diff --git a/.github/workflows/build-push.yml b/.github/workflows/build-push.yml index 407bd47d9b..6daaaf5791 100644 --- a/.github/workflows/build-push.yml +++ b/.github/workflows/build-push.yml @@ -125,7 +125,7 @@ jobs: with: images: ${{ env[matrix.image_name_env] }} tags: | - type=raw,value=latest,enable=${{ startsWith(github.ref, 'refs/tags/') }} + type=raw,value=latest,enable=${{ startsWith(github.ref, 'refs/tags/') && !contains(github.ref, '-') }} type=ref,event=branch type=sha,enable=true,priority=100,prefix=,suffix=,format=long type=raw,value=${{ github.ref_name }},enable=${{ startsWith(github.ref, 'refs/tags/') }} diff --git a/api/.env.example b/api/.env.example index a3db406aea..7e5c636ff8 100644 --- a/api/.env.example +++ b/api/.env.example @@ -162,6 +162,8 @@ PGVECTOR_PORT=5433 PGVECTOR_USER=postgres PGVECTOR_PASSWORD=postgres PGVECTOR_DATABASE=postgres +PGVECTOR_MIN_CONNECTION=1 +PGVECTOR_MAX_CONNECTION=5 # Tidb Vector configuration TIDB_VECTOR_HOST=xxx.eu-central-1.xxx.aws.tidbcloud.com diff --git a/api/configs/middleware/vdb/pgvector_config.py b/api/configs/middleware/vdb/pgvector_config.py index 395dcaa420..85f5dca7e2 100644 --- a/api/configs/middleware/vdb/pgvector_config.py +++ b/api/configs/middleware/vdb/pgvector_config.py @@ -33,3 +33,13 @@ class PGVectorConfig(BaseSettings): description="Name of the PostgreSQL database to connect to", default=None, ) + + PGVECTOR_MIN_CONNECTION: PositiveInt = Field( + description="Min connection of the PostgreSQL database", + default=1, + ) + + PGVECTOR_MAX_CONNECTION: PositiveInt = Field( + description="Max connection of the PostgreSQL database", + default=5, + ) diff --git a/api/controllers/console/__init__.py b/api/controllers/console/__init__.py index eb7c1464d3..c7282fcf14 100644 --- a/api/controllers/console/__init__.py +++ b/api/controllers/console/__init__.py @@ -37,7 +37,16 @@ from .auth import activate, data_source_bearer_auth, data_source_oauth, forgot_p from .billing import billing # Import datasets controllers -from .datasets import data_source, datasets, datasets_document, datasets_segments, file, hit_testing, website +from .datasets import ( + data_source, + datasets, + datasets_document, + datasets_segments, + external, + file, + hit_testing, + website, +) # Import explore controllers from .explore import ( diff --git a/api/controllers/console/datasets/datasets.py b/api/controllers/console/datasets/datasets.py index 2c4e5ac607..9561fd8b70 100644 --- a/api/controllers/console/datasets/datasets.py +++ b/api/controllers/console/datasets/datasets.py @@ -49,7 +49,7 @@ class DatasetListApi(Resource): page = request.args.get("page", default=1, type=int) limit = request.args.get("limit", default=20, type=int) ids = request.args.getlist("ids") - provider = request.args.get("provider", default="vendor") + # provider = request.args.get("provider", default="vendor") search = request.args.get("keyword", default=None, type=str) tag_ids = request.args.getlist("tag_ids") @@ -57,7 +57,7 @@ class DatasetListApi(Resource): datasets, total = DatasetService.get_datasets_by_ids(ids, current_user.current_tenant_id) else: datasets, total = DatasetService.get_datasets( - page, limit, provider, current_user.current_tenant_id, current_user, search, tag_ids + page, limit, current_user.current_tenant_id, current_user, search, tag_ids ) # check embedding setting @@ -110,6 +110,26 @@ class DatasetListApi(Resource): nullable=True, help="Invalid indexing technique.", ) + parser.add_argument( + "external_knowledge_api_id", + type=str, + nullable=True, + required=False, + ) + parser.add_argument( + "provider", + type=str, + nullable=True, + choices=Dataset.PROVIDER_LIST, + required=False, + default="vendor", + ) + parser.add_argument( + "external_knowledge_id", + type=str, + nullable=True, + required=False, + ) args = parser.parse_args() # The role of the current user in the ta table must be admin, owner, or editor, or dataset_operator @@ -123,6 +143,9 @@ class DatasetListApi(Resource): indexing_technique=args["indexing_technique"], account=current_user, permission=DatasetPermissionEnum.ONLY_ME, + provider=args["provider"], + external_knowledge_api_id=args["external_knowledge_api_id"], + external_knowledge_id=args["external_knowledge_id"], ) except services.errors.dataset.DatasetNameDuplicateError: raise DatasetNameDuplicateError() @@ -211,6 +234,33 @@ class DatasetApi(Resource): ) parser.add_argument("retrieval_model", type=dict, location="json", help="Invalid retrieval model.") parser.add_argument("partial_member_list", type=list, location="json", help="Invalid parent user list.") + + parser.add_argument( + "external_retrieval_model", + type=dict, + required=False, + nullable=True, + location="json", + help="Invalid external retrieval model.", + ) + + parser.add_argument( + "external_knowledge_id", + type=str, + required=False, + nullable=True, + location="json", + help="Invalid external knowledge id.", + ) + + parser.add_argument( + "external_knowledge_api_id", + type=str, + required=False, + nullable=True, + location="json", + help="Invalid external knowledge api id.", + ) args = parser.parse_args() data = request.get_json() @@ -563,10 +613,10 @@ class DatasetRetrievalSettingApi(Resource): case ( VectorType.MILVUS | VectorType.RELYT - | VectorType.PGVECTOR | VectorType.TIDB_VECTOR | VectorType.CHROMA | VectorType.TENCENT + | VectorType.PGVECTO_RS ): return {"retrieval_method": [RetrievalMethod.SEMANTIC_SEARCH.value]} case ( @@ -577,6 +627,7 @@ class DatasetRetrievalSettingApi(Resource): | VectorType.MYSCALE | VectorType.ORACLE | VectorType.ELASTICSEARCH + | VectorType.PGVECTOR ): return { "retrieval_method": [ diff --git a/api/controllers/console/datasets/external.py b/api/controllers/console/datasets/external.py new file mode 100644 index 0000000000..dcef979360 --- /dev/null +++ b/api/controllers/console/datasets/external.py @@ -0,0 +1,239 @@ +from flask import request +from flask_login import current_user +from flask_restful import Resource, marshal, reqparse +from werkzeug.exceptions import Forbidden, InternalServerError, NotFound + +import services +from controllers.console import api +from controllers.console.datasets.error import DatasetNameDuplicateError +from controllers.console.setup import setup_required +from controllers.console.wraps import account_initialization_required +from fields.dataset_fields import dataset_detail_fields +from libs.login import login_required +from services.dataset_service import DatasetService +from services.external_knowledge_service import ExternalDatasetService +from services.hit_testing_service import HitTestingService + + +def _validate_name(name): + if not name or len(name) < 1 or len(name) > 100: + raise ValueError("Name must be between 1 to 100 characters.") + return name + + +def _validate_description_length(description): + if description and len(description) > 400: + raise ValueError("Description cannot exceed 400 characters.") + return description + + +class ExternalApiTemplateListApi(Resource): + @setup_required + @login_required + @account_initialization_required + def get(self): + page = request.args.get("page", default=1, type=int) + limit = request.args.get("limit", default=20, type=int) + search = request.args.get("keyword", default=None, type=str) + + external_knowledge_apis, total = ExternalDatasetService.get_external_knowledge_apis( + page, limit, current_user.current_tenant_id, search + ) + response = { + "data": [item.to_dict() for item in external_knowledge_apis], + "has_more": len(external_knowledge_apis) == limit, + "limit": limit, + "total": total, + "page": page, + } + return response, 200 + + @setup_required + @login_required + @account_initialization_required + def post(self): + parser = reqparse.RequestParser() + parser.add_argument( + "name", + nullable=False, + required=True, + help="Name is required. Name must be between 1 to 100 characters.", + type=_validate_name, + ) + parser.add_argument( + "settings", + type=dict, + location="json", + nullable=False, + required=True, + ) + args = parser.parse_args() + + ExternalDatasetService.validate_api_list(args["settings"]) + + # The role of the current user in the ta table must be admin, owner, or editor, or dataset_operator + if not current_user.is_dataset_editor: + raise Forbidden() + + try: + external_knowledge_api = ExternalDatasetService.create_external_knowledge_api( + tenant_id=current_user.current_tenant_id, user_id=current_user.id, args=args + ) + except services.errors.dataset.DatasetNameDuplicateError: + raise DatasetNameDuplicateError() + + return external_knowledge_api.to_dict(), 201 + + +class ExternalApiTemplateApi(Resource): + @setup_required + @login_required + @account_initialization_required + def get(self, external_knowledge_api_id): + external_knowledge_api_id = str(external_knowledge_api_id) + external_knowledge_api = ExternalDatasetService.get_external_knowledge_api(external_knowledge_api_id) + if external_knowledge_api is None: + raise NotFound("API template not found.") + + return external_knowledge_api.to_dict(), 200 + + @setup_required + @login_required + @account_initialization_required + def patch(self, external_knowledge_api_id): + external_knowledge_api_id = str(external_knowledge_api_id) + + parser = reqparse.RequestParser() + parser.add_argument( + "name", + nullable=False, + required=True, + help="type is required. Name must be between 1 to 100 characters.", + type=_validate_name, + ) + parser.add_argument( + "settings", + type=dict, + location="json", + nullable=False, + required=True, + ) + args = parser.parse_args() + ExternalDatasetService.validate_api_list(args["settings"]) + + external_knowledge_api = ExternalDatasetService.update_external_knowledge_api( + tenant_id=current_user.current_tenant_id, + user_id=current_user.id, + external_knowledge_api_id=external_knowledge_api_id, + args=args, + ) + + return external_knowledge_api.to_dict(), 200 + + @setup_required + @login_required + @account_initialization_required + def delete(self, external_knowledge_api_id): + external_knowledge_api_id = str(external_knowledge_api_id) + + # The role of the current user in the ta table must be admin, owner, or editor + if not current_user.is_editor or current_user.is_dataset_operator: + raise Forbidden() + + ExternalDatasetService.delete_external_knowledge_api(current_user.current_tenant_id, external_knowledge_api_id) + return {"result": "success"}, 200 + + +class ExternalApiUseCheckApi(Resource): + @setup_required + @login_required + @account_initialization_required + def get(self, external_knowledge_api_id): + external_knowledge_api_id = str(external_knowledge_api_id) + + external_knowledge_api_is_using, count = ExternalDatasetService.external_knowledge_api_use_check( + external_knowledge_api_id + ) + return {"is_using": external_knowledge_api_is_using, "count": count}, 200 + + +class ExternalDatasetCreateApi(Resource): + @setup_required + @login_required + @account_initialization_required + def post(self): + # The role of the current user in the ta table must be admin, owner, or editor + if not current_user.is_editor: + raise Forbidden() + + parser = reqparse.RequestParser() + parser.add_argument("external_knowledge_api_id", type=str, required=True, nullable=False, location="json") + parser.add_argument("external_knowledge_id", type=str, required=True, nullable=False, location="json") + parser.add_argument( + "name", + nullable=False, + required=True, + help="name is required. Name must be between 1 to 100 characters.", + type=_validate_name, + ) + parser.add_argument("description", type=str, required=False, nullable=True, location="json") + parser.add_argument("external_retrieval_model", type=dict, required=False, location="json") + + args = parser.parse_args() + + # The role of the current user in the ta table must be admin, owner, or editor, or dataset_operator + if not current_user.is_dataset_editor: + raise Forbidden() + + try: + dataset = ExternalDatasetService.create_external_dataset( + tenant_id=current_user.current_tenant_id, + user_id=current_user.id, + args=args, + ) + except services.errors.dataset.DatasetNameDuplicateError: + raise DatasetNameDuplicateError() + + return marshal(dataset, dataset_detail_fields), 201 + + +class ExternalKnowledgeHitTestingApi(Resource): + @setup_required + @login_required + @account_initialization_required + def post(self, dataset_id): + dataset_id_str = str(dataset_id) + dataset = DatasetService.get_dataset(dataset_id_str) + if dataset is None: + raise NotFound("Dataset not found.") + + try: + DatasetService.check_dataset_permission(dataset, current_user) + except services.errors.account.NoPermissionError as e: + raise Forbidden(str(e)) + + parser = reqparse.RequestParser() + parser.add_argument("query", type=str, location="json") + parser.add_argument("external_retrieval_model", type=dict, required=False, location="json") + args = parser.parse_args() + + HitTestingService.hit_testing_args_check(args) + + try: + response = HitTestingService.external_retrieve( + dataset=dataset, + query=args["query"], + account=current_user, + external_retrieval_model=args["external_retrieval_model"], + ) + + return response + except Exception as e: + raise InternalServerError(str(e)) + + +api.add_resource(ExternalKnowledgeHitTestingApi, "/datasets//external-hit-testing") +api.add_resource(ExternalDatasetCreateApi, "/datasets/external") +api.add_resource(ExternalApiTemplateListApi, "/datasets/external-knowledge-api") +api.add_resource(ExternalApiTemplateApi, "/datasets/external-knowledge-api/") +api.add_resource(ExternalApiUseCheckApi, "/datasets/external-knowledge-api//use-check") diff --git a/api/controllers/console/datasets/hit_testing.py b/api/controllers/console/datasets/hit_testing.py index 0b4a7be986..6e6d8c0bd7 100644 --- a/api/controllers/console/datasets/hit_testing.py +++ b/api/controllers/console/datasets/hit_testing.py @@ -47,6 +47,7 @@ class HitTestingApi(Resource): parser = reqparse.RequestParser() parser.add_argument("query", type=str, location="json") parser.add_argument("retrieval_model", type=dict, required=False, location="json") + parser.add_argument("external_retrieval_model", type=dict, required=False, location="json") args = parser.parse_args() HitTestingService.hit_testing_args_check(args) @@ -57,6 +58,7 @@ class HitTestingApi(Resource): query=args["query"], account=current_user, retrieval_model=args["retrieval_model"], + external_retrieval_model=args["external_retrieval_model"], limit=10, ) diff --git a/api/controllers/console/datasets/website.py b/api/controllers/console/datasets/website.py index cb54f1aacb..e80ce17c68 100644 --- a/api/controllers/console/datasets/website.py +++ b/api/controllers/console/datasets/website.py @@ -14,7 +14,9 @@ class WebsiteCrawlApi(Resource): @account_initialization_required def post(self): parser = reqparse.RequestParser() - parser.add_argument("provider", type=str, choices=["firecrawl"], required=True, nullable=True, location="json") + parser.add_argument( + "provider", type=str, choices=["firecrawl", "jinareader"], required=True, nullable=True, location="json" + ) parser.add_argument("url", type=str, required=True, nullable=True, location="json") parser.add_argument("options", type=dict, required=True, nullable=True, location="json") args = parser.parse_args() @@ -33,7 +35,7 @@ class WebsiteCrawlStatusApi(Resource): @account_initialization_required def get(self, job_id: str): parser = reqparse.RequestParser() - parser.add_argument("provider", type=str, choices=["firecrawl"], required=True, location="args") + parser.add_argument("provider", type=str, choices=["firecrawl", "jinareader"], required=True, location="args") args = parser.parse_args() # get crawl status try: diff --git a/api/controllers/console/version.py b/api/controllers/console/version.py index 76adbfe6a9..deda1a0d02 100644 --- a/api/controllers/console/version.py +++ b/api/controllers/console/version.py @@ -38,11 +38,52 @@ class VersionApi(Resource): return result content = json.loads(response.content) - result["version"] = content["version"] - result["release_date"] = content["releaseDate"] - result["release_notes"] = content["releaseNotes"] - result["can_auto_update"] = content["canAutoUpdate"] + if _has_new_version(latest_version=content["version"], current_version=f"{args.get('current_version')}"): + result["version"] = content["version"] + result["release_date"] = content["releaseDate"] + result["release_notes"] = content["releaseNotes"] + result["can_auto_update"] = content["canAutoUpdate"] return result +def _has_new_version(*, latest_version: str, current_version: str) -> bool: + def parse_version(version: str) -> tuple: + # Split version into parts and pre-release suffix if any + parts = version.split("-") + version_parts = parts[0].split(".") + pre_release = parts[1] if len(parts) > 1 else None + + # Validate version format + if len(version_parts) != 3: + raise ValueError(f"Invalid version format: {version}") + + try: + # Convert version parts to integers + major, minor, patch = map(int, version_parts) + return (major, minor, patch, pre_release) + except ValueError: + raise ValueError(f"Invalid version format: {version}") + + latest = parse_version(latest_version) + current = parse_version(current_version) + + # Compare major, minor, and patch versions + for latest_part, current_part in zip(latest[:3], current[:3]): + if latest_part > current_part: + return True + elif latest_part < current_part: + return False + + # If versions are equal, check pre-release suffixes + if latest[3] is None and current[3] is not None: + return True + elif latest[3] is not None and current[3] is None: + return False + elif latest[3] is not None and current[3] is not None: + # Simple string comparison for pre-release versions + return latest[3] > current[3] + + return False + + api.add_resource(VersionApi, "/version") diff --git a/api/controllers/service_api/dataset/dataset.py b/api/controllers/service_api/dataset/dataset.py index c2c0672a03..f076cff6c8 100644 --- a/api/controllers/service_api/dataset/dataset.py +++ b/api/controllers/service_api/dataset/dataset.py @@ -28,11 +28,11 @@ class DatasetListApi(DatasetApiResource): page = request.args.get("page", default=1, type=int) limit = request.args.get("limit", default=20, type=int) - provider = request.args.get("provider", default="vendor") + # provider = request.args.get("provider", default="vendor") search = request.args.get("keyword", default=None, type=str) tag_ids = request.args.getlist("tag_ids") - datasets, total = DatasetService.get_datasets(page, limit, provider, tenant_id, current_user, search, tag_ids) + datasets, total = DatasetService.get_datasets(page, limit, tenant_id, current_user, search, tag_ids) # check embedding setting provider_manager = ProviderManager() configurations = provider_manager.get_configurations(tenant_id=current_user.current_tenant_id) @@ -82,6 +82,26 @@ class DatasetListApi(DatasetApiResource): required=False, nullable=False, ) + parser.add_argument( + "external_knowledge_api_id", + type=str, + nullable=True, + required=False, + default="_validate_name", + ) + parser.add_argument( + "provider", + type=str, + nullable=True, + required=False, + default="vendor", + ) + parser.add_argument( + "external_knowledge_id", + type=str, + nullable=True, + required=False, + ) args = parser.parse_args() try: @@ -91,6 +111,9 @@ class DatasetListApi(DatasetApiResource): indexing_technique=args["indexing_technique"], account=current_user, permission=args["permission"], + provider=args["provider"], + external_knowledge_api_id=args["external_knowledge_api_id"], + external_knowledge_id=args["external_knowledge_id"], ) except services.errors.dataset.DatasetNameDuplicateError: raise DatasetNameDuplicateError() diff --git a/api/core/app/apps/advanced_chat/generate_task_pipeline.py b/api/core/app/apps/advanced_chat/generate_task_pipeline.py index 94206a1b1c..897b6fd063 100644 --- a/api/core/app/apps/advanced_chat/generate_task_pipeline.py +++ b/api/core/app/apps/advanced_chat/generate_task_pipeline.py @@ -231,7 +231,8 @@ class AdvancedChatAppGenerateTaskPipeline(BasedGenerateTaskPipeline, WorkflowCyc except Exception as e: logger.error(e) break - yield MessageAudioEndStreamResponse(audio="", task_id=task_id) + if tts_publisher: + yield MessageAudioEndStreamResponse(audio="", task_id=task_id) def _process_stream_response( self, diff --git a/api/core/app/apps/workflow/generate_task_pipeline.py b/api/core/app/apps/workflow/generate_task_pipeline.py index 93edf8e0e8..798847a507 100644 --- a/api/core/app/apps/workflow/generate_task_pipeline.py +++ b/api/core/app/apps/workflow/generate_task_pipeline.py @@ -212,7 +212,8 @@ class WorkflowAppGenerateTaskPipeline(BasedGenerateTaskPipeline, WorkflowCycleMa except Exception as e: logger.error(e) break - yield MessageAudioEndStreamResponse(audio="", task_id=task_id) + if tts_publisher: + yield MessageAudioEndStreamResponse(audio="", task_id=task_id) def _process_stream_response( self, diff --git a/api/core/app/segments/exc.py b/api/core/app/segments/exc.py index d15d6d500f..5cf67c3bac 100644 --- a/api/core/app/segments/exc.py +++ b/api/core/app/segments/exc.py @@ -1,2 +1,2 @@ -class VariableError(Exception): +class VariableError(ValueError): pass diff --git a/api/core/app/task_pipeline/easy_ui_based_generate_task_pipeline.py b/api/core/app/task_pipeline/easy_ui_based_generate_task_pipeline.py index 8f834b6458..917649f34e 100644 --- a/api/core/app/task_pipeline/easy_ui_based_generate_task_pipeline.py +++ b/api/core/app/task_pipeline/easy_ui_based_generate_task_pipeline.py @@ -248,7 +248,8 @@ class EasyUIBasedGenerateTaskPipeline(BasedGenerateTaskPipeline, MessageCycleMan else: start_listener_time = time.time() yield MessageAudioStreamResponse(audio=audio.audio, task_id=task_id) - yield MessageAudioEndStreamResponse(audio="", task_id=task_id) + if publisher: + yield MessageAudioEndStreamResponse(audio="", task_id=task_id) def _process_stream_response( self, publisher: AppGeneratorTTSPublisher, trace_manager: Optional[TraceQueueManager] = None diff --git a/api/core/callback_handler/index_tool_callback_handler.py b/api/core/callback_handler/index_tool_callback_handler.py index 7cf472d984..23dc092895 100644 --- a/api/core/callback_handler/index_tool_callback_handler.py +++ b/api/core/callback_handler/index_tool_callback_handler.py @@ -59,7 +59,7 @@ class DatasetIndexToolCallbackHandler: for item in resource: dataset_retriever_resource = DatasetRetrieverResource( message_id=self._message_id, - position=item.get("position"), + position=item.get("position") or 0, dataset_id=item.get("dataset_id"), dataset_name=item.get("dataset_name"), document_id=item.get("document_id"), diff --git a/api/core/entities/provider_configuration.py b/api/core/entities/provider_configuration.py index 4797b69b85..807f09598c 100644 --- a/api/core/entities/provider_configuration.py +++ b/api/core/entities/provider_configuration.py @@ -119,7 +119,7 @@ class ProviderConfiguration(BaseModel): credentials = model_configuration.credentials break - if self.custom_configuration.provider: + if not credentials and self.custom_configuration.provider: credentials = self.custom_configuration.provider.credentials return credentials diff --git a/api/core/model_runtime/callbacks/base_callback.py b/api/core/model_runtime/callbacks/base_callback.py index 92da53c9a4..6bd9325785 100644 --- a/api/core/model_runtime/callbacks/base_callback.py +++ b/api/core/model_runtime/callbacks/base_callback.py @@ -1,3 +1,4 @@ +from abc import ABC, abstractmethod from typing import Optional from core.model_runtime.entities.llm_entities import LLMResult, LLMResultChunk @@ -13,7 +14,7 @@ _TEXT_COLOR_MAPPING = { } -class Callback: +class Callback(ABC): """ Base class for callbacks. Only for LLM. @@ -21,6 +22,7 @@ class Callback: raise_error: bool = False + @abstractmethod def on_before_invoke( self, llm_instance: AIModel, @@ -48,6 +50,7 @@ class Callback: """ raise NotImplementedError() + @abstractmethod def on_new_chunk( self, llm_instance: AIModel, @@ -77,6 +80,7 @@ class Callback: """ raise NotImplementedError() + @abstractmethod def on_after_invoke( self, llm_instance: AIModel, @@ -106,6 +110,7 @@ class Callback: """ raise NotImplementedError() + @abstractmethod def on_invoke_error( self, llm_instance: AIModel, diff --git a/api/core/model_runtime/docs/en_US/customizable_model_scale_out.md b/api/core/model_runtime/docs/en_US/customizable_model_scale_out.md new file mode 100644 index 0000000000..f5b806ade6 --- /dev/null +++ b/api/core/model_runtime/docs/en_US/customizable_model_scale_out.md @@ -0,0 +1,310 @@ +## Custom Integration of Pre-defined Models + +### Introduction + +After completing the vendors integration, the next step is to connect the vendor's models. To illustrate the entire connection process, we will use Xinference as an example to demonstrate a complete vendor integration. + +It is important to note that for custom models, each model connection requires a complete vendor credential. + +Unlike pre-defined models, a custom vendor integration always includes the following two parameters, which do not need to be defined in the vendor YAML file. + +![](images/index/image-3.png) + +As mentioned earlier, vendors do not need to implement validate_provider_credential. The runtime will automatically call the corresponding model layer's validate_credentials to validate the credentials based on the model type and name selected by the user. + +### Writing the Vendor YAML + +First, we need to identify the types of models supported by the vendor we are integrating. + +Currently supported model types are as follows: + +- `llm` Text Generation Models + +- `text_embedding` Text Embedding Models + +- `rerank` Rerank Models + +- `speech2text` Speech-to-Text + +- `tts` Text-to-Speech + +- `moderation` Moderation + +Xinference supports LLM, Text Embedding, and Rerank. So we will start by writing xinference.yaml. + +```yaml +provider: xinference #Define the vendor identifier +label: # Vendor display name, supports both en_US (English) and zh_Hans (Simplified Chinese). If zh_Hans is not set, it will use en_US by default. + en_US: Xorbits Inference +icon_small: # Small icon, refer to other vendors' icons stored in the _assets directory within the vendor implementation directory; follows the same language policy as the label + en_US: icon_s_en.svg +icon_large: # Large icon + en_US: icon_l_en.svg +help: # Help information + title: + en_US: How to deploy Xinference + zh_Hans: 如何部署 Xinference + url: + en_US: https://github.com/xorbitsai/inference +supported_model_types: # Supported model types. Xinference supports LLM, Text Embedding, and Rerank +- llm +- text-embedding +- rerank +configurate_methods: # Since Xinference is a locally deployed vendor with no predefined models, users need to deploy whatever models they need according to Xinference documentation. Thus, it only supports custom models. +- customizable-model +provider_credential_schema: + credential_form_schemas: +``` + + +Then, we need to determine what credentials are required to define a model in Xinference. + +- Since it supports three different types of models, we need to specify the model_type to denote the model type. Here is how we can define it: + +```yaml +provider_credential_schema: + credential_form_schemas: + - variable: model_type + type: select + label: + en_US: Model type + zh_Hans: 模型类型 + required: true + options: + - value: text-generation + label: + en_US: Language Model + zh_Hans: 语言模型 + - value: embeddings + label: + en_US: Text Embedding + - value: reranking + label: + en_US: Rerank +``` + +- Next, each model has its own model_name, so we need to define that here: + +```yaml + - variable: model_name + type: text-input + label: + en_US: Model name + zh_Hans: 模型名称 + required: true + placeholder: + zh_Hans: 填写模型名称 + en_US: Input model name +``` + +- Specify the Xinference local deployment address: + +```yaml + - variable: server_url + label: + zh_Hans: 服务器URL + en_US: Server url + type: text-input + required: true + placeholder: + zh_Hans: 在此输入Xinference的服务器地址，如 https://example.com/xxx + en_US: Enter the url of your Xinference, for example https://example.com/xxx +``` + +- Each model has a unique model_uid, so we also need to define that here: + +```yaml + - variable: model_uid + label: + zh_Hans: 模型UID + en_US: Model uid + type: text-input + required: true + placeholder: + zh_Hans: 在此输入您的Model UID + en_US: Enter the model uid +``` + +Now, we have completed the basic definition of the vendor. + +### Writing the Model Code + +Next, let's take the `llm` type as an example and write `xinference.llm.llm.py`. + +In `llm.py`, create a Xinference LLM class, we name it `XinferenceAILargeLanguageModel` (this can be arbitrary), inheriting from the `__base.large_language_model.LargeLanguageModel` base class, and implement the following methods: + +- LLM Invocation + +Implement the core method for LLM invocation, supporting both stream and synchronous responses. + +```python +def _invoke(self, model: str, credentials: dict, + prompt_messages: list[PromptMessage], model_parameters: dict, + tools: Optional[list[PromptMessageTool]] = None, stop: Optional[list[str]] = None, + stream: bool = True, user: Optional[str] = None) \ + -> Union[LLMResult, Generator]: + """ + Invoke large language model + + :param model: model name + :param credentials: model credentials + :param prompt_messages: prompt messages + :param model_parameters: model parameters + :param tools: tools for tool usage + :param stop: stop words + :param stream: is the response a stream + :param user: unique user id + :return: full response or stream response chunk generator result + """ +``` + +When implementing, ensure to use two functions to return data separately for synchronous and stream responses. This is important because Python treats functions containing the `yield` keyword as generator functions, mandating them to return `Generator` types. Here’s an example (note that the example uses simplified parameters; in real implementation, use the parameter list as defined above): + +```python +def _invoke(self, stream: bool, **kwargs) \ + -> Union[LLMResult, Generator]: + if stream: + return self._handle_stream_response(**kwargs) + return self._handle_sync_response(**kwargs) + +def _handle_stream_response(self, **kwargs) -> Generator: + for chunk in response: + yield chunk +def _handle_sync_response(self, **kwargs) -> LLMResult: + return LLMResult(**response) +``` + +- Pre-compute Input Tokens + +If the model does not provide an interface for pre-computing tokens, you can return 0 directly. + +```python +def get_num_tokens(self, model: str, credentials: dict, prompt_messages: list[PromptMessage],tools: Optional[list[PromptMessageTool]] = None) -> int: + """ + Get number of tokens for given prompt messages + + :param model: model name + :param credentials: model credentials + :param prompt_messages: prompt messages + :param tools: tools for tool usage + :return: token count + """ +``` + + +Sometimes, you might not want to return 0 directly. In such cases, you can use `self._get_num_tokens_by_gpt2(text: str)` to get pre-computed tokens. This method is provided by the `AIModel` base class, and it uses GPT2's Tokenizer for calculation. However, it should be noted that this is only a substitute and may not be fully accurate. + +- Model Credentials Validation + +Similar to vendor credentials validation, this method validates individual model credentials. + +```python +def validate_credentials(self, model: str, credentials: dict) -> None: + """ + Validate model credentials + + :param model: model name + :param credentials: model credentials + :return: None + """ +``` + +- Model Parameter Schema + +Unlike custom types, since the YAML file does not define which parameters a model supports, we need to dynamically generate the model parameter schema. + +For instance, Xinference supports `max_tokens`, `temperature`, and `top_p` parameters. + +However, some vendors may support different parameters for different models. For example, the `OpenLLM` vendor supports `top_k`, but not all models provided by this vendor support `top_k`. Let's say model A supports `top_k` but model B does not. In such cases, we need to dynamically generate the model parameter schema, as illustrated below: + +```python + def get_customizable_model_schema(self, model: str, credentials: dict) -> AIModelEntity | None: + """ + used to define customizable model schema + """ + rules = [ + ParameterRule( + name='temperature', type=ParameterType.FLOAT, + use_template='temperature', + label=I18nObject( + zh_Hans='温度', en_US='Temperature' + ) + ), + ParameterRule( + name='top_p', type=ParameterType.FLOAT, + use_template='top_p', + label=I18nObject( + zh_Hans='Top P', en_US='Top P' + ) + ), + ParameterRule( + name='max_tokens', type=ParameterType.INT, + use_template='max_tokens', + min=1, + default=512, + label=I18nObject( + zh_Hans='最大生成长度', en_US='Max Tokens' + ) + ) + ] + + # if model is A, add top_k to rules + if model == 'A': + rules.append( + ParameterRule( + name='top_k', type=ParameterType.INT, + use_template='top_k', + min=1, + default=50, + label=I18nObject( + zh_Hans='Top K', en_US='Top K' + ) + ) + ) + + """ + some NOT IMPORTANT code here + """ + + entity = AIModelEntity( + model=model, + label=I18nObject( + en_US=model + ), + fetch_from=FetchFrom.CUSTOMIZABLE_MODEL, + model_type=model_type, + model_properties={ + ModelPropertyKey.MODE: ModelType.LLM, + }, + parameter_rules=rules + ) + + return entity +``` + +- Exception Error Mapping + +When a model invocation error occurs, it should be mapped to the runtime's specified `InvokeError` type, enabling Dify to handle different errors appropriately. + +Runtime Errors: + +- `InvokeConnectionError` Connection error during invocation +- `InvokeServerUnavailableError` Service provider unavailable +- `InvokeRateLimitError` Rate limit reached +- `InvokeAuthorizationError` Authorization failure +- `InvokeBadRequestError` Invalid request parameters + +```python + @property + def _invoke_error_mapping(self) -> dict[type[InvokeError], list[type[Exception]]]: + """ + Map model invoke error to unified error + The key is the error type thrown to the caller + The value is the error type thrown by the model, + which needs to be converted into a unified error type for the caller. + + :return: Invoke error mapping + """ +``` + +For interface method details, see: [Interfaces](./interfaces.md). For specific implementations, refer to: [llm.py](https://github.com/langgenius/dify-runtime/blob/main/lib/model_providers/anthropic/llm/llm.py). \ No newline at end of file diff --git a/api/core/model_runtime/docs/en_US/images/index/image-1.png b/api/core/model_runtime/docs/en_US/images/index/image-1.png new file mode 100644 index 0000000000..b158d44b29 Binary files /dev/null and b/api/core/model_runtime/docs/en_US/images/index/image-1.png differ diff --git a/api/core/model_runtime/docs/en_US/images/index/image-2.png b/api/core/model_runtime/docs/en_US/images/index/image-2.png new file mode 100644 index 0000000000..c70cd3da5e Binary files /dev/null and b/api/core/model_runtime/docs/en_US/images/index/image-2.png differ diff --git a/api/core/model_runtime/docs/en_US/images/index/image-3.png b/api/core/model_runtime/docs/en_US/images/index/image-3.png new file mode 100644 index 0000000000..bf0b9a7f47 Binary files /dev/null and b/api/core/model_runtime/docs/en_US/images/index/image-3.png differ diff --git a/api/core/model_runtime/docs/en_US/images/index/image.png b/api/core/model_runtime/docs/en_US/images/index/image.png new file mode 100644 index 0000000000..eb63d107e1 Binary files /dev/null and b/api/core/model_runtime/docs/en_US/images/index/image.png differ diff --git a/api/core/model_runtime/docs/en_US/predefined_model_scale_out.md b/api/core/model_runtime/docs/en_US/predefined_model_scale_out.md new file mode 100644 index 0000000000..3e16257452 --- /dev/null +++ b/api/core/model_runtime/docs/en_US/predefined_model_scale_out.md @@ -0,0 +1,173 @@ +## Predefined Model Integration + +After completing the vendor integration, the next step is to integrate the models from the vendor. + +First, we need to determine the type of model to be integrated and create the corresponding model type `module` under the respective vendor's directory. + +Currently supported model types are: + +- `llm` Text Generation Model +- `text_embedding` Text Embedding Model +- `rerank` Rerank Model +- `speech2text` Speech-to-Text +- `tts` Text-to-Speech +- `moderation` Moderation + +Continuing with `Anthropic` as an example, `Anthropic` only supports LLM, so create a `module` named `llm` under `model_providers.anthropic`. + +For predefined models, we first need to create a YAML file named after the model under the `llm` `module`, such as `claude-2.1.yaml`. + +### Prepare Model YAML + +```yaml +model: claude-2.1 # Model identifier +# Display name of the model, which can be set to en_US English or zh_Hans Chinese. If zh_Hans is not set, it will default to en_US. +# This can also be omitted, in which case the model identifier will be used as the label +label: + en_US: claude-2.1 +model_type: llm # Model type, claude-2.1 is an LLM +features: # Supported features, agent-thought supports Agent reasoning, vision supports image understanding +- agent-thought +model_properties: # Model properties + mode: chat # LLM mode, complete for text completion models, chat for conversation models + context_size: 200000 # Maximum context size +parameter_rules: # Parameter rules for the model call; only LLM requires this +- name: temperature # Parameter variable name + # Five default configuration templates are provided: temperature/top_p/max_tokens/presence_penalty/frequency_penalty + # The template variable name can be set directly in use_template, which will use the default configuration in entities.defaults.PARAMETER_RULE_TEMPLATE + # Additional configuration parameters will override the default configuration if set + use_template: temperature +- name: top_p + use_template: top_p +- name: top_k + label: # Display name of the parameter + zh_Hans: 取样数量 + en_US: Top k + type: int # Parameter type, supports float/int/string/boolean + help: # Help information, describing the parameter's function + zh_Hans: 仅从每个后续标记的前 K 个选项中采样。 + en_US: Only sample from the top K options for each subsequent token. + required: false # Whether the parameter is mandatory; can be omitted +- name: max_tokens_to_sample + use_template: max_tokens + default: 4096 # Default value of the parameter + min: 1 # Minimum value of the parameter, applicable to float/int only + max: 4096 # Maximum value of the parameter, applicable to float/int only +pricing: # Pricing information + input: '8.00' # Input unit price, i.e., prompt price + output: '24.00' # Output unit price, i.e., response content price + unit: '0.000001' # Price unit, meaning the above prices are per 100K + currency: USD # Price currency +``` + +It is recommended to prepare all model configurations before starting the implementation of the model code. + +You can also refer to the YAML configuration information under the corresponding model type directories of other vendors in the `model_providers` directory. For the complete YAML rules, refer to: [Schema](schema.md#aimodelentity). + +### Implement the Model Call Code + +Next, create a Python file named `llm.py` under the `llm` `module` to write the implementation code. + +Create an Anthropic LLM class named `AnthropicLargeLanguageModel` (or any other name), inheriting from the `__base.large_language_model.LargeLanguageModel` base class, and implement the following methods: + +- LLM Call + +Implement the core method for calling the LLM, supporting both streaming and synchronous responses. + +```python + def _invoke(self, model: str, credentials: dict, + prompt_messages: list[PromptMessage], model_parameters: dict, + tools: Optional[list[PromptMessageTool]] = None, stop: Optional[list[str]] = None, + stream: bool = True, user: Optional[str] = None) \ + -> Union[LLMResult, Generator]: + """ + Invoke large language model + + :param model: model name + :param credentials: model credentials + :param prompt_messages: prompt messages + :param model_parameters: model parameters + :param tools: tools for tool calling + :param stop: stop words + :param stream: is stream response + :param user: unique user id + :return: full response or stream response chunk generator result + """ +``` + +Ensure to use two functions for returning data, one for synchronous returns and the other for streaming returns, because Python identifies functions containing the `yield` keyword as generator functions, fixing the return type to `Generator`. Thus, synchronous and streaming returns need to be implemented separately, as shown below (note that the example uses simplified parameters, for actual implementation follow the above parameter list): + +```python + def _invoke(self, stream: bool, **kwargs) \ + -> Union[LLMResult, Generator]: + if stream: + return self._handle_stream_response(**kwargs) + return self._handle_sync_response(**kwargs) + + def _handle_stream_response(self, **kwargs) -> Generator: + for chunk in response: + yield chunk + def _handle_sync_response(self, **kwargs) -> LLMResult: + return LLMResult(**response) +``` + +- Pre-compute Input Tokens + +If the model does not provide an interface to precompute tokens, return 0 directly. + +```python + def get_num_tokens(self, model: str, credentials: dict, prompt_messages: list[PromptMessage], + tools: Optional[list[PromptMessageTool]] = None) -> int: + """ + Get number of tokens for given prompt messages + + :param model: model name + :param credentials: model credentials + :param prompt_messages: prompt messages + :param tools: tools for tool calling + :return: + """ +``` + +- Validate Model Credentials + +Similar to vendor credential validation, but specific to a single model. + +```python + def validate_credentials(self, model: str, credentials: dict) -> None: + """ + Validate model credentials + + :param model: model name + :param credentials: model credentials + :return: + """ +``` + +- Map Invoke Errors + +When a model call fails, map it to a specific `InvokeError` type as required by Runtime, allowing Dify to handle different errors accordingly. + +Runtime Errors: + +- `InvokeConnectionError` Connection error + +- `InvokeServerUnavailableError` Service provider unavailable +- `InvokeRateLimitError` Rate limit reached +- `InvokeAuthorizationError` Authorization failed +- `InvokeBadRequestError` Parameter error + +```python + @property + def _invoke_error_mapping(self) -> dict[type[InvokeError], list[type[Exception]]]: + """ + Map model invoke error to unified error + The key is the error type thrown to the caller + The value is the error type thrown by the model, + which needs to be converted into a unified error type for the caller. + + :return: Invoke error mapping + """ +``` + +For interface method explanations, see: [Interfaces](./interfaces.md). For detailed implementation, refer to: [llm.py](https://github.com/langgenius/dify-runtime/blob/main/lib/model_providers/anthropic/llm/llm.py). \ No newline at end of file diff --git a/api/core/model_runtime/docs/en_US/provider_scale_out.md b/api/core/model_runtime/docs/en_US/provider_scale_out.md index ba356c5cab..07be5811d3 100644 --- a/api/core/model_runtime/docs/en_US/provider_scale_out.md +++ b/api/core/model_runtime/docs/en_US/provider_scale_out.md @@ -58,7 +58,7 @@ provider_credential_schema: # Provider credential rules, as Anthropic only supp en_US: Enter your API URL ``` -You can also refer to the YAML configuration information under other provider directories in `model_providers`. The complete YAML rules are available at: [Schema](schema.md#Provider). +You can also refer to the YAML configuration information under other provider directories in `model_providers`. The complete YAML rules are available at: [Schema](schema.md#provider). ### Implementing Provider Code diff --git a/api/core/model_runtime/docs/zh_Hans/provider_scale_out.md b/api/core/model_runtime/docs/zh_Hans/provider_scale_out.md index b34544c789..78aad8876f 100644 --- a/api/core/model_runtime/docs/zh_Hans/provider_scale_out.md +++ b/api/core/model_runtime/docs/zh_Hans/provider_scale_out.md @@ -117,7 +117,7 @@ model_credential_schema: en_US: Enter your API Base ``` -也可以参考 `model_providers` 目录下其他供应商目录下的 YAML 配置信息，完整的 YAML 规则见：[Schema](schema.md#Provider)。 +也可以参考 `model_providers` 目录下其他供应商目录下的 YAML 配置信息，完整的 YAML 规则见：[Schema](schema.md#provider)。 #### 实现供应商代码 diff --git a/api/core/model_runtime/model_providers/_position.yaml b/api/core/model_runtime/model_providers/_position.yaml index 80db22ea84..89fccef659 100644 --- a/api/core/model_runtime/model_providers/_position.yaml +++ b/api/core/model_runtime/model_providers/_position.yaml @@ -40,3 +40,4 @@ - fireworks - mixedbread - nomic +- voyage diff --git a/api/core/model_runtime/model_providers/bedrock/llm/_position.yaml b/api/core/model_runtime/model_providers/bedrock/llm/_position.yaml index 86c8061dee..47e2b020fd 100644 --- a/api/core/model_runtime/model_providers/bedrock/llm/_position.yaml +++ b/api/core/model_runtime/model_providers/bedrock/llm/_position.yaml @@ -6,6 +6,8 @@ - anthropic.claude-v2:1 - anthropic.claude-3-sonnet-v1:0 - anthropic.claude-3-haiku-v1:0 +- ai21.jamba-1-5-large-v1:0 +- ai21.jamba-1-5-mini-v1:0 - cohere.command-light-text-v14 - cohere.command-text-v14 - cohere.command-r-plus-v1.0 @@ -15,6 +17,10 @@ - meta.llama3-1-405b-instruct-v1:0 - meta.llama3-8b-instruct-v1:0 - meta.llama3-70b-instruct-v1:0 +- us.meta.llama3-2-1b-instruct-v1:0 +- us.meta.llama3-2-3b-instruct-v1:0 +- us.meta.llama3-2-11b-instruct-v1:0 +- us.meta.llama3-2-90b-instruct-v1:0 - meta.llama2-13b-chat-v1 - meta.llama2-70b-chat-v1 - mistral.mistral-large-2407-v1:0 diff --git a/api/core/model_runtime/model_providers/bedrock/llm/ai21.jamba-1-5-large-v1.0.yaml b/api/core/model_runtime/model_providers/bedrock/llm/ai21.jamba-1-5-large-v1.0.yaml new file mode 100644 index 0000000000..276c7312ce --- /dev/null +++ b/api/core/model_runtime/model_providers/bedrock/llm/ai21.jamba-1-5-large-v1.0.yaml @@ -0,0 +1,26 @@ +model: ai21.jamba-1-5-large-v1:0 +label: + en_US: Jamba 1.5 Large +model_type: llm +model_properties: + mode: completion + context_size: 256000 +parameter_rules: + - name: temperature + use_template: temperature + default: 1 + min: 0.0 + max: 2.0 + - name: top_p + use_template: top_p + - name: max_gen_len + use_template: max_tokens + required: true + default: 4096 + min: 1 + max: 4096 +pricing: + input: '0.002' + output: '0.008' + unit: '0.001' + currency: USD diff --git a/api/core/model_runtime/model_providers/bedrock/llm/ai21.jamba-1-5-mini-v1.0.yaml b/api/core/model_runtime/model_providers/bedrock/llm/ai21.jamba-1-5-mini-v1.0.yaml new file mode 100644 index 0000000000..3461d8ab71 --- /dev/null +++ b/api/core/model_runtime/model_providers/bedrock/llm/ai21.jamba-1-5-mini-v1.0.yaml @@ -0,0 +1,26 @@ +model: ai21.jamba-1-5-mini-v1:0 +label: + en_US: Jamba 1.5 Mini +model_type: llm +model_properties: + mode: completion + context_size: 256000 +parameter_rules: + - name: temperature + use_template: temperature + default: 1 + min: 0.0 + max: 2.0 + - name: top_p + use_template: top_p + - name: max_gen_len + use_template: max_tokens + required: true + default: 4096 + min: 1 + max: 4096 +pricing: + input: '0.0002' + output: '0.0004' + unit: '0.001' + currency: USD diff --git a/api/core/model_runtime/model_providers/bedrock/llm/llm.py b/api/core/model_runtime/model_providers/bedrock/llm/llm.py index 77bab0c294..d1961784f2 100644 --- a/api/core/model_runtime/model_providers/bedrock/llm/llm.py +++ b/api/core/model_runtime/model_providers/bedrock/llm/llm.py @@ -63,6 +63,7 @@ class BedrockLargeLanguageModel(LargeLanguageModel): {"prefix": "us.anthropic.claude-3", "support_system_prompts": True, "support_tool_use": True}, {"prefix": "eu.anthropic.claude-3", "support_system_prompts": True, "support_tool_use": True}, {"prefix": "anthropic.claude-3", "support_system_prompts": True, "support_tool_use": True}, + {"prefix": "us.meta.llama3-2", "support_system_prompts": True, "support_tool_use": True}, {"prefix": "meta.llama", "support_system_prompts": True, "support_tool_use": False}, {"prefix": "mistral.mistral-7b-instruct", "support_system_prompts": False, "support_tool_use": False}, {"prefix": "mistral.mixtral-8x7b-instruct", "support_system_prompts": False, "support_tool_use": False}, @@ -70,6 +71,7 @@ class BedrockLargeLanguageModel(LargeLanguageModel): {"prefix": "mistral.mistral-small", "support_system_prompts": True, "support_tool_use": True}, {"prefix": "cohere.command-r", "support_system_prompts": True, "support_tool_use": True}, {"prefix": "amazon.titan", "support_system_prompts": False, "support_tool_use": False}, + {"prefix": "ai21.jamba-1-5", "support_system_prompts": True, "support_tool_use": False}, ] @staticmethod diff --git a/api/core/model_runtime/model_providers/bedrock/llm/us.meta.llama3-2-11b-instruct-v1.0.yaml b/api/core/model_runtime/model_providers/bedrock/llm/us.meta.llama3-2-11b-instruct-v1.0.yaml new file mode 100644 index 0000000000..029f428776 --- /dev/null +++ b/api/core/model_runtime/model_providers/bedrock/llm/us.meta.llama3-2-11b-instruct-v1.0.yaml @@ -0,0 +1,29 @@ +model: us.meta.llama3-2-11b-instruct-v1:0 +label: + en_US: US Meta Llama 3.2 11B Instruct +model_type: llm +features: + - vision + - tool-call +model_properties: + mode: completion + context_size: 128000 +parameter_rules: + - name: temperature + use_template: temperature + default: 0.5 + min: 0.0 + max: 1 + - name: top_p + use_template: top_p + - name: max_gen_len + use_template: max_tokens + required: true + default: 512 + min: 1 + max: 2048 +pricing: + input: '0.00035' + output: '0.00035' + unit: '0.001' + currency: USD diff --git a/api/core/model_runtime/model_providers/bedrock/llm/us.meta.llama3-2-1b-instruct-v1.0.yaml b/api/core/model_runtime/model_providers/bedrock/llm/us.meta.llama3-2-1b-instruct-v1.0.yaml new file mode 100644 index 0000000000..51c8474e54 --- /dev/null +++ b/api/core/model_runtime/model_providers/bedrock/llm/us.meta.llama3-2-1b-instruct-v1.0.yaml @@ -0,0 +1,26 @@ +model: us.meta.llama3-2-1b-instruct-v1:0 +label: + en_US: US Meta Llama 3.2 1B Instruct +model_type: llm +model_properties: + mode: completion + context_size: 128000 +parameter_rules: + - name: temperature + use_template: temperature + default: 0.5 + min: 0.0 + max: 1 + - name: top_p + use_template: top_p + - name: max_gen_len + use_template: max_tokens + required: true + default: 512 + min: 1 + max: 2048 +pricing: + input: '0.0001' + output: '0.0001' + unit: '0.001' + currency: USD diff --git a/api/core/model_runtime/model_providers/bedrock/llm/us.meta.llama3-2-3b-instruct-v1.0.yaml b/api/core/model_runtime/model_providers/bedrock/llm/us.meta.llama3-2-3b-instruct-v1.0.yaml new file mode 100644 index 0000000000..472cc7403e --- /dev/null +++ b/api/core/model_runtime/model_providers/bedrock/llm/us.meta.llama3-2-3b-instruct-v1.0.yaml @@ -0,0 +1,26 @@ +model: us.meta.llama3-2-3b-instruct-v1:0 +label: + en_US: US Meta Llama 3.2 3B Instruct +model_type: llm +model_properties: + mode: completion + context_size: 128000 +parameter_rules: + - name: temperature + use_template: temperature + default: 0.5 + min: 0.0 + max: 1 + - name: top_p + use_template: top_p + - name: max_gen_len + use_template: max_tokens + required: true + default: 512 + min: 1 + max: 2048 +pricing: + input: '0.00015' + output: '0.00015' + unit: '0.001' + currency: USD diff --git a/api/core/model_runtime/model_providers/bedrock/llm/us.meta.llama3-2-90b-instruct-v1.0.yaml b/api/core/model_runtime/model_providers/bedrock/llm/us.meta.llama3-2-90b-instruct-v1.0.yaml new file mode 100644 index 0000000000..cecd0236ca --- /dev/null +++ b/api/core/model_runtime/model_providers/bedrock/llm/us.meta.llama3-2-90b-instruct-v1.0.yaml @@ -0,0 +1,31 @@ +model: us.meta.llama3-2-90b-instruct-v1:0 +label: + en_US: US Meta Llama 3.2 90B Instruct +model_type: llm +features: + - tool-call +model_properties: + mode: completion + context_size: 128000 +parameter_rules: + - name: temperature + use_template: temperature + default: 0.5 + min: 0.0 + max: 1 + - name: top_p + use_template: top_p + default: 0.9 + min: 0 + max: 1 + - name: max_gen_len + use_template: max_tokens + required: true + default: 512 + min: 1 + max: 2048 +pricing: + input: '0.002' + output: '0.002' + unit: '0.001' + currency: USD diff --git a/api/core/model_runtime/model_providers/perfxcloud/llm/_position.yaml b/api/core/model_runtime/model_providers/perfxcloud/llm/_position.yaml index 37bf400f1e..c6930e54f5 100644 --- a/api/core/model_runtime/model_providers/perfxcloud/llm/_position.yaml +++ b/api/core/model_runtime/model_providers/perfxcloud/llm/_position.yaml @@ -1,24 +1,23 @@ - Qwen2.5-72B-Instruct - Qwen2.5-7B-Instruct +- Qwen2-72B-Instruct +- Qwen2-72B-Instruct-AWQ-int4 +- Qwen2-72B-Instruct-GPTQ-Int4 +- Qwen2-7B-Instruct +- Qwen2-7B +- Qwen1.5-110B-Chat-GPTQ-Int4 +- Qwen1.5-72B-Chat-GPTQ-Int4 +- Qwen1.5-7B +- Qwen-14B-Chat-Int4 - Yi-Coder-1.5B-Chat - Yi-Coder-9B-Chat -- Qwen2-72B-Instruct-AWQ-int4 - Yi-1_5-9B-Chat-16K -- Qwen2-7B-Instruct - Reflection-Llama-3.1-70B -- Qwen2-72B-Instruct - Meta-Llama-3.1-8B-Instruct - - Meta-Llama-3.1-405B-Instruct-AWQ-INT4 - Meta-Llama-3-70B-Instruct-GPTQ-Int4 -- chatglm3-6b - Meta-Llama-3-8B-Instruct - Llama3-Chinese_v2 - deepseek-v2-lite-chat -- Qwen2-72B-Instruct-GPTQ-Int4 -- Qwen2-7B -- Qwen-14B-Chat-Int4 -- Qwen1.5-72B-Chat-GPTQ-Int4 -- Qwen1.5-7B -- Qwen1.5-110B-Chat-GPTQ-Int4 - deepseek-v2-chat +- chatglm3-6b diff --git a/api/core/model_runtime/model_providers/perfxcloud/text_embedding/_position.yaml b/api/core/model_runtime/model_providers/perfxcloud/text_embedding/_position.yaml new file mode 100644 index 0000000000..99163d4293 --- /dev/null +++ b/api/core/model_runtime/model_providers/perfxcloud/text_embedding/_position.yaml @@ -0,0 +1,4 @@ +- gte-Qwen2-7B-instruct +- BAAI/bge-large-en-v1.5 +- BAAI/bge-large-zh-v1.5 +- BAAI/bge-m3 diff --git a/api/core/model_runtime/model_providers/perfxcloud/text_embedding/gte-Qwen2-7B-instruct.yaml b/api/core/model_runtime/model_providers/perfxcloud/text_embedding/gte-Qwen2-7B-instruct.yaml index 03db0d8bce..161d5ea9a2 100644 --- a/api/core/model_runtime/model_providers/perfxcloud/text_embedding/gte-Qwen2-7B-instruct.yaml +++ b/api/core/model_runtime/model_providers/perfxcloud/text_embedding/gte-Qwen2-7B-instruct.yaml @@ -2,3 +2,4 @@ model: gte-Qwen2-7B-instruct model_type: text-embedding model_properties: context_size: 2048 +deprecated: true diff --git a/api/core/model_runtime/model_providers/siliconflow/llm/_position.yaml b/api/core/model_runtime/model_providers/siliconflow/llm/_position.yaml index a3e5d0981f..8d1df82140 100644 --- a/api/core/model_runtime/model_providers/siliconflow/llm/_position.yaml +++ b/api/core/model_runtime/model_providers/siliconflow/llm/_position.yaml @@ -1,18 +1,17 @@ - Qwen/Qwen2.5-72B-Instruct -- Qwen/Qwen2.5-Math-72B-Instruct - Qwen/Qwen2.5-32B-Instruct - Qwen/Qwen2.5-14B-Instruct - Qwen/Qwen2.5-7B-Instruct - Qwen/Qwen2.5-Coder-7B-Instruct -- deepseek-ai/DeepSeek-V2.5 +- Qwen/Qwen2.5-Math-72B-Instruct - Qwen/Qwen2-72B-Instruct - Qwen/Qwen2-57B-A14B-Instruct - Qwen/Qwen2-7B-Instruct - Qwen/Qwen2-1.5B-Instruct +- deepseek-ai/DeepSeek-V2.5 - deepseek-ai/DeepSeek-V2-Chat - deepseek-ai/DeepSeek-Coder-V2-Instruct - THUDM/glm-4-9b-chat -- THUDM/chatglm3-6b - 01-ai/Yi-1.5-34B-Chat-16K - 01-ai/Yi-1.5-9B-Chat-16K - 01-ai/Yi-1.5-6B-Chat @@ -26,13 +25,4 @@ - google/gemma-2-27b-it - google/gemma-2-9b-it - mistralai/Mistral-7B-Instruct-v0.2 -- Pro/Qwen/Qwen2-7B-Instruct -- Pro/Qwen/Qwen2-1.5B-Instruct -- Pro/THUDM/glm-4-9b-chat -- Pro/THUDM/chatglm3-6b -- Pro/01-ai/Yi-1.5-9B-Chat-16K -- Pro/01-ai/Yi-1.5-6B-Chat -- Pro/internlm/internlm2_5-7b-chat -- Pro/meta-llama/Meta-Llama-3.1-8B-Instruct -- Pro/meta-llama/Meta-Llama-3-8B-Instruct -- Pro/google/gemma-2-9b-it +- mistralai/Mixtral-8x7B-Instruct-v0.1 diff --git a/api/core/model_runtime/model_providers/siliconflow/llm/internlm2_5-20b-chat.yaml b/api/core/model_runtime/model_providers/siliconflow/llm/internlm2_5-20b-chat.yaml new file mode 100644 index 0000000000..d9663582e5 --- /dev/null +++ b/api/core/model_runtime/model_providers/siliconflow/llm/internlm2_5-20b-chat.yaml @@ -0,0 +1,30 @@ +model: internlm/internlm2_5-20b-chat +label: + en_US: internlm/internlm2_5-20b-chat +model_type: llm +features: + - agent-thought +model_properties: + mode: chat + context_size: 32768 +parameter_rules: + - name: temperature + use_template: temperature + - name: max_tokens + use_template: max_tokens + type: int + default: 512 + min: 1 + max: 4096 + help: + zh_Hans: 指定生成结果长度的上限。如果生成结果截断，可以调大该参数。 + en_US: Specifies the upper limit on the length of generated results. If the generated results are truncated, you can increase this parameter. + - name: top_p + use_template: top_p + - name: frequency_penalty + use_template: frequency_penalty +pricing: + input: '1' + output: '1' + unit: '0.000001' + currency: RMB diff --git a/api/core/model_runtime/model_providers/siliconflow/llm/qwen2.5-coder-7b-instruct.yaml b/api/core/model_runtime/model_providers/siliconflow/llm/qwen2.5-coder-7b-instruct.yaml new file mode 100644 index 0000000000..76526200cc --- /dev/null +++ b/api/core/model_runtime/model_providers/siliconflow/llm/qwen2.5-coder-7b-instruct.yaml @@ -0,0 +1,74 @@ +model: Qwen/Qwen2.5-Coder-7B-Instruct +label: + en_US: Qwen/Qwen2.5-Coder-7B-Instruct +model_type: llm +features: + - agent-thought +model_properties: + mode: chat + context_size: 131072 +parameter_rules: + - name: temperature + use_template: temperature + type: float + default: 0.3 + min: 0.0 + max: 2.0 + help: + zh_Hans: 用于控制随机性和多样性的程度。具体来说，temperature值控制了生成文本时对每个候选词的概率分布进行平滑的程度。较高的temperature值会降低概率分布的峰值，使得更多的低概率词被选择，生成结果更加多样化；而较低的temperature值则会增强概率分布的峰值，使得高概率词更容易被选择，生成结果更加确定。 + en_US: Used to control the degree of randomness and diversity. Specifically, the temperature value controls the degree to which the probability distribution of each candidate word is smoothed when generating text. A higher temperature value will reduce the peak value of the probability distribution, allowing more low-probability words to be selected, and the generated results will be more diverse; while a lower temperature value will enhance the peak value of the probability distribution, making it easier for high-probability words to be selected. , the generated results are more certain. + - name: max_tokens + use_template: max_tokens + type: int + default: 8192 + min: 1 + max: 8192 + help: + zh_Hans: 用于指定模型在生成内容时token的最大数量，它定义了生成的上限，但不保证每次都会生成到这个数量。 + en_US: It is used to specify the maximum number of tokens when the model generates content. It defines the upper limit of generation, but does not guarantee that this number will be generated every time. + - name: top_p + use_template: top_p + type: float + default: 0.8 + min: 0.1 + max: 0.9 + help: + zh_Hans: 生成过程中核采样方法概率阈值，例如，取值为0.8时，仅保留概率加起来大于等于0.8的最可能token的最小集合作为候选集。取值范围为（0,1.0)，取值越大，生成的随机性越高；取值越低，生成的确定性越高。 + en_US: The probability threshold of the kernel sampling method during the generation process. For example, when the value is 0.8, only the smallest set of the most likely tokens with a sum of probabilities greater than or equal to 0.8 is retained as the candidate set. The value range is (0,1.0). The larger the value, the higher the randomness generated; the lower the value, the higher the certainty generated. + - name: top_k + type: int + min: 0 + max: 99 + label: + zh_Hans: 取样数量 + en_US: Top k + help: + zh_Hans: 生成时，采样候选集的大小。例如，取值为50时，仅将单次生成中得分最高的50个token组成随机采样的候选集。取值越大，生成的随机性越高；取值越小，生成的确定性越高。 + en_US: The size of the sample candidate set when generated. For example, when the value is 50, only the 50 highest-scoring tokens in a single generation form a randomly sampled candidate set. The larger the value, the higher the randomness generated; the smaller the value, the higher the certainty generated. + - name: seed + required: false + type: int + default: 1234 + label: + zh_Hans: 随机种子 + en_US: Random seed + help: + zh_Hans: 生成时使用的随机数种子，用户控制模型生成内容的随机性。支持无符号64位整数，默认值为 1234。在使用seed时，模型将尽可能生成相同或相似的结果，但目前不保证每次生成的结果完全相同。 + en_US: The random number seed used when generating, the user controls the randomness of the content generated by the model. Supports unsigned 64-bit integers, default value is 1234. When using seed, the model will try its best to generate the same or similar results, but there is currently no guarantee that the results will be exactly the same every time. + - name: repetition_penalty + required: false + type: float + default: 1.1 + label: + zh_Hans: 重复惩罚 + en_US: Repetition penalty + help: + zh_Hans: 用于控制模型生成时的重复度。提高repetition_penalty时可以降低模型生成的重复度。1.0表示不做惩罚。 + en_US: Used to control the repeatability when generating models. Increasing repetition_penalty can reduce the duplication of model generation. 1.0 means no punishment. + - name: response_format + use_template: response_format +pricing: + input: '0' + output: '0' + unit: '0.000001' + currency: RMB diff --git a/api/core/model_runtime/model_providers/siliconflow/llm/qwen2.5-math-72b-instruct.yaml b/api/core/model_runtime/model_providers/siliconflow/llm/qwen2.5-math-72b-instruct.yaml new file mode 100644 index 0000000000..90afa0cfd5 --- /dev/null +++ b/api/core/model_runtime/model_providers/siliconflow/llm/qwen2.5-math-72b-instruct.yaml @@ -0,0 +1,74 @@ +model: Qwen/Qwen2.5-Math-72B-Instruct +label: + en_US: Qwen/Qwen2.5-Math-72B-Instruct +model_type: llm +features: + - agent-thought +model_properties: + mode: chat + context_size: 4096 +parameter_rules: + - name: temperature + use_template: temperature + type: float + default: 0.3 + min: 0.0 + max: 2.0 + help: + zh_Hans: 用于控制随机性和多样性的程度。具体来说，temperature值控制了生成文本时对每个候选词的概率分布进行平滑的程度。较高的temperature值会降低概率分布的峰值，使得更多的低概率词被选择，生成结果更加多样化；而较低的temperature值则会增强概率分布的峰值，使得高概率词更容易被选择，生成结果更加确定。 + en_US: Used to control the degree of randomness and diversity. Specifically, the temperature value controls the degree to which the probability distribution of each candidate word is smoothed when generating text. A higher temperature value will reduce the peak value of the probability distribution, allowing more low-probability words to be selected, and the generated results will be more diverse; while a lower temperature value will enhance the peak value of the probability distribution, making it easier for high-probability words to be selected. , the generated results are more certain. + - name: max_tokens + use_template: max_tokens + type: int + default: 2000 + min: 1 + max: 2000 + help: + zh_Hans: 用于指定模型在生成内容时token的最大数量，它定义了生成的上限，但不保证每次都会生成到这个数量。 + en_US: It is used to specify the maximum number of tokens when the model generates content. It defines the upper limit of generation, but does not guarantee that this number will be generated every time. + - name: top_p + use_template: top_p + type: float + default: 0.8 + min: 0.1 + max: 0.9 + help: + zh_Hans: 生成过程中核采样方法概率阈值，例如，取值为0.8时，仅保留概率加起来大于等于0.8的最可能token的最小集合作为候选集。取值范围为（0,1.0)，取值越大，生成的随机性越高；取值越低，生成的确定性越高。 + en_US: The probability threshold of the kernel sampling method during the generation process. For example, when the value is 0.8, only the smallest set of the most likely tokens with a sum of probabilities greater than or equal to 0.8 is retained as the candidate set. The value range is (0,1.0). The larger the value, the higher the randomness generated; the lower the value, the higher the certainty generated. + - name: top_k + type: int + min: 0 + max: 99 + label: + zh_Hans: 取样数量 + en_US: Top k + help: + zh_Hans: 生成时，采样候选集的大小。例如，取值为50时，仅将单次生成中得分最高的50个token组成随机采样的候选集。取值越大，生成的随机性越高；取值越小，生成的确定性越高。 + en_US: The size of the sample candidate set when generated. For example, when the value is 50, only the 50 highest-scoring tokens in a single generation form a randomly sampled candidate set. The larger the value, the higher the randomness generated; the smaller the value, the higher the certainty generated. + - name: seed + required: false + type: int + default: 1234 + label: + zh_Hans: 随机种子 + en_US: Random seed + help: + zh_Hans: 生成时使用的随机数种子，用户控制模型生成内容的随机性。支持无符号64位整数，默认值为 1234。在使用seed时，模型将尽可能生成相同或相似的结果，但目前不保证每次生成的结果完全相同。 + en_US: The random number seed used when generating, the user controls the randomness of the content generated by the model. Supports unsigned 64-bit integers, default value is 1234. When using seed, the model will try its best to generate the same or similar results, but there is currently no guarantee that the results will be exactly the same every time. + - name: repetition_penalty + required: false + type: float + default: 1.1 + label: + zh_Hans: 重复惩罚 + en_US: Repetition penalty + help: + zh_Hans: 用于控制模型生成时的重复度。提高repetition_penalty时可以降低模型生成的重复度。1.0表示不做惩罚。 + en_US: Used to control the repeatability when generating models. Increasing repetition_penalty can reduce the duplication of model generation. 1.0 means no punishment. + - name: response_format + use_template: response_format +pricing: + input: '4.13' + output: '4.13' + unit: '0.000001' + currency: RMB diff --git a/api/core/model_runtime/model_providers/tongyi/llm/qwen2.5-coder-7b-instruct.yaml b/api/core/model_runtime/model_providers/tongyi/llm/qwen2.5-coder-7b-instruct.yaml index fdcd3d4275..7ebeec3953 100644 --- a/api/core/model_runtime/model_providers/tongyi/llm/qwen2.5-coder-7b-instruct.yaml +++ b/api/core/model_runtime/model_providers/tongyi/llm/qwen2.5-coder-7b-instruct.yaml @@ -1,7 +1,7 @@ # for more details, please refer to https://help.aliyun.com/zh/model-studio/getting-started/models -model: qwen2.5-7b-instruct +model: qwen2.5-coder-7b-instruct label: - en_US: qwen2.5-7b-instruct + en_US: qwen2.5-coder-7b-instruct model_type: llm features: - agent-thought diff --git a/api/core/model_runtime/model_providers/voyage/__init__.py b/api/core/model_runtime/model_providers/voyage/__init__.py new file mode 100644 index 0000000000..e69de29bb2 diff --git a/api/core/model_runtime/model_providers/voyage/_assets/icon_l_en.svg b/api/core/model_runtime/model_providers/voyage/_assets/icon_l_en.svg new file mode 100644 index 0000000000..a961f5e435 --- /dev/null +++ b/api/core/model_runtime/model_providers/voyage/_assets/icon_l_en.svg @@ -0,0 +1,21 @@ + \ No newline at end of file diff --git a/api/core/model_runtime/model_providers/voyage/_assets/icon_s_en.svg b/api/core/model_runtime/model_providers/voyage/_assets/icon_s_en.svg new file mode 100644 index 0000000000..2c4e121dd7 --- /dev/null +++ b/api/core/model_runtime/model_providers/voyage/_assets/icon_s_en.svg @@ -0,0 +1,8 @@ + + + voyage + + + + + \ No newline at end of file diff --git a/api/core/model_runtime/model_providers/voyage/rerank/__init__.py b/api/core/model_runtime/model_providers/voyage/rerank/__init__.py new file mode 100644 index 0000000000..e69de29bb2 diff --git a/api/core/model_runtime/model_providers/voyage/rerank/rerank-1.yaml b/api/core/model_runtime/model_providers/voyage/rerank/rerank-1.yaml new file mode 100644 index 0000000000..9c894eda85 --- /dev/null +++ b/api/core/model_runtime/model_providers/voyage/rerank/rerank-1.yaml @@ -0,0 +1,4 @@ +model: rerank-1 +model_type: rerank +model_properties: + context_size: 8000 diff --git a/api/core/model_runtime/model_providers/voyage/rerank/rerank-lite-1.yaml b/api/core/model_runtime/model_providers/voyage/rerank/rerank-lite-1.yaml new file mode 100644 index 0000000000..b052d6f000 --- /dev/null +++ b/api/core/model_runtime/model_providers/voyage/rerank/rerank-lite-1.yaml @@ -0,0 +1,4 @@ +model: rerank-lite-1 +model_type: rerank +model_properties: + context_size: 4000 diff --git a/api/core/model_runtime/model_providers/voyage/rerank/rerank.py b/api/core/model_runtime/model_providers/voyage/rerank/rerank.py new file mode 100644 index 0000000000..33fdebbb45 --- /dev/null +++ b/api/core/model_runtime/model_providers/voyage/rerank/rerank.py @@ -0,0 +1,123 @@ +from typing import Optional + +import httpx + +from core.model_runtime.entities.common_entities import I18nObject +from core.model_runtime.entities.model_entities import AIModelEntity, FetchFrom, ModelPropertyKey, ModelType +from core.model_runtime.entities.rerank_entities import RerankDocument, RerankResult +from core.model_runtime.errors.invoke import ( + InvokeAuthorizationError, + InvokeBadRequestError, + InvokeConnectionError, + InvokeError, + InvokeRateLimitError, + InvokeServerUnavailableError, +) +from core.model_runtime.errors.validate import CredentialsValidateFailedError +from core.model_runtime.model_providers.__base.rerank_model import RerankModel + + +class VoyageRerankModel(RerankModel): + """ + Model class for Voyage rerank model. + """ + + def _invoke( + self, + model: str, + credentials: dict, + query: str, + docs: list[str], + score_threshold: Optional[float] = None, + top_n: Optional[int] = None, + user: Optional[str] = None, + ) -> RerankResult: + """ + Invoke rerank model + :param model: model name + :param credentials: model credentials + :param query: search query + :param docs: docs for reranking + :param score_threshold: score threshold + :param top_n: top n documents to return + :param user: unique user id + :return: rerank result + """ + if len(docs) == 0: + return RerankResult(model=model, docs=[]) + + base_url = credentials.get("base_url", "https://api.voyageai.com/v1") + base_url = base_url.removesuffix("/") + + try: + response = httpx.post( + base_url + "/rerank", + json={"model": model, "query": query, "documents": docs, "top_k": top_n, "return_documents": True}, + headers={"Authorization": f"Bearer {credentials.get('api_key')}", "Content-Type": "application/json"}, + ) + response.raise_for_status() + results = response.json() + + rerank_documents = [] + for result in results["data"]: + rerank_document = RerankDocument( + index=result["index"], + text=result["document"], + score=result["relevance_score"], + ) + if score_threshold is None or result["relevance_score"] >= score_threshold: + rerank_documents.append(rerank_document) + + return RerankResult(model=model, docs=rerank_documents) + except httpx.HTTPStatusError as e: + raise InvokeServerUnavailableError(str(e)) + + def validate_credentials(self, model: str, credentials: dict) -> None: + """ + Validate model credentials + :param model: model name + :param credentials: model credentials + :return: + """ + try: + self._invoke( + model=model, + credentials=credentials, + query="What is the capital of the United States?", + docs=[ + "Carson City is the capital city of the American state of Nevada. At the 2010 United States " + "Census, Carson City had a population of 55,274.", + "The Commonwealth of the Northern Mariana Islands is a group of islands in the Pacific Ocean that " + "are a political division controlled by the United States. Its capital is Saipan.", + ], + score_threshold=0.8, + ) + except Exception as ex: + raise CredentialsValidateFailedError(str(ex)) + + @property + def _invoke_error_mapping(self) -> dict[type[InvokeError], list[type[Exception]]]: + """ + Map model invoke error to unified error + """ + return { + InvokeConnectionError: [httpx.ConnectError], + InvokeServerUnavailableError: [httpx.RemoteProtocolError], + InvokeRateLimitError: [], + InvokeAuthorizationError: [httpx.HTTPStatusError], + InvokeBadRequestError: [httpx.RequestError], + } + + def get_customizable_model_schema(self, model: str, credentials: dict) -> AIModelEntity: + """ + generate custom model entities from credentials + """ + entity = AIModelEntity( + model=model, + label=I18nObject(en_US=model), + model_type=ModelType.RERANK, + fetch_from=FetchFrom.CUSTOMIZABLE_MODEL, + model_properties={ModelPropertyKey.CONTEXT_SIZE: int(credentials.get("context_size", "8000"))}, + ) + + return entity diff --git a/api/core/model_runtime/model_providers/voyage/text_embedding/__init__.py b/api/core/model_runtime/model_providers/voyage/text_embedding/__init__.py new file mode 100644 index 0000000000..e69de29bb2 diff --git a/api/core/model_runtime/model_providers/voyage/text_embedding/text_embedding.py b/api/core/model_runtime/model_providers/voyage/text_embedding/text_embedding.py new file mode 100644 index 0000000000..a8a4d3c15b --- /dev/null +++ b/api/core/model_runtime/model_providers/voyage/text_embedding/text_embedding.py @@ -0,0 +1,172 @@ +import time +from json import JSONDecodeError, dumps +from typing import Optional + +import requests + +from core.embedding.embedding_constant import EmbeddingInputType +from core.model_runtime.entities.common_entities import I18nObject +from core.model_runtime.entities.model_entities import AIModelEntity, FetchFrom, ModelPropertyKey, ModelType, PriceType +from core.model_runtime.entities.text_embedding_entities import EmbeddingUsage, TextEmbeddingResult +from core.model_runtime.errors.invoke import ( + InvokeAuthorizationError, + InvokeBadRequestError, + InvokeConnectionError, + InvokeError, + InvokeRateLimitError, + InvokeServerUnavailableError, +) +from core.model_runtime.errors.validate import CredentialsValidateFailedError +from core.model_runtime.model_providers.__base.text_embedding_model import TextEmbeddingModel + + +class VoyageTextEmbeddingModel(TextEmbeddingModel): + """ + Model class for Voyage text embedding model. + """ + + api_base: str = "https://api.voyageai.com/v1" + + def _invoke( + self, + model: str, + credentials: dict, + texts: list[str], + user: Optional[str] = None, + input_type: EmbeddingInputType = EmbeddingInputType.DOCUMENT, + ) -> TextEmbeddingResult: + """ + Invoke text embedding model + + :param model: model name + :param credentials: model credentials + :param texts: texts to embed + :param user: unique user id + :param input_type: input type + :return: embeddings result + """ + api_key = credentials["api_key"] + if not api_key: + raise CredentialsValidateFailedError("api_key is required") + + base_url = credentials.get("base_url", self.api_base) + base_url = base_url.removesuffix("/") + + url = base_url + "/embeddings" + headers = {"Authorization": "Bearer " + api_key, "Content-Type": "application/json"} + voyage_input_type = "null" + if input_type is not None: + voyage_input_type = input_type.value + data = {"model": model, "input": texts, "input_type": voyage_input_type} + + try: + response = requests.post(url, headers=headers, data=dumps(data)) + except Exception as e: + raise InvokeConnectionError(str(e)) + + if response.status_code != 200: + try: + resp = response.json() + msg = resp["detail"] + if response.status_code == 401: + raise InvokeAuthorizationError(msg) + elif response.status_code == 429: + raise InvokeRateLimitError(msg) + elif response.status_code == 500: + raise InvokeServerUnavailableError(msg) + else: + raise InvokeBadRequestError(msg) + except JSONDecodeError as e: + raise InvokeServerUnavailableError( + f"Failed to convert response to json: {e} with text: {response.text}" + ) + + try: + resp = response.json() + embeddings = resp["data"] + usage = resp["usage"] + except Exception as e: + raise InvokeServerUnavailableError(f"Failed to convert response to json: {e} with text: {response.text}") + + usage = self._calc_response_usage(model=model, credentials=credentials, tokens=usage["total_tokens"]) + + result = TextEmbeddingResult( + model=model, embeddings=[[float(data) for data in x["embedding"]] for x in embeddings], usage=usage + ) + + return result + + def get_num_tokens(self, model: str, credentials: dict, texts: list[str]) -> int: + """ + Get number of tokens for given prompt messages + + :param model: model name + :param credentials: model credentials + :param texts: texts to embed + :return: + """ + return sum(self._get_num_tokens_by_gpt2(text) for text in texts) + + def validate_credentials(self, model: str, credentials: dict) -> None: + """ + Validate model credentials + + :param model: model name + :param credentials: model credentials + :return: + """ + try: + self._invoke(model=model, credentials=credentials, texts=["ping"]) + except Exception as e: + raise CredentialsValidateFailedError(f"Credentials validation failed: {e}") + + @property + def _invoke_error_mapping(self) -> dict[type[InvokeError], list[type[Exception]]]: + return { + InvokeConnectionError: [InvokeConnectionError], + InvokeServerUnavailableError: [InvokeServerUnavailableError], + InvokeRateLimitError: [InvokeRateLimitError], + InvokeAuthorizationError: [InvokeAuthorizationError], + InvokeBadRequestError: [KeyError, InvokeBadRequestError], + } + + def _calc_response_usage(self, model: str, credentials: dict, tokens: int) -> EmbeddingUsage: + """ + Calculate response usage + + :param model: model name + :param credentials: model credentials + :param tokens: input tokens + :return: usage + """ + # get input price info + input_price_info = self.get_price( + model=model, credentials=credentials, price_type=PriceType.INPUT, tokens=tokens + ) + + # transform usage + usage = EmbeddingUsage( + tokens=tokens, + total_tokens=tokens, + unit_price=input_price_info.unit_price, + price_unit=input_price_info.unit, + total_price=input_price_info.total_amount, + currency=input_price_info.currency, + latency=time.perf_counter() - self.started_at, + ) + + return usage + + def get_customizable_model_schema(self, model: str, credentials: dict) -> AIModelEntity: + """ + generate custom model entities from credentials + """ + entity = AIModelEntity( + model=model, + label=I18nObject(en_US=model), + model_type=ModelType.TEXT_EMBEDDING, + fetch_from=FetchFrom.CUSTOMIZABLE_MODEL, + model_properties={ModelPropertyKey.CONTEXT_SIZE: int(credentials.get("context_size"))}, + ) + + return entity diff --git a/api/core/model_runtime/model_providers/voyage/text_embedding/voyage-3-lite.yaml b/api/core/model_runtime/model_providers/voyage/text_embedding/voyage-3-lite.yaml new file mode 100644 index 0000000000..a06bb7639f --- /dev/null +++ b/api/core/model_runtime/model_providers/voyage/text_embedding/voyage-3-lite.yaml @@ -0,0 +1,8 @@ +model: voyage-3-lite +model_type: text-embedding +model_properties: + context_size: 32000 +pricing: + input: '0.00002' + unit: '0.001' + currency: USD diff --git a/api/core/model_runtime/model_providers/voyage/text_embedding/voyage-3.yaml b/api/core/model_runtime/model_providers/voyage/text_embedding/voyage-3.yaml new file mode 100644 index 0000000000..117afbcaf3 --- /dev/null +++ b/api/core/model_runtime/model_providers/voyage/text_embedding/voyage-3.yaml @@ -0,0 +1,8 @@ +model: voyage-3 +model_type: text-embedding +model_properties: + context_size: 32000 +pricing: + input: '0.00006' + unit: '0.001' + currency: USD diff --git a/api/core/model_runtime/model_providers/voyage/voyage.py b/api/core/model_runtime/model_providers/voyage/voyage.py new file mode 100644 index 0000000000..3e33b45e11 --- /dev/null +++ b/api/core/model_runtime/model_providers/voyage/voyage.py @@ -0,0 +1,28 @@ +import logging + +from core.model_runtime.entities.model_entities import ModelType +from core.model_runtime.errors.validate import CredentialsValidateFailedError +from core.model_runtime.model_providers.