Adding examples for BigQuery integrations with Anthropic Claude model (GoogleCloudPlatform#1341)

* adding bq integrations with Anthropic Claude model

* adding the bqml claude examples to format checker skiplist given the current helper does not support JDK 21 code.

Author: prodriguezdefino

Diff for: examples/bigquery-ml-claudeintegrations/BQ_RemoteFunction_Sample/CloudFunction/main.py

@@ -0,0 +1,49 @@
+import functions_framework
+from anthropic import AnthropicVertex
+#from flask import jsonify, Flask, request, Response
+import os
+import json
+import flask
+
+
+LOCATION="europe-west1" # or "us-east5"
+
+
+client = AnthropicVertex(region=LOCATION, project_id="[yourprojectid]")
+
+
+@functions_framework.http
+def claude_http(request: flask.Request) -> flask.Response:
+   """HTTP Cloud Function.
+   Args:
+       request (flask.Request): The request object.
+       <https://flask.palletsprojects.com/en/1.1.x/api/#incoming-request-data>
+   Returns:
+       The response text, or any set of values that can be turned into a
+       Response object using `make_response`
+       <https://flask.palletsprojects.com/en/1.1.x/api/#flask.make_response>.
+   """
+   request_json = request.get_json()
+   calls=request_json['calls']
+
+
+   result = []
+   for call in calls:
+     message = client.messages.create(
+       max_tokens=1024,
+       messages=[
+         {
+           "role": "user",
+           "content": str(call),
+         }
+       ],
+       model="claude-3-5-sonnet@20240620",
+     )
+     content_text = message.content[0].text if message.content else ""
+     result.append(content_text)
+  
+   # Return a JSON object with all results
+   return flask.make_response(flask.jsonify({"replies": result}))
+   #return result
+
+

Diff for: examples/bigquery-ml-claudeintegrations/BQ_RemoteFunction_Sample/CloudFunction/requirement.txt

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+functions-framework==3.*
+anthropic[vertex]
+gunicorn==22.0.0
+python-dotenv==1.0.1
+Flask==3.0.3

Diff for: examples/bigquery-ml-claudeintegrations/BQ_RemoteFunction_Sample/README.md

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+# BigQuery Remote Function with Anthropic
+
+This README provides instructions for setting up a BigQuery Remote Function that uses Anthropic's Claude 3.5 Sonnet model via Google Cloud Functions.
+
+## References
+- [BQ Remote function Doc](https://cloud.google.com/bigquery/docs/remote-functions)
+- [Create Cloud Function Doc](https://cloud.google.com/functions/docs/create)
+
+# Required Access
+1. Developer needs to have the following roles:
+   - Cloud Run Developer
+   - Vertex AI User
+   - BigQuery User
+2. Grant Service Accounts IDs access between different services (see Step 2)
+
+## Step 1: Enable Vertex AI API and Enable Claude Models on Vertex AI 
+You can follow this documentation: [Link to Claude On Vertex AI Doc](https://cloud.google.com/vertex-ai/generative-ai/docs/partner-models/use-claude#before_you_begin_)
+
+## Step 2: Create Cloud Function using the [Create Cloud Function Doc](https://cloud.google.com/functions/docs/create)
+You can use the provided Sample Code below or in the /CloudFunction folder in this folder
+### requirements.txt
+```
+functions-framework==3.*
+anthropic[vertex]
+gunicorn==22.0.0
+python-dotenv==1.0.1
+Flask==3.0.3
+```
+
+### main.py
+```python
+import functions_framework
+from anthropic import AnthropicVertex
+import os
+import json
+import flask
+
+LOCATION = "europe-west1"  # or "us-east5"
+
+client = AnthropicVertex(region=LOCATION, project_id="[yourprojectid]")
+
+@functions_framework.http
+def claude_http(request: flask.Request) -> flask.Response:
+    request_json = request.get_json()
+    calls = request_json['calls']
+
+    result = []
+    for call in calls:
+        message = client.messages.create(
+            max_tokens=1024,
+            messages=[
+                {
+                    "role": "user",
+                    "content": str(call),
+                }
+            ],
+            model="claude-3-5-sonnet@20240620",
+        )
+        content_text = message.content[0].text if message.content else ""
+        result.append(content_text)
+    
+    return flask.make_response(flask.jsonify({"replies": result}))
+```
+
+### Test the function with sample event
+```json
+{
+ "calls": [
+   "What is the capital of France?",
+   "Explain the concept of photosynthesis in simple terms.",
+   "Write a haiku about artificial intelligence."
+ ]
+}
+```
+
+## Step 3: Create BQ Remote Function Connection
+Follow the [documentation](https://cloud.google.com/bigquery/docs/remote-functions#create_a_connection) to create a BigQuery Remote Function Connection and set up proper IAM access. Additionally, grant Cloud Run access to the Vertex AI user role.
+
+## Step 4: Create BQ Remote Function
+```sql
+CREATE OR REPLACE FUNCTION
+ `[yourproject].[yourdataset].claude35Sonnet`(prompt STRING) RETURNS STRING
+REMOTE WITH CONNECTION `[yourproject].us.llm_connection`
+OPTIONS (endpoint = 'https://[YOUR Function URI....]', max_batching_rows = 1);
+```
+
+## Step 5: Query the Function
+```sql
+SELECT
+  title,
+  `[yourproject].[yourdataset]`.claude35Sonnet(CONCAT("translate this into English and only return the translated result:", title)) AS translated_title
+FROM [yourprojectid].[your table]
+WHERE title IS NOT NULL 
+LIMIT 1;
+```
+
+This README provides a step-by-step guide to set up and use a BigQuery Remote Function with Anthropic's Claude model.
+