📖 docs: fixed `integration/llms` navbar (#9277)

Fixed navbar:
- renamed several files, so ToC is sorted correctly
- made ToC items consistent: formatted several Titles
- added several links
- reformatted several docs to a consistent format
- renamed several files (removed `_example` suffix)
- added renamed files to the `docs/docs_skeleton/vercel.json`

docs/docs_skeleton/vercel.json

@@ -2952,6 +2952,46 @@
       "source": "/docs/modules/model_io/models/llms/integrations/writer",
       "destination": "/docs/integrations/llms/writer"
     },
+    {
+      "source": "/docs/integrations/llms/amazon_api_gateway_example",
+      "destination": "/docs/integrations/llms/amazon_api_gateway"
+    },
+    {
+      "source": "/docs/integrations/llms/azureml_endpoint_example",
+      "destination": "/docs/integrations/llms/azure_ml"
+    },
+    {
+      "source": "/docs/integrations/llms/azure_openai_example",
+      "destination": "/docs/integrations/llms/azure_openai"
+    },
+    {
+      "source": "/docs/integrations/llms/cerebriumai_example",
+      "destination": "/docs/integrations/llms/cerebriumai"
+    },
+    {
+      "source": "/docs/integrations/llms/deepinfra_example",
+      "destination": "/docs/integrations/llms/deepinfra"
+    },
+    {
+      "source": "/docs/integrations/llms/Fireworks",
+      "destination": "/docs/integrations/llms/fireworks"
+    },
+    {
+      "source": "/docs/integrations/llms/forefrontai_example",
+      "destination": "/docs/integrations/llms/forefrontai"
+    },
+    {
+      "source": "/docs/integrations/llms/gooseai_example",
+      "destination": "/docs/integrations/llms/gooseai"
+    },
+    {
+      "source": "/docs/integrations/llms/petals_example",
+      "destination": "/docs/integrations/llms/petals"
+    },
+    {
+      "source": "/docs/integrations/llms/pipelineai_example",
+      "destination": "/docs/integrations/llms/pipelineai"
+    },
     {
       "source": "/en/latest/modules/prompts.html",
       "destination": "/docs/modules/model_io/prompts"

docs/extras/integrations/llms/amazon_api_gateway.ipynb

@@ -221,9 +221,9 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.8.15"
+   "version": "3.10.12"
   }
  },
  "nbformat": 4,
- "nbformat_minor": 1
+ "nbformat_minor": 4
 }

docs/extras/integrations/llms/azure_ml.ipynb

@@ -4,9 +4,9 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "# AzureML Online Endpoint\n",
+    "# Azure ML\n",
     "\n",
-    "[AzureML](https://azure.microsoft.com/en-us/products/machine-learning/) is a platform used to build, train, and deploy machine learning models. Users can explore the types of models to deploy in the Model Catalog, which provides Azure Foundation Models and OpenAI Models. Azure Foundation Models include various open-source models and popular Hugging Face models. Users can also import models of their liking into AzureML.\n",
+    "[Azure ML](https://azure.microsoft.com/en-us/products/machine-learning/) is a platform used to build, train, and deploy machine learning models. Users can explore the types of models to deploy in the Model Catalog, which provides Azure Foundation Models and OpenAI Models. Azure Foundation Models include various open-source models and popular Hugging Face models. Users can also import models of their liking into AzureML.\n",
     "\n",
     "This notebook goes over how to use an LLM hosted on an `AzureML online endpoint`"
    ]
@@ -236,9 +236,9 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.11.3"
+   "version": "3.10.12"
   }
  },
  "nbformat": 4,
- "nbformat_minor": 2
+ "nbformat_minor": 4
 }

docs/extras/integrations/llms/azure_openai.ipynb

@@ -216,7 +216,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.11.3"
+   "version": "3.10.12"
   },
   "vscode": {
    "interpreter": {

docs/extras/integrations/llms/octoai.ipynb

@@ -1,13 +1,16 @@
 {
  "cells": [
   {
-   "attachments": {},
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "# OctoAI Compute Service\n",
+    "# OctoAI\n",
+    "\n",
+    ">[OctoML](https://docs.octoai.cloud/docs) is a service with efficient compute. It enables users to integrate their choice of AI models into applications. The `OctoAI` compute service helps you run, tune, and scale AI applications.\n",
+    "\n",
     "This example goes over how to use LangChain to interact with `OctoAI` [LLM endpoints](https://octoai.cloud/templates)\n",
-    "## Environment setup\n",
+    "\n",
+    "## Setup\n",
     "\n",
     "To run our example app, there are four simple steps to take:\n",
     "\n",
@@ -43,6 +46,13 @@
     "from langchain import PromptTemplate, LLMChain"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Example"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": 15,
@@ -98,7 +108,7 @@
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "langchain",
+   "display_name": "Python 3 (ipykernel)",
    "language": "python",
    "name": "python3"
   },
@@ -112,9 +122,8 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.16"
+   "version": "3.10.12"
   },
-  "orig_nbformat": 4,
   "vscode": {
    "interpreter": {
     "hash": "97697b63fdcee0a640856f91cb41326ad601964008c341809e43189d1cab1047"
@@ -122,5 +131,5 @@
   }
  },
  "nbformat": 4,
- "nbformat_minor": 2
+ "nbformat_minor": 4
 }

