Merge branch 'main' into feat/agent-image

api/Dockerfile

@@ -7,7 +7,7 @@ LABEL maintainer="takatost@gmail.com"
 FROM base as packages
 
 RUN apt-get update \
-    && apt-get install -y --no-install-recommends gcc g++ libc-dev libffi-dev
+    && apt-get install -y --no-install-recommends gcc g++ libc-dev libffi-dev libgmp-dev libmpfr-dev libmpc-dev
 
 COPY requirements.txt /requirements.txt
 
@@ -32,7 +32,7 @@ ENV TZ UTC
 WORKDIR /app/api
 
 RUN apt-get update \
-    && apt-get install -y --no-install-recommends curl wget vim nodejs ffmpeg \
+    && apt-get install -y --no-install-recommends curl wget vim nodejs ffmpeg libgmp-dev libmpfr-dev libmpc-dev \
     && apt-get autoremove \
     && rm -rf /var/lib/apt/lists/*
 

api/commands.py

@@ -339,26 +339,7 @@ def create_qdrant_indexes():
 
                             )
                         except Exception:
-                            try:
-                                embedding_model = model_manager.get_default_model_instance(
-                                    tenant_id=dataset.tenant_id,
-                                    model_type=ModelType.TEXT_EMBEDDING,
-                                )
-                                dataset.embedding_model = embedding_model.model
-                                dataset.embedding_model_provider = embedding_model.provider
-                            except Exception:
-
-                                provider = Provider(
-                                    id='provider_id',
-                                    tenant_id=dataset.tenant_id,
-                                    provider_name='openai',
-                                    provider_type=ProviderType.SYSTEM.value,
-                                    encrypted_config=json.dumps({'openai_api_key': 'TEST'}),
-                                    is_valid=True,
-                                )
-                                model_provider = OpenAIProvider(provider=provider)
-                                embedding_model = OpenAIEmbedding(name="text-embedding-ada-002",
-                                                                  model_provider=model_provider)
+                            continue
                         embeddings = CacheEmbedding(embedding_model)
 
                         from core.index.vector_index.qdrant_vector_index import QdrantConfig, QdrantVectorIndex
@@ -405,7 +386,7 @@ def update_qdrant_indexes():
                 .order_by(Dataset.created_at.desc()).paginate(page=page, per_page=50)
         except NotFound:
             break
-
+        model_manager = ModelManager()
         page += 1
         for dataset in datasets:
             if dataset.index_struct_dict:
@@ -413,23 +394,15 @@ def update_qdrant_indexes():
                     try:
                         click.echo('Update dataset qdrant index: {}'.format(dataset.id))
                         try:
-                            embedding_model = ModelFactory.get_embedding_model(
+                            embedding_model = model_manager.get_model_instance(
                                 tenant_id=dataset.tenant_id,
-                                model_provider_name=dataset.embedding_model_provider,
-                                model_name=dataset.embedding_model
+                                provider=dataset.embedding_model_provider,
+                                model_type=ModelType.TEXT_EMBEDDING,
+                                model=dataset.embedding_model
+
                             )
                         except Exception:
-                            provider = Provider(
-                                id='provider_id',
-                                tenant_id=dataset.tenant_id,
-                                provider_name='openai',
-                                provider_type=ProviderType.CUSTOM.value,
-                                encrypted_config=json.dumps({'openai_api_key': 'TEST'}),
-                                is_valid=True,
-                            )
-                            model_provider = OpenAIProvider(provider=provider)
-                            embedding_model = OpenAIEmbedding(name="text-embedding-ada-002",
-                                                              model_provider=model_provider)
+                            continue
                         embeddings = CacheEmbedding(embedding_model)
 
                         from core.index.vector_index.qdrant_vector_index import QdrantConfig, QdrantVectorIndex
@@ -524,23 +497,17 @@ def deal_dataset_vector(flask_app: Flask, dataset: Dataset, normalization_count:
         try:
             click.echo('restore dataset index: {}'.format(dataset.id))
             try:
-                embedding_model = ModelFactory.get_embedding_model(
+                model_manager = ModelManager()
+
+                embedding_model = model_manager.get_model_instance(
                     tenant_id=dataset.tenant_id,
-                    model_provider_name=dataset.embedding_model_provider,
-                    model_name=dataset.embedding_model
+                    provider=dataset.embedding_model_provider,
+                    model_type=ModelType.TEXT_EMBEDDING,
+                    model=dataset.embedding_model
+
                 )
             except Exception:
-                provider = Provider(
-                    id='provider_id',
-                    tenant_id=dataset.tenant_id,
-                    provider_name='openai',
-                    provider_type=ProviderType.CUSTOM.value,
-                    encrypted_config=json.dumps({'openai_api_key': 'TEST'}),
-                    is_valid=True,
-                )
-                model_provider = OpenAIProvider(provider=provider)
-                embedding_model = OpenAIEmbedding(name="text-embedding-ada-002",
-                                                  model_provider=model_provider)
+                pass
             embeddings = CacheEmbedding(embedding_model)
             dataset_collection_binding = db.session.query(DatasetCollectionBinding). \
                 filter(DatasetCollectionBinding.provider_name == embedding_model.model_provider.provider_name,

api/config.py

@@ -40,17 +40,11 @@ DEFAULTS = {
     'HOSTED_OPENAI_QUOTA_LIMIT': 200,
     'HOSTED_OPENAI_TRIAL_ENABLED': 'False',
     'HOSTED_OPENAI_PAID_ENABLED': 'False',
-    'HOSTED_OPENAI_PAID_INCREASE_QUOTA': 1,
-    'HOSTED_OPENAI_PAID_MIN_QUANTITY': 1,
-    'HOSTED_OPENAI_PAID_MAX_QUANTITY': 1,
     'HOSTED_AZURE_OPENAI_ENABLED': 'False',
     'HOSTED_AZURE_OPENAI_QUOTA_LIMIT': 200,
     'HOSTED_ANTHROPIC_QUOTA_LIMIT': 600000,
     'HOSTED_ANTHROPIC_TRIAL_ENABLED': 'False',
     'HOSTED_ANTHROPIC_PAID_ENABLED': 'False',
-    'HOSTED_ANTHROPIC_PAID_INCREASE_QUOTA': 1,
-    'HOSTED_ANTHROPIC_PAID_MIN_QUANTITY': 1,
-    'HOSTED_ANTHROPIC_PAID_MAX_QUANTITY': 1,
     'HOSTED_MODERATION_ENABLED': 'False',
     'HOSTED_MODERATION_PROVIDERS': '',
     'CLEAN_DAY_SETTING': 30,
@@ -93,7 +87,7 @@ class Config:
         # ------------------------
         # General Configurations.
         # ------------------------
-        self.CURRENT_VERSION = "0.5.0"
+        self.CURRENT_VERSION = "0.5.2"
         self.COMMIT_SHA = get_env('COMMIT_SHA')
         self.EDITION = "SELF_HOSTED"
         self.DEPLOY_ENV = get_env('DEPLOY_ENV')
@@ -262,10 +256,6 @@ class Config:
         self.HOSTED_OPENAI_TRIAL_ENABLED = get_bool_env('HOSTED_OPENAI_TRIAL_ENABLED')
         self.HOSTED_OPENAI_QUOTA_LIMIT = int(get_env('HOSTED_OPENAI_QUOTA_LIMIT'))
         self.HOSTED_OPENAI_PAID_ENABLED = get_bool_env('HOSTED_OPENAI_PAID_ENABLED')
-        self.HOSTED_OPENAI_PAID_STRIPE_PRICE_ID = get_env('HOSTED_OPENAI_PAID_STRIPE_PRICE_ID')
-        self.HOSTED_OPENAI_PAID_INCREASE_QUOTA = int(get_env('HOSTED_OPENAI_PAID_INCREASE_QUOTA'))
-        self.HOSTED_OPENAI_PAID_MIN_QUANTITY = int(get_env('HOSTED_OPENAI_PAID_MIN_QUANTITY'))
-        self.HOSTED_OPENAI_PAID_MAX_QUANTITY = int(get_env('HOSTED_OPENAI_PAID_MAX_QUANTITY'))
 
         self.HOSTED_AZURE_OPENAI_ENABLED = get_bool_env('HOSTED_AZURE_OPENAI_ENABLED')
         self.HOSTED_AZURE_OPENAI_API_KEY = get_env('HOSTED_AZURE_OPENAI_API_KEY')
@@ -277,10 +267,6 @@ class Config:
         self.HOSTED_ANTHROPIC_TRIAL_ENABLED = get_bool_env('HOSTED_ANTHROPIC_TRIAL_ENABLED')
         self.HOSTED_ANTHROPIC_QUOTA_LIMIT = int(get_env('HOSTED_ANTHROPIC_QUOTA_LIMIT'))
         self.HOSTED_ANTHROPIC_PAID_ENABLED = get_bool_env('HOSTED_ANTHROPIC_PAID_ENABLED')
-        self.HOSTED_ANTHROPIC_PAID_STRIPE_PRICE_ID = get_env('HOSTED_ANTHROPIC_PAID_STRIPE_PRICE_ID')
-        self.HOSTED_ANTHROPIC_PAID_INCREASE_QUOTA = int(get_env('HOSTED_ANTHROPIC_PAID_INCREASE_QUOTA'))
-        self.HOSTED_ANTHROPIC_PAID_MIN_QUANTITY = int(get_env('HOSTED_ANTHROPIC_PAID_MIN_QUANTITY'))
-        self.HOSTED_ANTHROPIC_PAID_MAX_QUANTITY = int(get_env('HOSTED_ANTHROPIC_PAID_MAX_QUANTITY'))
 
         self.HOSTED_MINIMAX_ENABLED = get_bool_env('HOSTED_MINIMAX_ENABLED')
         self.HOSTED_SPARK_ENABLED = get_bool_env('HOSTED_SPARK_ENABLED')

api/controllers/console/__init__.py

@@ -19,5 +19,3 @@ from .explore import audio, completion, conversation, installed_app, message, pa
 from .workspace import account, members, model_providers, models, tool_providers, workspace
 # Import billing controllers
 from .billing import billing
-# Import operation controllers
-from .operation import operation

api/controllers/console/apikey.py

@@ -61,9 +61,7 @@ class BaseApiKeyListResource(Resource):
         resource_id = str(resource_id)
         _get_resource(resource_id, current_user.current_tenant_id,
                       self.resource_model)
-
-        # The role of the current user in the ta table must be admin or owner
-        if current_user.current_tenant.current_role not in ['admin', 'owner']:
+        if not current_user.is_admin_or_owner:
             raise Forbidden()
 
         current_key_count = db.session.query(ApiToken). \
@@ -102,7 +100,7 @@ class BaseApiKeyResource(Resource):
                       self.resource_model)
 
         # The role of the current user in the ta table must be admin or owner
-        if current_user.current_tenant.current_role not in ['admin', 'owner']:
+        if not current_user.is_admin_or_owner:
             raise Forbidden()
 
         key = db.session.query(ApiToken). \

api/controllers/console/app/annotation.py

@@ -21,7 +21,7 @@ class AnnotationReplyActionApi(Resource):
     @cloud_edition_billing_resource_check('annotation')
     def post(self, app_id, action):
         # The role of the current user in the ta table must be admin or owner
-        if current_user.current_tenant.current_role not in ['admin', 'owner']:
+        if not current_user.is_admin_or_owner:
             raise Forbidden()
 
         app_id = str(app_id)
@@ -45,7 +45,7 @@ class AppAnnotationSettingDetailApi(Resource):
     @account_initialization_required
     def get(self, app_id):
         # The role of the current user in the ta table must be admin or owner
-        if current_user.current_tenant.current_role not in ['admin', 'owner']:
+        if not current_user.is_admin_or_owner:
             raise Forbidden()
 
         app_id = str(app_id)
@@ -59,7 +59,7 @@ class AppAnnotationSettingUpdateApi(Resource):
     @account_initialization_required
     def post(self, app_id, annotation_setting_id):
         # The role of the current user in the ta table must be admin or owner
-        if current_user.current_tenant.current_role not in ['admin', 'owner']:
+        if not current_user.is_admin_or_owner:
             raise Forbidden()
 
         app_id = str(app_id)
@@ -80,7 +80,7 @@ class AnnotationReplyActionStatusApi(Resource):
     @cloud_edition_billing_resource_check('annotation')
     def get(self, app_id, job_id, action):
         # The role of the current user in the ta table must be admin or owner
-        if current_user.current_tenant.current_role not in ['admin', 'owner']:
+        if not current_user.is_admin_or_owner:
             raise Forbidden()
 
         job_id = str(job_id)
@@ -108,7 +108,7 @@ class AnnotationListApi(Resource):
     @account_initialization_required
     def get(self, app_id):
         # The role of the current user in the ta table must be admin or owner
-        if current_user.current_tenant.current_role not in ['admin', 'owner']:
+        if not current_user.is_admin_or_owner:
             raise Forbidden()
 
         page = request.args.get('page', default=1, type=int)
@@ -133,7 +133,7 @@ class AnnotationExportApi(Resource):
     @account_initialization_required
     def get(self, app_id):
         # The role of the current user in the ta table must be admin or owner
-        if current_user.current_tenant.current_role not in ['admin', 'owner']:
+        if not current_user.is_admin_or_owner:
             raise Forbidden()
 
         app_id = str(app_id)
@@ -152,7 +152,7 @@ class AnnotationCreateApi(Resource):
     @marshal_with(annotation_fields)
     def post(self, app_id):
         # The role of the current user in the ta table must be admin or owner
-        if current_user.current_tenant.current_role not in ['admin', 'owner']:
+        if not current_user.is_admin_or_owner:
             raise Forbidden()
 
         app_id = str(app_id)
@@ -172,7 +172,7 @@ class AnnotationUpdateDeleteApi(Resource):
     @marshal_with(annotation_fields)
     def post(self, app_id, annotation_id):
         # The role of the current user in the ta table must be admin or owner
-        if current_user.current_tenant.current_role not in ['admin', 'owner']:
+        if not current_user.is_admin_or_owner:
             raise Forbidden()
 
         app_id = str(app_id)
@@ -189,7 +189,7 @@ class AnnotationUpdateDeleteApi(Resource):
     @account_initialization_required
     def delete(self, app_id, annotation_id):
         # The role of the current user in the ta table must be admin or owner
-        if current_user.current_tenant.current_role not in ['admin', 'owner']:
+        if not current_user.is_admin_or_owner:
             raise Forbidden()
 
         app_id = str(app_id)
@@ -205,7 +205,7 @@ class AnnotationBatchImportApi(Resource):
     @cloud_edition_billing_resource_check('annotation')
     def post(self, app_id):
         # The role of the current user in the ta table must be admin or owner
-        if current_user.current_tenant.current_role not in ['admin', 'owner']:
+        if not current_user.is_admin_or_owner:
             raise Forbidden()
 
         app_id = str(app_id)
@@ -230,7 +230,7 @@ class AnnotationBatchImportStatusApi(Resource):
     @cloud_edition_billing_resource_check('annotation')
     def get(self, app_id, job_id):
         # The role of the current user in the ta table must be admin or owner
-        if current_user.current_tenant.current_role not in ['admin', 'owner']:
+        if not current_user.is_admin_or_owner:
             raise Forbidden()
 
         job_id = str(job_id)
@@ -257,7 +257,7 @@ class AnnotationHitHistoryListApi(Resource):
     @account_initialization_required
     def get(self, app_id, annotation_id):
         # The role of the current user in the table must be admin or owner
-        if current_user.current_tenant.current_role not in ['admin', 'owner']:
+        if not current_user.is_admin_or_owner:
             raise Forbidden()
 
         page = request.args.get('page', default=1, type=int)

api/controllers/console/app/app.py

@@ -88,7 +88,7 @@ class AppListApi(Resource):
         args = parser.parse_args()
 
         # The role of the current user in the ta table must be admin or owner
-        if current_user.current_tenant.current_role not in ['admin', 'owner']:
+        if not current_user.is_admin_or_owner:
             raise Forbidden()
 
         try:
@@ -237,7 +237,7 @@ class AppApi(Resource):
         """Delete app"""
         app_id = str(app_id)
 
