docs: add bigquery integration (#8024)

* docs: add bigquery integration

* link-to-datasets

* cleanup

* remove-description-tags

docs/docs/Integrations/Google/integrations-google-big-query.md

@@ -0,0 +1,85 @@
+---
+title: Integrate Google BigQuery with Langflow
+slug: /integrations-google-big-query
+---
+
+import Tabs from '@theme/Tabs';
+import TabItem from '@theme/TabItem';
+
+Langflow integrates with [Google BigQuery](https://cloud.google.com/bigquery) through the BigQuery component, allowing you to execute SQL queries and retrieve data from your BigQuery datasets.
+
+## Prerequisites
+
+* A [Google Cloud project](https://developers.google.com/workspace/guides/create-project) with the BigQuery API enabled
+* A [service account](https://developers.google.com/workspace/guides/create-credentials#service-account) with the **BigQuery Job User** role
+* A [BigQuery dataset and table](https://cloud.google.com/bigquery/docs/datasets-intro)
+
+## Create a service account with BigQuery access
+
+1. Select and enable your Google Cloud project.
+For more information, see [Create a Google Cloud project](https://developers.google.com/workspace/guides/create-project).
+2. Create a service account in your Google Cloud project.
+For more information, see [Create a service account](https://developers.google.com/workspace/guides/create-credentials#service-account).
+3. Assign the **BigQuery Job User** role to your new account.
+This role allows Langflow to access BigQuery resources with the service account.
+You may also need to allow access to your BigQuery dataset.
+For more information, see [BigQuery access control with IAM](https://cloud.google.com/bigquery/docs/access-control).
+4. To generate a new JSON key for the service account, navigate to your service account.
+5. Click **Add Key**, and then click **Create new key**.
+6. Under **Key type**, select **JSON**, and then click **Create**.
+A JSON private key file is downloaded to your machine.
+Now that you have a service account and a JSON private key, you need to configure the credentials in the Langflow BigQuery component.
+
+## Configure credentials in the Langflow component
+
+With your service account configured and your credentials JSON file created, follow these steps to authenticate the Langflow application.
+
+1. Create a new project in Langflow.
+2. From the components sidebar, drag and drop the BigQuery component to your workspace.
+3. In the BigQuery component's **Upload Service Account JSON** field, click **Select file**.
+4. In the **My Files** pane, select **Click or drag files here**.
+Your file browser opens.
+5. In your file browser, select the service account JSON file, and then click **Open**.
+6. In the **My Files** pane, select your service account JSON file, and then click **Select files**.
+The BigQuery component can now query your datasets and tables using your service account JSON file.
+
+## Query a BigQuery dataset
+
+With your component credentials configured, query your BigQuery datasets and tables to confirm connectivity.
+
+1. Connect a **Chat input** and **Chat output** component to the BigQuery component.
+The flow looks like this:
+![BigQuery component connected to chat input and output](/img/google/integrations-bigquery.png)
+2. Open the **Playground**, and then submit a valid SQL query.
+This example queries a table of Oscar winners stored within a BigQuery dataset called `the_oscar_award`.
+    <Tabs>
+      <TabItem value="sql query" label="SQL query" default>
+
+    ```sql
+    SELECT film, category, year_film
+    FROM `big-query-langflow-project.the_oscar_award.oscar_winners`
+    WHERE winner = TRUE
+    LIMIT 10
+    ```
+
+      </TabItem>
+      <TabItem value="result" label="Result">
+
+    ```text
+    film	category	year_film
+    The Last Command	ACTOR	1927
+    7th Heaven	ACTRESS	1927
+    The Dove;	ART DIRECTION	1927
+    Sunrise	CINEMATOGRAPHY	1927
+    Sunrise	CINEMATOGRAPHY	1927
+    Two Arabian Knights	DIRECTING (Comedy Picture)	1927
+    7th Heaven	DIRECTING (Dramatic Picture)	1927
+    Wings	ENGINEERING EFFECTS	1927
+    Wings	OUTSTANDING PICTURE	1927
+    Sunrise	UNIQUE AND ARTISTIC PICTURE	1927
+    ```
+      </TabItem>
+    </Tabs>
+
+    A successful chat confirms the component can access the BigQuery table.
+

docs/docs/Integrations/Google/integrations-setup-google-cloud-vertex-ai-langflow.md

@@ -1,7 +1,6 @@
 ---
 title: Integrate Google Cloud Vertex AI with Langflow
 slug: /integrations-setup-google-cloud-vertex-ai-langflow
-description: "A comprehensive guide on creating a Google OAuth app, obtaining tokens, and integrating them with Langflow's Google components."
 ---
 
 Langflow integrates with the [Google Vertex AI API](https://console.cloud.google.com/marketplace/product/google/aiplatform.googleapis.com) for authenticating the [Vertex AI embeddings model](/components-embedding-models#vertexai-embeddings) and [Vertex AI](/components-models#vertexai) components.

docs/docs/Integrations/Google/integrations-setup-google-oauth-langflow.md

@@ -1,8 +1,6 @@
 ---
 title: Integrate Google OAuth with Langflow
 slug: /integrations-setup-google-oauth-langflow
-
-description: "A comprehensive guide on creating a Google OAuth app, obtaining tokens, and integrating them with Langflow's Google components."
 ---
 
 import TOCInline from '@theme/TOCInline';

docs/sidebars.js

@@ -198,6 +198,7 @@ module.exports = {
           items: [
             'Integrations/Google/integrations-setup-google-oauth-langflow',
             'Integrations/Google/integrations-setup-google-cloud-vertex-ai-langflow',
+            'Integrations/Google/integrations-google-big-query',
           ],
         },
         "Integrations/integrations-langfuse",