feat: server multi models support (#799)

api/tests/integration_tests/.env.example

@@ -0,0 +1,35 @@
+# OpenAI API Key
+OPENAI_API_KEY=
+
+# Azure OpenAI API Base Endpoint & API Key
+AZURE_OPENAI_API_BASE=
+AZURE_OPENAI_API_KEY=
+
+# Anthropic API Key
+ANTHROPIC_API_KEY=
+
+# Replicate API Key
+REPLICATE_API_TOKEN=
+
+# Hugging Face API Key
+HUGGINGFACE_API_KEY=
+HUGGINGFACE_ENDPOINT_URL=
+
+# Minimax Credentials
+MINIMAX_API_KEY=
+MINIMAX_GROUP_ID=
+
+# Spark Credentials
+SPARK_APP_ID=
+SPARK_API_KEY=
+SPARK_API_SECRET=
+
+# Tongyi Credentials
+TONGYI_DASHSCOPE_API_KEY=
+
+# Wenxin Credentials
+WENXIN_API_KEY=
+WENXIN_SECRET_KEY=
+
+# ChatGLM Credentials
+CHATGLM_API_BASE=

api/tests/integration_tests/conftest.py

@@ -0,0 +1,19 @@
+import os
+
+# Getting the absolute path of the current file's directory
+ABS_PATH = os.path.dirname(os.path.abspath(__file__))
+
+# Getting the absolute path of the project's root directory
+PROJECT_DIR = os.path.abspath(os.path.join(ABS_PATH, os.pardir, os.pardir))
+
+
+# Loading the .env file if it exists
+def _load_env() -> None:
+    dotenv_path = os.path.join(PROJECT_DIR, "tests", "integration_tests", ".env")
+    if os.path.exists(dotenv_path):
+        from dotenv import load_dotenv
+
+        load_dotenv(dotenv_path)
+
+
+_load_env()

api/tests/integration_tests/models/embedding/test_azure_openai_embedding.py

@@ -0,0 +1,57 @@
+import json
+import os
+from unittest.mock import patch, MagicMock
+
+from core.model_providers.models.entity.model_params import ModelType
+from core.model_providers.providers.azure_openai_provider import AzureOpenAIProvider
+from core.model_providers.models.embedding.azure_openai_embedding import AzureOpenAIEmbedding
+from models.provider import Provider, ProviderType, ProviderModel
+
+
+def get_mock_provider():
+    return Provider(
+        id='provider_id',
+        tenant_id='tenant_id',
+        provider_name='azure_openai',
+        provider_type=ProviderType.CUSTOM.value,
+        encrypted_config='',
+        is_valid=True,
+    )
+
+
+def get_mock_azure_openai_embedding_model(mocker):
+    model_name = 'text-embedding-ada-002'
+    valid_openai_api_base = os.environ['AZURE_OPENAI_API_BASE']
+    valid_openai_api_key = os.environ['AZURE_OPENAI_API_KEY']
+    openai_provider = AzureOpenAIProvider(provider=get_mock_provider())
+
+    mock_query = MagicMock()
+    mock_query.filter.return_value.first.return_value = ProviderModel(
+        provider_name='azure_openai',
+        model_name=model_name,
+        model_type=ModelType.EMBEDDINGS.value,
+        encrypted_config=json.dumps({
+            'openai_api_base': valid_openai_api_base,
+            'openai_api_key': valid_openai_api_key,
+            'base_model_name': model_name
+        }),
+        is_valid=True,
+    )
+    mocker.patch('extensions.ext_database.db.session.query', return_value=mock_query)
+
+    return AzureOpenAIEmbedding(
+        model_provider=openai_provider,
+        name=model_name
+    )
+
+
+def decrypt_side_effect(tenant_id, encrypted_openai_api_key):
+    return encrypted_openai_api_key
+
+
+@patch('core.helper.encrypter.decrypt_token', side_effect=decrypt_side_effect)
+def test_embedding(mock_decrypt, mocker):
+    embedding_model = get_mock_azure_openai_embedding_model(mocker)
+    rst = embedding_model.client.embed_query('test')
+    assert isinstance(rst, list)
+    assert len(rst) == 1536

api/tests/integration_tests/models/embedding/test_minimax_embedding.py

@@ -0,0 +1,44 @@
+import json
+import os
+from unittest.mock import patch
+
+from core.model_providers.models.embedding.minimax_embedding import MinimaxEmbedding
+from core.model_providers.providers.minimax_provider import MinimaxProvider
+from models.provider import Provider, ProviderType
+
+
+def get_mock_provider(valid_group_id, valid_api_key):
+    return Provider(
+        id='provider_id',
+        tenant_id='tenant_id',
+        provider_name='minimax',
+        provider_type=ProviderType.CUSTOM.value,
+        encrypted_config=json.dumps({
+            'minimax_group_id': valid_group_id,
+            'minimax_api_key': valid_api_key
+        }),
+        is_valid=True,
+    )
+
+
+def get_mock_embedding_model():
+    model_name = 'embo-01'
+    valid_api_key = os.environ['MINIMAX_API_KEY']
+    valid_group_id = os.environ['MINIMAX_GROUP_ID']
+    provider = MinimaxProvider(provider=get_mock_provider(valid_group_id, valid_api_key))
+    return MinimaxEmbedding(
+        model_provider=provider,
+        name=model_name
+    )
+
+
+def decrypt_side_effect(tenant_id, encrypted_api_key):
+    return encrypted_api_key
+
+
+@patch('core.helper.encrypter.decrypt_token', side_effect=decrypt_side_effect)
+def test_embedding(mock_decrypt):
+    embedding_model = get_mock_embedding_model()
+    rst = embedding_model.client.embed_query('test')
+    assert isinstance(rst, list)
+    assert len(rst) == 1536

