Model Runtime (#1858)

Co-authored-by: StyleZhang <jasonapring2015@outlook.com> Co-authored-by: Garfield Dai <dai.hai@foxmail.com> Co-authored-by: chenhe <guchenhe@gmail.com> Co-authored-by: jyong <jyong@dify.ai> Co-authored-by: Joel <iamjoel007@gmail.com> Co-authored-by: Yeuoly <admin@srmxy.cn>
2025-12-25 02:33:00 +08:00 · 2024-01-02 23:42:00 +08:00
parent e91dd28a76
commit d069c668f8
807 changed files with 171310 additions and 23806 deletions
--- a/api/tests/integration_tests/model_runtime/huggingface_hub/init.py
+++ b/api/tests/integration_tests/model_runtime/huggingface_hub/init.py
--- a/api/tests/integration_tests/model_runtime/huggingface_hub/test_llm.py
+++ b/api/tests/integration_tests/model_runtime/huggingface_hub/test_llm.py
@@ -0,0 +1,304 @@
+import os
+from typing import Generator
+
+import pytest
+
+from core.model_runtime.entities.llm_entities import LLMResult, LLMResultChunk, \
+    LLMResultChunkDelta
+from core.model_runtime.entities.message_entities import UserPromptMessage, AssistantPromptMessage
+from core.model_runtime.errors.validate import CredentialsValidateFailedError
+from core.model_runtime.model_providers.huggingface_hub.llm.llm import HuggingfaceHubLargeLanguageModel
+
+from tests.integration_tests.model_runtime.__mock.huggingface import setup_huggingface_mock
+
+@pytest.mark.parametrize('setup_huggingface_mock', [['none']], indirect=True)
+def test_hosted_inference_api_validate_credentials(setup_huggingface_mock):
+    model = HuggingfaceHubLargeLanguageModel()
+
+    with pytest.raises(CredentialsValidateFailedError):
+        model.validate_credentials(
+            model='HuggingFaceH4/zephyr-7b-beta',
+            credentials={
+                'huggingfacehub_api_type': 'hosted_inference_api',
+                'huggingfacehub_api_token': 'invalid_key'
+            }
+        )
+
+    with pytest.raises(CredentialsValidateFailedError):
+        model.validate_credentials(
+            model='fake-model',
+            credentials={
+                'huggingfacehub_api_type': 'hosted_inference_api',
+                'huggingfacehub_api_token': 'invalid_key'
+            }
+        )
+
+    model.validate_credentials(
+        model='HuggingFaceH4/zephyr-7b-beta',
+        credentials={
+            'huggingfacehub_api_type': 'hosted_inference_api',
+            'huggingfacehub_api_token': os.environ.get('HUGGINGFACE_API_KEY')
+        }
+    )
+
+@pytest.mark.parametrize('setup_huggingface_mock', [['none']], indirect=True)
+def test_hosted_inference_api_invoke_model(setup_huggingface_mock):
+    model = HuggingfaceHubLargeLanguageModel()
+
+    response = model.invoke(
+        model='HuggingFaceH4/zephyr-7b-beta',
+        credentials={
+            'huggingfacehub_api_type': 'hosted_inference_api',
+            'huggingfacehub_api_token': os.environ.get('HUGGINGFACE_API_KEY')
+        },
+        prompt_messages=[
+            UserPromptMessage(
+                content='Who are you?'
+            )
+        ],
+        model_parameters={
+            'temperature': 1.0,
+            'top_k': 2,
+            'top_p': 0.5,
+        },
+        stop=['How'],
+        stream=False,
+        user="abc-123"
+    )
+
+    assert isinstance(response, LLMResult)
+    assert len(response.message.content) > 0
+
+@pytest.mark.parametrize('setup_huggingface_mock', [['none']], indirect=True)
+def test_hosted_inference_api_invoke_stream_model(setup_huggingface_mock):
+    model = HuggingfaceHubLargeLanguageModel()
+
+    response = model.invoke(
+        model='HuggingFaceH4/zephyr-7b-beta',
+        credentials={
+            'huggingfacehub_api_type': 'hosted_inference_api',
+            'huggingfacehub_api_token': os.environ.get('HUGGINGFACE_API_KEY')
+        },
+        prompt_messages=[
+            UserPromptMessage(
+                content='Who are you?'
