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- import json
- import logging
- from json import JSONDecodeError
- from typing import Type, Optional
- from flask import current_app
- from openai.error import AuthenticationError, OpenAIError
- import openai
- from core.helper import encrypter
- from core.model_providers.models.entity.provider import ModelFeature
- from core.model_providers.models.speech2text.openai_whisper import OpenAIWhisper
- from core.model_providers.models.base import BaseProviderModel
- from core.model_providers.models.embedding.openai_embedding import OpenAIEmbedding
- from core.model_providers.models.entity.model_params import ModelKwargsRules, KwargRule, ModelType
- from core.model_providers.models.llm.openai_model import OpenAIModel
- from core.model_providers.models.moderation.openai_moderation import OpenAIModeration
- from core.model_providers.providers.base import BaseModelProvider, CredentialsValidateFailedError
- from core.model_providers.providers.hosted import hosted_model_providers
- from models.provider import ProviderType, ProviderQuotaType
- class OpenAIProvider(BaseModelProvider):
- @property
- def provider_name(self):
- """
- Returns the name of a provider.
- """
- return 'openai'
- def _get_fixed_model_list(self, model_type: ModelType) -> list[dict]:
- if model_type == ModelType.TEXT_GENERATION:
- models = [
- {
- 'id': 'gpt-3.5-turbo',
- 'name': 'gpt-3.5-turbo',
- 'features': [
- ModelFeature.AGENT_THOUGHT.value
- ]
- },
- {
- 'id': 'gpt-3.5-turbo-instruct',
- 'name': 'GPT-3.5-Turbo-Instruct',
- },
- {
- 'id': 'gpt-3.5-turbo-16k',
- 'name': 'gpt-3.5-turbo-16k',
- 'features': [
- ModelFeature.AGENT_THOUGHT.value
- ]
- },
- {
- 'id': 'gpt-4',
- 'name': 'gpt-4',
- 'features': [
- ModelFeature.AGENT_THOUGHT.value
- ]
- },
- {
- 'id': 'gpt-4-32k',
- 'name': 'gpt-4-32k',
- 'features': [
- ModelFeature.AGENT_THOUGHT.value
- ]
- },
- {
- 'id': 'text-davinci-003',
- 'name': 'text-davinci-003',
- }
- ]
- if self.provider.provider_type == ProviderType.SYSTEM.value \
- and self.provider.quota_type == ProviderQuotaType.TRIAL.value:
- models = [item for item in models if item['id'] not in ['gpt-4', 'gpt-4-32k']]
- return models
- elif model_type == ModelType.EMBEDDINGS:
- return [
- {
- 'id': 'text-embedding-ada-002',
- 'name': 'text-embedding-ada-002'
- }
- ]
- elif model_type == ModelType.SPEECH_TO_TEXT:
- return [
- {
- 'id': 'whisper-1',
- 'name': 'whisper-1'
- }
- ]
- elif model_type == ModelType.MODERATION:
- return [
- {
- 'id': 'text-moderation-stable',
- 'name': 'text-moderation-stable'
- }
- ]
- else:
- return []
- def get_model_class(self, model_type: ModelType) -> Type[BaseProviderModel]:
- """
- Returns the model class.
- :param model_type:
- :return:
- """
- if model_type == ModelType.TEXT_GENERATION:
- model_class = OpenAIModel
- elif model_type == ModelType.EMBEDDINGS:
- model_class = OpenAIEmbedding
- elif model_type == ModelType.MODERATION:
- model_class = OpenAIModeration
- elif model_type == ModelType.SPEECH_TO_TEXT:
- model_class = OpenAIWhisper
- else:
- raise NotImplementedError
- return model_class
- def get_model_parameter_rules(self, model_name: str, model_type: ModelType) -> ModelKwargsRules:
- """
- get model parameter rules.
- :param model_name:
- :param model_type:
- :return:
- """
- model_max_tokens = {
- 'gpt-4': 8192,
- 'gpt-4-32k': 32768,
- 'gpt-3.5-turbo': 4096,
- 'gpt-3.5-turbo-instruct': 8192,
- 'gpt-3.5-turbo-16k': 16384,
- 'text-davinci-003': 4097,
- }
- return ModelKwargsRules(
- temperature=KwargRule[float](min=0, max=2, default=1, precision=2),
- top_p=KwargRule[float](min=0, max=1, default=1, precision=2),
- presence_penalty=KwargRule[float](min=-2, max=2, default=0, precision=2),
- frequency_penalty=KwargRule[float](min=-2, max=2, default=0, precision=2),
- max_tokens=KwargRule[int](min=10, max=model_max_tokens.get(model_name, 4097), default=16, precision=0),
- )
- @classmethod
- def is_provider_credentials_valid_or_raise(cls, credentials: dict):
- """
- Validates the given credentials.