api/tests/integration_tests/models/embedding/test_openai_embedding.py

@@ -0,0 +1,40 @@
+import json
+import os
+from unittest.mock import patch
+
+from core.model_providers.providers.openai_provider import OpenAIProvider
+from core.model_providers.models.embedding.openai_embedding import OpenAIEmbedding
+from models.provider import Provider, ProviderType
+
+
+def get_mock_provider(valid_openai_api_key):
+    return Provider(
+        id='provider_id',
+        tenant_id='tenant_id',
+        provider_name='openai',
+        provider_type=ProviderType.CUSTOM.value,
+        encrypted_config=json.dumps({'openai_api_key': valid_openai_api_key}),
+        is_valid=True,
+    )
+
+
+def get_mock_openai_embedding_model():
+    model_name = 'text-embedding-ada-002'
+    valid_openai_api_key = os.environ['OPENAI_API_KEY']
+    openai_provider = OpenAIProvider(provider=get_mock_provider(valid_openai_api_key))
+    return OpenAIEmbedding(
+        model_provider=openai_provider,
+        name=model_name
+    )
+
+
+def decrypt_side_effect(tenant_id, encrypted_openai_api_key):
+    return encrypted_openai_api_key
+
+
+@patch('core.helper.encrypter.decrypt_token', side_effect=decrypt_side_effect)
+def test_embedding(mock_decrypt):
+    embedding_model = get_mock_openai_embedding_model()
+    rst = embedding_model.client.embed_query('test')
+    assert isinstance(rst, list)
+    assert len(rst) == 1536

api/tests/integration_tests/models/embedding/test_replicate_embedding.py

@@ -0,0 +1,64 @@
+import json
+import os
+from unittest.mock import patch, MagicMock
+
+from core.model_providers.models.embedding.replicate_embedding import ReplicateEmbedding
+from core.model_providers.models.entity.model_params import ModelType
+from core.model_providers.providers.replicate_provider import ReplicateProvider
+from models.provider import Provider, ProviderType, ProviderModel
+
+
+def get_mock_provider():
+    return Provider(
+        id='provider_id',
+        tenant_id='tenant_id',
+        provider_name='replicate',
+        provider_type=ProviderType.CUSTOM.value,
+        encrypted_config='',
+        is_valid=True,
+    )
+
+
+def get_mock_embedding_model(mocker):
+    model_name = 'replicate/all-mpnet-base-v2'
+    valid_api_key = os.environ['REPLICATE_API_TOKEN']
+    model_provider = ReplicateProvider(provider=get_mock_provider())
+
+    mock_query = MagicMock()
+    mock_query.filter.return_value.first.return_value = ProviderModel(
+        provider_name='replicate',
+        model_name=model_name,
+        model_type=ModelType.EMBEDDINGS.value,
+        encrypted_config=json.dumps({
+            'replicate_api_token': valid_api_key,
+            'model_version': 'b6b7585c9640cd7a9572c6e129c9549d79c9c31f0d3fdce7baac7c67ca38f305'
+        }),
+        is_valid=True,
+    )
+    mocker.patch('extensions.ext_database.db.session.query', return_value=mock_query)
+
+    return ReplicateEmbedding(
+        model_provider=model_provider,
+        name=model_name
+    )
+
+
+def decrypt_side_effect(tenant_id, encrypted_api_key):
+    return encrypted_api_key
+
+
+@patch('core.helper.encrypter.decrypt_token', side_effect=decrypt_side_effect)
+def test_embed_documents(mock_decrypt, mocker):
+    embedding_model = get_mock_embedding_model(mocker)
+    rst = embedding_model.client.embed_documents(['test', 'test1'])
+    assert isinstance(rst, list)
+    assert len(rst) == 2
+    assert len(rst[0]) == 768
+
+
+@patch('core.helper.encrypter.decrypt_token', side_effect=decrypt_side_effect)
+def test_embed_query(mock_decrypt, mocker):
+    embedding_model = get_mock_embedding_model(mocker)
+    rst = embedding_model.client.embed_query('test')
+    assert isinstance(rst, list)
+    assert len(rst) == 768

