diff --git a/.github/workflows/build-push.yml b/.github/workflows/build-push.yml index cc735ae67c..2235ccc5ed 100644 --- a/.github/workflows/build-push.yml +++ b/.github/workflows/build-push.yml @@ -6,8 +6,9 @@ on: - "main" - "deploy/dev" - "deploy/enterprise" - tags: - - "*" + - "e-300" + release: + types: [published] concurrency: group: build-push-${{ github.head_ref || github.run_id }} diff --git a/.markdownlint.json b/.markdownlint.json new file mode 100644 index 0000000000..cb4aa7ebd8 --- /dev/null +++ b/.markdownlint.json @@ -0,0 +1,3 @@ +{ + "MD024": false +} diff --git a/CHANGELOG.md b/CHANGELOG.md new file mode 100644 index 0000000000..57c6180068 --- /dev/null +++ b/CHANGELOG.md @@ -0,0 +1,32 @@ +# Changelog + +All notable changes to Dify will be documented in this file. + +The format is based on [Keep a Changelog](https://keepachangelog.com/en/1.0.0/), +and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0.html). + +## [0.15.7] - 2025-04-27 + +### Added + +- Added support for GPT-4.1 in model providers (#18912) +- Added support for Amazon Bedrock DeepSeek-R1 model (#18908) +- Added support for Amazon Bedrock Claude Sonnet 3.7 model (#18788) +- Refined version compatibility logic in app DSL service + +### Fixed + +- Fixed issue with creating apps from template categories (#18807, #18868) +- Fixed DSL version check when creating apps from explore templates (#18872, #18878) + +## [0.15.6] - 2025-04-22 + +### Security + +- Fixed clickjacking vulnerability (#18552) +- Fixed reset password security issue (#18366) +- Updated reset password token when email code verification succeeds (#18362) + +### Fixed + +- Fixed Vertex AI Gemini 2.0 Flash 001 schema (#18405) diff --git a/api/controllers/console/app/app.py b/api/controllers/console/app/app.py index 3e908b76a7..0785033334 100644 --- a/api/controllers/console/app/app.py +++ b/api/controllers/console/app/app.py @@ -2,30 +2,28 @@ import uuid from typing import cast from flask_login import current_user # type: ignore -from flask_restful import Resource, inputs, marshal, marshal_with, reqparse # type: ignore +from flask_restful import (Resource, inputs, marshal, # type: ignore + marshal_with, reqparse) from sqlalchemy import select from sqlalchemy.orm import Session from werkzeug.exceptions import BadRequest, Forbidden, abort from controllers.console import api from controllers.console.app.wraps import get_app_model -from controllers.console.wraps import ( - account_initialization_required, - cloud_edition_billing_resource_check, - enterprise_license_required, - setup_required, -) +from controllers.console.wraps import (account_initialization_required, + cloud_edition_billing_resource_check, + enterprise_license_required, + setup_required) from core.ops.ops_trace_manager import OpsTraceManager from extensions.ext_database import db -from fields.app_fields import ( - app_detail_fields, - app_detail_fields_with_site, - app_pagination_fields, -) +from fields.app_fields import (app_detail_fields, app_detail_fields_with_site, + app_pagination_fields) from libs.login import login_required from models import Account, App from services.app_dsl_service import AppDslService, ImportMode from services.app_service import AppService +from services.enterprise.enterprise_service import EnterpriseService +from services.feature_service import FeatureService ALLOW_CREATE_APP_MODES = ["chat", "agent-chat", "advanced-chat", "workflow", "completion"] @@ -75,7 +73,17 @@ class AppListApi(Resource): if not app_pagination: return {"data": [], "total": 0, "page": 1, "limit": 20, "has_more": False} - return marshal(app_pagination, app_pagination_fields) + if FeatureService.get_system_features().webapp_auth.enabled: + app_ids = [str(app.id) for app in app_pagination.items] + res = EnterpriseService.WebAppAuth.batch_get_app_access_mode_by_id(app_ids=app_ids) + if len(res) != len(app_ids): + raise BadRequest("Invalid app id in webapp auth") + + for app in app_pagination.items: + if str(app.id) in res: + app.access_mode = res[str(app.id)].access_mode + + return marshal(app_pagination, app_pagination_fields), 200 @setup_required @login_required @@ -119,6 +127,10 @@ class AppApi(Resource): app_model = app_service.get_app(app_model) + if FeatureService.get_system_features().webapp_auth.enabled: + app_setting = EnterpriseService.WebAppAuth.get_app_access_mode_by_id(app_id=str(app_model.id)) + app_model.access_mode = app_setting.access_mode + return app_model @setup_required diff --git a/api/controllers/console/auth/forgot_password.py b/api/controllers/console/auth/forgot_password.py index d4a33645ab..33c33c30d4 100644 --- a/api/controllers/console/auth/forgot_password.py +++ b/api/controllers/console/auth/forgot_password.py @@ -24,7 +24,7 @@ from libs.password import hash_password, valid_password from models.account import Account from services.account_service import AccountService, TenantService from services.errors.account import AccountRegisterError -from services.errors.workspace import WorkSpaceNotAllowedCreateError +from services.errors.workspace import WorkSpaceNotAllowedCreateError, WorkspacesLimitExceededError from services.feature_service import FeatureService @@ -119,6 +119,9 @@ class ForgotPasswordResetApi(Resource): if not reset_data: raise InvalidTokenError() # Must use token in reset phase + if reset_data.get("phase", "") != "reset": + raise InvalidTokenError() + # Must use token in reset phase if reset_data.get("phase", "") != "reset": raise InvalidTokenError() diff --git a/api/controllers/console/auth/login.py b/api/controllers/console/auth/login.py index 16c1dcc441..fdcc47d680 100644 --- a/api/controllers/console/auth/login.py +++ b/api/controllers/console/auth/login.py @@ -21,6 +21,7 @@ from controllers.console.error import ( AccountNotFound, EmailSendIpLimitError, NotAllowedCreateWorkspace, + WorkspacesLimitExceeded, ) from controllers.console.wraps import email_password_login_enabled, setup_required from events.tenant_event import tenant_was_created @@ -30,7 +31,7 @@ from models.account import Account from services.account_service import AccountService, RegisterService, TenantService from services.billing_service import BillingService from services.errors.account import AccountRegisterError -from services.errors.workspace import WorkSpaceNotAllowedCreateError +from services.errors.workspace import WorkSpaceNotAllowedCreateError, WorkspacesLimitExceededError from services.feature_service import FeatureService @@ -88,10 +89,15 @@ class LoginApi(Resource): # SELF_HOSTED only have one workspace tenants = TenantService.get_join_tenants(account) if len(tenants) == 0: - return { - "result": "fail", - "data": "workspace not found, please contact system admin to invite you to join in a workspace", - } + system_features = FeatureService.get_system_features() + + if system_features.is_allow_create_workspace and not system_features.license.workspaces.is_available(): + raise WorkspacesLimitExceeded() + else: + return { + "result": "fail", + "data": "workspace not found, please contact system admin to invite you to join in a workspace", + } token_pair = AccountService.login(account=account, ip_address=extract_remote_ip(request)) AccountService.reset_login_error_rate_limit(args["email"]) @@ -198,6 +204,9 @@ class EmailCodeLoginApi(Resource): if account: tenant = TenantService.get_join_tenants(account) if not tenant: + workspaces = FeatureService.get_system_features().license.workspaces + if not workspaces.is_available(): + raise WorkspacesLimitExceeded() if not FeatureService.get_system_features().is_allow_create_workspace: raise NotAllowedCreateWorkspace() else: @@ -215,6 +224,8 @@ class EmailCodeLoginApi(Resource): return NotAllowedCreateWorkspace() except AccountRegisterError as are: raise AccountInFreezeError() + except WorkspacesLimitExceededError: + raise WorkspacesLimitExceeded() token_pair = AccountService.login(account, ip_address=extract_remote_ip(request)) AccountService.reset_login_error_rate_limit(args["email"]) return {"result": "success", "data": token_pair.model_dump()} diff --git a/api/controllers/console/error.py b/api/controllers/console/error.py index b8fd1f0358..6944c56bf8 100644 --- a/api/controllers/console/error.py +++ b/api/controllers/console/error.py @@ -46,6 +46,18 @@ class NotAllowedCreateWorkspace(BaseHTTPException): code = 400 +class WorkspaceMembersLimitExceeded(BaseHTTPException): + error_code = "limit_exceeded" + description = "Unable to add member because the maximum workspace's member limit was exceeded" + code = 400 + + +class WorkspacesLimitExceeded(BaseHTTPException): + error_code = "limit_exceeded" + description = "Unable to create workspace because the maximum workspace limit was exceeded" + code = 400 + + class AccountBannedError(BaseHTTPException): error_code = "account_banned" description = "Account is banned." diff --git a/api/controllers/console/explore/error.py b/api/controllers/console/explore/error.py index 18221b7797..1e05ff4206 100644 --- a/api/controllers/console/explore/error.py +++ b/api/controllers/console/explore/error.py @@ -23,3 +23,9 @@ class AppSuggestedQuestionsAfterAnswerDisabledError(BaseHTTPException): error_code = "app_suggested_questions_after_answer_disabled" description = "Function Suggested questions after answer disabled." code = 403 + + +class AppAccessDeniedError(BaseHTTPException): + error_code = "access_denied" + description = "App access denied." + code = 403 diff --git a/api/controllers/console/explore/installed_app.py b/api/controllers/console/explore/installed_app.py index 132da11878..957ce4c2fa 100644 --- a/api/controllers/console/explore/installed_app.py +++ b/api/controllers/console/explore/installed_app.py @@ -1,20 +1,26 @@ +import logging from datetime import UTC, datetime from typing import Any from flask import request from flask_login import current_user # type: ignore -from flask_restful import Resource, inputs, marshal_with, reqparse # type: ignore +from flask_restful import (Resource, inputs, marshal_with, # type: ignore + reqparse) from sqlalchemy import and_ from werkzeug.exceptions import BadRequest, Forbidden, NotFound from controllers.console import api from controllers.console.explore.wraps import InstalledAppResource -from controllers.console.wraps import account_initialization_required, cloud_edition_billing_resource_check +from controllers.console.wraps import (account_initialization_required, + cloud_edition_billing_resource_check) from extensions.ext_database import db from fields.installed_app_fields import installed_app_list_fields from libs.login import login_required from models import App, InstalledApp, RecommendedApp from services.account_service import TenantService +from services.app_service import AppService +from services.enterprise.enterprise_service import EnterpriseService +from services.feature_service import FeatureService class InstalledAppsListApi(Resource): @@ -48,6 +54,23 @@ class InstalledAppsListApi(Resource): for installed_app in installed_apps if installed_app.app is not None ] + + # filter out apps that user doesn't have access to + if FeatureService.get_system_features().webapp_auth.enabled: + user_id = current_user.id + res = [] + for installed_app in installed_app_list: + app_code = AppService.get_app_code_by_id(str(installed_app["app"].id)) + if EnterpriseService.WebAppAuth.is_user_allowed_to_access_webapp( + user_id=user_id, + app_code=app_code, + ): + res.append(installed_app) + installed_app_list = res + logging.info( + f"installed_app_list: {installed_app_list}, user_id: {user_id}" + ) + installed_app_list.sort( key=lambda app: ( -app["is_pinned"], diff --git a/api/controllers/console/explore/wraps.py b/api/controllers/console/explore/wraps.py index b7ba81fba2..b67ef6a949 100644 --- a/api/controllers/console/explore/wraps.py +++ b/api/controllers/console/explore/wraps.py @@ -4,10 +4,14 @@ from flask_login import current_user # type: ignore from flask_restful import Resource # type: ignore from werkzeug.exceptions import NotFound +from controllers.console.explore.error import AppAccessDeniedError from controllers.console.wraps import account_initialization_required from extensions.ext_database import db from libs.login import login_required from models import InstalledApp +from services.app_service import AppService +from services.enterprise.enterprise_service import EnterpriseService +from services.feature_service import FeatureService def installed_app_required(view=None): @@ -48,6 +52,30 @@ def installed_app_required(view=None): return decorator +def user_allowed_to_access_app(view=None): + def decorator(view): + @wraps(view) + def decorated(installed_app: InstalledApp, *args, **kwargs): + feature = FeatureService.get_system_features() + if feature.webapp_auth.enabled: + app_id = installed_app.app_id + app_code = AppService.get_app_code_by_id(app_id) + res = EnterpriseService.WebAppAuth.is_user_allowed_to_access_webapp( + user_id=str(current_user.id), + app_code=app_code, + ) + if not res: + raise AppAccessDeniedError() + + return view(installed_app, *args, **kwargs) + + return decorated + if view: + return decorator(view) + return decorator + + class InstalledAppResource(Resource): # must be reversed if there are multiple decorators - method_decorators = [installed_app_required, account_initialization_required, login_required] + + method_decorators = [user_allowed_to_access_app, installed_app_required, account_initialization_required, login_required] diff --git a/api/controllers/console/workspace/members.py b/api/controllers/console/workspace/members.py index a2b41c1d38..3628aa1670 100644 --- a/api/controllers/console/workspace/members.py +++ b/api/controllers/console/workspace/members.py @@ -6,6 +6,7 @@ from flask_restful import Resource, abort, marshal_with, reqparse # type: ignor import services from configs import dify_config from controllers.console import api +from controllers.console.error import WorkspaceMembersLimitExceeded from controllers.console.wraps import ( account_initialization_required, cloud_edition_billing_resource_check, @@ -17,6 +18,7 @@ from libs.login import login_required from models.account import Account, TenantAccountRole from services.account_service import RegisterService, TenantService from services.errors.account import AccountAlreadyInTenantError +from services.feature_service import FeatureService class MemberListApi(Resource): @@ -54,6 +56,12 @@ class MemberInviteEmailApi(Resource): inviter = current_user invitation_results = [] console_web_url = dify_config.CONSOLE_WEB_URL + + workspace_members = FeatureService.get_features(tenant_id=inviter.current_tenant.id).workspace_members + + if not workspace_members.is_available(len(invitee_emails)): + raise WorkspaceMembersLimitExceeded() + for invitee_email in invitee_emails: try: token = RegisterService.invite_new_member( diff --git a/api/controllers/console/wraps.py b/api/controllers/console/wraps.py index 6911181d82..36ee8492b4 100644 --- a/api/controllers/console/wraps.py +++ b/api/controllers/console/wraps.py @@ -44,6 +44,17 @@ def only_edition_cloud(view): return decorated +def only_enterprise_edition(view): + @wraps(view) + def decorated(*args, **kwargs): + if not dify_config.ENTERPRISE_ENABLED: + abort(404) + + return view(*args, **kwargs) + + return decorated + + def only_edition_self_hosted(view): @wraps(view) def decorated(*args, **kwargs): diff --git a/api/controllers/inner_api/__init__.py b/api/controllers/inner_api/__init__.py index f147a3453f..f3543e95be 100644 --- a/api/controllers/inner_api/__init__.py +++ b/api/controllers/inner_api/__init__.py @@ -6,4 +6,5 @@ bp = Blueprint("inner_api", __name__, url_prefix="/inner/api") api = ExternalApi(bp) from .plugin import plugin +from . import mail from .workspace import workspace diff --git a/api/controllers/inner_api/mail.py b/api/controllers/inner_api/mail.py new file mode 100644 index 0000000000..47cbcb713c --- /dev/null +++ b/api/controllers/inner_api/mail.py @@ -0,0 +1,27 @@ +from flask_restful import ( + Resource, # type: ignore + reqparse, +) + +from controllers.console.wraps import setup_required +from controllers.inner_api import api +from controllers.inner_api.wraps import inner_api_only +from services.enterprise.mail_service import DifyMail, EnterpriseMailService + + +class EnterpriseMail(Resource): + @setup_required + @inner_api_only + def post(self): + parser = reqparse.RequestParser() + parser.add_argument("to", type=str, action="append", required=True) + parser.add_argument("subject", type=str, required=True) + parser.add_argument("body", type=str, required=True) + parser.add_argument("substitutions", type=dict, required=False) + args = parser.parse_args() + + EnterpriseMailService.send_mail(DifyMail(**args)) + return {"message": "success"}, 200 + + +api.add_resource(EnterpriseMail, "/enterprise/mail") diff --git a/api/controllers/web/app.py b/api/controllers/web/app.py index a84b846112..122ebc30c6 100644 --- a/api/controllers/web/app.py +++ b/api/controllers/web/app.py @@ -1,12 +1,16 @@ -from flask_restful import marshal_with # type: ignore + +from flask import request +from flask_restful import Resource, marshal_with, reqparse # type: ignore from controllers.common import fields from controllers.web import api from controllers.web.error import AppUnavailableError from controllers.web.wraps import WebApiResource from core.app.app_config.common.parameters_mapping import get_parameters_from_feature_dict +from libs.passport import PassportService from models.model import App, AppMode from services.app_service import AppService +from services.enterprise.enterprise_service import EnterpriseService class AppParameterApi(WebApiResource): @@ -40,5 +44,51 @@ class AppMeta(WebApiResource): return AppService().get_app_meta(app_model) +class AppAccessMode(Resource): + def get(self): + parser = reqparse.RequestParser() + parser.add_argument("appId", type=str, required=True, location="args") + args = parser.parse_args() + + app_id = args["appId"] + res = EnterpriseService.WebAppAuth.get_app_access_mode_by_id(app_id) + + return {"accessMode": res.access_mode} + + +class AppWebAuthPermission(Resource): + def get(self): + user_id = "visitor" + try: + auth_header = request.headers.get("Authorization") + if auth_header is None: + raise + if " " not in auth_header: + raise + + auth_scheme, tk = auth_header.split(None, 1) + auth_scheme = auth_scheme.lower() + if auth_scheme != "bearer": + raise + + decoded = PassportService().verify(tk) + user_id = decoded.get("user_id", "visitor") + except Exception as e: + pass + + parser = reqparse.RequestParser() + parser.add_argument("appId", type=str, required=True, location="args") + args = parser.parse_args() + + app_id = args["appId"] + app_code = AppService.get_app_code_by_id(app_id) + + res = EnterpriseService.WebAppAuth.is_user_allowed_to_access_webapp(str(user_id), app_code) + return {"result": res} + + api.add_resource(AppParameterApi, "/parameters") api.add_resource(AppMeta, "/meta") +# webapp auth apis +api.add_resource(AppAccessMode, "/webapp/access-mode") +api.add_resource(AppWebAuthPermission, "/webapp/permission") diff --git a/api/controllers/web/error.py b/api/controllers/web/error.py index 9fe5d08d54..4371e679db 100644 --- a/api/controllers/web/error.py +++ b/api/controllers/web/error.py @@ -121,9 +121,15 @@ class UnsupportedFileTypeError(BaseHTTPException): code = 415 -class WebSSOAuthRequiredError(BaseHTTPException): +class WebAppAuthRequiredError(BaseHTTPException): error_code = "web_sso_auth_required" - description = "Web SSO authentication required." + description = "Web app authentication required." + code = 401 + + +class WebAppAuthAccessDeniedError(BaseHTTPException): + error_code = "web_app_access_denied" + description = "You do not have permission to access this web app." code = 401 diff --git a/api/controllers/web/login.py b/api/controllers/web/login.py new file mode 100644 index 0000000000..4106e6a179 --- /dev/null +++ b/api/controllers/web/login.py @@ -0,0 +1,121 @@ +from flask import request +from flask_restful import Resource, reqparse +from jwt import InvalidTokenError # type: ignore +from web import api +from werkzeug.exceptions import BadRequest + +import services +from controllers.console.auth.error import EmailCodeError, EmailOrPasswordMismatchError, InvalidEmailError +from controllers.console.error import AccountBannedError, AccountNotFound +from controllers.console.wraps import setup_required +from libs.helper import email +from libs.password import valid_password +from services.account_service import AccountService +from services.webapp_auth_service import WebAppAuthService + + +class LoginApi(Resource): + """Resource for web app email/password login.""" + + def post(self): + """Authenticate user and login.""" + parser = reqparse.RequestParser() + parser.add_argument("email", type=email, required=True, location="json") + parser.add_argument("password", type=valid_password, required=True, location="json") + args = parser.parse_args() + + app_code = request.headers.get("X-App-Code") + if app_code is None: + raise BadRequest("X-App-Code header is missing.") + + try: + account = WebAppAuthService.authenticate(args["email"], args["password"]) + except services.errors.account.AccountLoginError: + raise AccountBannedError() + except services.errors.account.AccountPasswordError: + raise EmailOrPasswordMismatchError() + except services.errors.account.AccountNotFoundError: + raise AccountNotFound() + + WebAppAuthService._validate_user_accessibility(account=account, app_code=app_code) + + end_user = WebAppAuthService.create_end_user(email=args["email"], app_code=app_code) + + token = WebAppAuthService.login(account=account, app_code=app_code, end_user_id=end_user.id) + return {"result": "success", "token": token} + + +# class LogoutApi(Resource): +# @setup_required +# def get(self): +# account = cast(Account, flask_login.current_user) +# if isinstance(account, flask_login.AnonymousUserMixin): +# return {"result": "success"} +# flask_login.logout_user() +# return {"result": "success"} + + +class EmailCodeLoginSendEmailApi(Resource): + @setup_required + def post(self): + parser = reqparse.RequestParser() + parser.add_argument("email", type=email, required=True, location="json") + parser.add_argument("language", type=str, required=False, location="json") + args = parser.parse_args() + + if args["language"] is not None and args["language"] == "zh-Hans": + language = "zh-Hans" + else: + language = "en-US" + + account = WebAppAuthService.get_user_through_email(args["email"]) + if account is None: + raise AccountNotFound() + else: + token = WebAppAuthService.send_email_code_login_email(account=account, language=language) + + return {"result": "success", "data": token} + + +class EmailCodeLoginApi(Resource): + @setup_required + def post(self): + parser = reqparse.RequestParser() + parser.add_argument("email", type=str, required=True, location="json") + parser.add_argument("code", type=str, required=True, location="json") + parser.add_argument("token", type=str, required=True, location="json") + args = parser.parse_args() + + user_email = args["email"] + app_code = request.headers.get("X-App-Code") + if app_code is None: + raise BadRequest("X-App-Code header is missing.") + + token_data = WebAppAuthService.get_email_code_login_data(args["token"]) + if token_data is None: + raise InvalidTokenError() + + if token_data["email"] != args["email"]: + raise InvalidEmailError() + + if token_data["code"] != args["code"]: + raise EmailCodeError() + + WebAppAuthService.revoke_email_code_login_token(args["token"]) + account = WebAppAuthService.get_user_through_email(user_email) + if not account: + raise AccountNotFound() + + WebAppAuthService._validate_user_accessibility(account=account, app_code=app_code) + + end_user = WebAppAuthService.create_end_user(email=user_email, app_code=app_code) + + token = WebAppAuthService.login(account=account, app_code=app_code, end_user_id=end_user.id) + AccountService.reset_login_error_rate_limit(args["email"]) + return {"result": "success", "token": token} + + +api.add_resource(LoginApi, "/login") +# api.add_resource(LogoutApi, "/logout") +api.add_resource(EmailCodeLoginSendEmailApi, "/email-code-login") +api.add_resource(EmailCodeLoginApi, "/email-code-login/validity") diff --git a/api/controllers/web/passport.py b/api/controllers/web/passport.py index e30998c803..f386d6855b 100644 --- a/api/controllers/web/passport.py +++ b/api/controllers/web/passport.py @@ -5,7 +5,7 @@ from flask_restful import Resource # type: ignore from werkzeug.exceptions import NotFound, Unauthorized from controllers.web import api -from controllers.web.error import WebSSOAuthRequiredError +from controllers.web.error import WebAppAuthRequiredError from extensions.ext_database import db from libs.passport import PassportService from models.model import App, EndUser, Site @@ -24,10 +24,10 @@ class PassportResource(Resource): if app_code is None: raise Unauthorized("X-App-Code header is missing.") - if system_features.sso_enforced_for_web: - app_web_sso_enabled = EnterpriseService.get_app_web_sso_enabled(app_code).get("enabled", False) - if app_web_sso_enabled: - raise WebSSOAuthRequiredError() + if system_features.webapp_auth.enabled: + app_settings = EnterpriseService.WebAppAuth.get_app_access_mode_by_code(app_code=app_code) + if not app_settings or not app_settings.access_mode == "public": + raise WebAppAuthRequiredError() # get site from db and check if it is normal site = db.session.query(Site).filter(Site.code == app_code, Site.status == "normal").first() diff --git a/api/controllers/web/wraps.py b/api/controllers/web/wraps.py index 1b4d263bee..8d35b8e4be 100644 --- a/api/controllers/web/wraps.py +++ b/api/controllers/web/wraps.py @@ -4,7 +4,7 @@ from flask import request from flask_restful import Resource # type: ignore from werkzeug.exceptions import BadRequest, NotFound, Unauthorized -from controllers.web.error import WebSSOAuthRequiredError +from controllers.web.error import WebAppAuthAccessDeniedError, WebAppAuthRequiredError from extensions.ext_database import db from libs.passport import PassportService from models.model import App, EndUser, Site @@ -57,35 +57,53 @@ def decode_jwt_token(): if not end_user: raise NotFound() - _validate_web_sso_token(decoded, system_features, app_code) + # for enterprise webapp auth + app_web_auth_enabled = False + if system_features.webapp_auth.enabled: + app_web_auth_enabled = ( + EnterpriseService.WebAppAuth.get_app_access_mode_by_code(app_code=app_code).access_mode != "public" + ) + + _validate_webapp_token(decoded, app_web_auth_enabled, system_features.webapp_auth.enabled) + _validate_user_accessibility(decoded, app_code, app_web_auth_enabled, system_features.webapp_auth.enabled) return app_model, end_user except Unauthorized as e: - if system_features.sso_enforced_for_web: - app_web_sso_enabled = EnterpriseService.get_app_web_sso_enabled(app_code).get("enabled", False) - if app_web_sso_enabled: - raise WebSSOAuthRequiredError() + if system_features.webapp_auth.enabled: + app_web_auth_enabled = ( + EnterpriseService.WebAppAuth.get_app_access_mode_by_code(app_code=app_code).access_mode != "public" + ) + if app_web_auth_enabled: + raise WebAppAuthRequiredError() raise Unauthorized(e.description) -def _validate_web_sso_token(decoded, system_features, app_code): - app_web_sso_enabled = False - - # Check if SSO is enforced for web, and if the token source is not SSO, raise an error and redirect to SSO login - if system_features.sso_enforced_for_web: - app_web_sso_enabled = EnterpriseService.get_app_web_sso_enabled(app_code).get("enabled", False) - if app_web_sso_enabled: - source = decoded.get("token_source") - if not source or source != "sso": - raise WebSSOAuthRequiredError() - - # Check if SSO is not enforced for web, and if the token source is SSO, - # raise an error and redirect to normal passport login - if not system_features.sso_enforced_for_web or not app_web_sso_enabled: +def _validate_webapp_token(decoded, app_web_auth_enabled: bool, system_webapp_auth_enabled: bool): + # Check if authentication is enforced for web app, and if the token source is not webapp, + # raise an error and redirect to login + if system_webapp_auth_enabled and app_web_auth_enabled: source = decoded.get("token_source") - if source and source == "sso": - raise Unauthorized("sso token expired.") + if not source or source != "webapp": + raise WebAppAuthRequiredError() + + # Check if authentication is not enforced for web, and if the token source is webapp, + # raise an error and redirect to normal passport login + if not system_webapp_auth_enabled or not app_web_auth_enabled: + source = decoded.get("token_source") + if source and source == "webapp": + raise Unauthorized("webapp token expired.") + + +def _validate_user_accessibility(decoded, app_code, app_web_auth_enabled: bool, system_webapp_auth_enabled: bool): + if system_webapp_auth_enabled and app_web_auth_enabled: + # Check if the user is allowed to access the web app + user_id = decoded.get("user_id") + if not user_id: + raise WebAppAuthRequiredError() + + if not EnterpriseService.WebAppAuth.is_user_allowed_to_access_webapp(user_id, app_code=app_code): + raise WebAppAuthAccessDeniedError() class WebApiResource(Resource): diff --git a/api/core/agent/cot_agent_runner.py b/api/core/agent/cot_agent_runner.py index feb8abf6ef..e12acd31ef 100644 --- a/api/core/agent/cot_agent_runner.py +++ b/api/core/agent/cot_agent_runner.py @@ -107,7 +107,6 @@ class CotAgentRunner(BaseAgentRunner, ABC): # recalc llm max tokens prompt_messages = self._organize_prompt_messages() - self.recalc_llm_max_tokens(self.model_config, prompt_messages) # invoke model chunks = model_instance.invoke_llm( prompt_messages=prompt_messages, diff --git a/api/core/agent/fc_agent_runner.py b/api/core/agent/fc_agent_runner.py index a1110e7709..f71639b08a 100644 --- a/api/core/agent/fc_agent_runner.py +++ b/api/core/agent/fc_agent_runner.py @@ -85,7 +85,6 @@ class FunctionCallAgentRunner(BaseAgentRunner): # recalc llm max tokens prompt_messages = self._organize_prompt_messages() - self.recalc_llm_max_tokens(self.model_config, prompt_messages) # invoke model chunks: Union[Generator[LLMResultChunk, None, None], LLMResult] = model_instance.invoke_llm( prompt_messages=prompt_messages, diff --git a/api/core/app/apps/base_app_runner.py b/api/core/app/apps/base_app_runner.py index c813dbb9d1..c44283de45 100644 --- a/api/core/app/apps/base_app_runner.py +++ b/api/core/app/apps/base_app_runner.py @@ -15,7 +15,6 @@ from core.app.features.annotation_reply.annotation_reply import AnnotationReplyF from core.app.features.hosting_moderation.hosting_moderation import HostingModerationFeature from core.external_data_tool.external_data_fetch import ExternalDataFetch from core.memory.token_buffer_memory import TokenBufferMemory -from core.model_manager import ModelInstance from core.model_runtime.entities.llm_entities import LLMResult, LLMResultChunk, LLMResultChunkDelta, LLMUsage from core.model_runtime.entities.message_entities import ( AssistantPromptMessage, @@ -35,106 +34,6 @@ if TYPE_CHECKING: class AppRunner: - def get_pre_calculate_rest_tokens( - self, - app_record: App, - model_config: ModelConfigWithCredentialsEntity, - prompt_template_entity: PromptTemplateEntity, - inputs: Mapping[str, str], - files: Sequence["File"], - query: Optional[str] = None, - ) -> int: - """ - Get pre calculate rest tokens - :param app_record: app record - :param model_config: model config entity - :param prompt_template_entity: prompt template entity - :param inputs: inputs - :param files: files - :param query: query - :return: - """ - # Invoke model - model_instance = ModelInstance( - provider_model_bundle=model_config.provider_model_bundle, model=model_config.model - ) - - model_context_tokens = model_config.model_schema.model_properties.get(ModelPropertyKey.CONTEXT_SIZE) - - max_tokens = 0 - for parameter_rule in model_config.model_schema.parameter_rules: - if parameter_rule.name == "max_tokens" or ( - parameter_rule.use_template and parameter_rule.use_template == "max_tokens" - ): - max_tokens = ( - model_config.parameters.get(parameter_rule.name) - or model_config.parameters.get(parameter_rule.use_template or "") - ) or 0 - - if model_context_tokens is None: - return -1 - - if max_tokens is None: - max_tokens = 0 - - # get prompt messages without memory and context - prompt_messages, stop = self.organize_prompt_messages( - app_record=app_record, - model_config=model_config, - prompt_template_entity=prompt_template_entity, - inputs=inputs, - files=files, - query=query, - ) - - prompt_tokens = model_instance.get_llm_num_tokens(prompt_messages) - - rest_tokens: int = model_context_tokens - max_tokens - prompt_tokens - if rest_tokens < 0: - raise InvokeBadRequestError( - "Query or prefix prompt is too long, you can reduce the prefix prompt, " - "or shrink the max token, or switch to a llm with a larger token limit size." - ) - - return rest_tokens - - def recalc_llm_max_tokens( - self, model_config: ModelConfigWithCredentialsEntity, prompt_messages: list[PromptMessage] - ): - # recalc max_tokens if sum(prompt_token + max_tokens) over model token limit - model_instance = ModelInstance( - provider_model_bundle=model_config.provider_model_bundle, model=model_config.model - ) - - model_context_tokens = model_config.model_schema.model_properties.get(ModelPropertyKey.CONTEXT_SIZE) - - max_tokens = 0 - for parameter_rule in model_config.model_schema.parameter_rules: - if parameter_rule.name == "max_tokens" or ( - parameter_rule.use_template and parameter_rule.use_template == "max_tokens" - ): - max_tokens = ( - model_config.parameters.get(parameter_rule.name) - or model_config.parameters.get(parameter_rule.use_template or "") - ) or 0 - - if model_context_tokens is None: - return -1 - - if max_tokens is None: - max_tokens = 0 - - prompt_tokens = model_instance.get_llm_num_tokens(prompt_messages) - - if prompt_tokens + max_tokens > model_context_tokens: - max_tokens = max(model_context_tokens - prompt_tokens, 16) - - for parameter_rule in model_config.model_schema.parameter_rules: - if parameter_rule.name == "max_tokens" or ( - parameter_rule.use_template and parameter_rule.use_template == "max_tokens" - ): - model_config.parameters[parameter_rule.name] = max_tokens - def organize_prompt_messages( self, app_record: App, diff --git a/api/core/app/apps/chat/app_runner.py b/api/core/app/apps/chat/app_runner.py index 39597fc036..64724e9d71 100644 --- a/api/core/app/apps/chat/app_runner.py +++ b/api/core/app/apps/chat/app_runner.py @@ -194,9 +194,6 @@ class ChatAppRunner(AppRunner): if hosting_moderation_result: return - # Re-calculate the max tokens if sum(prompt_token + max_tokens) over model token limit - self.recalc_llm_max_tokens(model_config=application_generate_entity.model_conf, prompt_messages=prompt_messages) - # Invoke model model_instance = ModelInstance( provider_model_bundle=application_generate_entity.model_conf.provider_model_bundle, diff --git a/api/core/app/apps/completion/app_runner.py b/api/core/app/apps/completion/app_runner.py index 80fdd0b80e..8440686c9d 100644 --- a/api/core/app/apps/completion/app_runner.py +++ b/api/core/app/apps/completion/app_runner.py @@ -152,9 +152,6 @@ class CompletionAppRunner(AppRunner): if hosting_moderation_result: return - # Re-calculate the max tokens if sum(prompt_token + max_tokens) over model token limit - self.recalc_llm_max_tokens(model_config=application_generate_entity.model_conf, prompt_messages=prompt_messages) - # Invoke model model_instance = ModelInstance( provider_model_bundle=application_generate_entity.model_conf.provider_model_bundle, diff --git a/api/core/memory/token_buffer_memory.py b/api/core/memory/token_buffer_memory.py index 2254b3d4d5..7cccc7120e 100644 --- a/api/core/memory/token_buffer_memory.py +++ b/api/core/memory/token_buffer_memory.py @@ -26,7 +26,7 @@ class TokenBufferMemory: self.model_instance = model_instance def get_history_prompt_messages( - self, max_token_limit: int = 2000, message_limit: Optional[int] = None + self, max_token_limit: int = 100000, message_limit: Optional[int] = None ) -> Sequence[PromptMessage]: """ Get history prompt messages. diff --git a/api/core/model_runtime/model_providers/bedrock/llm/eu.anthropic.claude-3.7-sonnet-v1.yaml b/api/core/model_runtime/model_providers/bedrock/llm/eu.anthropic.claude-3.7-sonnet-v1.yaml new file mode 100644 index 0000000000..6f95a91f0f --- /dev/null +++ b/api/core/model_runtime/model_providers/bedrock/llm/eu.anthropic.claude-3.7-sonnet-v1.yaml @@ -0,0 +1,115 @@ +model: us.anthropic.claude-3-7-sonnet-20250219-v1:0 +label: + en_US: Claude 3.7 Sonnet(US.Cross Region Inference) +icon: icon_s_en.svg +model_type: llm +features: + - agent-thought + - vision + - tool-call + - stream-tool-call +model_properties: + mode: chat + context_size: 200000 +# docs: https://docs.aws.amazon.com/bedrock/latest/userguide/model-parameters-anthropic-claude-messages.html +parameter_rules: + - name: enable_cache + label: + zh_Hans: 启用提示缓存 + en_US: Enable Prompt Cache + type: boolean + required: false + default: true + help: + zh_Hans: 启用提示缓存可以提高性能并降低成本。Claude 3.7 Sonnet支持在system、messages和tools字段中使用缓存检查点。 + en_US: Enable prompt caching to improve performance and reduce costs. Claude 3.7 Sonnet supports cache checkpoints in system, messages, and tools fields. + - name: reasoning_type + label: + zh_Hans: 推理配置 + en_US: Reasoning Type + type: boolean + required: false + default: false + placeholder: + zh_Hans: 设置推理配置 + en_US: Set reasoning configuration + help: + zh_Hans: 控制模型的推理能力。启用时，temperature将固定为1且top_p将被禁用。 + en_US: Controls the model's reasoning capability. When enabled, temperature will be fixed to 1 and top_p will be disabled. + - name: reasoning_budget + show_on: + - variable: reasoning_type + value: true + label: + zh_Hans: 推理预算 + en_US: Reasoning Budget + type: int + default: 1024 + min: 0 + max: 128000 + help: + zh_Hans: 推理的预算限制（最小1024），必须小于max_tokens。仅在推理类型为enabled时可用。 + en_US: Budget limit for reasoning (minimum 1024), must be less than max_tokens. Only available when reasoning type is enabled. + + - name: max_tokens + use_template: max_tokens + required: true + label: + zh_Hans: 最大token数 + en_US: Max Tokens + type: int + default: 8192 + min: 1 + max: 128000 + help: + zh_Hans: 停止前生成的最大令牌数。请注意，Anthropic Claude 模型可能会在达到 max_tokens 的值之前停止生成令牌。不同的 Anthropic Claude 模型对此参数具有不同的最大值。 + en_US: The maximum number of tokens to generate before stopping. Note that Anthropic Claude models might stop generating tokens before reaching the value of max_tokens. Different Anthropic Claude models have different maximum values for this parameter. + - name: temperature + use_template: temperature + required: false + label: + zh_Hans: 模型温度 + en_US: Model Temperature + type: float + default: 1 + min: 0.0 + max: 1.0 + help: + zh_Hans: 生成内容的随机性。当推理功能启用时，该值将被固定为1。 + en_US: The amount of randomness injected into the response. When reasoning is enabled, this value will be fixed to 1. + - name: top_p + show_on: + - variable: reasoning_type + value: disabled + use_template: top_p + label: + zh_Hans: Top P + en_US: Top P + required: false + type: float + default: 0.999 + min: 0.000 + max: 1.000 + help: + zh_Hans: 在核采样中的概率阈值。当推理功能启用时，该参数将被禁用。 + en_US: The probability threshold in nucleus sampling. When reasoning is enabled, this parameter will be disabled. + - name: top_k + label: + zh_Hans: 取样数量 + en_US: Top k + required: false + type: int + default: 0 + min: 0 + # tip docs from aws has error, max value is 500 + max: 500 + help: + zh_Hans: 对于每个后续标记，仅从前 K 个选项中进行采样。使用 top_k 删除长尾低概率响应。 + en_US: Only sample from the top K options for each subsequent token. Use top_k to remove long tail low probability responses. + - name: response_format + use_template: response_format +pricing: + input: '0.003' + output: '0.015' + unit: '0.001' + currency: USD \ No newline at end of file diff --git a/api/core/model_runtime/model_providers/bedrock/llm/llm.py b/api/core/model_runtime/model_providers/bedrock/llm/llm.py new file mode 100644 index 0000000000..8d93d39ab5 --- /dev/null +++ b/api/core/model_runtime/model_providers/bedrock/llm/llm.py @@ -0,0 +1,896 @@ +# standard import +import base64 +import json +import logging +from collections.abc import Generator +from typing import Optional, Union, cast + +# 3rd import +import boto3 # type: ignore +from botocore.config import Config # type: ignore +from botocore.exceptions import ( # type: ignore + ClientError, + EndpointConnectionError, + NoRegionError, + ServiceNotInRegionError, + UnknownServiceError, +) + +# local import +from core.model_runtime.callbacks.base_callback import Callback +from core.model_runtime.entities.llm_entities import LLMResult, LLMResultChunk, LLMResultChunkDelta +from core.model_runtime.entities.message_entities import ( + AssistantPromptMessage, + ImagePromptMessageContent, + PromptMessage, + PromptMessageContentType, + PromptMessageTool, + SystemPromptMessage, + TextPromptMessageContent, + ToolPromptMessage, + UserPromptMessage, +) +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.large_language_model import LargeLanguageModel +from core.model_runtime.model_providers.bedrock.get_bedrock_client import get_bedrock_client + +logger = logging.getLogger(__name__) +ANTHROPIC_BLOCK_MODE_PROMPT = """You should always follow the instructions and output a valid {{block}} object. +The structure of the {{block}} object you can found in the instructions, use {"answer": "$your_answer"} as the default structure +if you are not sure about the structure. + + +{{instructions}} + +""" # noqa: E501 + + +class BedrockLargeLanguageModel(LargeLanguageModel): + # please refer to the documentation: https://docs.aws.amazon.com/bedrock/latest/userguide/conversation-inference.html + # TODO There is invoke issue: context limit on Cohere Model, will add them after fixed. + CONVERSE_API_ENABLED_MODEL_INFO = [ + {"prefix": "anthropic.claude-v2", "support_system_prompts": True, "support_tool_use": False}, + {"prefix": "us.deepseek", "support_system_prompts": True, "support_tool_use": False}, + {"prefix": "anthropic.claude-v1", "support_system_prompts": True, "support_tool_use": False}, + {"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}, + {"prefix": "mistral.mistral-large", "support_system_prompts": True, "support_tool_use": True}, + {"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}, + {"prefix": "amazon.nova", "support_system_prompts": True, "support_tool_use": False}, + {"prefix": "us.amazon.nova", "support_system_prompts": True, "support_tool_use": False}, + ] + + @staticmethod + def _find_model_info(model_id): + for model in BedrockLargeLanguageModel.CONVERSE_API_ENABLED_MODEL_INFO: + if model_id.startswith(model["prefix"]): + return model + logger.info(f"current model id: {model_id} did not support by Converse API") + return None + + def _code_block_mode_wrapper( + 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, + callbacks: Optional[list[Callback]] = None, + ) -> Union[LLMResult, Generator]: + """ + Code block mode wrapper for invoking large language model + """ + if model_parameters.get("response_format"): + stop = stop or [] + if "```\n" not in stop: + stop.append("```\n") + if "\n```" not in stop: + stop.append("\n```") + response_format = model_parameters.pop("response_format") + format_prompt = SystemPromptMessage( + content=ANTHROPIC_BLOCK_MODE_PROMPT.replace("{{instructions}}", prompt_messages[0].content).replace( + "{{block}}", response_format + ) + ) + if len(prompt_messages) > 0 and isinstance(prompt_messages[0], SystemPromptMessage): + prompt_messages[0] = format_prompt + else: + prompt_messages.insert(0, format_prompt) + prompt_messages.append(AssistantPromptMessage(content=f"\n```{response_format}")) + return self._invoke(model, credentials, prompt_messages, model_parameters, tools, stop, stream, user) + + 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 + """ + + model_info = BedrockLargeLanguageModel._find_model_info(model) + if model_info: + model_info["model"] = model + # invoke models via boto3 converse API + return self._generate_with_converse( + model_info, credentials, prompt_messages, model_parameters, stop, stream, user, tools + ) + # invoke other models via boto3 client + return self._generate(model, credentials, prompt_messages, model_parameters, stop, stream, user) + + def _generate_with_converse( + self, + model_info: dict, + credentials: dict, + prompt_messages: list[PromptMessage], + model_parameters: dict, + stop: Optional[list[str]] = None, + stream: bool = True, + user: Optional[str] = None, + tools: Optional[list[PromptMessageTool]] = None, + ) -> Union[LLMResult, Generator]: + """ + Invoke large language model with converse API + + :param model_info: model information + :param credentials: model credentials + :param prompt_messages: prompt messages + :param model_parameters: model parameters + :param stop: stop words + :param stream: is stream response + :return: full response or stream response chunk generator result + """ + bedrock_client = get_bedrock_client("bedrock-runtime", credentials) + system, prompt_message_dicts = self._convert_converse_prompt_messages(prompt_messages) + inference_config, additional_model_fields = self._convert_converse_api_model_parameters(model_parameters, stop) + + parameters = { + "modelId": model_info["model"], + "messages": prompt_message_dicts, + "inferenceConfig": inference_config, + "additionalModelRequestFields": additional_model_fields, + } + + if model_info["support_system_prompts"] and system and len(system) > 0: + parameters["system"] = system + + if model_info["support_tool_use"] and tools: + parameters["toolConfig"] = self._convert_converse_tool_config(tools=tools) + try: + # for issue #10976 + conversations_list = parameters["messages"] + # if two consecutive user messages found, combine them into one message + for i in range(len(conversations_list) - 2, -1, -1): + if conversations_list[i]["role"] == conversations_list[i + 1]["role"]: + conversations_list[i]["content"].extend(conversations_list.pop(i + 1)["content"]) + + if stream: + response = bedrock_client.converse_stream(**parameters) + return self._handle_converse_stream_response( + model_info["model"], credentials, response, prompt_messages + ) + else: + response = bedrock_client.converse(**parameters) + return self._handle_converse_response(model_info["model"], credentials, response, prompt_messages) + except ClientError as ex: + error_code = ex.response["Error"]["Code"] + full_error_msg = f"{error_code}: {ex.response['Error']['Message']}" + raise self._map_client_to_invoke_error(error_code, full_error_msg) + except (EndpointConnectionError, NoRegionError, ServiceNotInRegionError) as ex: + raise InvokeConnectionError(str(ex)) + + except UnknownServiceError as ex: + raise InvokeServerUnavailableError(str(ex)) + + except Exception as ex: + raise InvokeError(str(ex)) + + def _handle_converse_response( + self, model: str, credentials: dict, response: dict, prompt_messages: list[PromptMessage] + ) -> LLMResult: + """ + Handle llm chat response + + :param model: model name + :param credentials: credentials + :param response: response + :param prompt_messages: prompt messages + :return: full response chunk generator result + """ + response_content = response["output"]["message"]["content"] + # transform assistant message to prompt message + if response["stopReason"] == "tool_use": + tool_calls = [] + text, tool_use = self._extract_tool_use(response_content) + + tool_call = AssistantPromptMessage.ToolCall( + id=tool_use["toolUseId"], + type="function", + function=AssistantPromptMessage.ToolCall.ToolCallFunction( + name=tool_use["name"], arguments=json.dumps(tool_use["input"]) + ), + ) + tool_calls.append(tool_call) + + assistant_prompt_message = AssistantPromptMessage(content=text, tool_calls=tool_calls) + else: + assistant_prompt_message = AssistantPromptMessage(content=response_content[0]["text"]) + + # calculate num tokens + if response["usage"]: + # transform usage + prompt_tokens = response["usage"]["inputTokens"] + completion_tokens = response["usage"]["outputTokens"] + else: + # calculate num tokens + prompt_tokens = self.get_num_tokens(model, credentials, prompt_messages) + completion_tokens = self.get_num_tokens(model, credentials, [assistant_prompt_message]) + + # transform usage + usage = self._calc_response_usage(model, credentials, prompt_tokens, completion_tokens) + + result = LLMResult( + model=model, + prompt_messages=prompt_messages, + message=assistant_prompt_message, + usage=usage, + ) + return result + + def _extract_tool_use(self, content: dict) -> tuple[str, dict]: + tool_use = {} + text = "" + for item in content: + if "toolUse" in item: + tool_use = item["toolUse"] + elif "text" in item: + text = item["text"] + else: + raise ValueError(f"Got