-        if current_user.current_tenant.current_role not in ['admin', 'owner']:
+        if not current_user.is_admin_or_owner:
             raise Forbidden()
 
         app = _get_app(app_id, current_user.current_tenant_id)

api/controllers/console/app/message.py

@@ -157,7 +157,7 @@ class MessageAnnotationApi(Resource):
     @marshal_with(annotation_fields)
     def post(self, app_id):
         # The role of the current user in the ta table must be admin or owner
-        if current_user.current_tenant.current_role not in ['admin', 'owner']:
+        if not current_user.is_admin_or_owner:
             raise Forbidden()
 
         app_id = str(app_id)

api/controllers/console/app/site.py

@@ -42,7 +42,7 @@ class AppSite(Resource):
         app_model = _get_app(app_id)
 
         # The role of the current user in the ta table must be admin or owner
-        if current_user.current_tenant.current_role not in ['admin', 'owner']:
+        if not current_user.is_admin_or_owner:
             raise Forbidden()
 
         site = db.session.query(Site). \
@@ -88,7 +88,7 @@ class AppSiteAccessTokenReset(Resource):
         app_model = _get_app(app_id)
 
         # The role of the current user in the ta table must be admin or owner
-        if current_user.current_tenant.current_role not in ['admin', 'owner']:
+        if not current_user.is_admin_or_owner:
             raise Forbidden()
 
         site = db.session.query(Site).filter(Site.app_id == app_model.id).first()

api/controllers/console/auth/data_source_oauth.py

@@ -30,7 +30,7 @@ def get_oauth_providers():
 class OAuthDataSource(Resource):
     def get(self, provider: str):
         # The role of the current user in the table must be admin or owner
-        if current_user.current_tenant.current_role not in ['admin', 'owner']:
+        if not current_user.is_admin_or_owner:
             raise Forbidden()
         OAUTH_DATASOURCE_PROVIDERS = get_oauth_providers()
         with current_app.app_context():

api/controllers/console/billing/billing.py

@@ -20,7 +20,7 @@ class Subscription(Resource):
         parser.add_argument('interval', type=str, required=True, location='args', choices=['month', 'year'])
         args = parser.parse_args()
 
-        BillingService.is_tenant_owner(current_user)
+        BillingService.is_tenant_owner_or_admin(current_user)
 
         return BillingService.get_subscription(args['plan'],
                                                args['interval'],
@@ -35,8 +35,8 @@ class Invoices(Resource):
     @account_initialization_required
     @only_edition_cloud
     def get(self):
-        BillingService.is_tenant_owner(current_user)
-        return BillingService.get_invoices(current_user.email)
+        BillingService.is_tenant_owner_or_admin(current_user)
+        return BillingService.get_invoices(current_user.email, current_user.current_tenant_id)
 
 
 api.add_resource(Subscription, '/billing/subscription')

api/controllers/console/datasets/datasets.py

@@ -103,7 +103,7 @@ class DatasetListApi(Resource):
         args = parser.parse_args()
 
         # The role of the current user in the ta table must be admin or owner
-        if current_user.current_tenant.current_role not in ['admin', 'owner']:
+        if not current_user.is_admin_or_owner:
             raise Forbidden()
 
         try:
@@ -187,7 +187,7 @@ class DatasetApi(Resource):
         args = parser.parse_args()
 
         # The role of the current user in the ta table must be admin or owner
-        if current_user.current_tenant.current_role not in ['admin', 'owner']:
+        if not current_user.is_admin_or_owner:
             raise Forbidden()
 
         dataset = DatasetService.update_dataset(
@@ -205,7 +205,7 @@ class DatasetApi(Resource):
         dataset_id_str = str(dataset_id)
 
         # The role of the current user in the ta table must be admin or owner
-        if current_user.current_tenant.current_role not in ['admin', 'owner']:
+        if not current_user.is_admin_or_owner:
             raise Forbidden()
 
         if DatasetService.delete_dataset(dataset_id_str, current_user):
@@ -391,7 +391,7 @@ class DatasetApiKeyApi(Resource):
     @marshal_with(api_key_fields)
     def post(self):
         # The role of the current user in the ta table must be admin or owner
-        if current_user.current_tenant.current_role not in ['admin', 'owner']:
+        if not current_user.is_admin_or_owner:
             raise Forbidden()
 
         current_key_count = db.session.query(ApiToken). \
@@ -425,7 +425,7 @@ class DatasetApiDeleteApi(Resource):
         api_key_id = str(api_key_id)
 
         # The role of the current user in the ta table must be admin or owner
-        if current_user.current_tenant.current_role not in ['admin', 'owner']:
+        if not current_user.is_admin_or_owner:
             raise Forbidden()
 
         key = db.session.query(ApiToken). \

api/controllers/console/datasets/datasets_document.py

@@ -204,7 +204,7 @@ class DatasetDocumentListApi(Resource):
             raise NotFound('Dataset not found.')
 
         # The role of the current user in the ta table must be admin or owner
-        if current_user.current_tenant.current_role not in ['admin', 'owner']:
+        if not current_user.is_admin_or_owner:
             raise Forbidden()
 
         try:
@@ -256,7 +256,7 @@ class DatasetInitApi(Resource):
     @cloud_edition_billing_resource_check('vector_space')
     def post(self):
         # The role of the current user in the ta table must be admin or owner
-        if current_user.current_tenant.current_role not in ['admin', 'owner']:
+        if not current_user.is_admin_or_owner:
             raise Forbidden()
 
         parser = reqparse.RequestParser()
@@ -599,7 +599,7 @@ class DocumentProcessingApi(DocumentResource):
         document = self.get_document(dataset_id, document_id)
 
         # The role of the current user in the ta table must be admin or owner
-        if current_user.current_tenant.current_role not in ['admin', 'owner']:
+        if not current_user.is_admin_or_owner:
             raise Forbidden()
 
         if action == "pause":
@@ -663,7 +663,7 @@ class DocumentMetadataApi(DocumentResource):
         doc_metadata = req_data.get('doc_metadata')
 
         # The role of the current user in the ta table must be admin or owner
-        if current_user.current_tenant.current_role not in ['admin', 'owner']:
+        if not current_user.is_admin_or_owner:
             raise Forbidden()
 
         if doc_type is None or doc_metadata is None:
@@ -710,7 +710,7 @@ class DocumentStatusApi(DocumentResource):
         document = self.get_document(dataset_id, document_id)
 
         # The role of the current user in the ta table must be admin or owner
-        if current_user.current_tenant.current_role not in ['admin', 'owner']:
+        if not current_user.is_admin_or_owner:
             raise Forbidden()
 
         indexing_cache_key = 'document_{}_indexing'.format(document.id)

api/controllers/console/datasets/datasets_segments.py

@@ -123,7 +123,7 @@ class DatasetDocumentSegmentApi(Resource):
         # check user's model setting
         DatasetService.check_dataset_model_setting(dataset)
         # The role of the current user in the ta table must be admin or owner
-        if current_user.current_tenant.current_role not in ['admin', 'owner']:
+        if not current_user.is_admin_or_owner:
             raise Forbidden()
 
         try:
@@ -219,7 +219,7 @@ class DatasetDocumentSegmentAddApi(Resource):
         if not document:
             raise NotFound('Document not found.')
         # The role of the current user in the ta table must be admin or owner
-        if current_user.current_tenant.current_role not in ['admin', 'owner']:
+        if not current_user.is_admin_or_owner:
             raise Forbidden()
         # check embedding model setting
         if dataset.indexing_technique == 'high_quality':
@@ -298,7 +298,7 @@ class DatasetDocumentSegmentUpdateApi(Resource):
         if not segment:
             raise NotFound('Segment not found.')
         # The role of the current user in the ta table must be admin or owner
-        if current_user.current_tenant.current_role not in ['admin', 'owner']:
+        if not current_user.is_admin_or_owner:
             raise Forbidden()
         try:
             DatasetService.check_dataset_permission(dataset, current_user)
@@ -342,7 +342,7 @@ class DatasetDocumentSegmentUpdateApi(Resource):
         if not segment:
             raise NotFound('Segment not found.')
         # The role of the current user in the ta table must be admin or owner
-        if current_user.current_tenant.current_role not in ['admin', 'owner']:
+        if not current_user.is_admin_or_owner:
             raise Forbidden()
         try:
             DatasetService.check_dataset_permission(dataset, current_user)

api/controllers/console/feature.py

@@ -3,10 +3,12 @@ from flask_restful import Resource
 from services.feature_service import FeatureService
 
 from . import api
+from .wraps import cloud_utm_record
 
 
 class FeatureApi(Resource):
 
+    @cloud_utm_record
     def get(self):
         return FeatureService.get_features(current_user.current_tenant_id).dict()
 

api/controllers/console/operation/operation.py

-from flask_login import current_user
-from flask_restful import Resource, reqparse
-
-from controllers.console import api
-from controllers.console.setup import setup_required
-from controllers.console.wraps import account_initialization_required, only_edition_cloud
-from libs.login import login_required
-from services.operation_service import OperationService
-
-
-class TenantUtm(Resource):
-
-    @setup_required
-    @login_required
-    @account_initialization_required
-    @only_edition_cloud
-    def post(self):
-
-        parser = reqparse.RequestParser()
-        parser.add_argument('utm_source', type=str, required=True)
-        parser.add_argument('utm_medium', type=str, required=True)
-        parser.add_argument('utm_campaign', type=str, required=False, default='')
-        parser.add_argument('utm_content', type=str, required=False, default='')
-        parser.add_argument('utm_term', type=str, required=False, default='')
-        args = parser.parse_args()
-
-        return OperationService.record_utm(current_user.current_tenant_id, args)
-
-
-api.add_resource(TenantUtm, '/operation/utm')

api/controllers/console/workspace/members.py

@@ -52,10 +52,12 @@ class MemberInviteEmailApi(Resource):
         parser = reqparse.RequestParser()
         parser.add_argument('emails', type=str, required=True, location='json', action='append')
         parser.add_argument('role', type=str, required=True, default='admin', location='json')
+        parser.add_argument('language', type=str, required=False, location='json')
         args = parser.parse_args()
 
         invitee_emails = args['emails']
         invitee_role = args['role']
+        interface_language = args['language']
         if invitee_role not in ['admin', 'normal']:
             return {'code': 'invalid-role', 'message': 'Invalid role'}, 400
 
@@ -64,8 +66,7 @@ class MemberInviteEmailApi(Resource):
         console_web_url = current_app.config.get("CONSOLE_WEB_URL")
         for invitee_email in invitee_emails:
             try:
-                token = RegisterService.invite_new_member(inviter.current_tenant, invitee_email, role=invitee_role,
-                                                          inviter=inviter)
+                token = RegisterService.invite_new_member(inviter.current_tenant, invitee_email, interface_language, role=invitee_role, inviter=inviter)
                 invitation_results.append({
                     'status': 'success',
                     'email': invitee_email,

api/controllers/console/workspace/model_providers.py

@@ -98,7 +98,7 @@ class ModelProviderApi(Resource):
     @login_required
     @account_initialization_required
     def post(self, provider: str):
-        if current_user.current_tenant.current_role not in ['admin', 'owner']:
+        if not current_user.is_admin_or_owner:
             raise Forbidden()
 
         parser = reqparse.RequestParser()
@@ -122,7 +122,7 @@ class ModelProviderApi(Resource):
     @login_required
     @account_initialization_required
     def delete(self, provider: str):
-        if current_user.current_tenant.current_role not in ['admin', 'owner']:
+        if not current_user.is_admin_or_owner:
             raise Forbidden()
 
         model_provider_service = ModelProviderService()
@@ -159,7 +159,7 @@ class PreferredProviderTypeUpdateApi(Resource):
     @login_required
     @account_initialization_required
     def post(self, provider: str):
-        if current_user.current_tenant.current_role not in ['admin', 'owner']:
+        if not current_user.is_admin_or_owner:
             raise Forbidden()
 
         tenant_id = current_user.current_tenant_id
@@ -186,10 +186,11 @@ class ModelProviderPaymentCheckoutUrlApi(Resource):
     def get(self, provider: str):
         if provider != 'anthropic':
             raise ValueError(f'provider name {provider} is invalid')
-
+        BillingService.is_tenant_owner_or_admin(current_user)
         data = BillingService.get_model_provider_payment_link(provider_name=provider,
                                                               tenant_id=current_user.current_tenant_id,
-                                                              account_id=current_user.id)
+                                                              account_id=current_user.id,
+                                                              prefilled_email=current_user.email)
         return data
 
 

api/controllers/console/workspace/tool_providers.py

@@ -43,7 +43,7 @@ class ToolBuiltinProviderDeleteApi(Resource):
     @login_required
     @account_initialization_required
     def post(self, provider):
-        if current_user.current_tenant.current_role not in ['admin', 'owner']:
+        if not current_user.is_admin_or_owner:
             raise Forbidden()
         
         user_id = current_user.id
@@ -60,7 +60,7 @@ class ToolBuiltinProviderUpdateApi(Resource):
     @login_required
     @account_initialization_required
     def post(self, provider):
-        if current_user.current_tenant.current_role not in ['admin', 'owner']:
+        if not current_user.is_admin_or_owner:
             raise Forbidden()
         
         user_id = current_user.id
@@ -114,7 +114,7 @@ class ToolApiProviderAddApi(Resource):
     @login_required
     @account_initialization_required
     def post(self):
-        if current_user.current_tenant.current_role not in ['admin', 'owner']:
+        if not current_user.is_admin_or_owner:
             raise Forbidden()
         
         user_id = current_user.id
@@ -183,7 +183,7 @@ class ToolApiProviderUpdateApi(Resource):
     @login_required
     @account_initialization_required
     def post(self):
-        if current_user.current_tenant.current_role not in ['admin', 'owner']:
+        if not current_user.is_admin_or_owner:
             raise Forbidden()
         
         user_id = current_user.id
@@ -217,7 +217,7 @@ class ToolApiProviderDeleteApi(Resource):
     @login_required
     @account_initialization_required
     def post(self):
-        if current_user.current_tenant.current_role not in ['admin', 'owner']:
+        if not current_user.is_admin_or_owner:
             raise Forbidden()
         
         user_id = current_user.id

api/controllers/console/wraps.py

 # -*- coding:utf-8 -*-
+import json
 from functools import wraps
+from flask import request
 
 from controllers.console.workspace.error import AccountNotInitializedError
 from flask import abort, current_app
 from flask_login import current_user
 from services.feature_service import FeatureService
+from services.operation_service import OperationService
 
 
 def account_initialization_required(view):
@@ -73,3 +76,20 @@ def cloud_edition_billing_resource_check(resource: str,
         return decorated
     return interceptor
 
+
+def cloud_utm_record(view):
+    @wraps(view)
+    def decorated(*args, **kwargs):
+        try:
+            features = FeatureService.get_features(current_user.current_tenant_id)
+
+            if features.billing.enabled:
+                utm_info = request.cookies.get('utm_info')
+
+                if utm_info:
+                    utm_info = json.loads(utm_info)
+                    OperationService.record_utm(current_user.current_tenant_id, utm_info)
+        except Exception as e:
+            pass
+        return view(*args, **kwargs)
+    return decorated

api/controllers/service_api/app/completion.py

@@ -13,7 +13,7 @@ from core.application_queue_manager import ApplicationQueueManager
 from core.entities.application_entities import InvokeFrom
 from core.errors.error import ModelCurrentlyNotSupportError, ProviderTokenNotInitError, QuotaExceededError
 from core.model_runtime.errors.invoke import InvokeError
-from flask import Response, stream_with_context, request
+from flask import Response, stream_with_context
 from flask_restful import reqparse
 from libs.helper import uuid_value
 from services.completion_service import CompletionService
@@ -75,18 +75,22 @@ class CompletionApi(AppApiResource):
 
 
 class CompletionStopApi(AppApiResource):
-    def post(self, app_model, _, task_id):
+    def post(self, app_model, end_user, task_id):
         if app_model.mode != 'completion':
             raise AppUnavailableError()
 
-        parser = reqparse.RequestParser()
-        parser.add_argument('user', required=True, nullable=False, type=str, location='json')
+        if end_user is None:
+            parser = reqparse.RequestParser()
+            parser.add_argument('user', required=True, nullable=False, type=str, location='json')
+            args = parser.parse_args()
 
-        args = parser.parse_args()
+            user = args.get('user')
+            if user is not None:
+                end_user = create_or_update_end_user_for_user_id(app_model, user)
+            else:
+                raise ValueError("arg user muse be input.")
 