api/tests/integration_tests/models/llm/test_anthropic_model.py

@@ -0,0 +1,61 @@
+import json
+import os
+from unittest.mock import patch
+
+from langchain.schema import ChatGeneration, AIMessage
+
+from core.model_providers.models.entity.message import PromptMessage, MessageType
+from core.model_providers.models.entity.model_params import ModelKwargs
+from core.model_providers.models.llm.anthropic_model import AnthropicModel
+from core.model_providers.providers.anthropic_provider import AnthropicProvider
+from models.provider import Provider, ProviderType
+
+
+def get_mock_provider(valid_api_key):
+    return Provider(
+        id='provider_id',
+        tenant_id='tenant_id',
+        provider_name='anthropic',
+        provider_type=ProviderType.CUSTOM.value,
+        encrypted_config=json.dumps({'anthropic_api_key': valid_api_key}),
+        is_valid=True,
+    )
+
+
+def get_mock_model(model_name):
+    model_kwargs = ModelKwargs(
+        max_tokens=10,
+        temperature=0
+    )
+    valid_api_key = os.environ['ANTHROPIC_API_KEY']
+    model_provider = AnthropicProvider(provider=get_mock_provider(valid_api_key))
+    return AnthropicModel(
+        model_provider=model_provider,
+        name=model_name,
+        model_kwargs=model_kwargs
+    )
+
+
+def decrypt_side_effect(tenant_id, encrypted_api_key):
+    return encrypted_api_key
+
+
+@patch('core.helper.encrypter.decrypt_token', side_effect=decrypt_side_effect)
+def test_get_num_tokens(mock_decrypt):
+    model = get_mock_model('claude-2')
+    rst = model.get_num_tokens([
+        PromptMessage(type=MessageType.HUMAN, content='Who is your manufacturer?')
+    ])
+    assert rst == 6
+
+
+@patch('core.helper.encrypter.decrypt_token', side_effect=decrypt_side_effect)
+def test_run(mock_decrypt):
+    model = get_mock_model('claude-2')
+    messages = [PromptMessage(content='Human: 1 + 1=? \nAssistant: ')]
+    rst = model.run(
+        messages,
+        stop=['\nHuman:'],
+    )
+    assert len(rst.content) > 0
+    assert rst.content.strip() == '2'

api/tests/integration_tests/models/llm/test_azure_openai_model.py

@@ -0,0 +1,86 @@
+import json
+import os
+from unittest.mock import patch, MagicMock
+
+import pytest
+from langchain.schema import ChatGeneration, AIMessage
+
+from core.model_providers.models.entity.model_params import ModelKwargs, ModelType
+from core.model_providers.models.llm.azure_openai_model import AzureOpenAIModel
+from core.model_providers.models.entity.message import PromptMessage, MessageType
+from core.model_providers.providers.azure_openai_provider import AzureOpenAIProvider
+from models.provider import Provider, ProviderType, ProviderModel
+
+
+def get_mock_provider():
+    return Provider(
+        id='provider_id',
+        tenant_id='tenant_id',
+        provider_name='azure_openai',
+        provider_type=ProviderType.CUSTOM.value,
+        encrypted_config='',
+        is_valid=True,
+    )
+
+
+def get_mock_azure_openai_model(model_name, mocker):
+    model_kwargs = ModelKwargs(
+        max_tokens=10,
+        temperature=0
+    )
+    valid_openai_api_base = os.environ['AZURE_OPENAI_API_BASE']
+    valid_openai_api_key = os.environ['AZURE_OPENAI_API_KEY']
+    provider = AzureOpenAIProvider(provider=get_mock_provider())
+
+    mock_query = MagicMock()
+    mock_query.filter.return_value.first.return_value = ProviderModel(
+        provider_name='azure_openai',
+        model_name=model_name,
+        model_type=ModelType.TEXT_GENERATION.value,
+        encrypted_config=json.dumps({
+            'openai_api_base': valid_openai_api_base,
+            'openai_api_key': valid_openai_api_key,
+            'base_model_name': model_name
+        }),
+        is_valid=True,
+    )
+    mocker.patch('extensions.ext_database.db.session.query', return_value=mock_query)
+
+    return AzureOpenAIModel(
+        model_provider=provider,
+        name=model_name,
+        model_kwargs=model_kwargs
+    )
+
+
+def decrypt_side_effect(tenant_id, encrypted_openai_api_key):
+    return encrypted_openai_api_key
+
+
+@patch('core.helper.encrypter.decrypt_token', side_effect=decrypt_side_effect)
+def test_get_num_tokens(mock_decrypt, mocker):
+    openai_model = get_mock_azure_openai_model('text-davinci-003', mocker)
+    rst = openai_model.get_num_tokens([PromptMessage(content='you are a kindness Assistant.')])
+    assert rst == 6
+
+
+@patch('core.helper.encrypter.decrypt_token', side_effect=decrypt_side_effect)
+def test_chat_get_num_tokens(mock_decrypt, mocker):
+    openai_model = get_mock_azure_openai_model('gpt-35-turbo', mocker)
+    rst = openai_model.get_num_tokens([
+        PromptMessage(type=MessageType.SYSTEM, content='you are a kindness Assistant.'),
+        PromptMessage(type=MessageType.HUMAN, content='Who is your manufacturer?')
+    ])
+    assert rst == 22
+
+
+@patch('core.helper.encrypter.decrypt_token', side_effect=decrypt_side_effect)
+def test_run(mock_decrypt, mocker):
+    openai_model = get_mock_azure_openai_model('gpt-35-turbo', mocker)
+    messages = [PromptMessage(content='Human: Are you Human? you MUST only answer `y` or `n`? \nAssistant: ')]
+    rst = openai_model.run(
+        messages,
+        stop=['\nHuman:'],
+    )
+    assert len(rst.content) > 0
+    assert rst.content.strip() == 'n'

