arena / response.py
Kang Suhyun
[#34] Block submission during response generation (#35)
3a85228 unverified
raw
history blame
3.17 kB
"""
This module contains functions for generating responses using LLMs.
"""
import enum
import json
import os
from random import sample
from google.cloud import secretmanager
from google.oauth2 import service_account
import gradio as gr
from litellm import completion
from credentials import get_credentials_json
GOOGLE_CLOUD_PROJECT = os.environ.get("GOOGLE_CLOUD_PROJECT")
MODELS_SECRET = os.environ.get("MODELS_SECRET")
secretmanager_client = secretmanager.SecretManagerServiceClient(
credentials=service_account.Credentials.from_service_account_info(
get_credentials_json()))
models_secret = secretmanager_client.access_secret_version(
name=secretmanager_client.secret_version_path(GOOGLE_CLOUD_PROJECT,
MODELS_SECRET, "latest"))
decoded_secret = models_secret.payload.data.decode("UTF-8")
supported_models = json.loads(decoded_secret)
class Category(enum.Enum):
SUMMARIZE = "Summarize"
TRANSLATE = "Translate"
# TODO(#31): Let the model builders set the instruction.
def get_instruction(category, source_lang, target_lang):
if category == Category.SUMMARIZE.value:
return "Summarize the following text, maintaining the original language of the text in the summary." # pylint: disable=line-too-long
if category == Category.TRANSLATE.value:
return f"Translate the following text from {source_lang} to {target_lang}."
def get_responses(user_prompt, category, source_lang, target_lang):
if not category:
raise gr.Error("Please select a category.")
if category == Category.TRANSLATE.value and (not source_lang or
not target_lang):
raise gr.Error("Please select source and target languages.")
models = sample(list(supported_models), 2)
instruction = get_instruction(category, source_lang, target_lang)
responses = []
for model in models:
model_config = supported_models[model]
model_name = model_config[
"provider"] + "/" + model if "provider" in model_config else model
api_key = model_config.get("apiKey", None)
api_base = model_config.get("apiBase", None)
try:
# TODO(#1): Allow user to set configuration.
response = completion(model=model_name,
api_key=api_key,
api_base=api_base,
messages=[{
"content": instruction,
"role": "system"
}, {
"content": user_prompt,
"role": "user"
}])
responses.append(response.choices[0].message.content)
# TODO(#1): Narrow down the exception type.
except Exception as e: # pylint: disable=broad-except
print(f"Error in bot_response: {e}")
raise e
# It simulates concurrent stream response generation.
max_response_length = max(len(response) for response in responses)
for i in range(max_response_length):
yield [response[:i + 1] for response in responses] + models + [instruction]
yield responses + models + [instruction]