add gemini documentation

docs/components/connectors/out-of-the-box-connectors/available-connectors-overview.md

@@ -47,6 +47,7 @@ import TabItem from "@theme/TabItem";
 - [Google Drive Connector](/components/connectors/out-of-the-box-connectors/googledrive.md) - Create folders or files from a [Google Drive](https://www.google.com/drive/) template from your BPMN process.
 - [Google Maps Platform Connector](/components/connectors/out-of-the-box-connectors/google-maps-platform.md) - Validate addresses, retrieve postal addresses, and calculate distances with [Google Maps Platform Service](https://mapsplatform.google.com/) from your BPMN process
 - [Google Sheets Connector](/components/connectors/out-of-the-box-connectors/google-sheets.md) - Allows you to work with an existing or new empty spreadsheet on [Google Drive](https://drive.google.com/) from your BPMN process.
+- [Google Gemini Connector](/components/connectors/out-of-the-box-connectors/google-gemini.md) - Allows you to work with an existing or new empty spreadsheet on [Google Drive](https://drive.google.com/) from your BPMN process.
 - [Hugging Face Connector](/components/connectors/out-of-the-box-connectors/hugging-face.md) - Interact with [Hugging Face](https://huggingface.co/) models from your BPMN process.
 - [Kafka Producer Connector](/components/connectors/out-of-the-box-connectors/kafka.md) - Produce messages to [Kafka](https://kafka.apache.org/) from your BPMN process.
 - [Microsoft Teams Connector](/components/connectors/out-of-the-box-connectors/microsoft-teams.md) - Interactions with [Microsoft Teams](https://www.microsoft.com/microsoft-teams/) from your BPMN process.

