feat: bump version to 0.3.16

Co-authored-by: StyleZhang <jasonapring2015@outlook.com>

api/config.py

@@ -100,7 +100,7 @@ class Config:
         self.CONSOLE_URL = get_env('CONSOLE_URL')
         self.API_URL = get_env('API_URL')
         self.APP_URL = get_env('APP_URL')
-        self.CURRENT_VERSION = "0.3.15"
+        self.CURRENT_VERSION = "0.3.16"
         self.COMMIT_SHA = get_env('COMMIT_SHA')
         self.EDITION = "SELF_HOSTED"
         self.DEPLOY_ENV = get_env('DEPLOY_ENV')

api/core/embedding/cached_embedding.py

@@ -1,6 +1,7 @@
 import logging
 from typing import List
 
+import numpy as np
 from langchain.embeddings.base import Embeddings
 from sqlalchemy.exc import IntegrityError
 
@@ -32,14 +33,17 @@ class CacheEmbedding(Embeddings):
                 embedding_results = self._embeddings.client.embed_documents(embedding_queue_texts)
             except Exception as ex:
                 raise self._embeddings.handle_exceptions(ex)
-
             i = 0
+            normalized_embedding_results = []
             for text in embedding_queue_texts:
                 hash = helper.generate_text_hash(text)
 
                 try:
                     embedding = Embedding(model_name=self._embeddings.name, hash=hash)
-                    embedding.set_embedding(embedding_results[i])
+                    vector = embedding_results[i]
+                    normalized_embedding = (vector / np.linalg.norm(vector)).tolist()
+                    normalized_embedding_results.append(normalized_embedding)
+                    embedding.set_embedding(normalized_embedding)
                     db.session.add(embedding)
                     db.session.commit()
                 except IntegrityError:
@@ -51,7 +55,7 @@ class CacheEmbedding(Embeddings):
                 finally:
                     i += 1
 
-            text_embeddings.extend(embedding_results)
+            text_embeddings.extend(normalized_embedding_results)
         return text_embeddings
 
     def embed_query(self, text: str) -> List[float]:
@@ -64,6 +68,7 @@ class CacheEmbedding(Embeddings):
 
         try:
             embedding_results = self._embeddings.client.embed_query(text)
+            embedding_results = (embedding_results / np.linalg.norm(embedding_results)).tolist()
         except Exception as ex:
             raise self._embeddings.handle_exceptions(ex)
 
@@ -79,4 +84,3 @@ class CacheEmbedding(Embeddings):
 
         return embedding_results
 
-

api/core/model_providers/models/llm/huggingface_hub_model.py

@@ -1,16 +1,14 @@
-import decimal
-from functools import wraps
 from typing import List, Optional, Any
 
 from langchain import HuggingFaceHub
 from langchain.callbacks.manager import Callbacks
-from langchain.llms import HuggingFaceEndpoint
 from langchain.schema import LLMResult
 
 from core.model_providers.error import LLMBadRequestError
 from core.model_providers.models.llm.base import BaseLLM
-from core.model_providers.models.entity.message import PromptMessage, MessageType
+from core.model_providers.models.entity.message import PromptMessage
 from core.model_providers.models.entity.model_params import ModelMode, ModelKwargs
+from core.third_party.langchain.llms.huggingface_endpoint_llm import HuggingFaceEndpointLLM
 
 
 class HuggingfaceHubModel(BaseLLM):
@@ -19,12 +17,12 @@ class HuggingfaceHubModel(BaseLLM):
     def _init_client(self) -> Any:
         provider_model_kwargs = self._to_model_kwargs_input(self.model_rules, self.model_kwargs)
         if self.credentials['huggingfacehub_api_type'] == 'inference_endpoints':
-            client = HuggingFaceEndpoint(
+            client = HuggingFaceEndpointLLM(
                 endpoint_url=self.credentials['huggingfacehub_endpoint_url'],
-                task='text2text-generation',
+                task=self.credentials['task_type'],
                 model_kwargs=provider_model_kwargs,
                 huggingfacehub_api_token=self.credentials['huggingfacehub_api_token'],
-                callbacks=self.callbacks,
+                callbacks=self.callbacks
             )
         else:
             client = HuggingFaceHub(

api/core/model_providers/providers/huggingface_hub_provider.py

@@ -2,7 +2,6 @@ import json
 from typing import Type
 
 from huggingface_hub import HfApi
-from langchain.llms import HuggingFaceEndpoint
 
 from core.helper import encrypter
 from core.model_providers.models.entity.model_params import KwargRule, ModelKwargsRules, ModelType
@@ -10,6 +9,7 @@ from core.model_providers.models.llm.huggingface_hub_model import HuggingfaceHub
 from core.model_providers.providers.base import BaseModelProvider, CredentialsValidateFailedError
 
 from core.model_providers.models.base import BaseProviderModel
+from core.third_party.langchain.llms.huggingface_endpoint_llm import HuggingFaceEndpointLLM
 from models.provider import ProviderType
 
 
@@ -85,10 +85,16 @@ class HuggingfaceHubProvider(BaseModelProvider):
             if 'huggingfacehub_endpoint_url' not in credentials:
                 raise CredentialsValidateFailedError('Hugging Face Hub Endpoint URL must be provided.')
 