docs/extras/integrations/llms/petals.ipynb

@@ -186,7 +186,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.10.6"
+   "version": "3.10.12"
   },
   "vscode": {
    "interpreter": {

docs/extras/integrations/llms/pipelineai.ipynb

@@ -1,23 +1,25 @@
 {
  "cells": [
   {
-   "attachments": {},
    "cell_type": "markdown",
    "metadata": {},
    "source": [
     "# PipelineAI\n",
     "\n",
-    "PipelineAI allows you to run your ML models at scale in the cloud. It also provides API access to [several LLM models](https://pipeline.ai).\n",
+    ">[PipelineAI](https://pipeline.ai) allows you to run your ML models at scale in the cloud. It also provides API access to [several LLM models](https://pipeline.ai).\n",
     "\n",
-    "This notebook goes over how to use Langchain with [PipelineAI](https://docs.pipeline.ai/docs)."
+    "This notebook goes over how to use Langchain with [PipelineAI](https://docs.pipeline.ai/docs).\n",
+    "\n",
+    "## PipelineAI example\n",
+    "\n",
+    "[This example shows how PipelineAI integrated with LangChain](https://docs.pipeline.ai/docs/langchain) and it is created by PipelineAI."
    ]
   },
   {
-   "attachments": {},
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "## Install pipeline-ai\n",
+    "## Setup\n",
     "The `pipeline-ai` library is required to use the `PipelineAI` API, AKA `Pipeline Cloud`. Install `pipeline-ai` using `pip install pipeline-ai`."
    ]
   },
@@ -35,7 +37,9 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "## Imports"
+    "## Example\n",
+    "\n",
+    "### Imports"
    ]
   },
   {
@@ -50,11 +54,10 @@
    ]
   },
   {
-   "attachments": {},
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "## Set the Environment API Key\n",
+    "### Set the Environment API Key\n",
     "Make sure to get your API key from PipelineAI. Check out the [cloud quickstart guide](https://docs.pipeline.ai/docs/cloud-quickstart). You'll be given a 30 day free trial with 10 hours of serverless GPU compute to test different models."
    ]
   },
@@ -68,7 +71,6 @@
    ]
   },
   {
-   "attachments": {},
    "cell_type": "markdown",
    "metadata": {},
    "source": [
@@ -89,7 +91,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "## Create a Prompt Template\n",
+    "### Create a Prompt Template\n",
     "We will create a prompt template for Question and Answer."
    ]
   },
@@ -110,7 +112,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "## Initiate the LLMChain"
+    "### Initiate the LLMChain"
    ]
   },
   {
@@ -126,7 +128,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "## Run the LLMChain\n",
+    "### Run the LLMChain\n",
     "Provide a question and run the LLMChain."
    ]
   },
@@ -158,7 +160,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.10.6"
+   "version": "3.10.12"
   },
   "vscode": {
    "interpreter": {

docs/extras/integrations/llms/titan_takeoff.ipynb

@@ -1,19 +1,17 @@
 {
  "cells": [
   {
-   "attachments": {},
    "cell_type": "markdown",
    "metadata": {},
    "source": [
     "# Titan Takeoff\n",
     "\n",
-    "TitanML helps businesses build and deploy better, smaller, cheaper, and faster NLP models through our training, compression, and inference optimization platform. \n",
+    ">`TitanML` helps businesses build and deploy better, smaller, cheaper, and faster NLP models through our training, compression, and inference optimization platform. \n",
     "\n",
-    "Our inference server, [Titan Takeoff](https://docs.titanml.co/docs/titan-takeoff/getting-started) enables deployment of LLMs locally on your hardware in a single command. Most generative model architectures are supported, such as Falcon, Llama 2, GPT2, T5 and many more."
+    ">Our inference server, [Titan Takeoff](https://docs.titanml.co/docs/titan-takeoff/getting-started) enables deployment of LLMs locally on your hardware in a single command. Most generative model architectures are supported, such as Falcon, Llama 2, GPT2, T5 and many more."
    ]
   },
   {
-   "attachments": {},
    "cell_type": "markdown",
    "metadata": {},
    "source": [
@@ -40,7 +38,6 @@
    ]
   },
   {
-   "attachments": {},
    "cell_type": "markdown",
    "metadata": {},
    "source": [
@@ -72,7 +69,6 @@
    ]
   },
   {
-   "attachments": {},
    "cell_type": "markdown",
    "metadata": {},
    "source": [
@@ -103,7 +99,6 @@
    ]
   },
   {
-   "attachments": {},
    "cell_type": "markdown",
    "metadata": {},
    "source": [
@@ -130,7 +125,6 @@
    ]
   },
   {
-   "attachments": {},
    "cell_type": "markdown",
    "metadata": {},
    "source": [
@@ -159,11 +153,24 @@
   }
  ],
  "metadata": {
-  "language_info": {
-   "name": "python"
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
   },
-  "orig_nbformat": 4
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.10.12"
+  }
  },
  "nbformat": 4,
- "nbformat_minor": 2
+ "nbformat_minor": 4
 }