Merge branch 'main' into feat/plugin-auto-upgrade-fe

.github/workflows/api-tests.yml

@@ -47,15 +47,17 @@ jobs:
       - name: Run Unit tests
         run: |
           uv run --project api bash dev/pytest/pytest_unit_tests.sh
+
+      - name: Coverage Summary
+        run: |
+          set -x
           # Extract coverage percentage and create a summary
           TOTAL_COVERAGE=$(python -c 'import json; print(json.load(open("coverage.json"))["totals"]["percent_covered_display"])')
 
           # Create a detailed coverage summary
           echo "### Test Coverage Summary :test_tube:" >> $GITHUB_STEP_SUMMARY
           echo "Total Coverage: ${TOTAL_COVERAGE}%" >> $GITHUB_STEP_SUMMARY
-          echo "\`\`\`" >> $GITHUB_STEP_SUMMARY
-          uv run --project api coverage report >> $GITHUB_STEP_SUMMARY
-          echo "\`\`\`" >> $GITHUB_STEP_SUMMARY
+          uv run --project api coverage report --format=markdown >> $GITHUB_STEP_SUMMARY
 
       - name: Run dify config tests
         run: uv run --project api dev/pytest/pytest_config_tests.py

.gitignore

@@ -214,3 +214,4 @@ mise.toml
 
 # AI Assistant
 .roo/
+api/.env.backup

api/configs/app_config.py

@@ -1,8 +1,11 @@
 import logging
+from pathlib import Path
 from typing import Any
 
 from pydantic.fields import FieldInfo
-from pydantic_settings import BaseSettings, PydanticBaseSettingsSource, SettingsConfigDict
+from pydantic_settings import BaseSettings, PydanticBaseSettingsSource, SettingsConfigDict, TomlConfigSettingsSource
+
+from libs.file_utils import search_file_upwards
 
 from .deploy import DeploymentConfig
 from .enterprise import EnterpriseFeatureConfig
@@ -99,4 +102,12 @@ class DifyConfig(
             RemoteSettingsSourceFactory(settings_cls),
             dotenv_settings,
             file_secret_settings,
+            TomlConfigSettingsSource(
+                settings_cls=settings_cls,
+                toml_file=search_file_upwards(
+                    base_dir_path=Path(__file__).parent,
+                    target_file_name="pyproject.toml",
+                    max_search_parent_depth=2,
+                ),
+            ),
         )

api/configs/packaging/__init__.py

@@ -1,17 +1,13 @@
 from pydantic import Field
-from pydantic_settings import BaseSettings
+
+from configs.packaging.pyproject import PyProjectConfig, PyProjectTomlConfig
 
 
-class PackagingInfo(BaseSettings):
+class PackagingInfo(PyProjectTomlConfig):
     """
     Packaging build information
     """
 
-    CURRENT_VERSION: str = Field(
-        description="Dify version",
-        default="1.5.0",
-    )
-
     COMMIT_SHA: str = Field(
         description="SHA-1 checksum of the git commit used to build the app",
         default="",

api/configs/packaging/pyproject.py

@@ -0,0 +1,17 @@
+from pydantic import BaseModel, Field
+from pydantic_settings import BaseSettings
+
+
+class PyProjectConfig(BaseModel):
+    version: str = Field(description="Dify version", default="")
+
+
+class PyProjectTomlConfig(BaseSettings):
+    """
+    configs in api/pyproject.toml
+    """
+
+    project: PyProjectConfig = Field(
+        description="configs in the project section of pyproject.toml",
+        default=PyProjectConfig(),
+    )

api/controllers/console/app/audio.py

@@ -90,23 +90,11 @@ class ChatMessageTextApi(Resource):
 
             message_id = args.get("message_id", None)
             text = args.get("text", None)
-            if (
-                app_model.mode in {AppMode.ADVANCED_CHAT.value, AppMode.WORKFLOW.value}
-                and app_model.workflow
-                and app_model.workflow.features_dict
-            ):
-                text_to_speech = app_model.workflow.features_dict.get("text_to_speech")
-                if text_to_speech is None:
-                    raise ValueError("TTS is not enabled")
-                voice = args.get("voice") or text_to_speech.get("voice")
-            else:
-                try:
-                    if app_model.app_model_config is None:
-                        raise ValueError("AppModelConfig not found")
-                    voice = args.get("voice") or app_model.app_model_config.text_to_speech_dict.get("voice")
-                except Exception:
-                    voice = None
-            response = AudioService.transcript_tts(app_model=app_model, text=text, message_id=message_id, voice=voice)
+            voice = args.get("voice", None)
+
+            response = AudioService.transcript_tts(
+                app_model=app_model, text=text, voice=voice, message_id=message_id, is_draft=True
+            )
             return response
         except services.errors.app_model_config.AppModelConfigBrokenError:
             logging.exception("App model config broken.")

