Feat/add 360-zhinao provider (#7069)

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小羽 2024-08-08 06:23:08 +00:00 committed by GitHub
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16 changed files with 348 additions and 1 deletions

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@ -36,3 +36,4 @@
- hunyuan
- siliconflow
- perfxcloud
- zhinao

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model: 360gpt-turbo-responsibility-8k
label:
zh_Hans: 360gpt-turbo-responsibility-8k
en_US: 360gpt-turbo-responsibility-8k
model_type: llm
features:
- agent-thought
model_properties:
mode: chat
context_size: 8192
parameter_rules:
- name: temperature
use_template: temperature
min: 0
max: 1
default: 0.5
- name: top_p
use_template: top_p
min: 0
max: 1
default: 1
- name: max_tokens
use_template: max_tokens
min: 1
max: 8192
default: 1024
- name: frequency_penalty
use_template: frequency_penalty
min: -2
max: 2
default: 0
- name: presence_penalty
use_template: presence_penalty
min: -2
max: 2
default: 0

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model: 360gpt-turbo
label:
zh_Hans: 360gpt-turbo
en_US: 360gpt-turbo
model_type: llm
features:
- agent-thought
model_properties:
mode: chat
context_size: 2048
parameter_rules:
- name: temperature
use_template: temperature
min: 0
max: 1
default: 0.5
- name: top_p
use_template: top_p
min: 0
max: 1
default: 1
- name: max_tokens
use_template: max_tokens
min: 1
max: 2048
default: 1024
- name: frequency_penalty
use_template: frequency_penalty
min: -2
max: 2
default: 0
- name: presence_penalty
use_template: presence_penalty
min: -2
max: 2
default: 0

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model: 360gpt2-pro
label:
zh_Hans: 360gpt2-pro
en_US: 360gpt2-pro
model_type: llm
features:
- agent-thought
model_properties:
mode: chat
context_size: 2048
parameter_rules:
- name: temperature
use_template: temperature
min: 0
max: 1
default: 0.5
- name: top_p
use_template: top_p
min: 0
max: 1
default: 1
- name: max_tokens
use_template: max_tokens
min: 1
max: 2048
default: 1024
- name: frequency_penalty
use_template: frequency_penalty
min: -2
max: 2
default: 0
- name: presence_penalty
use_template: presence_penalty
min: -2
max: 2
default: 0

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- 360gpt2-pro
- 360gpt-turbo
- 360gpt-turbo-responsibility-8k

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from collections.abc import Generator
from typing import Optional, Union
from core.model_runtime.entities.llm_entities import LLMResult
from core.model_runtime.entities.message_entities import PromptMessage, PromptMessageTool
from core.model_runtime.model_providers.openai_api_compatible.llm.llm import OAIAPICompatLargeLanguageModel
class ZhinaoLargeLanguageModel(OAIAPICompatLargeLanguageModel):
def _invoke(self, model: str, credentials: dict,
prompt_messages: list[PromptMessage], model_parameters: dict,
tools: Optional[list[PromptMessageTool]] = None, stop: Optional[list[str]] = None,
stream: bool = True, user: Optional[str] = None) \
-> Union[LLMResult, Generator]:
self._add_custom_parameters(credentials)
return super()._invoke(model, credentials, prompt_messages, model_parameters, tools, stop, stream)
def validate_credentials(self, model: str, credentials: dict) -> None:
self._add_custom_parameters(credentials)
super().validate_credentials(model, credentials)
@classmethod
def _add_custom_parameters(cls, credentials: dict) -> None:
credentials['mode'] = 'chat'
credentials['endpoint_url'] = 'https://api.360.cn/v1'

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import logging
from core.model_runtime.entities.model_entities import ModelType
from core.model_runtime.errors.validate import CredentialsValidateFailedError
from core.model_runtime.model_providers.__base.model_provider import ModelProvider
logger = logging.getLogger(__name__)
class ZhinaoProvider(ModelProvider):
def validate_provider_credentials(self, credentials: dict) -> None:
"""
Validate provider credentials
if validate failed, raise exception
:param credentials: provider credentials, credentials form defined in `provider_credential_schema`.
"""
try:
model_instance = self.get_model_instance(ModelType.LLM)
# Use `360gpt-turbo` model for validate,
# no matter what model you pass in, text completion model or chat model
model_instance.validate_credentials(
model='360gpt-turbo',
credentials=credentials
)
except CredentialsValidateFailedError as ex:
raise ex
except Exception as ex:
logger.exception(f'{self.get_provider_schema().provider} credentials validate failed')
raise ex