unknown item: {item}") + return text, tool_use + + def _handle_converse_stream_response( + self, + model: str, + credentials: dict, + response: dict, + prompt_messages: list[PromptMessage], + ) -> Generator: + """ + Handle llm chat stream response + + :param model: model name + :param credentials: credentials + :param response: response + :param prompt_messages: prompt messages + :return: full response or stream response chunk generator result + """ + + try: + full_assistant_content = "" + return_model = None + input_tokens = 0 + output_tokens = 0 + finish_reason = None + index = 0 + tool_calls: list[AssistantPromptMessage.ToolCall] = [] + tool_use = {} + + for chunk in response["stream"]: + if "messageStart" in chunk: + return_model = model + elif "messageStop" in chunk: + finish_reason = chunk["messageStop"]["stopReason"] + elif "contentBlockStart" in chunk: + tool = chunk["contentBlockStart"]["start"]["toolUse"] + tool_use["toolUseId"] = tool["toolUseId"] + tool_use["name"] = tool["name"] + elif "metadata" in chunk: + input_tokens = chunk["metadata"]["usage"]["inputTokens"] + output_tokens = chunk["metadata"]["usage"]["outputTokens"] + usage = self._calc_response_usage(model, credentials, input_tokens, output_tokens) + yield LLMResultChunk( + model=return_model, + prompt_messages=prompt_messages, + delta=LLMResultChunkDelta( + index=index, + message=AssistantPromptMessage(content="", tool_calls=tool_calls), + finish_reason=finish_reason, + usage=usage, + ), + ) + elif "contentBlockDelta" in chunk: + delta = chunk["contentBlockDelta"]["delta"] + if "text" in delta: + chunk_text = delta["text"] or "" + full_assistant_content += chunk_text + assistant_prompt_message = AssistantPromptMessage( + content=chunk_text or "", + ) + index = chunk["contentBlockDelta"]["contentBlockIndex"] + yield LLMResultChunk( + model=model, + prompt_messages=prompt_messages, + delta=LLMResultChunkDelta( + index=index + 1, + message=assistant_prompt_message, + ), + ) + elif "toolUse" in delta: + if "input" not in tool_use: + tool_use["input"] = "" + tool_use["input"] += delta["toolUse"]["input"] + elif "contentBlockStop" in chunk: + if "input" in tool_use: + tool_call = AssistantPromptMessage.ToolCall( + id=tool_use["toolUseId"], + type="function", + function=AssistantPromptMessage.ToolCall.ToolCallFunction( + name=tool_use["name"], arguments=tool_use["input"] + ), + ) + tool_calls.append(tool_call) + tool_use = {} + + except Exception as ex: + raise InvokeError(str(ex)) + + def _convert_converse_api_model_parameters( + self, model_parameters: dict, stop: Optional[list[str]] = None + ) -> tuple[dict, dict]: + inference_config = {} + additional_model_fields = {} + if "max_tokens" in model_parameters: + inference_config["maxTokens"] = model_parameters["max_tokens"] + + if "temperature" in model_parameters: + inference_config["temperature"] = model_parameters["temperature"] + + if "top_p" in model_parameters: + inference_config["topP"] = model_parameters["temperature"] + + if stop: + inference_config["stopSequences"] = stop + + if "top_k" in model_parameters: + additional_model_fields["top_k"] = model_parameters["top_k"] + + return inference_config, additional_model_fields + + def _convert_converse_prompt_messages(self, prompt_messages: list[PromptMessage]) -> tuple[str, list[dict]]: + """ + Convert prompt messages to dict list and system + """ + + system = [] + prompt_message_dicts = [] + for message in prompt_messages: + if isinstance(message, SystemPromptMessage): + message.content = message.content.strip() + system.append({"text": message.content}) + else: + prompt_message_dicts.append(self._convert_prompt_message_to_dict(message)) + + return system, prompt_message_dicts + + def _convert_converse_tool_config(self, tools: Optional[list[PromptMessageTool]] = None) -> dict: + tool_config = {} + configs = [] + if tools: + for tool in tools: + configs.append( + { + "toolSpec": { + "name": tool.name, + "description": tool.description, + "inputSchema": {"json": tool.parameters}, + } + } + ) + tool_config["tools"] = configs + return tool_config + + def _convert_prompt_message_to_dict(self, message: PromptMessage) -> dict: + """ + Convert PromptMessage to dict + """ + if isinstance(message, UserPromptMessage): + message = cast(UserPromptMessage, message) + if isinstance(message.content, str): + message_dict = {"role": "user", "content": [{"text": message.content}]} + else: + sub_messages = [] + for message_content in message.content: + if message_content.type == PromptMessageContentType.TEXT: + message_content = cast(TextPromptMessageContent, message_content) + sub_message_dict = {"text": message_content.data} + sub_messages.append(sub_message_dict) + elif message_content.type == PromptMessageContentType.IMAGE: + message_content = cast(ImagePromptMessageContent, message_content) + data_split = message_content.data.split(";base64,") + mime_type = data_split[0].replace("data:", "") + base64_data = data_split[1] + image_content = base64.b64decode(base64_data) + + if mime_type not in {"image/jpeg", "image/png", "image/gif", "image/webp"}: + raise ValueError( + f"Unsupported image type {mime_type}, " + f"only support image/jpeg, image/png, image/gif, and image/webp" + ) + + sub_message_dict = { + "image": {"format": mime_type.replace("image/", ""), "source": {"bytes": image_content}} + } + sub_messages.append(sub_message_dict) + + message_dict = {"role": "user", "content": sub_messages} + elif isinstance(message, AssistantPromptMessage): + message = cast(AssistantPromptMessage, message) + if message.tool_calls: + message_dict = { + "role": "assistant", + "content": [ + { + "toolUse": { + "toolUseId": message.tool_calls[0].id, + "name": message.tool_calls[0].function.name, + "input": json.loads(message.tool_calls[0].function.arguments), + } + } + ], + } + else: + message_dict = {"role": "assistant", "content": [{"text": message.content}]} + elif isinstance(message, SystemPromptMessage): + message = cast(SystemPromptMessage, message) + message_dict = [{"text": message.content}] + elif isinstance(message, ToolPromptMessage): + message = cast(ToolPromptMessage, message) + message_dict = { + "role": "user", + "content": [ + { + "toolResult": { + "toolUseId": message.tool_call_id, + "content": [{"json": {"text": message.content}}], + } + } + ], + } + else: + raise ValueError(f"Got unknown type {message}") + return message_dict + + def get_num_tokens( + self, + model: str, + credentials: dict, + prompt_messages: list[PromptMessage] | str, + 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 or message string + :param tools: tools for tool calling + :return:md = genai.GenerativeModel(model) + """ + prefix = model.split(".")[0] + model_name = model.split(".")[1] + + if isinstance(prompt_messages, str): + prompt = prompt_messages + else: + prompt = self._convert_messages_to_prompt(prompt_messages, prefix, model_name) + + return self._get_num_tokens_by_gpt2(prompt) + + def validate_credentials(self, model: str, credentials: dict) -> None: + """ + Validate model credentials + + :param model: model name + :param credentials: model credentials + :return: + """ + required_params = {} + if "anthropic" in model: + required_params = { + "max_tokens": 32, + } + elif "ai21" in model: + # ValidationException: Malformed input request: #/temperature: expected type: Number, + # found: Null#/maxTokens: expected type: Integer, found: Null#/topP: expected type: Number, found: Null, + # please reformat your input and try again. + required_params = { + "temperature": 0.7, + "topP": 0.9, + "maxTokens": 32, + } + + try: + ping_message = UserPromptMessage(content="ping") + self._invoke( + model=model, + credentials=credentials, + prompt_messages=[ping_message], + model_parameters=required_params, + stream=False, + ) + + except ClientError as ex: + error_code = ex.response["Error"]["Code"] + full_error_msg = f"{error_code}: {ex.response['Error']['Message']}" + raise CredentialsValidateFailedError(str(self._map_client_to_invoke_error(error_code, full_error_msg))) + + except Exception as ex: + raise CredentialsValidateFailedError(str(ex)) + + def _convert_one_message_to_text( + self, message: PromptMessage, model_prefix: str, model_name: Optional[str] = None + ) -> str: + """ + Convert a single message to a string. + + :param message: PromptMessage to convert. + :return: String representation of the message. + """ + human_prompt_prefix = "" + human_prompt_postfix = "" + ai_prompt = "" + + content = message.content + + if isinstance(message, UserPromptMessage): + body = content + if isinstance(content, list): + body = "".join([c.data for c in content if c.type == PromptMessageContentType.TEXT]) + message_text = f"{human_prompt_prefix} {body} {human_prompt_postfix}" + elif isinstance(message, AssistantPromptMessage): + message_text = f"{ai_prompt} {content}" + elif isinstance(message, SystemPromptMessage): + message_text = content + elif isinstance(message, ToolPromptMessage): + message_text = f"{human_prompt_prefix} {message.content}" + else: + raise ValueError(f"Got unknown type {message}") + + return message_text + + def _convert_messages_to_prompt( + self, messages: list[PromptMessage], model_prefix: str, model_name: Optional[str] = None + ) -> str: + """ + Format a list of messages into a full prompt for the Anthropic, Amazon and Llama models + + :param messages: List of PromptMessage to combine. + :param model_name: specific model name.Optional,just to distinguish llama2 and llama3 + :return: Combined string with necessary human_prompt and ai_prompt tags. + """ + if not messages: + return "" + + messages = messages.copy() # don't mutate the original list + if not isinstance(messages[-1], AssistantPromptMessage): + messages.append(AssistantPromptMessage(content="")) + + text = "".join(self._convert_one_message_to_text(message, model_prefix, model_name) for message in messages) + + # trim off the trailing ' ' that might come from the "Assistant: " + return text.rstrip() + + def _create_payload( + self, + model: str, + prompt_messages: list[PromptMessage], + model_parameters: dict, + stop: Optional[list[str]] = None, + stream: bool = True, + ): + """ + Create payload for bedrock api call depending on model provider + """ + payload = {} + model_prefix = model.split(".")[0] + model_name = model.split(".")[1] + + if model_prefix == "ai21": + payload["temperature"] = model_parameters.get("temperature") + payload["topP"] = model_parameters.get("topP") + payload["maxTokens"] = model_parameters.get("maxTokens") + payload["prompt"] = self._convert_messages_to_prompt(prompt_messages, model_prefix) + + if model_parameters.get("presencePenalty"): + payload["presencePenalty"] = {model_parameters.get("presencePenalty")} + if model_parameters.get("frequencyPenalty"): + payload["frequencyPenalty"] = {model_parameters.get("frequencyPenalty")} + if model_parameters.get("countPenalty"): + payload["countPenalty"] = {model_parameters.get("countPenalty")} + + elif model_prefix == "cohere": + payload = {**model_parameters} + payload["prompt"] = prompt_messages[0].content + payload["stream"] = stream + + else: + raise ValueError(f"Got unknown model prefix {model_prefix}") + + return payload + + def _generate( + self, + model: str, + credentials: dict, + prompt_messages: list[PromptMessage], + model_parameters: dict, + 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: credentials kwargs + :param prompt_messages: prompt messages + :param model_parameters: model parameters + :param stop: stop words + :param stream: is stream response + :param user: unique user id + :return: full response or stream response chunk generator result + """ + client_config = Config(region_name=credentials["aws_region"]) + + runtime_client = boto3.client( + service_name="bedrock-runtime", + config=client_config, + aws_access_key_id=credentials.get("aws_access_key_id"), + aws_secret_access_key=credentials.get("aws_secret_access_key"), + ) + + model_prefix = model.split(".")[0] + payload = self._create_payload(model, prompt_messages, model_parameters, stop, stream) + + # need workaround for ai21 models which doesn't support streaming + if stream and model_prefix != "ai21": + invoke = runtime_client.invoke_model_with_response_stream + else: + invoke = runtime_client.invoke_model + + try: + body_jsonstr = json.dumps(payload) + response = invoke(modelId=model, contentType="application/json", accept="*/*", body=body_jsonstr) + except ClientError as ex: + error_code = ex.response["Error"]["Code"] + full_error_msg = f"{error_code}: {ex.response['Error']['Message']}" + raise self._map_client_to_invoke_error(error_code, full_error_msg) + + except (EndpointConnectionError, NoRegionError, ServiceNotInRegionError) as ex: + raise InvokeConnectionError(str(ex)) + + except UnknownServiceError as ex: + raise InvokeServerUnavailableError(str(ex)) + + except Exception as ex: + raise InvokeError(str(ex)) + + if stream: + return self._handle_generate_stream_response(model, credentials, response, prompt_messages) + + return self._handle_generate_response(model, credentials, response, prompt_messages) + + def _handle_generate_response( + self, model: str, credentials: dict, response: dict, prompt_messages: list[PromptMessage] + ) -> LLMResult: + """ + Handle llm response + + :param model: model name + :param credentials: credentials + :param response: response + :param prompt_messages: prompt messages + :return: llm response + """ + response_body = json.loads(response.get("body").read().decode("utf-8")) + + finish_reason = response_body.get("error") + + if finish_reason is not None: + raise InvokeError(finish_reason) + + # get output text and calculate num tokens based on model / provider + model_prefix = model.split(".")[0] + + if model_prefix == "ai21": + output = response_body.get("completions")[0].get("data").get("text") + prompt_tokens = len(response_body.get("prompt").get("tokens")) + completion_tokens = len(response_body.get("completions")[0].get("data").get("tokens")) + + elif model_prefix == "cohere": + output = response_body.get("generations")[0].get("text") + prompt_tokens = self.get_num_tokens(model, credentials, prompt_messages) + completion_tokens = self.get_num_tokens(model, credentials, output or "") + + else: + raise ValueError(f"Got unknown model prefix {model_prefix} when handling block response") + + # construct assistant message from output + assistant_prompt_message = AssistantPromptMessage(content=output) + + # calculate usage + usage = self._calc_response_usage(model, credentials, prompt_tokens, completion_tokens) + + # construct response + result = LLMResult( + model=model, + prompt_messages=prompt_messages, + message=assistant_prompt_message, + usage=usage, + ) + + return result + + def _handle_generate_stream_response( + self, model: str, credentials: dict, response: dict, prompt_messages: list[PromptMessage] + ) -> Generator: + """ + Handle llm stream response + + :param model: model name + :param credentials: credentials + :param response: response + :param prompt_messages: prompt messages + :return: llm response chunk generator result + """ + model_prefix = model.split(".")[0] + if model_prefix == "ai21": + response_body = json.loads(response.get("body").read().decode("utf-8")) + + content = response_body.get("completions")[0].get("data").get("text") + finish_reason = response_body.get("completions")[0].get("finish_reason") + + prompt_tokens = len(response_body.get("prompt").get("tokens")) + completion_tokens = len(response_body.get("completions")[0].get("data").get("tokens")) + usage = self._calc_response_usage(model, credentials, prompt_tokens, completion_tokens) + yield LLMResultChunk( + model=model, + prompt_messages=prompt_messages, + delta=LLMResultChunkDelta( + index=0, message=AssistantPromptMessage(content=content), finish_reason=finish_reason, usage=usage + ), + ) + return + + stream = response.get("body") + if not stream: + raise InvokeError("No response body") + + index = -1 + for event in stream: + chunk = event.get("chunk") + + if not chunk: + exception_name = next(iter(event)) + full_ex_msg = f"{exception_name}: {event[exception_name]['message']}" + raise self._map_client_to_invoke_error(exception_name, full_ex_msg) + + payload = json.loads(chunk.get("bytes").decode()) + + model_prefix = model.split(".")[0] + if model_prefix == "cohere": + content_delta = payload.get("text") + finish_reason = payload.get("finish_reason") + + else: + raise ValueError(f"Got unknown model prefix {model_prefix} when handling stream response") + + # transform assistant message to prompt message + assistant_prompt_message = AssistantPromptMessage( + content=content_delta or "", + ) + index += 1 + + if not finish_reason: + yield LLMResultChunk( + model=model, + prompt_messages=prompt_messages, + delta=LLMResultChunkDelta(index=index, message=assistant_prompt_message), + ) + + else: + # get num tokens from metrics in last chunk + prompt_tokens = payload["amazon-bedrock-invocationMetrics"]["inputTokenCount"] + completion_tokens = payload["amazon-bedrock-invocationMetrics"]["outputTokenCount"] + + # transform usage + usage = self._calc_response_usage(model, credentials, prompt_tokens, completion_tokens) + + yield LLMResultChunk( + model=model, + prompt_messages=prompt_messages, + delta=LLMResultChunkDelta( + index=index, message=assistant_prompt_message, finish_reason=finish_reason, usage=usage + ), + ) + + @property + def _invoke_error_mapping(self) -> dict[type[InvokeError], list[type[Exception]]]: + """ + Map model invoke error to unified error + The key is the ermd = genai.GenerativeModel(model) error type thrown to the caller + The value is the md = genai.GenerativeModel(model) error type thrown by the model, + which needs to be converted into a unified error type for the caller. + + :return: Invoke emd = genai.GenerativeModel(model) error mapping + """ + return { + InvokeConnectionError: [], + InvokeServerUnavailableError: [], + InvokeRateLimitError: [], + InvokeAuthorizationError: [], + InvokeBadRequestError: [], + } + + def _map_client_to_invoke_error(self, error_code: str, error_msg: str) -> type[InvokeError]: + """ + Map client error to invoke error + + :param error_code: error code + :param error_msg: error message + :return: invoke error + """ + + if error_code == "AccessDeniedException": + return InvokeAuthorizationError(error_msg) + elif error_code in {"ResourceNotFoundException", "ValidationException"}: + return InvokeBadRequestError(error_msg) + elif error_code in {"ThrottlingException", "ServiceQuotaExceededException"}: + return InvokeRateLimitError(error_msg) + elif error_code in { + "ModelTimeoutException", + "ModelErrorException", + "InternalServerException", + "ModelNotReadyException", + }: + return InvokeServerUnavailableError(error_msg) + elif error_code == "ModelStreamErrorException": + return InvokeConnectionError(error_msg) + + return InvokeError(error_msg) diff --git a/api/core/model_runtime/model_providers/bedrock/llm/us.deepseek-r1.yaml b/api/core/model_runtime/model_providers/bedrock/llm/us.deepseek-r1.yaml new file mode 100644 index 0000000000..1191e3bd79 --- /dev/null +++ b/api/core/model_runtime/model_providers/bedrock/llm/us.deepseek-r1.yaml @@ -0,0 +1,63 @@ +model: us.deepseek.r1-v1:0 +label: + en_US: DeepSeek-R1(US.Cross Region Inference) +icon: icon_s_en.svg +model_type: llm +features: + - agent-thought + - vision + - tool-call + - stream-tool-call +model_properties: + mode: chat + context_size: 32768 +parameter_rules: + - name: max_tokens + use_template: max_tokens + required: true + label: + zh_Hans: 最大token数 + en_US: Max Tokens + type: int + default: 8192 + min: 1 + max: 128000 + help: + zh_Hans: 停止前生成的最大令牌数。 + en_US: The maximum number of tokens to generate before stopping. + - name: temperature + use_template: temperature + required: false + label: + zh_Hans: 模型温度 + en_US: Model Temperature + type: float + default: 1 + min: 0.0 + max: 1.0 + help: + zh_Hans: 生成内容的随机性。当推理功能启用时，该值将被固定为1。 + en_US: The amount of randomness injected into the response. When reasoning is enabled, this value will be fixed to 1. + - name: top_p + show_on: + - variable: reasoning_type + value: disabled + use_template: top_p + label: + zh_Hans: Top P + en_US: Top P + required: false + type: float + default: 0.999 + min: 0.000 + max: 1.000 + help: + zh_Hans: 在核采样中的概率阈值。当推理功能启用时，该参数将被禁用。 + en_US: The probability threshold in nucleus sampling. When reasoning is enabled, this parameter will be disabled. + - name: response_format + use_template: response_format +pricing: + input: '0.001' + output: '0.005' + unit: '0.001' + currency: USD \ No newline at end of file diff --git a/api/core/model_runtime/model_providers/google/google.py b/api/core/model_runtime/model_providers/google/google.py new file mode 100644 index 0000000000..88ea50ea2b --- /dev/null +++ b/api/core/model_runtime/model_providers/google/google.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 GoogleProvider(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.LLM) + + # Use `gemini-2.0-flash` model for validate, + model_instance.validate_credentials(model="gemini-2.0-flash", 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/google/llm/_position.yaml b/api/core/model_runtime/model_providers/google/llm/_position.yaml new file mode 100644 index 0000000000..4c7c4151f1 --- /dev/null +++ b/api/core/model_runtime/model_providers/google/llm/_position.yaml @@ -0,0 +1,21 @@ +- gemini-2.0-flash-001 +- gemini-2.0-flash-exp +- gemini-2.0-pro-exp-02-05 +- gemini-2.0-flash-thinking-exp-1219 +- gemini-2.0-flash-thinking-exp-01-21 +- gemini-1.5-pro +- gemini-1.5-pro-latest +- gemini-1.5-pro-001 +- gemini-1.5-pro-002 +- gemini-1.5-pro-exp-0801 +- gemini-1.5-pro-exp-0827 +- gemini-1.5-flash +- gemini-1.5-flash-latest +- gemini-1.5-flash-001 +- gemini-1.5-flash-002 +- gemini-1.5-flash-exp-0827 +- gemini-1.5-flash-8b-exp-0827 +- gemini-1.5-flash-8b-exp-0924 +- gemini-exp-1206 +- gemini-exp-1121 +- gemini-exp-1114 diff --git a/api/core/model_runtime/model_providers/openai/llm/_position.yaml b/api/core/model_runtime/model_providers/openai/llm/_position.yaml new file mode 100644 index 0000000000..688d4dbd09 --- /dev/null +++ b/api/core/model_runtime/model_providers/openai/llm/_position.yaml @@ -0,0 +1,33 @@ +- gpt-4.1 +- o1 +- o1-2024-12-17 +- o1-mini +- o1-mini-2024-09-12 +- o3-mini +- o3-mini-2025-01-31 +- gpt-4 +- gpt-4o +- gpt-4o-2024-05-13 +- gpt-4o-2024-08-06 +- gpt-4o-2024-11-20 +- chatgpt-4o-latest +- gpt-4o-mini +- gpt-4o-mini-2024-07-18 +- gpt-4-turbo +- gpt-4-turbo-2024-04-09 +- gpt-4-turbo-preview +- gpt-4-32k +- gpt-4-1106-preview +- gpt-4-0125-preview +- gpt-4-vision-preview +- gpt-3.5-turbo +- gpt-3.5-turbo-16k +- gpt-3.5-turbo-16k-0613 +- gpt-3.5-turbo-0125 +- gpt-3.5-turbo-1106 +- gpt-3.5-turbo-0613 +- gpt-3.5-turbo-instruct +- gpt-4o-audio-preview +- o1-preview +- o1-preview-2024-09-12 +- text-davinci-003 diff --git a/api/core/model_runtime/model_providers/openai/llm/gpt-4-1.yaml b/api/core/model_runtime/model_providers/openai/llm/gpt-4-1.yaml new file mode 100644 index 0000000000..f9f6edb4e6 --- /dev/null +++ b/api/core/model_runtime/model_providers/openai/llm/gpt-4-1.yaml @@ -0,0 +1,60 @@ +model: gpt-4.1 +label: + zh_Hans: gpt-4.1 + en_US: gpt-4.1 +model_type: llm +features: + - multi-tool-call + - agent-thought + - stream-tool-call + - vision +model_properties: + mode: chat + context_size: 1047576 +parameter_rules: + - name: temperature + use_template: temperature + - name: top_p + use_template: top_p + - name: presence_penalty + use_template: presence_penalty + - name: frequency_penalty + use_template: frequency_penalty + - name: max_tokens + use_template: max_tokens + default: 512 + min: 1 + max: 32768 + - name: reasoning_effort + label: + zh_Hans: 推理工作 + en_US: Reasoning Effort + type: string + help: + zh_Hans: 限制推理模型的推理工作 + en_US: Constrains effort on reasoning for reasoning models + required: false + options: + - low + - medium + - high + - name: response_format + label: + zh_Hans: 回复格式 + en_US: Response Format + type: string + help: + zh_Hans: 指定模型必须输出的格式 + en_US: specifying the format that the model must output + required: false + options: + - text + - json_object + - json_schema + - name: json_schema + use_template: json_schema +pricing: + input: '2.00' + output: '8.00' + unit: '0.000001' + currency: USD \ No newline at end of file diff --git a/api/core/model_runtime/model_providers/openai/llm/llm.py b/api/core/model_runtime/model_providers/openai/llm/llm.py new file mode 100644 index 0000000000..37f7b33514 --- /dev/null +++ b/api/core/model_runtime/model_providers/openai/llm/llm.py @@ -0,0 +1,1211 @@ +import json +import logging +import re +from collections.abc import Generator +from typing import Any, Optional, Union, cast + +import tiktoken +from openai import OpenAI, Stream +from openai.types import Completion +from openai.types.chat import ChatCompletion, ChatCompletionChunk, ChatCompletionMessageToolCall +from openai.types.chat.chat_completion_chunk import ChoiceDeltaFunctionCall, ChoiceDeltaToolCall +from openai.types.chat.chat_completion_message import FunctionCall + +from core.model_runtime.callbacks.base_callback import Callback +from core.model_runtime.entities import ( + AssistantPromptMessage, + AudioPromptMessageContent, + ImagePromptMessageContent, + PromptMessage, + PromptMessageContentType, + PromptMessageTool, + SystemPromptMessage, + TextPromptMessageContent, + ToolPromptMessage, + UserPromptMessage, +) +from core.model_runtime.entities.llm_entities import LLMMode, LLMResult, LLMResultChunk, LLMResultChunkDelta +from core.model_runtime.entities.model_entities import AIModelEntity, FetchFrom, I18nObject, ModelType, PriceConfig +from core.model_runtime.errors.validate import CredentialsValidateFailedError +from core.model_runtime.model_providers.