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apps.\nTrigger with phrases like \"langchain dev setup\", \"langchain local development\",\n\"langchain testing\", \"langchain development workflow\".","Dicklesworthstone\u002Fpi_agent_rust","Dicklesworthstone","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F35050222?v=4","01M6CG26AR942CSVMN1M5E3DSE","Jeff Emanuel","01M6CG26EPP71PSHW1VDS71121",1981,"MIT","https:\u002F\u002Fgithub.com\u002FDicklesworthstone\u002Fpi_agent_rust\u002Fblob\u002Fmain\u002Ftests\u002Fext_conformance\u002Fartifacts\u002Fplugins-community\u002Fplugins\u002Fsaas-packs\u002Flangchain-pack\u002Fskills\u002Flangchain-local-dev-loop\u002FSKILL.md",[18],{"categoryNo":19,"categoryName":20,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000008","测试与质量","SCENARIO","使用场景",[24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45],"local dev","dev loop","langchain local dev loop","local","langchain","loop","dev","Bash","configure","read","write","edit","up","development workflow","langchain development","workflow","iteration","io","apps","dev setup","when","testing","2026-11-10 10:12:30",false,"---\nname: langchain-local-dev-loop\ndescription: |\n  Configure LangChain local development workflow with hot reload and testing.\n  Use when setting up development environment, configuring test fixtures,\n  or establishing a rapid iteration workflow for LangChain apps.\n  Trigger with phrases like \"langchain dev setup\", \"langchain local development\",\n  \"langchain testing\", \"langchain development workflow\".\nallowed-tools: Read, Write, Edit, Bash(pytest:*), Bash(python:*)\nversion: 1.0.0\nlicense: MIT\nauthor: Jeremy Longshore \u003Cjeremy@intentsolutions.io>\n---\n\n# LangChain Local Dev Loop\n\n## Overview\nConfigure a rapid local development workflow for LangChain applications with testing, debugging, and hot reload capabilities.\n\n## Prerequisites\n- Completed `langchain-install-auth` setup\n- Python 3.9+ with virtual environment\n- pytest and related testing tools\n- IDE with Python support (VS Code recommended)\n\n## Instructions\n\n### Step 1: Set Up Project Structure\n```\nmy-langchain-app\u002F\n├── src\u002F\n│   ├── __init__.py\n│   ├── chains\u002F\n│   │   └── __init__.py\n│   ├── agents\u002F\n│   │   └── __init__.py\n│   └── prompts\u002F\n│       └── __init__.py\n├── tests\u002F\n│   ├── __init__.py\n│   ├── conftest.py\n│   └── test_chains.py\n├── .env\n├── .env.example\n├── pyproject.toml\n└── README.md\n```\n\n### Step 2: Configure Testing\n```python\n# tests\u002Fconftest.py\nimport pytest\nfrom unittest.mock import MagicMock\nfrom langchain_core.messages import AIMessage\n\n@pytest.fixture\ndef mock_llm():\n    \"\"\"Mock LLM for unit tests without API calls.\"\"\"\n    mock = MagicMock()\n    mock.invoke.return_value = AIMessage(content=\"Mocked response\")\n    return mock\n\n@pytest.fixture\ndef sample_prompt():\n    \"\"\"Sample prompt for testing.\"\"\"\n    from langchain_core.prompts import ChatPromptTemplate\n    return ChatPromptTemplate.from_template(\"Test: {input}\")\n```\n\n### Step 3: Create Test File\n```python\n# tests\u002Ftest_chains.py\ndef test_chain_construction(mock_llm, sample_prompt):\n    \"\"\"Test that chain can be constructed.\"\"\"\n    from langchain_core.output_parsers import StrOutputParser\n\n    chain = sample_prompt | mock_llm | StrOutputParser()\n    assert chain is not None\n\ndef test_chain_invoke(mock_llm, sample_prompt):\n    \"\"\"Test chain invocation with mock.