api/controllers/console/auth/data_source_oauth.py

@@ -41,7 +41,7 @@ class OAuthDataSource(Resource):
             if not internal_secret:
                 return ({"error": "Internal secret is not set"},)
             oauth_provider.save_internal_access_token(internal_secret)
-            return {"data": ""}
+            return {"data": "internal"}
         else:
             auth_url = oauth_provider.get_authorization_url()
             return {"data": auth_url}, 200

api/controllers/console/explore/audio.py

@@ -18,7 +18,6 @@ from controllers.console.app.error import (
 from controllers.console.explore.wraps import InstalledAppResource
 from core.errors.error import ModelCurrentlyNotSupportError, ProviderTokenNotInitError, QuotaExceededError
 from core.model_runtime.errors.invoke import InvokeError
-from models.model import AppMode
 from services.audio_service import AudioService
 from services.errors.audio import (
     AudioTooLargeServiceError,
@@ -79,19 +78,9 @@ class ChatTextApi(InstalledAppResource):
 
             message_id = args.get("message_id", None)
             text = args.get("text", None)
-            if (
-                app_model.mode in {AppMode.ADVANCED_CHAT.value, AppMode.WORKFLOW.value}
-                and app_model.workflow
-                and app_model.workflow.features_dict
-            ):
-                text_to_speech = app_model.workflow.features_dict.get("text_to_speech")
-                voice = args.get("voice") or text_to_speech.get("voice")
-            else:
-                try:
-                    voice = args.get("voice") or app_model.app_model_config.text_to_speech_dict.get("voice")
-                except Exception:
-                    voice = None
-            response = AudioService.transcript_tts(app_model=app_model, message_id=message_id, voice=voice, text=text)
+            voice = args.get("voice", None)
+
+            response = AudioService.transcript_tts(app_model=app_model, text=text, voice=voice, message_id=message_id)
             return response
         except services.errors.app_model_config.AppModelConfigBrokenError:
             logging.exception("App model config broken.")

api/controllers/console/version.py

@@ -18,7 +18,7 @@ class VersionApi(Resource):
         check_update_url = dify_config.CHECK_UPDATE_URL
 
         result = {
-            "version": dify_config.CURRENT_VERSION,
+            "version": dify_config.project.version,
             "release_date": "",
             "release_notes": "",
             "can_auto_update": False,

api/controllers/service_api/app/audio.py

@@ -20,7 +20,7 @@ from controllers.service_api.app.error import (
 from controllers.service_api.wraps import FetchUserArg, WhereisUserArg, validate_app_token
 from core.errors.error import ModelCurrentlyNotSupportError, ProviderTokenNotInitError, QuotaExceededError
 from core.model_runtime.errors.invoke import InvokeError
-from models.model import App, AppMode, EndUser
+from models.model import App, EndUser
 from services.audio_service import AudioService
 from services.errors.audio import (
     AudioTooLargeServiceError,
@@ -78,20 +78,9 @@ class TextApi(Resource):
 
             message_id = args.get("message_id", None)
             text = args.get("text", None)
-            if (
-                app_model.mode in {AppMode.ADVANCED_CHAT.value, AppMode.WORKFLOW.value}
-                and app_model.workflow
-                and app_model.workflow.features_dict
-            ):
-                text_to_speech = app_model.workflow.features_dict.get("text_to_speech", {})
-                voice = args.get("voice") or text_to_speech.get("voice")
-            else:
-                try:
-                    voice = args.get("voice") or app_model.app_model_config.text_to_speech_dict.get("voice")
-                except Exception:
-                    voice = None
+            voice = args.get("voice", None)
             response = AudioService.transcript_tts(
-                app_model=app_model, message_id=message_id, end_user=end_user.external_user_id, voice=voice, text=text
+                app_model=app_model, text=text, voice=voice, end_user=end_user.external_user_id, message_id=message_id
             )
 