api/tests/integration_tests/models/llm/test_huggingface_hub_model.py

@@ -0,0 +1,124 @@
+import json
+import os
+from unittest.mock import patch, MagicMock
+
+from langchain.schema import Generation
+
+from core.model_providers.models.entity.message import PromptMessage, MessageType
+from core.model_providers.models.entity.model_params import ModelKwargs, ModelType
+from core.model_providers.models.llm.huggingface_hub_model import HuggingfaceHubModel
+from core.model_providers.providers.huggingface_hub_provider import HuggingfaceHubProvider
+from models.provider import Provider, ProviderType, ProviderModel
+
+
+def get_mock_provider():
+    return Provider(
+        id='provider_id',
+        tenant_id='tenant_id',
+        provider_name='huggingface_hub',
+        provider_type=ProviderType.CUSTOM.value,
+        encrypted_config='',
+        is_valid=True,
+    )
+
+
+def get_mock_model(model_name, huggingfacehub_api_type, mocker):
+    model_kwargs = ModelKwargs(
+        max_tokens=10,
+        temperature=0.01
+    )
+    valid_api_key = os.environ['HUGGINGFACE_API_KEY']
+    endpoint_url = os.environ['HUGGINGFACE_ENDPOINT_URL']
+    model_provider = HuggingfaceHubProvider(provider=get_mock_provider())
+
+    credentials = {
+        'huggingfacehub_api_type': huggingfacehub_api_type,
+        'huggingfacehub_api_token': valid_api_key
+    }
+
+    if huggingfacehub_api_type == 'inference_endpoints':
+        credentials['huggingfacehub_endpoint_url'] = endpoint_url
+
+    mock_query = MagicMock()
+    mock_query.filter.return_value.first.return_value = ProviderModel(
+        provider_name='huggingface_hub',
+        model_name=model_name,
+        model_type=ModelType.TEXT_GENERATION.value,
+        encrypted_config=json.dumps(credentials),
+        is_valid=True,
+    )
+    mocker.patch('extensions.ext_database.db.session.query', return_value=mock_query)
+
+    return HuggingfaceHubModel(
+        model_provider=model_provider,
+        name=model_name,
+        model_kwargs=model_kwargs
+    )
+
+
+def decrypt_side_effect(tenant_id, encrypted_api_key):
+    return encrypted_api_key
+
+@patch('huggingface_hub.hf_api.ModelInfo')
+@patch('core.helper.encrypter.decrypt_token', side_effect=decrypt_side_effect)
+def test_hosted_inference_api_get_num_tokens(mock_decrypt, mock_model_info, mocker):
+    mock_model_info.return_value = MagicMock(pipeline_tag='text2text-generation')
+    mocker.patch('langchain.llms.huggingface_hub.HuggingFaceHub._call', return_value="abc")
+
+    model = get_mock_model(
+        'tiiuae/falcon-40b',
+        'hosted_inference_api',
+        mocker
+    )
+    rst = model.get_num_tokens([
+        PromptMessage(type=MessageType.HUMAN, content='Who is your manufacturer?')
+    ])
+    assert rst == 5
+
+
+@patch('huggingface_hub.hf_api.ModelInfo')
+@patch('core.helper.encrypter.decrypt_token', side_effect=decrypt_side_effect)
+def test_inference_endpoints_get_num_tokens(mock_decrypt, mock_model_info, mocker):
+    mock_model_info.return_value = MagicMock(pipeline_tag='text2text-generation')
+    mocker.patch('langchain.llms.huggingface_hub.HuggingFaceHub._call', return_value="abc")
+
+    model = get_mock_model(
+        '',
+        'inference_endpoints',
+        mocker
+    )
+    rst = model.get_num_tokens([
+        PromptMessage(type=MessageType.HUMAN, content='Who is your manufacturer?')
+    ])
+    assert rst == 5
+
+
+@patch('core.helper.encrypter.decrypt_token', side_effect=decrypt_side_effect)
+def test_hosted_inference_api_run(mock_decrypt, mocker):
+    model = get_mock_model(
+        'google/flan-t5-base',
+        'hosted_inference_api',
+        mocker
+    )
+
+    rst = model.run(
+        [PromptMessage(content='Human: Are you Really Human? you MUST only answer `y` or `n`? \nAssistant: ')],
+        stop=['\nHuman:'],
+    )
+    assert len(rst.content) > 0
+    assert rst.content.strip() == 'n'
+
+
+@patch('core.helper.encrypter.decrypt_token', side_effect=decrypt_side_effect)
+def test_inference_endpoints_run(mock_decrypt, mocker):
+    model = get_mock_model(
+        '',
+        'inference_endpoints',
+        mocker
+    )
+
+    rst = model.run(
+        [PromptMessage(content='Answer the following yes/no question. Can you write a whole Haiku in a single tweet?')],
+    )
+    assert len(rst.content) > 0
+    assert rst.content.strip() == 'no'

