{ "cells": [ { "cell_type": "raw", "id": "67db2992", "metadata": {}, "source": [ "---\n", "sidebar_label: __ModuleName__\n", "---" ] }, { "cell_type": "markdown", "id": "9597802c", "metadata": {}, "source": [ "# __ModuleName__LLM\n", "\n", "- [ ] TODO: Make sure API reference link is correct\n", "\n", "This will help you get started with __ModuleName__ completion models (LLMs) using LangChain. For detailed documentation on `__ModuleName__LLM` features and configuration options, please refer to the [API reference](https://api.python.langchain.com/en/latest/llms/__module_name__.llms.__ModuleName__LLM.html).\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/llms/__package_name_short_snake__) | Package downloads | Package latest |\n", "| :--- | :--- | :---: | :---: | :---: | :---: | :---: |\n", "| [__ModuleName__LLM](https://api.python.langchain.com/en/latest/llms/__module_name__.llms.__ModuleName__LLM.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", "## 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": "bc51e756", "metadata": {}, "outputs": [], "source": [ "import getpass\n", "import os\n", "\n", "if not os.getenv(\"__MODULE_NAME___API_KEY\"):\n", " os.environ[\"__MODULE_NAME___API_KEY\"] = getpass.getpass(\"Enter your __ModuleName__ API key: \")" ] }, { "cell_type": "markdown", "id": "4b6e1ca6", "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": "196c2b41", "metadata": {}, "outputs": [], "source": [ "# os.environ[\"LANGCHAIN_TRACING_V2\"] = \"true\"\n", "# os.environ[\"LANGCHAIN_API_KEY\"] = getpass.getpass(\"Enter your LangSmith API key: \")" ] }, { "cell_type": "markdown", "id": "809c6577", "metadata": {}, "source": [ "### Installation\n", "\n", "The LangChain __ModuleName__ integration lives in the `__package_name__` package:" ] }, { "cell_type": "code", "execution_count": null, "id": "59c710c4", "metadata": {}, "outputs": [], "source": [ "%pip install -qU __package_name__" ] }, { "cell_type": "markdown", "id": "0a760037", "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": "a0562a13", "metadata": {}, "outputs": [], "source": [ "from __module_name__ import __ModuleName__LLM\n", "\n", "llm = __ModuleName__LLM(\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": "0ee90032", "metadata": {}, "source": [ "## Invocation\n", "\n", "- [ ] TODO: Run cells so output can be seen." ] }, { "cell_type": "code", "execution_count": 4, "id": "035dea0f", "metadata": { "tags": [] }, "outputs": [], "source": [ "input_text = \"__ModuleName__ is an AI company that \"\n", "\n", "completion = llm.invoke(input_text)\n", "completion" ] }, { "cell_type": "markdown", "id": "add38532", "metadata": {}, "source": [ "## Chaining\n", "\n", "We can [chain](/docs/how_to/sequence/) our completion model with a prompt template like so:\n", "\n", "- TODO: Run cells so output can be seen." ] }, { "cell_type": "code", "execution_count": null, "id": "078e9db2", "metadata": {}, "outputs": [], "source": [ "from langchain_core.prompts import PromptTemplate\n", "\n", "prompt = PromptTemplate(\n", " \"How to say {input} in {output_language}:\\n\"\n", ")\n", "\n", "chain = prompt | llm\n", "chain.invoke(\n", " {\n", " \"output_language\": \"German\",\n", " \"input\": \"I love programming.\",\n", " }\n", ")" ] }, { "cell_type": "markdown", "id": "e99eef30", "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": "e9bdfcef", "metadata": {}, "source": [ "## API reference\n", "\n", "For detailed documentation of all `__ModuleName__LLM` features and configurations head to the API reference: https://api.python.langchain.com/en/latest/llms/__module_name__.llms.__ModuleName__LLM.html" ] } ], "metadata": { "kernelspec": { "display_name": "Python 3.11.1 64-bit", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.9.7" }, "vscode": { "interpreter": { "hash": "e971737741ff4ec9aff7dc6155a1060a59a8a6d52c757dbbe66bf8ee389494b1" } } }, "nbformat": 4, "nbformat_minor": 5 }