemorySaver:
from langgraph.checkpoint.memory import MemorySaver
import uuid, pytest
@pytest.fixturedefgraph_config():
return {"configurable": {"thread_id": str(uuid.uuid4())}}
@pytest.fixturedefcheckpointed_graph(fake_chat):
from my_app.graphs import build_graph
return build_graph(fake_chat).compile(checkpointer=MemorySaver())
deftest_node_emits_plan(checkpointed_graph, graph_config, fake_chat):
fake_chat.responses = ["step 1\nstep 2\nstep 3"]
result = checkpointed_graph.invoke({"goal": "deploy"}, graph_config)
# Assert state shape per node, not just the final output:assert result["plan"] == ["step 1", "step 2", "step 3"]
# Time-travel: inspect every checkpoint for debugging
history = list(checkpointed_graph.get_state_history(graph_config))
assert history[-1].values == {"goal": "deploy"} # initial state
Subgraph isolation testing cross-references langchain-langgraph-subgraphs
(pain P21 — parent cannot read child state unless the key is in the parent
schema). See LangGraph Test Patterns
for the subgraph-shared-state test recipe.
Output
tests/fakes.py with FakeChatWithUsage subclass that emits response_metadata
tests/conftest.py with fake-model fixtures, VCR config, and RUN_INTEGRATION gate
pyproject.toml[tool.pytest.ini_options] block with markers and filterwarnings
tests/cassettes/ committed with filtered headers (no Authorization / x-api-key)
Commit 1 — failing test uses real ChatAnthropic, passes locally, fails
1-in-5 in CI at temperature=0 (P05).
Commit 2 — swap to fake model uses FakeListChatModel, passes
deterministically, but the cost-logging callback crashes (P43).
Commit 3 — fake with metadata uses FakeChatWithUsage, the callback
reads response_metadata["token_usage"] cleanly, the test is green and
runs in 40ms.
See Fake Model Fixtures for the full
worked example including agent and retriever fakes.
Recording a cassette without leaking a key
# 1. Ensure conftest.py has filter_headers configured FIRST# 2. Record with real key present in the environment
ANTHROPIC_API_KEY=sk-ant-... pytest --record-mode=once tests/integration/test_summarize.py
# 3. Verify no leak
grep -E 'sk-|Bearer' tests/cassettes/*.yaml && echo"LEAK" || echo"clean"# 4. Commit cassettes/ — pre-commit hook runs the same grep as a hard gate
git add tests/cassettes/ && git commit -m "test: record summarize cassette"
See VCR Cassette Hygiene for
record-new-episodes mode, rerecord-on-mismatch, and the PR review checklist.
LangGraph time-travel debugging on a failing test
When a graph test fails mid-graph, get_state_history(config) returns every
checkpoint — you can replay from any point by passing its config.checkpoint_id
back into graph.invoke. See
LangGraph Test Patterns for the full
time-travel debugging recipe and the subgraph-shared-state test pattern
(cross-ref langchain-langgraph-subgraphs / pain L30).