__base.large_language_model import LargeLanguageModel +from core.model_runtime.model_providers.openai._common import _CommonOpenAI + +logger = logging.getLogger(__name__) + +OPENAI_BLOCK_MODE_PROMPT = """You should always follow the instructions and output a valid {{block}} object. +The structure of the {{block}} object you can found in the instructions, use {"answer": "$your_answer"} as the default structure +if you are not sure about the structure. + + +{{instructions}} + +""" # noqa: E501 + + +class OpenAILargeLanguageModel(_CommonOpenAI, LargeLanguageModel): + """ + Model class for OpenAI large language model. + """ + + 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 + """ + # handle fine tune remote models + base_model = model + if model.startswith("ft:"): + base_model = model.split(":")[1] + + # get model mode + model_mode = self.get_model_mode(base_model, credentials) + + if model_mode == LLMMode.CHAT: + # chat model + return self._chat_generate( + model=model, + credentials=credentials, + prompt_messages=prompt_messages, + model_parameters=model_parameters, + tools=tools, + stop=stop, + stream=stream, + user=user, + ) + else: + # text completion model + return self._generate( + model=model, + credentials=credentials, + prompt_messages=prompt_messages, + model_parameters=model_parameters, + stop=stop, + stream=stream, + user=user, + ) + + def _code_block_mode_wrapper( + 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, + callbacks: Optional[list[Callback]] = None, + ) -> Union[LLMResult, Generator]: + """ + Code block mode wrapper for invoking large language model + """ + # handle fine tune remote models + base_model = model + if model.startswith("ft:"): + base_model = model.split(":")[1] + + # get model mode + model_mode = self.get_model_mode(base_model, credentials) + + # transform response format + if "response_format" in model_parameters and model_parameters["response_format"] in {"JSON", "XML"}: + stop = stop or [] + if model_mode == LLMMode.CHAT: + # chat model + self._transform_chat_json_prompts( + model=base_model, + credentials=credentials, + prompt_messages=prompt_messages, + model_parameters=model_parameters, + tools=tools, + stop=stop, + stream=stream, + user=user, + response_format=model_parameters["response_format"], + ) + else: + self._transform_completion_json_prompts( + model=base_model, + credentials=credentials, + prompt_messages=prompt_messages, + model_parameters=model_parameters, + tools=tools, + stop=stop, + stream=stream, + user=user, + response_format=model_parameters["response_format"], + ) + model_parameters.pop("response_format") + + return self._invoke( + model=model, + credentials=credentials, + prompt_messages=prompt_messages, + model_parameters=model_parameters, + tools=tools, + stop=stop, + stream=stream, + user=user, + ) + + def _transform_chat_json_prompts( + self, + model: str, + credentials: dict, + prompt_messages: list[PromptMessage], + model_parameters: dict, + tools: list[PromptMessageTool] | None = None, + stop: list[str] | None = None, + stream: bool = True, + user: str | None = None, + response_format: str = "JSON", + ) -> None: + """ + Transform json prompts + """ + if "```\n" not in stop: + stop.append("```\n") + if "\n```" not in stop: + stop.append("\n```") + + # check if there is a system message + if len(prompt_messages) > 0 and isinstance(prompt_messages[0], SystemPromptMessage): + # override the system message + prompt_messages[0] = SystemPromptMessage( + content=OPENAI_BLOCK_MODE_PROMPT.replace("{{instructions}}", prompt_messages[0].content).replace( + "{{block}}", response_format + ) + ) + prompt_messages.append(AssistantPromptMessage(content=f"\n```{response_format}\n")) + else: + # insert the system message + prompt_messages.insert( + 0, + SystemPromptMessage( + content=OPENAI_BLOCK_MODE_PROMPT.replace( + "{{instructions}}", f"Please output a valid {response_format} object." + ).replace("{{block}}", response_format) + ), + ) + prompt_messages.append(AssistantPromptMessage(content=f"\n```{response_format}")) + + def _transform_completion_json_prompts( + self, + model: str, + credentials: dict, + prompt_messages: list[PromptMessage], + model_parameters: dict, + tools: list[PromptMessageTool] | None = None, + stop: list[str] | None = None, + stream: bool = True, + user: str | None = None, + response_format: str = "JSON", + ) -> None: + """ + Transform json prompts + """ + if "```\n" not in stop: + stop.append("```\n") + if "\n```" not in stop: + stop.append("\n```") + + # override the last user message + user_message = None + for i in range(len(prompt_messages) - 1, -1, -1): + if isinstance(prompt_messages[i], UserPromptMessage): + user_message = prompt_messages[i] + break + + if user_message: + if prompt_messages[i].content[-11:] == "Assistant: ": + # now we are in the chat app, remove the last assistant message + prompt_messages[i].content = prompt_messages[i].content[:-11] + prompt_messages[i] = UserPromptMessage( + content=OPENAI_BLOCK_MODE_PROMPT.replace("{{instructions}}", user_message.content).replace( + "{{block}}", response_format + ) + ) + prompt_messages[i].content += f"Assistant:\n```{response_format}\n" + else: + prompt_messages[i] = UserPromptMessage( + content=OPENAI_BLOCK_MODE_PROMPT.replace("{{instructions}}", user_message.content).replace( + "{{block}}", response_format + ) + ) + prompt_messages[i].content += f"\n```{response_format}\n" + + 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: + """ + # handle fine tune remote models + if model.startswith("ft:"): + base_model = model.split(":")[1] + else: + base_model = model + + # get model mode + model_mode = self.get_model_mode(model) + + if model_mode == LLMMode.CHAT: + # chat model + return self._num_tokens_from_messages(base_model, prompt_messages, tools) + else: + # text completion model, do not support tool calling + return self._num_tokens_from_string(base_model, prompt_messages[0].content) + + def validate_credentials(self, model: str, credentials: dict) -> None: + """ + Validate model credentials + + :param model: model name + :param credentials: model credentials + :return: + """ + try: + # transform credentials to kwargs for model instance + credentials_kwargs = self._to_credential_kwargs(credentials) + client = OpenAI(**credentials_kwargs) + + # handle fine tune remote models + base_model = model + # fine-tuned model name likes ft:gpt-3.5-turbo-0613:personal::xxxxx + if model.startswith("ft:"): + base_model = model.split(":")[1] + + # check if model exists + remote_models = self.remote_models(credentials) + remote_model_map = {model.model: model for model in remote_models} + if model not in remote_model_map: + raise CredentialsValidateFailedError(f"Fine-tuned model {model} not found") + + # get model mode + model_mode = self.get_model_mode(base_model, credentials) + + if model_mode == LLMMode.CHAT: + # chat model + client.chat.completions.create( + messages=[{"role": "user", "content": "ping"}], + model=model, + temperature=0, + max_tokens=20, + stream=False, + ) + else: + # text completion model + client.completions.create( + prompt="ping", + model=model, + temperature=0, + max_tokens=20, + stream=False, + ) + except Exception as ex: + raise CredentialsValidateFailedError(str(ex)) + + def remote_models(self, credentials: dict) -> list[AIModelEntity]: + """ + Return remote models if credentials are provided. + + :param credentials: provider credentials + :return: + """ + + # transform credentials to kwargs for model instance + credentials_kwargs = self._to_credential_kwargs(credentials) + client = OpenAI(**credentials_kwargs) + + # get all remote models + remote_models = client.models.list() + + fine_tune_models = [model for model in remote_models if model.id.startswith("ft:")] + + ai_model_entities = [] + for model in fine_tune_models: + base_model = model.id.split(":")[1] + + base_model_schema = None + for predefined_model in self.predefined_models(): + if predefined_model.model in base_model: + base_model_schema = predefined_model + break + + if not base_model_schema: + continue + + ai_model_entity = AIModelEntity( + model=model.id, + label=I18nObject(zh_Hans=model.id, en_US=model.id), + model_type=ModelType.LLM, + features=base_model_schema.features, + fetch_from=FetchFrom.CUSTOMIZABLE_MODEL, + model_properties=base_model_schema.model_properties, + parameter_rules=base_model_schema.parameter_rules, + pricing=PriceConfig(input=0.003, output=0.006, unit=0.001, currency="USD"), + ) + + ai_model_entities.append(ai_model_entity) + + return ai_model_entities + + def _generate( + self, + model: str, + credentials: dict, + prompt_messages: list[PromptMessage], + model_parameters: dict, + stop: Optional[list[str]] = None, + stream: bool = True, + user: Optional[str] = None, + ) -> Union[LLMResult, Generator]: + """ + Invoke llm completion model + + :param model: model name + :param credentials: credentials + :param prompt_messages: prompt messages + :param model_parameters: model parameters + :param stop: stop words + :param stream: is stream response + :param user: unique user id + :return: full response or stream response chunk generator result + """ + # transform credentials to kwargs for model instance + credentials_kwargs = self._to_credential_kwargs(credentials) + + # init model client + client = OpenAI(**credentials_kwargs) + + extra_model_kwargs = {} + + if stop: + extra_model_kwargs["stop"] = stop + + if user: + extra_model_kwargs["user"] = user + + if stream: + extra_model_kwargs["stream_options"] = {"include_usage": True} + + # text completion model + response = client.completions.create( + prompt=prompt_messages[0].content, + model=model, + stream=stream, + **model_parameters, + **extra_model_kwargs, + ) + + if stream: + return self._handle_generate_stream_response(model, credentials, response, prompt_messages) + + return self._handle_generate_response(model, credentials, response, prompt_messages) + + def _handle_generate_response( + self, model: str, credentials: dict, response: Completion, prompt_messages: list[PromptMessage] + ) -> LLMResult: + """ + Handle llm completion response + + :param model: model name + :param credentials: model credentials + :param response: response + :param prompt_messages: prompt messages + :return: llm result + """ + assistant_text = response.choices[0].text + + # transform assistant message to prompt message + assistant_prompt_message = AssistantPromptMessage(content=assistant_text) + + # calculate num tokens + if response.usage: + # transform usage + prompt_tokens = response.usage.prompt_tokens + completion_tokens = response.usage.completion_tokens + else: + # calculate num tokens + prompt_tokens = self._num_tokens_from_string(model, prompt_messages[0].content) + completion_tokens = self._num_tokens_from_string(model, assistant_text) + + # transform usage + usage = self._calc_response_usage(model, credentials, prompt_tokens, completion_tokens) + + # transform response + result = LLMResult( + model=response.model, + prompt_messages=prompt_messages, + message=assistant_prompt_message, + usage=usage, + system_fingerprint=response.system_fingerprint, + ) + + return result + + def _handle_generate_stream_response( + self, model: str, credentials: dict, response: Stream[Completion], prompt_messages: list[PromptMessage] + ) -> Generator: + """ + Handle llm completion stream response + + :param model: model name + :param credentials: model credentials + :param response: response + :param prompt_messages: prompt messages + :return: llm response chunk generator result + """ + full_text = "" + prompt_tokens = 0 + completion_tokens = 0 + + final_chunk = LLMResultChunk( + model=model, + prompt_messages=prompt_messages, + delta=LLMResultChunkDelta( + index=0, + message=AssistantPromptMessage(content=""), + ), + ) + + for chunk in response: + if len(chunk.choices) == 0: + if chunk.usage: + # calculate num tokens + prompt_tokens = chunk.usage.prompt_tokens + completion_tokens = chunk.usage.completion_tokens + continue + + delta = chunk.choices[0] + + if delta.finish_reason is None and (delta.text is None or delta.text == ""): + continue + + # transform assistant message to prompt message + text = delta.text or "" + assistant_prompt_message = AssistantPromptMessage(content=text) + + full_text += text + + if delta.finish_reason is not None: + final_chunk = LLMResultChunk( + model=chunk.model, + prompt_messages=prompt_messages, + system_fingerprint=chunk.system_fingerprint, + delta=LLMResultChunkDelta( + index=delta.index, + message=assistant_prompt_message, + finish_reason=delta.finish_reason, + ), + ) + else: + yield LLMResultChunk( + model=chunk.model, + prompt_messages=prompt_messages, + system_fingerprint=chunk.system_fingerprint, + delta=LLMResultChunkDelta( + index=delta.index, + message=assistant_prompt_message, + ), + ) + + if not prompt_tokens: + prompt_tokens = self._num_tokens_from_string(model, prompt_messages[0].content) + + if not completion_tokens: + completion_tokens = self._num_tokens_from_string(model, full_text) + + # transform usage + usage = self._calc_response_usage(model, credentials, prompt_tokens, completion_tokens) + + final_chunk.delta.usage = usage + + yield final_chunk + + def _chat_generate( + 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 llm chat model + + :param model: model name + :param credentials: 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 + """ + # transform credentials to kwargs for model instance + credentials_kwargs = self._to_credential_kwargs(credentials) + + # init model client + client = OpenAI(**credentials_kwargs) + + response_format = model_parameters.get("response_format") + if response_format: + if response_format == "json_schema": + json_schema = model_parameters.get("json_schema") + if not json_schema: + raise ValueError("Must define JSON Schema when the response format is json_schema") + try: + schema = json.loads(json_schema) + except: + raise ValueError(f"not correct json_schema format: {json_schema}") + model_parameters.pop("json_schema") + model_parameters["response_format"] = {"type": "json_schema", "json_schema": schema} + else: + model_parameters["response_format"] = {"type": response_format} + elif "json_schema" in model_parameters: + del model_parameters["json_schema"] + + extra_model_kwargs = {} + + if tools: + # extra_model_kwargs['tools'] = [helper.dump_model(PromptMessageFunction(function=tool)) for tool in tools] + extra_model_kwargs["functions"] = [ + {"name": tool.name, "description": tool.description, "parameters": tool.parameters} for tool in tools + ] + + if stop: + extra_model_kwargs["stop"] = stop + + if user: + extra_model_kwargs["user"] = user + + if stream: + extra_model_kwargs["stream_options"] = {"include_usage": True} + + # clear illegal prompt messages + prompt_messages = self._clear_illegal_prompt_messages(model, prompt_messages) + + # o1, o3 compatibility + block_as_stream = False + if model.startswith(("o1", "o3")): + if "max_tokens" in model_parameters: + model_parameters["max_completion_tokens"] = model_parameters["max_tokens"] + del model_parameters["max_tokens"] + + if re.match(r"^o1(-\d{4}-\d{2}-\d{2})?$", model): + if stream: + block_as_stream = True + stream = False + if "stream_options" in extra_model_kwargs: + del extra_model_kwargs["stream_options"] + + if "stop" in extra_model_kwargs: + del extra_model_kwargs["stop"] + + # chat model + messages: Any = [self._convert_prompt_message_to_dict(m) for m in prompt_messages] + response = client.chat.completions.create( + messages=messages, + model=model, + stream=stream, + **model_parameters, + **extra_model_kwargs, + ) + + if stream: + return self._handle_chat_generate_stream_response(model, credentials, response, prompt_messages, tools) + + block_result = self._handle_chat_generate_response(model, credentials, response, prompt_messages, tools) + + if block_as_stream: + return self._handle_chat_block_as_stream_response(block_result, prompt_messages, stop) + + return block_result + + def _handle_chat_block_as_stream_response( + self, + block_result: LLMResult, + prompt_messages: list[PromptMessage], + stop: Optional[list[str]] = None, + ) -> Generator[LLMResultChunk, None, None]: + """ + Handle llm chat response + :param model: model name + :param credentials: credentials + :param response: response + :param prompt_messages: prompt messages + :param tools: tools for tool calling + :return: llm response chunk generator + """ + text = block_result.message.content + text = cast(str, text) + + if stop: + text = self.enforce_stop_tokens(text, stop) + + yield LLMResultChunk( + model=block_result.model, + prompt_messages=prompt_messages, + system_fingerprint=block_result.system_fingerprint, + delta=LLMResultChunkDelta( + index=0, + message=block_result.message, + finish_reason="stop", + usage=block_result.usage, + ), + ) + + def _handle_chat_generate_response( + self, + model: str, + credentials: dict, + response: ChatCompletion, + prompt_messages: list[PromptMessage], + tools: Optional[list[PromptMessageTool]] = None, + ) -> LLMResult: + """ + Handle llm chat response + + :param model: model name + :param credentials: credentials + :param response: response + :param prompt_messages: prompt messages + :param tools: tools for tool calling + :return: llm response + """ + assistant_message = response.choices[0].message + # assistant_message_tool_calls = assistant_message.tool_calls + assistant_message_function_call = assistant_message.function_call + + # extract tool calls from response + # tool_calls = self._extract_response_tool_calls(assistant_message_tool_calls) + function_call = self._extract_response_function_call(assistant_message_function_call) + tool_calls = [function_call] if function_call else [] + + # transform assistant message to prompt message + assistant_prompt_message = AssistantPromptMessage(content=assistant_message.content, tool_calls=tool_calls) + + # calculate num tokens + if response.usage: + # transform usage + prompt_tokens = response.usage.prompt_tokens + completion_tokens = response.usage.completion_tokens + else: + # calculate num tokens + prompt_tokens = self._num_tokens_from_messages(model, prompt_messages, tools) + completion_tokens = self._num_tokens_from_messages(model, [assistant_prompt_message]) + + # transform usage + usage = self._calc_response_usage(model, credentials, prompt_tokens, completion_tokens) + + # transform response + response = LLMResult( + model=response.model, + prompt_messages=prompt_messages, + message=assistant_prompt_message, + usage=usage, + system_fingerprint=response.system_fingerprint, + ) + + return response + + def _handle_chat_generate_stream_response( + self, + model: str, + credentials: dict, + response: Stream[ChatCompletionChunk], + prompt_messages: list[PromptMessage], + tools: Optional[list[PromptMessageTool]] = None, + ) -> Generator: + """ + Handle llm chat stream response + + :param model: model name + :param response: response + :param prompt_messages: prompt messages + :param tools: tools for tool calling + :return: llm response chunk generator + """ + full_assistant_content = "" + delta_assistant_message_function_call_storage: ChoiceDeltaFunctionCall = None + prompt_tokens = 0 + completion_tokens = 0 + final_tool_calls = [] + final_chunk = LLMResultChunk( + model=model, + prompt_messages=prompt_messages, + delta=LLMResultChunkDelta( + index=0, + message=AssistantPromptMessage(content=""), + ), + ) + + for chunk in response: + if len(chunk.choices) == 0: + if chunk.usage: + # calculate num tokens + prompt_tokens = chunk.usage.prompt_tokens + completion_tokens = chunk.usage.completion_tokens + continue + + delta = chunk.choices[0] + has_finish_reason = delta.finish_reason is not None + # to fix issue #12215 yi model has special case for ligthing + # FIXME drop the case when yi model is updated + if model.startswith("yi-"): + if isinstance(delta.finish_reason, str): + # doc: https://platform.lingyiwanwu.com/docs/api-reference + has_finish_reason = delta.finish_reason.startswith(("length", "stop", "content_filter")) + + if ( + not has_finish_reason + and (delta.delta.content is None or delta.delta.content == "") + and delta.delta.function_call is None + ): + continue + + # assistant_message_tool_calls = delta.delta.tool_calls + assistant_message_function_call = delta.delta.function_call + + # extract tool calls from response + if delta_assistant_message_function_call_storage is not None: + # handle process of stream function call + if assistant_message_function_call: + # message has not ended ever + delta_assistant_message_function_call_storage.arguments += assistant_message_function_call.arguments + continue + else: + # message has ended + assistant_message_function_call = delta_assistant_message_function_call_storage + delta_assistant_message_function_call_storage = None + else: + if assistant_message_function_call: + # start of stream function call + delta_assistant_message_function_call_storage = assistant_message_function_call + if delta_assistant_message_function_call_storage.arguments is None: + delta_assistant_message_function_call_storage.arguments = "" + if not has_finish_reason: + continue + + # tool_calls = self._extract_response_tool_calls(assistant_message_tool_calls) + function_call = self._extract_response_function_call(assistant_message_function_call) + tool_calls = [function_call] if function_call else [] + if tool_calls: + final_tool_calls.extend(tool_calls) + + # transform assistant message to prompt message + assistant_prompt_message = AssistantPromptMessage(content=delta.delta.content or "", tool_calls=tool_calls) + + full_assistant_content += delta.delta.content or "" + + if has_finish_reason: + final_chunk = LLMResultChunk( + model=chunk.model, + prompt_messages=prompt_messages, + system_fingerprint=chunk.system_fingerprint, + delta=LLMResultChunkDelta( + index=delta.index, + message=assistant_prompt_message, + finish_reason=delta.finish_reason, + ), + ) + else: + yield LLMResultChunk( + model=chunk.model, + prompt_messages=prompt_messages, + system_fingerprint=chunk.system_fingerprint, + delta=LLMResultChunkDelta( + index=delta.index, + message=assistant_prompt_message, + ), + ) + + if not prompt_tokens: + prompt_tokens = self._num_tokens_from_messages(model, prompt_messages, tools) + + if not completion_tokens: + full_assistant_prompt_message = AssistantPromptMessage( + content=full_assistant_content, tool_calls=final_tool_calls + ) + completion_tokens = self._num_tokens_from_messages(model, [full_assistant_prompt_message]) + + # transform usage + usage = self._calc_response_usage(model, credentials, prompt_tokens, completion_tokens) + final_chunk.delta.usage = usage + + yield final_chunk + + def _extract_response_tool_calls( + self, response_tool_calls: list[ChatCompletionMessageToolCall | ChoiceDeltaToolCall] + ) -> list[AssistantPromptMessage.ToolCall]: + """ + Extract tool calls from response + + :param response_tool_calls: response tool calls + :return: list of tool calls + """ + tool_calls = [] + if response_tool_calls: + for