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Python Cloud Function to summarize text via PaLM2 Bison Text Model
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import os | |
import json | |
import functions_framework | |
import google.cloud.logging | |
import vertexai | |
from vertexai.language_models import TextGenerationModel | |
PROJECT_ID = os.environ.get('GCP_PROJECT','-') | |
LOCATION = os.environ.get('GCP_REGION','-') | |
client = google.cloud.logging.Client(project=PROJECT_ID) | |
client.setup_logging() | |
log_name = "slack-summarizeText-cloudfunction-log" | |
logger = client.logger(log_name) | |
@functions_framework.http | |
def summarizeText(request): | |
token = request.form['token'] | |
logger.log(f"token received = {token}") | |
#<TODO>Your code to validate token | |
request_text = request.form['text'] | |
logger.log(f"Received the following request to summarize : {request_text}") | |
vertexai.init(project=PROJECT_ID, location=LOCATION) | |
model = TextGenerationModel.from_pretrained("text-bison@001") | |
prompt = f"Summarize: {request_text}" | |
parameters = { | |
"temperature": 0.2, | |
"max_output_tokens": 256, | |
"top_p": 0.8, | |
"top_k": 40 | |
} | |
prompt_response = model.predict(prompt,**parameters) | |
logger.log("PaLM Text Bison Model response: {prompt_response.text}") | |
#Format the Slack message | |
data = {} | |
data['blocks'] = [] | |
data['blocks'].append({"type":"section", | |
"text": { | |
"type": "mrkdwn", | |
"text": "Your message: " + request_text + "\n>Summarization:" + prompt_response.text | |
} | |
}) | |
return json.dumps(data),200, {'Content-Type': 'application/json'} |
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