diff --git a/README.md b/README.md index 495a35bcc40..d845a72f916 100644 --- a/README.md +++ b/README.md @@ -12,13 +12,16 @@
-
+
-
+
+
+
+
-
+
diff --git a/libs/cli/README.md b/libs/cli/README.md
index f86c6ef69d4..7c29748e954 100644
--- a/libs/cli/README.md
+++ b/libs/cli/README.md
@@ -1,6 +1,30 @@
# langchain-cli
-This package implements the official CLI for LangChain. Right now, it is most useful
-for getting started with LangChain Templates!
+[](https://pypi.org/project/langchain-cli/#history)
+[](https://opensource.org/licenses/MIT)
+[](https://pypistats.org/packages/langchain-cli)
+[](https://twitter.com/langchainai)
+
+## Quick Install
+
+```bash
+pip install langchain-cli
+```
+
+## 🤔 What is this?
+
+This package implements the official CLI for LangChain. Right now, it is most useful for getting started with LangChain Templates!
+
+## 📖 Documentation
[CLI Docs](https://github.com/langchain-ai/langchain/blob/master/libs/cli/DOCS.md)
+
+## 📕 Releases & Versioning
+
+See our [Releases](https://docs.langchain.com/oss/python/release-policy) and [Versioning](https://docs.langchain.com/oss/python/versioning) policies.
+
+## 💁 Contributing
+
+As an open-source project in a rapidly developing field, we are extremely open to contributions, whether it be in the form of a new feature, improved infrastructure, or better documentation.
+
+For detailed information on how to contribute, see the [Contributing Guide](https://docs.langchain.com/oss/python/contributing/overview).
diff --git a/libs/cli/langchain_cli/integration_template/docs/chat.ipynb b/libs/cli/langchain_cli/integration_template/docs/chat.ipynb
index ff6e4d8cab2..32f4cb8e1b0 100644
--- a/libs/cli/langchain_cli/integration_template/docs/chat.ipynb
+++ b/libs/cli/langchain_cli/integration_template/docs/chat.ipynb
@@ -1,264 +1,264 @@
{
- "cells": [
- {
- "cell_type": "raw",
- "id": "afaf8039",
- "metadata": {},
- "source": [
- "---\n",
- "sidebar_label: __ModuleName__\n",
- "---"
- ]
+ "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 will help you get 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://python.langchain.com/api_reference/__package_name_short_snake__/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/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/docs/integrations/chat/__package_name_short_snake__) | Package downloads | Package latest |\n",
+ "| :--- | :--- | :---: | :---: | :---: | :---: | :---: |\n",
+ "| [Chat__ModuleName__](https://python.langchain.com/api_reference/__package_name_short_snake__/chat_models/__module_name__.chat_models.Chat__ModuleName__.html) | [__package_name__](https://python.langchain.com/api_reference/__package_name_short_snake__/) | ✅/❌ | beta/❌ | ✅/❌ |  |  |\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",
+ "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": "72ee0c4b-9764-423a-9dbf-95129e185210",
+ "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": "a15d341e-3e26-4ca3-830b-5aab30ed66de",
+ "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": "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",
+ "model = 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 = model.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(\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 | model\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://python.langchain.com/api_reference/__package_name_short_snake__/chat_models/__module_name__.chat_models.Chat__ModuleName__.html)"
+ ]
+ }
+ ],
+ "metadata": {
+ "kernelspec": {
+ "display_name": "Python 3 (ipykernel)",
+ "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": "3.11.9"
+ }
},
- {
- "cell_type": "markdown",
- "id": "e49f1e0d",
- "metadata": {},
- "source": [
- "# Chat__ModuleName__\n",
- "\n",
- "- TODO: Make sure API reference link is correct.\n",
- "\n",
- "This will help you get 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://python.langchain.com/api_reference/__package_name_short_snake__/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/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/docs/integrations/chat/__package_name_short_snake__) | Package downloads | Package latest |\n",
- "| :--- | :--- | :---: | :---: | :---: | :---: | :---: |\n",