docs/components/connectors/out-of-the-box-connectors/google-gemini.md

@@ -0,0 +1,227 @@
+---
+id: google-gemini
+title: Google Gemini Connector
+sidebar_label: Google Gemini Connector
+description: The Gemini large language models (LLMs) that are used by Gemini for Google Cloud are trained on datasets of publicly available code, Google Cloud-specific material, and other relevant technical information in addition to the datasets used to train the Gemini [foundation models](https://storage.googleapis.com/deepmind-media/gemini/gemini_1_report.pdf).
+---
+
+:::info
+The **Google Gemini Connector** is available for `8.7.0` or later.
+:::
+
+The **Google Gemini Connector** in an outbound Connector that allows you to access to Gemini multimodal models from Google, capable of understanding virtually any input, combining different types of information in BPMN process.
+
+## Create a Google Gemini Connector task
+
+import ConnectorTask from '../../../components/react-components/connector-task.md'
+
+<ConnectorTask/>
+
+## Make your Google Gemini Connector executable
+
+To execute the Google Gemini Connector, ensure all mandatory fields are correctly filled.
+
+:::note
+All the mandatory and non-mandatory fields and required settings depending on the operation selection you choose are covered in the upcoming sections.
+:::
+
+## 1. Authentication
+
+Choose an authentication type from the **Type** dropdown. For details on the different authentication types, refer to the [appendix](#google-authentication-types).
+
+## 2. Project ID
+
+Input your google cloud project identifier.
+
+## 3. Region
+
+Input region where you project located (for example, `us-central1 (lowa)`, `us-west1 (Oregon)`).
+
+## 4. Model
+
+Select model from dropdown, list of supported models below.
+
+- _gemini-1.5-flash-001_
+- _gemini-1.5-flash-002_
+- _gemini-1.5-pro-001_
+- _gemini-1.5-pro-002_
+- _gemini-1.0-pro-001_
+- _gemini-1.0-pro-002_
+- _gemini-1.0-pro-vision-001_
+
+## 5. Prompt
+
+Prompt should be inserted as feel expression where you can provide text and media.
+
+- If you want to provide text to gemini, then expression should contains key _"text"_ and text data. Like _"text"_ : _"your text"_
+- If you want to provide media to gemini, then expression should contains key _"mime"_ and mime type text, key _"uri"_ and media uri.
+  Like _"mime"_: _"mime type"_, _"uri"_: _"your uri"_.
+
+**Example:**
+
+```feel
+= [{"text": "who is this video about"},
+{"mime": "video/*", "uri": "https://youtu.be/..."}]
+```
+
+## 6. System instructions
+
+Input system instructions as string. System instructions inform how the model should respond. More info [here](https://cloud.google.com/vertex-ai/generative-ai/docs/learn/prompts/system-instructions?hl=en).
+
+## 7. Grounding
+
+Grounding connects model output to verifiable sources of information. This is useful in situations where accuracy and reliability are important. [Learn more about grounding](https://cloud.google.com/vertex-ai/generative-ai/docs/grounding/overview?hl=en).
+
+If you want to use grounding, select the _Grounding_ checkbox and input the path to the data store.
+
+## 8. Safety Filter Settings
+
+You can adjust the likelihood of receiving a model response that could contain harmful content. Content is blocked based on the probability that it's harmful.
+[Learn more](https://cloud.google.com/vertex-ai/docs/generative-ai/learn/responsible-ai?hl=en#safety_filters_and_attributes).
+
+If you want to use safety filter settings, select the _Safety Filter Settings_ checkbox and select the desired level from dropdown.
+
+:::note
+By default, all filters are set to OFF.
+:::
+
+## 9. Add stop sequence
+
+A stop sequence is a series of characters (including spaces) that stops response generation if the model encounters it.
+Stop sequence should be inserted as list of string.
+
+**Example:**
+
+```feel
+= ["text 1", "text 2"]
+```
+
+## 10. Temperature
+
+**Temperature** controls the randomness in token selection.
+
+- A lower temperature is good when you expect a true or correct response. A temperature of 0 means the highest probability token is usually selected.
+- A higher temperature can lead to diverse or unexpected results. Some models have a higher temperature max to encourage more random responses.
+
+## 11. Output token limit
+
+**Output token limit** determines the maximum amount of text output from one prompt. A token is approximately four characters.
+
+## 12. Seed
+
+Setting a **Seed** value is useful when you make repeated requests and want the same model response.
+
+Deterministic outcome isn’t guaranteed. Changing the model or other settings can cause variations in the response
+even when you use the same seed value.
+
+## 13. Top-K
+
+**Top-K** specifies the number of candidate tokens when the model is selecting an output token.
+Use a lower value for less random responses and a higher value for more random responses.
+
+:::note
+Only _gemini-1.0-pro-vision-001_ model supports Top-K .
+:::
+
+## 14. Top-P
+
+**Top-P** changes how the model selects tokens for output. Tokens are selected from most probable to least until the sum of their probabilities equals the top-p value.
+For example, if tokens A, B, and C have a probability of .3, .2, and .1 and the top-p value is .5, then the model will select either A or B as the next token (using temperature).
+For the least variable results, set top-P to 0.
+
+## 15 Functional call description
+
+**Function calling** is a feature of Gemini models that makes it easier for developers to get structured data outputs from generative models.
+**Functional call description** must be provided in fell format. [More info here](https://cloud.google.com/vertex-ai/generative-ai/docs/multimodal/function-calling).
+
+:::note
+It is important that all types must be registered with capslock.
+:::
+
+**Example:**
+
+```fell
+[
+  {
+    "name": "get_exchange_rate",
+    "description":"Get the exchange rate for currencies between countries",
+    "parameters": {
+      "type": "OBJECT",
+      "properties": {
+        "currency_date": {
+          "type": "STRING",
+          "description": "A date that must always be in YYYY-MM-DD format or the value 'latest' if a time period is not specified"
+        },
+        "currency_from": {
+          "type": "STRING",
+          "description": "The currency to convert from in ISO 4217 format"
+        },
+        "currency_to": {
+          "type": "STRING",
+          "description": "The currency to convert to in ISO 4217 format"
+        }
+      },
+      "required":[
+        "currency_date",
+        "currency_from",
+        "currency_to"
+      ]
+    }
+  }
+]
+```
+
+### Google authentication types
+
+The **Google Gemini Connector** currently supports two methods for authentication and authorization: based on short-lived JWT bearer token, and based on refresh token.
+
+Google supports multiple ways to obtain both. Refer to the [official Google OAuth documentation](https://developers.google.com/identity/protocols/oauth2) to get up-to-date instructions or refer to the examples below.
+
+#### Example 1: Obtaining JWT bearer token with a service account
+
+:::warning
+The following code snippet is for demonstration purposes only and must not be used for real production systems due to security concerns.
+For production usage, follow the [official Google guidelines](https://developers.google.com/identity/protocols/oauth2/service-account).
+:::
+
+Assuming you have created a service account and downloaded a JSON file with keys, run the following Python 3 snippet that prints the JWT token in the terminal:
+
+```python
+import google.auth
+import google.auth.transport.requests
+from google.oauth2 import service_account
+# Scopes required to execute 'create' endpoind with Google Drive API
+SCOPES = ['https://www.googleapis.com/auth/drive', 'https://www.googleapis.com/auth/drive.file', 'https://www.googleapis.com/auth/drive.appdata']
+# File with keys
+SERVICE_ACCOUNT_FILE = 'google-service-account-creds.json'
+credentials = service_account.Credentials.from_service_account_file(SERVICE_ACCOUNT_FILE, scopes=SCOPES)
+auth_req = google.auth.transport.requests.Request()
+credentials.refresh(auth_req)
+# Print token
+print(credentials.token)
+```
+
+#### Example 2: Obtaining bearer and refresh tokens with OAuth client
+
+:::warning
+The following code snippet is for demonstration purposes only and must not be used for real production systems due to security concerns.
+For production usage, follow the [official Google guidelines](https://developers.google.com/identity/protocols/oauth2/web-server).
+:::
+
+Assuming you have created an OAuth client, you can download key files from the Google [Console](https://console.cloud.google.com/apis/credentials). Run the following Python 3 snippet that prints the refresh token in the terminal:
+
+```python
+from google_auth_oauthlib.flow import InstalledAppFlow
+import pprint
+
+SCOPES = ['https://www.googleapis.com/auth/drive', 'https://www.googleapis.com/auth/documents']
+OAUTH_KEYS = './oauth-keys.json' # path to your file with OAuth credentials
+
+def main():
+    flow = InstalledAppFlow.from_client_secrets_file(OAUTH_KEYS, SCOPES)
+    creds = flow.run_local_server(port=54948)
+    pprint.pprint(vars(creds))
+
+if __name__ == "__main__":
+    main()
+```

optimize_sidebars.js

@@ -964,6 +964,10 @@ module.exports = {
                   "Google Sheets Connector",
                   "components/connectors/out-of-the-box-connectors/google-sheets/"
                 ),
+                docsLink(
+                  "Google Gemini Connector",
+                  "components/connectors/out-of-the-box-connectors/google-gemini/"
+                ),
               ],
             },
 

sidebars.js

@@ -339,6 +339,7 @@ module.exports = {
                 "components/connectors/out-of-the-box-connectors/googledrive",
                 "components/connectors/out-of-the-box-connectors/google-maps-platform",
                 "components/connectors/out-of-the-box-connectors/google-sheets",
+                "components/connectors/out-of-the-box-connectors/google-gemini",
               ],
             },
             "components/connectors/out-of-the-box-connectors/hugging-face",