api/tests/integration_tests/models/llm/test_minimax_model.py

@@ -0,0 +1,64 @@
+import json
+import os
+from unittest.mock import patch
+
+from langchain.schema import ChatGeneration, AIMessage, Generation
+
+from core.model_providers.models.entity.message import PromptMessage, MessageType
+from core.model_providers.models.entity.model_params import ModelKwargs
+from core.model_providers.models.llm.minimax_model import MinimaxModel
+from core.model_providers.providers.minimax_provider import MinimaxProvider
+from models.provider import Provider, ProviderType
+
+
+def get_mock_provider(valid_group_id, valid_api_key):
+    return Provider(
+        id='provider_id',
+        tenant_id='tenant_id',
+        provider_name='minimax',
+        provider_type=ProviderType.CUSTOM.value,
+        encrypted_config=json.dumps({
+            'minimax_group_id': valid_group_id,
+            'minimax_api_key': valid_api_key
+        }),
+        is_valid=True,
+    )
+
+
+def get_mock_model(model_name):
+    model_kwargs = ModelKwargs(
+        max_tokens=10,
+        temperature=0.01
+    )
+    valid_api_key = os.environ['MINIMAX_API_KEY']
+    valid_group_id = os.environ['MINIMAX_GROUP_ID']
+    model_provider = MinimaxProvider(provider=get_mock_provider(valid_group_id, valid_api_key))
+    return MinimaxModel(
+        model_provider=model_provider,
+        name=model_name,
+        model_kwargs=model_kwargs
+    )
+
+
+def decrypt_side_effect(tenant_id, encrypted_api_key):
+    return encrypted_api_key
+
+
+@patch('core.helper.encrypter.decrypt_token', side_effect=decrypt_side_effect)
+def test_get_num_tokens(mock_decrypt):
+    model = get_mock_model('abab5.5-chat')
+    rst = model.get_num_tokens([
+        PromptMessage(type=MessageType.HUMAN, content='Who is your manufacturer?')
+    ])
+    assert rst == 5
+
+
+@patch('core.helper.encrypter.decrypt_token', side_effect=decrypt_side_effect)
+def test_run(mock_decrypt):
+    model = get_mock_model('abab5.5-chat')
+    rst = model.run(
+        [PromptMessage(content='Human: Are you a real Human? you MUST only answer `y` or `n`? \nAssistant: ')],
+        stop=['\nHuman:'],
+    )
+    assert len(rst.content) > 0
+    assert rst.content.strip() == 'n'

api/tests/integration_tests/models/llm/test_openai_model.py

@@ -0,0 +1,80 @@
+import json
+import os
+from unittest.mock import patch
+
+from langchain.schema import Generation, ChatGeneration, AIMessage
+
+from core.model_providers.providers.openai_provider import OpenAIProvider
+from core.model_providers.models.entity.message import PromptMessage, MessageType
+from core.model_providers.models.entity.model_params import ModelKwargs
+from core.model_providers.models.llm.openai_model import OpenAIModel
+from models.provider import Provider, ProviderType
+
+
+def get_mock_provider(valid_openai_api_key):
+    return Provider(
+        id='provider_id',
+        tenant_id='tenant_id',
+        provider_name='openai',
+        provider_type=ProviderType.CUSTOM.value,
+        encrypted_config=json.dumps({'openai_api_key': valid_openai_api_key}),
+        is_valid=True,
+    )
+
+
+def get_mock_openai_model(model_name):
+    model_kwargs = ModelKwargs(
+        max_tokens=10,
+        temperature=0
+    )
+    model_name = model_name
+    valid_openai_api_key = os.environ['OPENAI_API_KEY']
+    openai_provider = OpenAIProvider(provider=get_mock_provider(valid_openai_api_key))
+    return OpenAIModel(
+        model_provider=openai_provider,
+        name=model_name,
+        model_kwargs=model_kwargs
+    )
+
+
+def decrypt_side_effect(tenant_id, encrypted_openai_api_key):
+    return encrypted_openai_api_key
+
+@patch('core.helper.encrypter.decrypt_token', side_effect=decrypt_side_effect)
+def test_get_num_tokens(mock_decrypt):
+    openai_model = get_mock_openai_model('text-davinci-003')
+    rst = openai_model.get_num_tokens([PromptMessage(content='you are a kindness Assistant.')])
+    assert rst == 6
+
+
+@patch('core.helper.encrypter.decrypt_token', side_effect=decrypt_side_effect)
+def test_chat_get_num_tokens(mock_decrypt):
+    openai_model = get_mock_openai_model('gpt-3.5-turbo')
+    rst = openai_model.get_num_tokens([
+        PromptMessage(type=MessageType.SYSTEM, content='you are a kindness Assistant.'),
+        PromptMessage(type=MessageType.HUMAN, content='Who is your manufacturer?')
+    ])
+    assert rst == 22
+
+
+@patch('core.helper.encrypter.decrypt_token', side_effect=decrypt_side_effect)
+def test_run(mock_decrypt):
+    openai_model = get_mock_openai_model('text-davinci-003')
+    rst = openai_model.run(
+        [PromptMessage(content='Human: Are you Human? you MUST only answer `y` or `n`? \nAssistant: ')],
+        stop=['\nHuman:'],
+    )
+    assert len(rst.content) > 0
+    assert rst.content.strip() == 'n'
+
+
+@patch('core.helper.encrypter.decrypt_token', side_effect=decrypt_side_effect)
+def test_chat_run(mock_decrypt):
+    openai_model = get_mock_openai_model('gpt-3.5-turbo')
+    messages = [PromptMessage(content='Human: Are you Human? you MUST only answer `y` or `n`? \nAssistant: ')]
+    rst = openai_model.run(
+        messages,
+        stop=['\nHuman:'],
+    )
+    assert len(rst.content) > 0
+    assert rst.content.strip() == 'n'