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provider: zhinao
label:
en_US: 360 AI
zh_Hans: 360 智脑
description:
en_US: Models provided by 360 AI.
zh_Hans: 360 智脑提供的模型。
icon_small:
en_US: icon_s_en.svg
icon_large:
en_US: icon_l_en.svg
background: "#e3f0ff"
help:
title:
en_US: Get your API Key from 360 AI.
zh_Hans: 从360 智脑获取 API Key
url:
en_US: https://ai.360.com/platform/keys
supported_model_types:
- llm
configurate_methods:
- predefined-model
provider_credential_schema:
credential_form_schemas:
- variable: api_key
label:
en_US: API Key
type: secret-input
required: true
placeholder:
zh_Hans: 在此输入您的 API Key
en_US: Enter your API Key

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@ -79,4 +79,7 @@ CODE_EXECUTION_API_KEY=
VOLC_API_KEY=
VOLC_SECRET_KEY=
VOLC_MODEL_ENDPOINT_ID=
VOLC_EMBEDDING_ENDPOINT_ID=
VOLC_EMBEDDING_ENDPOINT_ID=
# 360 AI Credentials
ZHINAO_API_KEY=

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import os
from collections.abc import Generator
import pytest
from core.model_runtime.entities.llm_entities import LLMResult, LLMResultChunk, LLMResultChunkDelta
from core.model_runtime.entities.message_entities import AssistantPromptMessage, SystemPromptMessage, UserPromptMessage
from core.model_runtime.errors.validate import CredentialsValidateFailedError
from core.model_runtime.model_providers.zhinao.llm.llm import ZhinaoLargeLanguageModel
def test_validate_credentials():
model = ZhinaoLargeLanguageModel()
with pytest.raises(CredentialsValidateFailedError):
model.validate_credentials(
model='360gpt2-pro',
credentials={
'api_key': 'invalid_key'
}
)
model.validate_credentials(
model='360gpt2-pro',
credentials={
'api_key': os.environ.get('ZHINAO_API_KEY')
}
)
def test_invoke_model():
model = ZhinaoLargeLanguageModel()
response = model.invoke(
model='360gpt2-pro',
credentials={
'api_key': os.environ.get('ZHINAO_API_KEY')
},
prompt_messages=[
UserPromptMessage(
content='Who are you?'
)
],
model_parameters={
'temperature': 0.5,
'max_tokens': 10
},
stop=['How'],
stream=False,
user="abc-123"
)
assert isinstance(response, LLMResult)
assert len(response.message.content) > 0
def test_invoke_stream_model():
model = ZhinaoLargeLanguageModel()
response = model.invoke(
model='360gpt2-pro',
credentials={
'api_key': os.environ.get('ZHINAO_API_KEY')
},
prompt_messages=[
UserPromptMessage(
content='Hello World!'
)
],
model_parameters={
'temperature': 0.5,
'max_tokens': 100,
'seed': 1234
},
stream=True,
user="abc-123"
)
assert isinstance(response, Generator)
for chunk in response:
assert isinstance(chunk, LLMResultChunk)
assert isinstance(chunk.delta, LLMResultChunkDelta)
assert isinstance(chunk.delta.message, AssistantPromptMessage)
assert len(chunk.delta.message.content) > 0 if chunk.delta.finish_reason is None else True
def test_get_num_tokens():
model = ZhinaoLargeLanguageModel()
num_tokens = model.get_num_tokens(
model='360gpt2-pro',
credentials={
'api_key': os.environ.get('ZHINAO_API_KEY')
},
prompt_messages=[
SystemPromptMessage(
content='You are a helpful AI assistant.',
),
UserPromptMessage(
content='Hello World!'
)
]
)
assert num_tokens == 21

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import os
import pytest
from core.model_runtime.errors.validate import CredentialsValidateFailedError
from core.model_runtime.model_providers.zhinao.zhinao import ZhinaoProvider
def test_validate_provider_credentials():
provider = ZhinaoProvider()
with pytest.raises(CredentialsValidateFailedError):
provider.validate_provider_credentials(
credentials={}
)
provider.validate_provider_credentials(
credentials={
'api_key': os.environ.get('ZHINAO_API_KEY')
}
)