\"\"\"\n    from langchain_core.output_parsers import StrOutputParser\n\n    chain = sample_prompt | mock_llm | StrOutputParser()\n    result = chain.invoke({\"input\": \"test\"})\n    assert result == \"Mocked response\"\n```\n\n### Step 4: Set Up Development Tools\n```toml\n# pyproject.toml\n[project]\nname = \"my-langchain-app\"\nversion = \"0.1.0\"\nrequires-python = \">=3.9\"\ndependencies = [\n    \"langchain>=0.3.0\",\n    \"langchain-openai>=0.2.0\",\n    \"python-dotenv>=1.0.0\",\n]\n\n[project.optional-dependencies]\ndev = [\n    \"pytest>=8.0.0\",\n    \"pytest-asyncio>=0.23.0\",\n    \"pytest-cov>=4.0.0\",\n    \"ruff>=0.1.0\",\n    \"mypy>=1.0.0\",\n]\n\n[tool.pytest.ini_options]\nasyncio_mode = \"auto\"\ntestpaths = [\"tests\"]\n\n[tool.ruff]\nline-length = 100\n```\n\n## Output\n- Organized project structure with separation of concerns\n- pytest configuration with fixtures for mocking LLMs\n- Development dependencies configured\n- Ready for rapid iteration\n\n## Error Handling\n| Error | Cause | Solution |\n|-------|-------|----------|\n| Import Error | Missing package | Install with `pip install -e \".[dev]\"` |\n| Fixture Not Found | conftest.py issue | Ensure conftest.py is in tests\u002F directory |\n| Async Test Error | Missing marker | Add `@pytest.mark.asyncio` decorator |\n| Env Var Missing | .env not loaded | Use `python-dotenv` and load_dotenv() |\n\n## Examples\n\n### Running Tests\n```bash\n# Run all tests\npytest\n\n# Run with coverage\npytest --cov=src --cov-report=html\n\n# Run specific test\npytest tests\u002Ftest_chains.py::test_chain_invoke -v\n\n# Watch mode (requires pytest-watch)\nptw\n```\n\n### Integration Test Example\n```python\n# tests\u002Ftest_integration.py\nimport pytest\nfrom dotenv import load_dotenv\n\nload_dotenv()\n\n@pytest.mark.integration\ndef test_real_llm_call():\n    \"\"\"Integration test with real LLM (requires API key).\"\"\"\n    from langchain_openai import ChatOpenAI\n\n    llm = ChatOpenAI(model=\"gpt-4o-mini\", temperature=0)\n    response = llm.invoke(\"Say 'test passed'\")\n    assert \"test\" in response.content.lower()\n```\n\n## Resources\n- [pytest Documentation](https:\u002F\u002Fdocs.pytest.org\u002F)\n- [LangChain Testing Guide](https:\u002F\u002Fpython.langchain.com\u002Fdocs\u002Fcontributing\u002Ftesting)\n- [python-dotenv](https:\u002F\u002Fpypi.org\u002Fproject\u002Fpython-dotenv\u002F)\n\n## Next Steps\nProceed to `langchain-sdk-patterns` for production-ready code patterns.\n","# LangChain Local Dev Loop\n\n## Overview\nConfigure a rapid local development workflow for LangChain applications with testing, debugging, and hot reload capabilities.\n\n## Prerequisites\n- Completed `langchain-install-auth` setup\n- Python 3.9+ with virtual environment\n- pytest and related testing tools\n- IDE with Python support (VS Code recommended)\n\n## Instructions\n\n### Step 1: Set Up Project Structure\n```\nmy-langchain-app\u002F\n├── src\u002F\n│   ├── __init__.py\n│   ├── chains\u002F\n│   │   └── __init__.py\n│   ├── agents\u002F\n│   │   └── __init__.py\n│   └── prompts\u002F\n│       └── __init__.py\n├── tests\u002F\n│   ├── __init__.py\n│   ├── conftest.py\n│   └── test_chains.py\n├── .env\n├── .env.example\n├── pyproject.toml\n└── README.md\n```\n\n### Step 2: Configure Testing\n```python\n# tests\u002Fconftest.py\nimport pytest\nfrom unittest.mock import MagicMock\nfrom langchain_core.messages import AIMessage\n\n@pytest.fixture\ndef mock_llm():\n    \"\"\"Mock LLM for unit tests without API calls.\"\"\"\n    mock = MagicMock()\n    mock.invoke.return_value = AIMessage(content=\"Mocked response\")\n    return mock\n\n@pytest.fixture\ndef sample_prompt():\n    \"\"\"Sample prompt for testing.