- "| [Chat__ModuleName__](https://python.langchain.com/api_reference/__package_name_short_snake__/chat_models/__module_name__.chat_models.Chat__ModuleName__.html) | [__package_name__](https://python.langchain.com/api_reference/__package_name_short_snake__/) | ✅/❌ | beta/❌ | ✅/❌ |  |  |\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",
- "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": "72ee0c4b-9764-423a-9dbf-95129e185210",
- "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": "a15d341e-3e26-4ca3-830b-5aab30ed66de",
- "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": "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",
- "model = 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 = model.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(\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 | model\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://python.langchain.com/api_reference/__package_name_short_snake__/chat_models/__module_name__.chat_models.Chat__ModuleName__.html)"
- ]
- }
- ],
- "metadata": {
- "kernelspec": {
- "display_name": "Python 3 (ipykernel)",
- "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": "3.11.9"
- }
- },
- "nbformat": 4,
- "nbformat_minor": 5
+ "nbformat": 4,
+ "nbformat_minor": 5
}
diff --git a/libs/cli/langchain_cli/integration_template/docs/llms.ipynb b/libs/cli/langchain_cli/integration_template/docs/llms.ipynb
index eb58d4fafbf..ffeff84e280 100644
--- a/libs/cli/langchain_cli/integration_template/docs/llms.ipynb
+++ b/libs/cli/langchain_cli/integration_template/docs/llms.ipynb
@@ -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/❌ | ✅/❌ |  |  |\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/❌ | ✅/❌ |  |  |\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
}
diff --git a/libs/cli/langchain_cli/integration_template/docs/stores.ipynb b/libs/cli/langchain_cli/integration_template/docs/stores.ipynb
index 5daa0568c4a..e250dcfa627 100644
--- a/libs/cli/langchain_cli/integration_template/docs/stores.ipynb
+++ b/libs/cli/langchain_cli/integration_template/docs/stores.ipynb
@@ -1,204 +1,204 @@
{
- "cells": [
- {
- "cell_type": "raw",
- "metadata": {
- "vscode": {
- "languageId": "raw"
+ "cells": [
+ {
+ "cell_type": "raw",
+ "metadata": {
+ "vscode": {
+ "languageId": "raw"
+ }
+ },
+ "source": [
+ "---\n",
+ "sidebar_label: __ModuleName__ByteStore\n",
+ "---"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "# __ModuleName__ByteStore\n",
+ "\n",
+ "- TODO: Make sure API reference link is correct.\n",
+ "\n",
+ "This will help you get started with __ModuleName__ [key-value stores](/docs/concepts/#key-value-stores). For detailed documentation of all __ModuleName__ByteStore features and configurations head to the [API reference](https://python.langchain.com/v0.2/api_reference/core/stores/langchain_core.stores.__module_name__ByteStore.html).\n",
+ "\n",
+ "- TODO: Add any other relevant links, like information about models, prices, context windows, etc. See https://python.langchain.com/docs/integrations/stores/in_memory/ for an example.\n",
+ "\n",
+ "## Overview\n",
+ "\n",
+ "- TODO: (Optional) A short introduction to the underlying technology/API.\n",
+ "\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 | [JS support](https://js.langchain.com/docs/integrations/stores/_package_name_) | Package downloads | Package latest |\n",
+ "| :--- | :--- | :---: | :---: | :---: | :---: |\n",
+ "| [__ModuleName__ByteStore](https://api.python.langchain.com/en/latest/stores/__module_name__.stores.__ModuleName__ByteStore.html) | [__package_name__](https://api.python.langchain.com/en/latest/__package_name_short_snake___api_reference.html) | ✅/❌ | ✅/❌ |  |  |\n",
+ "\n",
+ "## Setup\n",
+ "\n",
+ "- TODO: Update with relevant info.\n",
+ "\n",
+ "To create a __ModuleName__ byte store, 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, or omit if the service does not require any credentials.\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,
+ "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",
+ "metadata": {},
+ "source": [
+ "### Installation\n",
+ "\n",
+ "The LangChain __ModuleName__ integration lives in the `__package_name__` package:"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "%pip install -qU __package_name__"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "## Instantiation\n",
+ "\n",
+ "Now we can instantiate our byte store:\n",
+ "\n",
+ "- TODO: Update model instantiation with relevant params."