__base.model_provider import ModelProvider + +logger = logging.getLogger(__name__) + + +class VoyageProvider(ModelProvider): + def validate_provider_credentials(self, credentials: dict) -> None: + """ + Validate provider credentials + if validate failed, raise exception + + :param credentials: provider credentials, credentials form defined in `provider_credential_schema`. + """ + try: + model_instance = self.get_model_instance(ModelType.TEXT_EMBEDDING) + + # Use `voyage-3` model for validate, + # no matter what model you pass in, text completion model or chat model + model_instance.validate_credentials(model="voyage-3", credentials=credentials) + except CredentialsValidateFailedError as ex: + raise ex + except Exception as ex: + logger.exception(f"{self.get_provider_schema().provider} credentials validate failed") + raise ex diff --git a/api/core/model_runtime/model_providers/voyage/voyage.yaml b/api/core/model_runtime/model_providers/voyage/voyage.yaml new file mode 100644 index 0000000000..c64707800e --- /dev/null +++ b/api/core/model_runtime/model_providers/voyage/voyage.yaml @@ -0,0 +1,31 @@ +provider: voyage +label: + en_US: Voyage +description: + en_US: Embedding and Rerank Model Supported +icon_small: + en_US: icon_s_en.svg +icon_large: + en_US: icon_l_en.svg +background: "#EFFDFD" +help: + title: + en_US: Get your API key from Voyage AI + zh_Hans: 从 Voyage 获取 API Key + url: + en_US: https://dash.voyageai.com/ +supported_model_types: + - text-embedding + - rerank +configurate_methods: + - predefined-model +provider_credential_schema: + credential_form_schemas: + - variable: api_key + label: + en_US: API Key + type: secret-input + required: true + placeholder: + zh_Hans: 在此输入您的 API Key + en_US: Enter your API Key diff --git a/api/core/model_runtime/model_providers/xinference/llm/llm.py b/api/core/model_runtime/model_providers/xinference/llm/llm.py index 286640079b..0c9d08679a 100644 --- a/api/core/model_runtime/model_providers/xinference/llm/llm.py +++ b/api/core/model_runtime/model_providers/xinference/llm/llm.py @@ -59,6 +59,7 @@ from core.model_runtime.model_providers.__base.large_language_model import Large from core.model_runtime.model_providers.xinference.xinference_helper import ( XinferenceHelper, XinferenceModelExtraParameter, + validate_model_uid, ) from core.model_runtime.utils import helper @@ -114,7 +115,7 @@ class XinferenceAILargeLanguageModel(LargeLanguageModel): } """ try: - if "/" in credentials["model_uid"] or "?" in credentials["model_uid"] or "#" in credentials["model_uid"]: + if not validate_model_uid(credentials): raise CredentialsValidateFailedError("model_uid should not contain /, ?, or #") extra_param = XinferenceHelper.get_xinference_extra_parameter( diff --git a/api/core/model_runtime/model_providers/xinference/rerank/rerank.py b/api/core/model_runtime/model_providers/xinference/rerank/rerank.py index 8f18bc42d2..6368cd76dc 100644 --- a/api/core/model_runtime/model_providers/xinference/rerank/rerank.py +++ b/api/core/model_runtime/model_providers/xinference/rerank/rerank.py @@ -15,6 +15,7 @@ from core.model_runtime.errors.invoke import ( ) from core.model_runtime.errors.validate import CredentialsValidateFailedError from core.model_runtime.model_providers.__base.rerank_model import RerankModel +from core.model_runtime.model_providers.xinference.xinference_helper import validate_model_uid class XinferenceRerankModel(RerankModel): @@ -77,10 +78,7 @@ class XinferenceRerankModel(RerankModel): ) # score threshold check - if score_threshold is not None: - if result["relevance_score"] >= score_threshold: - rerank_documents.append(rerank_document) - else: + if score_threshold is None or result["relevance_score"] >= score_threshold: rerank_documents.append(rerank_document) return RerankResult(model=model, docs=rerank_documents) @@ -94,7 +92,7 @@ class XinferenceRerankModel(RerankModel): :return: """ try: - if "/" in credentials["model_uid"] or "?" in credentials["model_uid"] or "#" in credentials["model_uid"]: + if not validate_model_uid(credentials): raise CredentialsValidateFailedError("model_uid should not contain /, ?, or #") credentials["server_url"] = credentials["server_url"].removesuffix("/") diff --git a/api/core/model_runtime/model_providers/xinference/speech2text/speech2text.py b/api/core/model_runtime/model_providers/xinference/speech2text/speech2text.py index a6c5b8a0a5..c5ad383911 100644 --- a/api/core/model_runtime/model_providers/xinference/speech2text/speech2text.py +++ b/api/core/model_runtime/model_providers/xinference/speech2text/speech2text.py @@ -14,6 +14,7 @@ from core.model_runtime.errors.invoke import ( ) from core.model_runtime.errors.validate import CredentialsValidateFailedError from core.model_runtime.model_providers.__base.speech2text_model import Speech2TextModel +from core.model_runtime.model_providers.xinference.xinference_helper import validate_model_uid class XinferenceSpeech2TextModel(Speech2TextModel): @@ -42,7 +43,7 @@ class XinferenceSpeech2TextModel(Speech2TextModel): :return: """ try: - if "/" in credentials["model_uid"] or "?" in credentials["model_uid"] or "#" in credentials["model_uid"]: + if not validate_model_uid(credentials): raise CredentialsValidateFailedError("model_uid should not contain /, ?, or #") credentials["server_url"] = credentials["server_url"].removesuffix("/") diff --git a/api/core/model_runtime/model_providers/xinference/text_embedding/text_embedding.py b/api/core/model_runtime/model_providers/xinference/text_embedding/text_embedding.py index 1627239132..ddc21b365c 100644 --- a/api/core/model_runtime/model_providers/xinference/text_embedding/text_embedding.py +++ b/api/core/model_runtime/model_providers/xinference/text_embedding/text_embedding.py @@ -17,7 +17,7 @@ from core.model_runtime.errors.invoke import ( ) 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.xinference.xinference_helper import XinferenceHelper +from core.model_runtime.model_providers.xinference.xinference_helper import XinferenceHelper, validate_model_uid class XinferenceTextEmbeddingModel(TextEmbeddingModel): @@ -110,7 +110,7 @@ class XinferenceTextEmbeddingModel(TextEmbeddingModel): :return: """ try: - if "/" in credentials["model_uid"] or "?" in credentials["model_uid"] or "#" in credentials["model_uid"]: + if not validate_model_uid(credentials): raise CredentialsValidateFailedError("model_uid should not contain /, ?, or #") server_url = credentials["server_url"] diff --git a/api/core/model_runtime/model_providers/xinference/tts/tts.py b/api/core/model_runtime/model_providers/xinference/tts/tts.py index 81dbe397d2..6290e8551d 100644 --- a/api/core/model_runtime/model_providers/xinference/tts/tts.py +++ b/api/core/model_runtime/model_providers/xinference/tts/tts.py @@ -15,7 +15,7 @@ from core.model_runtime.errors.invoke import ( ) from core.model_runtime.errors.validate import CredentialsValidateFailedError from core.model_runtime.model_providers.__base.tts_model import TTSModel -from core.model_runtime.model_providers.xinference.xinference_helper import XinferenceHelper +from core.model_runtime.model_providers.xinference.xinference_helper import XinferenceHelper, validate_model_uid class XinferenceText2SpeechModel(TTSModel): @@ -70,7 +70,7 @@ class XinferenceText2SpeechModel(TTSModel): :return: """ try: - if "/" in credentials["model_uid"] or "?" in credentials["model_uid"] or "#" in credentials["model_uid"]: + if not validate_model_uid(credentials): raise CredentialsValidateFailedError("model_uid should not contain /, ?, or #") credentials["server_url"] = credentials["server_url"].removesuffix("/") diff --git a/api/core/model_runtime/model_providers/xinference/xinference_helper.py b/api/core/model_runtime/model_providers/xinference/xinference_helper.py index 619ee1492a..baa3ccbe8a 100644 --- a/api/core/model_runtime/model_providers/xinference/xinference_helper.py +++ b/api/core/model_runtime/model_providers/xinference/xinference_helper.py @@ -132,3 +132,16 @@ class XinferenceHelper: context_length=context_length, model_family=model_family, ) + + +def validate_model_uid(credentials: dict) -> bool: + """ + Validate the model_uid within the credentials dictionary to ensure it does not + contain forbidden characters ("/", "?", "#"). + + param credentials: model credentials + :return: True if the model_uid does not contain forbidden characters ("/", "?", "#"), else False. + """ + forbidden_characters = ["/", "?", "#"] + model_uid = credentials.get("model_uid", "") + return not any(char in forbidden_characters for char in model_uid) diff --git a/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/core/_base_models.py b/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/core/_base_models.py index 6d8ba700b7..69b1d3a83d 100644 --- a/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/core/_base_models.py +++ b/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/core/_base_models.py @@ -48,7 +48,7 @@ from ._utils import ( ) if TYPE_CHECKING: - from pydantic_core.core_schema import LiteralSchema, ModelField, ModelFieldsSchema + from pydantic_core.core_schema import ModelField __all__ = ["BaseModel", "GenericModel"] _BaseModelT = TypeVar("_BaseModelT", bound="BaseModel") diff --git a/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/core/_utils/_utils.py b/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/core/_utils/_utils.py index ce5e7786aa..3a7b234ab0 100644 --- a/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/core/_utils/_utils.py +++ b/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/core/_utils/_utils.py @@ -248,7 +248,7 @@ def required_args(*variants: Sequence[str]) -> Callable[[CallableT], CallableT]: @functools.wraps(func) def wrapper(*args: object, **kwargs: object) -> object: given_params: set[str] = set() - for i, _ in enumerate(args): + for i in range(len(args)): try: given_params.add(positional[i]) except IndexError: diff --git a/api/core/moderation/keywords/keywords.py b/api/core/moderation/keywords/keywords.py index dc6a7ec564..4846da8f93 100644 --- a/api/core/moderation/keywords/keywords.py +++ b/api/core/moderation/keywords/keywords.py @@ -18,8 +18,12 @@ class KeywordsModeration(Moderation): if not config.get("keywords"): raise ValueError("keywords is required") - if len(config.get("keywords")) > 1000: - raise ValueError("keywords length must be less than 1000") + if len(config.get("keywords")) > 10000: + raise ValueError("keywords length must be less than 10000") + + keywords_row_len = config["keywords"].split("\n") + if len(keywords_row_len) > 100: + raise ValueError("the number of rows for the keywords must be less than 100") def moderation_for_inputs(self, inputs: dict, query: str = "") -> ModerationInputsResult: flagged = False diff --git a/api/core/rag/datasource/keyword/jieba/jieba.py b/api/core/rag/datasource/keyword/jieba/jieba.py index 3073100746..a0153c1e58 100644 --- a/api/core/rag/datasource/keyword/jieba/jieba.py +++ b/api/core/rag/datasource/keyword/jieba/jieba.py @@ -45,7 +45,7 @@ class Jieba(BaseKeyword): keyword_table_handler = JiebaKeywordTableHandler() keyword_table = self._get_dataset_keyword_table() - keywords_list = kwargs.get("keywords_list", None) + keywords_list = kwargs.get("keywords_list") for i in range(len(texts)): text = texts[i] if keywords_list: diff --git a/api/core/rag/datasource/retrieval_service.py b/api/core/rag/datasource/retrieval_service.py index afac1bf300..d3fd0c672a 100644 --- a/api/core/rag/datasource/retrieval_service.py +++ b/api/core/rag/datasource/retrieval_service.py @@ -10,6 +10,7 @@ from core.rag.rerank.constants.rerank_mode import RerankMode from core.rag.retrieval.retrieval_methods import RetrievalMethod from extensions.ext_database import db from models.dataset import Dataset +from services.external_knowledge_service import ExternalDatasetService default_retrieval_model = { "search_method": RetrievalMethod.SEMANTIC_SEARCH.value, @@ -34,6 +35,9 @@ class RetrievalService: weights: Optional[dict] = None, ): dataset = db.session.query(Dataset).filter(Dataset.id == dataset_id).first() + if not dataset: + return [] + if not dataset or dataset.available_document_count == 0 or dataset.available_segment_count == 0: return [] all_documents = [] @@ -108,6 +112,16 @@ class RetrievalService: ) return all_documents + @classmethod + def external_retrieve(cls, dataset_id: str, query: str, external_retrieval_model: Optional[dict] = None): + dataset = db.session.query(Dataset).filter(Dataset.id == dataset_id).first() + if not dataset: + return [] + all_documents = ExternalDatasetService.fetch_external_knowledge_retrieval( + dataset.tenant_id, dataset_id, query, external_retrieval_model + ) + return all_documents + @classmethod def keyword_search( cls, flask_app: Flask, dataset_id: str, query: str, top_k: int, all_documents: list, exceptions: list diff --git a/api/core/rag/datasource/vdb/pgvector/pgvector.py b/api/core/rag/datasource/vdb/pgvector/pgvector.py index 79879d4f63..25a10a1e48 100644 --- a/api/core/rag/datasource/vdb/pgvector/pgvector.py +++ b/api/core/rag/datasource/vdb/pgvector/pgvector.py @@ -23,6 +23,8 @@ class PGVectorConfig(BaseModel): user: str password: str database: str + min_connection: int + max_connection: int @model_validator(mode="before") @classmethod @@ -37,6 +39,12 @@ class PGVectorConfig(BaseModel): raise ValueError("config PGVECTOR_PASSWORD is required") if not values["database"]: raise ValueError("config PGVECTOR_DATABASE is required") + if not values["min_connection"]: + raise ValueError("config PGVECTOR_MIN_CONNECTION is required") + if not values["max_connection"]: + raise ValueError("config PGVECTOR_MAX_CONNECTION is required") + if values["min_connection"] > values["max_connection"]: + raise ValueError("config PGVECTOR_MIN_CONNECTION should less than PGVECTOR_MAX_CONNECTION") return values @@ -61,8 +69,8 @@ class PGVector(BaseVector): def _create_connection_pool(self, config: PGVectorConfig): return psycopg2.pool.SimpleConnectionPool( - 1, - 5, + config.min_connection, + config.max_connection, host=config.host, port=config.port, user=config.user, @@ -158,7 +166,7 @@ class PGVector(BaseVector): with self._get_cursor() as cur: cur.execute( - f"""SELECT meta, text, ts_rank(to_tsvector(coalesce(text, '')), to_tsquery(%s)) AS score + f"""SELECT meta, text, ts_rank(to_tsvector(coalesce(text, '')), plainto_tsquery(%s)) AS score FROM {self.table_name} WHERE to_tsvector(text) @@ plainto_tsquery(%s) ORDER BY score DESC @@ -213,5 +221,7 @@ class PGVectorFactory(AbstractVectorFactory): user=dify_config.PGVECTOR_USER, password=dify_config.PGVECTOR_PASSWORD, database=dify_config.PGVECTOR_DATABASE, + min_connection=dify_config.PGVECTOR_MIN_CONNECTION, + max_connection=dify_config.PGVECTOR_MAX_CONNECTION, ), ) diff --git a/api/core/rag/datasource/vdb/tencent/tencent_vector.py b/api/core/rag/datasource/vdb/tencent/tencent_vector.py index faa373017b..39e3a7f6cf 100644 --- a/api/core/rag/datasource/vdb/tencent/tencent_vector.py +++ b/api/core/rag/datasource/vdb/tencent/tencent_vector.py @@ -56,7 +56,7 @@ class TencentVector(BaseVector): return self._client.create_database(database_name=self._client_config.database) def get_type(self) -> str: - return "tencent" + return VectorType.TENCENT def to_index_struct(self) -> dict: return {"type": self.get_type(), "vector_store": {"class_prefix": self._collection_name}} diff --git a/api/core/rag/entities/context_entities.py b/api/core/rag/entities/context_entities.py new file mode 100644 index 0000000000..dde3beccf6 --- /dev/null +++ b/api/core/rag/entities/context_entities.py @@ -0,0 +1,10 @@ +from pydantic import BaseModel + + +class DocumentContext(BaseModel): + """ + Model class for document context. + """ + + content: str + score: float diff --git a/api/core/rag/extractor/extract_processor.py b/api/core/rag/extractor/extract_processor.py index 0ffc89b214..9048138511 100644 --- a/api/core/rag/extractor/extract_processor.py +++ b/api/core/rag/extractor/extract_processor.py @@ -12,6 +12,7 @@ from core.rag.extractor.entity.extract_setting import ExtractSetting from core.rag.extractor.excel_extractor import ExcelExtractor from core.rag.extractor.firecrawl.firecrawl_web_extractor import FirecrawlWebExtractor from core.rag.extractor.html_extractor import HtmlExtractor +from core.rag.extractor.jina_reader_extractor import JinaReaderWebExtractor from core.rag.extractor.markdown_extractor import MarkdownExtractor from core.rag.extractor.notion_extractor import NotionExtractor from core.rag.extractor.pdf_extractor import PdfExtractor @@ -171,6 +172,15 @@ class ExtractProcessor: only_main_content=extract_setting.website_info.only_main_content, ) return extractor.extract() + elif extract_setting.website_info.provider == "jinareader": + extractor = JinaReaderWebExtractor( + url=extract_setting.website_info.url, + job_id=extract_setting.website_info.job_id, + tenant_id=extract_setting.website_info.tenant_id, + mode=extract_setting.website_info.mode, + only_main_content=extract_setting.website_info.only_main_content, + ) + return extractor.extract() else: raise ValueError(f"Unsupported website provider: {extract_setting.website_info.provider}") else: diff --git a/api/core/rag/extractor/jina_reader_extractor.py b/api/core/rag/extractor/jina_reader_extractor.py new file mode 100644 index 0000000000..5b780af126 --- /dev/null +++ b/api/core/rag/extractor/jina_reader_extractor.py @@ -0,0 +1,35 @@ +from core.rag.extractor.extractor_base import BaseExtractor +from core.rag.models.document import Document +from services.website_service import WebsiteService + + +class JinaReaderWebExtractor(BaseExtractor): + """ + Crawl and scrape websites and return content in clean llm-ready markdown. + """ + + def __init__(self, url: str, job_id: str, tenant_id: str, mode: str = "crawl", only_main_content: bool = False): + """Initialize with url, api_key, base_url and mode.""" + self._url = url + self.job_id = job_id + self.tenant_id = tenant_id + self.mode = mode + self.only_main_content = only_main_content + + def extract(self) -> list[Document]: + """Extract content from the URL.""" + documents = [] + if self.mode == "crawl": + crawl_data = WebsiteService.get_crawl_url_data(self.job_id, "jinareader", self._url, self.tenant_id) + if crawl_data is None: + return [] + document = Document( + page_content=crawl_data.get("content", ""), + metadata={ + "source_url": crawl_data.get("url"), + "description": crawl_data.get("description"), + "title": crawl_data.get("title"), + }, + ) + documents.append(document) + return documents diff --git a/api/core/rag/models/document.py b/api/core/rag/models/document.py index 0ff1fdb81c..1e9aaa24f0 100644 --- a/api/core/rag/models/document.py +++ b/api/core/rag/models/document.py @@ -17,6 +17,8 @@ class Document(BaseModel): """ metadata: Optional[dict] = Field(default_factory=dict) + provider: Optional[str] = "dify" + class BaseDocumentTransformer(ABC): """Abstract base class for document transformation systems. diff --git a/api/core/rag/rerank/rerank_model.py b/api/core/rag/rerank/rerank_model.py index 6356ff87ab..27f86aed34 100644 --- a/api/core/rag/rerank/rerank_model.py +++ b/api/core/rag/rerank/rerank_model.py @@ -28,11 +28,16 @@ class RerankModelRunner: docs = [] doc_id = [] unique_documents = [] - for document in documents: + dify_documents = [item for item in documents if item.provider == "dify"] + external_documents = [item for item in documents if item.provider == "external"] + for document in dify_documents: if document.metadata["doc_id"] not in doc_id: doc_id.append(document.metadata["doc_id"]) docs.append(document.page_content) unique_documents.append(document) + for document in external_documents: + docs.append(document.page_content) + unique_documents.append(document) documents = unique_documents @@ -46,14 +51,10 @@ class RerankModelRunner: # format document rerank_document = Document( page_content=result.text, - metadata={ - "doc_id": documents[result.index].metadata["doc_id"], - "doc_hash": documents[result.index].metadata["doc_hash"], - "document_id": documents[result.index].metadata["document_id"], - "dataset_id": documents[result.index].metadata["dataset_id"], - "score": result.score, - }, + metadata=documents[result.index].metadata, + provider=documents[result.index].provider, ) + rerank_document.metadata["score"] = result.score rerank_documents.append(rerank_document) return rerank_documents diff --git a/api/core/rag/retrieval/dataset_retrieval.py b/api/core/rag/retrieval/dataset_retrieval.py index 4603957d68..ae61ba7112 100644 --- a/api/core/rag/retrieval/dataset_retrieval.py +++ b/api/core/rag/retrieval/dataset_retrieval.py @@ -20,6 +20,7 @@ from core.ops.utils import measure_time from core.rag.data_post_processor.data_post_processor import DataPostProcessor from core.rag.datasource.keyword.jieba.jieba_keyword_table_handler import JiebaKeywordTableHandler from core.rag.datasource.retrieval_service import RetrievalService +from core.rag.entities.context_entities import DocumentContext from core.rag.models.document import Document from core.rag.retrieval.retrieval_methods import RetrievalMethod from core.rag.retrieval.router.multi_dataset_function_call_router import FunctionCallMultiDatasetRouter @@ -30,6 +31,7 @@ from core.tools.tool.dataset_retriever.dataset_retriever_tool import DatasetRetr from extensions.ext_database import db from models.dataset import Dataset, DatasetQuery, DocumentSegment from models.dataset import Document as DatasetDocument +from services.external_knowledge_service import ExternalDatasetService default_retrieval_model = { "search_method": RetrievalMethod.SEMANTIC_SEARCH.value, @@ -110,7 +112,7 @@ class DatasetRetrieval: continue # pass if dataset is not available - if dataset and dataset.available_document_count == 0: + if dataset and dataset.available_document_count == 0 and dataset.provider != "external": continue available_datasets.append(dataset) @@ -146,69 +148,93 @@ class DatasetRetrieval: message_id, ) - document_score_list = {} - for item in all_documents: - if item.metadata.get("score"): - document_score_list[item.metadata["doc_id"]] = item.metadata["score"] - + dify_documents = [item for item in all_documents if item.provider == "dify"] + external_documents = [item for item in all_documents if item.provider == "external"] document_context_list = [] - index_node_ids = [document.metadata["doc_id"] for document in all_documents] - segments = DocumentSegment.query.filter( - DocumentSegment.dataset_id.in_(dataset_ids), - DocumentSegment.completed_at.isnot(None), - DocumentSegment.status == "completed", - DocumentSegment.enabled == True, - DocumentSegment.index_node_id.in_(index_node_ids), - ).all() + retrieval_resource_list = [] + # deal with external documents + for item in external_documents: + document_context_list.append(DocumentContext(content=item.page_content, score=item.metadata.get("score"))) + source = { + "dataset_id": item.metadata.get("dataset_id"), + "dataset_name": item.metadata.get("dataset_name"), + "document_name": item.metadata.get("title"), + "data_source_type": "external", + "retriever_from": invoke_from.to_source(), + "score": item.metadata.get("score"), + "content": item.page_content, + } + retrieval_resource_list.append(source) + document_score_list = {} + # deal with dify documents + if dify_documents: + for item in dify_documents: + if item.metadata.get("score"): + document_score_list[item.metadata["doc_id"]] = item.metadata["score"] - if segments: - index_node_id_to_position = {id: position for position, id in enumerate(index_node_ids)} - sorted_segments = sorted( - segments, key=lambda segment: index_node_id_to_position.get(segment.index_node_id, float("inf")) - ) - for segment in sorted_segments: - if segment.answer: - document_context_list.append(f"question:{segment.get_sign_content()} answer:{segment.answer}") - else: - document_context_list.append(segment.get_sign_content()) - if show_retrieve_source: - context_list = [] - resource_number = 1 + index_node_ids = [document.metadata["doc_id"] for document in dify_documents] + segments = DocumentSegment.query.filter( + DocumentSegment.dataset_id.in_(dataset_ids), + DocumentSegment.status == "completed", + DocumentSegment.enabled == True, + DocumentSegment.index_node_id.in_(index_node_ids), + ).all() + + if segments: + index_node_id_to_position = {id: position for position, id in enumerate(index_node_ids)} + sorted_segments = sorted( + segments, key=lambda segment: index_node_id_to_position.get(segment.index_node_id, float("inf")) + ) for segment in sorted_segments: - dataset = Dataset.query.filter_by(id=segment.dataset_id).first() - document = DatasetDocument.query.filter( - DatasetDocument.id == segment.document_id, - DatasetDocument.enabled == True, - DatasetDocument.archived == False, - ).first() - if dataset and document: - source = { - "position": resource_number, - "dataset_id": dataset.id, - "dataset_name": dataset.name, - "document_id": document.id, - "document_name": document.name, - "data_source_type": document.data_source_type, - "segment_id": segment.id, - "retriever_from": invoke_from.to_source(), - "score": document_score_list.get(segment.index_node_id, None), - } + if segment.answer: + document_context_list.append( + DocumentContext( + content=f"question:{segment.get_sign_content()} answer:{segment.answer}", + score=document_score_list.get(segment.index_node_id, None), + ) + ) + else: + document_context_list.append( + DocumentContext( + content=segment.get_sign_content(), + score=document_score_list.get(segment.index_node_id, None), + ) + ) + if show_retrieve_source: + for segment in sorted_segments: + dataset = Dataset.query.filter_by(id=segment.dataset_id).first() + document = DatasetDocument.query.filter( + DatasetDocument.id == segment.document_id, + DatasetDocument.enabled == True, + DatasetDocument.archived == False, + ).first() + if dataset and document: + source = { + "dataset_id": dataset.id, + "dataset_name": dataset.name, + "document_id": document.id, + "document_name": document.name, + "data_source_type": document.data_source_type, + "segment_id": segment.id, + "retriever_from": invoke_from.to_source(), + "score": document_score_list.get(segment.index_node_id, None), + } - if invoke_from.to_source() == "dev": - source["hit_count"] = segment.hit_count - source["word_count"] = segment.word_count - source["segment_position"] = segment.position - source["index_node_hash"] = segment.index_node_hash - if segment.answer: - source["content"] = f"question:{segment.content} \nanswer:{segment.answer}" - else: - source["content"] = segment.content - context_list.append(source) - resource_number += 1 - if hit_callback: - hit_callback.return_retriever_resource_info(context_list) - - return str("\n".join(document_context_list)) + if invoke_from.to_source() == "dev": + source["hit_count"] = segment.hit_count + source["word_count"] = segment.word_count + source["segment_position"] = segment.position + source["index_node_hash"] = segment.index_node_hash + if segment.answer: + source["content"] = f"question:{segment.content} \nanswer:{segment.answer}" + else: + source["content"] = segment.content + retrieval_resource_list.append(source) + if hit_callback and retrieval_resource_list: + hit_callback.return_retriever_resource_info(retrieval_resource_list) + if document_context_list: + document_context_list = sorted(document_context_list, key=lambda x: x.score, reverse=True) + return str("\n".join([document_context.content for document_context in document_context_list])) return "" def single_retrieve( @@ -256,36 +282,58 @@ class DatasetRetrieval: # get retrieval model config dataset = db.session.query(Dataset).filter(Dataset.id == dataset_id).first() if dataset: - retrieval_model_config = dataset.retrieval_model or default_retrieval_model - - # get top k - top_k = retrieval_model_config["top_k"] - # get retrieval method - if dataset.indexing_technique == "economy": - retrieval_method = "keyword_search" - else: - retrieval_method = retrieval_model_config["search_method"] - # get reranking model - reranking_model = ( - retrieval_model_config["reranking_model"] if retrieval_model_config["reranking_enable"] else None - ) - # get score threshold - score_threshold = 0.0 - score_threshold_enabled = retrieval_model_config.get("score_threshold_enabled") - if score_threshold_enabled: - score_threshold = retrieval_model_config.get("score_threshold") - - with measure_time() as timer: - results = RetrievalService.retrieve( - retrieval_method=retrieval_method, - dataset_id=dataset.id, + results = [] + if dataset.provider == "external": + external_documents = ExternalDatasetService.fetch_external_knowledge_retrieval( + tenant_id=dataset.tenant_id, + dataset_id=dataset_id, query=query, - top_k=top_k, - score_threshold=score_threshold, - reranking_model=reranking_model, - reranking_mode=retrieval_model_config.get("reranking_mode", "reranking_model"), - weights=retrieval_model_config.get("weights", None), + external_retrieval_parameters=dataset.retrieval_model, ) + for external_document in external_documents: + document = Document( + page_content=external_document.get("content"), + metadata=external_document.get("metadata"), + provider="external", + ) + document.metadata["score"] = external_document.get("score") + document.metadata["title"] = external_document.get("title") + document.metadata["dataset_id"] = dataset_id + document.metadata["dataset_name"] = dataset.name + results.append(document) + else: + retrieval_model_config = dataset.retrieval_model or default_retrieval_model + + # get top k + top_k = retrieval_model_config["top_k"] + # get retrieval method + if dataset.indexing_technique == "economy": + retrieval_method = "keyword_search" + else: + retrieval_method = retrieval_model_config["search_method"] + # get reranking model + reranking_model = ( + retrieval_model_config["reranking_model"] + if retrieval_model_config["reranking_enable"] + else None + ) + # get score threshold + score_threshold = 0.0 + score_threshold_enabled = retrieval_model_config.get("score_threshold_enabled") + if score_threshold_enabled: + score_threshold = retrieval_model_config.get("score_threshold") + + with measure_time() as timer: + results = RetrievalService.retrieve( + retrieval_method=retrieval_method, + dataset_id=dataset.id, + query=query, + top_k=top_k, + score_threshold=score_threshold, + reranking_model=reranking_model, + reranking_mode=retrieval_model_config.get("reranking_mode", "reranking_model"), + weights=retrieval_model_config.get("weights", None), + ) self._on_query(query, [dataset_id], app_id, user_from, user_id) if results: @@ -356,7 +404,8 @@ class DatasetRetrieval: self, documents: list[Document], message_id: Optional[str] = None, timer: Optional[dict] = None ) -> None: """Handle retrieval end.""" - for document in documents: + dify_documents = [document for document in documents if document.provider == "dify"] + for document in dify_documents: query = db.session.query(DocumentSegment).filter( DocumentSegment.index_node_id == document.metadata["doc_id"] ) @@ -409,35 +458,54 @@ class DatasetRetrieval: if not dataset: return [] - # get retrieval model , if the model is not setting , using default - retrieval_model = dataset.retrieval_model or default_retrieval_model - - if dataset.indexing_technique == "economy": - # use keyword table query - documents = RetrievalService.retrieve( - retrieval_method="keyword_search", dataset_id=dataset.id, query=query, top_k=top_k + if dataset.provider == "external": + external_documents = ExternalDatasetService.fetch_external_knowledge_retrieval( + tenant_id=dataset.tenant_id, + dataset_id=dataset_id, + query=query, + external_retrieval_parameters=dataset.retrieval_model, ) - if documents: - all_documents.extend(documents) - else: - if top_k > 0: - # retrieval source - documents = RetrievalService.retrieve( - retrieval_method=retrieval_model["search_method"], - dataset_id=dataset.id, - query=query, - top_k=retrieval_model.get("top_k") or 2, - score_threshold=retrieval_model.get("score_threshold", 0.0) - if retrieval_model["score_threshold_enabled"] - else 0.0, - reranking_model=retrieval_model.get("reranking_model", None) - if retrieval_model["reranking_enable"] - else None, - reranking_mode=retrieval_model.get("reranking_mode") or "reranking_model", - weights=retrieval_model.get("weights", None), + for external_document in external_documents: + document = Document( + page_content=external_document.get("content"), + metadata=external_document.get("metadata"), + provider="external", ) + document.metadata["score"] = external_document.get("score") + document.metadata["title"] = external_document.get("title") + document.metadata["dataset_id"] = dataset_id + document.metadata["dataset_name"] = dataset.name + all_documents.append(document) + else: + # get retrieval model , if the model is not setting , using default + retrieval_model = dataset.retrieval_model or default_retrieval_model - all_documents.extend(documents) + if dataset.indexing_technique == "economy": + # use keyword table query + documents = RetrievalService.retrieve( + retrieval_method="keyword_search", dataset_id=dataset.id, query=query, top_k=top_k + ) + if documents: + all_documents.extend(documents) + else: + if top_k > 0: + # retrieval source + documents = RetrievalService.retrieve( + retrieval_method=retrieval_model["search_method"], + dataset_id=dataset.id, + query=query, + top_k=retrieval_model.get("top_k") or 2, + score_threshold=retrieval_model.get("score_threshold", 0.0) + if retrieval_model["score_threshold_enabled"] + else 0.0, + reranking_model=retrieval_model.get("reranking_model", None) + if retrieval_model["reranking_enable"] + else None, + reranking_mode=retrieval_model.get("reranking_mode") or "reranking_model", + weights=retrieval_model.get("weights", None), + ) + + all_documents.extend(documents) def to_dataset_retriever_tool( self, diff --git a/api/core/tools/provider/_position.yaml b/api/core/tools/provider/_position.yaml index 40c3356116..e0a8e7511e 100644 --- a/api/core/tools/provider/_position.yaml +++ b/api/core/tools/provider/_position.yaml @@ -34,5 +34,9 @@ - feishu_base - feishu_document - feishu_message +- feishu_wiki +- feishu_task +- feishu_calendar +- feishu_spreadsheet - slack - tianditu diff --git a/api/core/tools/provider/builtin/feishu_calendar/_assets/icon.png b/api/core/tools/provider/builtin/feishu_calendar/_assets/icon.png new file mode 100644 index 0000000000..2a934747a9 Binary files /dev/null and b/api/core/tools/provider/builtin/feishu_calendar/_assets/icon.png differ diff --git a/api/core/tools/provider/builtin/feishu_calendar/feishu_calendar.py b/api/core/tools/provider/builtin/feishu_calendar/feishu_calendar.py new file mode 100644 index 0000000000..a46a9fa9e8 --- /dev/null +++ b/api/core/tools/provider/builtin/feishu_calendar/feishu_calendar.py @@ -0,0 +1,7 @@ +from core.tools.provider.builtin_tool_provider import BuiltinToolProviderController +from core.tools.utils.feishu_api_utils import auth + + +class FeishuCalendarProvider(BuiltinToolProviderController): + def _validate_credentials(self, credentials: dict) -> None: + auth(credentials) diff --git a/api/core/tools/provider/builtin/feishu_calendar/feishu_calendar.yaml b/api/core/tools/provider/builtin/feishu_calendar/feishu_calendar.yaml new file mode 100644 index 0000000000..db5bab5c10 --- /dev/null +++ b/api/core/tools/provider/builtin/feishu_calendar/feishu_calendar.yaml @@ -0,0 +1,36 @@ +identity: + author: Doug Lea + name: feishu_calendar + label: + en_US: Feishu Calendar + zh_Hans: 飞书日历 + description: + en_US: | + Feishu calendar, requires the following permissions: calendar:calendar:read、calendar:calendar、contact:user.id:readonly. + zh_Hans: | + 飞书日历，需要开通以下权限: calendar:calendar:read、calendar:calendar、contact:user.id:readonly。 + icon: icon.png + tags: + - social + - productivity +credentials_for_provider: + app_id: + type: text-input + required: true + label: + en_US: APP ID + placeholder: + en_US: Please input your feishu app id + zh_Hans: 请输入你的飞书 app id + help: + en_US: Get your app_id and app_secret from Feishu + zh_Hans: 从飞书获取您的 app_id 和 app_secret + url: https://open.larkoffice.com/app + app_secret: + type: secret-input + required: true + label: + en_US: APP Secret + placeholder: + en_US: Please input your app secret + zh_Hans: 请输入你的飞书 app secret diff --git a/api/core/tools/provider/builtin/feishu_calendar/tools/add_event_attendees.py b/api/core/tools/provider/builtin/feishu_calendar/tools/add_event_attendees.py new file mode 100644 index 0000000000..8f83aea5ab --- /dev/null +++ b/api/core/tools/provider/builtin/feishu_calendar/tools/add_event_attendees.py @@ -0,0 +1,20 @@ +from typing import Any + +from core.tools.entities.tool_entities import ToolInvokeMessage +from core.tools.tool.builtin_tool import BuiltinTool +from core.tools.utils.feishu_api_utils import FeishuRequest + + +class AddEventAttendeesTool(BuiltinTool): + def _invoke(self, user_id: str, tool_parameters: dict[str, Any]) -> ToolInvokeMessage: + app_id = self.runtime.credentials.get("app_id") + app_secret = self.runtime.credentials.get("app_secret") + client = FeishuRequest(app_id, app_secret) + + event_id = tool_parameters.get("event_id") + attendee_phone_or_email = tool_parameters.get("attendee_phone_or_email") + need_notification = tool_parameters.get("need_notification", True) + + res = client.add_event_attendees(event_id, attendee_phone_or_email, need_notification) + + return self.create_json_message(res) diff --git a/api/core/tools/provider/builtin/feishu_calendar/tools/add_event_attendees.yaml b/api/core/tools/provider/builtin/feishu_calendar/tools/add_event_attendees.yaml new file mode 100644 index 0000000000..b7744499b0 --- /dev/null +++ b/api/core/tools/provider/builtin/feishu_calendar/tools/add_event_attendees.yaml @@ -0,0 +1,54 @@ +identity: + name: add_event_attendees + author: Doug Lea + label: + en_US: Add Event Attendees + zh_Hans: 添加日程参会人 +description: + human: + en_US: Add Event Attendees + zh_Hans: 添加日程参会人 + llm: A tool for adding attendees to events in Feishu. (在飞书中添加日程参会人) +parameters: + - name: event_id + type: string + required: true + label: + en_US: Event ID + zh_Hans: 日程 ID + human_description: + en_US: | + The ID of the event, which will be returned when the event is created. For example: fb2a6406-26d6-4c8d-a487-6f0246c94d2f_0. + zh_Hans: | + 创建日程时会返回日程 ID。例如: fb2a6406-26d6-4c8d-a487-6f0246c94d2f_0。 + llm_description: | + 日程 ID，创建日程时会返回日程 ID。例如: fb2a6406-26d6-4c8d-a487-6f0246c94d2f_0。 + form: llm + + - name: need_notification + type: boolean + required: false + default: true + label: + en_US: Need Notification + zh_Hans: 是否需要通知 + human_description: + en_US: | + Whether to send a Bot notification to attendees. true: send, false: do not send. + zh_Hans: | + 是否给参与人发送 Bot 通知，true: 发送，false: 不发送。 + llm_description: | + 是否给参与人发送 Bot 通知，true: 发送，false: 不发送。 + form: form + + - name: attendee_phone_or_email + type: string + required: true + label: + en_US: Attendee Phone or Email + zh_Hans: 参会人电话或邮箱 + human_description: + en_US: The list of attendee emails or phone numbers, separated by commas. + zh_Hans: 日程参会人邮箱或者手机号列表，使用逗号分隔。 + llm_description: 日程参会人邮箱或者手机号列表，使用逗号分隔。 + form: llm diff --git a/api/core/tools/provider/builtin/feishu_calendar/tools/create_event.py b/api/core/tools/provider/builtin/feishu_calendar/tools/create_event.py new file mode 100644 index 0000000000..8820bebdbe --- /dev/null +++ b/api/core/tools/provider/builtin/feishu_calendar/tools/create_event.py @@ -0,0 +1,26 @@ +from typing import Any + +from core.tools.entities.tool_entities import ToolInvokeMessage +from core.tools.tool.builtin_tool import BuiltinTool +from core.tools.utils.feishu_api_utils import FeishuRequest + + +class CreateEventTool(BuiltinTool): + def _invoke(self, user_id: str, tool_parameters: dict[str, Any]) -> ToolInvokeMessage: + app_id = self.runtime.credentials.get("app_id") + app_secret = self.runtime.credentials.get("app_secret") + client = FeishuRequest(app_id, app_secret) + + summary = tool_parameters.get("summary") + description = tool_parameters.get("description") + start_time = tool_parameters.get("start_time") + end_time = tool_parameters.get("end_time") + attendee_ability = tool_parameters.get("attendee_ability") + need_notification = tool_parameters.get("need_notification", True) + auto_record = tool_parameters.get("auto_record", False) + + res = client.create_event( + summary, description, start_time, end_time, attendee_ability, need_notification, auto_record + ) + + return self.create_json_message(res) diff --git a/api/core/tools/provider/builtin/feishu_calendar/tools/create_event.yaml b/api/core/tools/provider/builtin/feishu_calendar/tools/create_event.yaml new file mode 100644 index 0000000000..f0784221ce --- /dev/null +++ b/api/core/tools/provider/builtin/feishu_calendar/tools/create_event.yaml @@ -0,0 +1,119 @@ +identity: + name: create_event + author: Doug Lea + label: + en_US: Create Event + zh_Hans: 创建日程 +description: + human: + en_US: Create Event + zh_Hans: 创建日程 + llm: A tool for creating events in Feishu.