-        end_user_id = args.get('user')
-
-        ApplicationQueueManager.set_stop_flag(task_id, InvokeFrom.SERVICE_API, end_user_id)
+        ApplicationQueueManager.set_stop_flag(task_id, InvokeFrom.SERVICE_API, end_user.id)
 
         return {'result': 'success'}, 200
 
@@ -146,13 +150,22 @@ class ChatApi(AppApiResource):
 
 
 class ChatStopApi(AppApiResource):
-    def post(self, app_model, _, task_id):
+    def post(self, app_model, end_user, task_id):
         if app_model.mode != 'chat':
             raise NotChatAppError()
 
-        end_user_id = request.get_json().get('user')
+        if end_user is None:
+            parser = reqparse.RequestParser()
+            parser.add_argument('user', required=True, nullable=False, type=str, location='json')
+            args = parser.parse_args()
+
+            user = args.get('user')
+            if user is not None:
+                end_user = create_or_update_end_user_for_user_id(app_model, user)
+            else:
+                raise ValueError("arg user muse be input.")
 
-        ApplicationQueueManager.set_stop_flag(task_id, InvokeFrom.SERVICE_API, end_user_id)
+        ApplicationQueueManager.set_stop_flag(task_id, InvokeFrom.SERVICE_API, end_user.id)
 
         return {'result': 'success'}, 200
 

api/controllers/service_api/wraps.py

@@ -75,8 +75,8 @@ def validate_dataset_token(view=None):
             tenant_account_join = db.session.query(Tenant, TenantAccountJoin) \
                 .filter(Tenant.id == api_token.tenant_id) \
                 .filter(TenantAccountJoin.tenant_id == Tenant.id) \
-                .filter(TenantAccountJoin.role.in_(['owner', 'admin'])) \
-                .one_or_none()
+                .filter(TenantAccountJoin.role.in_(['owner'])) \
+                .one_or_none() # TODO: only owner information is required, so only one is returned.
             if tenant_account_join:
                 tenant, ta = tenant_account_join
                 account = Account.query.filter_by(id=ta.account_id).first()
@@ -86,9 +86,9 @@ def validate_dataset_token(view=None):
                     current_app.login_manager._update_request_context_with_user(account)
                     user_logged_in.send(current_app._get_current_object(), user=_get_user())
                 else:
-                    raise Unauthorized("Tenant owner account is not exist.")
+                    raise Unauthorized("Tenant owner account does not exist.")
             else:
-                raise Unauthorized("Tenant is not exist.")
+                raise Unauthorized("Tenant does not exist.")
             return view(api_token.tenant_id, *args, **kwargs)
         return decorated
 

api/core/entities/provider_entities.py

@@ -9,6 +9,7 @@ from pydantic import BaseModel
 class QuotaUnit(Enum):
     TIMES = 'times'
     TOKENS = 'tokens'
+    CREDITS = 'credits'
 
 
 class SystemConfigurationStatus(Enum):

api/core/hosting_configuration.py

@@ -20,10 +20,6 @@ class TrialHostingQuota(HostingQuota):
 
 class PaidHostingQuota(HostingQuota):
     quota_type: ProviderQuotaType = ProviderQuotaType.PAID
-    stripe_price_id: str = None
-    increase_quota: int = 1
-    min_quantity: int = 20
-    max_quantity: int = 100
 
 
 class FreeHostingQuota(HostingQuota):
@@ -102,7 +98,7 @@ class HostingConfiguration:
         )
 
     def init_openai(self, app_config: Config) -> HostingProvider:
-        quota_unit = QuotaUnit.TIMES
+        quota_unit = QuotaUnit.CREDITS
         quotas = []
 
         if app_config.get("HOSTED_OPENAI_TRIAL_ENABLED"):
@@ -114,6 +110,8 @@ class HostingConfiguration:
                     RestrictModel(model="gpt-3.5-turbo-1106", model_type=ModelType.LLM),
                     RestrictModel(model="gpt-3.5-turbo-instruct", model_type=ModelType.LLM),
                     RestrictModel(model="gpt-3.5-turbo-16k", model_type=ModelType.LLM),
+                    RestrictModel(model="gpt-3.5-turbo-16k-0613", model_type=ModelType.LLM),
+                    RestrictModel(model="gpt-3.5-turbo-0613", model_type=ModelType.LLM),
                     RestrictModel(model="text-davinci-003", model_type=ModelType.LLM),
                     RestrictModel(model="whisper-1", model_type=ModelType.SPEECH2TEXT),
                 ]
@@ -122,10 +120,20 @@ class HostingConfiguration:
 
         if app_config.get("HOSTED_OPENAI_PAID_ENABLED"):
             paid_quota = PaidHostingQuota(
-                stripe_price_id=app_config.get("HOSTED_OPENAI_PAID_STRIPE_PRICE_ID"),
-                increase_quota=int(app_config.get("HOSTED_OPENAI_PAID_INCREASE_QUOTA", "1")),
-                min_quantity=int(app_config.get("HOSTED_OPENAI_PAID_MIN_QUANTITY", "1")),
-                max_quantity=int(app_config.get("HOSTED_OPENAI_PAID_MAX_QUANTITY", "1"))
+                restrict_models=[
+                    RestrictModel(model="gpt-4", model_type=ModelType.LLM),
+                    RestrictModel(model="gpt-4-turbo-preview", model_type=ModelType.LLM),
+                    RestrictModel(model="gpt-4-32k", model_type=ModelType.LLM),
+                    RestrictModel(model="gpt-4-1106-preview", model_type=ModelType.LLM),
+                    RestrictModel(model="gpt-3.5-turbo", model_type=ModelType.LLM),
+                    RestrictModel(model="gpt-3.5-turbo-16k", model_type=ModelType.LLM),
+                    RestrictModel(model="gpt-3.5-turbo-16k-0613", model_type=ModelType.LLM),
+                    RestrictModel(model="gpt-3.5-turbo-1106", model_type=ModelType.LLM),
+                    RestrictModel(model="gpt-4-0125-preview", model_type=ModelType.LLM),
+                    RestrictModel(model="gpt-3.5-turbo-0613", model_type=ModelType.LLM),
+                    RestrictModel(model="gpt-3.5-turbo-instruct", model_type=ModelType.LLM),
+                    RestrictModel(model="text-davinci-003", model_type=ModelType.LLM),
+                ]
             )
             quotas.append(paid_quota)
 
@@ -164,12 +172,7 @@ class HostingConfiguration:
             quotas.append(trial_quota)
 
         if app_config.get("HOSTED_ANTHROPIC_PAID_ENABLED"):
-            paid_quota = PaidHostingQuota(
-                stripe_price_id=app_config.get("HOSTED_ANTHROPIC_PAID_STRIPE_PRICE_ID"),
-                increase_quota=int(app_config.get("HOSTED_ANTHROPIC_PAID_INCREASE_QUOTA", "1000000")),
-                min_quantity=int(app_config.get("HOSTED_ANTHROPIC_PAID_MIN_QUANTITY", "20")),
-                max_quantity=int(app_config.get("HOSTED_ANTHROPIC_PAID_MAX_QUANTITY", "100"))
-            )
+            paid_quota = PaidHostingQuota()
             quotas.append(paid_quota)
 
         if len(quotas) > 0:

api/core/indexing_runner.py

@@ -562,7 +562,7 @@ class IndexingRunner:
 
             character_splitter = FixedRecursiveCharacterTextSplitter.from_encoder(
                 chunk_size=segmentation["max_tokens"],
-                chunk_overlap=0,
+                chunk_overlap=segmentation.get('chunk_overlap', 0),
                 fixed_separator=separator,
                 separators=["\n\n", "。", ".", " ", ""],
                 embedding_model_instance=embedding_model_instance
@@ -571,7 +571,7 @@ class IndexingRunner:
             # Automatic segmentation
             character_splitter = EnhanceRecursiveCharacterTextSplitter.from_encoder(
                 chunk_size=DatasetProcessRule.AUTOMATIC_RULES['segmentation']['max_tokens'],
-                chunk_overlap=0,
+                chunk_overlap=DatasetProcessRule.AUTOMATIC_RULES['segmentation']['chunk_overlap'],
                 separators=["\n\n", "。", ".", " ", ""],
                 embedding_model_instance=embedding_model_instance
             )

api/core/model_runtime/model_providers/bedrock/llm/anthropic.claude-v1.yaml

@@ -8,9 +8,9 @@ model_properties:
 parameter_rules:
   - name: temperature
     use_template: temperature
-  - name: topP
+  - name: top_p
     use_template: top_p
-  - name: topK
+  - name: top_k
     label:
       zh_Hans: 取样数量
       en_US: Top K

api/core/model_runtime/model_providers/bedrock/llm/anthropic.claude-v2.1.yaml

@@ -8,9 +8,9 @@ model_properties:
 parameter_rules:
   - name: temperature
     use_template: temperature
-  - name: topP
+  - name: top_p
     use_template: top_p
-  - name: topK
+  - name: top_k
     label:
       zh_Hans: 取样数量
       en_US: Top K

api/core/model_runtime/model_providers/bedrock/llm/anthropic.claude-v2.yaml

@@ -8,9 +8,9 @@ model_properties:
 parameter_rules:
   - name: temperature
     use_template: temperature
-  - name: topP
+  - name: top_p
     use_template: top_p
-  - name: topK
+  - name: top_k
     label:
       zh_Hans: 取样数量
       en_US: Top K

api/core/model_runtime/model_providers/bedrock/llm/llm.py

@@ -250,9 +250,12 @@ class BedrockLargeLanguageModel(LargeLanguageModel):
             invoke = runtime_client.invoke_model
 
         try:
+            body_jsonstr=json.dumps(payload)
             response = invoke(
-                body=json.dumps(payload),
                 modelId=model,
+                contentType="application/json",
+                accept= "*/*",
+                body=body_jsonstr
             )
         except ClientError as ex:
             error_code = ex.response['Error']['Code']
@@ -385,7 +388,6 @@ class BedrockLargeLanguageModel(LargeLanguageModel):
             if not chunk:
                 exception_name = next(iter(event))
                 full_ex_msg = f"{exception_name}: {event[exception_name]['message']}"
-
                 raise self._map_client_to_invoke_error(exception_name, full_ex_msg)
 
             payload = json.loads(chunk.get('bytes').decode())
@@ -396,7 +398,7 @@ class BedrockLargeLanguageModel(LargeLanguageModel):
                 finish_reason = payload.get("completion_reason")
  
             elif model_prefix == "anthropic":
-                content_delta = payload
+                content_delta = payload.get("completion")
                 finish_reason = payload.get("stop_reason")
 
             elif model_prefix == "cohere":
@@ -410,12 +412,12 @@ class BedrockLargeLanguageModel(LargeLanguageModel):
             else:
                 raise ValueError(f"Got unknown model prefix {model_prefix} when handling stream response")
 
-            index += 1
-           
+            # transform assistant message to prompt message
             assistant_prompt_message = AssistantPromptMessage(
                 content = content_delta if content_delta else '',
             )
-  
+            index += 1
+           
             if not finish_reason:
                 yield LLMResultChunk(
                     model=model,

api/core/model_runtime/model_providers/ollama/ollama.yaml

@@ -11,7 +11,7 @@ help:
     en_US: How to integrate with Ollama
     zh_Hans: 如何集成 Ollama
   url:
-    en_US: https://docs.dify.ai/advanced/model-configuration/ollama
+    en_US: https://docs.dify.ai/tutorials/model-configuration/ollama
 supported_model_types:
   - llm
   - text-embedding

api/core/model_runtime/model_providers/openai/llm/_position.yaml

 - gpt-4
+- gpt-4-turbo-preview
 - gpt-4-32k
 - gpt-4-1106-preview
+- gpt-4-0125-preview
 - gpt-4-vision-preview
 - gpt-3.5-turbo
 - gpt-3.5-turbo-16k

api/core/model_runtime/model_providers/openai/llm/gpt-4-0125-preview.yaml

+model: gpt-4-0125-preview
+label:
+  zh_Hans: gpt-4-0125-preview
+  en_US: gpt-4-0125-preview
+model_type: llm
+features:
+  - multi-tool-call
+  - agent-thought
+model_properties:
+  mode: chat
+  context_size: 128000
+parameter_rules:
+  - name: temperature
+    use_template: temperature
+  - name: top_p
+    use_template: top_p
+  - name: presence_penalty
+    use_template: presence_penalty
+  - name: frequency_penalty
+    use_template: frequency_penalty
+  - name: max_tokens
+    use_template: max_tokens
+    default: 512
+    min: 1
+    max: 4096
+  - name: seed
+    label:
+      zh_Hans: 种子
+      en_US: Seed
+    type: int
+    help:
+      zh_Hans: 如果指定，模型将尽最大努力进行确定性采样，使得重复的具有相同种子和参数的请求应该返回相同的结果。不能保证确定性，您应该参考 system_fingerprint
+        响应参数来监视变化。
+      en_US: If specified, model will make a best effort to sample deterministically,
+        such that repeated requests with the same seed and parameters should return
+        the same result. Determinism is not guaranteed, and you should refer to the
+        system_fingerprint response parameter to monitor changes in the backend.
+    required: false
+    precision: 2
+    min: 0
+    max: 1
+  - name: response_format
+    label:
+      zh_Hans: 回复格式
+      en_US: response_format
+    type: string
+    help:
+      zh_Hans: 指定模型必须输出的格式
+      en_US: specifying the format that the model must output
+    required: false
+    options:
+      - text
+      - json_object
+pricing:
+  input: '0.01'
+  output: '0.03'
+  unit: '0.001'
+  currency: USD

api/core/model_runtime/model_providers/openai/llm/gpt-4-turbo-preview.yaml

+model: gpt-4-turbo-preview
+label:
+  zh_Hans: gpt-4-turbo-preview
+  en_US: gpt-4-turbo-preview
+model_type: llm
+features:
+  - multi-tool-call
+  - agent-thought
+model_properties:
+  mode: chat
+  context_size: 128000
+parameter_rules:
+  - name: temperature
+    use_template: temperature
+  - name: top_p
+    use_template: top_p
+  - name: presence_penalty
+    use_template: presence_penalty
+  - name: frequency_penalty
+    use_template: frequency_penalty
+  - name: max_tokens
+    use_template: max_tokens
+    default: 512
+    min: 1
+    max: 4096
+  - name: seed
+    label:
+      zh_Hans: 种子
+      en_US: Seed
+    type: int
+    help:
+      zh_Hans: 如果指定，模型将尽最大努力进行确定性采样，使得重复的具有相同种子和参数的请求应该返回相同的结果。不能保证确定性，您应该参考 system_fingerprint
+        响应参数来监视变化。
+      en_US: If specified, model will make a best effort to sample deterministically,
+        such that repeated requests with the same seed and parameters should return
+        the same result. Determinism is not guaranteed, and you should refer to the
+        system_fingerprint response parameter to monitor changes in the backend.
+    required: false
+    precision: 2
+    min: 0
+    max: 1
+  - name: response_format
+    label:
+      zh_Hans: 回复格式
+      en_US: response_format
+    type: string
+    help:
+      zh_Hans: 指定模型必须输出的格式
+      en_US: specifying the format that the model must output
+    required: false
+    options:
+      - text
+      - json_object
+pricing:
+  input: '0.01'
+  output: '0.03'
+  unit: '0.001'
+  currency: USD

api/core/model_runtime/model_providers/openai/llm/text-davinci-003.yaml

@@ -26,3 +26,4 @@ pricing:
   output: '0.002'
   unit: '0.001'
   currency: USD
+deprecated: true

api/core/model_runtime/model_providers/openai/text_embedding/text-embedding-3-large.yaml

+model: text-embedding-3-large
+model_type: text-embedding
+model_properties:
+  context_size: 8191
+  max_chunks: 32
+pricing:
+  input: '0.00013'
+  unit: '0.001'
+  currency: USD

api/core/model_runtime/model_providers/openai/text_embedding/text-embedding-3-small.yaml

+model: text-embedding-3-small
+model_type: text-embedding
+model_properties:
+  context_size: 8191
+  max_chunks: 32
+pricing:
+  input: '0.00002'
+  unit: '0.001'
+  currency: USD

api/core/model_runtime/model_providers/openai_api_compatible/llm/llm.py

@@ -224,7 +224,7 @@ class OAIAPICompatLargeLanguageModel(_CommonOAI_API_Compat, LargeLanguageModel):
             entity.model_properties[ModelPropertyKey.MODE] = LLMMode.COMPLETION.value
         else:
             raise ValueError(f"Unknown completion type {credentials['completion_type']}")
-    
+
         return entity
 
     # validate_credentials method has been rewritten to use the requests library for compatibility with all providers following OpenAI's API standard.
@@ -343,31 +343,37 @@ class OAIAPICompatLargeLanguageModel(_CommonOAI_API_Compat, LargeLanguageModel):
                 )
             )
 
