Configure LangChain CI/CD integration with GitHub Actions and testing. Use when setting up automated testing, configuring CI pipelines, or integrating LangChain tests into your build process. Trigger with phrases like "langchain CI", "langchain GitHub Actions", "langchain automated tests", "CI langchain", "langchain pipeline".
/plugin marketplace add jeremylongshore/claude-code-plugins-plus-skills/plugin install langchain-pack@claude-code-plugins-plusThis skill is limited to using the following tools:
Configure comprehensive CI/CD pipelines for LangChain applications with testing, linting, and deployment automation.
# .github/workflows/langchain-ci.yml
name: LangChain CI
on:
push:
branches: [main, develop]
pull_request:
branches: [main]
env:
PYTHON_VERSION: "3.11"
jobs:
lint:
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v4
- name: Set up Python
uses: actions/setup-python@v5
with:
python-version: ${{ env.PYTHON_VERSION }}
- name: Install dependencies
run: |
pip install ruff mypy
- name: Lint with Ruff
run: ruff check .
- name: Type check with mypy
run: mypy src/
test-unit:
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v4
- name: Set up Python
uses: actions/setup-python@v5
with:
python-version: ${{ env.PYTHON_VERSION }}
- name: Install dependencies
run: |
pip install -e ".[dev]"
- name: Run unit tests
run: |
pytest tests/unit -v --cov=src --cov-report=xml
- name: Upload coverage
uses: codecov/codecov-action@v4
with:
files: coverage.xml
test-integration:
runs-on: ubuntu-latest
needs: [lint, test-unit]
# Only run on main branch or manual trigger
if: github.ref == 'refs/heads/main' || github.event_name == 'workflow_dispatch'
steps:
- uses: actions/checkout@v4
- name: Set up Python
uses: actions/setup-python@v5
with:
python-version: ${{ env.PYTHON_VERSION }}
- name: Install dependencies
run: |
pip install -e ".[dev]"
- name: Run integration tests
env:
OPENAI_API_KEY: ${{ secrets.OPENAI_API_KEY }}
run: |
pytest tests/integration -v -m integration
# pyproject.toml
[tool.pytest.ini_options]
markers = [
"unit: Unit tests (no external API calls)",
"integration: Integration tests (requires API keys)",
"slow: Slow tests (skip in fast mode)",
]
asyncio_mode = "auto"
testpaths = ["tests"]
# tests/conftest.py
import pytest
from unittest.mock import MagicMock, AsyncMock
from langchain_core.messages import AIMessage
@pytest.fixture
def mock_llm():
"""Mock LLM for unit tests."""
mock = MagicMock()
mock.invoke.return_value = AIMessage(content="Mock response")
mock.ainvoke = AsyncMock(return_value=AIMessage(content="Mock response"))
return mock
@pytest.fixture
def mock_chain(mock_llm):
"""Mock chain for testing."""
from langchain_core.prompts import ChatPromptTemplate
from langchain_core.output_parsers import StrOutputParser
prompt = ChatPromptTemplate.from_template("{input}")
return prompt | mock_llm | StrOutputParser()
# .pre-commit-config.yaml
repos:
- repo: https://github.com/astral-sh/ruff-pre-commit
rev: v0.1.6
hooks:
- id: ruff
args: [--fix]
- id: ruff-format
- repo: https://github.com/pre-commit/mirrors-mypy
rev: v1.7.1
hooks:
- id: mypy
additional_dependencies:
- langchain-core
- pydantic
# Add to .github/workflows/langchain-ci.yml
deploy:
runs-on: ubuntu-latest
needs: [test-integration]
if: github.ref == 'refs/heads/main'
environment: production
steps:
- uses: actions/checkout@v4
- name: Deploy to Cloud Run
uses: google-github-actions/deploy-cloudrun@v2
with:
service: langchain-api
source: .
env_vars: |
LANGCHAIN_PROJECT=production
# Run unit tests only (fast)
pytest tests/unit -v
# Run with coverage
pytest tests/unit --cov=src --cov-report=html
# Run integration tests (requires API key)
OPENAI_API_KEY=sk-... pytest tests/integration -v -m integration
# Skip slow tests
pytest tests/ -v -m "not slow"
# tests/integration/test_chain.py
import pytest
from langchain_openai import ChatOpenAI
from langchain_core.prompts import ChatPromptTemplate
@pytest.mark.integration
def test_real_chain_invocation():
"""Test with real LLM (requires API key)."""
llm = ChatOpenAI(model="gpt-4o-mini", temperature=0)
prompt = ChatPromptTemplate.from_template("Say exactly: {word}")
chain = prompt | llm
result = chain.invoke({"word": "hello"})
assert "hello" in result.content.lower()
| Error | Cause | Solution |
|---|---|---|
| Secret Not Found | Missing GitHub secret | Add OPENAI_API_KEY to repository secrets |
| Rate Limit in CI | Too many API calls | Use mocks for unit tests, limit integration tests |
| Timeout | Slow tests | Add timeout markers, parallelize tests |
| Import Error | Missing dev dependencies | Ensure .[dev] extras installed |
Proceed to langchain-deploy-integration for deployment configuration.
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