response_tool_call in response_tool_calls: + function = AssistantPromptMessage.ToolCall.ToolCallFunction( + name=response_tool_call.function.name, arguments=response_tool_call.function.arguments + ) + + tool_call = AssistantPromptMessage.ToolCall( + id=response_tool_call.id, type=response_tool_call.type, function=function + ) + tool_calls.append(tool_call) + + return tool_calls + + def _extract_response_function_call( + self, response_function_call: FunctionCall | ChoiceDeltaFunctionCall + ) -> AssistantPromptMessage.ToolCall: + """ + Extract function call from response + + :param response_function_call: response function call + :return: tool call + """ + tool_call = None + if response_function_call: + function = AssistantPromptMessage.ToolCall.ToolCallFunction( + name=response_function_call.name, arguments=response_function_call.arguments + ) + + tool_call = AssistantPromptMessage.ToolCall( + id=response_function_call.name, type="function", function=function + ) + + return tool_call + + def _clear_illegal_prompt_messages(self, model: str, prompt_messages: list[PromptMessage]) -> list[PromptMessage]: + """ + Clear illegal prompt messages for OpenAI API + + :param model: model name + :param prompt_messages: prompt messages + :return: cleaned prompt messages + """ + checklist = ["gpt-4-turbo", "gpt-4-turbo-2024-04-09"] + + if model in checklist: + # count how many user messages are there + user_message_count = len([m for m in prompt_messages if isinstance(m, UserPromptMessage)]) + if user_message_count > 1: + for prompt_message in prompt_messages: + if isinstance(prompt_message, UserPromptMessage): + if isinstance(prompt_message.content, list): + prompt_message.content = "\n".join( + [ + item.data + if item.type == PromptMessageContentType.TEXT + else "[IMAGE]" + if item.type == PromptMessageContentType.IMAGE + else "" + for item in prompt_message.content + ] + ) + + if model.startswith(("o1", "o3")): + system_message_count = len([m for m in prompt_messages if isinstance(m, SystemPromptMessage)]) + if system_message_count > 0: + new_prompt_messages = [] + for prompt_message in prompt_messages: + if isinstance(prompt_message, SystemPromptMessage): + prompt_message = UserPromptMessage( + content=prompt_message.content, + name=prompt_message.name, + ) + + new_prompt_messages.append(prompt_message) + prompt_messages = new_prompt_messages + + return prompt_messages + + def _convert_prompt_message_to_dict(self, message: PromptMessage) -> dict: + """ + Convert PromptMessage to dict for OpenAI API + """ + if isinstance(message, UserPromptMessage): + if isinstance(message.content, str): + message_dict = {"role": "user", "content": message.content} + elif isinstance(message.content, list): + sub_messages = [] + for message_content in message.content: + if isinstance(message_content, TextPromptMessageContent): + sub_message_dict = {"type": "text", "text": message_content.data} + sub_messages.append(sub_message_dict) + elif isinstance(message_content, ImagePromptMessageContent): + sub_message_dict = { + "type": "image_url", + "image_url": {"url": message_content.data, "detail": message_content.detail.value}, + } + sub_messages.append(sub_message_dict) + elif isinstance(message_content, AudioPromptMessageContent): + data_split = message_content.data.split(";base64,") + base64_data = data_split[1] + sub_message_dict = { + "type": "input_audio", + "input_audio": { + "data": base64_data, + "format": message_content.format, + }, + } + sub_messages.append(sub_message_dict) + + message_dict = {"role": "user", "content": sub_messages} + elif isinstance(message, AssistantPromptMessage): + message = cast(AssistantPromptMessage, message) + message_dict = {"role": "assistant", "content": message.content} + if message.tool_calls: + # message_dict["tool_calls"] = [tool_call.dict() for tool_call in + # message.tool_calls] + function_call = message.tool_calls[0] + message_dict["function_call"] = { + "name": function_call.function.name, + "arguments": function_call.function.arguments, + } + elif isinstance(message, SystemPromptMessage): + message = cast(SystemPromptMessage, message) + if isinstance(message.content, list): + text_contents = filter(lambda c: isinstance(c, TextPromptMessageContent), message.content) + message.content = "".join(c.data for c in text_contents) + message_dict = {"role": "system", "content": message.content} + elif isinstance(message, ToolPromptMessage): + message = cast(ToolPromptMessage, message) + # message_dict = { + # "role": "tool", + # "content": message.content, + # "tool_call_id": message.tool_call_id + # } + message_dict = {"role": "function", "content": message.content, "name": message.tool_call_id} + else: + raise ValueError(f"Got unknown type {message}") + + if message.name: + message_dict["name"] = message.name + + return message_dict + + def _num_tokens_from_string(self, model: str, text: str, tools: Optional[list[PromptMessageTool]] = None) -> int: + """ + Calculate num tokens for text completion model with tiktoken package. + + :param model: model name + :param text: prompt text + :param tools: tools for tool calling + :return: number of tokens + """ + try: + encoding = tiktoken.encoding_for_model(model) + except KeyError: + encoding = tiktoken.get_encoding("cl100k_base") + + num_tokens = len(encoding.encode(text)) + + if tools: + num_tokens += self._num_tokens_for_tools(encoding, tools) + + return num_tokens + + def _num_tokens_from_messages( + self, model: str, messages: list[PromptMessage], tools: Optional[list[PromptMessageTool]] = None + ) -> int: + """Calculate num tokens for gpt-3.5-turbo and gpt-4 with tiktoken package. + + Official documentation: https://github.com/openai/openai-cookbook/blob/main/examples/How_to_format_inputs_to_ChatGPT_models.ipynb""" + if model.startswith("ft:"): + model = model.split(":")[1] + + # Currently, we can use gpt4o to calculate chatgpt-4o-latest's token. + if model == "chatgpt-4o-latest" or model.startswith(("o1", "o3")): + model = "gpt-4o" + + try: + encoding = tiktoken.get_encoding(model) + except KeyError: + logger.warning("Warning: model not found. Using cl100k_base encoding.") + model = "cl100k_base" + encoding = tiktoken.get_encoding(model) + + if model.startswith("gpt-3.5-turbo-0301"): + # every message follows {role/name}\n{content}\n + tokens_per_message = 4 + # if there's a name, the role is omitted + tokens_per_name = -1 + elif model.startswith("gpt-3.5-turbo") or model.startswith("gpt-4") or model.startswith(("o1", "o3")): + tokens_per_message = 3 + tokens_per_name = 1 + else: + raise NotImplementedError( + f"get_num_tokens_from_messages() is not presently implemented " + f"for model {model}." + "See https://platform.openai.com/docs/advanced-usage/managing-tokens for " + "information on how messages are converted to tokens." + ) + num_tokens = 0 + messages_dict = [self._convert_prompt_message_to_dict(m) for m in messages] + for message in messages_dict: + num_tokens += tokens_per_message + for key, value in message.items(): + # Cast str(value) in case the message value is not a string + # This occurs with function messages + # TODO: The current token calculation method for the image type is not implemented, + # which need to download the image and then get the resolution for calculation, + # and will increase the request delay + if isinstance(value, list): + text = "" + for item in value: + if isinstance(item, dict) and item["type"] == "text": + text += item["text"] + + value = text + + if key == "tool_calls": + for tool_call in value: + for t_key, t_value in tool_call.items(): + num_tokens += len(encoding.encode(t_key)) + if t_key == "function": + for f_key, f_value in t_value.items(): + num_tokens += len(encoding.encode(f_key)) + num_tokens += len(encoding.encode(f_value)) + else: + num_tokens += len(encoding.encode(t_key)) + num_tokens += len(encoding.encode(t_value)) + else: + num_tokens += len(encoding.encode(str(value))) + + if key == "name": + num_tokens += tokens_per_name + + # every reply is primed with assistant + num_tokens += 3 + + if tools: + num_tokens += self._num_tokens_for_tools(encoding, tools) + + return num_tokens + + def _num_tokens_for_tools(self, encoding: tiktoken.Encoding, tools: list[PromptMessageTool]) -> int: + """ + Calculate num tokens for tool calling with tiktoken package. + + :param encoding: encoding + :param tools: tools for tool calling + :return: number of tokens + """ + num_tokens = 0 + for tool in tools: + num_tokens += len(encoding.encode("type")) + num_tokens += len(encoding.encode("function")) + + # calculate num tokens for function object + num_tokens += len(encoding.encode("name")) + num_tokens += len(encoding.encode(tool.name)) + num_tokens += len(encoding.encode("description")) + num_tokens += len(encoding.encode(tool.description)) + parameters = tool.parameters + num_tokens += len(encoding.encode("parameters")) + if "title" in parameters: + num_tokens += len(encoding.encode("title")) + num_tokens += len(encoding.encode(parameters.get("title"))) + num_tokens += len(encoding.encode("type")) + num_tokens += len(encoding.encode(parameters.get("type"))) + if "properties" in parameters: + num_tokens += len(encoding.encode("properties")) + for key, value in parameters.get("properties").items(): + num_tokens += len(encoding.encode(key)) + for field_key, field_value in value.items(): + num_tokens += len(encoding.encode(field_key)) + if field_key == "enum": + for enum_field in field_value: + num_tokens += 3 + num_tokens += len(encoding.encode(enum_field)) + else: + num_tokens += len(encoding.encode(field_key)) + num_tokens += len(encoding.encode(str(field_value))) + if "required" in parameters: + num_tokens += len(encoding.encode("required")) + for required_field in parameters["required"]: + num_tokens += 3 + num_tokens += len(encoding.encode(required_field)) + + return num_tokens + + def get_customizable_model_schema(self, model: str, credentials: dict) -> AIModelEntity: + """ + OpenAI supports fine-tuning of their models. This method returns the schema of the base model + but renamed to the fine-tuned model name. + + :param model: model name + :param credentials: credentials + + :return: model schema + """ + if not model.startswith("ft:"): + base_model = model + else: + # get base_model + base_model = model.split(":")[1] + + # get model schema + base_model_schema = None + for predefined_model in self.predefined_models(): + if base_model == predefined_model.model: + base_model_schema = predefined_model + break + + if not base_model_schema: + raise ValueError(f"Base model {base_model} not found") + + base_model_schema_features = base_model_schema.features or [] + base_model_schema_model_properties = base_model_schema.model_properties + base_model_schema_parameters_rules = base_model_schema.parameter_rules + + entity = AIModelEntity( + model=model, + label=I18nObject(zh_Hans=model, en_US=model), + model_type=ModelType.LLM, + features=list(base_model_schema_features), + fetch_from=FetchFrom.CUSTOMIZABLE_MODEL, + model_properties=dict(base_model_schema_model_properties.items()), + parameter_rules=list(base_model_schema_parameters_rules), + pricing=base_model_schema.pricing, + ) + + return entity diff --git a/api/core/model_runtime/model_providers/vertex_ai/llm/gemini-2.0-flash-001.yaml b/api/core/model_runtime/model_providers/vertex_ai/llm/gemini-2.0-flash-001.yaml new file mode 100644 index 0000000000..494f5aa68e --- /dev/null +++ b/api/core/model_runtime/model_providers/vertex_ai/llm/gemini-2.0-flash-001.yaml @@ -0,0 +1,37 @@ +model: gemini-2.0-flash-001 +label: + en_US: Gemini 2.0 Flash 001 +model_type: llm +features: + - agent-thought + - vision +model_properties: + mode: chat + context_size: 1048576 +parameter_rules: + - name: temperature + use_template: temperature + - name: top_p + use_template: top_p + - name: top_k + label: + en_US: Top k + type: int + help: + en_US: Only sample from the top K options for each subsequent token. + required: false + - name: presence_penalty + use_template: presence_penalty + - name: frequency_penalty + use_template: frequency_penalty + - name: max_output_tokens + use_template: max_tokens + required: true + default: 8192 + min: 1 + max: 8192 +pricing: + input: '0.00' + output: '0.00' + unit: '0.000001' + currency: USD diff --git a/api/core/tools/provider/_position.yaml b/api/core/tools/provider/_position.yaml new file mode 100644 index 0000000000..6f13975e8a --- /dev/null +++ b/api/core/tools/provider/_position.yaml @@ -0,0 +1,80 @@ +- google +- bing +- perplexity +- duckduckgo +- searchapi +- serper +- searxng +- websearch +- tavily +- stackexchange +- pubmed +- arxiv +- aws +- nominatim +- devdocs +- spider +- firecrawl +- brave +- crossref +- jina +- webscraper +- dalle +- azuredalle +- stability +- stablediffusion +- cogview +- comfyui +- getimgai +- siliconflow +- spark +- stepfun +- xinference +- alphavantage +- yahoo +- openweather +- gaode +- aippt +- chart +- youtube +- did +- dingtalk +- discord +- feishu +- feishu_base +- feishu_document +- feishu_message +- feishu_wiki +- feishu_task +- feishu_calendar +- feishu_spreadsheet +- lark_base +- lark_document +- lark_message_and_group +- lark_wiki +- lark_task +- lark_calendar +- lark_spreadsheet +- slack +- twilio +- wecom +- wikipedia +- code +- wolframalpha +- maths +- github +- gitlab +- time +- vectorizer +- qrcode +- tianditu +- aliyuque +- google_translate +- hap +- json_process +- judge0ce +- novitaai +- onebot +- regex +- trello +- fal diff --git a/api/core/workflow/nodes/code/code_node.py b/api/core/workflow/nodes/code/code_node.py index 3c34c5b4e7..f5a1ec6b8a 100644 --- a/api/core/workflow/nodes/code/code_node.py +++ b/api/core/workflow/nodes/code/code_node.py @@ -199,7 +199,7 @@ class CodeNode(BaseNode[CodeNodeData]): if output_config.type == "object": # check if output is object if not isinstance(result.get(output_name), dict): - if result[output_name] is None: + if result.get(output_name) is None: transformed_result[output_name] = None else: raise OutputValidationError( diff --git a/api/core/workflow/nodes/llm/node.py b/api/core/workflow/nodes/llm/node.py index 35b146e5d9..d6462a731e 100644 --- a/api/core/workflow/nodes/llm/node.py +++ b/api/core/workflow/nodes/llm/node.py @@ -1193,14 +1193,12 @@ def _handle_memory_chat_mode( *, memory: TokenBufferMemory | None, memory_config: MemoryConfig | None, - model_config: ModelConfigWithCredentialsEntity, + model_config: ModelConfigWithCredentialsEntity, # TODO(-LAN-): Needs to remove ) -> Sequence[PromptMessage]: memory_messages: Sequence[PromptMessage] = [] # Get messages from memory for chat model if memory and memory_config: - rest_tokens = _calculate_rest_token(prompt_messages=[], model_config=model_config) memory_messages = memory.get_history_prompt_messages( - max_token_limit=rest_tokens, message_limit=memory_config.window.size if memory_config.window.enabled else None, ) return memory_messages diff --git a/api/fields/app_fields.py b/api/fields/app_fields.py index f42364f110..0006ae7569 100644 --- a/api/fields/app_fields.py +++ b/api/fields/app_fields.py @@ -63,6 +63,7 @@ app_detail_fields = { "created_at": TimestampField, "updated_by": fields.String, "updated_at": TimestampField, + "access_mode": fields.String, } prompt_config_fields = { @@ -98,6 +99,7 @@ app_partial_fields = { "updated_by": fields.String, "updated_at": TimestampField, "tags": fields.List(fields.Nested(tag_fields)), + "access_mode": fields.String, } @@ -176,6 +178,7 @@ app_detail_fields_with_site = { "updated_by": fields.String, "updated_at": TimestampField, "deleted_tools": fields.List(fields.Nested(deleted_tool_fields)), + "access_mode": fields.String, } diff --git a/api/poetry.lock b/api/poetry.lock new file mode 100644 index 0000000000..9f66d07b5f --- /dev/null +++ b/api/poetry.lock @@ -0,0 +1,12392 @@ +# This file is automatically @generated by Poetry 2.0.1 and should not be changed by hand. + +[[package]] +name = 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+opik = "~1.3.4" +pandas = { version = "~2.2.2", extras = ["performance", "excel"] } +pandas-stubs = "~2.2.3.241009" +psycogreen = "~1.0.2" +psycopg2-binary = "~2.9.6" +pycryptodome = "3.19.1" +pydantic = "~2.9.2" +pydantic-settings = "~2.6.0" +pydantic_extra_types = "~2.9.0" +pyjwt = "~2.8.0" +pypdfium2 = "~4.30.0" +python = ">=3.11,<3.13" +python-docx = "~1.1.0" +python-dotenv = "1.0.1" +pyyaml = "~6.0.1" +readabilipy = "0.2.0" +redis = { version = "~5.0.3", extras = ["hiredis"] } +replicate = "~0.22.0" +resend = "~0.7.0" +sagemaker = "~2.231.0" +scikit-learn = "~1.5.1" +sentry-sdk = { version = "~1.44.1", extras = ["flask"] } +sqlalchemy = "~2.0.29" +starlette = "0.41.0" +tencentcloud-sdk-python-hunyuan = "~3.0.1294" +tiktoken = "^0.9.0" +tokenizers = "~0.15.0" +transformers = "~4.35.0" +unstructured = { version = "~0.16.1", extras = ["docx", "epub", "md", "msg", "ppt", "pptx"] } +validators = "0.21.0" +volcengine-python-sdk = {extras = ["ark"], version = "~1.0.98"} +websocket-client = "~1.7.0" +xinference-client = "0.15.2" +yarl = "~1.18.3" +youtube-transcript-api = "~0.6.2" +zhipuai = "~2.1.5" +# Before adding new dependency, consider place it in alphabet order (a-z) and suitable group. + +############################################################ +# [ Indirect ] dependency group +# Related transparent dependencies with pinned version +# required by main implementations +############################################################ +[tool.poetry.group.indirect.dependencies] +kaleido = "0.2.1" +rank-bm25 = "~0.2.2" +safetensors = "~0.4.3" + +############################################################ +# [ Tools ] dependency group +############################################################ +[tool.poetry.group.tools.dependencies] +arxiv = "2.1.0" +cloudscraper = "1.2.71" +duckduckgo-search = "~6.3.0" +jsonpath-ng = "1.6.1" +matplotlib = "~3.8.2" +mplfonts = "~0.0.8" +newspaper3k = "0.2.8" +nltk = "3.9.1" +numexpr = "~2.9.0" +pydub = "~0.25.1" +qrcode = "~7.4.2" +twilio = "~9.0.4" +vanna = { version = "0.7.5", extras = ["postgres", "mysql", "clickhouse", "duckdb", "oracle"] } +wikipedia = "1.4.0" +yfinance = "~0.2.40" + +############################################################ +# [ Storage ] dependency group +# Required for storage clients +############################################################ +[tool.poetry.group.storage.dependencies] +azure-storage-blob = "12.13.0" +bce-python-sdk = "~0.9.23" +cos-python-sdk-v5 = "1.9.30" +esdk-obs-python = "3.24.6.1" +google-cloud-storage = "2.16.0" +opendal = "~0.45.12" +oss2 = "2.18.5" +supabase = "~2.8.1" +tos = "~2.7.1" + +############################################################ +# [ VDB ] dependency group +# Required by vector store clients +############################################################ +[tool.poetry.group.vdb.dependencies] +alibabacloud_gpdb20160503 = "~3.8.0" +alibabacloud_tea_openapi = "~0.3.9" +chromadb = "0.5.20" +clickhouse-connect = "~0.7.16" +couchbase = "~4.3.0" +elasticsearch = "8.14.0" +opensearch-py = "2.4.0" +oracledb = "~2.2.1" +pgvecto-rs = { version = "~0.2.1", extras = ['sqlalchemy'] } +pgvector = "0.2.5" +pymilvus = "~2.5.0" +pymochow = "1.3.1" +pyobvector = "~0.1.6" +qdrant-client = "1.7.3" +tcvectordb = "1.3.2" +tidb-vector = "0.0.9" +upstash-vector = "0.6.0" +volcengine-compat = "~1.0.156" +weaviate-client = "~3.21.0" ############################################################ # [ Dev ] dependency group diff --git a/api/services/account_service.py b/api/services/account_service.py index f930ef910b..cbfc275304 100644 --- a/api/services/account_service.py +++ b/api/services/account_service.py @@ -49,7 +49,7 @@ from services.errors.account import ( RoleAlreadyAssignedError, TenantNotFoundError, ) -from services.errors.workspace import WorkSpaceNotAllowedCreateError +from services.errors.workspace import WorkSpaceNotAllowedCreateError, WorkspacesLimitExceededError from services.feature_service import FeatureService from tasks.delete_account_task import delete_account_task from tasks.mail_account_deletion_task import send_account_deletion_verification_code @@ -622,6 +622,10 @@ class TenantService: if not FeatureService.get_system_features().is_allow_create_workspace and not is_setup: raise WorkSpaceNotAllowedCreateError() + workspaces = FeatureService.get_system_features().license.workspaces + if not workspaces.is_available(): + raise WorkspacesLimitExceededError() + if name: tenant = TenantService.create_tenant(name=name, is_setup=is_setup) else: @@ -914,7 +918,10 @@ class RegisterService: if open_id is not None and provider is not None: AccountService.link_account_integrate(provider, open_id, account) - if FeatureService.get_system_features().is_allow_create_workspace and create_workspace_required: + if (FeatureService.get_system_features().is_allow_create_workspace + and create_workspace_required + and FeatureService.get_system_features().license.workspaces.is_available() + ): tenant = TenantService.create_tenant(f"{account.name}'s Workspace") TenantService.create_tenant_member(tenant, account, role="owner") account.current_tenant = tenant diff --git a/api/services/app_service.py b/api/services/app_service.py index e87a1c7931..32a8c8d19c 100644 --- a/api/services/app_service.py +++ b/api/services/app_service.py @@ -18,8 +18,10 @@ from core.tools.utils.configuration import ToolParameterConfigurationManager from events.app_event import app_was_created from extensions.ext_database import db from models.account import Account -from models.model import App, AppMode, AppModelConfig +from models.model import App, AppMode, AppModelConfig, Site from models.tools import ApiToolProvider +from services.enterprise.enterprise_service import EnterpriseService +from services.feature_service import FeatureService from services.tag_service import TagService from tasks.remove_app_and_related_data_task import remove_app_and_related_data_task @@ -155,6 +157,10 @@ class AppService: app_was_created.send(app, account=account) + if FeatureService.get_system_features().webapp_auth.enabled: + # update web app setting as private + EnterpriseService.WebAppAuth.update_app_access_mode(app.id, "private") + return app def get_app(self, app: App) -> App: @@ -307,6 +313,10 @@ class AppService: db.session.delete(app) db.session.commit() + # clean up web app settings + if FeatureService.get_system_features().webapp_auth.enabled: + EnterpriseService.WebAppAuth.cleanup_webapp(app.id) + # Trigger asynchronous deletion of app and related data remove_app_and_related_data_task.delay(tenant_id=app.tenant_id, app_id=app.id) @@ -373,3 +383,15 @@ class AppService: meta["tool_icons"][tool_name] = {"background": "#252525", "content": "\ud83d\ude01"} return meta + + @staticmethod + def get_app_code_by_id(app_id: str) -> str: + """ + Get app code by app id + :param app_id: app id + :return: app code + """ + site = db.session.query(Site).filter(Site.app_id == app_id).first() + if not site: + raise ValueError(f"App with id {app_id} not found") + return str(site.code) diff --git a/api/services/enterprise/enterprise_service.py b/api/services/enterprise/enterprise_service.py index abc01ddf8f..9a0c478e75 100644 --- a/api/services/enterprise/enterprise_service.py +++ b/api/services/enterprise/enterprise_service.py @@ -1,11 +1,91 @@ + +from pydantic import BaseModel, Field + from services.enterprise.base import EnterpriseRequest +class WebAppSettings(BaseModel): + access_mode: str = Field( + description="Access mode for the web app. Can be 'public' or 'private'", + default="private", + alias="accessMode", + ) + + class EnterpriseService: @classmethod def get_info(cls): return EnterpriseRequest.send_request("GET", "/info") @classmethod - def get_app_web_sso_enabled(cls, app_code): - return EnterpriseRequest.send_request("GET", f"/app-sso-setting?appCode={app_code}") + def get_workspace_info(cls, tenant_id:str): + return EnterpriseRequest.send_request("GET", f"/workspace/{tenant_id}/info") + + class WebAppAuth: + @classmethod + def is_user_allowed_to_access_webapp(cls, user_id: str, app_code: str) -> bool: + params = {"userId": user_id, "appCode": app_code} + data = EnterpriseRequest.send_request("GET", "/webapp/permission", params=params) + + return data.get("result", False) + + @classmethod + def get_app_access_mode_by_id(cls, app_id: str) -> WebAppSettings: + if not app_id: + raise ValueError("app_id must be provided.") + params = {"appId": app_id} + data = EnterpriseRequest.send_request("GET", "/webapp/access-mode/id", params=params) + if not data: + raise ValueError("No data found.") + return WebAppSettings(**data) + + @classmethod + def batch_get_app_access_mode_by_id(cls, app_ids: list[str]) -> dict[str, WebAppSettings]: + if not app_ids: + return {} + body = {"appIds": app_ids} + data: dict[str, str] = EnterpriseRequest.send_request("POST", "/webapp/access-mode/batch/id", json=body) + if not data: + raise ValueError("No data found.") + + if not isinstance(data["accessModes"], dict): + raise ValueError("Invalid data format.") + + ret = {} + for key, value in data["accessModes"].items(): + curr = WebAppSettings() + curr.access_mode = value + ret[key] = curr + + return ret + + @classmethod + def get_app_access_mode_by_code(cls, app_code: str) -> WebAppSettings: + if not app_code: + raise ValueError("app_code must be provided.") + params = {"appCode": app_code} + data = EnterpriseRequest.send_request("GET", "/webapp/access-mode/code", params=params) + if not data: + raise ValueError("No data found.") + return WebAppSettings(**data) + + @classmethod + def update_app_access_mode(cls, app_id: str, access_mode: str) -> bool: + if not app_id: + raise ValueError("app_id must be provided.") + if access_mode not in ["public", "private", "private_all"]: + raise ValueError("access_mode must be either 'public', 'private', or 'private_all'") + + data = {"appId": app_id, "accessMode": access_mode} + + response = EnterpriseRequest.send_request("POST", "/webapp/access-mode", json=data) + + return response.get("result", False) + + @classmethod + def cleanup_webapp(cls, app_id: str): + if not app_id: + raise ValueError("app_id must be provided.") + + body = {"appId": app_id} + EnterpriseRequest.send_request("DELETE", "/webapp/clean", json=body) diff --git a/api/services/enterprise/mail_service.py b/api/services/enterprise/mail_service.py new file mode 100644 index 0000000000..630e7679ac --- /dev/null +++ b/api/services/enterprise/mail_service.py @@ -0,0 +1,18 @@ +from pydantic import BaseModel + +from tasks.mail_enterprise_task import send_enterprise_email_task + + +class DifyMail(BaseModel): + to: list[str] + subject: str + body: str + substitutions: dict[str, str] = {} + + +class EnterpriseMailService: + @classmethod + def send_mail(cls, mail: DifyMail): + send_enterprise_email_task.delay( + to=mail.to, subject=mail.subject, body=mail.body, substitutions=mail.substitutions + ) diff --git a/api/services/errors/workspace.py b/api/services/errors/workspace.py index 714064ffdf..577238507f 100644 --- a/api/services/errors/workspace.py +++ b/api/services/errors/workspace.py @@ -7,3 +7,7 @@ class WorkSpaceNotAllowedCreateError(BaseServiceError): class WorkSpaceNotFoundError(BaseServiceError): pass + + +class WorkspacesLimitExceededError(BaseServiceError): + pass diff --git a/api/services/feature_service.py b/api/services/feature_service.py index c2226c319f..be85a03e80 100644 --- a/api/services/feature_service.py +++ b/api/services/feature_service.py @@ -1,6 +1,6 @@ from enum import StrEnum -from pydantic import BaseModel, ConfigDict +from pydantic import BaseModel, ConfigDict, Field from configs import dify_config from services.billing_service import BillingService @@ -27,6 +27,32 @@ class LimitationModel(BaseModel): limit: int = 0 +class LicenseLimitationModel(BaseModel): + """ + - enabled: whether this limit is enforced + - size: current usage count + - limit: maximum allowed count; 0 means unlimited + """ + + enabled: bool = Field(False, description="Whether this limit is currently active") + size: int = Field(0, description="Number of resources already consumed") + limit: int = Field(0, description="Maximum number of resources allowed; 0 means no limit") + + def is_available(self, required: int = 1) -> bool: + """ + Determine whether the requested amount can be allocated. + + Returns True if: + - this limit is not active, or + - the limit is zero (unlimited), or + - there is enough remaining quota. + """ + if not self.enabled or self.limit == 0: + return True + + return (self.limit - self.size) >= required + + class LicenseStatus(StrEnum): NONE = "none" INACTIVE = "inactive" @@ -39,6 +65,27 @@ class LicenseStatus(StrEnum): class LicenseModel(BaseModel): status: LicenseStatus = LicenseStatus.NONE expired_at: str = "" + workspaces: LicenseLimitationModel = LicenseLimitationModel(enabled=False, size=0, limit=0) + + +class BrandingModel(BaseModel): + enabled: bool = False + application_title: str = "" + login_page_logo: str = "" + workspace_logo: str = "" + favicon: str = "" + + +class WebAppAuthSSOModel(BaseModel): + protocol: str = "" + + +class WebAppAuthModel(BaseModel): + enabled: bool = False + allow_sso: bool = False + sso_config: WebAppAuthSSOModel = WebAppAuthSSOModel() + allow_email_code_login: bool = False + allow_email_password_login: bool = False class FeatureModel(BaseModel): @@ -54,6 +101,8 @@ class FeatureModel(BaseModel): can_replace_logo: bool = False model_load_balancing_enabled: bool = False dataset_operator_enabled: bool = False + webapp_copyright_enabled: bool = False + workspace_members: LicenseLimitationModel = LicenseLimitationModel(enabled=False, size=0, limit=0) # pydantic configs model_config = ConfigDict(protected_namespaces=()) @@ -68,9 +117,6 @@ class KnowledgeRateLimitModel(BaseModel): class SystemFeatureModel(BaseModel): sso_enforced_for_signin: bool = False sso_enforced_for_signin_protocol: str = "" - sso_enforced_for_web: bool = False - sso_enforced_for_web_protocol: str = "" - enable_web_sso_switch_component: bool = False enable_marketplace: bool = False max_plugin_package_size: int = dify_config.PLUGIN_MAX_PACKAGE_SIZE enable_email_code_login: bool = False @@ -80,6 +126,8 @@ class SystemFeatureModel(BaseModel): is_allow_create_workspace: bool = False is_email_setup: bool = False license: LicenseModel = LicenseModel() + branding: BrandingModel = BrandingModel() + webapp_auth: WebAppAuthModel = WebAppAuthModel() class FeatureService: @@ -92,6 +140,10 @@ class FeatureService: if dify_config.BILLING_ENABLED and tenant_id: cls._fulfill_params_from_billing_api(features, tenant_id) + if dify_config.ENTERPRISE_ENABLED: + features.webapp_copyright_enabled = True + cls._fulfill_params_from_workspace_info(features, tenant_id) + return features @classmethod @@ -111,8 +163,8 @@ class FeatureService: cls._fulfill_system_params_from_env(system_features) if dify_config.ENTERPRISE_ENABLED: - system_features.enable_web_sso_switch_component = True - + system_features.branding.enabled = True + system_features.webapp_auth.enabled = True cls._fulfill_params_from_enterprise(system_features) if dify_config.MARKETPLACE_ENABLED: @@ -136,6 +188,14 @@ class FeatureService: features.dataset_operator_enabled = dify_config.DATASET_OPERATOR_ENABLED features.education.enabled = dify_config.EDUCATION_ENABLED + @classmethod + def _fulfill_params_from_workspace_info(cls, features: FeatureModel, tenant_id: str): + workspace_info = EnterpriseService.get_workspace_info(tenant_id) + if "WorkspaceMembers" in workspace_info: + features.workspace_members.size = workspace_info["WorkspaceMembers"]["used"] + features.workspace_members.limit = workspace_info["WorkspaceMembers"]["limit"] + features.workspace_members.enabled = workspace_info["WorkspaceMembers"]["enabled"] + @classmethod def _fulfill_params_from_billing_api(cls, features: FeatureModel, tenant_id: str): billing_info = BillingService.get_info(tenant_id) @@ -145,6 +205,9 @@ class FeatureService: features.billing.subscription.interval = billing_info["subscription"]["interval"] features.education.activated = billing_info["subscription"].get("education", False) + if features.billing.subscription.plan != "sandbox": + features.webapp_copyright_enabled = True + if "members" in billing_info: features.members.size = billing_info["members"]["size"] features.members.limit = billing_info["members"]["limit"] @@ -178,38 +241,53 @@ class FeatureService: features.knowledge_rate_limit = billing_info["knowledge_rate_limit"]["limit"] @classmethod - def _fulfill_params_from_enterprise(cls, features): + def _fulfill_params_from_enterprise(cls, features: SystemFeatureModel): enterprise_info = EnterpriseService.get_info() - if "sso_enforced_for_signin" in enterprise_info: - features.sso_enforced_for_signin = enterprise_info["sso_enforced_for_signin"] + if "SSOEnforcedForSignin" in enterprise_info: + features.sso_enforced_for_signin = enterprise_info["SSOEnforcedForSignin"] - if "sso_enforced_for_signin_protocol" in enterprise_info: - features.sso_enforced_for_signin_protocol = enterprise_info["sso_enforced_for_signin_protocol"] + if "SSOEnforcedForSigninProtocol" in enterprise_info: + features.sso_enforced_for_signin_protocol = enterprise_info["SSOEnforcedForSigninProtocol"] - if "sso_enforced_for_web" in enterprise_info: - features.sso_enforced_for_web = enterprise_info["sso_enforced_for_web"] + if "EnableEmailCodeLogin" in enterprise_info: + features.enable_email_code_login = enterprise_info["EnableEmailCodeLogin"] - if "sso_enforced_for_web_protocol" in enterprise_info: - features.sso_enforced_for_web_protocol = enterprise_info["sso_enforced_for_web_protocol"] + if "EnableEmailPasswordLogin" in enterprise_info: + features.enable_email_password_login = enterprise_info["EnableEmailPasswordLogin"] - if "enable_email_code_login" in enterprise_info: - features.enable_email_code_login = enterprise_info["enable_email_code_login"] + if "IsAllowRegister" in enterprise_info: + features.is_allow_register = enterprise_info["IsAllowRegister"] - if "enable_email_password_login" in enterprise_info: - features.enable_email_password_login = enterprise_info["enable_email_password_login"] + if "IsAllowCreateWorkspace" in enterprise_info: + features.is_allow_create_workspace = enterprise_info["IsAllowCreateWorkspace"] - if "is_allow_register" in enterprise_info: - features.is_allow_register = enterprise_info["is_allow_register"] + if "Branding" in enterprise_info: + features.branding.application_title = enterprise_info["Branding"].get("applicationTitle", "") + features.branding.login_page_logo = enterprise_info["Branding"].get("loginPageLogo", "") + features.branding.workspace_logo = enterprise_info["Branding"].get("workspaceLogo", "") + features.branding.favicon = enterprise_info["Branding"].get("favicon", "") - if "is_allow_create_workspace" in enterprise_info: - features.is_allow_create_workspace = enterprise_info["is_allow_create_workspace"] + if "WebAppAuth" in enterprise_info: + features.webapp_auth.allow_sso = enterprise_info["WebAppAuth"].get("allowSso", False) + features.webapp_auth.allow_email_code_login = enterprise_info["WebAppAuth"].get( + "allowEmailCodeLogin", False + ) + features.webapp_auth.allow_email_password_login = enterprise_info["WebAppAuth"].get( + "allowEmailPasswordLogin", False + ) + features.webapp_auth.sso_config.protocol = enterprise_info.get("SSOEnforcedForWebProtocol", "") - if "license" in enterprise_info: - license_info = enterprise_info["license"] + if "License" in enterprise_info: + license_info = enterprise_info["License"] if "status" in license_info: features.license.status = LicenseStatus(license_info.get("status", LicenseStatus.INACTIVE)) - if "expired_at" in license_info: - features.license.expired_at = license_info["expired_at"] + if "expiredAt" in license_info: + features.license.expired_at = license_info["expiredAt"] + + if "workspaces" in license_info: + features.license.workspaces.enabled = license_info["workspaces"]["enabled"] + features.license.workspaces.limit = license_info["workspaces"]["limit"] + features.license.workspaces.size = license_info["workspaces"]["used"] diff --git a/api/services/webapp_auth_service.py b/api/services/webapp_auth_service.py new file mode 100644 index 0000000000..506b7698e0 --- /dev/null +++ b/api/services/webapp_auth_service.py @@ -0,0 +1,137 @@ +import random +from datetime import UTC, datetime, timedelta +from typing import Any, Optional, cast + +from werkzeug.exceptions import NotFound, Unauthorized + +from configs import dify_config +from controllers.web.error import WebAppAuthAccessDeniedError +from extensions.ext_database import db +from libs.helper import TokenManager +from libs.passport import PassportService +from libs.password import compare_password +from models.account import Account, AccountStatus +from models.model import App, EndUser, Site +from services.enterprise.enterprise_service import EnterpriseService +from services.errors.account import AccountLoginError, AccountNotFoundError, AccountPasswordError +from services.feature_service import FeatureService +from tasks.mail_email_code_login import send_email_code_login_mail_task + + +class WebAppAuthService: + """Service for web app authentication.""" + + @staticmethod + def authenticate(email: str, password: str) -> Account: + """authenticate account with email and password""" + + account = Account.query.filter_by(email=email).first() + if not account: + raise AccountNotFoundError() + + if account.status == AccountStatus.BANNED.value: + raise AccountLoginError("Account is banned.") + + if account.password is None or not compare_password(password, account.password, account.password_salt): + raise AccountPasswordError("Invalid email or password.") + + return cast(Account, account) + + @classmethod + def login(cls, account: Account, app_code: str, end_user_id: str) -> str: + site = db.session.query(Site).filter(Site.code == app_code).first() + if not site: + raise NotFound("Site not found.") + + access_token = cls._get_account_jwt_token(account=account, site=site, end_user_id=end_user_id) + + return access_token + + @classmethod + def get_user_through_email(cls, email: str): + account = db.session.query(Account).filter(Account.email == email).first() + if not account: + return None + + if account.status == AccountStatus.BANNED.value: + raise Unauthorized("Account is banned.") + + return account + + @classmethod + def send_email_code_login_email( + cls, account: Optional[Account] = None, email: Optional[str] = None, language: Optional[str] = "en-US" + ): + email = account.email if account else email + if email is None: + raise ValueError("Email must be provided.") + + code = "".join([str(random.randint(0, 9)) for _ in range(6)]) + token = TokenManager.generate_token( + account=account, email=email, token_type="webapp_email_code_login", additional_data={"code": code} + ) + send_email_code_login_mail_task.delay( + language=language, + to=account.email if account else email, + code=code, + ) + + return token + + @classmethod + def get_email_code_login_data(cls, token: str) -> Optional[dict[str, Any]]: + return TokenManager.get_token_data(token, "webapp_email_code_login") + + @classmethod + def revoke_email_code_login_token(cls, token: str): + TokenManager.revoke_token(token, "webapp_email_code_login") + + @classmethod + def create_end_user(cls, app_code, email) -> EndUser: + site = db.session.query(Site).filter(Site.code == app_code).first() + app_model = db.session.query(App).filter(App.id == site.app_id).first() + end_user = EndUser( + tenant_id=app_model.tenant_id, + app_id=app_model.id, + type="browser", + is_anonymous=False, + session_id=email, + name="enterpriseuser", + external_user_id="enterpriseuser", + ) + db.session.add(end_user) + db.session.commit() + + return end_user + + @classmethod + def _validate_user_accessibility(cls, account: Account, app_code: str): + """Check if the user is allowed to access the app.""" + system_features = FeatureService.get_system_features() + if system_features.webapp_auth.enabled: + app_settings = EnterpriseService.WebAppAuth.get_app_access_mode_by_code(app_code=app_code) + + if ( + app_settings.access_mode != "public" + and not EnterpriseService.WebAppAuth.is_user_allowed_to_access_webapp(account.id, app_code=app_code) + ): + raise WebAppAuthAccessDeniedError() + + @classmethod + def _get_account_jwt_token(cls, account: Account, site: Site, end_user_id: str) -> str: + exp_dt = datetime.now(UTC) + timedelta(hours=dify_config.WebAppSessionTimeoutInHours * 24) + exp = int(exp_dt.timestamp()) + + payload = { + "iss": site.id, + "sub": "Web API Passport", + "app_id": site.app_id, + "app_code": site.code, + "user_id": account.id, + "end_user_id": end_user_id, + "token_source": "webapp", + "exp": exp, + } + + token: str = PassportService().issue(payload) + return token diff --git a/api/tasks/mail_email_code_login.py b/api/tasks/mail_email_code_login.py index 5dc935548f..ddad331725 100644 --- a/api/tasks/mail_email_code_login.py +++ b/api/tasks/mail_email_code_login.py @@ -6,6 +6,7 @@ from celery import shared_task # type: ignore from flask import render_template from extensions.ext_mail import mail +from services.feature_service import FeatureService @shared_task(queue="mail") @@ -25,10 +26,24 @@ def send_email_code_login_mail_task(language: str, to: str, code: str): # send email code login mail using different languages try: if language == "zh-Hans": - html_content = render_template("email_code_login_mail_template_zh-CN.html", to=to, code=code) + template = "email_code_login_mail_template_zh-CN.html" + system_features = FeatureService.get_system_features() + if system_features.branding.enabled: + application_title = system_features.branding.application_title + template = "without-brand/email_code_login_mail_template_zh-CN.html" + html_content = render_template(template, to=to, code=code, application_title=application_title) + else: + html_content = render_template(template, to=to, code=code) mail.send(to=to, subject="邮箱验证码", html=html_content) else: - html_content = render_template("email_code_login_mail_template_en-US.html", to=to, code=code) + template = "email_code_login_mail_template_en-US.html" + system_features = FeatureService.get_system_features() + if system_features.branding.enabled: + application_title = system_features.branding.application_title + template = "without-brand/email_code_login_mail_template_en-US.html" + html_content = render_template(template, to=to, code=code, application_title=application_title) + else: + html_content = render_template(template, to=to, code=code) mail.send(to=to, subject="Email Code", html=html_content) end_at = time.perf_counter() diff --git a/api/tasks/mail_enterprise_task.py b/api/tasks/mail_enterprise_task.py new file mode 100644 index 0000000000..b9d8fd55df --- /dev/null +++ b/api/tasks/mail_enterprise_task.py @@ -0,0 +1,33 @@ +import logging +import time + +import click +from celery import shared_task # type: ignore +from flask import render_template_string + +from extensions.ext_mail import mail + + +@shared_task(queue="mail") +def send_enterprise_email_task(to, subject, body, substitutions): + if not mail.is_inited(): + return + + logging.info(click.style("Start enterprise mail to {} with subject {}".format(to, subject), fg="green")) + start_at = time.perf_counter() + + try: + html_content = render_template_string(body, **substitutions) + + if isinstance(to, list): + for t in to: + mail.send(to=t, subject=subject, html=html_content) + else: + mail.send(to=to, subject=subject, html=html_content) + + end_at = time.perf_counter() + logging.info( + click.style("Send enterprise mail to {} succeeded: latency: {}".format(to, end_at - start_at), fg="green") + ) + except Exception: + logging.exception("Send enterprise mail to {} failed".format(to)) diff --git a/api/tasks/mail_invite_member_task.py b/api/tasks/mail_invite_member_task.py index 3094527fd4..7ca85c7f2d 100644 --- a/api/tasks/mail_invite_member_task.py +++ b/api/tasks/mail_invite_member_task.py @@ -7,6 +7,7 @@ from flask import render_template from configs import dify_config from extensions.ext_mail import mail +from services.feature_service import FeatureService @shared_task(queue="mail") @@ -33,23 +34,45 @@ def send_invite_member_mail_task(language: str, to: str, token: str, inviter_nam try: url = f"{dify_config.CONSOLE_WEB_URL}/activate?token={token}" if language == "zh-Hans": - html_content = render_template( - "invite_member_mail_template_zh-CN.html", - to=to, - inviter_name=inviter_name, - workspace_name=workspace_name, - url=url, - ) - mail.send(to=to, subject="立即加入 Dify 工作空间", html=html_content) + template = "invite_member_mail_template_zh-CN.html" + system_features = FeatureService.get_system_features() + if system_features.branding.enabled: + application_title = system_features.branding.application_title + template = "without-brand/invite_member_mail_template_zh-CN.html" + html_content = render_template( + template, + to=to, + inviter_name=inviter_name, + workspace_name=workspace_name, + url=url, + application_title=application_title, + ) + mail.send(to=to, subject=f"立即加入 {application_title} 工作空间", html=html_content) + else: + html_content = render_template( + template, to=to, inviter_name=inviter_name, workspace_name=workspace_name, url=url + ) + mail.send(to=to, subject="立即加入 Dify 工作空间", html=html_content) else: - html_content = render_template( - "invite_member_mail_template_en-US.html", - to=to, - inviter_name=inviter_name, - workspace_name=workspace_name, - url=url, - ) - mail.send(to=to, subject="Join Dify Workspace Now", html=html_content) + template = "invite_member_mail_template_en-US.html" + system_features = FeatureService.get_system_features() + if system_features.branding.enabled: + application_title = system_features.branding.application_title + template = "without-brand/invite_member_mail_template_en-US.html" + html_content = render_template( + template, + to=to, + inviter_name=inviter_name, + workspace_name=workspace_name, + url=url, + application_title=application_title, + ) + mail.send(to=to, subject=f"Join {application_title} Workspace Now", html=html_content) + else: + html_content = render_template( + template, to=to, inviter_name=inviter_name, workspace_name=workspace_name, url=url + ) + mail.send(to=to, subject="Join Dify Workspace Now", html=html_content) end_at = time.perf_counter() logging.info( diff --git a/api/tasks/mail_reset_password_task.py b/api/tasks/mail_reset_password_task.py index d5be94431b..d4f4482a48 100644 --- a/api/tasks/mail_reset_password_task.py +++ b/api/tasks/mail_reset_password_task.py @@ -6,6 +6,7 @@ from celery import shared_task # type: ignore from flask import render_template from extensions.ext_mail import mail +from services.feature_service import FeatureService @shared_task(queue="mail") @@ -25,11 +26,27 @@ def send_reset_password_mail_task(language: str, to: str, code: str): # send reset password mail using different languages try: if language == "zh-Hans": - html_content = render_template("reset_password_mail_template_zh-CN.html", to=to, code=code) - mail.send(to=to, subject="设置您的 Dify 密码", html=html_content) + template = "reset_password_mail_template_zh-CN.html" + system_features = FeatureService.get_system_features() + if system_features.branding.enabled: + application_title = system_features.branding.application_title + template = "without-brand/reset_password_mail_template_zh-CN.html" + html_content = render_template(template, to=to, code=code, application_title=application_title) + mail.send(to=to, subject=f"设置您的 {application_title} 密码", html=html_content) + else: + html_content = render_template(template, to=to, code=code) + mail.send(to=to, subject="设置您的 Dify 密码", html=html_content) else: - html_content = render_template("reset_password_mail_template_en-US.html", to=to, code=code) - mail.send(to=to, subject="Set Your Dify Password", html=html_content) + template = "reset_password_mail_template_en-US.html" + system_features = FeatureService.get_system_features() + if system_features.branding.enabled: + application_title = system_features.branding.application_title + template = "without-brand/reset_password_mail_template_en-US.html" + html_content = render_template(template, to=to, code=code, application_title=application_title) + mail.send(to=to, subject=f"Set Your {application_title} Password", html=html_content) + else: + html_content = render_template(template, to=to, code=code) + mail.send(to=to, subject="Set Your Dify Password", html=html_content) end_at = time.perf_counter() logging.info( diff --git a/api/templates/without-brand/email_code_login_mail_template_en-US.html b/api/templates/without-brand/email_code_login_mail_template_en-US.html new file mode 100644 index 0000000000..63f34ff1d3 --- /dev/null +++ b/api/templates/without-brand/email_code_login_mail_template_en-US.html @@ -0,0 +1,70 @@ + + + + + + +
+