(创建飞书日程) +parameters: + - name: summary + type: string + required: false + label: + en_US: Summary + zh_Hans: 日程标题 + human_description: + en_US: The title of the event. If not filled, the event title will display (No Subject). + zh_Hans: 日程标题，若不填则日程标题显示 (无主题)。 + llm_description: 日程标题，若不填则日程标题显示 (无主题)。 + form: llm + + - name: description + type: string + required: false + label: + en_US: Description + zh_Hans: 日程描述 + human_description: + en_US: The description of the event. + zh_Hans: 日程描述。 + llm_description: 日程描述。 + form: llm + + - name: need_notification + type: boolean + required: false + default: true + label: + en_US: Need Notification + zh_Hans: 是否发送通知 + human_description: + en_US: | + Whether to send a bot message when the event is created, true: send, false: do not send. + zh_Hans: 创建日程时是否发送 bot 消息，true：发送，false：不发送。 + llm_description: 创建日程时是否发送 bot 消息，true：发送，false：不发送。 + form: form + + - name: start_time + type: string + required: true + label: + en_US: Start Time + zh_Hans: 开始时间 + human_description: + en_US: | + The start time of the event, format: 2006-01-02 15:04:05. + zh_Hans: 日程开始时间，格式：2006-01-02 15:04:05。 + llm_description: 日程开始时间，格式：2006-01-02 15:04:05。 + form: llm + + - name: end_time + type: string + required: true + label: + en_US: End Time + zh_Hans: 结束时间 + human_description: + en_US: | + The end time of the event, format: 2006-01-02 15:04:05. + zh_Hans: 日程结束时间，格式：2006-01-02 15:04:05。 + llm_description: 日程结束时间，格式：2006-01-02 15:04:05。 + form: llm + + - name: attendee_ability + type: select + required: false + options: + - value: none + label: + en_US: none + zh_Hans: 无 + - value: can_see_others + label: + en_US: can_see_others + zh_Hans: 可以查看参与人列表 + - value: can_invite_others + label: + en_US: can_invite_others + zh_Hans: 可以邀请其它参与人 + - value: can_modify_event + label: + en_US: can_modify_event + zh_Hans: 可以编辑日程 + default: "none" + label: + en_US: attendee_ability + zh_Hans: 参会人权限 + human_description: + en_US: Attendee ability, optional values are none, can_see_others, can_invite_others, can_modify_event, with a default value of none. + zh_Hans: 参会人权限，可选值有无、可以查看参与人列表、可以邀请其它参与人、可以编辑日程，默认值为无。 + llm_description: 参会人权限，可选值有无、可以查看参与人列表、可以邀请其它参与人、可以编辑日程，默认值为无。 + form: form + + - name: auto_record + type: boolean + required: false + default: false + label: + en_US: Auto Record + zh_Hans: 自动录制 + human_description: + en_US: | + Whether to enable automatic recording, true: enabled, automatically record when the meeting starts; false: not enabled. + zh_Hans: 是否开启自动录制，true：开启，会议开始后自动录制；false：不开启。 + llm_description: 是否开启自动录制，true：开启，会议开始后自动录制；false：不开启。 + form: form diff --git a/api/core/tools/provider/builtin/feishu_calendar/tools/delete_event.py b/api/core/tools/provider/builtin/feishu_calendar/tools/delete_event.py new file mode 100644 index 0000000000..144889692f --- /dev/null +++ b/api/core/tools/provider/builtin/feishu_calendar/tools/delete_event.py @@ -0,0 +1,19 @@ +from typing import Any + +from core.tools.entities.tool_entities import ToolInvokeMessage +from core.tools.tool.builtin_tool import BuiltinTool +from core.tools.utils.feishu_api_utils import FeishuRequest + + +class DeleteEventTool(BuiltinTool): + def _invoke(self, user_id: str, tool_parameters: dict[str, Any]) -> ToolInvokeMessage: + app_id = self.runtime.credentials.get("app_id") + app_secret = self.runtime.credentials.get("app_secret") + client = FeishuRequest(app_id, app_secret) + + event_id = tool_parameters.get("event_id") + need_notification = tool_parameters.get("need_notification", True) + + res = client.delete_event(event_id, need_notification) + + return self.create_json_message(res) diff --git a/api/core/tools/provider/builtin/feishu_calendar/tools/delete_event.yaml b/api/core/tools/provider/builtin/feishu_calendar/tools/delete_event.yaml new file mode 100644 index 0000000000..54fdb04acc --- /dev/null +++ b/api/core/tools/provider/builtin/feishu_calendar/tools/delete_event.yaml @@ -0,0 +1,38 @@ +identity: + name: delete_event + author: Doug Lea + label: + en_US: Delete Event + zh_Hans: 删除日程 +description: + human: + en_US: Delete Event + zh_Hans: 删除日程 + llm: A tool for deleting events in Feishu.(在飞书中删除日程) +parameters: + - name: event_id + type: string + required: true + label: + en_US: Event ID + zh_Hans: 日程 ID + human_description: + en_US: | + The ID of the event, for example: e8b9791c-39ae-4908-8ad8-66b13159b9fb_0. + zh_Hans: 日程 ID，例如：e8b9791c-39ae-4908-8ad8-66b13159b9fb_0。 + llm_description: 日程 ID，例如：e8b9791c-39ae-4908-8ad8-66b13159b9fb_0。 + form: llm + + - name: need_notification + type: boolean + required: false + default: true + label: + en_US: Need Notification + zh_Hans: 是否需要通知 + human_description: + en_US: | + Indicates whether to send bot notifications to event participants upon deletion. true: send, false: do not send. + zh_Hans: 删除日程是否给日程参与人发送 bot 通知，true：发送，false：不发送。 + llm_description: 删除日程是否给日程参与人发送 bot 通知，true：发送，false：不发送。 + form: form diff --git a/api/core/tools/provider/builtin/feishu_calendar/tools/get_primary_calendar.py b/api/core/tools/provider/builtin/feishu_calendar/tools/get_primary_calendar.py new file mode 100644 index 0000000000..a2cd5a8b17 --- /dev/null +++ b/api/core/tools/provider/builtin/feishu_calendar/tools/get_primary_calendar.py @@ -0,0 +1,18 @@ +from typing import Any + +from core.tools.entities.tool_entities import ToolInvokeMessage +from core.tools.tool.builtin_tool import BuiltinTool +from core.tools.utils.feishu_api_utils import FeishuRequest + + +class GetPrimaryCalendarTool(BuiltinTool): + def _invoke(self, user_id: str, tool_parameters: dict[str, Any]) -> ToolInvokeMessage: + app_id = self.runtime.credentials.get("app_id") + app_secret = self.runtime.credentials.get("app_secret") + client = FeishuRequest(app_id, app_secret) + + user_id_type = tool_parameters.get("user_id_type", "open_id") + + res = client.get_primary_calendar(user_id_type) + + return self.create_json_message(res) diff --git a/api/core/tools/provider/builtin/feishu_calendar/tools/get_primary_calendar.yaml b/api/core/tools/provider/builtin/feishu_calendar/tools/get_primary_calendar.yaml new file mode 100644 index 0000000000..3440c85d4a --- /dev/null +++ b/api/core/tools/provider/builtin/feishu_calendar/tools/get_primary_calendar.yaml @@ -0,0 +1,37 @@ +identity: + name: get_primary_calendar + author: Doug Lea + label: + en_US: Get Primary Calendar + zh_Hans: 查询主日历信息 +description: + human: + en_US: Get Primary Calendar + zh_Hans: 查询主日历信息 + llm: A tool for querying primary calendar information in Feishu.(在飞书中查询主日历信息) +parameters: + - name: user_id_type + type: select + required: false + options: + - value: open_id + label: + en_US: open_id + zh_Hans: open_id + - value: union_id + label: + en_US: union_id + zh_Hans: union_id + - value: user_id + label: + en_US: user_id + zh_Hans: user_id + default: "open_id" + label: + en_US: user_id_type + zh_Hans: 用户 ID 类型 + human_description: + en_US: User ID type, optional values are open_id, union_id, user_id, with a default value of open_id. + zh_Hans: 用户 ID 类型，可选值有 open_id、union_id、user_id，默认值为 open_id。 + llm_description: 用户 ID 类型，可选值有 open_id、union_id、user_id，默认值为 open_id。 + form: form diff --git a/api/core/tools/provider/builtin/feishu_calendar/tools/list_events.py b/api/core/tools/provider/builtin/feishu_calendar/tools/list_events.py new file mode 100644 index 0000000000..8815b4c9c8 --- /dev/null +++ b/api/core/tools/provider/builtin/feishu_calendar/tools/list_events.py @@ -0,0 +1,21 @@ +from typing import Any + +from core.tools.entities.tool_entities import ToolInvokeMessage +from core.tools.tool.builtin_tool import BuiltinTool +from core.tools.utils.feishu_api_utils import FeishuRequest + + +class ListEventsTool(BuiltinTool): + def _invoke(self, user_id: str, tool_parameters: dict[str, Any]) -> ToolInvokeMessage: + app_id = self.runtime.credentials.get("app_id") + app_secret = self.runtime.credentials.get("app_secret") + client = FeishuRequest(app_id, app_secret) + + start_time = tool_parameters.get("start_time") + end_time = tool_parameters.get("end_time") + page_token = tool_parameters.get("page_token") + page_size = tool_parameters.get("page_size") + + res = client.list_events(start_time, end_time, page_token, page_size) + + return self.create_json_message(res) diff --git a/api/core/tools/provider/builtin/feishu_calendar/tools/list_events.yaml b/api/core/tools/provider/builtin/feishu_calendar/tools/list_events.yaml new file mode 100644 index 0000000000..f4a5bfe6ba --- /dev/null +++ b/api/core/tools/provider/builtin/feishu_calendar/tools/list_events.yaml @@ -0,0 +1,62 @@ +identity: + name: list_events + author: Doug Lea + label: + en_US: List Events + zh_Hans: 获取日程列表 +description: + human: + en_US: List Events + zh_Hans: 获取日程列表 + llm: A tool for listing events in Feishu.(在飞书中获取日程列表) +parameters: + - name: start_time + type: string + required: false + label: + en_US: Start Time + zh_Hans: 开始时间 + human_description: + en_US: | + The start time, defaults to 0:00 of the current day if not provided, format: 2006-01-02 15:04:05. + zh_Hans: 开始时间，不传值时默认当天 0 点时间，格式为:2006-01-02 15:04:05。 + llm_description: 开始时间，不传值时默认当天 0 点时间，格式为:2006-01-02 15:04:05。 + form: llm + + - name: end_time + type: string + required: false + label: + en_US: End Time + zh_Hans: 结束时间 + human_description: + en_US: | + The end time, defaults to 23:59 of the current day if not provided, format: 2006-01-02 15:04:05. + zh_Hans: 结束时间，不传值时默认当天 23:59 分时间，格式为:2006-01-02 15:04:05。 + llm_description: 结束时间，不传值时默认当天 23:59 分时间，格式为:2006-01-02 15:04:05。 + form: llm + + - name: page_size + type: number + required: false + default: 50 + label: + en_US: Page Size + zh_Hans: 分页大小 + human_description: + en_US: The page size, i.e., the number of data entries returned in a single request. The default value is 50, and the value range is [50,1000]. + zh_Hans: 分页大小，即单次请求所返回的数据条目数。默认值为 50，取值范围为 [50,1000]。 + llm_description: 分页大小，即单次请求所返回的数据条目数。默认值为 50，取值范围为 [50,1000]。 + form: llm + + - name: page_token + type: string + required: false + label: + en_US: Page Token + zh_Hans: 分页标记 + human_description: + en_US: The pagination token. Leave it blank for the first request, indicating to start traversing from the beginning; when the pagination query result has more items, a new page_token will be returned simultaneously, which can be used to obtain the query result in the next traversal. + zh_Hans: 分页标记，第一次请求不填，表示从头开始遍历；分页查询结果还有更多项时会同时返回新的 page_token，下次遍历可采用该 page_token 获取查询结果。 + llm_description: 分页标记，第一次请求不填，表示从头开始遍历；分页查询结果还有更多项时会同时返回新的 page_token，下次遍历可采用该 page_token 获取查询结果。 + form: llm diff --git a/api/core/tools/provider/builtin/feishu_calendar/tools/search_events.py b/api/core/tools/provider/builtin/feishu_calendar/tools/search_events.py new file mode 100644 index 0000000000..dc365205a4 --- /dev/null +++ b/api/core/tools/provider/builtin/feishu_calendar/tools/search_events.py @@ -0,0 +1,23 @@ +from typing import Any + +from core.tools.entities.tool_entities import ToolInvokeMessage +from core.tools.tool.builtin_tool import BuiltinTool +from core.tools.utils.feishu_api_utils import FeishuRequest + + +class SearchEventsTool(BuiltinTool): + def _invoke(self, user_id: str, tool_parameters: dict[str, Any]) -> ToolInvokeMessage: + app_id = self.runtime.credentials.get("app_id") + app_secret = self.runtime.credentials.get("app_secret") + client = FeishuRequest(app_id, app_secret) + + query = tool_parameters.get("query") + start_time = tool_parameters.get("start_time") + end_time = tool_parameters.get("end_time") + page_token = tool_parameters.get("page_token") + user_id_type = tool_parameters.get("user_id_type", "open_id") + page_size = tool_parameters.get("page_size", 20) + + res = client.search_events(query, start_time, end_time, page_token, user_id_type, page_size) + + return self.create_json_message(res) diff --git a/api/core/tools/provider/builtin/feishu_calendar/tools/search_events.yaml b/api/core/tools/provider/builtin/feishu_calendar/tools/search_events.yaml new file mode 100644 index 0000000000..e92a282091 --- /dev/null +++ b/api/core/tools/provider/builtin/feishu_calendar/tools/search_events.yaml @@ -0,0 +1,100 @@ +identity: + name: search_events + author: Doug Lea + label: + en_US: Search Events + zh_Hans: 搜索日程 +description: + human: + en_US: Search Events + zh_Hans: 搜索日程 + llm: A tool for searching events in Feishu.(在飞书中搜索日程) +parameters: + - name: user_id_type + type: select + required: false + options: + - value: open_id + label: + en_US: open_id + zh_Hans: open_id + - value: union_id + label: + en_US: union_id + zh_Hans: union_id + - value: user_id + label: + en_US: user_id + zh_Hans: user_id + default: "open_id" + label: + en_US: user_id_type + zh_Hans: 用户 ID 类型 + human_description: + en_US: User ID type, optional values are open_id, union_id, user_id, with a default value of open_id. + zh_Hans: 用户 ID 类型，可选值有 open_id、union_id、user_id，默认值为 open_id。 + llm_description: 用户 ID 类型，可选值有 open_id、union_id、user_id，默认值为 open_id。 + form: form + + - name: query + type: string + required: true + label: + en_US: Query + zh_Hans: 搜索关键字 + human_description: + en_US: The search keyword used for fuzzy searching event names, with a maximum input of 200 characters. + zh_Hans: 用于模糊查询日程名称的搜索关键字，最大输入 200 字符。 + llm_description: 用于模糊查询日程名称的搜索关键字，最大输入 200 字符。 + form: llm + + - name: start_time + type: string + required: false + label: + en_US: Start Time + zh_Hans: 开始时间 + human_description: + en_US: | + The start time, defaults to 0:00 of the current day if not provided, format: 2006-01-02 15:04:05. + zh_Hans: 开始时间，不传值时默认当天 0 点时间，格式为:2006-01-02 15:04:05。 + llm_description: 开始时间，不传值时默认当天 0 点时间，格式为:2006-01-02 15:04:05。 + form: llm + + - name: end_time + type: string + required: false + label: + en_US: End Time + zh_Hans: 结束时间 + human_description: + en_US: | + The end time, defaults to 23:59 of the current day if not provided, format: 2006-01-02 15:04:05. + zh_Hans: 结束时间，不传值时默认当天 23:59 分时间，格式为:2006-01-02 15:04:05。 + llm_description: 结束时间，不传值时默认当天 23:59 分时间，格式为:2006-01-02 15:04:05。 + form: llm + + - name: page_size + type: number + required: false + default: 20 + label: + en_US: Page Size + zh_Hans: 分页大小 + human_description: + en_US: The page size, i.e., the number of data entries returned in a single request. The default value is 20, and the value range is [10,100]. + zh_Hans: 分页大小，即单次请求所返回的数据条目数。默认值为 20，取值范围为 [10,100]。 + llm_description: 分页大小，即单次请求所返回的数据条目数。默认值为 20，取值范围为 [10,100]。 + form: llm + + - name: page_token + type: string + required: false + label: + en_US: Page Token + zh_Hans: 分页标记 + human_description: + en_US: The pagination token. Leave it blank for the first request, indicating to start traversing from the beginning; when the pagination query result has more items, a new page_token will be returned simultaneously, which can be used to obtain the query result in the next traversal. + zh_Hans: 分页标记，第一次请求不填，表示从头开始遍历；分页查询结果还有更多项时会同时返回新的 page_token，下次遍历可采用该 page_token 获取查询结果。 + llm_description: 分页标记，第一次请求不填，表示从头开始遍历；分页查询结果还有更多项时会同时返回新的 page_token，下次遍历可采用该 page_token 获取查询结果。 + form: llm diff --git a/api/core/tools/provider/builtin/feishu_calendar/tools/update_event.py b/api/core/tools/provider/builtin/feishu_calendar/tools/update_event.py new file mode 100644 index 0000000000..85bcb1d3f6 --- /dev/null +++ b/api/core/tools/provider/builtin/feishu_calendar/tools/update_event.py @@ -0,0 +1,24 @@ +from typing import Any + +from core.tools.entities.tool_entities import ToolInvokeMessage +from core.tools.tool.builtin_tool import BuiltinTool +from core.tools.utils.feishu_api_utils import FeishuRequest + + +class UpdateEventTool(BuiltinTool): + def _invoke(self, user_id: str, tool_parameters: dict[str, Any]) -> ToolInvokeMessage: + app_id = self.runtime.credentials.get("app_id") + app_secret = self.runtime.credentials.get("app_secret") + client = FeishuRequest(app_id, app_secret) + + event_id = tool_parameters.get("event_id") + summary = tool_parameters.get("summary") + description = tool_parameters.get("description") + need_notification = tool_parameters.get("need_notification", True) + start_time = tool_parameters.get("start_time") + end_time = tool_parameters.get("end_time") + auto_record = tool_parameters.get("auto_record", False) + + res = client.update_event(event_id, summary, description, need_notification, start_time, end_time, auto_record) + + return self.create_json_message(res) diff --git a/api/core/tools/provider/builtin/feishu_calendar/tools/update_event.yaml b/api/core/tools/provider/builtin/feishu_calendar/tools/update_event.yaml new file mode 100644 index 0000000000..4d60dbf8c8 --- /dev/null +++ b/api/core/tools/provider/builtin/feishu_calendar/tools/update_event.yaml @@ -0,0 +1,100 @@ +identity: + name: update_event + author: Doug Lea + label: + en_US: Update Event + zh_Hans: 更新日程 +description: + human: + en_US: Update Event + zh_Hans: 更新日程 + llm: A tool for updating events in Feishu.(更新飞书中的日程) +parameters: + - name: event_id + type: string + required: true + label: + en_US: Event ID + zh_Hans: 日程 ID + human_description: + en_US: | + The ID of the event, for example: e8b9791c-39ae-4908-8ad8-66b13159b9fb_0. + zh_Hans: 日程 ID，例如：e8b9791c-39ae-4908-8ad8-66b13159b9fb_0。 + llm_description: 日程 ID，例如：e8b9791c-39ae-4908-8ad8-66b13159b9fb_0。 + form: llm + + - name: summary + type: string + required: false + label: + en_US: Summary + zh_Hans: 日程标题 + human_description: + en_US: The title of the event. + zh_Hans: 日程标题。 + llm_description: 日程标题。 + form: llm + + - name: description + type: string + required: false + label: + en_US: Description + zh_Hans: 日程描述 + human_description: + en_US: The description of the event. + zh_Hans: 日程描述。 + llm_description: 日程描述。 + form: llm + + - name: need_notification + type: boolean + required: false + label: + en_US: Need Notification + zh_Hans: 是否发送通知 + human_description: + en_US: | + Whether to send a bot message when the event is updated, true: send, false: do not send. + zh_Hans: 更新日程时是否发送 bot 消息，true：发送，false：不发送。 + llm_description: 更新日程时是否发送 bot 消息，true：发送，false：不发送。 + form: form + + - name: start_time + type: string + required: false + label: + en_US: Start Time + zh_Hans: 开始时间 + human_description: + en_US: | + The start time of the event, format: 2006-01-02 15:04:05. + zh_Hans: 日程开始时间，格式：2006-01-02 15:04:05。 + llm_description: 日程开始时间，格式：2006-01-02 15:04:05。 + form: llm + + - name: end_time + type: string + required: false + label: + en_US: End Time + zh_Hans: 结束时间 + human_description: + en_US: | + The end time of the event, format: 2006-01-02 15:04:05. + zh_Hans: 日程结束时间，格式：2006-01-02 15:04:05。 + llm_description: 日程结束时间，格式：2006-01-02 15:04:05。 + form: llm + + - name: auto_record + type: boolean + required: false + label: + en_US: Auto Record + zh_Hans: 自动录制 + human_description: + en_US: | + Whether to enable automatic recording, true: enabled, automatically record when the meeting starts; false: not enabled. + zh_Hans: 是否开启自动录制，true：开启，会议开始后自动录制；false：不开启。 + llm_description: 是否开启自动录制，true：开启，会议开始后自动录制；false：不开启。 + form: form diff --git a/api/core/tools/provider/builtin/feishu_document/feishu_document.py b/api/core/tools/provider/builtin/feishu_document/feishu_document.py index b0a1e393eb..217ae52082 100644 --- a/api/core/tools/provider/builtin/feishu_document/feishu_document.py +++ b/api/core/tools/provider/builtin/feishu_document/feishu_document.py @@ -1,15 +1,7 @@ -from core.tools.errors import ToolProviderCredentialValidationError from core.tools.provider.builtin_tool_provider import BuiltinToolProviderController -from core.tools.utils.feishu_api_utils import FeishuRequest +from core.tools.utils.feishu_api_utils import auth class FeishuDocumentProvider(BuiltinToolProviderController): def _validate_credentials(self, credentials: dict) -> None: - app_id = credentials.get("app_id") - app_secret = credentials.get("app_secret") - if not app_id or not app_secret: - raise ToolProviderCredentialValidationError("app_id and app_secret is required") - try: - assert FeishuRequest(app_id, app_secret).tenant_access_token is not None - except Exception as e: - raise ToolProviderCredentialValidationError(str(e)) + auth(credentials) diff --git a/api/core/tools/provider/builtin/feishu_document/feishu_document.yaml b/api/core/tools/provider/builtin/feishu_document/feishu_document.yaml index 8eaa6b2704..8f9afa6149 100644 --- a/api/core/tools/provider/builtin/feishu_document/feishu_document.yaml +++ b/api/core/tools/provider/builtin/feishu_document/feishu_document.yaml @@ -5,8 +5,10 @@ identity: en_US: Lark Cloud Document zh_Hans: 飞书云文档 description: - en_US: Lark Cloud Document - zh_Hans: 飞书云文档 + en_US: | + Lark cloud document, requires the following permissions: docx:document、drive:drive、docs:document.content:read. + zh_Hans: | + 飞书云文档，需要开通以下权限: docx:document、drive:drive、docs:document.content:read。 icon: icon.svg tags: - social @@ -23,7 +25,7 @@ credentials_for_provider: help: en_US: Get your app_id and app_secret from Feishu zh_Hans: 从飞书获取您的 app_id 和 app_secret - url: https://open.feishu.cn + url: https://open.larkoffice.com/app app_secret: type: secret-input required: true diff --git a/api/core/tools/provider/builtin/feishu_document/tools/create_document.yaml b/api/core/tools/provider/builtin/feishu_document/tools/create_document.yaml index ddf2729f0e..85382e9d8e 100644 --- a/api/core/tools/provider/builtin/feishu_document/tools/create_document.yaml +++ b/api/core/tools/provider/builtin/feishu_document/tools/create_document.yaml @@ -7,7 +7,7 @@ identity: description: human: en_US: Create Lark document - zh_Hans: 创建飞书文档，支持创建空文档和带内容的文档，支持 markdown 语法创建。 + zh_Hans: 创建飞书文档，支持创建空文档和带内容的文档，支持 markdown 语法创建。应用需要开启机器人能力(https://open.feishu.cn/document/faq/trouble-shooting/how-to-enable-bot-ability)。 llm: A tool for creating Feishu documents. parameters: - name: title @@ -41,7 +41,8 @@ parameters: en_US: folder_token zh_Hans: 文档所在文件夹的 Token human_description: - en_US: The token of the folder where the document is located. If it is not passed or is empty, it means the root directory. - zh_Hans: 文档所在文件夹的 Token，不传或传空表示根目录。 - llm_description: 文档所在文件夹的 Token，不传或传空表示根目录。 + en_US: | + The token of the folder where the document is located. If it is not passed or is empty, it means the root directory. For Example: https://svi136aogf123.feishu.cn/drive/folder/JgR9fiG9AlPt8EdsSNpcGjIInbf + zh_Hans: 文档所在文件夹的 Token，不传或传空表示根目录。例如：https://svi136aogf123.feishu.cn/drive/folder/JgR9fiG9AlPt8EdsSNpcGjIInbf。 + llm_description: 文档所在文件夹的 Token，不传或传空表示根目录。例如：https://svi136aogf123.feishu.cn/drive/folder/JgR9fiG9AlPt8EdsSNpcGjIInbf。 form: llm diff --git a/api/core/tools/provider/builtin/feishu_document/tools/get_document_content.py b/api/core/tools/provider/builtin/feishu_document/tools/get_document_content.py index c94a5f70ed..e67a017fac 100644 --- a/api/core/tools/provider/builtin/feishu_document/tools/get_document_content.py +++ b/api/core/tools/provider/builtin/feishu_document/tools/get_document_content.py @@ -12,8 +12,8 @@ class GetDocumentRawContentTool(BuiltinTool): client = FeishuRequest(app_id, app_secret) document_id = tool_parameters.get("document_id") - mode = tool_parameters.get("mode") - lang = tool_parameters.get("lang", 0) + mode = tool_parameters.get("mode", "markdown") + lang = tool_parameters.get("lang", "0") res = client.get_document_content(document_id, mode, lang) return self.create_json_message(res) diff --git a/api/core/tools/provider/builtin/feishu_document/tools/get_document_content.yaml b/api/core/tools/provider/builtin/feishu_document/tools/get_document_content.yaml index 51eda73a60..15e827cde9 100644 --- a/api/core/tools/provider/builtin/feishu_document/tools/get_document_content.yaml +++ b/api/core/tools/provider/builtin/feishu_document/tools/get_document_content.yaml @@ -23,8 +23,18 @@ parameters: form: llm - name: mode - type: string + type: select required: false + options: + - value: text + label: + en_US: text + zh_Hans: text + - value: markdown + label: + en_US: markdown + zh_Hans: markdown + default: "markdown" label: en_US: mode zh_Hans: 文档返回格式 @@ -32,18 +42,29 @@ parameters: en_US: Format of the document return, optional values are text, markdown, can be empty, default is markdown. zh_Hans: 文档返回格式，可选值有 text、markdown，可以为空，默认值为 markdown。 llm_description: 文档返回格式，可选值有 text、markdown，可以为空，默认值为 markdown。 - form: llm + form: form - name: lang - type: number + type: select required: false - default: 0 + options: + - value: "0" + label: + en_US: User's default name + zh_Hans: 用户的默认名称 + - value: "1" + label: + en_US: User's English name + zh_Hans: 用户的英文名称 + default: "0" label: en_US: lang zh_Hans: 指定@用户的语言 human_description: en_US: | Specifies the language for MentionUser, optional values are [0, 1]. 0: User's default name, 1: User's English name, default is 0. - zh_Hans: 指定返回的 MentionUser，即 @用户 的语言，可选值有 [0,1]。0：该用户的默认名称，1：该用户的英文名称，默认值为 0。 - llm_description: 指定返回的 MentionUser，即 @用户 的语言，可选值有 [0,1]。0：该用户的默认名称，1：该用户的英文名称，默认值为 0。 - form: llm + zh_Hans: | + 指定返回的 MentionUser，即@用户的语言，可选值有 [0,1]。0: 该用户的默认名称，1: 该用户的英文名称，默认值为 0。 + llm_description: | + 指定返回的 MentionUser，即@用户的语言，可选值有 [0,1]。0: 该用户的默认名称，1: 该用户的英文名称，默认值为 0。 + form: form diff --git a/api/core/tools/provider/builtin/feishu_document/tools/list_document_blocks.py b/api/core/tools/provider/builtin/feishu_document/tools/list_document_blocks.py index 572a7abf28..dd57c6870d 100644 --- a/api/core/tools/provider/builtin/feishu_document/tools/list_document_blocks.py +++ b/api/core/tools/provider/builtin/feishu_document/tools/list_document_blocks.py @@ -12,8 +12,9 @@ class ListDocumentBlockTool(BuiltinTool): client = FeishuRequest(app_id, app_secret) document_id = tool_parameters.get("document_id") - page_size = tool_parameters.get("page_size", 500) page_token = tool_parameters.get("page_token", "") + user_id_type = tool_parameters.get("user_id_type", "open_id") + page_size = tool_parameters.get("page_size", 500) - res = client.list_document_blocks(document_id, page_token, page_size) + res = client.list_document_blocks(document_id, page_token, user_id_type, page_size) return self.create_json_message(res) diff --git a/api/core/tools/provider/builtin/feishu_document/tools/list_document_blocks.yaml b/api/core/tools/provider/builtin/feishu_document/tools/list_document_blocks.yaml index 019ac98390..5b8ef7d53c 100644 --- a/api/core/tools/provider/builtin/feishu_document/tools/list_document_blocks.yaml +++ b/api/core/tools/provider/builtin/feishu_document/tools/list_document_blocks.yaml @@ -46,12 +46,12 @@ parameters: en_US: User ID type, optional values are open_id, union_id, user_id, with a default value of open_id. zh_Hans: 用户 ID 类型，可选值有 open_id、union_id、user_id，默认值为 open_id。 llm_description: 用户 ID 类型，可选值有 open_id、union_id、user_id，默认值为 open_id。 - form: llm + form: form - name: page_size type: number required: false - default: "500" + default: 500 label: en_US: page_size zh_Hans: 分页大小 diff --git a/api/core/tools/provider/builtin/feishu_document/tools/write_document.py b/api/core/tools/provider/builtin/feishu_document/tools/write_document.py index 6061250e48..59f08f53dc 100644 --- a/api/core/tools/provider/builtin/feishu_document/tools/write_document.py +++ b/api/core/tools/provider/builtin/feishu_document/tools/write_document.py @@ -13,7 +13,7 @@ class CreateDocumentTool(BuiltinTool): document_id = tool_parameters.get("document_id") content = tool_parameters.get("content") - position = tool_parameters.get("position") + position = tool_parameters.get("position", "end") res = client.write_document(document_id, content, position) return self.create_json_message(res) diff --git a/api/core/tools/provider/builtin/feishu_document/tools/write_document.yaml b/api/core/tools/provider/builtin/feishu_document/tools/write_document.yaml index 4282e3dcf3..de70f4e772 100644 --- a/api/core/tools/provider/builtin/feishu_document/tools/write_document.yaml +++ b/api/core/tools/provider/builtin/feishu_document/tools/write_document.yaml @@ -35,25 +35,23 @@ parameters: form: llm - name: position - type: string + type: select required: false - label: - en_US: position - zh_Hans: 添加位置 - human_description: - en_US: | - Enumeration values: start or end. Use 'start' to add content at the beginning of the document, and 'end' to add content at the end. The default value is 'end'. - zh_Hans: 枚举值：start 或 end。使用 'start' 在文档开头添加内容，使用 'end' 在文档结尾添加内容，默认值为 'end'。 - llm_description: | - 枚举值 start、end，start: 在文档开头添加内容；end: 在文档结尾添加内容，默认值为 end。 - form: llm options: - value: start label: - en_US: start - zh_Hans: 在文档开头添加内容 + en_US: document start + zh_Hans: 文档开始 - value: end label: - en_US: end - zh_Hans: 在文档结尾添加内容 - default: start + en_US: document end + zh_Hans: 文档结束 + default: "end" + label: + en_US: position + zh_Hans: 内容添加位置 + human_description: + en_US: Content insertion position, optional values are start, end. 'start' means adding content at the beginning of the document; 'end' means adding content at the end of the document. The default value is end. + zh_Hans: 内容添加位置，可选值有 start、end。start 表示在文档开头添加内容；end 表示在文档结尾添加内容，默认值为 end。 + llm_description: 内容添加位置，可选值有 start、end。start 表示在文档开头添加内容；end 表示在文档结尾添加内容，默认值为 end。 + form: form diff --git a/api/core/tools/provider/builtin/feishu_message/feishu_message.py b/api/core/tools/provider/builtin/feishu_message/feishu_message.py index 7b3adb9293..a3b5473769 100644 --- a/api/core/tools/provider/builtin/feishu_message/feishu_message.py +++ b/api/core/tools/provider/builtin/feishu_message/feishu_message.py @@ -1,15 +1,7 @@ -from core.tools.errors import ToolProviderCredentialValidationError from core.tools.provider.builtin_tool_provider import BuiltinToolProviderController -from core.tools.utils.feishu_api_utils import FeishuRequest +from core.tools.utils.feishu_api_utils import auth class FeishuMessageProvider(BuiltinToolProviderController): def _validate_credentials(self, credentials: dict) -> None: - app_id = credentials.get("app_id") - app_secret = credentials.get("app_secret") - if not app_id or not app_secret: - raise ToolProviderCredentialValidationError("app_id and app_secret is required") - try: - assert FeishuRequest(app_id, app_secret).tenant_access_token is not None - except Exception as e: - raise ToolProviderCredentialValidationError(str(e)) + auth(credentials) diff --git a/api/core/tools/provider/builtin/feishu_message/feishu_message.yaml b/api/core/tools/provider/builtin/feishu_message/feishu_message.yaml index 1bd8953ddd..56683ec168 100644 --- a/api/core/tools/provider/builtin/feishu_message/feishu_message.yaml +++ b/api/core/tools/provider/builtin/feishu_message/feishu_message.yaml @@ -5,8 +5,10 @@ identity: en_US: Lark Message zh_Hans: 飞书消息 description: - en_US: Lark Message - zh_Hans: 飞书消息 + en_US: | + Lark message, requires the following permissions: im:message、im:message.group_msg. + zh_Hans: | + 飞书消息，需要开通以下权限: im:message、im:message.group_msg。 icon: icon.svg tags: - social @@ -23,7 +25,7 @@ credentials_for_provider: help: en_US: Get your app_id and app_secret from Feishu zh_Hans: 从飞书获取您的 app_id 和 app_secret - url: https://open.feishu.cn + url: https://open.larkoffice.com/app app_secret: type: secret-input required: true diff --git a/api/core/tools/provider/builtin/feishu_message/tools/get_chat_messages.py b/api/core/tools/provider/builtin/feishu_message/tools/get_chat_messages.py new file mode 100644 index 0000000000..7eb29230b2 --- /dev/null +++ b/api/core/tools/provider/builtin/feishu_message/tools/get_chat_messages.py @@ -0,0 +1,23 @@ +from typing import Any + +from core.tools.entities.tool_entities import ToolInvokeMessage +from core.tools.tool.builtin_tool import BuiltinTool +from core.tools.utils.feishu_api_utils import FeishuRequest + + +class GetChatMessagesTool(BuiltinTool): + def _invoke(self, user_id: str, tool_parameters: dict[str, Any]) -> ToolInvokeMessage: + app_id = self.runtime.credentials.get("app_id") + app_secret = self.runtime.credentials.get("app_secret") + client = FeishuRequest(app_id, app_secret) + + container_id = tool_parameters.get("container_id") + start_time = tool_parameters.get("start_time") + end_time = tool_parameters.get("end_time") + page_token = tool_parameters.get("page_token") + sort_type = tool_parameters.get("sort_type", "ByCreateTimeAsc") + page_size = tool_parameters.get("page_size", 20) + + res = client.get_chat_messages(container_id, start_time, end_time, page_token, sort_type, page_size) + + return self.create_json_message(res) diff --git a/api/core/tools/provider/builtin/feishu_message/tools/get_chat_messages.yaml b/api/core/tools/provider/builtin/feishu_message/tools/get_chat_messages.yaml new file mode 100644 index 0000000000..153c8c80e5 --- /dev/null +++ b/api/core/tools/provider/builtin/feishu_message/tools/get_chat_messages.yaml @@ -0,0 +1,96 @@ +identity: + name: get_chat_messages + author: Doug Lea + label: + en_US: Get Chat Messages + zh_Hans: 获取指定单聊、群聊的消息历史 +description: + human: + en_US: Get Chat Messages + zh_Hans: 获取指定单聊、群聊的消息历史 + llm: A tool for getting chat messages from specific one-on-one chats or group chats.(获取指定单聊、群聊的消息历史) +parameters: + - name: container_id + type: string + required: true + label: + en_US: Container Id + zh_Hans: 群聊或单聊的 ID + human_description: + en_US: The ID of the group chat or single chat. Refer to the group ID description for how to obtain it. https://open.feishu.cn/document/server-docs/group/chat/chat-id-description + zh_Hans: 群聊或单聊的 ID，获取方式参见群 ID 说明。https://open.feishu.cn/document/server-docs/group/chat/chat-id-description + llm_description: 群聊或单聊的 ID，获取方式参见群 ID 说明。https://open.feishu.cn/document/server-docs/group/chat/chat-id-description + form: llm + + - name: start_time + type: string + required: false + label: + en_US: Start Time + zh_Hans: 起始时间 + human_description: + en_US: The start time for querying historical messages, formatted as "2006-01-02 15:04:05". + zh_Hans: 待查询历史信息的起始时间，格式为 "2006-01-02 15:04:05"。 + llm_description: 待查询历史信息的起始时间，格式为 "2006-01-02 15:04:05"。 + form: llm + + - name: end_time + type: string + required: false + label: + en_US: End Time + zh_Hans: 结束时间 + human_description: + en_US: The end time for querying historical messages, formatted as "2006-01-02 15:04:05". + zh_Hans: 待查询历史信息的结束时间，格式为 "2006-01-02 15:04:05"。 + llm_description: 待查询历史信息的结束时间，格式为 "2006-01-02 15:04:05"。 + form: llm + + - name: sort_type + type: select + required: false + options: + - value: ByCreateTimeAsc + label: + en_US: ByCreateTimeAsc + zh_Hans: ByCreateTimeAsc + - value: ByCreateTimeDesc + label: + en_US: ByCreateTimeDesc + zh_Hans: ByCreateTimeDesc + default: "ByCreateTimeAsc" + label: + en_US: Sort Type + zh_Hans: 排序方式 + human_description: + en_US: | + The message sorting method. Optional values are ByCreateTimeAsc: sorted in ascending order by message creation time; ByCreateTimeDesc: sorted in descending order by message creation time. The default value is ByCreateTimeAsc. Note: When using page_token for pagination requests, the sorting method (sort_type) is consistent with the first request and cannot be changed midway. + zh_Hans: | + 消息排序方式，可选值有 ByCreateTimeAsc：按消息创建时间升序排列；ByCreateTimeDesc：按消息创建时间降序排列。默认值为：ByCreateTimeAsc。注意：使用 page_token 分页请求时，排序方式（sort_type）均与第一次请求一致，不支持中途改换排序方式。 + llm_description: 消息排序方式，可选值有 ByCreateTimeAsc：按消息创建时间升序排列；ByCreateTimeDesc：按消息创建时间降序排列。默认值为：ByCreateTimeAsc。注意：使用 page_token 分页请求时，排序方式（sort_type）均与第一次请求一致，不支持中途改换排序方式。 + form: form + + - name: page_size + type: number + required: false + default: 20 + label: + en_US: Page Size + zh_Hans: 分页大小 + human_description: + en_US: The page size, i.e., the number of data entries returned in a single request. The default value is 20, and the value range is [1,50]. + zh_Hans: 分页大小，即单次请求所返回的数据条目数。默认值为 20，取值范围为 [1,50]。 + llm_description: 分页大小，即单次请求所返回的数据条目数。默认值为 20，取值范围为 [1,50]。 + form: llm + + - name: page_token + type: string + required: false + label: + en_US: Page Token + zh_Hans: 分页标记 + human_description: + en_US: The pagination token. Leave it blank for the first request, indicating to start traversing from the beginning; when the pagination query result has more items, a new page_token will be returned simultaneously, which can be used to obtain the query result in the next traversal. + zh_Hans: 分页标记，第一次请求不填，表示从头开始遍历；分页查询结果还有更多项时会同时返回新的 page_token，下次遍历可采用该 page_token 获取查询结果。 + llm_description: 分页标记，第一次请求不填，表示从头开始遍历；分页查询结果还有更多项时会同时返回新的 page_token，下次遍历可采用该 page_token 获取查询结果。 + form: llm diff --git a/api/core/tools/provider/builtin/feishu_message/tools/get_thread_messages.py b/api/core/tools/provider/builtin/feishu_message/tools/get_thread_messages.py new file mode 100644 index 0000000000..3b14f46e00 --- /dev/null +++ b/api/core/tools/provider/builtin/feishu_message/tools/get_thread_messages.py @@ -0,0 +1,21 @@ +from typing import Any + +from core.tools.entities.tool_entities import ToolInvokeMessage +from core.tools.tool.builtin_tool import BuiltinTool +from core.tools.utils.feishu_api_utils import FeishuRequest + + +class GetChatMessagesTool(BuiltinTool): + def _invoke(self, user_id: str, tool_parameters: dict[str, Any]) -> ToolInvokeMessage: + app_id = self.runtime.credentials.get("app_id") + app_secret = self.runtime.credentials.get("app_secret") + client = FeishuRequest(app_id, app_secret) + + container_id = tool_parameters.get("container_id") + page_token = tool_parameters.get("page_token") + sort_type = tool_parameters.get("sort_type", "ByCreateTimeAsc") + page_size = tool_parameters.get("page_size", 20) + + res = client.get_thread_messages(container_id, page_token, sort_type, page_size) + + return self.create_json_message(res) diff --git a/api/core/tools/provider/builtin/feishu_message/tools/get_thread_messages.yaml b/api/core/tools/provider/builtin/feishu_message/tools/get_thread_messages.yaml new file mode 100644 index 0000000000..8d5fed9d0b --- /dev/null +++ b/api/core/tools/provider/builtin/feishu_message/tools/get_thread_messages.yaml @@ -0,0 +1,72 @@ +identity: + name: get_thread_messages + author: Doug Lea + label: + en_US: Get Thread Messages + zh_Hans: 获取指定话题的消息历史 +description: + human: + en_US: Get Thread Messages + zh_Hans: 获取指定话题的消息历史 + llm: A tool for getting chat messages from specific threads.(获取指定话题的消息历史) +parameters: + - name: container_id + type: string + required: true + label: + en_US: Thread Id + zh_Hans: 话题 ID + human_description: + en_US: The ID of the thread. Refer to the thread overview on how to obtain the thread_id. https://open.feishu.cn/document/uAjLw4CM/ukTMukTMukTM/reference/im-v1/message/thread-introduction + zh_Hans: 话题 ID，获取方式参见话题概述的如何获取 thread_id 章节。https://open.feishu.cn/document/uAjLw4CM/ukTMukTMukTM/reference/im-v1/message/thread-introduction + llm_description: 话题 ID，获取方式参见话题概述的如何获取 thread_id 章节。https://open.feishu.cn/document/uAjLw4CM/ukTMukTMukTM/reference/im-v1/message/thread-introduction + form: llm + + - name: sort_type + type: select + required: false + options: + - value: ByCreateTimeAsc + label: + en_US: ByCreateTimeAsc + zh_Hans: ByCreateTimeAsc + - value: ByCreateTimeDesc + label: + en_US: ByCreateTimeDesc + zh_Hans: ByCreateTimeDesc + default: "ByCreateTimeAsc" + label: + en_US: Sort Type + zh_Hans: 排序方式 + human_description: + en_US: | + The message sorting method. Optional values are ByCreateTimeAsc: sorted in ascending order by message creation time; ByCreateTimeDesc: sorted in descending order by message creation time. The default value is ByCreateTimeAsc. Note: When using page_token for pagination requests, the sorting method (sort_type) is consistent with the first request and cannot be changed midway. + zh_Hans: | + 消息排序方式，可选值有 ByCreateTimeAsc：按消息创建时间升序排列；ByCreateTimeDesc：按消息创建时间降序排列。默认值为：ByCreateTimeAsc。注意：使用 page_token 分页请求时，排序方式（sort_type）均与第一次请求一致，不支持中途改换排序方式。 + llm_description: 消息排序方式，可选值有 ByCreateTimeAsc：按消息创建时间升序排列；ByCreateTimeDesc：按消息创建时间降序排列。默认值为：ByCreateTimeAsc。