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "from __module_name__ import __ModuleName__ByteStore\n",
+ "\n",
+ "kv_store = __ModuleName__ByteStore(\n",
+ " # params...\n",
+ ")"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "## Usage\n",
+ "\n",
+ "- TODO: Run cells so output can be seen.\n",
+ "\n",
+ "You can set data under keys like this using the `mset` method:"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "kv_store.mset(\n",
+ " [\n",
+ " [\"key1\", b\"value1\"],\n",
+ " [\"key2\", b\"value2\"],\n",
+ " ]\n",
+ ")\n",
+ "\n",
+ "kv_store.mget(\n",
+ " [\n",
+ " \"key1\",\n",
+ " \"key2\",\n",
+ " ]\n",
+ ")"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "And you can delete data using the `mdelete` method:"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "kv_store.mdelete(\n",
+ " [\n",
+ " \"key1\",\n",
+ " \"key2\",\n",
+ " ]\n",
+ ")\n",
+ "\n",
+ "kv_store.mget(\n",
+ " [\n",
+ " \"key1\",\n",
+ " \"key2\",\n",
+ " ]\n",
+ ")"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "## TODO: Any functionality specific to this key-value store provider\n",
+ "\n",
+ "E.g. extra initialization. Delete if not relevant."
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "## API reference\n",
+ "\n",
+ "For detailed documentation of all __ModuleName__ByteStore features and configurations, head to the API reference: https://api.python.langchain.com/en/latest/stores/__module_name__.stores.__ModuleName__ByteStore.html"
+ ]
+ }
+ ],
+ "metadata": {
+ "kernelspec": {
+ "display_name": "Python 3",
+ "language": "python",
+ "name": "python3"
+ },
+ "language_info": {
+ "name": "python",
+ "version": "3.10.5"
}
- },
- "source": [
- "---\n",
- "sidebar_label: __ModuleName__ByteStore\n",
- "---"
- ]
},
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "# __ModuleName__ByteStore\n",
- "\n",
- "- TODO: Make sure API reference link is correct.\n",
- "\n",
- "This will help you get started with __ModuleName__ [key-value stores](/docs/concepts/#key-value-stores). For detailed documentation of all __ModuleName__ByteStore features and configurations head to the [API reference](https://python.langchain.com/v0.2/api_reference/core/stores/langchain_core.stores.__module_name__ByteStore.html).\n",
- "\n",
- "- TODO: Add any other relevant links, like information about models, prices, context windows, etc. See https://python.langchain.com/docs/integrations/stores/in_memory/ for an example.\n",
- "\n",
- "## Overview\n",
- "\n",
- "- TODO: (Optional) A short introduction to the underlying technology/API.\n",
- "\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 | [JS support](https://js.langchain.com/docs/integrations/stores/_package_name_) | Package downloads | Package latest |\n",
- "| :--- | :--- | :---: | :---: | :---: | :---: |\n",
- "| [__ModuleName__ByteStore](https://api.python.langchain.com/en/latest/stores/__module_name__.stores.__ModuleName__ByteStore.html) | [__package_name__](https://api.python.langchain.com/en/latest/__package_name_short_snake___api_reference.html) | ✅/❌ | ✅/❌ |  |  |\n",
- "\n",
- "## Setup\n",
- "\n",
- "- TODO: Update with relevant info.\n",
- "\n",
- "To create a __ModuleName__ byte store, 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, or omit if the service does not require any credentials.\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,
- "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",
- "metadata": {},
- "source": [
- "### Installation\n",
- "\n",
- "The LangChain __ModuleName__ integration lives in the `__package_name__` package:"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {},
- "outputs": [],
- "source": [
- "%pip install -qU __package_name__"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "## Instantiation\n",
- "\n",
- "Now we can instantiate our byte store:\n",
- "\n",
- "- TODO: Update model instantiation with relevant params."
