Spaces:
Running
Running
| """ | |
| This module contains functions for generating responses using LLMs. | |
| """ | |
| import enum | |
| import json | |
| import os | |
| from random import sample | |
| from uuid import uuid4 | |
| from firebase_admin import firestore | |
| 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 | |
| from leaderboard import db | |
| 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) | |
| def create_history(model_name: str, instruction: str, prompt: str, | |
| response: str): | |
| doc_id = uuid4().hex | |
| doc = { | |
| "id": doc_id, | |
| "model": model_name, | |
| "instruction": instruction, | |
| "prompt": prompt, | |
| "response": response, | |
| "timestamp": firestore.SERVER_TIMESTAMP | |
| } | |
| doc_ref = db.collection("arena-history").document(doc_id) | |
| doc_ref.set(doc) | |
| 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" | |
| }]) | |
| content = response.choices[0].message.content | |
| create_history(model, instruction, user_prompt, content) | |
| responses.append(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] | |