-        for chunk in response.iter_lines(decode_unicode=True, delimiter='\n\n'):
+        # delimiter for stream response, need unicode_escape
+        import codecs
+        delimiter = credentials.get("stream_mode_delimiter", "\n\n")
+        delimiter = codecs.decode(delimiter, "unicode_escape")
+
+        for chunk in response.iter_lines(decode_unicode=True, delimiter=delimiter):
             if chunk:
                 decoded_chunk = chunk.strip().lstrip('data: ').lstrip()
-
                 chunk_json = None
                 try:
                     chunk_json = json.loads(decoded_chunk)
                 # stream ended
                 except json.JSONDecodeError as e:
+                    logger.error(f"decoded_chunk error,delimiter={delimiter},decoded_chunk={decoded_chunk}")
                     yield create_final_llm_result_chunk(
                         index=chunk_index + 1,
                         message=AssistantPromptMessage(content=""),
                         finish_reason="Non-JSON encountered."
                     )
                     break
-
                 if not chunk_json or len(chunk_json['choices']) == 0:
                     continue
 
                 choice = chunk_json['choices'][0]
+                finish_reason = chunk_json['choices'][0].get('finish_reason')
                 chunk_index += 1
 
                 if 'delta' in choice:
                     delta = choice['delta']
-                    if delta.get('content') is None or delta.get('content') == '':
+                    delta_content = delta.get('content')
+                    if delta_content is None or delta_content == '':
                         continue
 
                     assistant_message_tool_calls = delta.get('tool_calls', None)
@@ -381,30 +387,28 @@ class OAIAPICompatLargeLanguageModel(_CommonOAI_API_Compat, LargeLanguageModel):
 
                     # transform assistant message to prompt message
                     assistant_prompt_message = AssistantPromptMessage(
-                        content=delta.get('content', ''),
+                        content=delta_content,
                         tool_calls=tool_calls if assistant_message_tool_calls else []
                     )
 
-                    full_assistant_content += delta.get('content', '')
+                    full_assistant_content += delta_content
                 elif 'text' in choice:
-                    if choice.get('text') is None or choice.get('text') == '':
+                    choice_text = choice.get('text', '')
+                    if choice_text == '':
                         continue
 
                     # transform assistant message to prompt message
-                    assistant_prompt_message = AssistantPromptMessage(
-                        content=choice.get('text', '')
-                    )
-
-                    full_assistant_content += choice.get('text', '')
+                    assistant_prompt_message = AssistantPromptMessage(content=choice_text)
+                    full_assistant_content += choice_text
                 else:
                     continue
 
                 # check payload indicator for completion
-                if chunk_json['choices'][0].get('finish_reason') is not None:
+                if finish_reason is not None:
                     yield create_final_llm_result_chunk(
                         index=chunk_index,
                         message=assistant_prompt_message,
-                        finish_reason=chunk_json['choices'][0]['finish_reason']
+                        finish_reason=finish_reason
                     )
                 else:
                     yield LLMResultChunk(

api/core/model_runtime/model_providers/openai_api_compatible/openai_api_compatible.yaml

@@ -75,3 +75,12 @@ model_credential_schema:
           value: llm
       default: '4096'
       type: text-input
+    - variable: stream_mode_delimiter
+      label:
+        zh_Hans: 流模式返回结果的分隔符
+        en_US: Delimiter for streaming results
+      show_on:
+        - variable: __model_type
+          value: llm
+      default: '\n\n'
+      type: text-input

api/core/model_runtime/model_providers/zhipuai/_client.py

-"""Wrapper around ZhipuAI APIs."""
-from __future__ import annotations
-
-import logging
-import posixpath
-
-from pydantic import BaseModel, Extra
-from zhipuai.model_api.api import InvokeType
-from zhipuai.utils import jwt_token
-from zhipuai.utils.http_client import post, stream
-from zhipuai.utils.sse_client import SSEClient
-
-logger = logging.getLogger(__name__)
-
-
-class ZhipuModelAPI(BaseModel):
-    base_url: str = "https://open.bigmodel.cn/api/paas/v3/model-api"
-    api_key: str
-    api_timeout_seconds = 60
-
-    class Config:
-        """Configuration for this pydantic object."""
-
-        extra = Extra.forbid
-
-    def invoke(self, **kwargs):
-        url = self._build_api_url(kwargs, InvokeType.SYNC)
-        response = post(url, self._generate_token(), kwargs, self.api_timeout_seconds)
-        if not response['success']:
-            raise ValueError(
-                f"Error Code: {response['code']}, Message: {response['msg']} "
-            )
-        return response
-
-    def sse_invoke(self, **kwargs):
-        url = self._build_api_url(kwargs, InvokeType.SSE)
-        data = stream(url, self._generate_token(), kwargs, self.api_timeout_seconds)
-        return SSEClient(data)
-
-    def _build_api_url(self, kwargs, *path):
-        if kwargs:
-            if "model" not in kwargs:
-                raise Exception("model param missed")
-            model = kwargs.pop("model")
-        else:
-            model = "-"
-
-        return posixpath.join(self.base_url, model, *path)
-
-    def _generate_token(self):
-        if not self.api_key:
-            raise Exception(
-                "api_key not provided, you could provide it."
-            )
-
-        try:
-            return jwt_token.generate_token(self.api_key)
-        except Exception:
-            raise ValueError(
-                f"Your api_key is invalid, please check it."
-            )

api/core/model_runtime/model_providers/zhipuai/llm/glm_3_turbo.yaml

@@ -28,15 +28,3 @@ parameter_rules:
       zh_Hans: SSE接口调用时，用于控制每次返回内容方式是增量还是全量，不提供此参数时默认为增量返回，true 为增量返回，false 为全量返回。
       en_US: When the SSE interface is called, it is used to control whether the content is returned incrementally or in full. If this parameter is not provided, the default is incremental return. true means incremental return, false means full return.
     required: false
-  - name: return_type
-    label:
-      zh_Hans: 回复类型
-      en_US: Return Type
-    type: string
-    help:
-      zh_Hans: 用于控制每次返回内容的类型，空或者没有此字段时默认按照 json_string 返回，json_string 返回标准的 JSON 字符串，text 返回原始的文本内容。
-      en_US: Used to control the type of content returned each time. When it is empty or does not have this field, it will be returned as json_string by default. json_string returns a standard JSON string, and text returns the original text content.
-    required: false
-    options:
-      - text
-      - json_string

api/core/model_runtime/model_providers/zhipuai/llm/glm_4.yaml

@@ -28,15 +28,3 @@ parameter_rules:
       zh_Hans: SSE接口调用时，用于控制每次返回内容方式是增量还是全量，不提供此参数时默认为增量返回，true 为增量返回，false 为全量返回。
       en_US: When the SSE interface is called, it is used to control whether the content is returned incrementally or in full. If this parameter is not provided, the default is incremental return. true means incremental return, false means full return.
     required: false
-  - name: return_type
-    label:
-      zh_Hans: 回复类型
-      en_US: Return Type
-    type: string
-    help:
-      zh_Hans: 用于控制每次返回内容的类型，空或者没有此字段时默认按照 json_string 返回，json_string 返回标准的 JSON 字符串，text 返回原始的文本内容。
-      en_US: Used to control the type of content returned each time. When it is empty or does not have this field, it will be returned as json_string by default. json_string returns a standard JSON string, and text returns the original text content.
-    required: false
-    options:
-      - text
-      - json_string

api/core/model_runtime/model_providers/zhipuai/llm/glm_4v.yaml

@@ -30,15 +30,3 @@ parameter_rules:
       zh_Hans: SSE接口调用时，用于控制每次返回内容方式是增量还是全量，不提供此参数时默认为增量返回，true 为增量返回，false 为全量返回。
       en_US: When the SSE interface is called, it is used to control whether the content is returned incrementally or in full. If this parameter is not provided, the default is incremental return. true means incremental return, false means full return.
     required: false
-  - name: return_type
-    label:
-      zh_Hans: 回复类型
-      en_US: Return Type
-    type: string
-    help:
-      zh_Hans: 用于控制每次返回内容的类型，空或者没有此字段时默认按照 json_string 返回，json_string 返回标准的 JSON 字符串，text 返回原始的文本内容。
-      en_US: Used to control the type of content returned each time. When it is empty or does not have this field, it will be returned as json_string by default. json_string returns a standard JSON string, and text returns the original text content.
-    required: false
-    options:
-      - text
-      - json_string

api/core/model_runtime/model_providers/zhipuai/text_embedding/text_embedding.py

@@ -5,7 +5,7 @@ from core.model_runtime.entities.model_entities import PriceType
 from core.model_runtime.entities.text_embedding_entities import EmbeddingUsage, TextEmbeddingResult
 from core.model_runtime.errors.validate import CredentialsValidateFailedError
 from core.model_runtime.model_providers.__base.text_embedding_model import TextEmbeddingModel
-from core.model_runtime.model_providers.zhipuai._client import ZhipuModelAPI
+from core.model_runtime.model_providers.zhipuai.zhipuai_sdk._client import ZhipuAI
 from core.model_runtime.model_providers.zhipuai._common import _CommonZhipuaiAI
 from langchain.schema.language_model import _get_token_ids_default_method
 
@@ -28,7 +28,7 @@ class ZhipuAITextEmbeddingModel(_CommonZhipuaiAI, TextEmbeddingModel):
         :return: embeddings result
         """
         credentials_kwargs = self._to_credential_kwargs(credentials)
-        client = ZhipuModelAPI(
+        client = ZhipuAI(
             api_key=credentials_kwargs['api_key']
         )
 
@@ -69,7 +69,7 @@ class ZhipuAITextEmbeddingModel(_CommonZhipuaiAI, TextEmbeddingModel):
         try:
             # transform credentials to kwargs for model instance
             credentials_kwargs = self._to_credential_kwargs(credentials)
-            client = ZhipuModelAPI(
+            client = ZhipuAI(
                 api_key=credentials_kwargs['api_key']
             )
 
@@ -82,7 +82,7 @@ class ZhipuAITextEmbeddingModel(_CommonZhipuaiAI, TextEmbeddingModel):
         except Exception as ex:
             raise CredentialsValidateFailedError(str(ex))
 
-    def embed_documents(self, model: str, client: ZhipuModelAPI, texts: List[str]) -> Tuple[List[List[float]], int]:
+    def embed_documents(self, model: str, client: ZhipuAI, texts: List[str]) -> Tuple[List[List[float]], int]:
         """Call out to ZhipuAI's embedding endpoint.
 
         Args:
@@ -91,17 +91,16 @@ class ZhipuAITextEmbeddingModel(_CommonZhipuaiAI, TextEmbeddingModel):
         Returns:
             List of embeddings, one for each text.
         """
-        
-
         embeddings = []
-        for text in texts:
-            response = client.invoke(model=model, prompt=text)
-            data = response["data"]
-            embeddings.append(data.get('embedding'))
+        embedding_used_tokens = 0
 
-        embedding_used_tokens = data.get('usage')
+        for text in texts:
+            response = client.embeddings.create(model=model, input=text)
+            data = response.data[0]
+            embeddings.append(data.embedding)
+            embedding_used_tokens += response.usage.total_tokens
 
-        return [list(map(float, e)) for e in embeddings], embedding_used_tokens['total_tokens'] if embedding_used_tokens else 0
+        return [list(map(float, e)) for e in embeddings], embedding_used_tokens
     
     def embed_query(self, text: str) -> List[float]:
         """Call out to ZhipuAI's embedding endpoint.

api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/__init__.py

+
+from ._client import ZhipuAI
+
+from .core._errors import (
+    ZhipuAIError,
+    APIStatusError,
+    APIRequestFailedError,
+    APIAuthenticationError,
+    APIReachLimitError,
+    APIInternalError,
+    APIServerFlowExceedError,
+    APIResponseError,
+    APIResponseValidationError,
+    APITimeoutError,
+)
+
+from .__version__ import __version__

api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/__version__.py

+
+__version__ = 'v2.0.1'
\ No newline at end of file

api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/_client.py

+from __future__ import annotations
+
+from typing import Union, Mapping
+
+from typing_extensions import override
+
+from .core import _jwt_token
+from .core._errors import ZhipuAIError
+from .core._http_client import HttpClient, ZHIPUAI_DEFAULT_MAX_RETRIES
+from .core._base_type import NotGiven, NOT_GIVEN
+from . import api_resource
+import os
+import httpx
+from httpx import Timeout
+
+
+class ZhipuAI(HttpClient):
+    chat: api_resource.chat
+    api_key: str
+
+    def __init__(
+            self,
+            *,
+            api_key: str | None = None,
+            base_url: str | httpx.URL | None = None,
+            timeout: Union[float, Timeout, None, NotGiven] = NOT_GIVEN,
+            max_retries: int = ZHIPUAI_DEFAULT_MAX_RETRIES,
+            http_client: httpx.Client | None = None,
+            custom_headers: Mapping[str, str] | None = None
+    ) -> None:
+        # if api_key is None:
+        #     api_key = os.environ.get("ZHIPUAI_API_KEY")
+        if api_key is None:
+            raise ZhipuAIError("未提供api_key，请通过参数或环境变量提供")
+        self.api_key = api_key
+
+        if base_url is None:
+            base_url = os.environ.get("ZHIPUAI_BASE_URL")
+        if base_url is None:
+            base_url = f"https://open.bigmodel.cn/api/paas/v4"
+        from .__version__ import __version__
+        super().__init__(
+            version=__version__,
+            base_url=base_url,
+            timeout=timeout,
+            custom_httpx_client=http_client,
+            custom_headers=custom_headers,
+        )
+        self.chat = api_resource.chat.Chat(self)
+        self.images = api_resource.images.Images(self)
+        self.embeddings = api_resource.embeddings.Embeddings(self)
+        self.files = api_resource.files.Files(self)
+        self.fine_tuning = api_resource.fine_tuning.FineTuning(self)
+
+    @property
+    @override
+    def _auth_headers(self) -> dict[str, str]:
+        api_key = self.api_key
+        return {"Authorization": f"{_jwt_token.generate_token(api_key)}"}
+
+    def __del__(self) -> None:
+        if (not hasattr(self, "_has_custom_http_client")
+                or not hasattr(self, "close")
+                or not hasattr(self, "_client")):
+            # if the '__init__' method raised an error, self would not have client attr
+            return
+
+        if self._has_custom_http_client:
+            return
+
+        self.close()

api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/api_resource/__init__.py

+from .chat import chat
+from .images import Images
+from .embeddings import Embeddings
+from .files import Files
+from .fine_tuning import fine_tuning

api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/api_resource/chat/async_completions.py

+from __future__ import annotations
+
+from typing import Union, List, Optional, TYPE_CHECKING
+
+import httpx
+from typing_extensions import Literal
+
+from ...core._base_api import BaseAPI
+from ...core._base_type import NotGiven, NOT_GIVEN, Headers
+from ...core._http_client import make_user_request_input
+from ...types.chat.async_chat_completion import AsyncTaskStatus, AsyncCompletion
+
+if TYPE_CHECKING:
+    from ..._client import ZhipuAI
+
+
+class AsyncCompletions(BaseAPI):
+    def __init__(self, client: "ZhipuAI") -> None:
+        super().__init__(client)
+
+
+    def create(
+            self,
+            *,
+            model: str,
+            request_id: Optional[str] | NotGiven = NOT_GIVEN,
+            do_sample: Optional[Literal[False]] | Literal[True] | NotGiven = NOT_GIVEN,
+            temperature: Optional[float] | NotGiven = NOT_GIVEN,
+            top_p: Optional[float] | NotGiven = NOT_GIVEN,
+            max_tokens: int | NotGiven = NOT_GIVEN,
+            seed: int | NotGiven = NOT_GIVEN,
+            messages: Union[str, List[str], List[int], List[List[int]], None],
+            stop: Optional[Union[str, List[str], None]] | NotGiven = NOT_GIVEN,
+            sensitive_word_check: Optional[object] | NotGiven = NOT_GIVEN,
+            tools: Optional[object] | NotGiven = NOT_GIVEN,
+            tool_choice: str | NotGiven = NOT_GIVEN,
+            extra_headers: Headers | None = None,
+            disable_strict_validation: Optional[bool] | None = None,
+            timeout: float | httpx.Timeout | None | NotGiven = NOT_GIVEN,
+    ) -> AsyncTaskStatus:
+        _cast_type = AsyncTaskStatus
+
+        if disable_strict_validation:
+            _cast_type = object
+        return self._post(
+            "/async/chat/completions",
+            body={
+                "model": model,
+                "request_id": request_id,
+                "temperature": temperature,
+                "top_p": top_p,
+                "do_sample": do_sample,
+                "max_tokens": max_tokens,
+                "seed": seed,
+                "messages": messages,
+                "stop": stop,
+                "sensitive_word_check": sensitive_word_check,
+                "tools": tools,
+                "tool_choice": tool_choice,
+            },
+            options=make_user_request_input(
+                extra_headers=extra_headers, timeout=timeout
+            ),
+            cast_type=_cast_type,
+            enable_stream=False,
+        )
+
+    def retrieve_completion_result(
+        self,
+        id: str,
+        extra_headers: Headers | None = None,
+        disable_strict_validation: Optional[bool] | None = None,
+        timeout: float | httpx.Timeout | None | NotGiven = NOT_GIVEN,
+    ) -> Union[AsyncCompletion, AsyncTaskStatus]:
+        _cast_type = Union[AsyncCompletion,AsyncTaskStatus]
+        if disable_strict_validation:
+            _cast_type = object
+        return self._get(
+            path=f"/async-result/{id}",
+            cast_type=_cast_type,
+            options=make_user_request_input(
+                extra_headers=extra_headers,
+                timeout=timeout
+            )
+        )
+
+

api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/api_resource/chat/chat.py