api/tests/integration_tests/models/llm/test_replicate_model.py

@@ -0,0 +1,73 @@
+import json
+import os
+from unittest.mock import patch, MagicMock
+
+from langchain.schema import Generation
+
+from core.model_providers.models.entity.message import PromptMessage, MessageType
+from core.model_providers.models.entity.model_params import ModelKwargs, ModelType
+from core.model_providers.models.llm.replicate_model import ReplicateModel
+from core.model_providers.providers.replicate_provider import ReplicateProvider
+from models.provider import Provider, ProviderType, ProviderModel
+
+
+def get_mock_provider():
+    return Provider(
+        id='provider_id',
+        tenant_id='tenant_id',
+        provider_name='replicate',
+        provider_type=ProviderType.CUSTOM.value,
+        encrypted_config='',
+        is_valid=True,
+    )
+
+
+def get_mock_model(model_name, model_version, mocker):
+    model_kwargs = ModelKwargs(
+        max_tokens=10,
+        temperature=0.01
+    )
+    valid_api_key = os.environ['REPLICATE_API_TOKEN']
+    model_provider = ReplicateProvider(provider=get_mock_provider())
+
+    mock_query = MagicMock()
+    mock_query.filter.return_value.first.return_value = ProviderModel(
+        provider_name='replicate',
+        model_name=model_name,
+        model_type=ModelType.TEXT_GENERATION.value,
+        encrypted_config=json.dumps({
+            'replicate_api_token': valid_api_key,
+            'model_version': model_version
+        }),
+        is_valid=True,
+    )
+    mocker.patch('extensions.ext_database.db.session.query', return_value=mock_query)
+
+    return ReplicateModel(
+        model_provider=model_provider,
+        name=model_name,
+        model_kwargs=model_kwargs
+    )
+
+
+def decrypt_side_effect(tenant_id, encrypted_api_key):
+    return encrypted_api_key
+
+
+@patch('core.helper.encrypter.decrypt_token', side_effect=decrypt_side_effect)
+def test_get_num_tokens(mock_decrypt, mocker):
+    model = get_mock_model('a16z-infra/llama-2-13b-chat', '2a7f981751ec7fdf87b5b91ad4db53683a98082e9ff7bfd12c8cd5ea85980a52', mocker)
+    rst = model.get_num_tokens([
+        PromptMessage(type=MessageType.HUMAN, content='Who is your manufacturer?')
+    ])
+    assert rst == 7
+
+
+@patch('core.helper.encrypter.decrypt_token', side_effect=decrypt_side_effect)
+def test_run(mock_decrypt, mocker):
+    model = get_mock_model('a16z-infra/llama-2-13b-chat', '2a7f981751ec7fdf87b5b91ad4db53683a98082e9ff7bfd12c8cd5ea85980a52', mocker)
+    messages = [PromptMessage(content='Human: 1+1=? \nAnswer: ')]
+    rst = model.run(
+        messages
+    )
+    assert len(rst.content) > 0