\"\"\"\n    from langchain_core.prompts import ChatPromptTemplate\n    return ChatPromptTemplate.from_template(\"Test: {input}\")\n```\n\n### Step 3: Create Test File\n```python\n# tests\u002Ftest_chains.py\ndef test_chain_construction(mock_llm, sample_prompt):\n    \"\"\"Test that chain can be constructed.\"\"\"\n    from langchain_core.output_parsers import StrOutputParser\n\n    chain = sample_prompt | mock_llm | StrOutputParser()\n    assert chain is not None\n\ndef test_chain_invoke(mock_llm, sample_prompt):\n    \"\"\"Test chain invocation with mock.\"\"\"\n    from langchain_core.output_parsers import StrOutputParser\n\n    chain = sample_prompt | mock_llm | StrOutputParser()\n    result = chain.invoke({\"input\": \"test\"})\n    assert result == \"Mocked response\"\n```\n\n### Step 4: Set Up Development Tools\n```toml\n# pyproject.toml\n[project]\nname = \"my-langchain-app\"\nversion = \"0.1.0\"\nrequires-python = \">=3.9\"\ndependencies = [\n    \"langchain>=0.3.0\",\n    \"langchain-openai>=0.2.0\",\n    \"python-dotenv>=1.0.0\",\n]\n\n[project.optional-dependencies]\ndev = [\n    \"pytest>=8.0.0\",\n    \"pytest-asyncio>=0.23.0\",\n    \"pytest-cov>=4.0.0\",\n    \"ruff>=0.1.0\",\n    \"mypy>=1.0.0\",\n]\n\n[tool.pytest.ini_options]\nasyncio_mode = \"auto\"\ntestpaths = [\"tests\"]\n\n[tool.ruff]\nline-length = 100\n```\n\n## Output\n- Organized project structure with separation of concerns\n- pytest configuration with fixtures for mocking LLMs\n- Development dependencies configured\n- Ready for rapid iteration\n\n## Error Handling\n| Error | Cause | Solution |\n|-------|-------|----------|\n| Import Error | Missing package | Install with `pip install -e \".[dev]\"` |\n| Fixture Not Found | conftest.py issue | Ensure conftest.py is in tests\u002F directory |\n| Async Test Error | Missing marker | Add `@pytest.mark.asyncio` decorator |\n| Env Var Missing | .env not loaded | Use `python-dotenv` and load_dotenv() |\n\n## Examples\n\n### Running Tests\n```bash\n# Run all tests\npytest\n\n# Run with coverage\npytest --cov=src --cov-report=html\n\n# Run specific test\npytest tests\u002Ftest_chains.py::test_chain_invoke -v\n\n# Watch mode (requires pytest-watch)\nptw\n```\n\n### Integration Test Example\n```python\n# tests\u002Ftest_integration.py\nimport pytest\nfrom dotenv import load_dotenv\n\nload_dotenv()\n\n@pytest.mark.integration\ndef test_real_llm_call():\n    \"\"\"Integration test with real LLM (requires API key).\"\"\"\n    from langchain_openai import ChatOpenAI\n\n    llm = ChatOpenAI(model=\"gpt-4o-mini\", temperature=0)\n    response = llm.invoke(\"Say 'test passed'\")\n    assert \"test\" in response.content.lower()\n```\n\n## Resources\n- [pytest Documentation](https:\u002F\u002Fdocs.pytest.org\u002F)\n- [LangChain Testing Guide](https:\u002F\u002Fpython.langchain.com\u002Fdocs\u002Fcontributing\u002Ftesting)\n- [python-dotenv](https:\u002F\u002Fpypi.org\u002Fproject\u002Fpython-dotenv\u002F)\n\n## Next Steps\nProceed to `langchain-sdk-patterns` for production-ready code patterns.\n",{"name":5,"author":51,"license":15,"version":52,"description":53,"allowed-tools":54},"Jeremy Longshore \u003Cjeremy@intentsolutions.io>","1.0.0","Configure LangChain local development workflow with hot reload and testing.\nUse when setting up development environment, configuring test fixtures,\nor establishing a rapid iteration workflow for LangChain apps.\nTrigger with phrases like \"langchain dev setup\", \"langchain local development\",\n\"langchain testing\", \"langchain development workflow\".\n","Read, Write, Edit, Bash(pytest:*), 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