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {},
- "outputs": [],
- "source": [
- "from __module_name__ import __ModuleName__ByteStore\n",
- "\n",
- "kv_store = __ModuleName__ByteStore(\n",
- " # params...\n",
- ")"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "## Usage\n",
- "\n",
- "- TODO: Run cells so output can be seen.\n",
- "\n",
- "You can set data under keys like this using the `mset` method:"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {},
- "outputs": [],
- "source": [
- "kv_store.mset(\n",
- " [\n",
- " [\"key1\", b\"value1\"],\n",
- " [\"key2\", b\"value2\"],\n",
- " ]\n",
- ")\n",
- "\n",
- "kv_store.mget(\n",
- " [\n",
- " \"key1\",\n",
- " \"key2\",\n",
- " ]\n",
- ")"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "And you can delete data using the `mdelete` method:"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {},
- "outputs": [],
- "source": [
- "kv_store.mdelete(\n",
- " [\n",
- " \"key1\",\n",
- " \"key2\",\n",
- " ]\n",
- ")\n",
- "\n",
- "kv_store.mget(\n",
- " [\n",
- " \"key1\",\n",
- " \"key2\",\n",
- " ]\n",
- ")"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "## TODO: Any functionality specific to this key-value store provider\n",
- "\n",
- "E.g. extra initialization. Delete if not relevant."
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "## API reference\n",
- "\n",
- "For detailed documentation of all __ModuleName__ByteStore features and configurations, head to the API reference: https://api.python.langchain.com/en/latest/stores/__module_name__.stores.__ModuleName__ByteStore.html"
- ]
- }
- ],
- "metadata": {
- "kernelspec": {
- "display_name": "Python 3",
- "language": "python",
- "name": "python3"
- },
- "language_info": {
- "name": "python",
- "version": "3.10.5"
- }
- },
- "nbformat": 4,
- "nbformat_minor": 2
+ "nbformat": 4,
+ "nbformat_minor": 2
}
diff --git a/libs/cli/langchain_cli/integration_template/docs/tools.ipynb b/libs/cli/langchain_cli/integration_template/docs/tools.ipynb
index 97853ad8669..0310a839850 100644
--- a/libs/cli/langchain_cli/integration_template/docs/tools.ipynb
+++ b/libs/cli/langchain_cli/integration_template/docs/tools.ipynb
@@ -1,271 +1,271 @@
{
- "cells": [
- {
- "cell_type": "raw",
- "id": "10238e62-3465-4973-9279-606cbb7ccf16",
- "metadata": {},
- "source": [
- "---\n",
- "sidebar_label: __ModuleName__\n",
- "---"
- ]
+ "cells": [
+ {
+ "cell_type": "raw",
+ "id": "10238e62-3465-4973-9279-606cbb7ccf16",
+ "metadata": {},
+ "source": [
+ "---\n",
+ "sidebar_label: __ModuleName__\n",
+ "---"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "a6f91f20",
+ "metadata": {},
+ "source": [
+ "# __ModuleName__\n",
+ "\n",
+ "- TODO: Make sure API reference link is correct.\n",
+ "\n",
+ "This notebook provides a quick overview for getting started with __ModuleName__ [tool](/docs/integrations/tools/). For detailed documentation of all __ModuleName__ features and configurations head to the [API reference](https://python.langchain.com/v0.2/api_reference/community/tools/langchain_community.tools.__module_name__.tool.__ModuleName__.html).\n",
+ "\n",
+ "- TODO: Add any other relevant links, like information about underlying API, etc.\n",
+ "\n",
+ "## Overview\n",
+ "\n",
+ "### Integration details\n",
+ "\n",
+ "- TODO: Make sure links and features are correct\n",
+ "\n",
+ "| Class | Package | Serializable | [JS support](https://js.langchain.com/docs/integrations/tools/__module_name__) | Package latest |\n",
+ "| :--- | :--- | :---: | :---: | :---: |\n",
+ "| [__ModuleName__](https://python.langchain.com/v0.2/api_reference/community/tools/langchain_community.tools.__module_name__.tool.__ModuleName__.html) | [langchain-community](https://api.python.langchain.com/en/latest/community_api_reference.html) | beta/❌ | ✅/❌ |  |\n",
+ "\n",
+ "### Tool features\n",
+ "\n",
+ "- TODO: Add feature table if it makes sense\n",
+ "\n",
+ "\n",
+ "## Setup\n",
+ "\n",
+ "- TODO: Add any additional deps\n",
+ "\n",
+ "The integration lives in the `langchain-community` package."
