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docs: update package READMEs (#33488)

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Mason Daugherty
2025-10-15 10:49:35 -04:00
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libs/cli/langchain_cli/integration_template/docs/llms.ipynb
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@@ -1,238 +1,238 @@
{
"cells": [
{
"cell_type": "raw",
"id": "67db2992",
"metadata": {},
"source": [
"---\n",
"sidebar_label: __ModuleName__\n",
"---"
]
"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/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__&label=%20) | ![PyPI - Version](https://img.shields.io/pypi/v/__package_name__&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(\n",
" \"Enter your __ModuleName__ API key: \"\n",
" )"
]
},
{
"cell_type": "markdown",
"id": "4b6e1ca6",
"metadata": {},
"source": [
"To enable automated tracing of your model calls, set your [LangSmith](https://docs.smith.langchain.com/) API key:"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "196c2b41",
"metadata": {},
"outputs": [],
"source": [
"# os.environ[\"LANGSMITH_TRACING\"] = \"true\"\n",
"# os.environ[\"LANGSMITH_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",
"model = __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": null,
"id": "035dea0f",
"metadata": {
"tags": []
},
"outputs": [],
"source": [
"input_text = \"__ModuleName__ is an AI company that \"\n",
"\n",
"completion = model.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(\"How to say {input} in {output_language}:\\n\")\n",
"\n",
"chain = prompt | model\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"
}
}
},
{
"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/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(\n",
" \"Enter your __ModuleName__ API key: \"\n",
" )"
]
},
{
"cell_type": "markdown",
"id": "4b6e1ca6",
"metadata": {},
"source": [
"To enable automated tracing of your model calls, set your [LangSmith](https://docs.smith.langchain.com/) API key:"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "196c2b41",
"metadata": {},
"outputs": [],
"source": [
"# os.environ[\"LANGSMITH_TRACING\"] = \"true\"\n",
"# os.environ[\"LANGSMITH_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",
"model = __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": null,
"id": "035dea0f",
"metadata": {
"tags": []
},
"outputs": [],
"source": [
"input_text = \"__ModuleName__ is an AI company that \"\n",
"\n",
"completion = model.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(\"How to say {input} in {output_language}:\\n\")\n",
"\n",
"chain = prompt | model\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
"nbformat": 4,
"nbformat_minor": 5
}