{
 "cells": [
  {
   "cell_type": "raw",
   "id": "afaf8039",
   "metadata": {},
   "source": [
    "---\n",
    "sidebar_label: __ModuleName__\n",
    "---"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e49f1e0d",
   "metadata": {},
   "source": [
    "# Chat__ModuleName__\n",
    "\n",
    "- TODO: Make sure API reference link is correct.\n",
    "\n",
    "This notebook provides a quick overview for getting started with __ModuleName__ [chat models](/docs/concepts/#chat-models). For detailed documentation of all Chat__ModuleName__ features and configurations head to the [API reference](https://api.python.langchain.com/en/latest/chat_models/__module_name__.chat_models.Chat__ModuleName__.html).\n",
    "\n",
    "- TODO: Add any other relevant links, like information about models, prices, context windows, etc. See https://python.langchain.com/v0.2/docs/integrations/chat/openai/ for an example.\n",
    "\n",
    "## Overview\n",
    "### Integration details\n",
    "\n",
    "- TODO: Fill in table features.\n",
    "- TODO: Remove JS support link if not relevant, otherwise ensure link is correct.\n",
    "- TODO: Make sure API reference links are correct.\n",
    "\n",
    "| Class | Package | Local | Serializable | [JS support](https://js.langchain.com/v0.2/docs/integrations/chat/__package_name_short_snake__) | Package downloads | Package latest |\n",
    "| :--- | :--- | :---: | :---: |  :---: | :---: | :---: |\n",
    "| [Chat__ModuleName__](https://api.python.langchain.com/en/latest/chat_models/__module_name__.chat_models.Chat__ModuleName__.html) | [__package__name__](https://api.python.langchain.com/en/latest/__package_name_short_snake___api_reference.html) | ✅/❌ | beta/❌ | ✅/❌ | ![PyPI - Downloads](https://img.shields.io/pypi/dm/__package_name__?style=flat-square&label=%20) | ![PyPI - Version](https://img.shields.io/pypi/v/__package_name__?style=flat-square&label=%20) |\n",
    "\n",
    "### Model features\n",
    "| [Tool calling](/docs/how_to/tool_calling/) | [Structured output](/docs/how_to/structured_output/) | JSON mode | [Image input](/docs/how_to/multimodal_inputs/) | Audio input | Video input | [Token-level streaming](/docs/how_to/chat_streaming/) | Native async | [Token usage](/docs/how_to/chat_token_usage_tracking/) | [Logprobs](/docs/how_to/logprobs/) |\n",
    "| :---: | :---: | :---: | :---: |  :---: | :---: | :---: | :---: | :---: | :---: |\n",
    "| ✅/❌ | ✅/❌ | ✅/❌ | ✅/❌ | ✅/❌ | ✅/❌ | ✅/❌ | ✅/❌ | ✅/❌ | ✅/❌ | \n",
    "\n",
    "## Setup\n",
    "\n",
    "- TODO: Update with relevant info.\n",
    "\n",
    "To access __ModuleName__ models you'll need to create a/an __ModuleName__ account, get an API key, and install the `__package_name__` integration package.\n",
    "\n",
    "### Credentials\n",
    "\n",
    "- TODO: Update with relevant info.\n",
    "\n",
    "Head to (TODO: link) to sign up to __ModuleName__ and generate an API key. Once you've done this set the __MODULE_NAME___API_KEY environment variable:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "433e8d2b-9519-4b49-b2c4-7ab65b046c94",
   "metadata": {},
   "outputs": [],
   "source": [
    "import getpass\n",
    "import os\n",
    "\n",
    "os.environ[\"__MODULE_NAME___API_KEY\"] = getpass.getpass(\"Enter your __ModuleName__ API key: \")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "72ee0c4b-9764-423a-9dbf-95129e185210",
   "metadata": {},
   "source": [
    "If you want to get automated tracing of your model calls you can also set your [LangSmith](https://docs.smith.langchain.com/) API key by uncommenting below:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "a15d341e-3e26-4ca3-830b-5aab30ed66de",
   "metadata": {},
   "outputs": [],
   "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",
   "metadata": {},
   "source": [
    "### Installation\n",
    "\n",
    "The LangChain __ModuleName__ integration lives in the `__package_name__` package:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "652d6238-1f87-422a-b135-f5abbb8652fc",
   "metadata": {},
   "outputs": [],
   "source": [
    "%pip install -qU __package_name__"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a38cde65-254d-4219-a441-068766c0d4b5",
   "metadata": {},
   "source": [
    "## Instantiation\n",
    "\n",
    "Now we can instantiate our model object and generate chat completions:\n",
    "\n",
    "- TODO: Update model instantiation with relevant params."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "cb09c344-1836-4e0c-acf8-11d13ac1dbae",
   "metadata": {},
   "outputs": [],
   "source": [
    "from __module_name__ import Chat__ModuleName__\n",
    "\n",
    "llm = Chat__ModuleName__(\n",
    "    model=\"model-name\",\n",
    "    temperature=0,\n",
    "    max_tokens=None,\n",
    "    timeout=None,\n",
    "    max_retries=2,\n",
    "    # other params...\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2b4f3e15",
   "metadata": {},
   "source": [
    "## Invocation\n",
    "\n",
    "- TODO: Run cells so output can be seen."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "62e0dbc3",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "messages = [\n",
    "    (\n",
    "        \"system\",\n",
    "        \"You are a helpful assistant that translates English to French. Translate the user sentence.\",\n",
    "    ),\n",
    "    (\"human\", \"I love programming.\"),\n",
    "]\n",
    "ai_msg = llm.invoke(messages)\n",
    "ai_msg"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "d86145b3-bfef-46e8-b227-4dda5c9c2705",
   "metadata": {},
   "outputs": [],
   "source": [
    "print(ai_msg.content)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "18e2bfc0-7e78-4528-a73f-499ac150dca8",
   "metadata": {},
   "source": [
    "## Chaining\n",
    "\n",
    "We can [chain](/docs/how_to/sequence/) our model with a prompt template like so:\n",
    "\n",
    "- TODO: Run cells so output can be seen."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "e197d1d7-a070-4c96-9f8a-a0e86d046e0b",
   "metadata": {},
   "outputs": [],
   "source": [
    "from langchain_core.prompts import ChatPromptTemplate\n",
    "\n",
    "prompt = ChatPromptTemplate.from_messages(\n",
    "    [\n",
    "        (\n",
    "            \"system\",\n",
    "            \"You are a helpful assistant that translates {input_language} to {output_language}.\",\n",
    "        ),\n",
    "        (\"human\", \"{input}\"),\n",
    "    ]\n",
    ")\n",
    "\n",
    "chain = prompt | llm\n",
    "chain.invoke(\n",
    "    {\n",
    "        \"input_language\": \"English\",\n",
    "        \"output_language\": \"German\",\n",
    "        \"input\": \"I love programming.\",\n",
    "    }\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d1ee55bc-ffc8-4cfa-801c-993953a08cfd",
   "metadata": {},
   "source": [
    "## TODO: Any functionality specific to this model provider\n",
    "\n",
    "E.g. creating/using finetuned models via this provider. Delete if not relevant."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3a5bb5ca-c3ae-4a58-be67-2cd18574b9a3",
   "metadata": {},
   "source": [
    "## API reference\n",
    "\n",
    "For detailed documentation of all Chat__ModuleName__ features and configurations head to the API reference: https://api.python.langchain.com/en/latest/chat_models/__module_name__.chat_models.Chat__ModuleName__.html"
   ]
  }
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