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add deepseek-coder-v2 in siliconflow (#6149)
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senseb authored Jul 29, 2024
1 parent 94d68b6 commit 3e18d32
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model: deepseek-ai/DeepSeek-Coder-V2-Instruct
label:
en_US: deepseek-ai/DeepSeek-Coder-V2-Instruct
model_type: llm
features:
- agent-thought
model_properties:
mode: chat
context_size: 32768
parameter_rules:
- name: temperature
use_template: temperature
- name: max_tokens
use_template: max_tokens
type: int
default: 512
min: 1
max: 4096
help:
zh_Hans: 指定生成结果长度的上限。如果生成结果截断,可以调大该参数。
en_US: Specifies the upper limit on the length of generated results. If the generated results are truncated, you can increase this parameter.
- name: top_p
use_template: top_p
- name: frequency_penalty
use_template: frequency_penalty
pricing:
input: '1.33'
output: '1.33'
unit: '0.000001'
currency: RMB
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model: deepseek-ai/deepseek-v2-chat
label:
en_US: deepseek-ai/deepseek-v2-chat
en_US: deepseek-ai/DeepSeek-V2-Chat
model_type: llm
features:
- multi-tool-call
- agent-thought
- stream-tool-call
model_properties:
mode: chat
context_size: 32768
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model: zhipuai/glm4-9B-chat
label:
en_US: zhipuai/glm4-9B-chat
en_US: THUDM/glm-4-9b-chat
model_type: llm
features:
- multi-tool-call
- agent-thought
- stream-tool-call
model_properties:
mode: chat
context_size: 32768
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model: alibaba/Qwen2-57B-A14B-Instruct
label:
en_US: alibaba/Qwen2-57B-A14B-Instruct
en_US: Qwen/Qwen2-57B-A14B-Instruct
model_type: llm
features:
- multi-tool-call
- agent-thought
- stream-tool-call
model_properties:
mode: chat
context_size: 32768
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model: alibaba/Qwen2-72B-Instruct
label:
en_US: alibaba/Qwen2-72B-Instruct
en_US: Qwen/Qwen2-72B-Instruct
model_type: llm
features:
- multi-tool-call
- agent-thought
- stream-tool-call
model_properties:
mode: chat
context_size: 32768
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model: alibaba/Qwen2-7B-Instruct
label:
en_US: alibaba/Qwen2-7B-Instruct
en_US: Qwen/Qwen2-7B-Instruct
model_type: llm
features:
- multi-tool-call
- agent-thought
- stream-tool-call
model_properties:
mode: chat
context_size: 32768
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model: 01-ai/Yi-1.5-34B-Chat
label:
en_US: 01-ai/Yi-1.5-34B-Chat
en_US: 01-ai/Yi-1.5-34B-Chat-16K
model_type: llm
features:
- multi-tool-call
- agent-thought
- stream-tool-call
model_properties:
mode: chat
context_size: 16384
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Expand Up @@ -3,9 +3,7 @@ label:
en_US: 01-ai/Yi-1.5-6B-Chat
model_type: llm
features:
- multi-tool-call
- agent-thought
- stream-tool-call
model_properties:
mode: chat
context_size: 4096
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model: 01-ai/Yi-1.5-9B-Chat
label:
en_US: 01-ai/Yi-1.5-9B-Chat
en_US: 01-ai/Yi-1.5-9B-Chat-16K
model_type: llm
features:
- multi-tool-call
- agent-thought
- stream-tool-call
model_properties:
mode: chat
context_size: 16384
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Expand Up @@ -19,7 +19,7 @@ def validate_provider_credentials(self, credentials: dict) -> None:
model_instance = self.get_model_instance(ModelType.LLM)

model_instance.validate_credentials(
model='deepseek-ai/deepseek-v2-chat',
model='deepseek-ai/DeepSeek-V2-Chat',
credentials=credentials
)
except CredentialsValidateFailedError as ex:
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Empty file.
106 changes: 106 additions & 0 deletions api/tests/integration_tests/model_runtime/siliconflow/test_llm.py
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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.siliconflow.llm.llm import SiliconflowLargeLanguageModel


def test_validate_credentials():
model = SiliconflowLargeLanguageModel()

with pytest.raises(CredentialsValidateFailedError):
model.validate_credentials(
model='deepseek-ai/DeepSeek-V2-Chat',
credentials={
'api_key': 'invalid_key'
}
)

model.validate_credentials(
model='deepseek-ai/DeepSeek-V2-Chat',
credentials={
'api_key': os.environ.get('API_KEY')
}
)


def test_invoke_model():
model = SiliconflowLargeLanguageModel()

response = model.invoke(
model='deepseek-ai/DeepSeek-V2-Chat',
credentials={
'api_key': os.environ.get('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 = SiliconflowLargeLanguageModel()

response = model.invoke(
model='deepseek-ai/DeepSeek-V2-Chat',
credentials={
'api_key': os.environ.get('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 = SiliconflowLargeLanguageModel()

num_tokens = model.get_num_tokens(
model='deepseek-ai/DeepSeek-V2-Chat',
credentials={
'api_key': os.environ.get('API_KEY')
},
prompt_messages=[
SystemPromptMessage(
content='You are a helpful AI assistant.',
),
UserPromptMessage(
content='Hello World!'
)
]
)

assert num_tokens == 12
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import os

import pytest

from core.model_runtime.errors.validate import CredentialsValidateFailedError
from core.model_runtime.model_providers.siliconflow.siliconflow import SiliconflowProvider


def test_validate_provider_credentials():
provider = SiliconflowProvider()

with pytest.raises(CredentialsValidateFailedError):
provider.validate_provider_credentials(
credentials={}
)

provider.validate_provider_credentials(
credentials={
'api_key': os.environ.get('API_KEY')
}
)

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