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "f85b4089",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "%pip install --quiet -U langchain-community"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "b15e9266",
+ "metadata": {},
+ "source": [
+ "### Credentials\n",
+ "\n",
+ "- TODO: Add any credentials that are needed"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 2,
+ "id": "e0b178a2-8816-40ca-b57c-ccdd86dde9c9",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "import getpass\n",
+ "import os\n",
+ "\n",
+ "# if not os.environ.get(\"__MODULE_NAME___API_KEY\"):\n",
+ "# os.environ[\"__MODULE_NAME___API_KEY\"] = getpass.getpass(\"__MODULE_NAME__ API key:\\n\")"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "bc5ab717-fd27-4c59-b912-bdd099541478",
+ "metadata": {},
+ "source": [
+ "It's also helpful (but not needed) to set up [LangSmith](https://smith.langchain.com/) for best-in-class observability:"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 3,
+ "id": "a6c2f136-6367-4f1f-825d-ae741e1bf281",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# os.environ[\"LANGSMITH_TRACING\"] = \"true\"\n",
+ "# os.environ[\"LANGSMITH_API_KEY\"] = getpass.getpass()"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "1c97218f-f366-479d-8bf7-fe9f2f6df73f",
+ "metadata": {},
+ "source": [
+ "## Instantiation\n",
+ "\n",
+ "- TODO: Fill in instantiation params\n",
+ "\n",
+ "Here we show how to instantiate an instance of the __ModuleName__ tool, with "
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 4,
+ "id": "8b3ddfe9-ca79-494c-a7ab-1f56d9407a64",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "from langchain_community.tools import __ModuleName__\n",
+ "\n",
+ "\n",
+ "tool = __ModuleName__(...)"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "74147a1a",
+ "metadata": {},
+ "source": [
+ "## Invocation\n",
+ "\n",
+ "### [Invoke directly with args](/docs/concepts/tools/#use-the-tool-directly)\n",
+ "\n",
+ "- TODO: Describe what the tool args are, fill them in, run cell"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "65310a8b-eb0c-4d9e-a618-4f4abe2414fc",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "tool.invoke({...})"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "d6e73897",
+ "metadata": {},
+ "source": [
+ "### [Invoke with ToolCall](/docs/concepts/tool_calling/#tool-execution)\n",
+ "\n",
+ "We can also invoke the tool with a model-generated ToolCall, in which case a ToolMessage will be returned:\n",
+ "\n",
+ "- TODO: Fill in tool args and run cell"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "f90e33a7",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# This is usually generated by a model, but we'll create a tool call directly for demo purposes.\n",
+ "model_generated_tool_call = {\n",
+ " \"args\": {...}, # TODO: FILL IN\n",
+ " \"id\": \"1\",\n",
+ " \"name\": tool.name,\n",
+ " \"type\": \"tool_call\",\n",
+ "}\n",
+ "tool.invoke(model_generated_tool_call)"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "659f9fbd-6fcf-445f-aa8c-72d8e60154bd",
+ "metadata": {},
+ "source": [
+ "## Use within an agent\n",
+ "\n",
+ "- TODO: Add user question and run cells\n",
+ "\n",
+ "We can use our tool in an [agent](/docs/concepts/agents/). For this we will need a LLM with [tool-calling](/docs/how_to/tool_calling/) capabilities:\n",
+ "\n",
+ "import ChatModelTabs from \"@theme/ChatModelTabs\";\n",
+ "\n",
+ "