+            )
+        ],
+        model_parameters={
+            'temperature': 1.0,
+            'top_k': 2,
+            'top_p': 0.5,
+        },
+        stop=['How'],
+        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
+
+@pytest.mark.parametrize('setup_huggingface_mock', [['none']], indirect=True)
+def test_inference_endpoints_text_generation_validate_credentials(setup_huggingface_mock):
+    model = HuggingfaceHubLargeLanguageModel()
+
+    with pytest.raises(CredentialsValidateFailedError):
+        model.validate_credentials(
+            model='openchat/openchat_3.5',
+            credentials={
+                'huggingfacehub_api_type': 'inference_endpoints',
+                'huggingfacehub_api_token': 'invalid_key',
+                'huggingfacehub_endpoint_url': os.environ.get('HUGGINGFACE_TEXT_GEN_ENDPOINT_URL'),
+                'task_type': 'text-generation'
+            }
+        )
+
+    model.validate_credentials(
+        model='openchat/openchat_3.5',
+        credentials={
+            'huggingfacehub_api_type': 'inference_endpoints',
+            'huggingfacehub_api_token': os.environ.get('HUGGINGFACE_API_KEY'),
+            'huggingfacehub_endpoint_url': os.environ.get('HUGGINGFACE_TEXT_GEN_ENDPOINT_URL'),
+            'task_type': 'text-generation'
+        }
+    )
+
+@pytest.mark.parametrize('setup_huggingface_mock', [['none']], indirect=True)
+def test_inference_endpoints_text_generation_invoke_model(setup_huggingface_mock):
+    model = HuggingfaceHubLargeLanguageModel()
+
+    response = model.invoke(
+        model='openchat/openchat_3.5',
+        credentials={
+            'huggingfacehub_api_type': 'inference_endpoints',
+            'huggingfacehub_api_token': os.environ.get('HUGGINGFACE_API_KEY'),
+            'huggingfacehub_endpoint_url': os.environ.get('HUGGINGFACE_TEXT_GEN_ENDPOINT_URL'),
+            'task_type': 'text-generation'
+        },
+        prompt_messages=[
+            UserPromptMessage(
+                content='Who are you?'
+            )
+        ],
+        model_parameters={
+            'temperature': 1.0,
+            'top_k': 2,
+            'top_p': 0.5,
+        },
+        stop=['How'],
+        stream=False,
+        user="abc-123"
+    )
+
+    assert isinstance(response, LLMResult)
+    assert len(response.message.content) > 0
+
+@pytest.mark.parametrize('setup_huggingface_mock', [['none']], indirect=True)
+def test_inference_endpoints_text_generation_invoke_stream_model(setup_huggingface_mock):
+    model = HuggingfaceHubLargeLanguageModel()
+
+    response = model.invoke(
+        model='openchat/openchat_3.5',
+        credentials={
+            'huggingfacehub_api_type': 'inference_endpoints',
+            'huggingfacehub_api_token': os.environ.get('HUGGINGFACE_API_KEY'),
+            'huggingfacehub_endpoint_url': os.environ.get('HUGGINGFACE_TEXT_GEN_ENDPOINT_URL'),
+            'task_type': 'text-generation'
+        },
+        prompt_messages=[
+            UserPromptMessage(
+                content='Who are you?'