注意：使用 page_token 分页请求时，排序方式（sort_type）均与第一次请求一致，不支持中途改换排序方式。 + form: form + + - name: page_size + type: number + required: false + default: 20 + label: + en_US: Page Size + zh_Hans: 分页大小 + human_description: + en_US: The page size, i.e., the number of data entries returned in a single request. The default value is 20, and the value range is [1,50]. + zh_Hans: 分页大小，即单次请求所返回的数据条目数。默认值为 20，取值范围为 [1,50]。 + llm_description: 分页大小，即单次请求所返回的数据条目数。默认值为 20，取值范围为 [1,50]。 + form: llm + + - name: page_token + type: string + required: false + label: + en_US: Page Token + zh_Hans: 分页标记 + human_description: + en_US: The pagination token. Leave it blank for the first request, indicating to start traversing from the beginning; when the pagination query result has more items, a new page_token will be returned simultaneously, which can be used to obtain the query result in the next traversal. + zh_Hans: 分页标记，第一次请求不填，表示从头开始遍历；分页查询结果还有更多项时会同时返回新的 page_token，下次遍历可采用该 page_token 获取查询结果。 + llm_description: 分页标记，第一次请求不填，表示从头开始遍历；分页查询结果还有更多项时会同时返回新的 page_token，下次遍历可采用该 page_token 获取查询结果。 + form: llm diff --git a/api/core/tools/provider/builtin/feishu_message/tools/send_bot_message.yaml b/api/core/tools/provider/builtin/feishu_message/tools/send_bot_message.yaml index 6e398b18ab..4f7f65a8a7 100644 --- a/api/core/tools/provider/builtin/feishu_message/tools/send_bot_message.yaml +++ b/api/core/tools/provider/builtin/feishu_message/tools/send_bot_message.yaml @@ -10,53 +10,53 @@ description: zh_Hans: 发送飞书应用消息 llm: A tool for sending Feishu application messages. parameters: + - name: receive_id + type: string + required: true + label: + en_US: receive_id + zh_Hans: 消息接收者的 ID + human_description: + en_US: The ID of the message receiver, the ID type is consistent with the value of the query parameter receive_id_type. + zh_Hans: 消息接收者的 ID，ID 类型与查询参数 receive_id_type 的取值一致。 + llm_description: 消息接收者的 ID，ID 类型与查询参数 receive_id_type 的取值一致。 + form: llm + - name: receive_id_type type: select required: true options: - value: open_id label: - en_US: open id - zh_Hans: open id + en_US: open_id + zh_Hans: open_id - value: union_id label: - en_US: union id - zh_Hans: union id + en_US: union_id + zh_Hans: union_id - value: user_id label: - en_US: user id - zh_Hans: user id + en_US: user_id + zh_Hans: user_id - value: email label: en_US: email zh_Hans: email - value: chat_id label: - en_US: chat id - zh_Hans: chat id + en_US: chat_id + zh_Hans: chat_id label: - en_US: User ID Type - zh_Hans: 用户 ID 类型 + en_US: receive_id_type + zh_Hans: 消息接收者的 ID 类型 human_description: - en_US: User ID Type - zh_Hans: 用户 ID 类型，可选值有 open_id、union_id、user_id、email、chat_id。 - llm_description: 用户 ID 类型，可选值有 open_id、union_id、user_id、email、chat_id。 - form: llm - - - name: receive_id - type: string - required: true - label: - en_US: Receive Id - zh_Hans: 消息接收者的 ID - human_description: - en_US: The ID of the message receiver. The ID type should correspond to the query parameter receive_id_type. - zh_Hans: 消息接收者的 ID，ID 类型应与查询参数 receive_id_type 对应。 - llm_description: 消息接收者的 ID，ID 类型应与查询参数 receive_id_type 对应。 - form: llm + en_US: The ID type of the message receiver, optional values are open_id, union_id, user_id, email, chat_id, with a default value of open_id. + zh_Hans: 消息接收者的 ID 类型，可选值有 open_id、union_id、user_id、email、chat_id，默认值为 open_id。 + llm_description: 消息接收者的 ID 类型，可选值有 open_id、union_id、user_id、email、chat_id，默认值为 open_id。 + form: form - name: msg_type - type: string + type: select required: true options: - value: text @@ -65,27 +65,61 @@ parameters: zh_Hans: 文本 - value: interactive label: - en_US: message card - zh_Hans: 消息卡片 + en_US: interactive + zh_Hans: 卡片 + - value: post + label: + en_US: post + zh_Hans: 富文本 + - value: image + label: + en_US: image + zh_Hans: 图片 + - value: file + label: + en_US: file + zh_Hans: 文件 + - value: audio + label: + en_US: audio + zh_Hans: 语音 + - value: media + label: + en_US: media + zh_Hans: 视频 + - value: sticker + label: + en_US: sticker + zh_Hans: 表情包 + - value: share_chat + label: + en_US: share_chat + zh_Hans: 分享群名片 + - value: share_user + label: + en_US: share_user + zh_Hans: 分享个人名片 + - value: system + label: + en_US: system + zh_Hans: 系统消息 label: - en_US: Message type + en_US: msg_type zh_Hans: 消息类型 human_description: - en_US: Message type, optional values are, text (text), interactive (message card). - zh_Hans: 消息类型，可选值有：text(文本)、interactive(消息卡片)。 - llm_description: 消息类型，可选值有：text(文本)、interactive(消息卡片)。 - form: llm + en_US: Message type. Optional values are text, post, image, file, audio, media, sticker, interactive, share_chat, share_user, system. For detailed introduction of different message types, refer to the message content(https://open.larkoffice.com/document/server-docs/im-v1/message-content-description/create_json). + zh_Hans: 消息类型。可选值有：text、post、image、file、audio、media、sticker、interactive、share_chat、share_user、system。不同消息类型的详细介绍，参见发送消息内容(https://open.larkoffice.com/document/server-docs/im-v1/message-content-description/create_json)。 + llm_description: 消息类型。可选值有：text、post、image、file、audio、media、sticker、interactive、share_chat、share_user、system。不同消息类型的详细介绍，参见发送消息内容(https://open.larkoffice.com/document/server-docs/im-v1/message-content-description/create_json)。 + form: form - name: content type: string required: true label: - en_US: Message content + en_US: content zh_Hans: 消息内容 human_description: - en_US: Message content - zh_Hans: | - 消息内容，JSON 结构序列化后的字符串。不同 msg_type 对应不同内容， - 具体格式说明参考：https://open.larkoffice.com/document/server-docs/im-v1/message-content-description/create_json - llm_description: 消息内容，JSON 结构序列化后的字符串。不同 msg_type 对应不同内容。 + en_US: Message content, a JSON structure serialized string. The value of this parameter corresponds to msg_type. For example, if msg_type is text, this parameter needs to pass in text type content. To understand the format and usage limitations of different message types, refer to the message content(https://open.larkoffice.com/document/server-docs/im-v1/message-content-description/create_json). + zh_Hans: 消息内容，JSON 结构序列化后的字符串。该参数的取值与 msg_type 对应，例如 msg_type 取值为 text，则该参数需要传入文本类型的内容。了解不同类型的消息内容格式、使用限制，可参见发送消息内容(https://open.larkoffice.com/document/server-docs/im-v1/message-content-description/create_json)。 + llm_description: 消息内容，JSON 结构序列化后的字符串。该参数的取值与 msg_type 对应，例如 msg_type 取值为 text，则该参数需要传入文本类型的内容。了解不同类型的消息内容格式、使用限制，可参见发送消息内容(https://open.larkoffice.com/document/server-docs/im-v1/message-content-description/create_json)。 form: llm diff --git a/api/core/tools/provider/builtin/feishu_message/tools/send_webhook_message.yaml b/api/core/tools/provider/builtin/feishu_message/tools/send_webhook_message.yaml index 8b39ce4874..eeeae8b29c 100644 --- a/api/core/tools/provider/builtin/feishu_message/tools/send_webhook_message.yaml +++ b/api/core/tools/provider/builtin/feishu_message/tools/send_webhook_message.yaml @@ -15,15 +15,18 @@ parameters: required: true label: en_US: webhook - zh_Hans: webhook 的地址 + zh_Hans: webhook human_description: - en_US: The address of the webhook - zh_Hans: webhook 的地址 - llm_description: webhook 的地址 + en_US: | + The address of the webhook, the format of the webhook address corresponding to the bot is as follows: https://open.feishu.cn/open-apis/bot/v2/hook/xxxxxxxxxxxxxxxxx. For details, please refer to: Feishu Custom Bot Usage Guide(https://open.larkoffice.com/document/client-docs/bot-v3/add-custom-bot) + zh_Hans: | + webhook 的地址，机器人对应的 webhook 地址格式如下: https://open.feishu.cn/open-apis/bot/v2/hook/xxxxxxxxxxxxxxxxx，详情可参考: 飞书自定义机器人使用指南(https://open.larkoffice.com/document/client-docs/bot-v3/add-custom-bot) + llm_description: | + webhook 的地址，机器人对应的 webhook 地址格式如下: https://open.feishu.cn/open-apis/bot/v2/hook/xxxxxxxxxxxxxxxxx，详情可参考: 飞书自定义机器人使用指南(https://open.larkoffice.com/document/client-docs/bot-v3/add-custom-bot) form: llm - name: msg_type - type: string + type: select required: true options: - value: text @@ -32,27 +35,34 @@ parameters: zh_Hans: 文本 - value: interactive label: - en_US: message card - zh_Hans: 消息卡片 + en_US: interactive + zh_Hans: 卡片 + - value: image + label: + en_US: image + zh_Hans: 图片 + - value: share_chat + label: + en_US: share_chat + zh_Hans: 分享群名片 label: - en_US: Message type + en_US: msg_type zh_Hans: 消息类型 human_description: - en_US: Message type, optional values are, text (text), interactive (message card). - zh_Hans: 消息类型，可选值有：text(文本)、interactive(消息卡片)。 - llm_description: 消息类型，可选值有：text(文本)、interactive(消息卡片)。 - form: llm + en_US: Message type. Optional values are text, image, interactive, share_chat. For detailed introduction of different message types, refer to the message content(https://open.larkoffice.com/document/server-docs/im-v1/message-content-description/create_json). + zh_Hans: 消息类型。可选值有：text、image、interactive、share_chat。不同消息类型的详细介绍，参见发送消息内容(https://open.larkoffice.com/document/server-docs/im-v1/message-content-description/create_json)。 + llm_description: 消息类型。可选值有：text、image、interactive、share_chat。不同消息类型的详细介绍，参见发送消息内容(https://open.larkoffice.com/document/server-docs/im-v1/message-content-description/create_json)。 + form: form + - name: content type: string required: true label: - en_US: Message content + en_US: content zh_Hans: 消息内容 human_description: - en_US: Message content - zh_Hans: | - 消息内容，JSON 结构序列化后的字符串。不同 msg_type 对应不同内容， - 具体格式说明参考：https://open.larkoffice.com/document/server-docs/im-v1/message-content-description/create_json - llm_description: 消息内容，JSON 结构序列化后的字符串。不同 msg_type 对应不同内容。 + en_US: Message content, a JSON structure serialized string. The value of this parameter corresponds to msg_type. For example, if msg_type is text, this parameter needs to pass in text type content. To understand the format and usage limitations of different message types, refer to the message content(https://open.larkoffice.com/document/server-docs/im-v1/message-content-description/create_json). + zh_Hans: 消息内容，JSON 结构序列化后的字符串。该参数的取值与 msg_type 对应，例如 msg_type 取值为 text，则该参数需要传入文本类型的内容。了解不同类型的消息内容格式、使用限制，可参见发送消息内容(https://open.larkoffice.com/document/server-docs/im-v1/message-content-description/create_json)。 + llm_description: 消息内容，JSON 结构序列化后的字符串。该参数的取值与 msg_type 对应，例如 msg_type 取值为 text，则该参数需要传入文本类型的内容。了解不同类型的消息内容格式、使用限制，可参见发送消息内容(https://open.larkoffice.com/document/server-docs/im-v1/message-content-description/create_json)。 form: llm diff --git a/api/core/tools/provider/builtin/feishu_spreadsheet/_assets/icon.png b/api/core/tools/provider/builtin/feishu_spreadsheet/_assets/icon.png new file mode 100644 index 0000000000..258b361261 Binary files /dev/null and b/api/core/tools/provider/builtin/feishu_spreadsheet/_assets/icon.png differ diff --git a/api/core/tools/provider/builtin/feishu_spreadsheet/feishu_spreadsheet.py b/api/core/tools/provider/builtin/feishu_spreadsheet/feishu_spreadsheet.py new file mode 100644 index 0000000000..a3b5473769 --- /dev/null +++ b/api/core/tools/provider/builtin/feishu_spreadsheet/feishu_spreadsheet.py @@ -0,0 +1,7 @@ +from core.tools.provider.builtin_tool_provider import BuiltinToolProviderController +from core.tools.utils.feishu_api_utils import auth + + +class FeishuMessageProvider(BuiltinToolProviderController): + def _validate_credentials(self, credentials: dict) -> None: + auth(credentials) diff --git a/api/core/tools/provider/builtin/feishu_spreadsheet/feishu_spreadsheet.yaml b/api/core/tools/provider/builtin/feishu_spreadsheet/feishu_spreadsheet.yaml new file mode 100644 index 0000000000..29e448d730 --- /dev/null +++ b/api/core/tools/provider/builtin/feishu_spreadsheet/feishu_spreadsheet.yaml @@ -0,0 +1,36 @@ +identity: + author: Doug Lea + name: feishu_spreadsheet + label: + en_US: Feishu Spreadsheet + zh_Hans: 飞书电子表格 + description: + en_US: | + Feishu Spreadsheet, requires the following permissions: sheets:spreadsheet. + zh_Hans: | + 飞书电子表格，需要开通以下权限: sheets:spreadsheet。 + icon: icon.png + tags: + - social + - productivity +credentials_for_provider: + app_id: + type: text-input + required: true + label: + en_US: APP ID + placeholder: + en_US: Please input your feishu app id + zh_Hans: 请输入你的飞书 app id + help: + en_US: Get your app_id and app_secret from Feishu + zh_Hans: 从飞书获取您的 app_id 和 app_secret + url: https://open.larkoffice.com/app + app_secret: + type: secret-input + required: true + label: + en_US: APP Secret + placeholder: + en_US: Please input your app secret + zh_Hans: 请输入你的飞书 app secret diff --git a/api/core/tools/provider/builtin/feishu_spreadsheet/tools/add_cols.py b/api/core/tools/provider/builtin/feishu_spreadsheet/tools/add_cols.py new file mode 100644 index 0000000000..44d062f9bd --- /dev/null +++ b/api/core/tools/provider/builtin/feishu_spreadsheet/tools/add_cols.py @@ -0,0 +1,22 @@ +from typing import Any + +from core.tools.entities.tool_entities import ToolInvokeMessage +from core.tools.tool.builtin_tool import BuiltinTool +from core.tools.utils.feishu_api_utils import FeishuRequest + + +class AddColsTool(BuiltinTool): + def _invoke(self, user_id: str, tool_parameters: dict[str, Any]) -> ToolInvokeMessage: + app_id = self.runtime.credentials.get("app_id") + app_secret = self.runtime.credentials.get("app_secret") + client = FeishuRequest(app_id, app_secret) + + spreadsheet_token = tool_parameters.get("spreadsheet_token") + sheet_id = tool_parameters.get("sheet_id") + sheet_name = tool_parameters.get("sheet_name") + length = tool_parameters.get("length") + values = tool_parameters.get("values") + + res = client.add_cols(spreadsheet_token, sheet_id, sheet_name, length, values) + + return self.create_json_message(res) diff --git a/api/core/tools/provider/builtin/feishu_spreadsheet/tools/add_cols.yaml b/api/core/tools/provider/builtin/feishu_spreadsheet/tools/add_cols.yaml new file mode 100644 index 0000000000..ef457f8e00 --- /dev/null +++ b/api/core/tools/provider/builtin/feishu_spreadsheet/tools/add_cols.yaml @@ -0,0 +1,72 @@ +identity: + name: add_cols + author: Doug Lea + label: + en_US: Add Cols + zh_Hans: 新增多列至工作表最后 +description: + human: + en_US: Add Cols + zh_Hans: 新增多列至工作表最后 + llm: A tool for adding multiple columns to the end of a spreadsheet. (新增多列至工作表最后) +parameters: + - name: spreadsheet_token + type: string + required: true + label: + en_US: spreadsheet_token + zh_Hans: 电子表格 token + human_description: + en_US: Spreadsheet token, supports input of spreadsheet URL. + zh_Hans: 电子表格 token，支持输入电子表格 url。 + llm_description: 电子表格 token，支持输入电子表格 url。 + form: llm + + - name: sheet_id + type: string + required: false + label: + en_US: sheet_id + zh_Hans: 工作表 ID + human_description: + en_US: Sheet ID, either sheet_id or sheet_name must be filled. + zh_Hans: 工作表 ID，与 sheet_name 二者其一必填。 + llm_description: 工作表 ID，与 sheet_name 二者其一必填。 + form: llm + + - name: sheet_name + type: string + required: false + label: + en_US: sheet_name + zh_Hans: 工作表名称 + human_description: + en_US: Sheet name, either sheet_id or sheet_name must be filled. + zh_Hans: 工作表名称，与 sheet_id 二者其一必填。 + llm_description: 工作表名称，与 sheet_id 二者其一必填。 + form: llm + + - name: length + type: number + required: true + label: + en_US: length + zh_Hans: 要增加的列数 + human_description: + en_US: Number of columns to add, range (0-5000]. + zh_Hans: 要增加的列数，范围(0-5000]。 + llm_description: 要增加的列数，范围(0-5000]。 + form: llm + + - name: values + type: string + required: false + label: + en_US: values + zh_Hans: 新增列的单元格内容 + human_description: + en_US: | + Content of the new columns, array of objects in string format, each array represents a row of table data, format like: [ [ "ID","Name","Age" ],[ 1,"Zhang San",10 ],[ 2,"Li Si",11 ] ]. + zh_Hans: 新增列的单元格内容，数组对象字符串，每个数组一行表格数据，格式：[["编号","姓名","年龄"],[1,"张三",10],[2,"李四",11]]。 + llm_description: 新增列的单元格内容，数组对象字符串，每个数组一行表格数据，格式：[["编号","姓名","年龄"],[1,"张三",10],[2,"李四",11]]。 + form: llm diff --git a/api/core/tools/provider/builtin/feishu_spreadsheet/tools/add_rows.py b/api/core/tools/provider/builtin/feishu_spreadsheet/tools/add_rows.py new file mode 100644 index 0000000000..3a85b7b46c --- /dev/null +++ b/api/core/tools/provider/builtin/feishu_spreadsheet/tools/add_rows.py @@ -0,0 +1,22 @@ +from typing import Any + +from core.tools.entities.tool_entities import ToolInvokeMessage +from core.tools.tool.builtin_tool import BuiltinTool +from core.tools.utils.feishu_api_utils import FeishuRequest + + +class AddRowsTool(BuiltinTool): + def _invoke(self, user_id: str, tool_parameters: dict[str, Any]) -> ToolInvokeMessage: + app_id = self.runtime.credentials.get("app_id") + app_secret = self.runtime.credentials.get("app_secret") + client = FeishuRequest(app_id, app_secret) + + spreadsheet_token = tool_parameters.get("spreadsheet_token") + sheet_id = tool_parameters.get("sheet_id") + sheet_name = tool_parameters.get("sheet_name") + length = tool_parameters.get("length") + values = tool_parameters.get("values") + + res = client.add_rows(spreadsheet_token, sheet_id, sheet_name, length, values) + + return self.create_json_message(res) diff --git a/api/core/tools/provider/builtin/feishu_spreadsheet/tools/add_rows.yaml b/api/core/tools/provider/builtin/feishu_spreadsheet/tools/add_rows.yaml new file mode 100644 index 0000000000..37653325ae --- /dev/null +++ b/api/core/tools/provider/builtin/feishu_spreadsheet/tools/add_rows.yaml @@ -0,0 +1,72 @@ +identity: + name: add_rows + author: Doug Lea + label: + en_US: Add Rows + zh_Hans: 新增多行至工作表最后 +description: + human: + en_US: Add Rows + zh_Hans: 新增多行至工作表最后 + llm: A tool for adding multiple rows to the end of a spreadsheet. (新增多行至工作表最后) +parameters: + - name: spreadsheet_token + type: string + required: true + label: + en_US: spreadsheet_token + zh_Hans: 电子表格 token + human_description: + en_US: Spreadsheet token, supports input of spreadsheet URL. + zh_Hans: 电子表格 token，支持输入电子表格 url。 + llm_description: 电子表格 token，支持输入电子表格 url。 + form: llm + + - name: sheet_id + type: string + required: false + label: + en_US: sheet_id + zh_Hans: 工作表 ID + human_description: + en_US: Sheet ID, either sheet_id or sheet_name must be filled. + zh_Hans: 工作表 ID，与 sheet_name 二者其一必填。 + llm_description: 工作表 ID，与 sheet_name 二者其一必填。 + form: llm + + - name: sheet_name + type: string + required: false + label: + en_US: sheet_name + zh_Hans: 工作表名称 + human_description: + en_US: Sheet name, either sheet_id or sheet_name must be filled. + zh_Hans: 工作表名称，与 sheet_id 二者其一必填。 + llm_description: 工作表名称，与 sheet_id 二者其一必填。 + form: llm + + - name: length + type: number + required: true + label: + en_US: length + zh_Hans: 要增加行数 + human_description: + en_US: Number of rows to add, range (0-5000]. + zh_Hans: 要增加行数，范围(0-5000]。 + llm_description: 要增加行数，范围(0-5000]。 + form: llm + + - name: values + type: string + required: false + label: + en_US: values + zh_Hans: 新增行的表格内容 + human_description: + en_US: | + Content of the new rows, array of objects in string format, each array represents a row of table data, format like: [ [ "ID","Name","Age" ],[ 1,"Zhang San",10 ],[ 2,"Li Si",11 ] ]. + zh_Hans: 新增行的表格内容，数组对象字符串，每个数组一行表格数据，格式,如：[["编号","姓名","年龄"],[1,"张三",10],[2,"李四",11]]。 + llm_description: 新增行的表格内容，数组对象字符串，每个数组一行表格数据，格式,如：[["编号","姓名","年龄"],[1,"张三",10],[2,"李四",11]]。 + form: llm diff --git a/api/core/tools/provider/builtin/feishu_spreadsheet/tools/create_spreadsheet.py b/api/core/tools/provider/builtin/feishu_spreadsheet/tools/create_spreadsheet.py new file mode 100644 index 0000000000..647364fab0 --- /dev/null +++ b/api/core/tools/provider/builtin/feishu_spreadsheet/tools/create_spreadsheet.py @@ -0,0 +1,19 @@ +from typing import Any + +from core.tools.entities.tool_entities import ToolInvokeMessage +from core.tools.tool.builtin_tool import BuiltinTool +from core.tools.utils.feishu_api_utils import FeishuRequest + + +class CreateSpreadsheetTool(BuiltinTool): + def _invoke(self, user_id: str, tool_parameters: dict[str, Any]) -> ToolInvokeMessage: + app_id = self.runtime.credentials.get("app_id") + app_secret = self.runtime.credentials.get("app_secret") + client = FeishuRequest(app_id, app_secret) + + title = tool_parameters.get("title") + folder_token = tool_parameters.get("folder_token") + + res = client.create_spreadsheet(title, folder_token) + + return self.create_json_message(res) diff --git a/api/core/tools/provider/builtin/feishu_spreadsheet/tools/create_spreadsheet.yaml b/api/core/tools/provider/builtin/feishu_spreadsheet/tools/create_spreadsheet.yaml new file mode 100644 index 0000000000..931310e631 --- /dev/null +++ b/api/core/tools/provider/builtin/feishu_spreadsheet/tools/create_spreadsheet.yaml @@ -0,0 +1,35 @@ +identity: + name: create_spreadsheet + author: Doug Lea + label: + en_US: Create Spreadsheet + zh_Hans: 创建电子表格 +description: + human: + en_US: Create Spreadsheet + zh_Hans: 创建电子表格 + llm: A tool for creating spreadsheets. (创建电子表格) +parameters: + - name: title + type: string + required: false + label: + en_US: Spreadsheet Title + zh_Hans: 电子表格标题 + human_description: + en_US: The title of the spreadsheet + zh_Hans: 电子表格的标题 + llm_description: 电子表格的标题 + form: llm + + - name: folder_token + type: string + required: false + label: + en_US: Folder Token + zh_Hans: 文件夹 token + human_description: + en_US: The token of the folder, supports folder URL input, e.g., https://bytedance.larkoffice.com/drive/folder/CxHEf4DCSlNkL2dUTCJcPRgentg + zh_Hans: 文件夹 token，支持文件夹 URL 输入，如：https://bytedance.larkoffice.com/drive/folder/CxHEf4DCSlNkL2dUTCJcPRgentg + llm_description: 文件夹 token，支持文件夹 URL 输入，如：https://bytedance.larkoffice.com/drive/folder/CxHEf4DCSlNkL2dUTCJcPRgentg + form: llm diff --git a/api/core/tools/provider/builtin/feishu_spreadsheet/tools/get_spreadsheet.py b/api/core/tools/provider/builtin/feishu_spreadsheet/tools/get_spreadsheet.py new file mode 100644 index 0000000000..dda8c59daf --- /dev/null +++ b/api/core/tools/provider/builtin/feishu_spreadsheet/tools/get_spreadsheet.py @@ -0,0 +1,19 @@ +from typing import Any + +from core.tools.entities.tool_entities import ToolInvokeMessage +from core.tools.tool.builtin_tool import BuiltinTool +from core.tools.utils.feishu_api_utils import FeishuRequest + + +class GetSpreadsheetTool(BuiltinTool): + def _invoke(self, user_id: str, tool_parameters: dict[str, Any]) -> ToolInvokeMessage: + app_id = self.runtime.credentials.get("app_id") + app_secret = self.runtime.credentials.get("app_secret") + client = FeishuRequest(app_id, app_secret) + + spreadsheet_token = tool_parameters.get("spreadsheet_token") + user_id_type = tool_parameters.get("user_id_type", "open_id") + + res = client.get_spreadsheet(spreadsheet_token, user_id_type) + + return self.create_json_message(res) diff --git a/api/core/tools/provider/builtin/feishu_spreadsheet/tools/get_spreadsheet.yaml b/api/core/tools/provider/builtin/feishu_spreadsheet/tools/get_spreadsheet.yaml new file mode 100644 index 0000000000..c519938617 --- /dev/null +++ b/api/core/tools/provider/builtin/feishu_spreadsheet/tools/get_spreadsheet.yaml @@ -0,0 +1,49 @@ +identity: + name: get_spreadsheet + author: Doug Lea + label: + en_US: Get Spreadsheet + zh_Hans: 获取电子表格信息 +description: + human: + en_US: Get Spreadsheet + zh_Hans: 获取电子表格信息 + llm: A tool for getting information from spreadsheets. (获取电子表格信息) +parameters: + - name: spreadsheet_token + type: string + required: true + label: + en_US: Spreadsheet Token + zh_Hans: 电子表格 token + human_description: + en_US: Spreadsheet token, supports input of spreadsheet URL. + zh_Hans: 电子表格 token，支持输入电子表格 URL。 + llm_description: 电子表格 token，支持输入电子表格 URL。 + form: llm + + - name: user_id_type + type: select + required: false + options: + - value: open_id + label: + en_US: open_id + zh_Hans: open_id + - value: union_id + label: + en_US: union_id + zh_Hans: union_id + - value: user_id + label: + en_US: user_id + zh_Hans: user_id + default: "open_id" + label: + en_US: user_id_type + zh_Hans: 用户 ID 类型 + human_description: + en_US: User ID type, optional values are open_id, union_id, user_id, with a default value of open_id. + zh_Hans: 用户 ID 类型，可选值有 open_id、union_id、user_id，默认值为 open_id。 + llm_description: 用户 ID 类型，可选值有 open_id、union_id、user_id，默认值为 open_id。 + form: form diff --git a/api/core/tools/provider/builtin/feishu_spreadsheet/tools/list_spreadsheet_sheets.py b/api/core/tools/provider/builtin/feishu_spreadsheet/tools/list_spreadsheet_sheets.py new file mode 100644 index 0000000000..98497791c0 --- /dev/null +++ b/api/core/tools/provider/builtin/feishu_spreadsheet/tools/list_spreadsheet_sheets.py @@ -0,0 +1,18 @@ +from typing import Any + +from core.tools.entities.tool_entities import ToolInvokeMessage +from core.tools.tool.builtin_tool import BuiltinTool +from core.tools.utils.feishu_api_utils import FeishuRequest + + +class ListSpreadsheetSheetsTool(BuiltinTool): + def _invoke(self, user_id: str, tool_parameters: dict[str, Any]) -> ToolInvokeMessage: + app_id = self.runtime.credentials.get("app_id") + app_secret = self.runtime.credentials.get("app_secret") + client = FeishuRequest(app_id, app_secret) + + spreadsheet_token = tool_parameters.get("spreadsheet_token") + + res = client.list_spreadsheet_sheets(spreadsheet_token) + + return self.create_json_message(res) diff --git a/api/core/tools/provider/builtin/feishu_spreadsheet/tools/list_spreadsheet_sheets.yaml b/api/core/tools/provider/builtin/feishu_spreadsheet/tools/list_spreadsheet_sheets.yaml new file mode 100644 index 0000000000..c6a7ef45d4 --- /dev/null +++ b/api/core/tools/provider/builtin/feishu_spreadsheet/tools/list_spreadsheet_sheets.yaml @@ -0,0 +1,23 @@ +identity: + name: list_spreadsheet_sheets + author: Doug Lea + label: + en_US: List Spreadsheet Sheets + zh_Hans: 列出电子表格所有工作表 +description: + human: + en_US: List Spreadsheet Sheets + zh_Hans: 列出电子表格所有工作表 + llm: A tool for listing all sheets in a spreadsheet. (列出电子表格所有工作表) +parameters: + - name: spreadsheet_token + type: string + required: true + label: + en_US: Spreadsheet Token + zh_Hans: 电子表格 token + human_description: + en_US: Spreadsheet token, supports input of spreadsheet URL. + zh_Hans: 电子表格 token，支持输入电子表格 URL。 + llm_description: 电子表格 token，支持输入电子表格 URL。 + form: llm diff --git a/api/core/tools/provider/builtin/feishu_spreadsheet/tools/read_cols.py b/api/core/tools/provider/builtin/feishu_spreadsheet/tools/read_cols.py new file mode 100644 index 0000000000..ebe3f619d0 --- /dev/null +++ b/api/core/tools/provider/builtin/feishu_spreadsheet/tools/read_cols.py @@ -0,0 +1,23 @@ +from typing import Any + +from core.tools.entities.tool_entities import ToolInvokeMessage +from core.tools.tool.builtin_tool import BuiltinTool +from core.tools.utils.feishu_api_utils import FeishuRequest + + +class ReadColsTool(BuiltinTool): + def _invoke(self, user_id: str, tool_parameters: dict[str, Any]) -> ToolInvokeMessage: + app_id = self.runtime.credentials.get("app_id") + app_secret = self.runtime.credentials.get("app_secret") + client = FeishuRequest(app_id, app_secret) + + spreadsheet_token = tool_parameters.get("spreadsheet_token") + sheet_id = tool_parameters.get("sheet_id") + sheet_name = tool_parameters.get("sheet_name") + start_col = tool_parameters.get("start_col") + num_cols = tool_parameters.get("num_cols") + user_id_type = tool_parameters.get("user_id_type", "open_id") + + res = client.read_cols(spreadsheet_token, sheet_id, sheet_name, start_col, num_cols, user_id_type) + + return self.create_json_message(res) diff --git a/api/core/tools/provider/builtin/feishu_spreadsheet/tools/read_cols.yaml b/api/core/tools/provider/builtin/feishu_spreadsheet/tools/read_cols.yaml new file mode 100644 index 0000000000..3273857b70 --- /dev/null +++ b/api/core/tools/provider/builtin/feishu_spreadsheet/tools/read_cols.yaml @@ -0,0 +1,97 @@ +identity: + name: read_cols + author: Doug Lea + label: + en_US: Read Cols + zh_Hans: 读取工作表列数据 +description: + human: + en_US: Read Cols + zh_Hans: 读取工作表列数据 + llm: A tool for reading column data from a spreadsheet. (读取工作表列数据) +parameters: + - name: spreadsheet_token + type: string + required: true + label: + en_US: spreadsheet_token + zh_Hans: 电子表格 token + human_description: + en_US: Spreadsheet token, supports input of spreadsheet URL. + zh_Hans: 电子表格 token，支持输入电子表格 url。 + llm_description: 电子表格 token，支持输入电子表格 url。 + form: llm + + - name: sheet_id + type: string + required: false + label: + en_US: sheet_id + zh_Hans: 工作表 ID + human_description: + en_US: Sheet ID, either sheet_id or sheet_name must be filled. + zh_Hans: 工作表 ID，与 sheet_name 二者其一必填。 + llm_description: 工作表 ID，与 sheet_name 二者其一必填。 + form: llm + + - name: sheet_name + type: string + required: false + label: + en_US: sheet_name + zh_Hans: 工作表名称 + human_description: + en_US: Sheet name, either sheet_id or sheet_name must be filled. + zh_Hans: 工作表名称，与 sheet_id 二者其一必填。 + llm_description: 工作表名称，与 sheet_id 二者其一必填。 + form: llm + + - name: user_id_type + type: select + required: false + options: + - value: open_id + label: + en_US: open_id + zh_Hans: open_id + - value: union_id + label: + en_US: union_id + zh_Hans: union_id + - value: user_id + label: + en_US: user_id + zh_Hans: user_id + default: "open_id" + label: + en_US: user_id_type + zh_Hans: 用户 ID 类型 + human_description: + en_US: User ID type, optional values are open_id, union_id, user_id, with a default value of open_id. + zh_Hans: 用户 ID 类型，可选值有 open_id、union_id、user_id，默认值为 open_id。 + llm_description: 用户 ID 类型，可选值有 open_id、union_id、user_id，默认值为 open_id。 + form: form + + - name: start_col + type: number + required: false + label: + en_US: start_col + zh_Hans: 起始列号 + human_description: + en_US: Starting column number, starting from 1. + zh_Hans: 起始列号，从 1 开始。 + llm_description: 起始列号，从 1 开始。 + form: llm + + - name: num_cols + type: number + required: true + label: + en_US: num_cols + zh_Hans: 读取列数 + human_description: + en_US: Number of columns to read. + zh_Hans: 读取列数 + llm_description: 读取列数 + form: llm diff --git a/api/core/tools/provider/builtin/feishu_spreadsheet/tools/read_rows.py b/api/core/tools/provider/builtin/feishu_spreadsheet/tools/read_rows.py new file mode 100644 index 0000000000..86b91b104b --- /dev/null +++ b/api/core/tools/provider/builtin/feishu_spreadsheet/tools/read_rows.py @@ -0,0 +1,23 @@ +from typing import Any + +from core.tools.entities.tool_entities import ToolInvokeMessage +from core.tools.tool.builtin_tool import BuiltinTool +from core.tools.utils.feishu_api_utils import FeishuRequest + + +class ReadRowsTool(BuiltinTool): + def _invoke(self, user_id: str, tool_parameters: dict[str, Any]) -> ToolInvokeMessage: + app_id = self.runtime.credentials.get("app_id") + app_secret = self.runtime.credentials.get("app_secret") + client = FeishuRequest(app_id, app_secret) + + spreadsheet_token = tool_parameters.get("spreadsheet_token") + sheet_id = tool_parameters.get("sheet_id") + sheet_name = tool_parameters.get("sheet_name") + start_row = tool_parameters.get("start_row") + num_rows = tool_parameters.get("num_rows") + user_id_type = tool_parameters.get("user_id_type", "open_id") + + res = client.read_rows(spreadsheet_token, sheet_id, sheet_name, start_row, num_rows, user_id_type) + + return self.create_json_message(res) diff --git a/api/core/tools/provider/builtin/feishu_spreadsheet/tools/read_rows.yaml b/api/core/tools/provider/builtin/feishu_spreadsheet/tools/read_rows.yaml new file mode 100644 index 0000000000..3e9206e8ef --- /dev/null +++ b/api/core/tools/provider/builtin/feishu_spreadsheet/tools/read_rows.yaml @@ -0,0 +1,97 @@ +identity: + name: read_rows + author: Doug Lea + label: + en_US: Read Rows + zh_Hans: 读取工作表行数据 +description: + human: + en_US: Read Rows + zh_Hans: 读取工作表行数据 + llm: A tool for reading row data from a spreadsheet. (读取工作表行数据) +parameters: + - name: spreadsheet_token + type: string + required: true + label: + en_US: spreadsheet_token + zh_Hans: 电子表格 token + human_description: + en_US: Spreadsheet token, supports input of spreadsheet URL. + zh_Hans: 电子表格 token，支持输入电子表格 url。 + llm_description: 电子表格 token，支持输入电子表格 url。 + form: llm + + - name: sheet_id + type: string + required: false + label: + en_US: sheet_id + zh_Hans: 工作表 ID + human_description: + en_US: Sheet ID, either sheet_id or sheet_name must be filled. + zh_Hans: 工作表 ID，与 sheet_name 二者其一必填。 + llm_description: 工作表 ID，与 sheet_name 二者其一必填。 + form: llm + + - name: sheet_name + type: string + required: false + label: + en_US: sheet_name + zh_Hans: 工作表名称 + human_description: + en_US: Sheet name, either sheet_id or sheet_name must be filled. + zh_Hans: 工作表名称，与 sheet_id 二者其一必填。 + llm_description: 工作表名称，与 sheet_id 二者其一必填。 + form: llm + + - name: user_id_type + type: select + required: false + options: + - value: open_id + label: + en_US: open_id + zh_Hans: open_id + - value: union_id + label: + en_US: union_id + zh_Hans: union_id + - value: user_id + label: + en_US: user_id + zh_Hans: user_id + default: "open_id" + label: + en_US: user_id_type + zh_Hans: 用户 ID 类型 + human_description: + en_US: User ID type, optional values are open_id, union_id, user_id, with a default value of open_id. + zh_Hans: 用户 ID 类型，可选值有 open_id、union_id、user_id，默认值为 open_id。 + llm_description: 用户 ID 类型，可选值有 open_id、union_id、user_id，默认值为 open_id。 + form: form + + - name: start_row + type: number + required: false + label: + en_US: start_row + zh_Hans: 起始行号 + human_description: + en_US: Starting row number, starting from 1. + zh_Hans: 起始行号，从 1 开始。 + llm_description: 起始行号，从 1 开始。 + form: llm + + - name: num_rows + type: number + required: true + label: + en_US: num_rows + zh_Hans: 读取行数 + human_description: + en_US: Number of rows to read. + zh_Hans: 读取行数 + llm_description: 读取行数 + form: llm diff --git a/api/core/tools/provider/builtin/feishu_spreadsheet/tools/read_table.py b/api/core/tools/provider/builtin/feishu_spreadsheet/tools/read_table.py new file mode 100644 index 0000000000..ddd607d878 --- /dev/null +++ b/api/core/tools/provider/builtin/feishu_spreadsheet/tools/read_table.py @@ -0,0 +1,23 @@ +from typing import Any + +from core.tools.entities.tool_entities import ToolInvokeMessage +from core.tools.tool.builtin_tool import BuiltinTool +from core.tools.utils.feishu_api_utils import FeishuRequest + + +class ReadTableTool(BuiltinTool): + def _invoke(self, user_id: str, tool_parameters: dict[str, Any]) -> ToolInvokeMessage: + app_id = self.runtime.credentials.get("app_id") + app_secret = self.runtime.credentials.get("app_secret") + client = FeishuRequest(app_id, app_secret) + + spreadsheet_token = tool_parameters.get("spreadsheet_token") + sheet_id = tool_parameters.get("sheet_id") + sheet_name = tool_parameters.get("sheet_name") + num_range = tool_parameters.get("num_range") + query = tool_parameters.get("query") + user_id_type = tool_parameters.get("user_id_type", "open_id") + + res = client.read_table(spreadsheet_token, sheet_id, sheet_name, num_range, query, user_id_type) + + return self.create_json_message(res) diff --git a/api/core/tools/provider/builtin/feishu_spreadsheet/tools/read_table.yaml b/api/core/tools/provider/builtin/feishu_spreadsheet/tools/read_table.yaml new file mode 100644 index 0000000000..e3dc80e1eb --- /dev/null +++ b/api/core/tools/provider/builtin/feishu_spreadsheet/tools/read_table.yaml @@ -0,0 +1,122 @@ +identity: + name: read_table + author: Doug Lea + label: + en_US: Read Table + zh_Hans: 自定义读取电子表格行列数据 +description: + human: + en_US: Read Table + zh_Hans: 自定义读取电子表格行列数据 + llm: A tool for custom reading of row and column data from a spreadsheet. (自定义读取电子表格行列数据) +parameters: + - name: spreadsheet_token + type: string + required: true + label: + en_US: spreadsheet_token + zh_Hans: 电子表格 token + human_description: + en_US: Spreadsheet token, supports input of spreadsheet URL. + zh_Hans: 电子表格 token，支持输入电子表格 url。 + llm_description: 电子表格 token，支持输入电子表格 url。 + form: llm + + - name: sheet_id + type: string + required: false + label: + en_US: sheet_id + zh_Hans: 工作表 ID + human_description: + en_US: Sheet ID, either sheet_id or sheet_name must be filled. + zh_Hans: 工作表 ID，与 sheet_name 二者其一必填。 + llm_description: 工作表 ID，与 sheet_name 二者其一必填。 + form: llm + + - name: sheet_name + type: string + required: false + label: + en_US: sheet_name + zh_Hans: 工作表名称 + human_description: + en_US: Sheet name, either sheet_id or sheet_name must be filled. + zh_Hans: 工作表名称，与 sheet_id 二者其一必填。 + llm_description: 工作表名称，与 sheet_id 二者其一必填。 + form: llm + + - name: user_id_type + type: select + required: false + options: + - value: open_id + label: + en_US: open_id + zh_Hans: open_id + - value: union_id + label: + en_US: union_id + zh_Hans: union_id + - value: user_id + label: + en_US: user_id + zh_Hans: user_id + default: "open_id" + label: + en_US: user_id_type + zh_Hans: 用户 ID 类型 + human_description: + en_US: User ID type, optional values are open_id, union_id, user_id, with a default value of open_id. + zh_Hans: 用户 ID 类型，可选值有 open_id、union_id、user_id，默认值为 open_id。 + llm_description: 用户 ID 类型，可选值有 open_id、union_id、user_id，默认值为 open_id。 + form: form + + - name: start_row + type: number + required: false + label: + en_US: start_row + zh_Hans: 起始行号 + human_description: + en_US: Starting row number, starting from 1. + zh_Hans: 起始行号，从 1 开始。 + llm_description: 起始行号，从 1 开始。 + form: llm + + - name: num_rows + type: number + required: false + label: + en_US: num_rows + zh_Hans: 读取行数 + human_description: + en_US: Number of rows to read. + zh_Hans: 读取行数 + llm_description: 读取行数 + form: llm + + - name: range + type: string + required: false + label: + en_US: range + zh_Hans: 取数范围 + human_description: + en_US: | + Data range, format like: A1:B2, can be empty when query=all. + zh_Hans: 取数范围,格式如:A1:B2，query=all 时可为空。 + llm_description: 取数范围,格式如:A1:B2，query=all 时可为空。 + form: llm + + - name: query + type: string + required: false + label: + en_US: query + zh_Hans: 查询 + human_description: + en_US: Pass "all" to query all data in the table, but no more than 100 columns. + zh_Hans: 传 all，表示查询表格所有数据，但最多查询 100 列数据。 + llm_description: 传 all，表示查询表格所有数据，但最多查询 100 列数据。 + form: llm diff --git a/api/core/tools/provider/builtin/feishu_task/_assets/icon.png b/api/core/tools/provider/builtin/feishu_task/_assets/icon.png new file mode 100644 index 0000000000..3485be0d0f Binary files /dev/null and b/api/core/tools/provider/builtin/feishu_task/_assets/icon.png differ diff --git a/api/core/tools/provider/builtin/feishu_task/feishu_task.py b/api/core/tools/provider/builtin/feishu_task/feishu_task.py new file mode 100644 index 0000000000..6df05968d8 --- /dev/null +++ b/api/core/tools/provider/builtin/feishu_task/feishu_task.py @@ -0,0 +1,7 @@ +from core.tools.provider.builtin_tool_provider import BuiltinToolProviderController +from core.tools.utils.feishu_api_utils import auth + + +class FeishuTaskProvider(BuiltinToolProviderController): + def _validate_credentials(self, credentials: dict) -> None: + auth(credentials) diff --git a/api/core/tools/provider/builtin/feishu_task/feishu_task.yaml b/api/core/tools/provider/builtin/feishu_task/feishu_task.yaml new file mode 100644 index 0000000000..88736f79a0 --- /dev/null +++ b/api/core/tools/provider/builtin/feishu_task/feishu_task.yaml @@ -0,0 +1,36 @@ +identity: + author: Doug Lea + name: feishu_task + label: + en_US: Feishu Task + zh_Hans: 飞书任务 + description: + en_US: | + Feishu Task, requires the following permissions: task:task:write、contact:user.id:readonly. + zh_Hans: | + 飞书任务，需要开通以下权限: task:task:write、contact:user.id:readonly。 + icon: icon.png + tags: + - social + - productivity +credentials_for_provider: + app_id: + type: text-input + required: true + label: + en_US: APP ID + placeholder: + en_US: Please input your feishu app id + zh_Hans: 请输入你的飞书 app id + help: + en_US: Get your app_id and app_secret from Feishu + zh_Hans: 从飞书获取您的 app_id 和 app_secret + url: https://open.larkoffice.com/app + app_secret: + type: secret-input + required: true + label: + en_US: APP Secret + placeholder: + en_US: Please input your app secret + zh_Hans: 请输入你的飞书 app secret diff --git a/api/core/tools/provider/builtin/feishu_task/tools/add_members.py b/api/core/tools/provider/builtin/feishu_task/tools/add_members.py new file mode 100644 index 0000000000..e58ed22e0f --- /dev/null +++ b/api/core/tools/provider/builtin/feishu_task/tools/add_members.py @@ -0,0 +1,20 @@ +from typing import Any + +from core.tools.entities.tool_entities import ToolInvokeMessage +from core.tools.tool.builtin_tool import BuiltinTool +from core.tools.utils.feishu_api_utils import FeishuRequest + + +class AddMembersTool(BuiltinTool): + def _invoke(self, user_id: str, tool_parameters: dict[str, Any]) -> ToolInvokeMessage: + app_id = self.runtime.credentials.get("app_id") + app_secret = self.runtime.credentials.get("app_secret") + client = FeishuRequest(app_id, app_secret) + + task_guid = tool_parameters.get("task_guid") + member_phone_or_email = tool_parameters.get("member_phone_or_email") + member_role = tool_parameters.get("member_role", "follower") + + res = client.add_members(task_guid, member_phone_or_email, member_role) + + return self.create_json_message(res) diff --git a/api/core/tools/provider/builtin/feishu_task/tools/add_members.yaml b/api/core/tools/provider/builtin/feishu_task/tools/add_members.yaml new file mode 100644 index 0000000000..063c0f7f04 --- /dev/null +++ b/api/core/tools/provider/builtin/feishu_task/tools/add_members.yaml @@ -0,0 +1,58 @@ +identity: + name: add_members + author: Doug Lea + label: + en_US: Add Members + zh_Hans: 添加任务成员 +description: + human: + en_US: Add Members + zh_Hans: 添加任务成员 + llm: A tool for adding members to a Feishu task.(添加任务成员) +parameters: + - name: task_guid + type: string + required: true + label: + en_US: Task GUID + zh_Hans: 任务 GUID + human_description: + en_US: | + The GUID of the task to be added, supports passing either the Task ID or the Task link URL. Example of Task ID: 8b5425ec-9f2a-43bd-a3ab-01912f50282b; Example of Task link URL: https://applink.feishu-pre.net/client/todo/detail?guid=8c6bf822-e4da-449a-b82a-dc44020f9be9&suite_entity_num=t21587362 + zh_Hans: 要添加的任务的 GUID，支持传任务 ID 和任务链接 URL。任务 ID 示例：8b5425ec-9f2a-43bd-a3ab-01912f50282b；任务链接 URL 示例：https://applink.feishu-pre.net/client/todo/detail?guid=8c6bf822-e4da-449a-b82a-dc44020f9be9&suite_entity_num=t21587362 + llm_description: 要添加的任务的 GUID，支持传任务 ID 和任务链接 URL。任务 ID 示例：8b5425ec-9f2a-43bd-a3ab-01912f50282b；任务链接 URL 示例：https://applink.feishu-pre.net/client/todo/detail?guid=8c6bf822-e4da-449a-b82a-dc44020f9be9&suite_entity_num=t21587362 + form: llm + + - name: member_phone_or_email + type: string + required: true + label: + en_US: Task Member Phone Or Email + zh_Hans: 任务成员的电话或邮箱 + human_description: + en_US: A list of member emails or phone numbers, separated by commas. + zh_Hans: 任务成员邮箱或者手机号列表，使用逗号分隔。 + llm_description: 任务成员邮箱或者手机号列表，使用逗号分隔。 + form: llm + + - name: member_role + type: select + required: true + options: + - value: assignee + label: + en_US: assignee + zh_Hans: 负责人 + - value: follower + label: + en_US: follower + zh_Hans: 关注人 + default: "follower" + label: + en_US: member_role + zh_Hans: 成员的角色 + human_description: + en_US: Member role, optional values are "assignee" (responsible person) and "follower" (observer), with a default value of "assignee". + zh_Hans: 成员的角色，可选值有 "assignee"（负责人）和 "follower"（关注人），默认值为 "assignee"。 + llm_description: 成员的角色，可选值有 "assignee"（负责人）和 "follower"（关注人），默认值为 "assignee"。 + form: form diff --git a/api/core/tools/provider/builtin/feishu_task/tools/create_task.py b/api/core/tools/provider/builtin/feishu_task/tools/create_task.py new file mode 100644 index 0000000000..96cdcd71f6 --- /dev/null +++ b/api/core/tools/provider/builtin/feishu_task/tools/create_task.py @@ -0,0 +1,22 @@ +from typing import Any + +from core.tools.entities.tool_entities import ToolInvokeMessage +from core.tools.tool.builtin_tool import BuiltinTool +from core.tools.utils.feishu_api_utils import FeishuRequest + + +class CreateTaskTool(BuiltinTool): + def _invoke(self, user_id: str, tool_parameters: dict[str, Any]) -> ToolInvokeMessage: + app_id = self.runtime.credentials.get("app_id") + app_secret = self.runtime.credentials.get("app_secret") + client = FeishuRequest(app_id, app_secret) + + summary = tool_parameters.get("summary") + start_time = tool_parameters.get("start_time") + end_time = tool_parameters.get("end_time") + completed_time = tool_parameters.get("completed_time") + description = tool_parameters.get("description") + + res = client.create_task(summary, start_time, end_time, completed_time, description) + + return self.create_json_message(res) diff --git a/api/core/tools/provider/builtin/feishu_task/tools/create_task.yaml b/api/core/tools/provider/builtin/feishu_task/tools/create_task.yaml new file mode 100644 index 0000000000..7eb4af168b --- /dev/null +++ b/api/core/tools/provider/builtin/feishu_task/tools/create_task.yaml @@ -0,0 +1,74 @@ +identity: + name: create_task + author: Doug Lea + label: + en_US: Create Task + zh_Hans: 创建飞书任务 +description: + human: + en_US: Create Feishu Task + zh_Hans: 创建飞书任务 + llm: A tool for creating tasks in Feishu.(创建飞书任务) +parameters: + - name: summary + type: string + required: true + label: + en_US: Task Title + zh_Hans: 任务标题 + human_description: + en_US: The title of the task. + zh_Hans: 任务标题 + llm_description: 任务标题 + form: llm + + - name: description + type: string + required: false + label: + en_US: Task Description + zh_Hans: 任务备注 + human_description: + en_US: The description or notes for the task. + zh_Hans: 任务备注 + llm_description: 任务备注 + form: llm + + - name: start_time + type: string + required: false + label: + en_US: Start Time + zh_Hans: 任务开始时间 + human_description: + en_US: | + The start time of the task, in the format: 2006-01-02 15:04:05 + zh_Hans: 任务开始时间，格式为：2006-01-02 15:04:05 + llm_description: 任务开始时间，格式为：2006-01-02 15:04:05 + form: llm + + - name: end_time + type: string + required: false + label: + en_US: End Time + zh_Hans: 任务结束时间 + human_description: + en_US: | + The end time of the task, in the format: 2006-01-02 15:04:05 + zh_Hans: 任务结束时间，格式为：2006-01-02 15:04:05 + llm_description: 任务结束时间，格式为：2006-01-02 15:04:05 + form: llm + + - name: completed_time + type: string + required: false + label: + en_US: Completed Time + zh_Hans: 任务完成时间 + human_description: + en_US: | + The completion time of the task, in the format: 2006-01-02 15:04:05. Leave empty to create an incomplete task; fill in a specific time to create a completed task. + zh_Hans: 任务完成时间，格式为：2006-01-02 15:04:05，不填写表示创建一个未完成任务；填写一个具体的时间表示创建一个已完成任务。 + llm_description: 任务完成时间，格式为：2006-01-02 15:04:05，不填写表示创建一个未完成任务；填写一个具体的时间表示创建一个已完成任务。 + form: llm diff --git a/api/core/tools/provider/builtin/feishu_task/tools/delete_task.py b/api/core/tools/provider/builtin/feishu_task/tools/delete_task.py new file mode 100644 index 0000000000..dee036fee5 --- /dev/null +++ b/api/core/tools/provider/builtin/feishu_task/tools/delete_task.py @@ -0,0 +1,18 @@ +from typing import Any + +from core.tools.entities.tool_entities import ToolInvokeMessage +from core.tools.tool.builtin_tool import BuiltinTool +from core.tools.utils.feishu_api_utils import FeishuRequest + + +class UpdateTaskTool(BuiltinTool): + def _invoke(self, user_id: str, tool_parameters: dict[str, Any]) -> ToolInvokeMessage: + app_id = self.runtime.credentials.get("app_id") + app_secret = self.runtime.credentials.get("app_secret") + client = FeishuRequest(app_id, app_secret) + + task_guid = tool_parameters.get("task_guid") + + res = client.delete_task(task_guid) + + return self.create_json_message(res) diff --git a/api/core/tools/provider/builtin/feishu_task/tools/delete_task.yaml b/api/core/tools/provider/builtin/feishu_task/tools/delete_task.yaml new file mode 100644 index 0000000000..d3f9741367 --- /dev/null +++ b/api/core/tools/provider/builtin/feishu_task/tools/delete_task.yaml @@ -0,0 +1,24 @@ +identity: + name: delete_task + author: Doug Lea + label: + en_US: Delete Task + zh_Hans: 删除飞书任务 +description: + human: + en_US: Delete Task + zh_Hans: 删除飞书任务 + llm: A tool for deleting tasks in Feishu.(删除飞书任务) +parameters: + - name: task_guid + type: string + required: true + label: + en_US: Task GUID + zh_Hans: 任务 GUID + human_description: + en_US: | + The GUID of the task to be deleted, supports passing either the Task ID or the Task link URL. Example of Task ID: 8b5425ec-9f2a-43bd-a3ab-01912f50282b; Example of Task link URL: https://applink.feishu-pre.net/client/todo/detail?guid=8c6bf822-e4da-449a-b82a-dc44020f9be9&suite_entity_num=t21587362 + zh_Hans: 要删除的任务的 GUID，支持传任务 ID 和任务链接 URL。任务 ID 示例：8b5425ec-9f2a-43bd-a3ab-01912f50282b；任务链接 URL 示例：https://applink.feishu-pre.net/client/todo/detail?guid=8c6bf822-e4da-449a-b82a-dc44020f9be9&suite_entity_num=t21587362 + llm_description: 要删除的任务的 GUID，支持传任务 ID 和任务链接 URL。任务 ID 示例：8b5425ec-9f2a-43bd-a3ab-01912f50282b；任务链接 URL 示例：https://applink.feishu-pre.net/client/todo/detail?guid=8c6bf822-e4da-449a-b82a-dc44020f9be9&suite_entity_num=t21587362 + form: llm diff --git a/api/core/tools/provider/builtin/feishu_task/tools/update_task.py b/api/core/tools/provider/builtin/feishu_task/tools/update_task.py new file mode 100644 index 0000000000..4a48cd283a --- /dev/null +++ b/api/core/tools/provider/builtin/feishu_task/tools/update_task.py @@ -0,0 +1,23 @@ +from typing import Any + +from core.tools.entities.tool_entities import ToolInvokeMessage +from core.tools.tool.builtin_tool import BuiltinTool +from core.tools.utils.feishu_api_utils import FeishuRequest + + +class UpdateTaskTool(BuiltinTool): + def _invoke(self, user_id: str, tool_parameters: dict[str, Any]) -> ToolInvokeMessage: + app_id = self.runtime.credentials.get("app_id") + app_secret = self.runtime.credentials.get("app_secret") + client = FeishuRequest(app_id, app_secret) + + task_guid = tool_parameters.get("task_guid") + summary = tool_parameters.get("summary") + start_time = tool_parameters.get("start_time") + end_time = tool_parameters.get("end_time") + completed_time = tool_parameters.get("completed_time") + description = tool_parameters.get("description") + + res = client.update_task(task_guid, summary, start_time, end_time, completed_time, description) + + return self.create_json_message(res) diff --git a/api/core/tools/provider/builtin/feishu_task/tools/update_task.yaml b/api/core/tools/provider/builtin/feishu_task/tools/update_task.yaml new file mode 100644 index 0000000000..83c9bcb1c4 --- /dev/null +++ b/api/core/tools/provider/builtin/feishu_task/tools/update_task.yaml @@ -0,0 +1,89 @@ +identity: + name: update_task + author: Doug Lea + label: + en_US: Update Task + zh_Hans: 更新飞书任务 +description: + human: + en_US: Update Feishu Task + zh_Hans: 更新飞书任务 + llm: A tool for updating tasks in Feishu.(更新飞书任务) +parameters: + - name: task_guid + type: string + required: true + label: + en_US: Task GUID + zh_Hans: 任务 GUID + human_description: + en_US: | + The task ID, supports inputting either the Task ID or the Task link URL. Example of Task ID: 42cad8a0-f8c8-4344-9be2-d1d7e8e91b64; Example of Task link URL: https://applink.feishu-pre.net/client/todo/detail?guid=42cad8a0-f8c8-4344-9be2-d1d7e8e91b64&suite_entity_num=t21700217 + zh_Hans: | + 任务ID，支持传入任务 ID 和任务链接 URL。任务 ID 示例: 42cad8a0-f8c8-4344-9be2-d1d7e8e91b64；任务链接 URL 示例: https://applink.feishu-pre.net/client/todo/detail?guid=42cad8a0-f8c8-4344-9be2-d1d7e8e91b64&suite_entity_num=t21700217 + llm_description: | + 任务ID，支持传入任务 ID 和任务链接 URL。任务 ID 示例: 42cad8a0-f8c8-4344-9be2-d1d7e8e91b64；任务链接 URL 示例: https://applink.feishu-pre.net/client/todo/detail?guid=42cad8a0-f8c8-4344-9be2-d1d7e8e91b64&suite_entity_num=t21700217 + form: llm + + - name: summary + type: string + required: true + label: + en_US: Task Title + zh_Hans: 任务标题 + human_description: + en_US: The title of the task. + zh_Hans: 任务标题 + llm_description: 任务标题 + form: llm + + - name: description + type: string + required: false + label: + en_US: Task Description + zh_Hans: 任务备注 + human_description: + en_US: The description or notes for the task. + zh_Hans: 任务备注 + llm_description: 任务备注 + form: llm + + - name: start_time + type: string + required: false + label: + en_US: Start Time + zh_Hans: 任务开始时间 + human_description: + en_US: | + The start time of the task, in the format: 2006-01-02 15:04:05 + zh_Hans: 任务开始时间，格式为：2006-01-02 15:04:05 + llm_description: 任务开始时间，格式为：2006-01-02 15:04:05 + form: llm + + - name: end_time + type: string + required: false + label: + en_US: End Time + zh_Hans: 任务结束时间 + human_description: + en_US: | + The end time of the task, in the format: 2006-01-02 15:04:05 + zh_Hans: 任务结束时间，格式为：2006-01-02 15:04:05 + llm_description: 任务结束时间，格式为：2006-01-02 15:04:05 + form: llm + + - name: completed_time + type: string + required: false + label: + en_US: Completed Time + zh_Hans: 任务完成时间 + human_description: + en_US: | + The completion time of the task, in the format: 2006-01-02 15:04:05 + zh_Hans: 任务完成时间，格式为：2006-01-02 15:04:05 + llm_description: 任务完成时间，格式为：2006-01-02 15:04:05 + form: llm diff --git a/api/core/tools/provider/builtin/feishu_wiki/_assets/icon.png b/api/core/tools/provider/builtin/feishu_wiki/_assets/icon.png new file mode 100644 index 0000000000..878672c9ae Binary files /dev/null and b/api/core/tools/provider/builtin/feishu_wiki/_assets/icon.png differ diff --git a/api/core/tools/provider/builtin/feishu_wiki/feishu_wiki.py b/api/core/tools/provider/builtin/feishu_wiki/feishu_wiki.py new file mode 100644 index 0000000000..6c5fccb1a3 --- /dev/null +++ b/api/core/tools/provider/builtin/feishu_wiki/feishu_wiki.py @@ -0,0 +1,7 @@ +from core.tools.provider.builtin_tool_provider import BuiltinToolProviderController +from core.tools.utils.feishu_api_utils import auth + + +class FeishuWikiProvider(BuiltinToolProviderController): + def _validate_credentials(self, credentials: dict) -> None: + auth(credentials) diff --git a/api/core/tools/provider/builtin/feishu_wiki/feishu_wiki.yaml b/api/core/tools/provider/builtin/feishu_wiki/feishu_wiki.yaml new file mode 100644 index 0000000000..1fb5f71cbc --- /dev/null +++ b/api/core/tools/provider/builtin/feishu_wiki/feishu_wiki.yaml @@ -0,0 +1,36 @@ +identity: + author: Doug Lea + name: feishu_wiki + label: + en_US: Feishu Wiki + zh_Hans: 飞书知识库 + description: + en_US: | + Feishu Wiki, requires the following permissions: wiki:wiki:readonly. + zh_Hans: | + 飞书知识库，需要开通以下权限: wiki:wiki:readonly。 + icon: icon.png + tags: + - social + - productivity +credentials_for_provider: + app_id: + type: text-input + required: true + label: + en_US: APP ID + placeholder: + en_US: Please input your feishu app id + zh_Hans: 请输入你的飞书 app id + help: + en_US: Get your app_id and app_secret from Feishu + zh_Hans: 从飞书获取您的 app_id 和 app_secret + url: https://open.larkoffice.com/app + app_secret: + type: secret-input + required: true + label: + en_US: APP Secret + placeholder: + en_US: Please input your app secret + zh_Hans: 请输入你的飞书 app secret diff --git a/api/core/tools/provider/builtin/feishu_wiki/tools/get_wiki_nodes.py b/api/core/tools/provider/builtin/feishu_wiki/tools/get_wiki_nodes.py new file mode 100644 index 0000000000..374b4c9a7d --- /dev/null +++ b/api/core/tools/provider/builtin/feishu_wiki/tools/get_wiki_nodes.py @@ -0,0 +1,21 @@ +from typing import Any + +from core.tools.entities.tool_entities import ToolInvokeMessage +from core.tools.tool.builtin_tool import BuiltinTool +from core.tools.utils.feishu_api_utils import FeishuRequest + + +class GetWikiNodesTool(BuiltinTool): + def _invoke(self, user_id: str, tool_parameters: dict[str, Any]) -> ToolInvokeMessage: + app_id = self.runtime.credentials.get("app_id") + app_secret = self.runtime.credentials.get("app_secret") + client = FeishuRequest(app_id, app_secret) + + space_id = tool_parameters.get("space_id") + parent_node_token = tool_parameters.get("parent_node_token") + page_token = tool_parameters.get("page_token") + page_size = tool_parameters.get("page_size") + + res = client.get_wiki_nodes(space_id, parent_node_token, page_token, page_size) + + return self.create_json_message(res) diff --git a/api/core/tools/provider/builtin/feishu_wiki/tools/get_wiki_nodes.yaml b/api/core/tools/provider/builtin/feishu_wiki/tools/get_wiki_nodes.yaml new file mode 100644 index 0000000000..7d6ac3c824 --- /dev/null +++ b/api/core/tools/provider/builtin/feishu_wiki/tools/get_wiki_nodes.yaml @@ -0,0 +1,63 @@ +identity: + name: get_wiki_nodes + author: Doug Lea + label: + en_US: Get Wiki Nodes + zh_Hans: 获取知识空间子节点列表 +description: + human: + en_US: | + Get the list of child nodes in Wiki, make sure the app/bot is a member of the wiki space. See How to add an app as a wiki base administrator (member). https://open.feishu.cn/document/server-docs/docs/wiki-v2/wiki-qa + zh_Hans: | + 获取知识库全部子节点列表，请确保应用/机器人为知识空间成员。参阅如何将应用添加为知识库管理员（成员）。https://open.feishu.cn/document/server-docs/docs/wiki-v2/wiki-qa + llm: A tool for getting all sub-nodes of a knowledge base.(获取知识空间子节点列表) +parameters: + - name: space_id + type: string + required: true + label: + en_US: Space Id + zh_Hans: 知识空间 ID + human_description: + en_US: | + The ID of the knowledge space. Supports space link URL, for example: https://svi136aogf123.feishu.cn/wiki/settings/7166950623940706332 + zh_Hans: 知识空间 ID，支持空间链接 URL，例如：https://svi136aogf123.feishu.cn/wiki/settings/7166950623940706332 + llm_description: 知识空间 ID，支持空间链接 URL，例如：https://svi136aogf123.feishu.cn/wiki/settings/7166950623940706332 + form: llm + + - name: page_size + type: number + required: false + default: 10 + label: + en_US: Page Size + zh_Hans: 分页大小 + human_description: + en_US: The size of each page, with a maximum value of 50. + zh_Hans: 分页大小，最大值 50。 + llm_description: 分页大小，最大值 50。 + form: llm + + - name: page_token + type: string + required: false + label: + en_US: Page Token + zh_Hans: 分页标记 + human_description: + en_US: The pagination token. Leave empty for the first request to start from the beginning; if the paginated query result has more items, a new page_token will be returned, which can be used to get the next set of results. + zh_Hans: 分页标记，第一次请求不填，表示从头开始遍历；分页查询结果还有更多项时会同时返回新的 page_token，下次遍历可采用该 page_token 获取查询结果。 + llm_description: 分页标记，第一次请求不填，表示从头开始遍历；分页查询结果还有更多项时会同时返回新的 page_token，下次遍历可采用该 page_token 获取查询结果。 + form: llm + + - name: parent_node_token + type: string + required: false + label: + en_US: Parent Node Token + zh_Hans: 父节点 token + human_description: + en_US: The token of the parent node. + zh_Hans: 父节点 token + llm_description: 父节点 token + form: llm diff --git a/api/core/tools/utils/feishu_api_utils.py b/api/core/tools/utils/feishu_api_utils.py index ffdb06498f..ce1fd7dc19 100644 --- a/api/core/tools/utils/feishu_api_utils.py +++ b/api/core/tools/utils/feishu_api_utils.py @@ -1,9 +1,23 @@ import httpx +from core.tools.errors import ToolProviderCredentialValidationError from extensions.ext_redis import redis_client +def auth(credentials): + app_id = credentials.get("app_id") + app_secret = credentials.get("app_secret") + if not app_id or not app_secret: + raise ToolProviderCredentialValidationError("app_id and app_secret is required") + try: + assert FeishuRequest(app_id, app_secret).tenant_access_token is not None + except Exception as e: + raise ToolProviderCredentialValidationError(str(e)) + + class FeishuRequest: + API_BASE_URL = "https://lark-plugin-api.solutionsuite.cn/lark-plugin" + def __init__(self, app_id: str, app_secret: str): self.app_id = app_id self.app_secret = app_secret @@ -42,7 +56,7 @@ class FeishuRequest: "expire": 7200 } """ - url = "https://lark-plugin-api.solutionsuite.cn/lark-plugin/access_token/get_tenant_access_token" + url = f"{self.API_BASE_URL}/access_token/get_tenant_access_token" payload = {"app_id": app_id, "app_secret": app_secret} res = self._send_request(url, require_token=False, payload=payload) return res @@ -63,7 +77,7 @@ class FeishuRequest: "msg": "创建飞书文档成功，请查看" } """ - url = "https://lark-plugin-api.solutionsuite.cn/lark-plugin/document/create_document" + url = f"{self.API_BASE_URL}/document/create_document" payload = { "title": title, "content": content, @@ -72,13 +86,13 @@ class FeishuRequest: res = self._send_request(url, payload=payload) return res.get("data") - def write_document(self, document_id: str, content: str, position: str = "start") -> dict: - url = "https://lark-plugin-api.solutionsuite.cn/lark-plugin/document/write_document" + def write_document(self, document_id: str, content: str, position: str = "end") -> dict: + url = f"{self.API_BASE_URL}/document/write_document" payload = {"document_id": document_id, "content": content, "position": position} res = self._send_request(url, payload=payload) return res - def get_document_content(self, document_id: str, mode: str, lang: int = 0) -> dict: + def get_document_content(self, document_id: str, mode: str = "markdown", lang: str = "0") -> dict: """ API url: https://open.larkoffice.com/document/server-docs/docs/docs/docx-v1/document/raw_content Example Response: @@ -95,45 +109,404 @@ class FeishuRequest: "mode": mode, "lang": lang, } - url = "https://lark-plugin-api.solutionsuite.cn/lark-plugin/document/get_document_content" - res = self._send_request(url, method="get", params=params) + url = f"{self.API_BASE_URL}/document/get_document_content" + res = self._send_request(url, method="GET", params=params) return res.get("data").get("content") - def list_document_blocks(self, document_id: str, page_token: str, page_size: int = 500) -> dict: + def list_document_blocks( + self, document_id: str, page_token: str, user_id_type: str = "open_id", page_size: int = 500 + ) -> dict: """ API url: https://open.larkoffice.com/document/server-docs/docs/docs/docx-v1/document/list """ - url = "https://lark-plugin-api.solutionsuite.cn/lark-plugin/document/list_document_blocks" params = { + "user_id_type": user_id_type, "document_id": document_id, "page_size": page_size, "page_token": page_token, } - res = self._send_request(url, method="get", params=params) + url = f"{self.API_BASE_URL}/document/list_document_blocks" + res = self._send_request(url, method="GET", params=params) return res.get("data") def send_bot_message(self, receive_id_type: str, receive_id: str, msg_type: str, content: str) -> dict: """ API url: https://open.larkoffice.com/document/server-docs/im-v1/message/create """ - url = "https://lark-plugin-api.solutionsuite.cn/lark-plugin/message/send_bot_message" + url = f"{self.API_BASE_URL}/message/send_bot_message" params = { "receive_id_type": receive_id_type, } payload = { "receive_id": receive_id, "msg_type": msg_type, - "content": content, + "content": content.strip('"').replace(r"\"", '"').replace(r"\\", "\\"), } res = self._send_request(url, params=params, payload=payload) return res.get("data") def send_webhook_message(self, webhook: str, msg_type: str, content: str) -> dict: - url = "https://lark-plugin-api.solutionsuite.cn/lark-plugin/message/send_webhook_message" + url = f"{self.API_BASE_URL}/message/send_webhook_message" payload = { "webhook": webhook, "msg_type": msg_type, - "content": content, + "content": content.strip('"').replace(r"\"", '"').replace(r"\\", "\\"), } res = self._send_request(url, require_token=False, payload=payload) return res + + def get_chat_messages( + self, + container_id: str, + start_time: str, + end_time: str, + page_token: str, + sort_type: str = "ByCreateTimeAsc", + page_size: int = 20, + ) -> dict: + """ + API url: https://open.larkoffice.com/document/server-docs/im-v1/message/list + """ + url = f"{self.API_BASE_URL}/message/get_chat_messages" + params = { + "container_id": container_id, + "start_time": start_time, + "end_time": end_time, + "sort_type": sort_type, + "page_token": page_token, + "page_size": page_size, + } + res = self._send_request(url, method="GET", params=params) + return res.get("data") + + def get_thread_messages( + self, container_id: str, page_token: str, sort_type: str = "ByCreateTimeAsc", page_size: int = 20 + ) -> dict: + """ + API url: https://open.larkoffice.com/document/server-docs/im-v1/message/list + """ + url = f"{self.API_BASE_URL}/message/get_thread_messages" + params = { + "container_id": container_id, + "sort_type": sort_type, + "page_token": page_token, + "page_size": page_size, + } + res = self._send_request(url, method="GET", params=params) + return res.get("data") + + def create_task(self, summary: str, start_time: str, end_time: str, completed_time: str, description: str) -> dict: + # 创建任务 + url = f"{self.API_BASE_URL}/task/create_task" + payload = { + "summary": summary, + "start_time": start_time, + "end_time": end_time, + "completed_at": completed_time, + "description": description, + } + res = self._send_request(url, payload=payload) + return res.get("data") + + def update_task( + self, task_guid: str, summary: str, start_time: str, end_time: str, completed_time: str, description: str + ) -> dict: + # 更新任务 + url = f"{self.API_BASE_URL}/task/update_task" + payload = { + "task_guid": task_guid, + "summary": summary, + "start_time": start_time, + "end_time": end_time, + "completed_time": completed_time, + "description": description, + } + res = self._send_request(url, method="PATCH", payload=payload) + return res.get("data") + + def delete_task(self, task_guid: str) -> dict: + # 删除任务 + url = f"{self.API_BASE_URL}/task/delete_task" + payload = { + "task_guid": task_guid, + } + res = self._send_request(url, method="DELETE", payload=payload) + return res + + def add_members(self, task_guid: str, member_phone_or_email: str, member_role: str) -> dict: + # 删除任务 + url = f"{self.API_BASE_URL}/task/add_members" + payload = { + "task_guid": task_guid, + "member_phone_or_email": member_phone_or_email, + "member_role": member_role, + } + res = self._send_request(url, payload=payload) + return res + + def get_wiki_nodes(self, space_id: str, parent_node_token: str, page_token: str, page_size: int = 20) -> dict: + # 获取知识库全部子节点列表 + url = f"{self.API_BASE_URL}/wiki/get_wiki_nodes" + payload = { + "space_id": space_id, + "parent_node_token": parent_node_token, + "page_token": page_token, + "page_size": page_size, + } + res = self._send_request(url, payload=payload) + return res.get("data") + + def get_primary_calendar(self, user_id_type: str = "open_id") -> dict: + url = f"{self.API_BASE_URL}/calendar/get_primary_calendar" + params = { + "user_id_type": user_id_type, + } + res = self._send_request(url, method="GET", params=params) + return res.get("data") + + def create_event( + self, + summary: str, + description: str, + start_time: str, + end_time: str, + attendee_ability: str, + need_notification: bool = True, + auto_record: bool = False, + ) -> dict: + url = f"{self.API_BASE_URL}/calendar/create_event" + payload = { + "summary": summary, + "description": description, + "need_notification": need_notification, + "start_time": start_time, + "end_time": end_time, + "auto_record": auto_record, + "attendee_ability": attendee_ability, + } + res = self._send_request(url, payload=payload) + return res.get("data") + + def update_event( + self, + event_id: str, + summary: str, + description: str, + need_notification: bool, + start_time: str, + end_time: str, + auto_record: bool, + ) -> dict: + url = f"{self.API_BASE_URL}/calendar/update_event/{event_id}" + payload = {} + if summary: + payload["summary"] = summary + if description: + payload["description"] = description + if start_time: + payload["start_time"] = start_time + if end_time: + payload["end_time"] = end_time + if need_notification: + payload["need_notification"] = need_notification + if auto_record: + payload["auto_record"] = auto_record + res = self._send_request(url, method="PATCH", payload=payload) + return res + + def delete_event(self, event_id: str, need_notification: bool = True) -> dict: + url = f"{self.API_BASE_URL}/calendar/delete_event/{event_id}" + params = { + "need_notification": need_notification, + } + res = self._send_request(url, method="DELETE", params=params) + return res + + def list_events(self, start_time: str, end_time: str, page_token: str, page_size: int = 50) -> dict: + url = f"{self.API_BASE_URL}/calendar/list_events" + params = { + "start_time": start_time, + "end_time": end_time, + "page_token": page_token, + "page_size": page_size, + } + res = self._send_request(url, method="GET", params=params) + return res.get("data") + + def search_events( + self, + query: str, + start_time: str, + end_time: str, + page_token: str, + user_id_type: str = "open_id", + page_size: int = 20, + ) -> dict: + url = f"{self.API_BASE_URL}/calendar/search_events" + payload = { + "query": query, + "start_time": start_time, + "end_time": end_time, + "page_token": page_token, + "user_id_type": user_id_type, + "page_size": page_size, + } + res = self._send_request(url, payload=payload) + return res.get("data") + + def add_event_attendees(self, event_id: str, attendee_phone_or_email: str, need_notification: bool = True) -> dict: + # 参加日程参会人 + url = f"{self.API_BASE_URL}/calendar/add_event_attendees" + payload = { + "event_id": event_id, + "attendee_phone_or_email": attendee_phone_or_email, + "need_notification": need_notification, + } + res = self._send_request(url, payload=payload) + return res.get("data") + + def create_spreadsheet( + self, + title: str, + folder_token: str, + ) -> dict: + # 创建电子表格 + url = f"{self.API_BASE_URL}/spreadsheet/create_spreadsheet" + payload = { + "title": title, + "folder_token": folder_token, + } + res = self._send_request(url, payload=payload) + return res.get("data") + + def get_spreadsheet( + self, + spreadsheet_token: str, + user_id_type: str = "open_id", + ) -> dict: + # 获取电子表格信息 + url = f"{self.API_BASE_URL}/spreadsheet/get_spreadsheet" + params = { + "spreadsheet_token": spreadsheet_token, + "user_id_type": user_id_type, + } + res = self._send_request(url, method="GET", params=params) + return res.get("data") + + def list_spreadsheet_sheets( + self, + spreadsheet_token: str, + ) -> dict: + # 列出电子表格的所有工作表 + url = f"{self.API_BASE_URL}/spreadsheet/list_spreadsheet_sheets" + params = { + "spreadsheet_token": spreadsheet_token, + } + res = self._send_request(url, method="GET", params=params) + return res.get("data") + + def add_rows( + self, + spreadsheet_token: str, + sheet_id: str, + sheet_name: str, + length: int, + values: str, + ) -> dict: + # 增加行,在工作表最后添加 + url = f"{self.API_BASE_URL}/spreadsheet/add_rows" + payload = { + "spreadsheet_token": spreadsheet_token, + "sheet_id": sheet_id, + "sheet_name": sheet_name, + "length": length, + "values": values, + } + res = self._send_request(url, payload=payload) + return res.get("data") + + def add_cols( + self, + spreadsheet_token: str, + sheet_id: str, + sheet_name: str, + length: int, + values: str, + ) -> dict: + # 增加列,在工作表最后添加 + url = f"{self.API_BASE_URL}/spreadsheet/add_cols" + payload = { + "spreadsheet_token": spreadsheet_token, + "sheet_id": sheet_id, + "sheet_name": sheet_name, + "length": length, + "values": values, + } + res = self._send_request(url, payload=payload) + return res.get("data") + + def read_rows( + self, + spreadsheet_token: str, + sheet_id: str, + sheet_name: str, + start_row: int, + num_rows: int, + user_id_type: str = "open_id", + ) -> dict: + # 读取工作表行数据 + url = f"{self.API_BASE_URL}/spreadsheet/read_rows" + params = { + "spreadsheet_token": spreadsheet_token, + "sheet_id": sheet_id, + "sheet_name": sheet_name, + "start_row": start_row, + "num_rows": num_rows, + "user_id_type": user_id_type, + } + res = self._send_request(url, method="GET", params=params) + return res.get("data") + + def read_cols( + self, + spreadsheet_token: str, + sheet_id: str, + sheet_name: str, + start_col: int, + num_cols: int, + user_id_type: str = "open_id", + ) -> dict: + # 读取工作表列数据 + url = f"{self.API_BASE_URL}/spreadsheet/read_cols" + params = { + "spreadsheet_token": spreadsheet_token, + "sheet_id": sheet_id, + "sheet_name": sheet_name, + "start_col": start_col, + "num_cols": num_cols, + "user_id_type": user_id_type, + } + res = self._send_request(url, method="GET", params=params) + return res.get("data") + + def read_table( + self, + spreadsheet_token: str, + sheet_id: str, + sheet_name: str, + num_range: str, + query: str, + user_id_type: str = "open_id", + ) -> dict: + # 自定义读取行列数据 + url = f"{self.API_BASE_URL}/spreadsheet/read_table" + params = { + "spreadsheet_token": spreadsheet_token, + "sheet_id": sheet_id, + "sheet_name": sheet_name, + "range": num_range, + "query": query, + "user_id_type": user_id_type, + } + res = self._send_request(url, method="GET", params=params) + return res.get("data") diff --git a/api/core/workflow/nodes/knowledge_retrieval/knowledge_retrieval_node.py b/api/core/workflow/nodes/knowledge_retrieval/knowledge_retrieval_node.py index af55688a52..c08dc143a6 100644 --- a/api/core/workflow/nodes/knowledge_retrieval/knowledge_retrieval_node.py +++ b/api/core/workflow/nodes/knowledge_retrieval/knowledge_retrieval_node.py @@ -156,16 +156,34 @@ class KnowledgeRetrievalNode(BaseNode): weights, node_data.multiple_retrieval_config.reranking_enable, ) - - context_list = [] - if all_documents: + dify_documents = [item for item in all_documents if item.provider == "dify"] + external_documents = [item for item in all_documents if item.provider == "external"] + retrieval_resource_list = [] + # deal with external documents + for item in external_documents: + source = { + "metadata": { + "_source": "knowledge", + "dataset_id": item.metadata.get("dataset_id"), + "dataset_name": item.metadata.get("dataset_name"), + "document_name": item.metadata.get("title"), + "data_source_type": "external", + "retriever_from": "workflow", + "score": item.metadata.get("score"), + }, + "title": item.metadata.get("title"), + "content": item.page_content, + } + retrieval_resource_list.append(source) + document_score_list = {} + # deal with dify documents + if dify_documents: document_score_list = {} - page_number_list = {} - for item in all_documents: + for item in dify_documents: if item.metadata.get("score"): document_score_list[item.metadata["doc_id"]] = item.metadata["score"] - index_node_ids = [document.metadata["doc_id"] for document in all_documents] + index_node_ids = [document.metadata["doc_id"] for document in dify_documents] segments = DocumentSegment.query.filter( DocumentSegment.dataset_id.in_(dataset_ids), DocumentSegment.completed_at.isnot(None), @@ -186,13 +204,10 @@ class KnowledgeRetrievalNode(BaseNode): Document.enabled == True, Document.archived == False, ).first() - - resource_number = 1 if dataset and document: source = { "metadata": { "_source": "knowledge", - "position": resource_number, "dataset_id": dataset.id, "dataset_name": dataset.name, "document_id": document.id, @@ -212,9 +227,14 @@ class KnowledgeRetrievalNode(BaseNode): source["content"] = f"question:{segment.get_sign_content()} \nanswer:{segment.answer}" else: source["content"] = segment.get_sign_content() - context_list.append(source) - resource_number += 1 - return context_list + retrieval_resource_list.append(source) + if retrieval_resource_list: + retrieval_resource_list = sorted(retrieval_resource_list, key=lambda x: x.get("score"), reverse=True) + position = 1 + for item in retrieval_resource_list: + item["metadata"]["position"] = position + position += 1 + return retrieval_resource_list @classmethod def _extract_variable_selector_to_variable_mapping( diff --git a/api/events/event_handlers/create_document_index.py b/api/events/event_handlers/create_document_index.py index 54f6a76e16..5af45e1e50 100644 --- a/api/events/event_handlers/create_document_index.py +++ b/api/events/event_handlers/create_document_index.py @@ -14,7 +14,7 @@ from models.dataset import Document @document_index_created.connect def handle(sender, **kwargs): dataset_id = sender - document_ids = kwargs.get("document_ids", None) + document_ids = kwargs.get("document_ids") documents = [] start_at = time.perf_counter() for document_id in document_ids: diff --git a/api/fields/dataset_fields.py b/api/fields/dataset_fields.py index 9cf8da7acd..b32423f10c 100644 --- a/api/fields/dataset_fields.py +++ b/api/fields/dataset_fields.py @@ -38,9 +38,20 @@ dataset_retrieval_model_fields = { "score_threshold_enabled": fields.Boolean, "score_threshold": fields.Float, } +external_retrieval_model_fields = { + "top_k": fields.Integer, + "score_threshold": fields.Float, +} tag_fields = {"id": fields.String, "name": fields.String, "type": fields.String} +external_knowledge_info_fields = { + "external_knowledge_id": fields.String, + "external_knowledge_api_id": fields.String, + "external_knowledge_api_name": fields.String, + "external_knowledge_api_endpoint": fields.String, +} + dataset_detail_fields = { "id": fields.String, "name": fields.String, @@ -61,6 +72,8 @@ dataset_detail_fields = { "embedding_available": fields.Boolean, "retrieval_model_dict": fields.Nested(dataset_retrieval_model_fields), "tags": fields.List(fields.Nested(tag_fields)), + "external_knowledge_info": fields.Nested(external_knowledge_info_fields), + "external_retrieval_model": fields.Nested(external_retrieval_model_fields, allow_null=True), } dataset_query_detail_fields = { diff --git a/api/fields/external_dataset_fields.py b/api/fields/external_dataset_fields.py new file mode 100644 index 0000000000..2281460fe2 --- /dev/null +++ b/api/fields/external_dataset_fields.py @@ -0,0 +1,11 @@ +from flask_restful import fields + +from libs.helper import TimestampField + +external_knowledge_api_query_detail_fields = { + "id": fields.String, + "name": fields.String, + "setting": fields.String, + "created_by": fields.String, + "created_at": TimestampField, +} diff --git a/api/migrations/versions/2024_09_24_0922-6af6a521a53e_update_retrieval_resource.py b/api/migrations/versions/2024_09_24_0922-6af6a521a53e_update_retrieval_resource.py new file mode 100644 index 0000000000..5337b340db --- /dev/null +++ b/api/migrations/versions/2024_09_24_0922-6af6a521a53e_update_retrieval_resource.py @@ -0,0 +1,48 @@ +"""update-retrieval-resource + +Revision ID: 6af6a521a53e +Revises: ec3df697ebbb +Create Date: 2024-09-24 09:22:43.570120 + +""" +from alembic import op +import models as models +import sqlalchemy as sa +from sqlalchemy.dialects import postgresql + +# revision identifiers, used by Alembic. +revision = '6af6a521a53e' +down_revision = 'd57ba9ebb251' +branch_labels = None +depends_on = None + + +def upgrade(): + # ### commands auto generated by Alembic - please adjust! ### + with op.batch_alter_table('dataset_retriever_resources', schema=None) as batch_op: + batch_op.alter_column('document_id', + existing_type=sa.UUID(), + nullable=True) + batch_op.alter_column('data_source_type', + existing_type=sa.TEXT(), + nullable=True) + batch_op.alter_column('segment_id', + existing_type=sa.UUID(), + nullable=True) + # ### end Alembic commands ### + + +def downgrade(): + # ### commands auto generated by Alembic - please adjust! ### + with op.batch_alter_table('dataset_retriever_resources', schema=None) as batch_op: + batch_op.alter_column('segment_id', + existing_type=sa.UUID(), + nullable=False) + batch_op.alter_column('data_source_type', + existing_type=sa.TEXT(), + nullable=False) + batch_op.alter_column('document_id', + existing_type=sa.UUID(), + nullable=False) + + # ### end Alembic commands ### diff --git a/api/migrations/versions/2024_09_25_0434-33f5fac87f29_external_knowledge_api.py b/api/migrations/versions/2024_09_25_0434-33f5fac87f29_external_knowledge_api.py new file mode 100644 index 0000000000..3cb76e72c1 --- /dev/null +++ b/api/migrations/versions/2024_09_25_0434-33f5fac87f29_external_knowledge_api.py @@ -0,0 +1,73 @@ +"""external_knowledge_api + +Revision ID: 33f5fac87f29 +Revises: 6af6a521a53e +Create Date: 2024-09-25 04:34:57.249436 + +""" +from alembic import op +import models as models +import sqlalchemy as sa +from sqlalchemy.dialects import postgresql + +# revision identifiers, used by Alembic. +revision = '33f5fac87f29' +down_revision = '6af6a521a53e' +branch_labels = None +depends_on = None + + +def upgrade(): + # ### commands auto generated by Alembic - please adjust! ### + op.create_table('external_knowledge_apis', + sa.Column('id', models.types.StringUUID(), server_default=sa.text('uuid_generate_v4()'), nullable=False), + sa.Column('name', sa.String(length=255), nullable=False), + sa.Column('description', sa.String(length=255), nullable=False), + sa.Column('tenant_id', models.types.StringUUID(), nullable=False), + sa.Column('settings', sa.Text(), nullable=True), + sa.Column('created_by', models.types.StringUUID(), nullable=False), + sa.Column('created_at', sa.DateTime(), server_default=sa.text('CURRENT_TIMESTAMP(0)'), nullable=False), + sa.Column('updated_by', models.types.StringUUID(), nullable=True), + sa.Column('updated_at', sa.DateTime(), server_default=sa.text('CURRENT_TIMESTAMP(0)'), nullable=False), + sa.PrimaryKeyConstraint('id', name='external_knowledge_apis_pkey') + ) + with