api/tests/integration_tests/models/llm/test_spark_model.py

@@ -0,0 +1,69 @@
+import json
+import os
+from unittest.mock import patch
+
+from langchain.schema import ChatGeneration, AIMessage, Generation
+
+from core.model_providers.models.entity.message import PromptMessage, MessageType
+from core.model_providers.models.entity.model_params import ModelKwargs
+from core.model_providers.models.llm.minimax_model import MinimaxModel
+from core.model_providers.models.llm.spark_model import SparkModel
+from core.model_providers.providers.minimax_provider import MinimaxProvider
+from core.model_providers.providers.spark_provider import SparkProvider
+from models.provider import Provider, ProviderType
+
+
+def get_mock_provider(valid_app_id, valid_api_key, valid_api_secret):
+    return Provider(
+        id='provider_id',
+        tenant_id='tenant_id',
+        provider_name='spark',
+        provider_type=ProviderType.CUSTOM.value,
+        encrypted_config=json.dumps({
+                'app_id': valid_app_id,
+                'api_key': valid_api_key,
+                'api_secret': valid_api_secret,
+            }),
+        is_valid=True,
+    )
+
+
+def get_mock_model(model_name):
+    model_kwargs = ModelKwargs(
+        max_tokens=10,
+        temperature=0.01
+    )
+    valid_app_id = os.environ['SPARK_APP_ID']
+    valid_api_key = os.environ['SPARK_API_KEY']
+    valid_api_secret = os.environ['SPARK_API_SECRET']
+    model_provider = SparkProvider(provider=get_mock_provider(valid_app_id, valid_api_key, valid_api_secret))
+    return SparkModel(
+        model_provider=model_provider,
+        name=model_name,
+        model_kwargs=model_kwargs
+    )
+
+
+def decrypt_side_effect(tenant_id, encrypted_api_key):
+    return encrypted_api_key
+
+
+@patch('core.helper.encrypter.decrypt_token', side_effect=decrypt_side_effect)
+def test_get_num_tokens(mock_decrypt):
+    model = get_mock_model('spark')
+    rst = model.get_num_tokens([
+        PromptMessage(type=MessageType.HUMAN, content='Who is your manufacturer?')
+    ])
+    assert rst == 6
+
+
+@patch('core.helper.encrypter.decrypt_token', side_effect=decrypt_side_effect)
+def test_run(mock_decrypt):
+    model = get_mock_model('spark')
+    messages = [PromptMessage(content='Human: 1 + 1=? \nAssistant: Integer answer is:')]
+    rst = model.run(
+        messages,
+        stop=['\nHuman:'],
+    )
+    assert len(rst.content) > 0
+    assert rst.content.strip() == '2'

api/tests/integration_tests/models/llm/test_tongyi_model.py

@@ -0,0 +1,61 @@
+import json
+import os
+from unittest.mock import patch
+
+from langchain.schema import ChatGeneration, AIMessage, Generation
+
+from core.model_providers.models.entity.message import PromptMessage, MessageType
+from core.model_providers.models.entity.model_params import ModelKwargs
+from core.model_providers.models.llm.tongyi_model import TongyiModel
+from core.model_providers.providers.tongyi_provider import TongyiProvider
+from models.provider import Provider, ProviderType
+
+
+def get_mock_provider(valid_api_key):
+    return Provider(
+        id='provider_id',
+        tenant_id='tenant_id',
+        provider_name='tongyi',
+        provider_type=ProviderType.CUSTOM.value,
+        encrypted_config=json.dumps({
+            'dashscope_api_key': valid_api_key,
+        }),
+        is_valid=True,
+    )
+
+
+def get_mock_model(model_name):
+    model_kwargs = ModelKwargs(
+        max_tokens=10,
+        temperature=0.01
+    )
+    valid_api_key = os.environ['TONGYI_DASHSCOPE_API_KEY']
+    model_provider = TongyiProvider(provider=get_mock_provider(valid_api_key))
+    return TongyiModel(
+        model_provider=model_provider,
+        name=model_name,
+        model_kwargs=model_kwargs
+    )
+
+
+def decrypt_side_effect(tenant_id, encrypted_api_key):
+    return encrypted_api_key
+
+
+@patch('core.helper.encrypter.decrypt_token', side_effect=decrypt_side_effect)
+def test_get_num_tokens(mock_decrypt):
+    model = get_mock_model('qwen-v1')
+    rst = model.get_num_tokens([
+        PromptMessage(type=MessageType.HUMAN, content='Who is your manufacturer?')
+    ])
+    assert rst == 5
+
+
+@patch('core.helper.encrypter.decrypt_token', side_effect=decrypt_side_effect)
+def test_run(mock_decrypt):
+    model = get_mock_model('qwen-v1')
+    rst = model.run(
+        [PromptMessage(content='Human: Are you Human? you MUST only answer `y` or `n`? \nAssistant: ')],
+        stop=['\nHuman:'],
+    )
+    assert len(rst.content) > 0

