gemini/use-cases/applying-llms-to-data/using-gemini-with-bigquery-remote-functions/function/text/main.py (35 lines of code) (raw):
# Copyright 2023 Google LLC
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
# http://www.apache.org/licenses/LICENSE-2.0
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
import json
import os
import functions_framework
import vertexai
from vertexai.generative_models import GenerativeModel
@functions_framework.http
def list_text_input(request) -> str | tuple[str, int]:
print(request)
try:
request_json = request.get_json()
calls = request_json["calls"]
for call in calls:
text_prompt = str(call[0])
print(text_prompt)
return text_prompt
except Exception as e:
return json.dumps({"errorMessage": str(e)}), 400
def generate_text_from_prompt(text_string) -> str | None:
# this is the text-to-text model
text_model = GenerativeModel("gemini-2.0-flash")
responses = text_model.generate_content(text_string, stream=False)
print(responses)
output = " ".join(responses.text.strip().split("\n"))
print(output)
return output
def run_it(request) -> str | tuple[str, int]:
try:
project_id = os.environ.get("PROJECT_ID")
region = os.environ.get("REGION")
vertexai.init(project=project_id, location=region)
text_to_analyze = list_text_input(request)
text_output = generate_text_from_prompt(text_to_analyze)
result = text_output or "Unable to generate description"
return json.dumps({"replies": [result]})
except Exception as e:
return json.dumps({"errorMessage": str(e)}), 400