Your login code for {{application_title}}

+

Copy and paste this code, this code will only be valid for the next 5 minutes.

+
+ {{code}} +
+

If you didn't request a login, don't worry. You can safely ignore this email.

+
+ + diff --git a/api/templates/without-brand/email_code_login_mail_template_zh-CN.html b/api/templates/without-brand/email_code_login_mail_template_zh-CN.html new file mode 100644 index 0000000000..63d2a2ec61 --- /dev/null +++ b/api/templates/without-brand/email_code_login_mail_template_zh-CN.html @@ -0,0 +1,70 @@ + + + + + + +
+

{{application_title}} 的登录验证码

+

复制并粘贴此验证码，注意验证码仅在接下来的 5 分钟内有效。

+
+ {{code}} +
+

如果您没有请求登录，请不要担心。您可以安全地忽略此电子邮件。

+
+ + diff --git a/api/templates/without-brand/invite_member_mail_template_en-US.html b/api/templates/without-brand/invite_member_mail_template_en-US.html new file mode 100644 index 0000000000..45f2ea292c --- /dev/null +++ b/api/templates/without-brand/invite_member_mail_template_en-US.html @@ -0,0 +1,69 @@ + + + + + + +
+
+

Dear {{ to }},

+

{{ inviter_name }} is pleased to invite you to join our workspace on {{application_title}}, a platform specifically designed for LLM application development. On {{application_title}}, you can explore, create, and collaborate to build and operate AI applications.

+

Click the button below to log in to {{application_title}} and join the workspace.

+

Login Here

+
+
+

Best regards,

+

{{application_title}} Team

+

Please do not reply directly to this email; it is automatically sent by the system.

+
+
+ + + diff --git a/api/templates/without-brand/invite_member_mail_template_zh-CN.html b/api/templates/without-brand/invite_member_mail_template_zh-CN.html new file mode 100644 index 0000000000..d4f80c66f8 --- /dev/null +++ b/api/templates/without-brand/invite_member_mail_template_zh-CN.html @@ -0,0 +1,69 @@ + + + + + + + +
+
+

尊敬的 {{ to }}，

+

{{ inviter_name }} 现邀请您加入我们在 {{application_title}} 的工作区，这是一个专为 LLM 应用开发而设计的平台。在 {{application_title}} 上，您可以探索、创造和合作，构建和运营 AI 应用。

+

点击下方按钮即可登录 {{application_title}} 并且加入空间。

+

在此登录

+
+
+

此致，

+

{{application_title}} 团队

+

请不要直接回复此电子邮件；由系统自动发送。

+
+
+ + diff --git a/api/templates/without-brand/reset_password_mail_template_en-US.html b/api/templates/without-brand/reset_password_mail_template_en-US.html new file mode 100644 index 0000000000..a285ec74a9 --- /dev/null +++ b/api/templates/without-brand/reset_password_mail_template_en-US.html @@ -0,0 +1,70 @@ + + + + + + +
+

Set your {{application_title}} password

+

Copy and paste this code, this code will only be valid for the next 5 minutes.

+
+ {{code}} +
+

If you didn't request, don't worry. You can safely ignore this email.

+
+ + diff --git a/api/templates/without-brand/reset_password_mail_template_zh-CN.html b/api/templates/without-brand/reset_password_mail_template_zh-CN.html new file mode 100644 index 0000000000..3fbaf2e892 --- /dev/null +++ b/api/templates/without-brand/reset_password_mail_template_zh-CN.html @@ -0,0 +1,70 @@ + + + + + + +
+

设置您的 {{application_title}} 账户密码

+

复制并粘贴此验证码，注意验证码仅在接下来的 5 分钟内有效。

+
+ {{code}} +
+

如果您没有请求，请不要担心。您可以安全地忽略此电子邮件。

+
+ + diff --git a/docker/docker-compose-template.yaml b/docker/docker-compose-template.yaml index bfbfe6c19a..c224b690e0 100644 --- a/docker/docker-compose-template.yaml +++ b/docker/docker-compose-template.yaml @@ -1,4 +1,4 @@ -x-shared-env: &shared-api-worker-env +x-shared-env: &shared-api-worker-env services: # API service api: diff --git a/web/app/(commonLayout)/app/(appDetailLayout)/[appId]/overview/cardView.tsx b/web/app/(commonLayout)/app/(appDetailLayout)/[appId]/overview/cardView.tsx index 79b45941f1..084adceef2 100644 --- a/web/app/(commonLayout)/app/(appDetailLayout)/[appId]/overview/cardView.tsx +++ b/web/app/(commonLayout)/app/(appDetailLayout)/[appId]/overview/cardView.tsx @@ -2,25 +2,22 @@ import type { FC } from 'react' import React from 'react' import { useTranslation } from 'react-i18next' -import { useContext, useContextSelector } from 'use-context-selector' +import { useContext } from 'use-context-selector' import AppCard from '@/app/components/app/overview/appCard' import Loading from '@/app/components/base/loading' import { ToastContext } from '@/app/components/base/toast' import { fetchAppDetail, - fetchAppSSO, - updateAppSSO, updateAppSiteAccessToken, updateAppSiteConfig, updateAppSiteStatus, } from '@/service/apps' -import type { App, AppSSO } from '@/types/app' +import type { App } from '@/types/app' import type { UpdateAppSiteCodeResponse } from '@/models/app' import { asyncRunSafe } from '@/utils' import { NEED_REFRESH_APP_LIST_KEY } from '@/config' import type { IAppCardProps } from '@/app/components/app/overview/appCard' import { useStore as useAppStore } from '@/app/components/app/store' -import AppContext from '@/context/app-context' export type ICardViewProps = { appId: string @@ -33,18 +30,11 @@ const CardView: FC = ({ appId, isInPanel, className }) => { const { notify } = useContext(ToastContext) const appDetail = useAppStore(state => state.appDetail) const setAppDetail = useAppStore(state => state.setAppDetail) - const systemFeatures = useContextSelector(AppContext, state => state.systemFeatures) const updateAppDetail = async () => { try { const res = await fetchAppDetail({ url: '/apps', id: appId }) - if (systemFeatures.enable_web_sso_switch_component) { - const ssoRes = await fetchAppSSO({ appId }) - setAppDetail({ ...res, enable_sso: ssoRes.enabled }) - } - else { - setAppDetail({ ...res }) - } + setAppDetail({ ...res }) } catch (error) { console.error(error) } } @@ -95,16 +85,6 @@ const CardView: FC = ({ appId, isInPanel, className }) => { if (!err) localStorage.setItem(NEED_REFRESH_APP_LIST_KEY, '1') - if (systemFeatures.enable_web_sso_switch_component) { - const [sso_err] = await asyncRunSafe( - updateAppSSO({ id: appId, enabled: Boolean(params.enable_sso) }) as Promise, - ) - if (sso_err) { - handleCallbackResult(sso_err) - return - } - } - handleCallbackResult(err) } diff --git a/web/app/(commonLayout)/app/(appDetailLayout)/layout.tsx b/web/app/(commonLayout)/app/(appDetailLayout)/layout.tsx index dda198fc89..126bf45842 100644 --- a/web/app/(commonLayout)/app/(appDetailLayout)/layout.tsx +++ b/web/app/(commonLayout)/app/(appDetailLayout)/layout.tsx @@ -2,7 +2,9 @@ import type { FC } from 'react' import React, { useEffect } from 'react' import { useRouter } from 'next/navigation' +import { useTranslation } from 'react-i18next' import { useAppContext } from '@/context/app-context' +import useDocumentTitle from '@/hooks/use-document-title' export type IAppDetail = { children: React.ReactNode @@ -11,12 +13,13 @@ export type IAppDetail = { const AppDetail: FC = ({ children }) => { const router = useRouter() const { isCurrentWorkspaceDatasetOperator } = useAppContext() + const { t } = useTranslation() + useDocumentTitle(t('common.menus.appDetail')) useEffect(() => { if (isCurrentWorkspaceDatasetOperator) return router.replace('/datasets') - // eslint-disable-next-line react-hooks/exhaustive-deps - }, [isCurrentWorkspaceDatasetOperator]) + }, [isCurrentWorkspaceDatasetOperator, router]) return ( <> diff --git a/web/app/(commonLayout)/apps/AppCard.tsx b/web/app/(commonLayout)/apps/AppCard.tsx index 3f8c180c1a..315520e10f 100644 --- a/web/app/(commonLayout)/apps/AppCard.tsx +++ b/web/app/(commonLayout)/apps/AppCard.tsx @@ -4,7 +4,8 @@ import { useContext, useContextSelector } from 'use-context-selector' import { useRouter } from 'next/navigation' import { useCallback, useEffect, useState } from 'react' import { useTranslation } from 'react-i18next' -import { RiMoreFill } from '@remixicon/react' +import { RiBuildingLine, RiGlobalLine, RiLockLine, RiMoreFill } from '@remixicon/react' +import cn from '@/utils/classnames' import type { App } from '@/types/app' import Confirm from '@/app/components/base/confirm' import Toast, { ToastContext } from '@/app/components/base/toast' @@ -30,7 +31,9 @@ import DSLExportConfirmModal from '@/app/components/workflow/dsl-export-confirm- import { fetchWorkflowDraft } from '@/service/workflow' import { fetchInstalledAppList } from '@/service/explore' import { AppTypeIcon } from '@/app/components/app/type-selector' -import cn from '@/utils/classnames' +import Tooltip from '@/app/components/base/tooltip' +import AccessControl from '@/app/components/app/app-access-control' +import { AccessMode } from '@/models/access-control' export type AppCardProps = { app: App @@ -53,6 +56,7 @@ const AppCard = ({ app, onRefresh }: AppCardProps) => { const [showDuplicateModal, setShowDuplicateModal] = useState(false) const [showSwitchModal, setShowSwitchModal] = useState(false) const [showConfirmDelete, setShowConfirmDelete] = useState(false) + const [showAccessControl, setShowAccessControl] = useState(false) const [secretEnvList, setSecretEnvList] = useState([]) const onConfirmDelete = useCallback(async () => { @@ -71,8 +75,7 @@ const AppCard = ({ app, onRefresh }: AppCardProps) => { }) } setShowConfirmDelete(false) - // eslint-disable-next-line react-hooks/exhaustive-deps - }, [app.id]) + }, [app.id, mutateApps, notify, onPlanInfoChanged, onRefresh, t]) const onEdit: CreateAppModalProps['onConfirm'] = useCallback(async ({ name, @@ -176,6 +179,13 @@ const AppCard = ({ app, onRefresh }: AppCardProps) => { setShowSwitchModal(false) } + const onUpdateAccessControl = useCallback(() => { + if (onRefresh) + onRefresh() + mutateApps() + setShowAccessControl(false) + }, [onRefresh, mutateApps, setShowAccessControl]) + const Operations = (props: HtmlContentProps) => { const onMouseLeave = async () => { props.onClose?.() @@ -210,6 +220,12 @@ const AppCard = ({ app, onRefresh }: AppCardProps) => { e.preventDefault() setShowConfirmDelete(true) } + const onClickAccessControl = async (e: React.MouseEvent) => { + e.stopPropagation() + props.onClick?.() + e.preventDefault() + setShowAccessControl(true) + } const onClickInstalledApp = async (e: React.MouseEvent) => { e.stopPropagation() props.onClick?.() @@ -253,6 +269,14 @@ const AppCard = ({ app, onRefresh }: AppCardProps) => { {t('app.openInExplore')} + { + isCurrentWorkspaceEditor && <> + + + + }
{ {app.mode === 'completion' &&
{t('app.types.completion').toUpperCase()}
}
+
+ {app.access_mode === AccessMode.PUBLIC && + + } + {app.access_mode === AccessMode.SPECIFIC_GROUPS_MEMBERS && + + } + {app.access_mode === AccessMode.ORGANIZATION && + + } +
{ popupClassName={ (app.mode === 'completion' || app.mode === 'chat') ? '!w-[256px] translate-x-[-224px]' - : '!w-[160px] translate-x-[-128px]' + : '!w-[216px] translate-x-[-128px]' } className={'!z-20 h-fit'} /> @@ -419,6 +454,9 @@ const AppCard = ({ app, onRefresh }: AppCardProps) => { onClose={() => setSecretEnvList([])} /> )} + {showAccessControl && ( + setShowAccessControl(false)} /> + )} ) } diff --git a/web/app/(commonLayout)/apps/page.tsx b/web/app/(commonLayout)/apps/page.tsx index 4a146d9b65..1a78a8fcd0 100644 --- a/web/app/(commonLayout)/apps/page.tsx +++ b/web/app/(commonLayout)/apps/page.tsx @@ -1,24 +1,22 @@ 'use client' -import { useContextSelector } from 'use-context-selector' import { useTranslation } from 'react-i18next' import { RiDiscordFill, RiGithubFill } from '@remixicon/react' import Link from 'next/link' import style from '../list.module.css' import Apps from './Apps' -import AppContext from '@/context/app-context' -import { LicenseStatus } from '@/types/feature' import { useEducationInit } from '@/app/education-apply/hooks' +import { useGlobalPublicStore } from '@/context/global-public-context' +import useDocumentTitle from '@/hooks/use-document-title' const AppList = () => { const { t } = useTranslation() useEducationInit() - - const systemFeatures = useContextSelector(AppContext, v => v.systemFeatures) - + const { systemFeatures } = useGlobalPublicStore() + useDocumentTitle(t('common.menus.apps')) return (
- {systemFeatures.license.status === LicenseStatus.NONE &&
+ {!systemFeatures.branding.enabled &&

{t('app.join')}

{t('app.communityIntro')}

diff --git a/web/app/(commonLayout)/datasets/Container.tsx b/web/app/(commonLayout)/datasets/Container.tsx index 771fa7c3f9..a836cd644a 100644 --- a/web/app/(commonLayout)/datasets/Container.tsx +++ b/web/app/(commonLayout)/datasets/Container.tsx @@ -29,9 +29,11 @@ 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' +import { useGlobalPublicStore } from '@/context/global-public-context' const Container = () => { const { t } = useTranslation() + const { systemFeatures } = useGlobalPublicStore() const router = useRouter() const { currentWorkspace, isCurrentWorkspaceOwner } = useAppContext() const showTagManagementModal = useTagStore(s => s.showTagManagementModal) @@ -125,7 +127,7 @@ const Container = () => { {activeTab === 'dataset' && ( <> - + {!systemFeatures.branding.enabled && } {showTagManagementModal && ( )} diff --git a/web/app/(commonLayout)/datasets/Datasets.tsx b/web/app/(commonLayout)/datasets/Datasets.tsx index 6383513e9e..fa7ac447e8 100644 --- a/web/app/(commonLayout)/datasets/Datasets.tsx +++ b/web/app/(commonLayout)/datasets/Datasets.tsx @@ -3,12 +3,12 @@ import { useCallback, useEffect, useRef } from 'react' import useSWRInfinite from 'swr/infinite' import { debounce } from 'lodash-es' -import { useTranslation } from 'react-i18next' import NewDatasetCard from './NewDatasetCard' import DatasetCard from './DatasetCard' import type { DataSetListResponse, FetchDatasetsParams } from '@/models/datasets' import { fetchDatasets } from '@/service/datasets' import { useAppContext } from '@/context/app-context' +import { useTranslation } from 'react-i18next' const getKey = ( pageIndex: number, @@ -48,6 +48,7 @@ const Datasets = ({ keywords, includeAll, }: Props) => { + const { t } = useTranslation() const { isCurrentWorkspaceEditor } = useAppContext() const { data, isLoading, setSize, mutate } = useSWRInfinite( (pageIndex: number, previousPageData: DataSetListResponse) => getKey(pageIndex, previousPageData, tags, keywords, includeAll), @@ -57,8 +58,6 @@ const Datasets = ({ const loadingStateRef = useRef(false) const anchorRef = useRef(null) - const { t } = useTranslation() - useEffect(() => { loadingStateRef.current = isLoading document.title = `${t('dataset.knowledge')} - Dify` @@ -87,7 +86,7 @@ const Datasets = ({ return (
- {/* SSO */} - {systemFeatures.enable_web_sso_switch_component && ( - <> - -
-