+            )
+        ],
+        model_parameters={
+            'temperature': 1.0,
+            'top_k': 2,
+            'top_p': 0.5,
+        },
+        stop=['How'],
+        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
+
+@pytest.mark.parametrize('setup_huggingface_mock', [['none']], indirect=True)
+def test_inference_endpoints_text2text_generation_validate_credentials(setup_huggingface_mock):
+    model = HuggingfaceHubLargeLanguageModel()
+
+    with pytest.raises(CredentialsValidateFailedError):
+        model.validate_credentials(
+            model='google/mt5-base',
+            credentials={
+                'huggingfacehub_api_type': 'inference_endpoints',
+                'huggingfacehub_api_token': 'invalid_key',
+                'huggingfacehub_endpoint_url': os.environ.get('HUGGINGFACE_TEXT2TEXT_GEN_ENDPOINT_URL'),
+                'task_type': 'text2text-generation'
+            }
+        )
+
+    model.validate_credentials(
+        model='google/mt5-base',
+        credentials={
+            'huggingfacehub_api_type': 'inference_endpoints',
+            'huggingfacehub_api_token': os.environ.get('HUGGINGFACE_API_KEY'),
+            'huggingfacehub_endpoint_url': os.environ.get('HUGGINGFACE_TEXT2TEXT_GEN_ENDPOINT_URL'),
+            'task_type': 'text2text-generation'
+        }
+    )
+
+@pytest.mark.parametrize('setup_huggingface_mock', [['none']], indirect=True)
+def test_inference_endpoints_text2text_generation_invoke_model(setup_huggingface_mock):
+    model = HuggingfaceHubLargeLanguageModel()
+
+    response = model.invoke(
+        model='google/mt5-base',
+        credentials={
+            'huggingfacehub_api_type': 'inference_endpoints',
+            'huggingfacehub_api_token': os.environ.get('HUGGINGFACE_API_KEY'),
+            'huggingfacehub_endpoint_url': os.environ.get('HUGGINGFACE_TEXT2TEXT_GEN_ENDPOINT_URL'),
+            'task_type': 'text2text-generation'
+        },
+        prompt_messages=[
+            UserPromptMessage(
+                content='Who are you?'
+            )
+        ],
+        model_parameters={
+            'temperature': 1.0,
+            'top_k': 2,
+            'top_p': 0.5,
+        },
+        stop=['How'],
+        stream=False,
+        user="abc-123"
+    )
+
+    assert isinstance(response, LLMResult)
+    assert len(response.message.content) > 0
+
+@pytest.mark.parametrize('setup_huggingface_mock', [['none']], indirect=True)
+def test_inference_endpoints_text2text_generation_invoke_stream_model(setup_huggingface_mock):
+    model = HuggingfaceHubLargeLanguageModel()
+
+    response = model.invoke(
+        model='google/mt5-base',
+        credentials={
+            'huggingfacehub_api_type': 'inference_endpoints',
+            'huggingfacehub_api_token': os.environ.get('HUGGINGFACE_API_KEY'),
+            'huggingfacehub_endpoint_url': os.environ.get('HUGGINGFACE_TEXT2TEXT_GEN_ENDPOINT_URL'),
+            'task_type': 'text2text-generation'
+        },
+        prompt_messages=[
+            UserPromptMessage(
+                content='Who are you?'
+            )
+        ],
+        model_parameters={
+            'temperature': 1.0,
+            'top_k': 2,
+            'top_p': 0.5,
+        },
+        stop=['How'],
+        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 = HuggingfaceHubLargeLanguageModel()
+
+    num_tokens = model.get_num_tokens(
+        model='google/mt5-base',
+        credentials={
+            'huggingfacehub_api_type': 'inference_endpoints',
+            'huggingfacehub_api_token': os.environ.get('HUGGINGFACE_API_KEY'),
+            'huggingfacehub_endpoint_url': os.environ.get('HUGGINGFACE_TEXT2TEXT_GEN_ENDPOINT_URL'),
+            'task_type': 'text2text-generation'
+        },
+        prompt_messages=[
+            UserPromptMessage(
+                content='Hello World!'