+from typing import TYPE_CHECKING
+from .completions import Completions
+from .async_completions import AsyncCompletions
+from ...core._base_api import BaseAPI
+
+if TYPE_CHECKING:
+    from ..._client import ZhipuAI
+
+
+class Chat(BaseAPI):
+    completions: Completions
+
+    def __init__(self, client: "ZhipuAI") -> None:
+        super().__init__(client)
+        self.completions = Completions(client)
+        self.asyncCompletions = AsyncCompletions(client)

api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/api_resource/chat/completions.py

+from __future__ import annotations
+
+from typing import Union, List, Optional, TYPE_CHECKING
+
+import httpx
+from typing_extensions import Literal
+
+from ...core._base_api import BaseAPI
+from ...core._base_type import NotGiven, NOT_GIVEN, Headers
+from ...core._http_client import make_user_request_input
+from ...core._sse_client import StreamResponse
+from ...types.chat.chat_completion import Completion
+from ...types.chat.chat_completion_chunk import ChatCompletionChunk
+
+if TYPE_CHECKING:
+    from ..._client import ZhipuAI
+
+
+class Completions(BaseAPI):
+    def __init__(self, client: "ZhipuAI") -> None:
+        super().__init__(client)
+
+    def create(
+            self,
+            *,
+            model: str,
+            request_id: Optional[str] | NotGiven = NOT_GIVEN,
+            do_sample: Optional[Literal[False]] | Literal[True] | NotGiven = NOT_GIVEN,
+            stream: Optional[Literal[False]] | Literal[True] | NotGiven = NOT_GIVEN,
+            temperature: Optional[float] | NotGiven = NOT_GIVEN,
+            top_p: Optional[float] | NotGiven = NOT_GIVEN,
+            max_tokens: int | NotGiven = NOT_GIVEN,
+            seed: int | NotGiven = NOT_GIVEN,
+            messages: Union[str, List[str], List[int], object, None],
+            stop: Optional[Union[str, List[str], None]] | NotGiven = NOT_GIVEN,
+            sensitive_word_check: Optional[object] | NotGiven = NOT_GIVEN,
+            tools: Optional[object] | NotGiven = NOT_GIVEN,
+            tool_choice: str | NotGiven = NOT_GIVEN,
+            extra_headers: Headers | None = None,
+            disable_strict_validation: Optional[bool] | None = None,
+            timeout: float | httpx.Timeout | None | NotGiven = NOT_GIVEN,
+    ) -> Completion | StreamResponse[ChatCompletionChunk]:
+        _cast_type = Completion
+        _stream_cls = StreamResponse[ChatCompletionChunk]
+        if disable_strict_validation:
+            _cast_type = object
+            _stream_cls = StreamResponse[object]
+        return self._post(
+            "/chat/completions",
+            body={
+                "model": model,
+                "request_id": request_id,
+                "temperature": temperature,
+                "top_p": top_p,
+                "do_sample": do_sample,
+                "max_tokens": max_tokens,
+                "seed": seed,
+                "messages": messages,
+                "stop": stop,
+                "sensitive_word_check": sensitive_word_check,
+                "stream": stream,
+                "tools": tools,
+                "tool_choice": tool_choice,
+            },
+            options=make_user_request_input(
+                extra_headers=extra_headers,
+            ),
+            cast_type=_cast_type,
+            enable_stream=stream or False,
+            stream_cls=_stream_cls,
+        )

api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/api_resource/embeddings.py

+from __future__ import annotations
+
+from typing import Union, List, Optional, TYPE_CHECKING
+
+import httpx
+
+from ..core._base_api import BaseAPI
+from ..core._base_type import NotGiven, NOT_GIVEN, Headers
+from ..core._http_client import make_user_request_input
+from ..types.embeddings import EmbeddingsResponded
+
+if TYPE_CHECKING:
+    from .._client import ZhipuAI
+
+
+class Embeddings(BaseAPI):
+    def __init__(self, client: "ZhipuAI") -> None:
+        super().__init__(client)
+
+    def create(
+            self,
+            *,
+            input: Union[str, List[str], List[int], List[List[int]]],
+            model: Union[str],
+            encoding_format: str | NotGiven = NOT_GIVEN,
+            user: str | NotGiven = NOT_GIVEN,
+            sensitive_word_check: Optional[object] | NotGiven = NOT_GIVEN,
+            extra_headers: Headers | None = None,
+            disable_strict_validation: Optional[bool] | None = None,
+            timeout: float | httpx.Timeout | None | NotGiven = NOT_GIVEN,
+    ) -> EmbeddingsResponded:
+        _cast_type = EmbeddingsResponded
+        if disable_strict_validation:
+            _cast_type = object
+        return self._post(
+            "/embeddings",
+            body={
+                "input": input,
+                "model": model,
+                "encoding_format": encoding_format,
+                "user": user,
+                "sensitive_word_check": sensitive_word_check,
+            },
+            options=make_user_request_input(
+                extra_headers=extra_headers, timeout=timeout
+            ),
+            cast_type=_cast_type,
+            enable_stream=False,
+        )

api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/api_resource/files.py

+from __future__ import annotations
+
+from typing import TYPE_CHECKING
+
+import httpx
+
+from ..core._base_api import BaseAPI
+from ..core._base_type import NOT_GIVEN, Body, Query, Headers, NotGiven, FileTypes
+from ..core._files import is_file_content
+from ..core._http_client import (
+    make_user_request_input,
+)
+from ..types.file_object import FileObject, ListOfFileObject
+
+if TYPE_CHECKING:
+    from .._client import ZhipuAI
+
+__all__ = ["Files"]
+
+
+class Files(BaseAPI):
+
+    def __init__(self, client: "ZhipuAI") -> None:
+        super().__init__(client)
+
+    def create(
+            self,
+            *,
+            file: FileTypes,
+            purpose: str,
+            extra_headers: Headers | None = None,
+            timeout: float | httpx.Timeout | None | NotGiven = NOT_GIVEN,
+    ) -> FileObject:
+        if not is_file_content(file):
+            prefix = f"Expected file input `{file!r}`"
+            raise RuntimeError(
+                f"{prefix} to be bytes, an io.IOBase instance, PathLike or a tuple but received {type(file)} instead."
+            ) from None
+        files = [("file", file)]
+
+        extra_headers = {"Content-Type": "multipart/form-data", **(extra_headers or {})}
+
+        return self._post(
+            "/files",
+            body={
+                "purpose": purpose,
+            },
+            files=files,
+            options=make_user_request_input(
+                extra_headers=extra_headers, timeout=timeout
+            ),
+            cast_type=FileObject,
+        )
+
+    def list(
+            self,
+            *,
+            purpose: str | NotGiven = NOT_GIVEN,
+            limit: int  | NotGiven = NOT_GIVEN,
+            after: str | NotGiven = NOT_GIVEN,
+            order: str | NotGiven = NOT_GIVEN,
+            extra_headers: Headers | None = None,
+            timeout: float | httpx.Timeout | None | NotGiven = NOT_GIVEN,
+    ) -> ListOfFileObject:
+        return self._get(
+            "/files",
+            cast_type=ListOfFileObject,
+            options=make_user_request_input(
+                extra_headers=extra_headers,
+                timeout=timeout,
+                query={
+                    "purpose": purpose,
+                    "limit": limit,
+                    "after": after,
+                    "order": order,
+                },
+            ),
+        )

api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/api_resource/fine_tuning/fine_tuning.py

+from typing import TYPE_CHECKING
+from .jobs import Jobs
+from ...core._base_api import BaseAPI
+
+if TYPE_CHECKING:
+    from ..._client import ZhipuAI
+
+
+class FineTuning(BaseAPI):
+    jobs: Jobs
+
+    def __init__(self, client: "ZhipuAI") -> None:
+        super().__init__(client)
+        self.jobs = Jobs(client)
+

api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/api_resource/fine_tuning/jobs.py

+from __future__ import annotations
+
+from typing import Optional, TYPE_CHECKING
+
+import httpx
+
+from ...core._base_api import BaseAPI
+from ...core._base_type import NOT_GIVEN, Headers, NotGiven
+from ...core._http_client import (
+    make_user_request_input,
+)
+from ...types.fine_tuning import (
+    FineTuningJob,
+    job_create_params,
+    ListOfFineTuningJob,
+    FineTuningJobEvent,
+)
+
+if TYPE_CHECKING:
+    from ..._client import ZhipuAI
+
+__all__ = ["Jobs"]
+
+
+class Jobs(BaseAPI):
+
+    def __init__(self, client: "ZhipuAI") -> None:
+        super().__init__(client)
+
+    def create(
+            self,
+            *,
+            model: str,
+            training_file: str,
+            hyperparameters: job_create_params.Hyperparameters | NotGiven = NOT_GIVEN,
+            suffix: Optional[str] | NotGiven = NOT_GIVEN,
+            request_id: Optional[str] | NotGiven = NOT_GIVEN,
+            validation_file: Optional[str] | NotGiven = NOT_GIVEN,
+            extra_headers: Headers | None = None,
+            timeout: float | httpx.Timeout | None | NotGiven = NOT_GIVEN,
+    ) -> FineTuningJob:
+        return self._post(
+            "/fine_tuning/jobs",
+            body={
+                "model": model,
+                "training_file": training_file,
+                "hyperparameters": hyperparameters,
+                "suffix": suffix,
+                "validation_file": validation_file,
+                "request_id": request_id,
+            },
+            options=make_user_request_input(
+                extra_headers=extra_headers, timeout=timeout
+            ),
+            cast_type=FineTuningJob,
+        )
+
+    def retrieve(
+            self,
+            fine_tuning_job_id: str,
+            *,
+            extra_headers: Headers | None = None,
+            timeout: float | httpx.Timeout | None | NotGiven = NOT_GIVEN,
+    ) -> FineTuningJob:
+        return self._get(
+            f"/fine_tuning/jobs/{fine_tuning_job_id}",
+            options=make_user_request_input(
+                extra_headers=extra_headers, timeout=timeout
+            ),
+            cast_type=FineTuningJob,
+        )
+
+    def list(
+            self,
+            *,
+            after: str | NotGiven = NOT_GIVEN,
+            limit: int | NotGiven = NOT_GIVEN,
+            extra_headers: Headers | None = None,
+            timeout: float | httpx.Timeout | None | NotGiven = NOT_GIVEN,
+    ) -> ListOfFineTuningJob:
+        return self._get(
+            "/fine_tuning/jobs",
+            cast_type=ListOfFineTuningJob,
+            options=make_user_request_input(
+                extra_headers=extra_headers,
+                timeout=timeout,
+                query={
+                    "after": after,
+                    "limit": limit,
+                },
+            ),
+        )
+
+    def list_events(
+        self,
+        fine_tuning_job_id: str,
+        *,
+        after: str | NotGiven = NOT_GIVEN,
+        limit: int | NotGiven = NOT_GIVEN,
+        extra_headers: Headers | None = None,
+        timeout: float | httpx.Timeout | None | NotGiven = NOT_GIVEN,
+    ) -> FineTuningJobEvent:
+
+        return self._get(
+            f"/fine_tuning/jobs/{fine_tuning_job_id}/events",
+            cast_type=FineTuningJobEvent,
+            options=make_user_request_input(
+                extra_headers=extra_headers,
+                timeout=timeout,
+                query={
+                    "after": after,
+                    "limit": limit,
+                },
+            ),
+        )

api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/api_resource/images.py

+from __future__ import annotations
+
+from typing import Union, List, Optional, TYPE_CHECKING
+
+import httpx
+
+from ..core._base_api import BaseAPI
+from ..core._base_type import NotGiven, NOT_GIVEN, Headers
+from ..core._http_client import make_user_request_input
+from ..types.image import ImagesResponded
+
+if TYPE_CHECKING:
+    from .._client import ZhipuAI
+
+
+class Images(BaseAPI):
+    def __init__(self, client: "ZhipuAI") -> None:
+        super().__init__(client)
+
+    def generations(
+            self,
+            *,
+            prompt: str,
+            model: str | NotGiven = NOT_GIVEN,
+            n: Optional[int] | NotGiven = NOT_GIVEN,
+            quality: Optional[str] | NotGiven = NOT_GIVEN,
+            response_format: Optional[str] | NotGiven = NOT_GIVEN,
+            size: Optional[str] | NotGiven = NOT_GIVEN,
+            style: Optional[str] | NotGiven = NOT_GIVEN,
+            user: str | NotGiven = NOT_GIVEN,
+            extra_headers: Headers | None = None,
+            disable_strict_validation: Optional[bool] | None = None,
+            timeout: float | httpx.Timeout | None | NotGiven = NOT_GIVEN,
+    ) -> ImagesResponded:
+        _cast_type = ImagesResponded
+        if disable_strict_validation:
+            _cast_type = object
+        return self._post(
+            "/images/generations",
+            body={
+                "prompt": prompt,
+                "model": model,
+                "n": n,
+                "quality": quality,
+                "response_format": response_format,
+                "size": size,
+                "style": style,
+                "user": user,
+            },
+            options=make_user_request_input(
+                extra_headers=extra_headers, timeout=timeout
+            ),
+            cast_type=_cast_type,
+            enable_stream=False,
+        )

api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/core/_base_api.py

+from __future__ import annotations
+from typing import TYPE_CHECKING
+
+if TYPE_CHECKING:
+    from .._client import ZhipuAI
+
+
+class BaseAPI:
+    _client: ZhipuAI
+
+    def __init__(self, client: ZhipuAI) -> None:
+        self._client = client
+        self._delete = client.delete
+        self._get = client.get
+        self._post = client.post
+        self._put = client.put
+        self._patch = client.patch