+            if 'task_type' not in credentials:
+                raise CredentialsValidateFailedError('Task Type must be provided.')
+
+            if credentials['task_type'] not in ("text2text-generation", "text-generation", "summarization"):
+                raise CredentialsValidateFailedError('Task Type must be one of text2text-generation, text-generation, summarization.')
+
             try:
-                llm = HuggingFaceEndpoint(
+                llm = HuggingFaceEndpointLLM(
                     endpoint_url=credentials['huggingfacehub_endpoint_url'],
-                    task="text2text-generation",
+                    task=credentials['task_type'],
                     model_kwargs={"temperature": 0.5, "max_new_tokens": 200},
                     huggingfacehub_api_token=credentials['huggingfacehub_api_token']
                 )
@@ -160,6 +166,10 @@ class HuggingfaceHubProvider(BaseModelProvider):
             }
 
         credentials = json.loads(provider_model.encrypted_config)
+
+        if 'task_type' not in credentials:
+            credentials['task_type'] = 'text-generation'
+
         if credentials['huggingfacehub_api_token']:
             credentials['huggingfacehub_api_token'] = encrypter.decrypt_token(
                 self.provider.tenant_id,

api/core/third_party/langchain/llms/huggingface_endpoint_llm.py

@@ -0,0 +1,39 @@
+from typing import Dict
+
+from langchain.llms import HuggingFaceEndpoint
+from pydantic import Extra, root_validator
+
+from langchain.utils import get_from_dict_or_env
+
+
+class HuggingFaceEndpointLLM(HuggingFaceEndpoint):
+    """HuggingFace Endpoint models.
+
+    To use, you should have the ``huggingface_hub`` python package installed, and the
+    environment variable ``HUGGINGFACEHUB_API_TOKEN`` set with your API token, or pass
+    it as a named parameter to the constructor.
+
+    Only supports `text-generation` and `text2text-generation` for now.
+
+    Example:
+        .. code-block:: python
+
+            from langchain.llms import HuggingFaceEndpoint
+            endpoint_url = (
+                "https://abcdefghijklmnop.us-east-1.aws.endpoints.huggingface.cloud"
+            )
+            hf = HuggingFaceEndpoint(
+                endpoint_url=endpoint_url,
+                huggingfacehub_api_token="my-api-key"
+            )
+    """
+
+    @root_validator(allow_reuse=True)
+    def validate_environment(cls, values: Dict) -> Dict:
+        """Validate that api key and python package exists in environment."""
+        huggingfacehub_api_token = get_from_dict_or_env(
+            values, "huggingfacehub_api_token", "HUGGINGFACEHUB_API_TOKEN"
+        )
+
+        values["huggingfacehub_api_token"] = huggingfacehub_api_token
+        return values

api/requirements.txt

@@ -49,4 +49,4 @@ huggingface_hub~=0.16.4
 transformers~=4.31.0
 stripe~=5.5.0
 pandas==1.5.3
-xinference==0.2.0
+xinference==0.2.1

api/services/hit_testing_service.py

@@ -19,7 +19,7 @@ from models.dataset import Dataset, DocumentSegment, DatasetQuery
 class HitTestingService:
     @classmethod
     def retrieve(cls, dataset: Dataset, query: str, account: Account, limit: int = 10) -> dict:
-        if dataset.available_document_count == 0 or dataset.available_document_count == 0:
+        if dataset.available_document_count == 0 or dataset.available_segment_count == 0:
             return {
                 "query": {
                     "content": query,

api/tests/unit_tests/model_providers/test_huggingface_hub_provider.py

@@ -17,7 +17,8 @@ HOSTED_INFERENCE_API_VALIDATE_CREDENTIAL = {
 INFERENCE_ENDPOINTS_VALIDATE_CREDENTIAL = {
     'huggingfacehub_api_type': 'inference_endpoints',
     'huggingfacehub_api_token': 'valid_key',
-    'huggingfacehub_endpoint_url': 'valid_url'
+    'huggingfacehub_endpoint_url': 'valid_url',
+    'task_type': 'text-generation'
 }
 
 def encrypt_side_effect(tenant_id, encrypt_key):

docker/docker-compose.yaml

@@ -2,7 +2,7 @@ version: '3.1'
 services:
   # API service
   api:
-    image: langgenius/dify-api:0.3.15
+    image: langgenius/dify-api:0.3.16
     restart: always
     environment:
       # Startup mode, 'api' starts the API server.
@@ -124,7 +124,7 @@ services:
   # worker service
   # The Celery worker for processing the queue.
   worker:
-    image: langgenius/dify-api:0.3.15
+    image: langgenius/dify-api:0.3.16
     restart: always
     environment:
       # Startup mode, 'worker' starts the Celery worker for processing the queue.
@@ -176,7 +176,7 @@ services:
 