op.batch_alter_table('external_knowledge_apis', schema=None) as batch_op: + batch_op.create_index('external_knowledge_apis_name_idx', ['name'], unique=False) + batch_op.create_index('external_knowledge_apis_tenant_idx', ['tenant_id'], unique=False) + + op.create_table('external_knowledge_bindings', + sa.Column('id', models.types.StringUUID(), server_default=sa.text('uuid_generate_v4()'), nullable=False), + sa.Column('tenant_id', models.types.StringUUID(), nullable=False), + sa.Column('external_knowledge_api_id', models.types.StringUUID(), nullable=False), + sa.Column('dataset_id', models.types.StringUUID(), nullable=False), + sa.Column('external_knowledge_id', sa.Text(), nullable=False), + sa.Column('created_by', models.types.StringUUID(), nullable=False), + sa.Column('created_at', sa.DateTime(), server_default=sa.text('CURRENT_TIMESTAMP(0)'), nullable=False), + sa.Column('updated_by', models.types.StringUUID(), nullable=True), + sa.Column('updated_at', sa.DateTime(), server_default=sa.text('CURRENT_TIMESTAMP(0)'), nullable=False), + sa.PrimaryKeyConstraint('id', name='external_knowledge_bindings_pkey') + ) + with op.batch_alter_table('external_knowledge_bindings', schema=None) as batch_op: + batch_op.create_index('external_knowledge_bindings_dataset_idx', ['dataset_id'], unique=False) + batch_op.create_index('external_knowledge_bindings_external_knowledge_api_idx', ['external_knowledge_api_id'], unique=False) + batch_op.create_index('external_knowledge_bindings_external_knowledge_idx', ['external_knowledge_id'], unique=False) + batch_op.create_index('external_knowledge_bindings_tenant_idx', ['tenant_id'], unique=False) + + # ### end Alembic commands ### + + +def downgrade(): + # ### commands auto generated by Alembic - please adjust! ### + with op.batch_alter_table('external_knowledge_bindings', schema=None) as batch_op: + batch_op.drop_index('external_knowledge_bindings_tenant_idx') + batch_op.drop_index('external_knowledge_bindings_external_knowledge_idx') + batch_op.drop_index('external_knowledge_bindings_external_knowledge_api_idx') + batch_op.drop_index('external_knowledge_bindings_dataset_idx') + + op.drop_table('external_knowledge_bindings') + with op.batch_alter_table('external_knowledge_apis', schema=None) as batch_op: + batch_op.drop_index('external_knowledge_apis_tenant_idx') + batch_op.drop_index('external_knowledge_apis_name_idx') + + op.drop_table('external_knowledge_apis') + # ### end Alembic commands ### diff --git a/api/migrations/versions/fca025d3b60f_add_dataset_retrival_model.py b/api/migrations/versions/fca025d3b60f_add_dataset_retrival_model.py index 1f8250c3eb..52495be60a 100644 --- a/api/migrations/versions/fca025d3b60f_add_dataset_retrival_model.py +++ b/api/migrations/versions/fca025d3b60f_add_dataset_retrival_model.py @@ -1,4 +1,4 @@ -"""add-dataset-retrival-model +"""add-dataset-retrieval-model Revision ID: fca025d3b60f Revises: b3a09c049e8e diff --git a/api/models/dataset.py b/api/models/dataset.py index a2d2a3454d..4224ee5e9c 100644 --- a/api/models/dataset.py +++ b/api/models/dataset.py @@ -38,6 +38,7 @@ class Dataset(db.Model): ) INDEXING_TECHNIQUE_LIST = ["high_quality", "economy", None] + PROVIDER_LIST = ["vendor", "external", None] id = db.Column(StringUUID, server_default=db.text("uuid_generate_v4()")) tenant_id = db.Column(StringUUID, nullable=False) @@ -71,6 +72,14 @@ class Dataset(db.Model): def index_struct_dict(self): return json.loads(self.index_struct) if self.index_struct else None + @property + def external_retrieval_model(self): + default_retrieval_model = { + "top_k": 2, + "score_threshold": 0.0, + } + return self.retrieval_model or default_retrieval_model + @property def created_by_account(self): return db.session.get(Account, self.created_by) @@ -162,6 +171,29 @@ class Dataset(db.Model): return tags or [] + @property + def external_knowledge_info(self): + if self.provider != "external": + return None + external_knowledge_binding = ( + db.session.query(ExternalKnowledgeBindings).filter(ExternalKnowledgeBindings.dataset_id == self.id).first() + ) + if not external_knowledge_binding: + return None + external_knowledge_api = ( + db.session.query(ExternalKnowledgeApis) + .filter(ExternalKnowledgeApis.id == external_knowledge_binding.external_knowledge_api_id) + .first() + ) + if not external_knowledge_api: + return None + return { + "external_knowledge_id": external_knowledge_binding.external_knowledge_id, + "external_knowledge_api_id": external_knowledge_api.id, + "external_knowledge_api_name": external_knowledge_api.name, + "external_knowledge_api_endpoint": json.loads(external_knowledge_api.settings).get("endpoint", ""), + } + @staticmethod def gen_collection_name_by_id(dataset_id: str) -> str: normalized_dataset_id = dataset_id.replace("-", "_") @@ -687,3 +719,77 @@ class DatasetPermission(db.Model): tenant_id = db.Column(StringUUID, nullable=False) has_permission = db.Column(db.Boolean, nullable=False, server_default=db.text("true")) created_at = db.Column(db.DateTime, nullable=False, server_default=db.text("CURRENT_TIMESTAMP(0)")) + + +class ExternalKnowledgeApis(db.Model): + __tablename__ = "external_knowledge_apis" + __table_args__ = ( + db.PrimaryKeyConstraint("id", name="external_knowledge_apis_pkey"), + db.Index("external_knowledge_apis_tenant_idx", "tenant_id"), + db.Index("external_knowledge_apis_name_idx", "name"), + ) + + id = db.Column(StringUUID, nullable=False, server_default=db.text("uuid_generate_v4()")) + name = db.Column(db.String(255), nullable=False) + description = db.Column(db.String(255), nullable=False) + tenant_id = db.Column(StringUUID, nullable=False) + settings = db.Column(db.Text, nullable=True) + created_by = db.Column(StringUUID, nullable=False) + created_at = db.Column(db.DateTime, nullable=False, server_default=db.text("CURRENT_TIMESTAMP(0)")) + updated_by = db.Column(StringUUID, nullable=True) + updated_at = db.Column(db.DateTime, nullable=False, server_default=db.text("CURRENT_TIMESTAMP(0)")) + + def to_dict(self): + return { + "id": self.id, + "tenant_id": self.tenant_id, + "name": self.name, + "description": self.description, + "settings": self.settings_dict, + "dataset_bindings": self.dataset_bindings, + "created_by": self.created_by, + "created_at": self.created_at.isoformat(), + } + + @property + def settings_dict(self): + try: + return json.loads(self.settings) if self.settings else None + except JSONDecodeError: + return None + + @property + def dataset_bindings(self): + external_knowledge_bindings = ( + db.session.query(ExternalKnowledgeBindings) + .filter(ExternalKnowledgeBindings.external_knowledge_api_id == self.id) + .all() + ) + dataset_ids = [binding.dataset_id for binding in external_knowledge_bindings] + datasets = db.session.query(Dataset).filter(Dataset.id.in_(dataset_ids)).all() + dataset_bindings = [] + for dataset in datasets: + dataset_bindings.append({"id": dataset.id, "name": dataset.name}) + + return dataset_bindings + + +class ExternalKnowledgeBindings(db.Model): + __tablename__ = "external_knowledge_bindings" + __table_args__ = ( + db.PrimaryKeyConstraint("id", name="external_knowledge_bindings_pkey"), + db.Index("external_knowledge_bindings_tenant_idx", "tenant_id"), + db.Index("external_knowledge_bindings_dataset_idx", "dataset_id"), + db.Index("external_knowledge_bindings_external_knowledge_idx", "external_knowledge_id"), + db.Index("external_knowledge_bindings_external_knowledge_api_idx", "external_knowledge_api_id"), + ) + + id = db.Column(StringUUID, nullable=False, server_default=db.text("uuid_generate_v4()")) + tenant_id = db.Column(StringUUID, nullable=False) + external_knowledge_api_id = db.Column(StringUUID, nullable=False) + dataset_id = db.Column(StringUUID, nullable=False) + external_knowledge_id = db.Column(db.Text, nullable=False) + created_by = db.Column(StringUUID, nullable=False) + created_at = db.Column(db.DateTime, nullable=False, server_default=db.text("CURRENT_TIMESTAMP(0)")) + updated_by = db.Column(StringUUID, nullable=True) + updated_at = db.Column(db.DateTime, nullable=False, server_default=db.text("CURRENT_TIMESTAMP(0)")) diff --git a/api/models/model.py b/api/models/model.py index 53940a5a16..0ac9334321 100644 --- a/api/models/model.py +++ b/api/models/model.py @@ -1423,10 +1423,10 @@ class DatasetRetrieverResource(db.Model): position = db.Column(db.Integer, nullable=False) dataset_id = db.Column(StringUUID, nullable=False) dataset_name = db.Column(db.Text, nullable=False) - document_id = db.Column(StringUUID, nullable=False) + document_id = db.Column(StringUUID, nullable=True) document_name = db.Column(db.Text, nullable=False) - data_source_type = db.Column(db.Text, nullable=False) - segment_id = db.Column(StringUUID, nullable=False) + data_source_type = db.Column(db.Text, nullable=True) + segment_id = db.Column(StringUUID, nullable=True) score = db.Column(db.Float, nullable=True) content = db.Column(db.Text, nullable=False) hit_count = db.Column(db.Integer, nullable=True) diff --git a/api/poetry.lock b/api/poetry.lock index bce21fb547..4fb8d54f11 100644 --- a/api/poetry.lock +++ b/api/poetry.lock @@ -2,13 +2,13 @@ [[package]] name = "aiohappyeyeballs" -version = "2.4.0" +version = "2.4.2" description = "Happy Eyeballs for asyncio" optional = false python-versions = ">=3.8" files = [ - {file = "aiohappyeyeballs-2.4.0-py3-none-any.whl", hash = "sha256:7ce92076e249169a13c2f49320d1967425eaf1f407522d707d59cac7628d62bd"}, - {file = "aiohappyeyeballs-2.4.0.tar.gz", hash = "sha256:55a1714f084e63d49639800f95716da97a1f173d46a16dfcfda0016abb93b6b2"}, + {file = "aiohappyeyeballs-2.4.2-py3-none-any.whl", hash = "sha256:8522691d9a154ba1145b157d6d5c15e5c692527ce6a53c5e5f9876977f6dab2f"}, + {file = "aiohappyeyeballs-2.4.2.tar.gz", hash = "sha256:4ca893e6c5c1f5bf3888b04cb5a3bee24995398efef6e0b9f747b5e89d84fd74"}, ] [[package]] @@ -153,13 +153,13 @@ frozenlist = ">=1.1.0" [[package]] name = "alembic" -version = "1.13.2" +version = "1.13.3" description = "A database migration tool for SQLAlchemy." optional = false python-versions = ">=3.8" files = [ - {file = "alembic-1.13.2-py3-none-any.whl", hash = "sha256:6b8733129a6224a9a711e17c99b08462dbf7cc9670ba8f2e2ae9af860ceb1953"}, - {file = "alembic-1.13.2.tar.gz", hash = "sha256:1ff0ae32975f4fd96028c39ed9bb3c867fe3af956bd7bb37343b54c9fe7445ef"}, + {file = "alembic-1.13.3-py3-none-any.whl", hash = "sha256:908e905976d15235fae59c9ac42c4c5b75cfcefe3d27c0fbf7ae15a37715d80e"}, + {file = "alembic-1.13.3.tar.gz", hash = "sha256:203503117415561e203aa14541740643a611f641517f0209fcae63e9fa09f1a2"}, ] [package.dependencies] @@ -293,13 +293,13 @@ alibabacloud-tea = 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TEI_RERANK_SERVER_URL = "http://a.abc.com:11451" MIXEDBREAD_API_KEY = "mk-aaaaaaaaaaaaaaaaaaaa" +VOYAGE_API_KEY = "va-aaaaaaaaaaaaaaaaaaaa" [tool.poetry] name = "dify-api" @@ -220,6 +221,7 @@ volcengine-python-sdk = {extras = ["ark"], version = "^1.0.98"} oci = "^2.133.0" tos = "^2.7.1" nomic = "^3.1.2" +validators = "0.21.0" [tool.poetry.group.indriect.dependencies] kaleido = "0.2.1" rank-bm25 = "~0.2.2" @@ -286,4 +288,4 @@ optional = true [tool.poetry.group.lint.dependencies] dotenv-linter = "~0.5.0" -ruff = "~0.6.5" +ruff = "~0.6.8" diff --git a/api/schedule/clean_unused_messages_task.py b/api/schedule/clean_unused_messages_task.py new file mode 100644 index 0000000000..85e6a58a0e --- /dev/null +++ b/api/schedule/clean_unused_messages_task.py @@ -0,0 +1,92 @@ +import datetime +import time + +import click +from sqlalchemy import func +from werkzeug.exceptions import NotFound + +import app +from configs import dify_config +from core.rag.index_processor.index_processor_factory import IndexProcessorFactory +from extensions.ext_database import db +from models.dataset import Dataset, DatasetQuery, Document + + +@app.celery.task(queue="dataset") +def clean_unused_message_task(): + click.echo(click.style("Start clean unused messages .", fg="green")) + clean_days = int(dify_config.CLEAN_DAY_SETTING) + start_at = time.perf_counter() + thirty_days_ago = datetime.datetime.now() - datetime.timedelta(days=clean_days) + page = 1 + while True: + try: + # Subquery for counting new documents + document_subquery_new = ( + db.session.query(Document.dataset_id, func.count(Document.id).label("document_count")) + .filter( + Document.indexing_status == "completed", + Document.enabled == True, + Document.archived == False, + Document.updated_at > thirty_days_ago, + ) + .group_by(Document.dataset_id) + .subquery() + ) + + # Subquery for counting old documents + document_subquery_old = ( + db.session.query(Document.dataset_id, func.count(Document.id).label("document_count")) + .filter( + Document.indexing_status == "completed", + Document.enabled == True, + Document.archived == False, + Document.updated_at < thirty_days_ago, + ) + .group_by(Document.dataset_id) + .subquery() + ) + + # Main query with join and filter + datasets = ( + db.session.query(Dataset) + .outerjoin(document_subquery_new, Dataset.id == document_subquery_new.c.dataset_id) + .outerjoin(document_subquery_old, Dataset.id == document_subquery_old.c.dataset_id) + .filter( + Dataset.created_at < thirty_days_ago, + func.coalesce(document_subquery_new.c.document_count, 0) == 0, + func.coalesce(document_subquery_old.c.document_count, 0) > 0, + ) + .order_by(Dataset.created_at.desc()) + .paginate(page=page, per_page=50) + ) + + except NotFound: + break + if datasets.items is None or len(datasets.items) == 0: + break + page += 1 + for dataset in datasets: + dataset_query = ( + db.session.query(DatasetQuery) + .filter(DatasetQuery.created_at > thirty_days_ago, DatasetQuery.dataset_id == dataset.id) + .all() + ) + if not dataset_query or len(dataset_query) == 0: + try: + # remove index + index_processor = IndexProcessorFactory(dataset.doc_form).init_index_processor() + index_processor.clean(dataset, None) + + # update document + update_params = {Document.enabled: False} + + Document.query.filter_by(dataset_id=dataset.id).update(update_params) + db.session.commit() + click.echo(click.style("Cleaned unused dataset {} from db success!".format(dataset.id), fg="green")) + except Exception as e: + click.echo( + click.style("clean dataset index error: {} {}".format(e.__class__.__name__, str(e)), fg="red") + ) + end_at = time.perf_counter() + click.echo(click.style("Cleaned unused dataset from db success latency: {}".format(end_at - start_at), fg="green")) diff --git a/api/services/auth/api_key_auth_factory.py b/api/services/auth/api_key_auth_factory.py index ae5b953b47..36387e9c2e 100644 --- a/api/services/auth/api_key_auth_factory.py +++ b/api/services/auth/api_key_auth_factory.py @@ -1,10 +1,13 @@ from services.auth.firecrawl import FirecrawlAuth +from services.auth.jina import JinaAuth class ApiKeyAuthFactory: def __init__(self, provider: str, credentials: dict): if provider == "firecrawl": self.auth = FirecrawlAuth(credentials) + elif provider == "jinareader": + self.auth = JinaAuth(credentials) else: raise ValueError("Invalid provider") diff --git a/api/services/auth/jina.py b/api/services/auth/jina.py new file mode 100644 index 0000000000..de898a1f94 --- /dev/null +++ b/api/services/auth/jina.py @@ -0,0 +1,44 @@ +import json + +import requests + +from services.auth.api_key_auth_base import ApiKeyAuthBase + + +class JinaAuth(ApiKeyAuthBase): + def __init__(self, credentials: dict): + super().__init__(credentials) + auth_type = credentials.get("auth_type") + if auth_type != "bearer": + raise ValueError("Invalid auth type, Jina Reader auth type must be Bearer") + self.api_key = credentials.get("config").get("api_key", None) + + if not self.api_key: + raise ValueError("No API key provided") + + def validate_credentials(self): + headers = self._prepare_headers() + options = { + "url": "https://example.com", + } + response = self._post_request("https://r.jina.ai", options, headers) + if response.status_code == 200: + return True + else: + self._handle_error(response) + + def _prepare_headers(self): + return {"Content-Type": "application/json", "Authorization": f"Bearer {self.api_key}"} + + def _post_request(self, url, data, headers): + return requests.post(url, headers=headers, json=data) + + def _handle_error(self, response): + if response.status_code in {402, 409, 500}: + error_message = response.json().get("error", "Unknown error occurred") + raise Exception(f"Failed to authorize. Status code: {response.status_code}. Error: {error_message}") + else: + if response.text: + error_message = json.loads(response.text).get("error", "Unknown error occurred") + raise Exception(f"Failed to authorize. Status code: {response.status_code}. Error: {error_message}") + raise Exception(f"Unexpected error occurred while trying to authorize. Status code: {response.status_code}") diff --git a/api/services/dataset_service.py b/api/services/dataset_service.py index e96f06ed40..c165def6d5 100644 --- a/api/services/dataset_service.py +++ b/api/services/dataset_service.py @@ -32,6 +32,7 @@ from models.dataset import ( DatasetQuery, Document, DocumentSegment, + ExternalKnowledgeBindings, ) from models.model import UploadFile from models.source import DataSourceOauthBinding @@ -39,6 +40,7 @@ from services.errors.account import NoPermissionError from services.errors.dataset import DatasetNameDuplicateError from services.errors.document import DocumentIndexingError from services.errors.file import FileNotExistsError +from services.external_knowledge_service import ExternalDatasetService from services.feature_service import FeatureModel, FeatureService from services.tag_service import TagService from services.vector_service import VectorService @@ -56,10 +58,8 @@ from tasks.sync_website_document_indexing_task import sync_website_document_inde class DatasetService: @staticmethod - def get_datasets(page, per_page, provider="vendor", tenant_id=None, user=None, search=None, tag_ids=None): - query = Dataset.query.filter(Dataset.provider == provider, Dataset.tenant_id == tenant_id).order_by( - Dataset.created_at.desc() - ) + def get_datasets(page, per_page, tenant_id=None, user=None, search=None, tag_ids=None): + query = Dataset.query.filter(Dataset.tenant_id == tenant_id).order_by(Dataset.created_at.desc()) if user: # get permitted dataset ids @@ -137,7 +137,14 @@ class DatasetService: @staticmethod def create_empty_dataset( - tenant_id: str, name: str, indexing_technique: Optional[str], account: Account, permission: Optional[str] = None + tenant_id: str, + name: str, + indexing_technique: Optional[str], + account: Account, + permission: Optional[str] = None, + provider: str = "vendor", + external_knowledge_api_id: Optional[str] = None, + external_knowledge_id: Optional[str] = None, ): # check if dataset name already exists if Dataset.query.filter_by(name=name, tenant_id=tenant_id).first(): @@ -156,12 +163,28 @@ class DatasetService: dataset.embedding_model_provider = embedding_model.provider if embedding_model else None dataset.embedding_model = embedding_model.model if embedding_model else None dataset.permission = permission or DatasetPermissionEnum.ONLY_ME + dataset.provider = provider db.session.add(dataset) + db.session.flush() + + if provider == "external" and external_knowledge_api_id: + external_knowledge_api = ExternalDatasetService.get_external_knowledge_api(external_knowledge_api_id) + if not external_knowledge_api: + raise ValueError("External API template not found.") + external_knowledge_binding = ExternalKnowledgeBindings( + tenant_id=tenant_id, + dataset_id=dataset.id, + external_knowledge_api_id=external_knowledge_api_id, + external_knowledge_id=external_knowledge_id, + created_by=account.id, + ) + db.session.add(external_knowledge_binding) + db.session.commit() return dataset @staticmethod - def get_dataset(dataset_id): + def get_dataset(dataset_id) -> Dataset: return Dataset.query.filter_by(id=dataset_id).first() @staticmethod @@ -202,81 +225,103 @@ class DatasetService: @staticmethod def update_dataset(dataset_id, data, user): - data.pop("partial_member_list", None) - filtered_data = {k: v for k, v in data.items() if v is not None or k == "description"} dataset = DatasetService.get_dataset(dataset_id) + DatasetService.check_dataset_permission(dataset, user) - action = None - if dataset.indexing_technique != data["indexing_technique"]: - # if update indexing_technique - if data["indexing_technique"] == "economy": - action = "remove" - filtered_data["embedding_model"] = None - filtered_data["embedding_model_provider"] = None - filtered_data["collection_binding_id"] = None - elif data["indexing_technique"] == "high_quality": - action = "add" - # get embedding model setting - try: - model_manager = ModelManager() - embedding_model = model_manager.get_model_instance( - tenant_id=current_user.current_tenant_id, - provider=data["embedding_model_provider"], - model_type=ModelType.TEXT_EMBEDDING, - model=data["embedding_model"], - ) - filtered_data["embedding_model"] = embedding_model.model - filtered_data["embedding_model_provider"] = embedding_model.provider - dataset_collection_binding = DatasetCollectionBindingService.get_dataset_collection_binding( - embedding_model.provider, embedding_model.model - ) - filtered_data["collection_binding_id"] = dataset_collection_binding.id - except LLMBadRequestError: - raise ValueError( - "No Embedding Model available. Please configure a valid provider " - "in the Settings -> Model Provider." - ) - except ProviderTokenNotInitError as ex: - raise ValueError(ex.description) - else: + if dataset.provider == "external": + dataset.retrieval_model = data.get("external_retrieval_model", None) + dataset.name = data.get("name", dataset.name) + dataset.description = data.get("description", "") + external_knowledge_id = data.get("external_knowledge_id", None) + db.session.add(dataset) + if not external_knowledge_id: + raise ValueError("External knowledge id is required.") + external_knowledge_api_id = data.get("external_knowledge_api_id", None) + if not external_knowledge_api_id: + raise ValueError("External knowledge api id is required.") + external_knowledge_binding = ExternalKnowledgeBindings.query.filter_by(dataset_id=dataset_id).first() if ( - data["embedding_model_provider"] != dataset.embedding_model_provider - or data["embedding_model"] != dataset.embedding_model + external_knowledge_binding.external_knowledge_id != external_knowledge_id + or external_knowledge_binding.external_knowledge_api_id != external_knowledge_api_id ): - action = "update" - try: - model_manager = ModelManager() - embedding_model = model_manager.get_model_instance( - tenant_id=current_user.current_tenant_id, - provider=data["embedding_model_provider"], - model_type=ModelType.TEXT_EMBEDDING, - model=data["embedding_model"], - ) - filtered_data["embedding_model"] = embedding_model.model - filtered_data["embedding_model_provider"] = embedding_model.provider - dataset_collection_binding = DatasetCollectionBindingService.get_dataset_collection_binding( - embedding_model.provider, embedding_model.model - ) - filtered_data["collection_binding_id"] = dataset_collection_binding.id - except LLMBadRequestError: - raise ValueError( - "No Embedding Model available. Please configure a valid provider " - "in the Settings -> Model Provider." - ) - except ProviderTokenNotInitError as ex: - raise ValueError(ex.description) + external_knowledge_binding.external_knowledge_id = external_knowledge_id + external_knowledge_binding.external_knowledge_api_id = external_knowledge_api_id + db.session.add(external_knowledge_binding) + db.session.commit() + else: + data.pop("partial_member_list", None) + filtered_data = {k: v for k, v in data.items() if v is not None or k == "description"} + action = None + if dataset.indexing_technique != data["indexing_technique"]: + # if update indexing_technique + if data["indexing_technique"] == "economy": + action = "remove" + filtered_data["embedding_model"] = None + filtered_data["embedding_model_provider"] = None + filtered_data["collection_binding_id"] = None + elif data["indexing_technique"] == "high_quality": + action = "add" + # get embedding model setting + try: + model_manager = ModelManager() + embedding_model = model_manager.get_model_instance( + tenant_id=current_user.current_tenant_id, + provider=data["embedding_model_provider"], + model_type=ModelType.TEXT_EMBEDDING, + model=data["embedding_model"], + ) + filtered_data["embedding_model"] = embedding_model.model + filtered_data["embedding_model_provider"] = embedding_model.provider + dataset_collection_binding = DatasetCollectionBindingService.get_dataset_collection_binding( + embedding_model.provider, embedding_model.model + ) + filtered_data["collection_binding_id"] = dataset_collection_binding.id + except LLMBadRequestError: + raise ValueError( + "No Embedding Model available. Please configure a valid provider " + "in the Settings -> Model Provider." + ) + except ProviderTokenNotInitError as ex: + raise ValueError(ex.description) + else: + if ( + data["embedding_model_provider"] != dataset.embedding_model_provider + or data["embedding_model"] != dataset.embedding_model + ): + action = "update" + try: + model_manager = ModelManager() + embedding_model = model_manager.get_model_instance( + tenant_id=current_user.current_tenant_id, + provider=data["embedding_model_provider"], + model_type=ModelType.TEXT_EMBEDDING, + model=data["embedding_model"], + ) + filtered_data["embedding_model"] = embedding_model.model + filtered_data["embedding_model_provider"] = embedding_model.provider + dataset_collection_binding = DatasetCollectionBindingService.get_dataset_collection_binding( + embedding_model.provider, embedding_model.model + ) + filtered_data["collection_binding_id"] = dataset_collection_binding.id + except LLMBadRequestError: + raise ValueError( + "No Embedding Model available. Please configure a valid provider " + "in the Settings -> Model Provider." + ) + except ProviderTokenNotInitError as ex: + raise ValueError(ex.description) - filtered_data["updated_by"] = user.id - filtered_data["updated_at"] = datetime.datetime.now() + filtered_data["updated_by"] = user.id + filtered_data["updated_at"] = datetime.datetime.now() - # update Retrieval model - filtered_data["retrieval_model"] = data["retrieval_model"] + # update Retrieval model + filtered_data["retrieval_model"] = data["retrieval_model"] - dataset.query.filter_by(id=dataset_id).update(filtered_data) + dataset.query.filter_by(id=dataset_id).update(filtered_data) - db.session.commit() - if action: - deal_dataset_vector_index_task.delay(dataset_id, action) + db.session.commit() + if action: + deal_dataset_vector_index_task.delay(dataset_id, action) return dataset @staticmethod diff --git a/api/services/entities/external_knowledge_entities/external_knowledge_entities.py b/api/services/entities/external_knowledge_entities/external_knowledge_entities.py new file mode 100644 index 0000000000..4545f385eb --- /dev/null +++ b/api/services/entities/external_knowledge_entities/external_knowledge_entities.py @@ -0,0 +1,26 @@ +from typing import Literal, Optional, Union + +from pydantic import BaseModel + + +class AuthorizationConfig(BaseModel): + type: Literal[None, "basic", "bearer", "custom"] + api_key: Union[None, str] = None + header: Union[None, str] = None + + +class Authorization(BaseModel): + type: Literal["no-auth", "api-key"] + config: Optional[AuthorizationConfig] = None + + +class ProcessStatusSetting(BaseModel): + request_method: str + url: str + + +class ExternalKnowledgeApiSetting(BaseModel): + url: str + request_method: str + headers: Optional[dict] = None + params: Optional[dict] = None diff --git a/api/services/external_knowledge_service.py b/api/services/external_knowledge_service.py new file mode 100644 index 0000000000..4efdf8d7db --- /dev/null +++ b/api/services/external_knowledge_service.py @@ -0,0 +1,274 @@ +import json +from copy import deepcopy +from datetime import datetime, timezone +from typing import Any, Optional, Union + +import httpx +import validators + +# from tasks.external_document_indexing_task import external_document_indexing_task +from core.helper import ssrf_proxy +from extensions.ext_database import db +from models.dataset import ( + Dataset, + ExternalKnowledgeApis, + ExternalKnowledgeBindings, +) +from services.entities.external_knowledge_entities.external_knowledge_entities import ( + Authorization, + ExternalKnowledgeApiSetting, +) +from services.errors.dataset import DatasetNameDuplicateError + + +class ExternalDatasetService: + @staticmethod + def get_external_knowledge_apis(page, per_page, tenant_id, search=None) -> tuple[list[ExternalKnowledgeApis], int]: + query = ExternalKnowledgeApis.query.filter(ExternalKnowledgeApis.tenant_id == tenant_id).order_by( + ExternalKnowledgeApis.created_at.desc() + ) + if search: + query = query.filter(ExternalKnowledgeApis.name.ilike(f"%{search}%")) + + external_knowledge_apis = query.paginate(page=page, per_page=per_page, max_per_page=100, error_out=False) + + return external_knowledge_apis.items, external_knowledge_apis.total + + @classmethod + def validate_api_list(cls, api_settings: dict): + if not api_settings: + raise ValueError("api list is empty") + if "endpoint" not in api_settings and not api_settings["endpoint"]: + raise ValueError("endpoint is required") + if "api_key" not in api_settings and not api_settings["api_key"]: + raise ValueError("api_key is required") + + @staticmethod + def create_external_knowledge_api(tenant_id: str, user_id: str, args: dict) -> ExternalKnowledgeApis: + ExternalDatasetService.check_endpoint_and_api_key(args.get("settings")) + external_knowledge_api = ExternalKnowledgeApis( + tenant_id=tenant_id, + created_by=user_id, + updated_by=user_id, + name=args.get("name"), + description=args.get("description", ""), + settings=json.dumps(args.get("settings"), ensure_ascii=False), + ) + + db.session.add(external_knowledge_api) + db.session.commit() + return external_knowledge_api + + @staticmethod + def check_endpoint_and_api_key(settings: dict): + if "endpoint" not in settings or not settings["endpoint"]: + raise ValueError("endpoint is required") + if "api_key" not in settings or not settings["api_key"]: + raise ValueError("api_key is required") + + endpoint = f"{settings['endpoint']}/retrieval" + api_key = settings["api_key"] + if not validators.url(endpoint): + raise ValueError(f"invalid endpoint: {endpoint}") + try: + response = httpx.post(endpoint, headers={"Authorization": f"Bearer {api_key}"}) + except Exception as e: + raise ValueError(f"failed to connect to the endpoint: {endpoint}") + if response.status_code == 502: + raise ValueError(f"Bad Gateway: failed to connect to the endpoint: {endpoint}") + if response.status_code == 404: + raise ValueError(f"Not Found: failed to connect to the endpoint: {endpoint}") + if response.status_code == 403: + raise ValueError(f"Forbidden: Authorization failed with api_key: {api_key}") + + @staticmethod + def get_external_knowledge_api(external_knowledge_api_id: str) -> ExternalKnowledgeApis: + return ExternalKnowledgeApis.query.filter_by(id=external_knowledge_api_id).first() + + @staticmethod + def update_external_knowledge_api(tenant_id, user_id, external_knowledge_api_id, args) -> ExternalKnowledgeApis: + external_knowledge_api = ExternalKnowledgeApis.query.filter_by( + id=external_knowledge_api_id, tenant_id=tenant_id + ).first() + if external_knowledge_api is None: + raise ValueError("api template not found") + + external_knowledge_api.name = args.get("name") + external_knowledge_api.description = args.get("description", "") + external_knowledge_api.settings = json.dumps(args.get("settings"), ensure_ascii=False) + external_knowledge_api.updated_by = user_id + external_knowledge_api.updated_at = datetime.now(timezone.utc).replace(tzinfo=None) + db.session.commit() + + return external_knowledge_api + + @staticmethod + def delete_external_knowledge_api(tenant_id: str, external_knowledge_api_id: str): + external_knowledge_api = ExternalKnowledgeApis.query.filter_by( + id=external_knowledge_api_id, tenant_id=tenant_id + ).first() + if external_knowledge_api is None: + raise ValueError("api template not found") + + db.session.delete(external_knowledge_api) + db.session.commit() + + @staticmethod + def external_knowledge_api_use_check(external_knowledge_api_id: str) -> tuple[bool, int]: + count = ExternalKnowledgeBindings.query.filter_by(external_knowledge_api_id=external_knowledge_api_id).count() + if count > 0: + return True, count + return False, 0 + + @staticmethod + def get_external_knowledge_binding_with_dataset_id(tenant_id: str, dataset_id: str) -> ExternalKnowledgeBindings: + external_knowledge_binding = ExternalKnowledgeBindings.query.filter_by( + dataset_id=dataset_id, tenant_id=tenant_id + ).first() + if not external_knowledge_binding: + raise ValueError("external knowledge binding not found") + return external_knowledge_binding + + @staticmethod + def document_create_args_validate(tenant_id: str, external_knowledge_api_id: str, process_parameter: dict): + external_knowledge_api = ExternalKnowledgeApis.query.filter_by( + id=external_knowledge_api_id, tenant_id=tenant_id + ).first() + if external_knowledge_api is None: + raise ValueError("api template not found") + settings = json.loads(external_knowledge_api.settings) + for setting in settings: + custom_parameters = setting.get("document_process_setting") + if custom_parameters: + for parameter in custom_parameters: + if parameter.get("required", False) and not process_parameter.get(parameter.get("name")): + raise ValueError(f'{parameter.get("name")} is required') + + @staticmethod + def process_external_api( + settings: ExternalKnowledgeApiSetting, files: Union[None, dict[str, Any]] + ) -> httpx.Response: + """ + do http request depending on api bundle + """ + + kwargs = { + "url": settings.url, + "headers": settings.headers, + "follow_redirects": True, + } + + response = getattr(ssrf_proxy, settings.request_method)(data=json.dumps(settings.params), files=files, **kwargs) + + return response + + @staticmethod + def assembling_headers(authorization: Authorization, headers: Optional[dict] = None) -> dict[str, Any]: + authorization = deepcopy(authorization) + if headers: + headers = deepcopy(headers) + else: + headers = {} + if authorization.type == "api-key": + if authorization.config is None: + raise ValueError("authorization config is required") + + if authorization.config.api_key is None: + raise ValueError("api_key is required") + + if not authorization.config.header: + authorization.config.header = "Authorization" + + if authorization.config.type == "bearer": + headers[authorization.config.header] = f"Bearer {authorization.config.api_key}" + elif authorization.config.type == "basic": + headers[authorization.config.header] = f"Basic {authorization.config.api_key}" + elif authorization.config.type == "custom": + headers[authorization.config.header] = authorization.config.api_key + + return headers + + @staticmethod + def get_external_knowledge_api_settings(settings: dict) -> ExternalKnowledgeApiSetting: + return ExternalKnowledgeApiSetting.parse_obj(settings) + + @staticmethod + def create_external_dataset(tenant_id: str, user_id: str, args: dict) -> Dataset: + # check if dataset name already exists + if Dataset.query.filter_by(name=args.get("name"), tenant_id=tenant_id).first(): + raise DatasetNameDuplicateError(f"Dataset with name {args.get('name')} already exists.") + external_knowledge_api = ExternalKnowledgeApis.query.filter_by( + id=args.get("external_knowledge_api_id"), tenant_id=tenant_id + ).first() + + if external_knowledge_api is None: + raise ValueError("api template not found") + + dataset = Dataset( + tenant_id=tenant_id, + name=args.get("name"), + description=args.get("description", ""), + provider="external", + retrieval_model=args.get("external_retrieval_model"), + created_by=user_id, + ) + + db.session.add(dataset) + db.session.flush() + + external_knowledge_binding = ExternalKnowledgeBindings( + tenant_id=tenant_id, + dataset_id=dataset.id, + external_knowledge_api_id=args.get("external_knowledge_api_id"), + external_knowledge_id=args.get("external_knowledge_id"), + created_by=user_id, + ) + db.session.add(external_knowledge_binding) + + db.session.commit() + + return dataset + + @staticmethod + def fetch_external_knowledge_retrieval( + tenant_id: str, dataset_id: str, query: str, external_retrieval_parameters: dict + ) -> list: + external_knowledge_binding = ExternalKnowledgeBindings.query.filter_by( + dataset_id=dataset_id, tenant_id=tenant_id + ).first() + if not external_knowledge_binding: + raise ValueError("external knowledge binding not found") + + external_knowledge_api = ExternalKnowledgeApis.query.filter_by( + id=external_knowledge_binding.external_knowledge_api_id + ).first() + if not external_knowledge_api: + raise ValueError("external api template not found") + + settings = json.loads(external_knowledge_api.settings) + headers = {"Content-Type": "application/json"} + if settings.get("api_key"): + headers["Authorization"] = f"Bearer {settings.get('api_key')}" + score_threshold_enabled = external_retrieval_parameters.get("score_threshold_enabled") or False + score_threshold = external_retrieval_parameters.get("score_threshold", 0.0) if score_threshold_enabled else 0.0 + request_params = { + "retrieval_setting": { + "top_k": external_retrieval_parameters.get("top_k"), + "score_threshold": score_threshold, + }, + "query": query, + "knowledge_id": external_knowledge_binding.external_knowledge_id, + } + + external_knowledge_api_setting = { + "url": f"{settings.get('endpoint')}/retrieval", + "request_method": "post", + "headers": headers, + "params": request_params, + } + response = ExternalDatasetService.process_external_api( + ExternalKnowledgeApiSetting(**external_knowledge_api_setting), None + ) + if response.status_code == 200: + return response.json().get("records", []) + return [] diff --git a/api/services/hit_testing_service.py b/api/services/hit_testing_service.py index 3dafafd5b4..7957b4dc82 100644 --- a/api/services/hit_testing_service.py +++ b/api/services/hit_testing_service.py @@ -19,7 +19,15 @@ default_retrieval_model = { class HitTestingService: @classmethod - def retrieve(cls, dataset: Dataset, query: str, account: Account, retrieval_model: dict, limit: int = 10) -> dict: + def retrieve( + cls, + dataset: Dataset, + query: str, + account: Account, + retrieval_model: dict, + external_retrieval_model: dict, + limit: int = 10, + ) -> dict: if dataset.available_document_count == 0 or dataset.available_segment_count == 0: return { "query": { @@ -62,10 +70,44 @@ class HitTestingService: return cls.compact_retrieve_response(dataset, query, all_documents) + @classmethod + def external_retrieve( + cls, + dataset: Dataset, + query: str, + account: Account, + external_retrieval_model: dict, + ) -> dict: + if dataset.provider != "external": + return { + "query": {"content": query}, + "records": [], + } + + start = time.perf_counter() + + all_documents = RetrievalService.external_retrieve( + dataset_id=dataset.id, + query=cls.escape_query_for_search(query), + external_retrieval_model=external_retrieval_model, + ) + + end = time.perf_counter() + logging.debug(f"External knowledge hit testing retrieve in {end - start:0.4f} seconds") + + dataset_query = DatasetQuery( + dataset_id=dataset.id, content=query, source="hit_testing", created_by_role="account", created_by=account.id + ) + + db.session.add(dataset_query) + db.session.commit() + + return