langchain/libs/cli/langchain_cli/integration_template/docs/retrievers.ipynb

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    "---\n",
    "sidebar_label: __ModuleName__\n",
    "---"
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   "source": [
    "# __ModuleName__Retriever\n",
    "\n",
    "- TODO: Make sure API reference link is correct.\n",
    "\n",
    "This will help you get started with the __ModuleName__ [retriever](/docs/concepts/retrievers). For detailed documentation of all __ModuleName__Retriever features and configurations head to the [API reference](https://api.python.langchain.com/en/latest/retrievers/__module_name__.retrievers.__ModuleName__.__ModuleName__Retriever.html).\n",
    "\n",
    "### Integration details\n",
    "\n",
    "TODO: Select one of the tables below, as appropriate.\n",
    "\n",
    "1: Bring-your-own data (i.e., index and search a custom corpus of documents):\n",
    "\n",
    "| Retriever | Self-host | Cloud offering | Package |\n",
    "| :--- | :--- | :---: | :---: |\n",
    "[__ModuleName__Retriever](https://api.python.langchain.com/en/latest/retrievers/__package_name__.retrievers.__module_name__.__ModuleName__Retriever.html) | ❌ | ❌ | __package_name__ |\n",
    "\n",
    "2: External index (e.g., constructed from Internet data or similar)):\n",
    "\n",
    "| Retriever | Source | Package |\n",
    "| :--- | :--- | :---: |\n",
    "[__ModuleName__Retriever](https://api.python.langchain.com/en/latest/retrievers/__package_name__.retrievers.__module_name__.__ModuleName__Retriever.html) | Source description | __package_name__ |\n",
    "\n",
    "## Setup\n",
    "\n",
    "- TODO: Update with relevant info."
   ]
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  {
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   "source": [
    "If you want to get automated tracing from individual queries, you can also set your [LangSmith](https://docs.smith.langchain.com/) API key by uncommenting below:"
   ]
  },
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   "source": [
    "# os.environ[\"LANGSMITH_API_KEY\"] = getpass.getpass(\"Enter your LangSmith API key: \")\n",
    "# os.environ[\"LANGSMITH_TRACING\"] = \"true\""
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0730d6a1-c893-4840-9817-5e5251676d5d",
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   "source": [
    "### Installation\n",
    "\n",
    "This retriever lives in the `__package_name__` package:"
   ]
  },
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   "id": "652d6238-1f87-422a-b135-f5abbb8652fc",
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   "source": [
    "%pip install -qU __package_name__"
   ]
  },
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   "source": [
    "## Instantiation\n",
    "\n",
    "Now we can instantiate our retriever:\n",
    "\n",
    "- TODO: Update model instantiation with relevant params."
   ]
  },
  {
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   "source": [
    "from __module_name__ import __ModuleName__Retriever\n",
    "\n",
    "retriever = __ModuleName__Retriever(\n",
    "    # ...\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
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   "source": [
    "## Usage"
   ]
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   "source": [
    "query = \"...\"\n",
    "\n",
    "retriever.invoke(query)"
   ]
  },
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   "source": [
    "## Use within a chain\n",
    "\n",
    "Like other retrievers, __ModuleName__Retriever can be incorporated into LLM applications via [chains](/docs/how_to/sequence/).\n",
    "\n",
    "We will need a LLM or chat model:\n",
    "\n",
    "import ChatModelTabs from \"@theme/ChatModelTabs\";\n",
    "\n",
    "<ChatModelTabs customVarName=\"llm\" />"
   ]
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    "# | output: false\n",
    "# | echo: false\n",
    "\n",
    "from langchain_openai import ChatOpenAI\n",
    "\n",
    "llm = ChatOpenAI(model=\"gpt-3.5-turbo-0125\", temperature=0)"
   ]
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    "from langchain_core.output_parsers import StrOutputParser\n",
    "from langchain_core.prompts import ChatPromptTemplate\n",
    "from langchain_core.runnables import RunnablePassthrough\n",
    "\n",
    "prompt = ChatPromptTemplate.from_template(\n",
    "    \"\"\"Answer the question based only on the context provided.\n",
    "\n",
    "Context: {context}\n",
    "\n",
    "Question: {question}\"\"\"\n",
    ")\n",
    "\n",
    "\n",
    "def format_docs(docs):\n",
    "    return \"\\n\\n\".join(doc.page_content for doc in docs)\n",
    "\n",
    "\n",
    "chain = (\n",
    "    {\"context\": retriever | format_docs, \"question\": RunnablePassthrough()}\n",
    "    | prompt\n",
    "    | llm\n",
    "    | StrOutputParser()\n",
    ")"
   ]
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    "chain.invoke(\"...\")"
   ]
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   "cell_type": "markdown",
   "id": "d1ee55bc-ffc8-4cfa-801c-993953a08cfd",
   "metadata": {},
   "source": [
    "## TODO: Any functionality or considerations specific to this retriever\n",
    "\n",
    "Fill in or delete if not relevant."
   ]
  },
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   "cell_type": "markdown",
   "id": "3a5bb5ca-c3ae-4a58-be67-2cd18574b9a3",
   "metadata": {},
   "source": [
    "## API reference\n",
    "\n",
    "For detailed documentation of all __ModuleName__Retriever features and configurations head to the [API reference](https://api.python.langchain.com/en/latest/retrievers/__module_name__.retrievers.__ModuleName__.__ModuleName__Retriever.html)."
   ]
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