docs: platform pages update (#14637)

Updated examples and platform pages. - added missed tools - added links and descriptions
langchain-ai · Dec 13, 2023 · 0d6471c · 0d6471c
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diff --git a/docs/docs/integrations/platforms/google.mdx b/docs/docs/integrations/platforms/google.mdx
@@ -280,6 +280,26 @@ documents = docai_wh_retriever.get_relevant_documents(
 
 ## Tools
 
+### Google Cloud Text-to-Speech
+
+>[Google Cloud Text-to-Speech](https://cloud.google.com/text-to-speech) enables developers to 
+> synthesize natural-sounding speech with 100+ voices, available in multiple languages and variants. 
+> It applies DeepMind’s groundbreaking research in WaveNet and Google’s powerful neural networks 
+> to deliver the highest fidelity possible.
+
+We need to install a python package.
+
+```bash
+pip install google-cloud-text-to-speech
+```
+
+See a [usage example and authorization instructions](/docs/integrations/tools/google_cloud_texttospeech).
+
+```python
+from langchain.tools import GoogleCloudTextToSpeechTool
+```
+
+
 ### Google Drive
 
 We need to install several python packages.
@@ -397,6 +417,7 @@ from langchain.tools.google_trends import GoogleTrendsQueryRun
 from langchain.utilities.google_trends import GoogleTrendsAPIWrapper
 ```
 
+
 ## Document Transformers
 
 ### Google Document AI

diff --git a/docs/docs/integrations/platforms/microsoft.mdx b/docs/docs/integrations/platforms/microsoft.mdx
@@ -222,6 +222,9 @@ from langchain.retrievers import AzureCognitiveSearchRetriever
 
 ### Bing Search API
 
+>[Microsoft Bing](https://www.bing.com/), commonly referred to as `Bing` or `Bing Search`, 
+> is a web search engine owned and operated by `Microsoft`.
+
 See a [usage example](/docs/integrations/tools/bing_search).
 
 ```python

diff --git a/docs/docs/integrations/platforms/openai.mdx b/docs/docs/integrations/platforms/openai.mdx
@@ -106,3 +106,18 @@ See a [usage example](/docs/integrations/adapters/openai).
 ```python
 from langchain.adapters import openai as lc_openai
 ```
+
+## Tools
+
+### Dall-E Image Generator
+
+>[OpenAI Dall-E](https://openai.com/dall-e-3) are text-to-image models developed by `OpenAI` 
+> using deep learning methodologies to generate digital images from natural language descriptions, 
+> called "prompts".
+
+
+See a [usage example](/docs/integrations/tools/dalle_image_generator).
+
+```python
+from langchain.utilities.dalle_image_generator import DallEAPIWrapper
+```
diff --git a/docs/docs/integrations/tools/bing_search.ipynb b/docs/docs/integrations/tools/bing_search.ipynb
@@ -4,7 +4,9 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "# Bing Search"
+    "# Bing Search\n",
+    "\n",
+    ">[Microsoft Bing](https://www.bing.com/), commonly referred to as `Bing` or `Bing Search`, is a web search engine owned and operated by `Microsoft`."
    ]
   },
   {
@@ -180,7 +182,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.10.9"
+   "version": "3.10.12"
   },
   "vscode": {
    "interpreter": {
@@ -189,5 +191,5 @@
   }
  },
  "nbformat": 4,
- "nbformat_minor": 2
+ "nbformat_minor": 4
 }
diff --git a/docs/docs/integrations/tools/dalle_image_generator.ipynb b/docs/docs/integrations/tools/dalle_image_generator.ipynb
@@ -7,7 +7,9 @@
    "source": [
     "# Dall-E Image Generator\n",
     "\n",
-    "This notebook shows how you can generate images from a prompt synthesized using an OpenAI LLM. The images are generated using Dall-E, which uses the same OpenAI API key as the LLM."
+    ">[OpenAI Dall-E](https://openai.com/dall-e-3) are text-to-image models developed by `OpenAI` using deep learning methodologies to generate digital images from natural language descriptions, called \"prompts\".\n",
+    "\n",
+    "This notebook shows how you can generate images from a prompt synthesized using an OpenAI LLM. The images are generated using `Dall-E`, which uses the same OpenAI API key as the LLM."
    ]
   },
   {
@@ -169,9 +171,9 @@
    "provenance": []
   },
   "kernelspec": {
-   "display_name": "poetry-venv",
+   "display_name": "Python 3 (ipykernel)",
    "language": "python",
-   "name": "poetry-venv"
+   "name": "python3"
   },
   "language_info": {
    "codemirror_mode": {
@@ -183,7 +185,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.1"
+   "version": "3.10.12"
   },
   "vscode": {
    "interpreter": {

diff --git a/docs/docs/integrations/tools/google_cloud_texttospeech.ipynb b/docs/docs/integrations/tools/google_cloud_texttospeech.ipynb
@@ -7,6 +7,8 @@
    "source": [
     "# Google Cloud Text-to-Speech\n",
     "\n",
+    ">[Google Cloud Text-to-Speech](https://cloud.google.com/text-to-speech) enables developers to synthesize natural-sounding speech with 100+ voices, available in multiple languages and variants. It applies DeepMind’s groundbreaking research in WaveNet and Google’s powerful neural networks to deliver the highest fidelity possible.\n",
+    "\n",
     "This notebook shows how to interact with the `Google Cloud Text-to-Speech API` to achieve speech synthesis capabilities."
    ]
   },
@@ -86,7 +88,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.11.0"
+   "version": "3.10.12"
   }
  },
  "nbformat": 4,