cls.compact_external_retrieve_response(dataset, query, all_documents) + @classmethod def compact_retrieve_response(cls, dataset: Dataset, query: str, documents: list[Document]): - i = 0 records = [] + for document in documents: index_node_id = document.metadata["doc_id"] @@ -81,7 +123,6 @@ class HitTestingService: ) if not segment: - i += 1 continue record = { @@ -91,8 +132,6 @@ class HitTestingService: records.append(record) - i += 1 - return { "query": { "content": query, @@ -100,6 +139,25 @@ class HitTestingService: "records": records, } + @classmethod + def compact_external_retrieve_response(cls, dataset: Dataset, query: str, documents: list): + records = [] + if dataset.provider == "external": + for document in documents: + record = { + "content": document.get("content", None), + "title": document.get("title", None), + "score": document.get("score", None), + "metadata": document.get("metadata", None), + } + records.append(record) + return { + "query": { + "content": query, + }, + "records": records, + } + @classmethod def hit_testing_args_check(cls, args): query = args["query"] diff --git a/api/services/website_service.py b/api/services/website_service.py index fea605cf30..be01815720 100644 --- a/api/services/website_service.py +++ b/api/services/website_service.py @@ -1,6 +1,7 @@ import datetime import json +import requests from flask_login import current_user from core.helper import encrypter @@ -65,6 +66,35 @@ class WebsiteService: time = str(datetime.datetime.now().timestamp()) redis_client.setex(website_crawl_time_cache_key, 3600, time) return {"status": "active", "job_id": job_id} + elif provider == "jinareader": + api_key = encrypter.decrypt_token( + tenant_id=current_user.current_tenant_id, token=credentials.get("config").get("api_key") + ) + crawl_sub_pages = options.get("crawl_sub_pages", False) + if not crawl_sub_pages: + response = requests.get( + f"https://r.jina.ai/{url}", + headers={"Accept": "application/json", "Authorization": f"Bearer {api_key}"}, + ) + if response.json().get("code") != 200: + raise ValueError("Failed to crawl") + return {"status": "active", "data": response.json().get("data")} + else: + response = requests.post( + "https://adaptivecrawl-kir3wx7b3a-uc.a.run.app", + json={ + "url": url, + "maxPages": options.get("limit", 1), + "useSitemap": options.get("use_sitemap", True), + }, + headers={ + "Content-Type": "application/json", + "Authorization": f"Bearer {api_key}", + }, + ) + if response.json().get("code") != 200: + raise ValueError("Failed to crawl") + return {"status": "active", "job_id": response.json().get("data", {}).get("taskId")} else: raise ValueError("Invalid provider") @@ -93,6 +123,42 @@ class WebsiteService: time_consuming = abs(end_time - float(start_time)) crawl_status_data["time_consuming"] = f"{time_consuming:.2f}" redis_client.delete(website_crawl_time_cache_key) + elif provider == "jinareader": + api_key = encrypter.decrypt_token( + tenant_id=current_user.current_tenant_id, token=credentials.get("config").get("api_key") + ) + response = requests.post( + "https://adaptivecrawlstatus-kir3wx7b3a-uc.a.run.app", + headers={"Content-Type": "application/json", "Authorization": f"Bearer {api_key}"}, + json={"taskId": job_id}, + ) + data = response.json().get("data", {}) + crawl_status_data = { + "status": data.get("status", "active"), + "job_id": job_id, + "total": len(data.get("urls", [])), + "current": len(data.get("processed", [])) + len(data.get("failed", [])), + "data": [], + "time_consuming": data.get("duration", 0) / 1000, + } + + if crawl_status_data["status"] == "completed": + response = requests.post( + "https://adaptivecrawlstatus-kir3wx7b3a-uc.a.run.app", + headers={"Content-Type": "application/json", "Authorization": f"Bearer {api_key}"}, + json={"taskId": job_id, "urls": list(data.get("processed", {}).keys())}, + ) + data = response.json().get("data", {}) + formatted_data = [ + { + "title": item.get("data", {}).get("title"), + "source_url": item.get("data", {}).get("url"), + "description": item.get("data", {}).get("description"), + "markdown": item.get("data", {}).get("content"), + } + for item in data.get("processed", {}).values() + ] + crawl_status_data["data"] = formatted_data else: raise ValueError("Invalid provider") return crawl_status_data @@ -119,6 +185,40 @@ class WebsiteService: if item.get("source_url") == url: return item return None + elif provider == "jinareader": + file_key = "website_files/" + job_id + ".txt" + if storage.exists(file_key): + data = storage.load_once(file_key) + if data: + data = json.loads(data.decode("utf-8")) + elif not job_id: + response = requests.get( + f"https://r.jina.ai/{url}", + headers={"Accept": "application/json", "Authorization": f"Bearer {api_key}"}, + ) + if response.json().get("code") != 200: + raise ValueError("Failed to crawl") + return response.json().get("data") + else: + api_key = encrypter.decrypt_token(tenant_id=tenant_id, token=credentials.get("config").get("api_key")) + response = requests.post( + "https://adaptivecrawlstatus-kir3wx7b3a-uc.a.run.app", + headers={"Content-Type": "application/json", "Authorization": f"Bearer {api_key}"}, + json={"taskId": job_id}, + ) + data = response.json().get("data", {}) + if data.get("status") != "completed": + raise ValueError("Crawl job is not completed") + + response = requests.post( + "https://adaptivecrawlstatus-kir3wx7b3a-uc.a.run.app", + headers={"Content-Type": "application/json", "Authorization": f"Bearer {api_key}"}, + json={"taskId": job_id, "urls": list(data.get("processed", {}).keys())}, + ) + data = response.json().get("data", {}) + for item in data.get("processed", {}).values(): + if item.get("data", {}).get("url") == url: + return item.get("data", {}) else: raise ValueError("Invalid provider") diff --git a/api/tasks/external_document_indexing_task.py b/api/tasks/external_document_indexing_task.py new file mode 100644 index 0000000000..6fc719ae8d --- /dev/null +++ b/api/tasks/external_document_indexing_task.py @@ -0,0 +1,93 @@ +import json +import logging +import time + +import click +from celery import shared_task + +from core.indexing_runner import DocumentIsPausedException +from extensions.ext_database import db +from extensions.ext_storage import storage +from models.dataset import Dataset, ExternalKnowledgeApis +from models.model import UploadFile +from services.external_knowledge_service import ExternalDatasetService + + +@shared_task(queue="dataset") +def external_document_indexing_task( + dataset_id: str, external_knowledge_api_id: str, data_source: dict, process_parameter: dict +): + """ + Async process document + :param dataset_id: + :param external_knowledge_api_id: + :param data_source: + :param process_parameter: + Usage: external_document_indexing_task.delay(dataset_id, document_id) + """ + start_at = time.perf_counter() + + dataset = db.session.query(Dataset).filter(Dataset.id == dataset_id).first() + if not dataset: + logging.info( + click.style("Processed external dataset: {} failed, dataset not exit.".format(dataset_id), fg="red") + ) + return + + # get external api template + external_knowledge_api = ( + db.session.query(ExternalKnowledgeApis) + .filter( + ExternalKnowledgeApis.id == external_knowledge_api_id, ExternalKnowledgeApis.tenant_id == dataset.tenant_id + ) + .first() + ) + + if not external_knowledge_api: + logging.info( + click.style( + "Processed external dataset: {} failed, api template: {} not exit.".format( + dataset_id, external_knowledge_api_id + ), + fg="red", + ) + ) + return + files = {} + if data_source["type"] == "upload_file": + upload_file_list = data_source["info_list"]["file_info_list"]["file_ids"] + for file_id in upload_file_list: + file = ( + db.session.query(UploadFile) + .filter(UploadFile.tenant_id == dataset.tenant_id, UploadFile.id == file_id) + .first() + ) + if file: + files[file.id] = (file.name, storage.load_once(file.key), file.mime_type) + try: + settings = ExternalDatasetService.get_external_knowledge_api_settings( + json.loads(external_knowledge_api.settings) + ) + # assemble headers + headers = ExternalDatasetService.assembling_headers(settings.authorization, settings.headers) + + # do http request + response = ExternalDatasetService.process_external_api(settings, headers, process_parameter, files) + job_id = response.json().get("job_id") + if job_id: + # save job_id to dataset + dataset.job_id = job_id + db.session.commit() + + end_at = time.perf_counter() + logging.info( + click.style( + "Processed external dataset: {} successful, latency: {}".format(dataset.id, end_at - start_at), + fg="green", + ) + ) + except DocumentIsPausedException as ex: + logging.info(click.style(str(ex), fg="yellow")) + + except Exception: + pass diff --git a/api/tests/integration_tests/model_runtime/voyage/__init__.py b/api/tests/integration_tests/model_runtime/voyage/__init__.py new file mode 100644 index 0000000000..e69de29bb2 diff --git a/api/tests/integration_tests/model_runtime/voyage/test_provider.py b/api/tests/integration_tests/model_runtime/voyage/test_provider.py new file mode 100644 index 0000000000..08978c88a9 --- /dev/null +++ b/api/tests/integration_tests/model_runtime/voyage/test_provider.py @@ -0,0 +1,25 @@ +import os +from unittest.mock import Mock, patch + +import pytest + +from core.model_runtime.errors.validate import CredentialsValidateFailedError +from core.model_runtime.model_providers.voyage.voyage import VoyageProvider + + +def test_validate_provider_credentials(): + provider = VoyageProvider() + + with pytest.raises(CredentialsValidateFailedError): + provider.validate_provider_credentials(credentials={"api_key": "hahahaha"}) + with patch("requests.post") as mock_post: + mock_response = Mock() + mock_response.json.return_value = { + "object": "list", + "data": [{"object": "embedding", "embedding": [0.23333 for _ in range(1024)], "index": 0}], + "model": "voyage-3", + "usage": {"total_tokens": 1}, + } + mock_response.status_code = 200 + mock_post.return_value = mock_response + provider.validate_provider_credentials(credentials={"api_key": os.environ.get("VOYAGE_API_KEY")}) diff --git a/api/tests/integration_tests/model_runtime/voyage/test_rerank.py b/api/tests/integration_tests/model_runtime/voyage/test_rerank.py new file mode 100644 index 0000000000..e97a9e4c81 --- /dev/null +++ b/api/tests/integration_tests/model_runtime/voyage/test_rerank.py @@ -0,0 +1,92 @@ +import os +from unittest.mock import Mock, patch + +import pytest + +from core.model_runtime.entities.rerank_entities import RerankResult +from core.model_runtime.errors.validate import CredentialsValidateFailedError +from core.model_runtime.model_providers.voyage.rerank.rerank import VoyageRerankModel + + +def test_validate_credentials(): + model = VoyageRerankModel() + + with pytest.raises(CredentialsValidateFailedError): + model.validate_credentials( + model="rerank-lite-1", + credentials={"api_key": "invalid_key"}, + ) + with patch("httpx.post") as mock_post: + mock_response = Mock() + mock_response.json.return_value = { + "object": "list", + "data": [ + { + "relevance_score": 0.546875, + "index": 0, + "document": "Carson City is the capital city of the American state of Nevada. At the 2010 United " + "States Census, Carson City had a population of 55,274.", + }, + { + "relevance_score": 0.4765625, + "index": 1, + "document": "The Commonwealth of the Northern Mariana Islands is a group of islands in the " + "Pacific Ocean that are a political division controlled by the United States. Its " + "capital is Saipan.", + }, + ], + "model": "rerank-lite-1", + "usage": {"total_tokens": 96}, + } + mock_response.status_code = 200 + mock_post.return_value = mock_response + model.validate_credentials( + model="rerank-lite-1", + credentials={ + "api_key": os.environ.get("VOYAGE_API_KEY"), + }, + ) + + +def test_invoke_model(): + model = VoyageRerankModel() + with patch("httpx.post") as mock_post: + mock_response = Mock() + mock_response.json.return_value = { + "object": "list", + "data": [ + { + "relevance_score": 0.84375, + "index": 0, + "document": "Kasumi is a girl name of Japanese origin meaning mist.", + }, + { + "relevance_score": 0.4765625, + "index": 1, + "document": "Her music is a kawaii bass, a mix of future bass, pop, and kawaii music and she " + "leads a team named PopiParty.", + }, + ], + "model": "rerank-lite-1", + "usage": {"total_tokens": 59}, + } + mock_response.status_code = 200 + mock_post.return_value = mock_response + result = model.invoke( + model="rerank-lite-1", + credentials={ + "api_key": os.environ.get("VOYAGE_API_KEY"), + }, + query="Who is Kasumi?", + docs=[ + "Kasumi is a girl name of Japanese origin meaning mist.", + "Her music is a kawaii bass, a mix of future bass, pop, and kawaii music and she leads a team named " + "PopiParty.", + ], + score_threshold=0.5, + ) + + assert isinstance(result, RerankResult) + assert len(result.docs) == 1 + assert result.docs[0].index == 0 + assert result.docs[0].score >= 0.5 diff --git a/api/tests/integration_tests/model_runtime/voyage/test_text_embedding.py b/api/tests/integration_tests/model_runtime/voyage/test_text_embedding.py new file mode 100644 index 0000000000..75719672a9 --- /dev/null +++ b/api/tests/integration_tests/model_runtime/voyage/test_text_embedding.py @@ -0,0 +1,70 @@ +import os +from unittest.mock import Mock, patch + +import pytest + +from core.model_runtime.entities.text_embedding_entities import TextEmbeddingResult +from core.model_runtime.errors.validate import CredentialsValidateFailedError +from core.model_runtime.model_providers.voyage.text_embedding.text_embedding import VoyageTextEmbeddingModel + + +def test_validate_credentials(): + model = VoyageTextEmbeddingModel() + + with pytest.raises(CredentialsValidateFailedError): + model.validate_credentials(model="voyage-3", credentials={"api_key": "invalid_key"}) + with patch("requests.post") as mock_post: + mock_response = Mock() + mock_response.json.return_value = { + "object": "list", + "data": [{"object": "embedding", "embedding": [0.23333 for _ in range(1024)], "index": 0}], + "model": "voyage-3", + "usage": {"total_tokens": 1}, + } + mock_response.status_code = 200 + mock_post.return_value = mock_response + model.validate_credentials(model="voyage-3", credentials={"api_key": os.environ.get("VOYAGE_API_KEY")}) + + +def test_invoke_model(): + model = VoyageTextEmbeddingModel() + + with patch("requests.post") as mock_post: + mock_response = Mock() + mock_response.json.return_value = { + "object": "list", + "data": [ + {"object": "embedding", "embedding": [0.23333 for _ in range(1024)], "index": 0}, + {"object": "embedding", "embedding": [0.23333 for _ in range(1024)], "index": 1}, + ], + "model": "voyage-3", + "usage": {"total_tokens": 2}, + } + mock_response.status_code = 200 + mock_post.return_value = mock_response + result = model.invoke( + model="voyage-3", + credentials={ + "api_key": os.environ.get("VOYAGE_API_KEY"), + }, + texts=["hello", "world"], + user="abc-123", + ) + + assert isinstance(result, TextEmbeddingResult) + assert len(result.embeddings) == 2 + assert result.usage.total_tokens == 2 + + +def test_get_num_tokens(): + model = VoyageTextEmbeddingModel() + + num_tokens = model.get_num_tokens( + model="voyage-3", + credentials={ + "api_key": os.environ.get("VOYAGE_API_KEY"), + }, + texts=["ping"], + ) + + assert num_tokens == 1 diff --git a/api/tests/integration_tests/tools/__mock/http.py b/api/tests/integration_tests/tools/__mock/http.py index d3c1f3101c..42cf87e317 100644 --- a/api/tests/integration_tests/tools/__mock/http.py +++ b/api/tests/integration_tests/tools/__mock/http.py @@ -17,7 +17,7 @@ class MockedHttp: request = httpx.Request( method, url, params=kwargs.get("params"), headers=kwargs.get("headers"), cookies=kwargs.get("cookies") ) - data = kwargs.get("data", None) + data = kwargs.get("data") resp = json.dumps(data).encode("utf-8") if data else b"OK" response = httpx.Response( status_code=200, diff --git a/api/tests/integration_tests/vdb/pgvector/test_pgvector.py b/api/tests/integration_tests/vdb/pgvector/test_pgvector.py index c5a986b747..72efdc2780 100644 --- a/api/tests/integration_tests/vdb/pgvector/test_pgvector.py +++ b/api/tests/integration_tests/vdb/pgvector/test_pgvector.py @@ -18,6 +18,8 @@ class PGVectorTest(AbstractVectorTest): user="postgres", password="difyai123456", database="dify", + min_connection=1, + max_connection=5, ), ) diff --git a/api/tests/integration_tests/workflow/nodes/__mock/http.py b/api/tests/integration_tests/workflow/nodes/__mock/http.py index f1ab23b002..ec013183b7 100644 --- a/api/tests/integration_tests/workflow/nodes/__mock/http.py +++ b/api/tests/integration_tests/workflow/nodes/__mock/http.py @@ -22,8 +22,8 @@ class MockedHttp: return response # get data, files - data = kwargs.get("data", None) - files = kwargs.get("files", None) + data = kwargs.get("data") + files = kwargs.get("files") if data is not None: resp = dumps(data).encode("utf-8") elif files is not None: diff --git a/api/tests/unit_tests/controllers/test_compare_versions.py b/api/tests/unit_tests/controllers/test_compare_versions.py new file mode 100644 index 0000000000..87902b6d44 --- /dev/null +++ b/api/tests/unit_tests/controllers/test_compare_versions.py @@ -0,0 +1,38 @@ +import pytest + +from controllers.console.version import _has_new_version + + +@pytest.mark.parametrize( + ("latest_version", "current_version", "expected"), + [ + ("1.0.1", "1.0.0", True), + ("1.1.0", "1.0.0", True), + ("2.0.0", "1.9.9", True), + ("1.0.0", "1.0.0", False), + ("1.0.0", "1.0.1", False), + ("1.0.0", "2.0.0", False), + ("1.0.1", "1.0.0-beta", True), + ("1.0.0", "1.0.0-alpha", True), + ("1.0.0-beta", "1.0.0-alpha", True), + ("1.0.0", "1.0.0-rc1", True), + ("1.0.0", "0.9.9", True), + ("1.0.0", "1.0.0-dev", True), + ], +) +def test_has_new_version(latest_version, current_version, expected): + assert _has_new_version(latest_version=latest_version, current_version=current_version) == expected + + +def test_has_new_version_invalid_input(): + with pytest.raises(ValueError): + _has_new_version(latest_version="1.0", current_version="1.0.0") + + with pytest.raises(ValueError): + _has_new_version(latest_version="1.0.0", current_version="1.0") + + with pytest.raises(ValueError): + _has_new_version(latest_version="invalid", current_version="1.0.0") + + with pytest.raises(ValueError): + _has_new_version(latest_version="1.0.0", current_version="invalid") diff --git a/dev/pytest/pytest_model_runtime.sh b/dev/pytest/pytest_model_runtime.sh index b60ff64fdc..63891eb9f8 100755 --- a/dev/pytest/pytest_model_runtime.sh +++ b/dev/pytest/pytest_model_runtime.sh @@ -9,4 +9,5 @@ pytest api/tests/integration_tests/model_runtime/anthropic \ api/tests/integration_tests/model_runtime/upstage \ api/tests/integration_tests/model_runtime/fireworks \ api/tests/integration_tests/model_runtime/nomic \ - api/tests/integration_tests/model_runtime/mixedbread + api/tests/integration_tests/model_runtime/mixedbread \ + api/tests/integration_tests/model_runtime/voyage \ No newline at end of file diff --git a/docker/.env.example b/docker/.env.example index d43c3edc7e..eb05f7aa4f 100644 --- a/docker/.env.example +++ b/docker/.env.example @@ -391,6 +391,8 @@ PGVECTOR_PORT=5432 PGVECTOR_USER=postgres PGVECTOR_PASSWORD=difyai123456 PGVECTOR_DATABASE=dify +PGVECTOR_MIN_CONNECTION=1 +PGVECTOR_MAX_CONNECTION=5 # pgvecto-rs configurations, only available when VECTOR_STORE is `pgvecto-rs` PGVECTO_RS_HOST=pgvecto-rs diff --git a/web/app/(commonLayout)/datasets/(datasetDetailLayout)/[datasetId]/layout.tsx b/web/app/(commonLayout)/datasets/(datasetDetailLayout)/[datasetId]/layout.tsx index e691cc05f6..a58027bcd1 100644 --- a/web/app/(commonLayout)/datasets/(datasetDetailLayout)/[datasetId]/layout.tsx +++ b/web/app/(commonLayout)/datasets/(datasetDetailLayout)/[datasetId]/layout.tsx @@ -1,6 +1,6 @@ 'use client' import type { FC, SVGProps } from 'react' -import React, { useEffect } from 'react' +import React, { useEffect, useMemo } from 'react' import { usePathname } from 'next/navigation' import useSWR from 'swr' import { useTranslation } from 'react-i18next' @@ -203,12 +203,23 @@ const DatasetDetailLayout: FC = (props) => { datasetId, }, apiParams => fetchDatasetRelatedApps(apiParams.datasetId)) - const navigation = [ - { name: t('common.datasetMenus.documents'), href: `/datasets/${datasetId}/documents`, icon: DocumentTextIcon, selectedIcon: DocumentTextSolidIcon }, - { name: t('common.datasetMenus.hitTesting'), href: `/datasets/${datasetId}/hitTesting`, icon: TargetIcon, selectedIcon: TargetSolidIcon }, - // { name: 'api & webhook', href: `/datasets/${datasetId}/api`, icon: CommandLineIcon, selectedIcon: CommandLineSolidIcon }, - { name: t('common.datasetMenus.settings'), href: `/datasets/${datasetId}/settings`, icon: Cog8ToothIcon, selectedIcon: Cog8ToothSolidIcon }, - ] + const navigation = useMemo(() => { + const baseNavigation = [ + { name: t('common.datasetMenus.hitTesting'), href: `/datasets/${datasetId}/hitTesting`, icon: TargetIcon, selectedIcon: TargetSolidIcon }, + // { name: 'api & webhook', href: `/datasets/${datasetId}/api`, icon: CommandLineIcon, selectedIcon: CommandLineSolidIcon }, + { name: t('common.datasetMenus.settings'), href: `/datasets/${datasetId}/settings`, icon: Cog8ToothIcon, selectedIcon: Cog8ToothSolidIcon }, + ] + + if (datasetRes?.provider !== 'external') { + baseNavigation.unshift({ + name: t('common.datasetMenus.documents'), + href: `/datasets/${datasetId}/documents`, + icon: DocumentTextIcon, + selectedIcon: DocumentTextSolidIcon, + }) + } + return baseNavigation + }, [datasetRes?.provider, datasetId, t]) useEffect(() => { if (datasetRes) @@ -233,6 +244,7 @@ const DatasetDetailLayout: FC = (props) => { icon={datasetRes?.icon || 'https://static.dify.ai/images/dataset-default-icon.png'} icon_background={datasetRes?.icon_background || '#F5F5F5'} desc={datasetRes?.description || '--'} + isExternal={datasetRes?.provider === 'external'} navigation={navigation} extraInfo={!isCurrentWorkspaceDatasetOperator ? mode => : undefined} iconType={datasetRes?.data_source_type === DataSourceType.NOTION ? 'notion' : 'dataset'} diff --git a/web/app/(commonLayout)/datasets/Container.tsx b/web/app/(commonLayout)/datasets/Container.tsx index 6b2c6fd29e..02b3cbb61d 100644 --- a/web/app/(commonLayout)/datasets/Container.tsx +++ b/web/app/(commonLayout)/datasets/Container.tsx @@ -8,14 +8,17 @@ import { useDebounceFn } from 'ahooks' import useSWR from 'swr' // Components +import ExternalAPIPanel from '../../components/datasets/external-api/external-api-panel' import Datasets from './Datasets' import DatasetFooter from './DatasetFooter' import ApiServer from './ApiServer' import Doc from './Doc' import TabSliderNew from '@/app/components/base/tab-slider-new' -import Input from '@/app/components/base/input' import TagManagementModal from '@/app/components/base/tag-management' import TagFilter from '@/app/components/base/tag-management/filter' +import Button from '@/app/components/base/button' +import { ApiConnectionMod } from '@/app/components/base/icons/src/vender/solid/development' +import SearchInput from '@/app/components/base/search-input' // Services import { fetchDatasetApiBaseUrl } from '@/service/datasets' @@ -24,12 +27,14 @@ import { fetchDatasetApiBaseUrl } from '@/service/datasets' import { useTabSearchParams } from '@/hooks/use-tab-searchparams' import { useStore as useTagStore } from '@/app/components/base/tag-management/store' import { useAppContext } from '@/context/app-context' +import { useExternalApiPanel } from '@/context/external-api-panel-context' const Container = () => { const { t } = useTranslation() const router = useRouter() const { currentWorkspace } = useAppContext() const showTagManagementModal = useTagStore(s => s.showTagManagementModal) + const { showExternalApiPanel, setShowExternalApiPanel } = useExternalApiPanel() const options = useMemo(() => { return [ @@ -66,7 +71,7 @@ const Container = () => { useEffect(() => { if (currentWorkspace.role === 'normal') return router.replace('/apps') - }, [currentWorkspace]) + }, [currentWorkspace, router]) return (
@@ -79,19 +84,19 @@ const Container = () => { {activeTab === 'dataset' && (
- handleKeywordsChange(e.target.value)} - onClear={() => handleKeywordsChange('')} - /> + +
+
)} {activeTab === 'api' && data && }
- {activeTab === 'dataset' && ( <> @@ -101,10 +106,10 @@ const Container = () => { )} )} - {activeTab === 'api' && data && } -
+ {showExternalApiPanel && setShowExternalApiPanel(false)} />} + ) } diff --git a/web/app/(commonLayout)/datasets/DatasetCard.tsx b/web/app/(commonLayout)/datasets/DatasetCard.tsx index f66c6bccf4..e8ccddbcb7 100644 --- a/web/app/(commonLayout)/datasets/DatasetCard.tsx +++ b/web/app/(commonLayout)/datasets/DatasetCard.tsx @@ -18,6 +18,7 @@ import Divider from '@/app/components/base/divider' import RenameDatasetModal from '@/app/components/datasets/rename-modal' import type { Tag } from '@/app/components/base/tag-management/constant' import TagSelector from '@/app/components/base/tag-management/selector' +import CornerLabel from '@/app/components/base/corner-label' import { useAppContext } from '@/context/app-context' export type DatasetCardProps = { @@ -32,6 +33,7 @@ const DatasetCard = ({ const { t } = useTranslation() const { notify } = useContext(ToastContext) const { push } = useRouter() + const EXTERNAL_PROVIDER = 'external' as const const { isCurrentWorkspaceDatasetOperator } = useAppContext() const [tags, setTags] = useState(dataset.tags) @@ -39,6 +41,7 @@ const DatasetCard = ({ const [showRenameModal, setShowRenameModal] = useState(false) const [showConfirmDelete, setShowConfirmDelete] = useState(false) const [confirmMessage, setConfirmMessage] = useState('') + const isExternalProvider = (provider: string): boolean => provider === EXTERNAL_PROVIDER const detectIsUsedByApp = useCallback(async () => { try { const { is_using: isUsedByApp } = await checkIsUsedInApp(dataset.id) @@ -108,13 +111,16 @@ const DatasetCard = ({ return ( <>
{ e.preventDefault() - push(`/datasets/${dataset.id}/documents`) + isExternalProvider(dataset.provider) + ? push(`/datasets/${dataset.id}/hitTesting`) + : push(`/datasets/${dataset.id}/documents`) }} > + {isExternalProvider(dataset.provider) && }
- {dataset.document_count}{t('dataset.documentCount')} - · - {Math.round(dataset.word_count / 1000)}{t('dataset.wordCount')} - · - {dataset.app_count}{t('dataset.appCount')} + {dataset.provider === 'external' + ? <> + {dataset.app_count}{t('dataset.appCount')} + + : <> + {dataset.document_count}{t('dataset.documentCount')} + · + {Math.round(dataset.word_count / 1000)}{t('dataset.wordCount')} + · + {dataset.app_count}{t('dataset.appCount')} + + }
diff --git a/web/app/(commonLayout)/datasets/NewDatasetCard.tsx b/web/app/(commonLayout)/datasets/NewDatasetCard.tsx index f76efa5769..5dd244ad41 100644 --- a/web/app/(commonLayout)/datasets/NewDatasetCard.tsx +++ b/web/app/(commonLayout)/datasets/NewDatasetCard.tsx @@ -4,21 +4,32 @@ import { forwardRef } from 'react' import { useTranslation } from 'react-i18next' import { RiAddLine, + RiArrowRightLine, } from '@remixicon/react' const CreateAppCard = forwardRef((_, ref) => { const { t } = useTranslation() return ( - -
- ) }) diff --git a/web/app/(commonLayout)/datasets/connect/page.tsx b/web/app/(commonLayout)/datasets/connect/page.tsx new file mode 100644 index 0000000000..724c506a7f --- /dev/null +++ b/web/app/(commonLayout)/datasets/connect/page.tsx @@ -0,0 +1,8 @@ +import React from 'react' +import ExternalKnowledgeBaseConnector from '@/app/components/datasets/external-knowledge-base/connector' + +const ExternalKnowledgeBaseCreation = () => { + return +} + +export default ExternalKnowledgeBaseCreation diff --git a/web/app/(commonLayout)/datasets/layout.tsx b/web/app/(commonLayout)/datasets/layout.tsx new file mode 100644 index 0000000000..aecb537aa6 --- /dev/null +++ b/web/app/(commonLayout)/datasets/layout.tsx @@ -0,0 +1,14 @@ +'use client' + +import { ExternalApiPanelProvider } from '@/context/external-api-panel-context' +import { ExternalKnowledgeApiProvider } from '@/context/external-knowledge-api-context' + +export default function DatasetsLayout({ children }: { children: React.ReactNode }) { + return ( + + + {children} + + + ) +} diff --git a/web/app/(commonLayout)/datasets/page.tsx b/web/app/(commonLayout)/datasets/page.tsx index 5aa11aa275..096a1b8979 100644 --- a/web/app/(commonLayout)/datasets/page.tsx +++ b/web/app/(commonLayout)/datasets/page.tsx @@ -1,9 +1,7 @@ import Container from './Container' const AppList = async () => { - return ( - - ) + return } export const metadata = { diff --git a/web/app/(commonLayout)/datasets/store.ts b/web/app/(commonLayout)/datasets/store.ts new file mode 100644 index 0000000000..40b7b15594 --- /dev/null +++ b/web/app/(commonLayout)/datasets/store.ts @@ -0,0 +1,11 @@ +import { create } from 'zustand' + +type DatasetStore = { + showExternalApiPanel: boolean + setShowExternalApiPanel: (show: boolean) => void +} + +export const useDatasetStore = create(set => ({ + showExternalApiPanel: false, + setShowExternalApiPanel: show => set({ showExternalApiPanel: show }), +})) diff --git a/web/app/components/app-sidebar/basic.tsx b/web/app/components/app-sidebar/basic.tsx index c939cb7bb3..51fc10721e 100644 --- a/web/app/components/app-sidebar/basic.tsx +++ b/web/app/components/app-sidebar/basic.tsx @@ -1,4 +1,5 @@ import React from 'react' +import { useTranslation } from 'react-i18next' import AppIcon from '../base/app-icon' import Tooltip from '@/app/components/base/tooltip' @@ -6,6 +7,7 @@ export type IAppBasicProps = { iconType?: 'app' | 'api' | 'dataset' | 'webapp' | 'notion' icon?: string icon_background?: string | null + isExternal?: boolean name: string type: string | React.ReactNode hoverTip?: string @@ -52,7 +54,9 @@ const ICON_MAP = { notion: , } -export default function AppBasic({ icon, icon_background, name, type, hoverTip, textStyle, mode = 'expand', iconType = 'app' }: IAppBasicProps) { +export default function AppBasic({ icon, icon_background, name, isExternal, type, hoverTip, textStyle, mode = 'expand', iconType = 'app' }: IAppBasicProps) { + const { t } = useTranslation() + return (
{icon && icon_background && iconType === 'app' && ( @@ -83,6 +87,7 @@ export default function AppBasic({ icon, icon_background, name, type, hoverTip, }
{type}
+
{isExternal ? t('dataset.externalTag') : ''}
}
) diff --git a/web/app/components/app-sidebar/index.tsx b/web/app/components/app-sidebar/index.tsx index 5d5d407dc0..5ee063ad64 100644 --- a/web/app/components/app-sidebar/index.tsx +++ b/web/app/components/app-sidebar/index.tsx @@ -15,6 +15,7 @@ export type IAppDetailNavProps = { iconType?: 'app' | 'dataset' | 'notion' title: string desc: string + isExternal?: boolean icon: string icon_background: string navigation: Array<{ @@ -26,7 +27,7 @@ export type IAppDetailNavProps = { extraInfo?: (modeState: string) => React.ReactNode } -const AppDetailNav = ({ title, desc, icon, icon_background, navigation, extraInfo, iconType = 'app' }: IAppDetailNavProps) => { +const AppDetailNav = ({ title, desc, isExternal, icon, icon_background, navigation, extraInfo, iconType = 'app' }: IAppDetailNavProps) => { const { appSidebarExpand, setAppSiderbarExpand } = useAppStore(useShallow(state => ({ appSidebarExpand: state.appSidebarExpand, setAppSiderbarExpand: state.setAppSiderbarExpand, @@ -70,6 +71,7 @@ const AppDetailNav = ({ title, desc, icon, icon_background, navigation, extraInf icon_background={icon_background} name={title} type={desc} + isExternal={isExternal} /> )} diff --git a/web/app/components/app/configuration/dataset-config/card-item/item.tsx b/web/app/components/app/configuration/dataset-config/card-item/item.tsx index 184a598e10..9c5e6fa785 100644 --- a/web/app/components/app/configuration/dataset-config/card-item/item.tsx +++ b/web/app/components/app/configuration/dataset-config/card-item/item.tsx @@ -5,6 +5,7 @@ import { RiDeleteBinLine, RiEditLine, } from '@remixicon/react' +import { useTranslation } from 'react-i18next' import SettingsModal from '../settings-modal' import type { DataSet } from '@/models/datasets' import { DataSourceType } from '@/models/datasets' @@ -33,6 +34,7 @@ const Item: FC = ({ const isMobile = media === MediaType.mobile const [showSettingsModal, setShowSettingsModal] = useState(false) const { formatIndexingTechniqueAndMethod } = useKnowledge() + const { t } = useTranslation() const handleSave = (newDataset: DataSet) => { onSave(newDataset) @@ -65,9 +67,11 @@ const Item: FC = ({
{config.name}
- + {config.provider === 'external' + ? + : }
diff --git a/web/app/components/app/configuration/dataset-config/params-config/config-content.tsx b/web/app/components/app/configuration/dataset-config/params-config/config-content.tsx index 91cae54bb8..f99496b14f 100644 --- a/web/app/components/app/configuration/dataset-config/params-config/config-content.tsx +++ b/web/app/components/app/configuration/dataset-config/params-config/config-content.tsx @@ -174,6 +174,20 @@ const ConfigContent: FC = ({
) } + { + selectedDatasetsMode.mixtureInternalAndExternal && ( +
+ {t('dataset.mixtureInternalAndExternalTip')} +
+ ) + } + { + selectedDatasetsMode.allExternal && ( +
+ {t('dataset.allExternalTip')} +
+ ) + } { selectedDatasetsMode.mixtureHighQualityAndEconomic && ( @@ -229,15 +243,15 @@ const ConfigContent: FC = ({ /> ) } -
{t('common.modelProvider.rerankModel.key')}
+
{t('common.modelProvider.rerankModel.key')}
{t('common.modelProvider.rerankModel.tip')} } - popupClassName='ml-0.5' - triggerClassName='ml-0.5 w-3.5 h-3.5' + popupClassName='ml-1' + triggerClassName='ml-1 w-4 h-4' />
diff --git a/web/app/components/app/configuration/dataset-config/params-config/index.tsx b/web/app/components/app/configuration/dataset-config/params-config/index.tsx index 656cbfea65..2d3df0b039 100644 --- a/web/app/components/app/configuration/dataset-config/params-config/index.tsx +++ b/web/app/components/app/configuration/dataset-config/params-config/index.tsx @@ -39,13 +39,26 @@ const ParamsConfig = ({ useEffect(() => { const { allEconomic, + allHighQuality, + allHighQualityFullTextSearch, + allHighQualityVectorSearch, + allExternal, + mixtureHighQualityAndEconomic, + inconsistentEmbeddingModel, + mixtureInternalAndExternal, } = getSelectedDatasetsMode(selectedDatasets) const { datasets, retrieval_model, score_threshold_enabled, ...restConfigs } = datasetConfigs let rerankEnable = restConfigs.reranking_enable - if (allEconomic && !restConfigs.reranking_model?.reranking_provider_name && rerankEnable === undefined) + if ((allEconomic && !restConfigs.reranking_model?.reranking_provider_name && rerankEnable === undefined) || allExternal) rerankEnable = false + if (allEconomic || allHighQuality || allHighQualityFullTextSearch || allHighQualityVectorSearch || (allExternal && selectedDatasets.length === 1)) + setRerankSettingModalOpen(false) + + if (mixtureHighQualityAndEconomic || inconsistentEmbeddingModel || mixtureInternalAndExternal || (allExternal && selectedDatasets.length > 1)) + setRerankSettingModalOpen(true) + setTempDataSetConfigs({ ...getMultipleRetrievalConfig({ top_k: restConfigs.top_k, diff --git a/web/app/components/app/configuration/dataset-config/select-dataset/index.tsx b/web/app/components/app/configuration/dataset-config/select-dataset/index.tsx index 4493755ba0..0d94e599b4 100644 --- a/web/app/components/app/configuration/dataset-config/select-dataset/index.tsx +++ b/web/app/components/app/configuration/dataset-config/select-dataset/index.tsx @@ -47,7 +47,7 @@ const SelectDataSet: FC = ({ const { data, has_more } = await fetchDatasets({ url: '/datasets', params: { page } }) setPage(getPage() + 1) setIsNoMore(!has_more) - const newList = [...(datasets || []), ...data.filter(item => item.indexing_technique)] + const newList = [...(datasets || []), ...data.filter(item => item.indexing_technique || item.provider === 'external')] setDataSets(newList) setLoaded(true) if (!selected.find(item => !item.name)) @@ -145,6 +145,11 @@ const SelectDataSet: FC = ({ /> ) } + { + item.provider === 'external' && ( + + ) + }
))} diff --git a/web/app/components/app/configuration/dataset-config/settings-modal/index.tsx b/web/app/components/app/configuration/dataset-config/settings-modal/index.tsx index dc79042525..81a2ccc72b 100644 --- a/web/app/components/app/configuration/dataset-config/settings-modal/index.tsx +++ b/web/app/components/app/configuration/dataset-config/settings-modal/index.tsx @@ -5,8 +5,10 @@ import { useTranslation } from 'react-i18next' import { isEqual } from 'lodash-es' import { RiCloseLine } from '@remixicon/react' import { BookOpenIcon } from '@heroicons/react/24/outline' +import { ApiConnectionMod } from '@/app/components/base/icons/src/vender/solid/development' import cn from '@/utils/classnames' import IndexMethodRadio from '@/app/components/datasets/settings/index-method-radio' +import Divider from '@/app/components/base/divider' import Button from '@/app/components/base/button' import Input from '@/app/components/base/input' import Textarea from '@/app/components/base/textarea' @@ -16,6 +18,7 @@ import { updateDatasetSetting } from '@/service/datasets' import { useAppContext } from '@/context/app-context' import { useModalContext } from '@/context/modal-context' import type { RetrievalConfig } from '@/types/app' +import RetrievalSettings from '@/app/components/datasets/external-knowledge-base/create/RetrievalSettings' import RetrievalMethodConfig from '@/app/components/datasets/common/retrieval-method-config' import EconomicalRetrievalMethodConfig from '@/app/components/datasets/common/economical-retrieval-method-config' import { ensureRerankModelSelected, isReRankModelSelected } from '@/app/components/datasets/common/check-rerank-model' @@ -58,6 +61,9 @@ const SettingsModal: FC = ({ const { t } = useTranslation() const { notify } = useToastContext() const ref = useRef(null) + const [topK, setTopK] = useState(currentDataset?.external_retrieval_model.top_k ?? 2) + const [scoreThreshold, setScoreThreshold] = useState(currentDataset?.external_retrieval_model.score_threshold ?? 0.5) + const [scoreThresholdEnabled, setScoreThresholdEnabled] = useState(currentDataset?.external_retrieval_model.score_threshold_enabled ?? false) const { setShowAccountSettingModal } = useModalContext() const [loading, setLoading] = useState(false) @@ -75,6 +81,15 @@ const SettingsModal: FC = ({ const [isHideChangedTip, setIsHideChangedTip] = useState(false) const isRetrievalChanged = !isEqual(retrievalConfig, localeCurrentDataset?.retrieval_model_dict) || indexMethod !== localeCurrentDataset?.indexing_technique + const handleSettingsChange = (data: { top_k?: number; score_threshold?: number; score_threshold_enabled?: boolean }) => { + if (data.top_k !== undefined) + setTopK(data.top_k) + if (data.score_threshold !== undefined) + setScoreThreshold(data.score_threshold) + if (data.score_threshold_enabled !== undefined) + setScoreThresholdEnabled(data.score_threshold_enabled) + } + const handleSave = async () => { if (loading) return @@ -109,10 +124,17 @@ const SettingsModal: FC = ({ description, permission, indexing_technique: indexMethod, + external_retrieval_model: { + top_k: topK, + score_threshold: scoreThreshold, + score_threshold_enabled: scoreThresholdEnabled, + }, retrieval_model: { ...postRetrievalConfig, score_threshold: postRetrievalConfig.score_threshold_enabled ? postRetrievalConfig.score_threshold : 0, }, + external_knowledge_id: currentDataset!.external_knowledge_info.external_knowledge_id, + external_knowledge_api_id: currentDataset!.external_knowledge_info.external_knowledge_api_id, embedding_model: localeCurrentDataset.embedding_model, embedding_model_provider: localeCurrentDataset.embedding_model_provider, }, @@ -180,7 +202,7 @@ const SettingsModal: FC = ({ }}>
- {t('datasetSettings.form.name')} +
{t('datasetSettings.form.name')}
= ({
- {t('datasetSettings.form.desc')} +
{t('datasetSettings.form.desc')}