+            )
+        ]
+    )
+
+    assert num_tokens == 7
--- a/api/tests/integration_tests/model_runtime/huggingface_hub/test_text_embedding.py
+++ b/api/tests/integration_tests/model_runtime/huggingface_hub/test_text_embedding.py
@@ -0,0 +1,120 @@
+import os
+
+import pytest
+
+from core.model_runtime.entities.text_embedding_entities import TextEmbeddingResult
+from core.model_runtime.errors.validate import CredentialsValidateFailedError
+from core.model_runtime.model_providers.huggingface_hub.text_embedding.text_embedding import \
+    HuggingfaceHubTextEmbeddingModel
+
+
+def test_hosted_inference_api_validate_credentials():
+    model = HuggingfaceHubTextEmbeddingModel()
+
+    with pytest.raises(CredentialsValidateFailedError):
+        model.validate_credentials(
+            model='facebook/bart-base',
+            credentials={
+                'huggingfacehub_api_type': 'hosted_inference_api',
+                'huggingfacehub_api_token': 'invalid_key',
+            }
+        )
+
+    model.validate_credentials(
+        model='facebook/bart-base',
+        credentials={
+            'huggingfacehub_api_type': 'hosted_inference_api',
+            'huggingfacehub_api_token': os.environ.get('HUGGINGFACE_API_KEY'),
+        }
+    )
+
+
+def test_hosted_inference_api_invoke_model():
+    model = HuggingfaceHubTextEmbeddingModel()
+
+    result = model.invoke(
+        model='facebook/bart-base',
+        credentials={
+            'huggingfacehub_api_type': 'hosted_inference_api',
+            'huggingfacehub_api_token': os.environ.get('HUGGINGFACE_API_KEY'),
+        },
+        texts=[
+            "hello",
+            "world"
+        ]
+    )
+
+    assert isinstance(result, TextEmbeddingResult)
+    assert len(result.embeddings) == 2
+    assert result.usage.total_tokens == 2
+
+
+def test_inference_endpoints_validate_credentials():
+    model = HuggingfaceHubTextEmbeddingModel()
+
+    with pytest.raises(CredentialsValidateFailedError):
+        model.validate_credentials(
+            model='all-MiniLM-L6-v2',
+            credentials={
+                'huggingfacehub_api_type': 'inference_endpoints',
+                'huggingfacehub_api_token': 'invalid_key',
+                'huggingface_namespace': 'Dify-AI',
+                'huggingfacehub_endpoint_url': os.environ.get('HUGGINGFACE_EMBEDDINGS_ENDPOINT_URL'),
+                'task_type': 'feature-extraction'
+            }
+        )
+
+    model.validate_credentials(
+        model='all-MiniLM-L6-v2',
+        credentials={
+            'huggingfacehub_api_type': 'inference_endpoints',
+            'huggingfacehub_api_token': os.environ.get('HUGGINGFACE_API_KEY'),
+            'huggingface_namespace': 'Dify-AI',
+            'huggingfacehub_endpoint_url': os.environ.get('HUGGINGFACE_EMBEDDINGS_ENDPOINT_URL'),
+            'task_type': 'feature-extraction'
+        }
+    )
+
+
+def test_inference_endpoints_invoke_model():
+    model = HuggingfaceHubTextEmbeddingModel()
+
+    result = model.invoke(
+        model='all-MiniLM-L6-v2',
+        credentials={
+            'huggingfacehub_api_type': 'inference_endpoints',
+            'huggingfacehub_api_token': os.environ.get('HUGGINGFACE_API_KEY'),
+            'huggingface_namespace': 'Dify-AI',
+            'huggingfacehub_endpoint_url': os.environ.get('HUGGINGFACE_EMBEDDINGS_ENDPOINT_URL'),
+            'task_type': 'feature-extraction'
+        },
+        texts=[
+            "hello",
+            "world"
+        ]
+    )
+
+    assert isinstance(result, TextEmbeddingResult)
+    assert len(result.embeddings) == 2
+    assert result.usage.total_tokens == 0
+
+
+def test_get_num_tokens():
+    model = HuggingfaceHubTextEmbeddingModel()
+
+    num_tokens = model.get_num_tokens(
+        model='all-MiniLM-L6-v2',
+        credentials={
+            'huggingfacehub_api_type': 'inference_endpoints',
+            'huggingfacehub_api_token': os.environ.get('HUGGINGFACE_API_KEY'),
+            'huggingface_namespace': 'Dify-AI',
+            'huggingfacehub_endpoint_url': os.environ.get('HUGGINGFACE_EMBEDDINGS_ENDPOINT_URL'),
+            'task_type': 'feature-extraction'
+        },
+        texts=[
+            "hello",
+            "world"
+        ]
+    )
+
+    assert num_tokens == 2