api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/core/_base_type.py

+from __future__ import annotations
+
+from os import PathLike
+from typing import (
+    TYPE_CHECKING,
+    Type,
+    Union,
+    Mapping,
+    TypeVar, IO, Tuple, Sequence, Any, List,
+)
+
+import pydantic
+from typing_extensions import (
+    Literal,
+    override,
+)
+
+
+Query = Mapping[str, object]
+Body = object
+AnyMapping = Mapping[str, object]
+PrimitiveData = Union[str, int, float, bool, None]
+Data = Union[PrimitiveData, List[Any], Tuple[Any], "Mapping[str, Any]"]
+ModelT = TypeVar("ModelT", bound=pydantic.BaseModel)
+_T = TypeVar("_T")
+
+if TYPE_CHECKING:
+    NoneType: Type[None]
+else:
+    NoneType = type(None)
+
+
+# Sentinel class used until PEP 0661 is accepted
+class NotGiven(pydantic.BaseModel):
+    """
+    A sentinel singleton class used to distinguish omitted keyword arguments
+    from those passed in with the value None (which may have different behavior).
+
+    For example:
+
+    ```py
+    def get(timeout: Union[int, NotGiven, None] = NotGiven()) -> Response: ...
+
+    get(timeout=1) # 1s timeout
+    get(timeout=None) # No timeout
+    get() # Default timeout behavior, which may not be statically known at the method definition.
+    ```
+    """
+
+    def __bool__(self) -> Literal[False]:
+        return False
+
+    @override
+    def __repr__(self) -> str:
+        return "NOT_GIVEN"
+
+
+NotGivenOr = Union[_T, NotGiven]
+NOT_GIVEN = NotGiven()
+
+
+class Omit(pydantic.BaseModel):
+    """In certain situations you need to be able to represent a case where a default value has
+    to be explicitly removed and `None` is not an appropriate substitute, for example:
+
+    ```py
+    # as the default `Content-Type` header is `application/json` that will be sent
+    client.post('/upload/files', files={'file': b'my raw file content'})
+
+    # you can't explicitly override the header as it has to be dynamically generated
+    # to look something like: 'multipart/form-data; boundary=0d8382fcf5f8c3be01ca2e11002d2983'
+    client.post(..., headers={'Content-Type': 'multipart/form-data'})
+
+    # instead you can remove the default `application/json` header by passing Omit
+    client.post(..., headers={'Content-Type': Omit()})
+    ```
+    """
+
+    def __bool__(self) -> Literal[False]:
+        return False
+
+
+Headers = Mapping[str, Union[str, Omit]]
+
+ResponseT = TypeVar(
+    "ResponseT",
+    bound="Union[str, None, BaseModel, List[Any], Dict[str, Any], Response, UnknownResponse, ModelBuilderProtocol, BinaryResponseContent]",
+)
+
+# for user input files
+if TYPE_CHECKING:
+    FileContent = Union[IO[bytes], bytes, PathLike[str]]
+else:
+    FileContent = Union[IO[bytes], bytes, PathLike]
+
+FileTypes = Union[
+    FileContent,  # file content
+    Tuple[str, FileContent],  # (filename, file)
+    Tuple[str, FileContent, str],  # (filename, file , content_type)
+    Tuple[str, FileContent, str, Mapping[str, str]],  # (filename, file , content_type, headers)
+]
+
+RequestFiles = Union[Mapping[str, FileTypes], Sequence[Tuple[str, FileTypes]]]
+
+# for httpx client supported files
+
+HttpxFileContent = Union[bytes, IO[bytes]]
+HttpxFileTypes = Union[
+    FileContent,  # file content
+    Tuple[str, HttpxFileContent],  # (filename, file)
+    Tuple[str, HttpxFileContent, str],  # (filename, file , content_type)
+    Tuple[str, HttpxFileContent, str, Mapping[str, str]],  # (filename, file , content_type, headers)
+]
+
+HttpxRequestFiles = Union[Mapping[str, HttpxFileTypes], Sequence[Tuple[str, HttpxFileTypes]]]

api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/core/_errors.py

+from __future__ import annotations
+
+import httpx
+
+__all__ = [
+    "ZhipuAIError",
+    "APIStatusError",
+    "APIRequestFailedError",
+    "APIAuthenticationError",
+    "APIReachLimitError",
+    "APIInternalError",
+    "APIServerFlowExceedError",
+    "APIResponseError",
+    "APIResponseValidationError",
+    "APITimeoutError",
+]
+
+
+class ZhipuAIError(Exception):
+    def __init__(self, message: str, ) -> None:
+        super().__init__(message)
+
+
+class APIStatusError(Exception):
+    response: httpx.Response
+    status_code: int
+
+    def __init__(self, message: str, *, response: httpx.Response) -> None:
+        super().__init__(message)
+        self.response = response
+        self.status_code = response.status_code
+
+
+class APIRequestFailedError(APIStatusError):
+    ...
+
+
+class APIAuthenticationError(APIStatusError):
+    ...
+
+
+class APIReachLimitError(APIStatusError):
+    ...
+
+
+class APIInternalError(APIStatusError):
+    ...
+
+
+class APIServerFlowExceedError(APIStatusError):
+    ...
+
+
+class APIResponseError(Exception):
+    message: str
+    request: httpx.Request
+    json_data: object
+
+    def __init__(self, message: str, request: httpx.Request, json_data: object):
+        self.message = message
+        self.request = request
+        self.json_data = json_data
+        super().__init__(message)
+
+
+class APIResponseValidationError(APIResponseError):
+    status_code: int
+    response: httpx.Response
+
+    def __init__(
+            self,
+            response: httpx.Response,
+            json_data: object | None, *,
+            message: str | None = None
+    ) -> None:
+        super().__init__(
+            message=message or "Data returned by API invalid for expected schema.",
+            request=response.request,
+            json_data=json_data
+        )
+        self.response = response
+        self.status_code = response.status_code
+
+
+class APITimeoutError(Exception):
+    request: httpx.Request
+
+    def __init__(self, request: httpx.Request):
+        self.request = request
+        super().__init__("Request Timeout")

api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/core/_files.py

+from __future__ import annotations
+
+import io
+import os
+from pathlib import Path
+from typing import Mapping, Sequence
+
+from ._base_type import (
+    FileTypes,
+    HttpxFileTypes,
+    HttpxRequestFiles,
+    RequestFiles,
+)
+
+
+def is_file_content(obj: object) -> bool:
+    return isinstance(obj, (bytes, tuple, io.IOBase, os.PathLike))
+
+
+def _transform_file(file: FileTypes) -> HttpxFileTypes:
+    if is_file_content(file):
+        if isinstance(file, os.PathLike):
+            path = Path(file)
+            return path.name, path.read_bytes()
+        else:
+            return file
+    if isinstance(file, tuple):
+        if isinstance(file[1], os.PathLike):
+            return (file[0], Path(file[1]).read_bytes(), *file[2:])
+        else:
+            return (file[0], file[1], *file[2:])
+    else:
+        raise TypeError(f"Unexpected input file with type {type(file)},Expected FileContent type or tuple type")
+
+
+def make_httpx_files(files: RequestFiles | None) -> HttpxRequestFiles | None:
+    if files is None:
+        return None
+
+    if isinstance(files, Mapping):
+        files = {key: _transform_file(file) for key, file in files.items()}
+    elif isinstance(files, Sequence):
+        files = [(key, _transform_file(file)) for key, file in files]
+    else:
+        raise TypeError(f"Unexpected input file with type {type(files)}, excepted Mapping or Sequence")
+    return files

api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/core/_jwt_token.py

+# -*- coding:utf-8 -*-
+import time
+
+import cachetools.func
+import jwt
+
+API_TOKEN_TTL_SECONDS = 3 * 60
+
+CACHE_TTL_SECONDS = API_TOKEN_TTL_SECONDS - 30
+
+
+@cachetools.func.ttl_cache(maxsize=10, ttl=CACHE_TTL_SECONDS)
+def generate_token(apikey: str):
+    try:
+        api_key, secret = apikey.split(".")
+    except Exception as e:
+        raise Exception("invalid api_key", e)
+
+    payload = {
+        "api_key": api_key,
+        "exp": int(round(time.time() * 1000)) + API_TOKEN_TTL_SECONDS * 1000,
+        "timestamp": int(round(time.time() * 1000)),
+    }
+    ret = jwt.encode(
+        payload,
+        secret,
+        algorithm="HS256",
+        headers={"alg": "HS256", "sign_type": "SIGN"},
+    )
+    return ret

api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/core/_request_opt.py

+from __future__ import annotations
+
+from typing import Union, Any, cast
+
+import pydantic.generics
+from httpx import Timeout
+from pydantic import ConfigDict
+from typing_extensions import (
+    Unpack, ClassVar, TypedDict
+)
+
+from ._base_type import Body, NotGiven, Headers, HttpxRequestFiles, Query
+from ._utils import remove_notgiven_indict
+
+
+class UserRequestInput(TypedDict, total=False):
+    max_retries: int
+    timeout: float | Timeout | None
+    headers: Headers
+    params: Query | None
+
+
+class ClientRequestParam():
+    method: str
+    url: str
+    max_retries: Union[int, NotGiven] = NotGiven()
+    timeout: Union[float, NotGiven] = NotGiven()
+    headers: Union[Headers, NotGiven] = NotGiven()
+    json_data: Union[Body, None] = None
+    files: Union[HttpxRequestFiles, None] = None
+    params: Query = {}
+    model_config: ClassVar[ConfigDict] = ConfigDict(arbitrary_types_allowed=True)
+
+    def get_max_retries(self, max_retries) -> int:
+        if isinstance(self.max_retries, NotGiven):
+            return max_retries
+        return self.max_retries
+
+    @classmethod
+    def construct(  # type: ignore
+            cls,
+            _fields_set: set[str] | None = None,
+            **values: Unpack[UserRequestInput],
+    ) -> ClientRequestParam :
+        kwargs: dict[str, Any] = {
+            key: remove_notgiven_indict(value) for key, value in values.items()
+        }
+        client = cls()
+        client.__dict__.update(kwargs)
+
+        return client
+
+    model_construct = construct
+

api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/core/_response.py

+from __future__ import annotations
+
+import datetime
+from typing import TypeVar, Generic, cast, Any, TYPE_CHECKING
+
+import httpx
+import pydantic
+from typing_extensions import ParamSpec, get_origin, get_args
+
+from ._base_type import NoneType
+from ._sse_client import StreamResponse
+
+if TYPE_CHECKING:
+    from ._http_client import HttpClient
+
+P = ParamSpec("P")
+R = TypeVar("R")
+
+
+class HttpResponse(Generic[R]):
+    _cast_type: type[R]
+    _client: "HttpClient"
+    _parsed: R | None
+    _enable_stream: bool
+    _stream_cls: type[StreamResponse[Any]]
+    http_response: httpx.Response
+
+    def __init__(
+            self,
+            *,
+            raw_response: httpx.Response,
+            cast_type: type[R],
+            client: "HttpClient",
+            enable_stream: bool = False,
+            stream_cls: type[StreamResponse[Any]] | None = None,
+    ) -> None:
+        self._cast_type = cast_type
+        self._client = client
+        self._parsed = None
+        self._stream_cls = stream_cls
+        self._enable_stream = enable_stream
+        self.http_response = raw_response
+
+    def parse(self) -> R:
+        self._parsed = self._parse()
+        return self._parsed
+
+    def _parse(self) -> R:
+        if self._enable_stream:
+            self._parsed = cast(
+                R,
+                self._stream_cls(
+                    cast_type=cast(type, get_args(self._stream_cls)[0]),
+                    response=self.http_response,
+                    client=self._client
+                )
+            )
+            return self._parsed
+        cast_type = self._cast_type
+        if cast_type is NoneType:
+            return cast(R, None)
+        http_response = self.http_response
+        if cast_type == str:
+            return cast(R, http_response.text)
+
+        content_type, *_ = http_response.headers.get("content-type", "application/json").split(";")
+        origin = get_origin(cast_type) or cast_type
+        if content_type != "application/json":
+            if issubclass(origin, pydantic.BaseModel):
+                data = http_response.json()
+                return self._client._process_response_data(
+                    data=data,
+                    cast_type=cast_type,  # type: ignore
+                    response=http_response,
+                )
+
+            return http_response.text
+
+        data = http_response.json()
+
+        return self._client._process_response_data(
+            data=data,
+            cast_type=cast_type,  # type: ignore
+            response=http_response,
+        )
+
+    @property
+    def headers(self) -> httpx.Headers:
+        return self.http_response.headers
+
+    @property
+    def http_request(self) -> httpx.Request:
+        return self.http_response.request
+
+    @property
+    def status_code(self) -> int:
+        return self.http_response.status_code
+
+    @property
+    def url(self) -> httpx.URL:
+        return self.http_response.url
+
+    @property
+    def method(self) -> str:
+        return self.http_request.method
+
+    @property
+    def content(self) -> bytes:
+        return self.http_response.content
+
+    @property
+    def text(self) -> str:
+        return self.http_response.text
+
+    @property
+    def http_version(self) -> str:
+        return self.http_response.http_version
+
+    @property
+    def elapsed(self) -> datetime.timedelta:
+        return self.http_response.elapsed

api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/core/_sse_client.py

+# -*- coding:utf-8 -*-
+from __future__ import annotations
+
+import json
+from typing import Generic, Iterator, TYPE_CHECKING, Mapping
+
+import httpx
+
+from ._base_type import ResponseT
+from ._errors import APIResponseError
+
+_FIELD_SEPARATOR = ":"
+
+if TYPE_CHECKING:
+    from ._http_client import HttpClient
+
+
+class StreamResponse(Generic[ResponseT]):
+
+    response: httpx.Response
+    _cast_type: type[ResponseT]
+
+    def __init__(
+            self,
+            *,
+            cast_type: type[ResponseT],
+            response: httpx.Response,
+            client: HttpClient,
+    ) -> None:
+        self.response = response
+        self._cast_type = cast_type
+        self._data_process_func = client._process_response_data
+        self._stream_chunks = self.__stream__()
+
+    def __next__(self) -> ResponseT:
+        return self._stream_chunks.__next__()
+
+    def __iter__(self) -> Iterator[ResponseT]:
+        for item in self._stream_chunks:
+            yield item
+
+    def __stream__(self) -> Iterator[ResponseT]:
+
+        sse_line_parser = SSELineParser()
+        iterator = sse_line_parser.iter_lines(self.response.iter_lines())
+
+        for sse in iterator:
+            if sse.data.startswith("[DONE]"):
+                break
+
+            if sse.event is None:
+                data = sse.json_data()
+                if isinstance(data, Mapping) and data.get("error"):
+                    raise APIResponseError(
+                        message="An error occurred during streaming",
+                        request=self.response.request,
+                        json_data=data["error"],
+                    )
+
+                yield self._data_process_func(data=data, cast_type=self._cast_type, response=self.response)
+        for sse in iterator:
+            pass
+
+
+class Event(object):
+    def __init__(
+            self,
+            event: str | None = None,
+            data: str | None = None,
+            id: str | None = None,
+            retry: int | None = None
+    ):
+        self._event = event
+        self._data = data
+        self._id = id
+        self._retry = retry
+
+    def __repr__(self):
+        data_len = len(self._data) if self._data else 0
+        return f"Event(event={self._event}, data={self._data} ,data_length={data_len}, id={self._id}, retry={self._retry}"
+
+    @property
+    def event(self): return self._event
+
+    @property
+    def data(self): return self._data
+
+    def json_data(self): return json.loads(self._data)
+
+    @property
+    def id(self): return self._id
+
+    @property
+    def retry(self): return self._retry
+
+
+class SSELineParser:
+    _data: list[str]
+    _event: str | None
+    _retry: int | None
+    _id: str | None
+
+    def __init__(self):
+        self._event = None
+        self._data = []
+        self._id = None
+        self._retry = None
+
+    def iter_lines(self, lines: Iterator[str]) -> Iterator[Event]:
+        for line in lines:
+            line = line.rstrip('\n')
+            if not line:
+                if self._event is None and \
+                        not self._data and \
+                        self._id is None and \
+                        self._retry is None:
+                    continue
+                sse_event = Event(
+                    event=self._event,
+                    data='\n'.join(self._data),
+                    id=self._id,
+                    retry=self._retry
+                )
+                self._event = None
+                self._data = []
+                self._id = None
+                self._retry = None
+
+                yield sse_event
+            self.decode_line(line)
+
+    def decode_line(self, line: str):
+        if line.startswith(":") or not line:
+            return
+
+        field, _p, value = line.partition(":")
+
+        if value.startswith(' '):
+            value = value[1:]
+        if field == "data":
+            self._data.append(value)
+        elif field == "event":
+            self._event = value
+        elif field == "retry":
+            try:
+                self._retry = int(value)
+            except (TypeError, ValueError):
+                pass
+        return

api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/core/_utils.py

+from __future__ import annotations
+
+from typing import Mapping, Iterable, TypeVar
+
+from ._base_type import NotGiven
+
+
+def remove_notgiven_indict(obj):
+    if obj is None or (not isinstance(obj, Mapping)):
+        return obj
+    return {key: value for key, value in obj.items() if not isinstance(value, NotGiven)}
+
+
+_T = TypeVar("_T")
+
+
+def flatten(t: Iterable[Iterable[_T]]) -> list[_T]:
+    return [item for sublist in t for item in sublist]

api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/types/chat/async_chat_completion.py

+from typing import List, Optional
+
+from pydantic import BaseModel
+
+from .chat_completion import CompletionChoice, CompletionUsage
+
+__all__ = ["AsyncTaskStatus"]
+
+
+class AsyncTaskStatus(BaseModel):
+    id: Optional[str] = None
+    request_id: Optional[str] = None
+    model: Optional[str] = None
+    task_status: Optional[str] = None
+
+
+class AsyncCompletion(BaseModel):
+    id: Optional[str] = None
+    request_id: Optional[str] = None
+    model: Optional[str] = None
+    task_status: str
+    choices: List[CompletionChoice]
+    usage: CompletionUsage
\ No newline at end of file

api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/types/chat/chat_completion.py

