community: add AzureOpenAIWhisperParser (#27796)

Commandeered from https://github.com/langchain-ai/langchain/pull/26757.

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Co-authored-by: Sheepsta300 <128811766+Sheepsta300@users.noreply.github.com>

docs/docs/integrations/document_loaders/parsers/azure_openai_whisper_parser.ipynb

@@ -0,0 +1,192 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Azure OpenAI Whisper Parser"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    ">[Azure OpenAI Whisper Parser](https://learn.microsoft.com/en-us/azure/ai-services/speech-service/whisper-overview) is a wrapper around the Azure OpenAI Whisper API which utilizes machine learning to transcribe audio files to english text. \n",
+    ">\n",
+    ">The Parser supports `.mp3`, `.mp4`, `.mpeg`, `.mpga`, `.m4a`, `.wav`, and `.webm`.\n",
+    "\n",
+    "The current implementation follows LangChain core principles and can be used with other loaders to handle both audio downloading and parsing. As a result of this the parser will `yield` an `Iterator[Document]`."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Prerequisites"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The service requires Azure credentials, Azure endpoint and Whisper Model deployment, which can be set up by following the guide [here](https://learn.microsoft.com/en-us/azure/ai-services/openai/whisper-quickstart?tabs=command-line%2Cpython-new%2Cjavascript&pivots=programming-language-python). Furthermore, the required dependencies must be installed.\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "%pip install -Uq  langchain langchain-community openai"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Example 1"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The `AzureOpenAIWhisperParser`'s method, `.lazy_parse`, accepts a `Blob` object as a parameter containing the file path of the file to be transcribed."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from langchain_core.documents.base import Blob\n",
+    "\n",
+    "audio_path = \"path/to/your/audio/file\"\n",
+    "audio_blob = Blob(path=audio_path)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from langchain_community.document_loaders.parsers.audio import AzureOpenAIWhisperParser\n",
+    "\n",
+    "endpoint = \"<your_endpoint>\"\n",
+    "key = \"<your_api_key\"\n",
+    "version = \"<your_api_version>\"\n",
+    "name = \"<your_deployment_name>\"\n",
+    "\n",
+    "parser = AzureOpenAIWhisperParser(\n",
+    "    api_key=key, azure_endpoint=endpoint, api_version=version, deployment_name=name\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "documents = parser.lazy_parse(blob=audio_blob)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "for doc in documents:\n",
+    "    print(doc.page_content)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Example 2"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The `AzureOpenAIWhisperParser` can also be used in conjuction with audio loaders, like the `YoutubeAudioLoader` with a `GenericLoader`."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from langchain_community.document_loaders.blob_loaders.youtube_audio import (\n",
+    "    YoutubeAudioLoader,\n",
+    ")\n",
+    "from langchain_community.document_loaders.generic import GenericLoader"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Must be a list\n",
+    "url = [\"www.youtube.url.com\"]\n",
+    "\n",
+    "save_dir = \"save/directory/\""
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "name = \"<your_deployment_name>\"\n",
+    "\n",
+    "loader = GenericLoader(\n",
+    "    YoutubeAudioLoader(url, save_dir), AzureOpenAIWhisperParser(deployment_name=name)\n",
+    ")\n",
+    "\n",
+    "docs = loader.load()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "for doc in documents:\n",
+    "    print(doc.page_content)"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "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": "3.12.6"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}