- """
- if 'openai_api_key' not in credentials:
- raise CredentialsValidateFailedError('OpenAI API key is required')
- try:
- credentials_kwargs = {
- "api_key": credentials['openai_api_key']
- }
- if 'openai_api_base' in credentials and credentials['openai_api_base']:
- credentials_kwargs['api_base'] = credentials['openai_api_base'] + '/v1'
- if 'openai_organization' in credentials:
- credentials_kwargs['organization'] = credentials['openai_organization']
- openai.ChatCompletion.create(
- messages=[{"role": "user", "content": 'ping'}],
- model='gpt-3.5-turbo',
- timeout=10,
- request_timeout=(5, 30),
- max_tokens=20,
- **credentials_kwargs
- )
- except (AuthenticationError, OpenAIError) as ex:
- raise CredentialsValidateFailedError(str(ex))
- except Exception as ex:
- logging.exception('OpenAI config validation failed')
- raise ex
- @classmethod
- def encrypt_provider_credentials(cls, tenant_id: str, credentials: dict) -> dict:
- credentials['openai_api_key'] = encrypter.encrypt_token(tenant_id, credentials['openai_api_key'])
- return credentials
- def get_provider_credentials(self, obfuscated: bool = False) -> dict:
- if self.provider.provider_type == ProviderType.CUSTOM.value:
- try:
- credentials = json.loads(self.provider.encrypted_config)
- except JSONDecodeError:
- credentials = {
- 'openai_api_base': None,
- 'openai_api_key': self.provider.encrypted_config,
- 'openai_organization': None
- }
- if credentials['openai_api_key']:
- credentials['openai_api_key'] = encrypter.decrypt_token(
- self.provider.tenant_id,
- credentials['openai_api_key']
- )
- if obfuscated:
- credentials['openai_api_key'] = encrypter.obfuscated_token(credentials['openai_api_key'])
- if 'openai_api_base' not in credentials or not credentials['openai_api_base']:
- credentials['openai_api_base'] = None
- else:
- credentials['openai_api_base'] = credentials['openai_api_base'] + '/v1'
- if 'openai_organization' not in credentials:
- credentials['openai_organization'] = None
- return credentials
- else:
- if hosted_model_providers.openai:
- return {
- 'openai_api_base': hosted_model_providers.openai.api_base,
- 'openai_api_key': hosted_model_providers.openai.api_key,
- 'openai_organization': hosted_model_providers.openai.api_organization
- }
- else:
- return {
- 'openai_api_base': None,
- 'openai_api_key': None,
- 'openai_organization': None
- }
- @classmethod
- def is_provider_type_system_supported(cls) -> bool:
- if current_app.config['EDITION'] != 'CLOUD':
- return False
- if hosted_model_providers.openai:
- return True
- return False
- def should_deduct_quota(self):
- if hosted_model_providers.openai \
- and hosted_model_providers.openai.quota_limit and hosted_model_providers.openai.quota_limit > 0:
- return True
- return False
- def get_payment_info(self) -> Optional[dict]:
- """
- get payment info if it payable.
- :return:
- """
- if hosted_model_providers.openai \
- and hosted_model_providers.openai.paid_enabled:
- return {
- 'product_id': hosted_model_providers.openai.paid_stripe_price_id,
- 'increase_quota': hosted_model_providers.openai.paid_increase_quota,
- }
- return None
- @classmethod
- def is_model_credentials_valid_or_raise(cls, model_name: str, model_type: ModelType, credentials: dict):
- """
- check model credentials valid.
- :param model_name:
- :param model_type:
- :param credentials:
- """
- return
- @classmethod
- def encrypt_model_credentials(cls, tenant_id: str, model_name: str, model_type: ModelType, credentials: dict) -> dict:
- """
- encrypt model credentials for save.
- :param tenant_id:
- :param model_name:
- :param model_type:
- :param credentials:
- :return:
- """
- return {}
- def get_model_credentials(self, model_name: str, model_type: ModelType, obfuscated: bool = False) -> dict:
- """
- get credentials for llm use.
- :param model_name:
- :param model_type:
- :param obfuscated:
- :return:
- """
- return self.get_provider_credentials(obfuscated)
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