+from typing import List, Optional
+
+from pydantic import BaseModel
+
+__all__ = ["Completion", "CompletionUsage"]
+
+
+class Function(BaseModel):
+    arguments: str
+    name: str
+
+
+class CompletionMessageToolCall(BaseModel):
+    id: str
+    function: Function
+    type: str
+
+
+class CompletionMessage(BaseModel):
+    content: Optional[str] = None
+    role: str
+    tool_calls: Optional[List[CompletionMessageToolCall]] = None
+
+
+class CompletionUsage(BaseModel):
+    prompt_tokens: int
+    completion_tokens: int
+    total_tokens: int
+
+
+class CompletionChoice(BaseModel):
+    index: int
+    finish_reason: str
+    message: CompletionMessage
+
+
+class Completion(BaseModel):
+    model: Optional[str] = None
+    created: Optional[int] = None
+    choices: List[CompletionChoice]
+    request_id: Optional[str] = None
+    id: Optional[str] = None
+    usage: CompletionUsage
+
+

api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/types/chat/chat_completion_chunk.py

+from typing import List, Optional
+
+from pydantic import BaseModel
+
+__all__ = [
+    "ChatCompletionChunk",
+    "Choice",
+    "ChoiceDelta",
+    "ChoiceDeltaFunctionCall",
+    "ChoiceDeltaToolCall",
+    "ChoiceDeltaToolCallFunction",
+]
+
+
+class ChoiceDeltaFunctionCall(BaseModel):
+    arguments: Optional[str] = None
+    name: Optional[str] = None
+
+
+class ChoiceDeltaToolCallFunction(BaseModel):
+    arguments: Optional[str] = None
+    name: Optional[str] = None
+
+
+class ChoiceDeltaToolCall(BaseModel):
+    index: int
+    id: Optional[str] = None
+    function: Optional[ChoiceDeltaToolCallFunction] = None
+    type: Optional[str] = None
+
+
+class ChoiceDelta(BaseModel):
+    content: Optional[str] = None
+    role: Optional[str] = None
+    tool_calls: Optional[List[ChoiceDeltaToolCall]] = None
+
+
+class Choice(BaseModel):
+    delta: ChoiceDelta
+    finish_reason: Optional[str] = None
+    index: int
+
+
+class CompletionUsage(BaseModel):
+    prompt_tokens: int
+    completion_tokens: int
+    total_tokens: int
+
+
+class ChatCompletionChunk(BaseModel):
+    id: Optional[str] = None
+    choices: List[Choice]
+    created: Optional[int] = None
+    model: Optional[str] = None
+    usage: Optional[CompletionUsage] = None

api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/types/chat/chat_completions_create_param.py

+from typing import Optional
+
+from typing_extensions import TypedDict
+
+
+class Reference(TypedDict, total=False):
+    enable: Optional[bool]
+    search_query: Optional[str]

api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/types/embeddings.py

+from __future__ import annotations
+
+from typing import Optional, List
+
+from pydantic import BaseModel
+from .chat.chat_completion import CompletionUsage
+__all__ = ["Embedding", "EmbeddingsResponded"]
+
+
+class Embedding(BaseModel):
+    object: str
+    index: Optional[int] = None
+    embedding: List[float]
+
+
+class EmbeddingsResponded(BaseModel):
+    object: str
+    data: List[Embedding]
+    model: str
+    usage: CompletionUsage

api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/types/file_object.py

+from typing import Optional, List
+
+from pydantic import BaseModel
+
+__all__ = ["FileObject"]
+
+
+class FileObject(BaseModel):
+
+    id: Optional[str] = None
+    bytes: Optional[int] = None
+    created_at: Optional[int] = None
+    filename: Optional[str] = None
+    object: Optional[str] = None
+    purpose: Optional[str] = None
+    status: Optional[str] = None
+    status_details: Optional[str] = None
+
+
+class ListOfFileObject(BaseModel):
+
+    object: Optional[str] = None
+    data: List[FileObject]
+    has_more: Optional[bool] = None

api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/types/fine_tuning/__init__.py

+from __future__ import annotations
+
+from .fine_tuning_job import FineTuningJob as FineTuningJob
+from .fine_tuning_job import ListOfFineTuningJob as ListOfFineTuningJob
+from .fine_tuning_job_event import FineTuningJobEvent as FineTuningJobEvent

api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/types/fine_tuning/fine_tuning_job.py

+from typing import List, Union, Optional
+from typing_extensions import Literal
+
+from pydantic import BaseModel
+
+__all__ = ["FineTuningJob", "Error", "Hyperparameters", "ListOfFineTuningJob" ]
+
+
+class Error(BaseModel):
+    code: str
+    message: str
+    param: Optional[str] = None
+
+
+class Hyperparameters(BaseModel):
+    n_epochs: Union[str, int, None] = None
+
+
+class FineTuningJob(BaseModel):
+    id: Optional[str] = None
+
+    request_id: Optional[str] = None
+
+    created_at: Optional[int] = None
+
+    error: Optional[Error] = None
+
+    fine_tuned_model: Optional[str] = None
+
+    finished_at: Optional[int] = None
+
+    hyperparameters: Optional[Hyperparameters] = None
+
+    model: Optional[str] = None
+
+    object: Optional[str] = None
+
+    result_files: List[str]
+
+    status: str
+
+    trained_tokens: Optional[int] = None
+
+    training_file: str
+
+    validation_file: Optional[str] = None
+
+
+class ListOfFineTuningJob(BaseModel):
+    object: Optional[str] = None
+    data: List[FineTuningJob]
+    has_more: Optional[bool] = None

api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/types/fine_tuning/fine_tuning_job_event.py

+from typing import List, Union, Optional
+from typing_extensions import Literal
+
+from pydantic import BaseModel
+
+__all__ = ["FineTuningJobEvent", "Metric", "JobEvent"]
+
+
+class Metric(BaseModel):
+    epoch: Optional[Union[str, int, float]] = None
+    current_steps: Optional[int] = None
+    total_steps: Optional[int] = None
+    elapsed_time: Optional[str] = None
+    remaining_time: Optional[str] = None
+    trained_tokens: Optional[int] = None
+    loss: Optional[Union[str, int, float]] = None
+    eval_loss: Optional[Union[str, int, float]] = None
+    acc: Optional[Union[str, int, float]] = None
+    eval_acc: Optional[Union[str, int, float]] = None
+    learning_rate: Optional[Union[str, int, float]] = None
+
+
+class JobEvent(BaseModel):
+    object: Optional[str] = None
+    id: Optional[str] = None
+    type: Optional[str] = None
+    created_at: Optional[int] = None
+    level: Optional[str] = None
+    message: Optional[str] = None
+    data: Optional[Metric] = None
+
+
+class FineTuningJobEvent(BaseModel):
+    object: Optional[str] = None
+    data: List[JobEvent]
+    has_more: Optional[bool] = None

api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/types/fine_tuning/job_create_params.py

+from __future__ import annotations
+
+from typing import Union
+
+from typing_extensions import Literal, TypedDict
+
+__all__ = ["Hyperparameters"]
+
+
+class Hyperparameters(TypedDict, total=False):
+    batch_size: Union[Literal["auto"], int]
+
+    learning_rate_multiplier: Union[Literal["auto"], float]
+
+    n_epochs: Union[Literal["auto"], int]

api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/types/image.py

+from __future__ import annotations
+
+from typing import Optional, List
+
+from pydantic import BaseModel
+
+__all__ = ["GeneratedImage", "ImagesResponded"]
+
+
+class GeneratedImage(BaseModel):
+    b64_json: Optional[str] = None
+    url: Optional[str] = None
+    revised_prompt: Optional[str] = None
+
+
+class ImagesResponded(BaseModel):
+    created: int
+    data: List[GeneratedImage]

api/core/tools/provider/builtin/_positions.py

@@ -26,4 +26,4 @@ class BuiltinToolProviderSort:
         
         sorted_providers = sorted(providers, key=sort_compare)
 
-        return sorted_providers
+        return sorted_providers
\ No newline at end of file

api/core/tools/provider/builtin/azuredalle/azuredalle.py

+from core.tools.provider.builtin_tool_provider import BuiltinToolProviderController
+from core.tools.provider.builtin.azuredalle.tools.dalle3 import DallE3Tool
+from core.tools.errors import ToolProviderCredentialValidationError
+
+from typing import Any, Dict
+
+class AzureDALLEProvider(BuiltinToolProviderController):
+    def _validate_credentials(self, credentials: Dict[str, Any]) -> None:
+        try:
+            DallE3Tool().fork_tool_runtime(
+                meta={
+                    "credentials": credentials,
+                }
+            ).invoke(
+                user_id='',
+                tool_paramters={
+                    "prompt": "cute girl, blue eyes, white hair, anime style",
+                    "size": "square",
+                    "n": 1
+                },
+            )
+        except Exception as e:
+            raise ToolProviderCredentialValidationError(str(e))

api/core/tools/provider/builtin/azuredalle/azuredalle.yaml

+identity:
+  author: Leslie
+  name: azuredalle
+  label:
+    en_US: AZURE DALL-E
+    zh_Hans: AZURE DALL-E 绘画
+    pt_BR: AZURE DALL-E
+  description:
+    en_US: AZURE DALL-E art
+    zh_Hans: AZURE DALL-E 绘画
+    pt_BR: AZURE DALL-E art
+  icon: icon.png
+credentials_for_provider:
+  azure_openai_api_key:
+    type: secret-input
+    required: true
+    label:
+      en_US: API key
+      zh_Hans: 密钥
+      pt_BR: API key
+    help:
+      en_US: Please input your Azure OpenAI API key
+      zh_Hans: 请输入你的 Azure OpenAI API key
+      pt_BR: Please input your Azure OpenAI API key
+    placeholder:
+      en_US: Please input your Azure OpenAI API key
+      zh_Hans: 请输入你的 Azure OpenAI API key
+      pt_BR: Please input your Azure OpenAI API key
+  azure_openai_api_model_name:
+    type: text-input
+    required: true
+    label:
+      en_US: Deployment Name
+      zh_Hans: 部署名称
+      pt_BR: Deployment Name
+    help:
+      en_US: Please input the name of your Azure Openai DALL-E API deployment
+      zh_Hans: 请输入你的 Azure Openai DALL-E API 部署名称
+      pt_BR: Please input the name of your Azure Openai DALL-E API deployment
+    placeholder:
+      en_US: Please input the name of your Azure Openai DALL-E API deployment
+      zh_Hans: 请输入你的 Azure Openai DALL-E API 部署名称
+      pt_BR: Please input the name of your Azure Openai DALL-E API deployment
+  azure_openai_base_url:
+    type: text-input
+    required: true
+    label:
+      en_US: API Endpoint URL
+      zh_Hans: API 域名
+      pt_BR: API Endpoint URL
+    help:
+      en_US: Please input your Azure OpenAI Endpoint URL,eg:https://xxx.openai.azure.com/
+      zh_Hans: 请输入你的 Azure OpenAI API域名，例如：https://xxx.openai.azure.com/
+      pt_BR: Please input your Azure OpenAI Endpoint URL,eg:https://xxx.openai.azure.com/
+    placeholder:
+      en_US: Please input your Azure OpenAI Endpoint URL,eg:https://xxx.openai.azure.com/
+      zh_Hans: 请输入你的 Azure OpenAI API域名，例如：https://xxx.openai.azure.com/
+      pt_BR: Please input your Azure OpenAI Endpoint URL,eg:https://xxx.openai.azure.com/
+  azure_openai_api_version:
+    type: text-input
+    required: true
+    label:
+      en_US: API Version
+      zh_Hans: API 版本
+      pt_BR: API Version
+    help:
+      en_US: Please input your Azure OpenAI API Version,eg:2023-12-01-preview
+      zh_Hans: 请输入你的 Azure OpenAI API 版本，例如：2023-12-01-preview
+      pt_BR: Please input your Azure OpenAI API Version,eg:2023-12-01-preview
+    placeholder:
+      en_US: Please input your Azure OpenAI API Version,eg:2023-12-01-preview
+      zh_Hans: 请输入你的 Azure OpenAI API 版本，例如：2023-12-01-preview
+      pt_BR: Please input your Azure OpenAI API Version,eg:2023-12-01-preview

api/core/tools/provider/builtin/azuredalle/tools/dalle3.py

+from typing import Any, Dict, List, Union
+from core.tools.entities.tool_entities import ToolInvokeMessage
+from core.tools.tool.builtin_tool import BuiltinTool
+
+from base64 import b64decode
+from os.path import join
+
+from openai import AzureOpenAI
+
+class DallE3Tool(BuiltinTool):
+    def _invoke(self, 
+                user_id: str, 
+               tool_paramters: Dict[str, Any], 
+        ) -> Union[ToolInvokeMessage, List[ToolInvokeMessage]]:
+        """
+            invoke tools
+        """
+        client = AzureOpenAI(
+            api_version=self.runtime.credentials['azure_openai_api_version'],
+            azure_endpoint=self.runtime.credentials['azure_openai_base_url'],
+            api_key=self.runtime.credentials['azure_openai_api_key'],
+        )
+
+        SIZE_MAPPING = {
+            'square': '1024x1024',
+            'vertical': '1024x1792',
+            'horizontal': '1792x1024',
+        }
+
+        # prompt
+        prompt = tool_paramters.get('prompt', '')
+        if not prompt:
+            return self.create_text_message('Please input prompt')
+        # get size
+        size = SIZE_MAPPING[tool_paramters.get('size', 'square')]
+        # get n
+        n = tool_paramters.get('n', 1)
+        # get quality
+        quality = tool_paramters.get('quality', 'standard')
+        if quality not in ['standard', 'hd']:
+            return self.create_text_message('Invalid quality')
+        # get style
+        style = tool_paramters.get('style', 'vivid')
+        if style not in ['natural', 'vivid']:
+            return self.create_text_message('Invalid style')
+
+        # call openapi dalle3
+        model=self.runtime.credentials['azure_openai_api_model_name']
+        response = client.images.generate(
+            prompt=prompt,
+            model=model,
+            size=size,
+            n=n,
+            style=style,
+            quality=quality,
+            response_format='b64_json'
+        )
+
+        result = []
+
+        for image in response.data:
+            result.append(self.create_blob_message(blob=b64decode(image.b64_json), 
+                                                   meta={ 'mime_type': 'image/png' },
+                                                    save_as=self.VARIABLE_KEY.IMAGE.value))
+
+        return result

api/core/tools/provider/builtin/azuredalle/tools/dalle3.yaml

+identity:
+  name: dalle3
+  author: Leslie
+  label:
+    en_US: DALL-E 3
+    zh_Hans: DALL-E 3 绘画
+    pt_BR: DALL-E 3
+  description:
+    en_US: DALL-E 3 is a powerful drawing tool that can draw the image you want based on your prompt, compared to DallE 2, DallE 3 has stronger drawing ability, but it will consume more resources
+    zh_Hans: DALL-E 3 是一个强大的绘画工具，它可以根据您的提示词绘制出您想要的图像，相比于DallE 2， DallE 3拥有更强的绘画能力，但会消耗更多的资源
+    pt_BR: DALL-E 3 is a powerful drawing tool that can draw the image you want based on your prompt, compared to DallE 2, DallE 3 has stronger drawing ability, but it will consume more resources
+description:
+  human:
+    en_US: DALL-E is a text to image tool
+    zh_Hans: DALL-E 是一个文本到图像的工具
+    pt_BR: DALL-E is a text to image tool
+  llm: DALL-E is a tool used to generate images from text
+parameters:
+  - name: prompt
+    type: string
+    required: true
+    label:
+      en_US: Prompt
+      zh_Hans: 提示词
+      pt_BR: Prompt
+    human_description:
+      en_US: Image prompt, you can check the official documentation of DallE 3
+      zh_Hans: 图像提示词，您可以查看DallE 3 的官方文档
+      pt_BR: Image prompt, you can check the official documentation of DallE 3
+    llm_description: Image prompt of DallE 3, you should describe the image you want to generate as a list of words as possible as detailed
+    form: llm
+  - name: size
+    type: select
+    required: true
+    human_description:
+      en_US: selecting the image size
+      zh_Hans: 选择图像大小
+      pt_BR: selecting the image size
+    label:
+      en_US: Image size
+      zh_Hans: 图像大小
+      pt_BR: Image size
+    form: form
+    options:
+      - value: square
+        label:
+          en_US: Squre(1024x1024)
+          zh_Hans: 方(1024x1024)
+          pt_BR: Squre(1024x1024)
+      - value: vertical
+        label:
+          en_US: Vertical(1024x1792)
+          zh_Hans: 竖屏(1024x1792)
+          pt_BR: Vertical(1024x1792)
+      - value: horizontal
+        label:
+          en_US: Horizontal(1792x1024)
+          zh_Hans: 横屏(1792x1024)
+          pt_BR: Horizontal(1792x1024)
+    default: square
+  - name: n
+    type: number
+    required: true
+    human_description:
+      en_US: selecting the number of images
+      zh_Hans: 选择图像数量
+      pt_BR: selecting the number of images
+    label:
+      en_US: Number of images
+      zh_Hans: 图像数量
+      pt_BR: Number of images
+    form: form
+    min: 1
+    max: 1
+    default: 1
+  - name: quality
+    type: select
+    required: true
+    human_description:
+      en_US: selecting the image quality
+      zh_Hans: 选择图像质量
+      pt_BR: selecting the image quality
+    label:
+      en_US: Image quality
+      zh_Hans: 图像质量
+      pt_BR: Image quality
+    form: form
+    options:
+      - value: standard
+        label:
+          en_US: Standard
+          zh_Hans: 标准
+          pt_BR: Standard
+      - value: hd
+        label:
+          en_US: HD
+          zh_Hans: 高清
+          pt_BR: HD
+    default: standard
+  - name: style
+    type: select
+    required: true
+    human_description:
+      en_US: selecting the image style
+      zh_Hans: 选择图像风格
+      pt_BR: selecting the image style
+    label:
+      en_US: Image style
+      zh_Hans: 图像风格
+      pt_BR: Image style
+    form: form
+    options:
+      - value: vivid
+        label:
+          en_US: Vivid
+          zh_Hans: 生动
+          pt_BR: Vivid
+      - value: natural
+        label:
+          en_US: Natural
+          zh_Hans: 自然
+          pt_BR: Natural
+    default: vivid

