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docs: platform pages update (#14637)
Updated examples and platform pages. - added missed tools - added links and descriptions
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@ -280,6 +280,26 @@ documents = docai_wh_retriever.get_relevant_documents(
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## Tools
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## Tools
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### Google Cloud Text-to-Speech
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>[Google Cloud Text-to-Speech](https://cloud.google.com/text-to-speech) enables developers to
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> synthesize natural-sounding speech with 100+ voices, available in multiple languages and variants.
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> It applies DeepMind’s groundbreaking research in WaveNet and Google’s powerful neural networks
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> to deliver the highest fidelity possible.
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We need to install a python package.
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```bash
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pip install google-cloud-text-to-speech
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```
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See a [usage example and authorization instructions](/docs/integrations/tools/google_cloud_texttospeech).
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```python
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from langchain.tools import GoogleCloudTextToSpeechTool
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```
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### Google Drive
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### Google Drive
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We need to install several python packages.
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We need to install several python packages.
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@ -397,6 +417,7 @@ from langchain.tools.google_trends import GoogleTrendsQueryRun
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from langchain.utilities.google_trends import GoogleTrendsAPIWrapper
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from langchain.utilities.google_trends import GoogleTrendsAPIWrapper
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```
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```
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## Document Transformers
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## Document Transformers
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### Google Document AI
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### Google Document AI
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@ -222,6 +222,9 @@ from langchain.retrievers import AzureCognitiveSearchRetriever
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### Bing Search API
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### Bing Search API
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>[Microsoft Bing](https://www.bing.com/), commonly referred to as `Bing` or `Bing Search`,
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> is a web search engine owned and operated by `Microsoft`.
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See a [usage example](/docs/integrations/tools/bing_search).
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See a [usage example](/docs/integrations/tools/bing_search).
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```python
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```python
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@ -106,3 +106,18 @@ See a [usage example](/docs/integrations/adapters/openai).
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```python
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```python
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from langchain.adapters import openai as lc_openai
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from langchain.adapters import openai as lc_openai
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```
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```
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## Tools
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### Dall-E Image Generator
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>[OpenAI Dall-E](https://openai.com/dall-e-3) are text-to-image models developed by `OpenAI`
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> using deep learning methodologies to generate digital images from natural language descriptions,
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> called "prompts".
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See a [usage example](/docs/integrations/tools/dalle_image_generator).
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```python
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from langchain.utilities.dalle_image_generator import DallEAPIWrapper
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```
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@ -4,7 +4,9 @@
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"cell_type": "markdown",
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"cell_type": "markdown",
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"metadata": {},
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"metadata": {},
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"source": [
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"source": [
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"# Bing Search"
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"# Bing Search\n",
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"\n",
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">[Microsoft Bing](https://www.bing.com/), commonly referred to as `Bing` or `Bing Search`, is a web search engine owned and operated by `Microsoft`."
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]
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]
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},
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},
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{
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{
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@ -180,7 +182,7 @@
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"name": "python",
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"name": "python",
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"nbconvert_exporter": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"pygments_lexer": "ipython3",
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"version": "3.10.9"
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"version": "3.10.12"
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},
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},
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"vscode": {
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"vscode": {
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"interpreter": {
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"interpreter": {
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@ -189,5 +191,5 @@
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}
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}
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},
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},
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"nbformat": 4,
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"nbformat": 4,
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"nbformat_minor": 2
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"nbformat_minor": 4
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}
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}
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@ -7,7 +7,9 @@
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"source": [
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"source": [
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"# Dall-E Image Generator\n",
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"# Dall-E Image Generator\n",
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"\n",
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"\n",
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"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."
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">[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",
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"\n",
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"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."
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]
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]
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},
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},
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{
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{
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@ -169,9 +171,9 @@
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"provenance": []
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"provenance": []
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},
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},
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"kernelspec": {
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"kernelspec": {
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"display_name": "poetry-venv",
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"display_name": "Python 3 (ipykernel)",
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"language": "python",
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"language": "python",
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"name": "poetry-venv"
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"name": "python3"
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},
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},
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"language_info": {
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"language_info": {
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"codemirror_mode": {
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"codemirror_mode": {
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@ -183,7 +185,7 @@
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"name": "python",
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"name": "python",
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"nbconvert_exporter": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"pygments_lexer": "ipython3",
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"version": "3.9.1"
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"version": "3.10.12"
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},
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},
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"vscode": {
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"vscode": {
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"interpreter": {
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"interpreter": {
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@ -7,6 +7,8 @@
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"source": [
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"source": [
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"# Google Cloud Text-to-Speech\n",
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"# Google Cloud Text-to-Speech\n",
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"\n",
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"\n",
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">[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",
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"\n",
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"This notebook shows how to interact with the `Google Cloud Text-to-Speech API` to achieve speech synthesis capabilities."
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"This notebook shows how to interact with the `Google Cloud Text-to-Speech API` to achieve speech synthesis capabilities."
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]
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]
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},
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},
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@ -86,7 +88,7 @@
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"name": "python",
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"name": "python",
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"nbconvert_exporter": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"pygments_lexer": "ipython3",
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"version": "3.11.0"
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"version": "3.10.12"
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}
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}
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},
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},
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"nbformat": 4,
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"nbformat": 4,
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