{t(`${prefixSettings}.sso.label`)}

-
-
{t(`${prefixSettings}.sso.title`)}
- {t(`${prefixSettings}.sso.tooltip`)}
- } - asChild={false} - > - setInputInfo({ ...inputInfo, enable_sso: v })}> - -
-

{t(`${prefixSettings}.sso.description`)}

-
- - )} {/* more settings switch */} {!isShowMore && ( @@ -392,14 +367,14 @@ const SettingsModal: FC = ({ )}
{t(`${prefixSettings}.more.copyrightTooltip`)}
+
{t(`${prefixSettings}.more.copyrightTooltip`)}
} asChild={false} > setInputInfo({ ...inputInfo, copyrightSwitchValue: v })} /> @@ -450,7 +425,6 @@ const SettingsModal: FC = ({ - {showAppIconPicker && (
e.stopPropagation()}> ({ + accessMode: AccessMode.SPECIFIC_GROUPS_MEMBERS, + userCanAccess: false, currentConversationId: '', appPrevChatTree: [], pinnedConversationList: [], diff --git a/web/app/components/base/chat/chat-with-history/hooks.tsx b/web/app/components/base/chat/chat-with-history/hooks.tsx index 91ceaffd1e..2794e5a054 100644 --- a/web/app/components/base/chat/chat-with-history/hooks.tsx +++ b/web/app/components/base/chat/chat-with-history/hooks.tsx @@ -43,6 +43,7 @@ import { useAppFavicon } from '@/hooks/use-app-favicon' import { InputVarType } from '@/app/components/workflow/types' import { TransferMethod } from '@/types/app' import { noop } from 'lodash-es' +import { useGetAppAccessMode, useGetUserCanAccessApp } from '@/service/access-control' function getFormattedChatList(messages: any[]) { const newChatList: ChatItem[] = [] @@ -73,6 +74,8 @@ function getFormattedChatList(messages: any[]) { export const useChatWithHistory = (installedAppInfo?: InstalledApp) => { const isInstalledApp = useMemo(() => !!installedAppInfo, [installedAppInfo]) const { data: appInfo, isLoading: appInfoLoading, error: appInfoError } = useSWR(installedAppInfo ? null : 'appInfo', fetchAppInfo) + const { isPending: isGettingAccessMode, data: appAccessMode } = useGetAppAccessMode({ appId: installedAppInfo?.app.id || appInfo?.app_id, isInstalledApp }) + const { isPending: isCheckingPermission, data: userCanAccessResult } = useGetUserCanAccessApp({ appId: installedAppInfo?.app.id || appInfo?.app_id, isInstalledApp }) useAppFavicon({ enable: !installedAppInfo, @@ -447,7 +450,9 @@ export const useChatWithHistory = (installedAppInfo?: InstalledApp) => { return { appInfoError, - appInfoLoading, + appInfoLoading: appInfoLoading || isGettingAccessMode || isCheckingPermission, + accessMode: appAccessMode?.accessMode, + userCanAccess: userCanAccessResult?.result, isInstalledApp, appId, currentConversationId, diff --git a/web/app/components/base/chat/chat-with-history/index.tsx b/web/app/components/base/chat/chat-with-history/index.tsx index dfd7bd21a7..bc9bdd1dbc 100644 --- a/web/app/components/base/chat/chat-with-history/index.tsx +++ b/web/app/components/base/chat/chat-with-history/index.tsx @@ -28,6 +28,7 @@ const ChatWithHistory: FC = ({ className, }) => { const { + userCanAccess, appInfoError, appData, appInfoLoading, @@ -58,6 +59,8 @@ const ChatWithHistory: FC = ({ ) } + if (!userCanAccess) + return if (appInfoError) { return ( @@ -124,6 +127,8 @@ const ChatWithHistoryWrap: FC = ({ const { appInfoError, appInfoLoading, + accessMode, + userCanAccess, appData, appParams, appMeta, @@ -166,6 +171,8 @@ const ChatWithHistoryWrap: FC = ({ appInfoError, appInfoLoading, appData, + accessMode, + userCanAccess, appParams, appMeta, appChatListDataLoading, diff --git a/web/app/components/base/chat/chat-with-history/sidebar/index.tsx b/web/app/components/base/chat/chat-with-history/sidebar/index.tsx index c563b5dec3..b7f0615944 100644 --- a/web/app/components/base/chat/chat-with-history/sidebar/index.tsx +++ b/web/app/components/base/chat/chat-with-history/sidebar/index.tsx @@ -19,6 +19,7 @@ import RenameModal from '@/app/components/base/chat/chat-with-history/sidebar/re import LogoSite from '@/app/components/base/logo/logo-site' import type { ConversationItem } from '@/models/share' import cn from '@/utils/classnames' +import { AccessMode } from '@/models/access-control' type Props = { isPanel?: boolean @@ -27,6 +28,8 @@ type Props = { const Sidebar = ({ isPanel }: Props) => { const { t } = useTranslation() const { + isInstalledApp, + accessMode, appData, handleNewConversation, pinnedConversationList, @@ -136,7 +139,7 @@ const Sidebar = ({ isPanel }: Props) => { )}
- + {/* powered by */}
{!appData?.custom_config?.remove_webapp_brand && ( @@ -153,25 +156,25 @@ const Sidebar = ({ isPanel }: Props) => {
)}
+ {!!showConfirm && ( + + )} + {showRename && ( + + )} - {!!showConfirm && ( - - )} - {showRename && ( - - )} ) } diff --git a/web/app/components/base/chat/embedded-chatbot/context.tsx b/web/app/components/base/chat/embedded-chatbot/context.tsx index fb00dbd64d..0dd6e7a29a 100644 --- a/web/app/components/base/chat/embedded-chatbot/context.tsx +++ b/web/app/components/base/chat/embedded-chatbot/context.tsx @@ -15,8 +15,11 @@ import type { ConversationItem, } from '@/models/share' import { noop } from 'lodash-es' +import { AccessMode } from '@/models/access-control' export type EmbeddedChatbotContextValue = { + accessMode?: AccessMode + userCanAccess?: boolean appInfoError?: any appInfoLoading?: boolean appMeta?: AppMeta @@ -53,6 +56,8 @@ export type EmbeddedChatbotContextValue = { } export const EmbeddedChatbotContext = createContext({ + userCanAccess: false, + accessMode: AccessMode.SPECIFIC_GROUPS_MEMBERS, currentConversationId: '', appPrevChatList: [], pinnedConversationList: [], diff --git a/web/app/components/base/chat/embedded-chatbot/hooks.tsx b/web/app/components/base/chat/embedded-chatbot/hooks.tsx index 7efbc95dee..5ac0cc9f48 100644 --- a/web/app/components/base/chat/embedded-chatbot/hooks.tsx +++ b/web/app/components/base/chat/embedded-chatbot/hooks.tsx @@ -36,6 +36,7 @@ import { InputVarType } from '@/app/components/workflow/types' import { TransferMethod } from '@/types/app' import { addFileInfos, sortAgentSorts } from '@/app/components/tools/utils' import { noop } from 'lodash-es' +import { useGetAppAccessMode, useGetUserCanAccessApp } from '@/service/access-control' function getFormattedChatList(messages: any[]) { const newChatList: ChatItem[] = [] @@ -66,6 +67,8 @@ function getFormattedChatList(messages: any[]) { export const useEmbeddedChatbot = () => { const isInstalledApp = false const { data: appInfo, isLoading: appInfoLoading, error: appInfoError } = useSWR('appInfo', fetchAppInfo) + const { isPending: isGettingAccessMode, data: appAccessMode } = useGetAppAccessMode({ appId: appInfo?.app_id, isInstalledApp }) + const { isPending: isCheckingPermission, data: userCanAccessResult } = useGetUserCanAccessApp({ appId: appInfo?.app_id, isInstalledApp }) const appData = useMemo(() => { return appInfo @@ -364,7 +367,9 @@ export const useEmbeddedChatbot = () => { return { appInfoError, - appInfoLoading, + appInfoLoading: appInfoLoading || isGettingAccessMode || isCheckingPermission, + accessMode: appAccessMode?.accessMode, + userCanAccess: userCanAccessResult?.result, isInstalledApp, allowResetChat, appId, diff --git a/web/app/components/base/chat/embedded-chatbot/index.tsx b/web/app/components/base/chat/embedded-chatbot/index.tsx index 96dff67bf4..3021d64989 100644 --- a/web/app/components/base/chat/embedded-chatbot/index.tsx +++ b/web/app/components/base/chat/embedded-chatbot/index.tsx @@ -24,6 +24,7 @@ import cn from '@/utils/classnames' const Chatbot = () => { const { + userCanAccess, isMobile, allowResetChat, appInfoError, @@ -66,6 +67,9 @@ const Chatbot = () => { ) } + if (!userCanAccess) + return + if (appInfoError) { return ( <> @@ -137,6 +141,8 @@ const EmbeddedChatbotWrapper = () => { appInfoError, appInfoLoading, appData, + accessMode, + userCanAccess, appParams, appMeta, appChatListDataLoading, @@ -168,6 +174,8 @@ const EmbeddedChatbotWrapper = () => { } = useEmbeddedChatbot() return file.belongs_to === 'assistant') || [] + chatList.push({ + id: item.id, + content: item.answer, + agent_thoughts: addFileInfos(item.agent_thoughts ? sortAgentSorts(item.agent_thoughts) : item.agent_thoughts, item.message_files), + feedback: item.feedback, + isAnswer: true, + citation: item.retriever_resources, + message_files: getProcessedFilesFromResponse(answerFiles.map((item: any) => ({ ...item, related_id: item.id }))), + }) + const questionFiles = item.message_files?.filter((file: any) => file.belongs_to === 'user') || [] + chatList.push({ + id: `question-${item.id}`, + content: item.query, + isAnswer: false, + message_files: getProcessedFilesFromResponse(questionFiles.map((item: any) => ({ ...item, related_id: item.id }))), + }) +} + +/** + * Computes the latest thread messages from all messages of the conversation. + * Same logic as backend codebase `api/core/prompt/utils/extract_thread_messages.py` + * + * @param fetchedMessages - The history chat list data from the backend, sorted by created_at in descending order. This includes all flattened history messages of the conversation. + * @returns An array of ChatItems representing the latest thread. + */ + +function getPrevChatList(fetchedMessages: any[]) { + const ret: ChatItem[] = [] + let nextMessageId = null + + for (const item of fetchedMessages) { + if (!item.parent_message_id) { + appendQAToChatList(ret, item) + break + } + + if (!nextMessageId) { + appendQAToChatList(ret, item) + nextMessageId = item.parent_message_id + } + else { + if (item.id === nextMessageId || nextMessageId === UUID_NIL) { + appendQAToChatList(ret, item) + nextMessageId = item.parent_message_id + } + } + } + return ret.reverse() +} function isValidGeneratedAnswer(item?: ChatItem | ChatItemInTree): boolean { return !!item && item.isAnswer && !item.id.startsWith('answer-placeholder-') && !item.isOpeningStatement @@ -187,6 +241,7 @@ export { getProcessedInputsFromUrlParams, getProcessedSystemVariablesFromUrlParams, isValidGeneratedAnswer, + getPrevChatList, getLastAnswer, buildChatItemTree, getThreadMessages, diff --git a/web/app/components/base/logo/logo-site.tsx b/web/app/components/base/logo/logo-site.tsx index 0a93fae87d..1ce392bed3 100644 --- a/web/app/components/base/logo/logo-site.tsx +++ b/web/app/components/base/logo/logo-site.tsx @@ -2,6 +2,7 @@ import type { FC } from 'react' import { basePath } from '@/utils/var' import classNames from '@/utils/classnames' +import { useGlobalPublicStore } from '@/context/global-public-context' type LogoSiteProps = { className?: string @@ -10,9 +11,15 @@ type LogoSiteProps = { const LogoSite: FC = ({ className, }) => { + const { systemFeatures } = useGlobalPublicStore() + + let src = `${basePath}/logo/logo.png` + if (systemFeatures.branding.enabled) + src = systemFeatures.branding.workspace_logo + return ( logo diff --git a/web/app/components/base/mermaid/index.tsx b/web/app/components/base/mermaid/index.tsx index 8fd8ae8b59..a484261a51 100644 --- a/web/app/components/base/mermaid/index.tsx +++ b/web/app/components/base/mermaid/index.tsx @@ -476,15 +476,15 @@ const Flowchart = React.forwardRef((props: { 'bg-white': currentTheme === Theme.light, 'bg-slate-900': currentTheme === Theme.dark, }), - mermaidDiv: cn('mermaid cursor-pointer h-auto w-full relative', { + mermaidDiv: cn('mermaid relative h-auto w-full cursor-pointer', { 'bg-white': currentTheme === Theme.light, 'bg-slate-900': currentTheme === Theme.dark, }), - errorMessage: cn('py-4 px-[26px]', { + errorMessage: cn('px-[26px] py-4', { 'text-red-500': currentTheme === Theme.light, 'text-red-400': currentTheme === Theme.dark, }), - errorIcon: cn('w-6 h-6', { + errorIcon: cn('h-6 w-6', { 'text-red-500': currentTheme === Theme.light, 'text-red-400': currentTheme === Theme.dark, }), @@ -492,7 +492,7 @@ const Flowchart = React.forwardRef((props: { 'text-gray-700': currentTheme === Theme.light, 'text-gray-300': currentTheme === Theme.dark, }), - themeToggle: cn('flex items-center justify-center w-10 h-10 rounded-full transition-all duration-300 shadow-md backdrop-blur-sm', { + themeToggle: cn('flex h-10 w-10 items-center justify-center rounded-full shadow-md backdrop-blur-sm transition-all duration-300', { 'bg-white/80 hover:bg-white hover:shadow-lg text-gray-700 border border-gray-200': currentTheme === Theme.light, 'bg-slate-800/80 hover:bg-slate-700 hover:shadow-lg text-yellow-300 border border-slate-600': currentTheme === Theme.dark, }), @@ -501,7 +501,7 @@ const Flowchart = React.forwardRef((props: { // Style classes for look options const getLookButtonClass = (lookType: 'classic' | 'handDrawn') => { return cn( - 'flex items-center justify-center mb-4 w-[calc((100%-8px)/2)] h-8 rounded-lg border border-components-option-card-option-border bg-components-option-card-option-bg cursor-pointer system-sm-medium text-text-secondary', + 'system-sm-medium mb-4 flex h-8 w-[calc((100%-8px)/2)] cursor-pointer items-center justify-center rounded-lg border border-components-option-card-option-border bg-components-option-card-option-bg text-text-secondary', look === lookType && 'border-[1.5px] border-components-option-card-option-selected-border bg-components-option-card-option-selected-bg text-text-primary', currentTheme === Theme.dark && 'border-slate-600 bg-slate-800 text-slate-300', look === lookType && currentTheme === Theme.dark && 'border-blue-500 bg-slate-700 text-white', @@ -512,7 +512,7 @@ const Flowchart = React.forwardRef((props: {
} className={themeClasses.container}>
-
+
{currentProvider && !currentProvider.plugin_id && ( { + useDocumentTitle('') const searchParams = useSearchParams() const token = searchParams.get('token') + const { systemFeatures } = useGlobalPublicStore() return (
{token ? : } -
+ {!systemFeatures.branding.enabled &&
© {new Date().getFullYear()} LangGenius, Inc. All rights reserved. -
+
}
) diff --git a/web/app/init/InitPasswordPopup.tsx b/web/app/init/InitPasswordPopup.tsx index 464da9edea..6c0e9e3078 100644 --- a/web/app/init/InitPasswordPopup.tsx +++ b/web/app/init/InitPasswordPopup.tsx @@ -8,8 +8,10 @@ import Button from '@/app/components/base/button' import { basePath } from '@/utils/var' import { fetchInitValidateStatus, initValidate } from '@/service/common' import type { InitValidateStatusResponse } from '@/models/common' +import useDocumentTitle from '@/hooks/use-document-title' const InitPasswordPopup = () => { + useDocumentTitle('') const [password, setPassword] = useState('') const [loading, setLoading] = useState(true) const [validated, setValidated] = useState(false) diff --git a/web/app/install/installForm.tsx b/web/app/install/installForm.tsx index 99f2ec6b77..277d98f8ff 100644 --- a/web/app/install/installForm.tsx +++ b/web/app/install/installForm.tsx @@ -17,6 +17,7 @@ import Button from '@/app/components/base/button' import { fetchInitValidateStatus, fetchSetupStatus, setup } from '@/service/common' import type { InitValidateStatusResponse, SetupStatusResponse } from '@/models/common' import { basePath } from '@/utils/var' +import useDocumentTitle from '@/hooks/use-document-title' const validPassword = /^(?=.*[a-zA-Z])(?=.*\d).{8,}$/ @@ -34,6 +35,7 @@ const accountFormSchema = z.object({ type AccountFormValues = z.infer const InstallForm = () => { + useDocumentTitle('') const { t } = useTranslation() const router = useRouter() const [showPassword, setShowPassword] = React.useState(false) diff --git a/web/app/install/page.tsx b/web/app/install/page.tsx index f63fdf8443..304f44b35c 100644 --- a/web/app/install/page.tsx +++ b/web/app/install/page.tsx @@ -1,17 +1,20 @@ +'use client' import React from 'react' import Header from '../signin/_header' import InstallForm from './installForm' import cn from '@/utils/classnames' +import { useGlobalPublicStore } from '@/context/global-public-context' const Install = () => { + const { systemFeatures } = useGlobalPublicStore() return (
-
+ {!systemFeatures.branding.enabled &&
© {new Date().getFullYear()} LangGenius, Inc. All rights reserved. -
+
}
) diff --git a/web/app/layout.tsx b/web/app/layout.tsx index 438f56d363..f6c988a979 100644 --- a/web/app/layout.tsx +++ b/web/app/layout.tsx @@ -1,5 +1,5 @@ -import type { Viewport } from 'next' import RoutePrefixHandle from './routePrefixHandle' +import type { Metadata, Viewport } from 'next' import I18nServer from './components/i18n-server' import BrowserInitor from './components/browser-initor' import SentryInitor from './components/sentry-initor' @@ -8,10 +8,7 @@ import { TanstackQueryIniter } from '@/context/query-client' import { ThemeProvider } from 'next-themes' import './styles/globals.css' import './styles/markdown.scss' - -export const metadata = { - title: 'Dify', -} +import GlobalPublicStoreProvider from '@/context/global-public-context' export const viewport: Viewport = { width: 'device-width', @@ -20,6 +17,10 @@ export const viewport: Viewport = { viewportFit: 'cover', userScalable: false, } +export const metadata: Metadata = { + title: ' ', + icons: 'data:', +} const LocaleLayout = async ({ children, @@ -69,7 +70,9 @@ const LocaleLayout = async ({ disableTransitionOnChange > - {children} + + {children} + diff --git a/web/app/reset-password/layout.tsx b/web/app/reset-password/layout.tsx index 3d053e4d34..979c64e7c9 100644 --- a/web/app/reset-password/layout.tsx +++ b/web/app/reset-password/layout.tsx @@ -1,8 +1,11 @@ +'use client' import Header from '../signin/_header' import cn from '@/utils/classnames' +import { useGlobalPublicStore } from '@/context/global-public-context' -export default async function SignInLayout({ children }: any) { +export default function SignInLayout({ children }: any) { + const { systemFeatures } = useGlobalPublicStore() return <>
@@ -18,9 +21,9 @@ export default async function SignInLayout({ children }: any) { {children}
-
+ {!systemFeatures.branding.enabled &&
© {new Date().getFullYear()} LangGenius, Inc. All rights reserved. -
+
}
diff --git a/web/app/reset-password/page.tsx b/web/app/reset-password/page.tsx index dd8cdbc69e..8a9bf78eb9 100644 --- a/web/app/reset-password/page.tsx +++ b/web/app/reset-password/page.tsx @@ -13,9 +13,11 @@ import Toast from '@/app/components/base/toast' import { sendResetPasswordCode } from '@/service/common' import I18NContext from '@/context/i18n' import { noop } from 'lodash-es' +import useDocumentTitle from '@/hooks/use-document-title' export default function CheckCode() { const { t } = useTranslation() + useDocumentTitle('') const searchParams = useSearchParams() const router = useRouter() const [email, setEmail] = useState('') diff --git a/web/app/signin/LoginLogo.tsx b/web/app/signin/LoginLogo.tsx new file mode 100644 index 0000000000..0753d1f98a --- /dev/null +++ b/web/app/signin/LoginLogo.tsx @@ -0,0 +1,34 @@ +'use client' +import type { FC } from 'react' +import classNames from '@/utils/classnames' +import { useSelector } from '@/context/app-context' +import { useGlobalPublicStore } from '@/context/global-public-context' + +type LoginLogoProps = { + className?: string +} + +const LoginLogo: FC = ({ + className, +}) => { + const { systemFeatures } = useGlobalPublicStore() + const { theme } = useSelector((s) => { + return { + theme: s.theme, + } + }) + + let src = theme === 'light' ? '/logo/logo-site.png' : `/logo/logo-site-${theme}.png` + if (systemFeatures.branding.enabled) + src = systemFeatures.branding.login_page_logo + + return ( + logo + ) +} + +export default LoginLogo diff --git a/web/app/signin/_header.tsx b/web/app/signin/_header.tsx index c7b1e67092..6db917c78f 100644 --- a/web/app/signin/_header.tsx +++ b/web/app/signin/_header.tsx @@ -1,17 +1,17 @@ 'use client' import React from 'react' import { useContext } from 'use-context-selector' +import LoginLogo from './LoginLogo' import Select from '@/app/components/base/select/locale' import { languages } from '@/i18n/language' import type { Locale } from '@/i18n' import I18n from '@/context/i18n' -import LogoSite from '@/app/components/base/logo/logo-site' const Header = () => { const { locale, setLocaleOnClient } = useContext(I18n) return
- +