   # Frontend web application.
   web:
-    image: langgenius/dify-web:0.3.15
+    image: langgenius/dify-web:0.3.16
     restart: always
     environment:
       EDITION: SELF_HOSTED

web/.gitignore

@@ -15,6 +15,8 @@
 # production
 /build
 
+/.history
+
 # misc
 .DS_Store
 *.pem

web/app/components/header/account-setting/model-page/configs/huggingface_hub.tsx

@@ -38,6 +38,7 @@ const config: ProviderConfig = {
     defaultValue: {
       model_type: 'text-generation',
       huggingfacehub_api_type: 'hosted_inference_api',
+      task_type: 'text-generation',
     },
     validateKeys: (v?: FormValue) => {
       if (v?.huggingfacehub_api_type === 'hosted_inference_api') {
@@ -51,10 +52,36 @@ const config: ProviderConfig = {
           'huggingfacehub_api_token',
           'model_name',
           'huggingfacehub_endpoint_url',
+          'task_type',
         ]
       }
       return []
     },
+    filterValue: (v?: FormValue) => {
+      let filteredKeys: string[] = []
+      if (v?.huggingfacehub_api_type === 'hosted_inference_api') {
+        filteredKeys = [
+          'huggingfacehub_api_type',
+          'huggingfacehub_api_token',
+          'model_name',
+          'model_type',
+        ]
+      }
+      if (v?.huggingfacehub_api_type === 'inference_endpoints') {
+        filteredKeys = [
+          'huggingfacehub_api_type',
+          'huggingfacehub_api_token',
+          'model_name',
+          'huggingfacehub_endpoint_url',
+          'task_type',
+          'model_type',
+        ]
+      }
+      return filteredKeys.reduce((prev: FormValue, next: string) => {
+        prev[next] = v?.[next] || ''
+        return prev
+      }, {})
+    },
     fields: [
       {
         type: 'radio',
@@ -120,6 +147,32 @@ const config: ProviderConfig = {
           'zh-Hans': '在此输入您的端点 URL',
         },
       },
+      {
+        hidden: (value?: FormValue) => value?.huggingfacehub_api_type === 'hosted_inference_api',
+        type: 'radio',
+        key: 'task_type',
+        required: true,
+        label: {
+          'en': 'Task',
+          'zh-Hans': 'Task',
+        },
+        options: [
+          {
+            key: 'text2text-generation',
+            label: {
+              'en': 'Text-to-Text Generation',
+              'zh-Hans': 'Text-to-Text Generation',
+            },
+          },
+          {
+            key: 'text-generation',
+            label: {
+              'en': 'Text Generation',
+              'zh-Hans': 'Text Generation',
+            },
+          },
+        ],
+      },
     ],
   },
 }

web/app/components/header/account-setting/model-page/declarations.ts

@@ -91,6 +91,7 @@ export type ProviderConfigModal = {
   icon: ReactElement
   defaultValue?: FormValue
   validateKeys?: string[] | ((v?: FormValue) => string[])
+  filterValue?: (v?: FormValue) => FormValue
   fields: Field[]
   link: {
     href: string

web/app/components/header/account-setting/model-page/index.tsx

@@ -124,8 +124,9 @@ const ModelPage = () => {
     updateModelList(ModelType.embeddings)
     mutateProviders()
   }
-  const handleSave = async (v?: FormValue) => {
-    if (v && modelModalConfig) {
+  const handleSave = async (originValue?: FormValue) => {
+    if (originValue && modelModalConfig) {
+      const v = modelModalConfig.filterValue ? modelModalConfig.filterValue(originValue) : originValue
       let body, url
       if (ConfigurableProviders.includes(modelModalConfig.key)) {
         const { model_name, model_type, ...config } = v

web/app/components/header/account-setting/model-page/model-modal/Form.tsx

@@ -68,7 +68,7 @@ const Form: FC<FormProps> = ({
           return true
         },
         run: () => {
-          return validateModelProviderFn(modelModal!.key, v)
+          return validateModelProviderFn(modelModal!.key, modelModal?.filterValue ? modelModal?.filterValue(v) : v)
         },
       })
     }

web/package.json

@@ -1,6 +1,6 @@
 {
   "name": "dify-web",
-  "version": "0.3.15",
+  "version": "0.3.16",
   "private": true,
   "scripts": {
     "dev": "next dev",