api/tests/integration_tests/models/llm/test_wenxin_model.py

@@ -0,0 +1,63 @@
+import json
+import os
+from unittest.mock import patch
+
+
+from core.model_providers.models.entity.message import PromptMessage, MessageType
+from core.model_providers.models.entity.model_params import ModelKwargs
+from core.model_providers.models.llm.wenxin_model import WenxinModel
+from core.model_providers.providers.wenxin_provider import WenxinProvider
+from models.provider import Provider, ProviderType
+
+
+def get_mock_provider(valid_api_key, valid_secret_key):
+    return Provider(
+        id='provider_id',
+        tenant_id='tenant_id',
+        provider_name='wenxin',
+        provider_type=ProviderType.CUSTOM.value,
+        encrypted_config=json.dumps({
+            'api_key': valid_api_key,
+            'secret_key': valid_secret_key,
+        }),
+        is_valid=True,
+    )
+
+
+def get_mock_model(model_name):
+    model_kwargs = ModelKwargs(
+        temperature=0.01
+    )
+    valid_api_key = os.environ['WENXIN_API_KEY']
+    valid_secret_key = os.environ['WENXIN_SECRET_KEY']
+    model_provider = WenxinProvider(provider=get_mock_provider(valid_api_key, valid_secret_key))
+    return WenxinModel(
+        model_provider=model_provider,
+        name=model_name,
+        model_kwargs=model_kwargs
+    )
+
+
+def decrypt_side_effect(tenant_id, encrypted_api_key):
+    return encrypted_api_key
+
+
+@patch('core.helper.encrypter.decrypt_token', side_effect=decrypt_side_effect)
+def test_get_num_tokens(mock_decrypt):
+    model = get_mock_model('ernie-bot')
+    rst = model.get_num_tokens([
+        PromptMessage(type=MessageType.HUMAN, content='Who is your manufacturer?')
+    ])
+    assert rst == 5
+
+
+@patch('core.helper.encrypter.decrypt_token', side_effect=decrypt_side_effect)
+def test_run(mock_decrypt):
+    model = get_mock_model('ernie-bot')
+    messages = [PromptMessage(content='Human: 1 + 1=? \nAssistant: Integer answer is:')]
+    rst = model.run(
+        messages,
+        stop=['\nHuman:'],
+    )
+    assert len(rst.content) > 0
+    assert rst.content.strip() == '2'

api/tests/integration_tests/models/moderation/test_openai_moderation.py

@@ -0,0 +1,40 @@
+import json
+import os
+from unittest.mock import patch
+
+from core.model_providers.models.moderation.openai_moderation import OpenAIModeration, DEFAULT_AUDIO_MODEL
+from core.model_providers.providers.openai_provider import OpenAIProvider
+from models.provider import Provider, ProviderType
+
+
+def get_mock_provider(valid_openai_api_key):
+    return Provider(
+        id='provider_id',
+        tenant_id='tenant_id',
+        provider_name='openai',
+        provider_type=ProviderType.CUSTOM.value,
+        encrypted_config=json.dumps({'openai_api_key': valid_openai_api_key}),
+        is_valid=True,
+    )
+
+
+def get_mock_openai_moderation_model():
+    valid_openai_api_key = os.environ['OPENAI_API_KEY']
+    openai_provider = OpenAIProvider(provider=get_mock_provider(valid_openai_api_key))
+    return OpenAIModeration(
+        model_provider=openai_provider,
+        name=DEFAULT_AUDIO_MODEL
+    )
+
+
+def decrypt_side_effect(tenant_id, encrypted_openai_api_key):
+    return encrypted_openai_api_key
+
+
+@patch('core.helper.encrypter.decrypt_token', side_effect=decrypt_side_effect)
+def test_run(mock_decrypt):
+    model = get_mock_openai_moderation_model()
+    rst = model.run('hello')
+
+    assert isinstance(rst, dict)
+    assert 'id' in rst

api/tests/integration_tests/models/speech2text/test_openai_whisper.py

@@ -0,0 +1,50 @@
+import json
+import os
+from unittest.mock import patch
+
+from core.model_providers.models.speech2text.openai_whisper import OpenAIWhisper
+from core.model_providers.providers.openai_provider import OpenAIProvider
+from models.provider import Provider, ProviderType
+
+
+def get_mock_provider(valid_openai_api_key):
+    return Provider(
+        id='provider_id',
+        tenant_id='tenant_id',
+        provider_name='openai',
+        provider_type=ProviderType.CUSTOM.value,
+        encrypted_config=json.dumps({'openai_api_key': valid_openai_api_key}),
+        is_valid=True,
+    )
+
+
+def get_mock_openai_whisper_model():
+    model_name = 'whisper-1'
+    valid_openai_api_key = os.environ['OPENAI_API_KEY']
+    openai_provider = OpenAIProvider(provider=get_mock_provider(valid_openai_api_key))
+    return OpenAIWhisper(
+        model_provider=openai_provider,
+        name=model_name
+    )
+
+
+def decrypt_side_effect(tenant_id, encrypted_openai_api_key):
+    return encrypted_openai_api_key
+
+
+@patch('core.helper.encrypter.decrypt_token', side_effect=decrypt_side_effect)
+def test_run(mock_decrypt):
+    # Get the directory of the current file
+    current_dir = os.path.dirname(os.path.abspath(__file__))
+
+    # Construct the path to the audio file
+    audio_file_path = os.path.join(current_dir, 'audio.mp3')
+
+    model = get_mock_openai_whisper_model()
+
+    # Open the file and get the file object
+    with open(audio_file_path, 'rb') as audio_file:
+        rst = model.run(audio_file)
+
+    assert isinstance(rst, dict)
+    assert rst['text'] == '1, 2, 3, 4, 5, 6, 7, 8, 9, 10'