api/core/tools/provider/builtin/gaode/gaode.py

+import requests
+import urllib.parse
+from core.tools.provider.builtin_tool_provider import BuiltinToolProviderController
+from core.tools.errors import ToolProviderCredentialValidationError
+
+
+class GaodeProvider(BuiltinToolProviderController):
+    def _validate_credentials(self, credentials: dict) -> None:
+        try:
+            if 'api_key' not in credentials or not credentials.get('api_key'):
+                raise ToolProviderCredentialValidationError("Gaode API key is required.")
+
+            try:
+                response = requests.get(url="https://restapi.amap.com/v3/geocode/geo?address={address}&key={apikey}"
+                                            "".format(address=urllib.parse.quote('广东省广州市天河区广州塔'),
+                                                      apikey=credentials.get('api_key')))
+                if response.status_code == 200 and (response.json()).get('info') == 'OK':
+                    pass
+                else:
+                    raise ToolProviderCredentialValidationError((response.json()).get('info'))
+            except Exception as e:
+                raise ToolProviderCredentialValidationError("Gaode API Key is invalid. {}".format(e))
+        except Exception as e:
+            raise ToolProviderCredentialValidationError(str(e))

api/core/tools/provider/builtin/gaode/gaode.yaml

+identity:
+  author: CharlirWei
+  name: gaode
+  label:
+    en_US: GaoDe
+    zh_Hans: 高德
+    pt_BR: GaoDe
+  description:
+    en_US: Autonavi Open Platform service toolkit.
+    zh_Hans: 高德开放平台服务工具包。
+    pt_BR: Kit de ferramentas de serviço Autonavi Open Platform.
+  icon: icon.png
+credentials_for_provider:
+  api_key:
+    type: secret-input
+    required: true
+    label:
+      en_US: API Key
+      zh_Hans: API Key
+      pt_BR: Fogo a chave
+    placeholder:
+      en_US: Please enter your GaoDe API Key
+      zh_Hans: 请输入你的高德开放平台 API Key
+      pt_BR: Insira sua chave de API GaoDe
+    help:
+      en_US: Get your API Key from GaoDe
+      zh_Hans: 从高德获取您的 API Key
+      pt_BR: Obtenha sua chave de API do GaoDe
+    url: https://console.amap.com/dev/key/app

api/core/tools/provider/builtin/gaode/tools/gaode_weather.py

+import json
+import requests
+from core.tools.tool.builtin_tool import BuiltinTool
+from core.tools.entities.tool_entities import ToolInvokeMessage
+from typing import Any, Dict, List, Union
+
+
+class GaodeRepositoriesTool(BuiltinTool):
+    def _invoke(self, user_id: str, tool_paramters: Dict[str, Any]) -> Union[ToolInvokeMessage, List[ToolInvokeMessage]]:
+        """
+            invoke tools
+        """
+        city = tool_paramters.get('city', '')
+        if not city:
+            return self.create_text_message('Please tell me your city')
+
+        if 'api_key' not in self.runtime.credentials or not self.runtime.credentials.get('api_key'):
+            return self.create_text_message("Gaode API key is required.")
+
+        try:
+            s = requests.session()
+            api_domain = 'https://restapi.amap.com/v3'
+            city_response = s.request(method='GET', headers={"Content-Type": "application/json; charset=utf-8"},
+                                      url="{url}/config/district?keywords={keywords}"
+                                          "&subdistrict=0&extensions=base&key={apikey}"
+                                          "".format(url=api_domain, keywords=city,
+                                                    apikey=self.runtime.credentials.get('api_key')))
+            City_data = city_response.json()
+            if city_response.status_code == 200 and City_data.get('info') == 'OK':
+                if len(City_data.get('districts')) > 0:
+                    CityCode = City_data['districts'][0]['adcode']
+                    weatherInfo_response = s.request(method='GET',
+                                                     url="{url}/weather/weatherInfo?city={citycode}&extensions=all&key={apikey}&output=json"
+                                                         "".format(url=api_domain, citycode=CityCode,
+                                                                   apikey=self.runtime.credentials.get('api_key')))
+                    weatherInfo_data = weatherInfo_response.json()
+                    if weatherInfo_response.status_code == 200 and weatherInfo_data.get('info') == 'OK':
+                        contents = list()
+                        if len(weatherInfo_data.get('forecasts')) > 0:
+                            for item in weatherInfo_data['forecasts'][0]['casts']:
+                                content = dict()
+                                content['date'] = item.get('date')
+                                content['week'] = item.get('week')
+                                content['dayweather'] = item.get('dayweather')
+                                content['daytemp_float'] = item.get('daytemp_float')
+                                content['daywind'] = item.get('daywind')
+                                content['nightweather'] = item.get('nightweather')
+                                content['nighttemp_float'] = item.get('nighttemp_float')
+                                contents.append(content)
+                            s.close()
+                            return self.create_text_message(self.summary(user_id=user_id, content=json.dumps(contents, ensure_ascii=False)))
+            s.close()
+            return self.create_text_message(f'No weather information for {city} was found.')
+        except Exception as e:
+            return self.create_text_message("Github API Key and Api Version is invalid. {}".format(e))

api/core/tools/provider/builtin/gaode/tools/gaode_weather.yaml

+identity:
+  name: gaode_weather
+  author: CharlieWei
+  label:
+    en_US: Weather Forecast
+    zh_Hans: 天气预报
+    pt_BR: Previsão do tempo
+  icon: icon.svg
+description:
+  human:
+    en_US: Weather forecast inquiry
+    zh_Hans: 天气预报查询。
+    pt_BR: Inquérito sobre previsão meteorológica.
+  llm: A tool when you want to ask about the weather or weather-related question.
+parameters:
+  - name: city
+    type: string
+    required: true
+    label:
+      en_US: city
+      zh_Hans: 城市
+      pt_BR: cidade
+    human_description:
+      en_US: Target city for weather forecast query.
+      zh_Hans: 天气预报查询的目标城市。
+      pt_BR: Cidade de destino para consulta de previsão do tempo.
+    llm_description: If you don't know you can extract the city name from the question or you can reply：Please tell me your city. You have to extract the Chinese city name from the question.
+    form: llm

api/core/tools/provider/builtin/github/github.py

+import requests
+from core.tools.provider.builtin_tool_provider import BuiltinToolProviderController
+from core.tools.errors import ToolProviderCredentialValidationError
+
+
+class GihubProvider(BuiltinToolProviderController):
+    def _validate_credentials(self, credentials: dict) -> None:
+        try:
+            if 'access_tokens' not in credentials or not credentials.get('access_tokens'):
+                raise ToolProviderCredentialValidationError("Github API Access Tokens is required.")
+            if 'api_version' not in credentials or not credentials.get('api_version'):
+                api_version = '2022-11-28'
+            else:
+                api_version = credentials.get('api_version')
+
+            try:
+                headers = {
+                    "Content-Type": "application/vnd.github+json",
+                    "Authorization": f"Bearer {credentials.get('access_tokens')}",
+                    "X-GitHub-Api-Version": api_version
+                }
+
+                response = requests.get(
+                    url="https://api.github.com/search/users?q={account}".format(account='charli117'),
+                    headers=headers)
+                if response.status_code != 200:
+                    raise ToolProviderCredentialValidationError((response.json()).get('message'))
+            except Exception as e:
+                raise ToolProviderCredentialValidationError("Github API Key and Api Version is invalid. {}".format(e))
+        except Exception as e:
+            raise ToolProviderCredentialValidationError(str(e))

api/core/tools/provider/builtin/github/github.yaml

+identity:
+  author: CharlirWei
+  name: github
+  label:
+    en_US: Github
+    zh_Hans: Github
+    pt_BR: Github
+  description:
+    en_US: GitHub is an online software source code hosting service.
+    zh_Hans: GitHub是一个在线软件源代码托管服务平台。
+    pt_BR: GitHub é uma plataforma online para serviços de hospedagem de código fonte de software.
+  icon: icon.png
+credentials_for_provider:
+  access_tokens:
+    type: secret-input
+    required: true
+    label:
+      en_US: Access Tokens
+      zh_Hans: Access Tokens
+      pt_BR: Tokens de acesso
+    placeholder:
+      en_US: Please input your Github Access Tokens
+      zh_Hans: 请输入你的 Github Access Tokens
+      pt_BR: Insira seus Tokens de Acesso do Github
+    help:
+      en_US: Get your Access Tokens from Github
+      zh_Hans: 从 Github 获取您的 Access Tokens
+      pt_BR: Obtenha sua chave da API do Google no Google
+    url: https://github.com/settings/tokens?type=beta
+  api_version:
+    type: text-input
+    required: false
+    default: '2022-11-28'
+    label:
+      en_US: API Version
+      zh_Hans: API Version
+      pt_BR: Versão da API
+    placeholder:
+      en_US: Please input your Github API Version
+      zh_Hans: 请输入你的 Github API Version
+      pt_BR: Insira sua versão da API do Github
+    help:
+      en_US: Get your API Version from Github
+      zh_Hans: 从 Github 获取您的 API Version
+      pt_BR: Obtenha sua versão da API do Github
+    url: https://docs.github.com/en/rest/about-the-rest-api/api-versions?apiVersion=2022-11-28

api/core/tools/provider/builtin/github/tools/repositories.py

+import json
+import requests
+from datetime import datetime
+from urllib.parse import quote
+from core.tools.tool.builtin_tool import BuiltinTool
+from core.tools.entities.tool_entities import ToolInvokeMessage
+
+from typing import Any, Dict, List, Union
+
+
+class GihubRepositoriesTool(BuiltinTool):
+    def _invoke(self, user_id: str, tool_paramters: Dict[str, Any]) -> Union[ToolInvokeMessage, List[ToolInvokeMessage]]:
+        """
+            invoke tools
+        """
+        top_n = tool_paramters.get('top_n', 5)
+        query = tool_paramters.get('query', '')
+        if not query:
+            return self.create_text_message('Please input symbol')
+
+        if 'access_tokens' not in self.runtime.credentials or not self.runtime.credentials.get('access_tokens'):
+            return self.create_text_message("Github API Access Tokens is required.")
+        if 'api_version' not in self.runtime.credentials or not self.runtime.credentials.get('api_version'):
+            api_version = '2022-11-28'
+        else:
+            api_version = self.runtime.credentials.get('api_version')
+
+        try:
+            headers = {
+                "Content-Type": "application/vnd.github+json",
+                "Authorization": f"Bearer {self.runtime.credentials.get('access_tokens')}",
+                "X-GitHub-Api-Version": api_version
+            }
+            s = requests.session()
+            api_domain = 'https://api.github.com'
+            response = s.request(method='GET', headers=headers,
+                                 url=f"{api_domain}/search/repositories?"
+                                     f"q={quote(query)}&sort=stars&per_page={top_n}&order=desc")
+            response_data = response.json()
+            if response.status_code == 200 and isinstance(response_data.get('items'), list):
+                contents = list()
+                if len(response_data.get('items')) > 0:
+                    for item in response_data.get('items'):
+                        content = dict()
+                        updated_at_object = datetime.strptime(item['updated_at'], "%Y-%m-%dT%H:%M:%SZ")
+                        content['owner'] = item['owner']['login']
+                        content['name'] = item['name']
+                        content['description'] = item['description'][:100] + '...' if len(item['description']) > 100 else item['description']
+                        content['url'] = item['html_url']
+                        content['star'] = item['watchers']
+                        content['forks'] = item['forks']
+                        content['updated'] = updated_at_object.strftime("%Y-%m-%d")
+                        contents.append(content)
+                    s.close()
+                    return self.create_text_message(self.summary(user_id=user_id, content=json.dumps(contents, ensure_ascii=False)))
+                else:
+                    return self.create_text_message(f'No items related to {query} were found.')
+            else:
+                return self.create_text_message((response.json()).get('message'))
+        except Exception as e:
+            return self.create_text_message("Github API Key and Api Version is invalid. {}".format(e))

api/core/tools/provider/builtin/github/tools/repositories.yaml

+identity:
+  name: repositories
+  author: CharlieWei
+  label:
+    en_US: Search Repositories
+    zh_Hans: 仓库搜索
+    pt_BR: Pesquisar Repositórios
+  icon: icon.svg
+description:
+  human:
+    en_US: Search the Github repository to retrieve the open source projects you need
+    zh_Hans: 搜索Github仓库，检索你需要的开源项目。
+    pt_BR: Pesquise o repositório do Github para recuperar os projetos de código aberto necessários.
+  llm: A tool when you wants to search for popular warehouses or open source projects for any keyword. format query condition like "keywords+language:js", language can be other dev languages.
+parameters:
+  - name: query
+    type: string
+    required: true
+    label:
+      en_US: query
+      zh_Hans: 关键字
+      pt_BR: consulta
+    human_description:
+      en_US: You want to find the project development language, keywords, For example. Find 10 Python developed PDF document parsing projects.
+      zh_Hans: 你想要找的项目开发语言、关键字，如：找10个Python开发的PDF文档解析项目。
+      pt_BR: Você deseja encontrar a linguagem de desenvolvimento do projeto, palavras-chave, Por exemplo. Encontre 10 projetos de análise de documentos PDF desenvolvidos em Python.
+    llm_description: The query of you want to search, format query condition like "keywords+language:js", language can be other dev languages, por exemplo. Procuro um projeto de análise de documentos PDF desenvolvido em Python.
+    form: llm
+  - name: top_n
+    type: number
+    default: 5
+    required: true
+    label:
+      en_US: Top N
+      zh_Hans: Top N
+      pt_BR: Topo N
+    human_description:
+      en_US: Number of records returned by sorting based on stars. 5 is returned by default.
+      zh_Hans: 基于stars排序返回的记录数, 默认返回5条。
+      pt_BR: Número de registros retornados por classificação com base em estrelas. 5 é retornado por padrão.
+    llm_description: Extract the first N records from the returned result.
+    form: llm

api/core/tools/provider/builtin_tool_provider.py

@@ -40,7 +40,7 @@ class BuiltinToolProviderController(ToolProviderController):
             'credentials_schema': provider_yaml['credentials_for_provider'] if 'credentials_for_provider' in provider_yaml else None,
         })
 
-    def _get_bulitin_tools(self) -> List[Tool]:
+    def _get_builtin_tools(self) -> List[Tool]:
         """
             returns a list of tools that the provider can provide
 
@@ -101,7 +101,7 @@ class BuiltinToolProviderController(ToolProviderController):
 
             :return: list of tools
         """
-        return self._get_bulitin_tools()
+        return self._get_builtin_tools()
     
     def get_tool(self, tool_name: str) -> Tool:
         """