             return response

api/controllers/service_api/dataset/document.py

@@ -3,7 +3,7 @@ import json
 from flask import request
 from flask_restful import marshal, reqparse
 from sqlalchemy import desc, select
-from werkzeug.exceptions import NotFound
+from werkzeug.exceptions import Forbidden, NotFound
 
 import services
 from controllers.common.errors import FilenameNotExistsError
@@ -18,6 +18,7 @@ from controllers.service_api.app.error import (
 from controllers.service_api.dataset.error import (
     ArchivedDocumentImmutableError,
     DocumentIndexingError,
+    InvalidMetadataError,
 )
 from controllers.service_api.wraps import (
     DatasetApiResource,
@@ -210,6 +211,9 @@ class DocumentAddByFileApi(DatasetApiResource):
         if not dataset:
             raise ValueError("Dataset does not exist.")
 
+        if dataset.provider == "external":
+            raise ValueError("External datasets are not supported.")
+
         indexing_technique = args.get("indexing_technique") or dataset.indexing_technique
         if not indexing_technique:
             raise ValueError("indexing_technique is required.")
@@ -300,6 +304,9 @@ class DocumentUpdateByFileApi(DatasetApiResource):
         if not dataset:
             raise ValueError("Dataset does not exist.")
 
+        if dataset.provider == "external":
+            raise ValueError("External datasets are not supported.")
+
         # indexing_technique is already set in dataset since this is an update
         args["indexing_technique"] = dataset.indexing_technique
 
@@ -466,6 +473,101 @@ class DocumentIndexingStatusApi(DatasetApiResource):
         return data
 
 
+class DocumentDetailApi(DatasetApiResource):
+    METADATA_CHOICES = {"all", "only", "without"}
+
+    def get(self, tenant_id, dataset_id, document_id):
+        dataset_id = str(dataset_id)
+        document_id = str(document_id)
+
+        dataset = self.get_dataset(dataset_id, tenant_id)
+
+        document = DocumentService.get_document(dataset.id, document_id)
+
+        if not document:
+            raise NotFound("Document not found.")
+
+        if document.tenant_id != str(tenant_id):
+            raise Forbidden("No permission.")
+
+        metadata = request.args.get("metadata", "all")
+        if metadata not in self.METADATA_CHOICES:
+            raise InvalidMetadataError(f"Invalid metadata value: {metadata}")
+
+        if metadata == "only":
+            response = {"id": document.id, "doc_type": document.doc_type, "doc_metadata": document.doc_metadata_details}
+        elif metadata == "without":
+            dataset_process_rules = DatasetService.get_process_rules(dataset_id)
+            document_process_rules = document.dataset_process_rule.to_dict()
+            data_source_info = document.data_source_detail_dict
+            response = {
+                "id": document.id,
+                "position": document.position,
+                "data_source_type": document.data_source_type,
+                "data_source_info": data_source_info,
+                "dataset_process_rule_id": document.dataset_process_rule_id,
+                "dataset_process_rule": dataset_process_rules,
+                "document_process_rule": document_process_rules,
+                "name": document.name,
+                "created_from": document.created_from,
+                "created_by": document.created_by,
+                "created_at": document.created_at.timestamp(),
+                "tokens": document.tokens,
+                "indexing_status": document.indexing_status,
+                "completed_at": int(document.completed_at.timestamp()) if document.completed_at else None,
+                "updated_at": int(document.updated_at.timestamp()) if document.updated_at else None,
+                "indexing_latency": document.indexing_latency,
+                "error": document.error,
+                "enabled": document.enabled,
+                "disabled_at": int(document.disabled_at.timestamp()) if document.disabled_at else None,
+                "disabled_by": document.disabled_by,
+                "archived": document.archived,
+                "segment_count": document.segment_count,
+                "average_segment_length": document.average_segment_length,
+                "hit_count": document.hit_count,
+                "display_status": document.display_status,
+                "doc_form": document.doc_form,
+                "doc_language": document.doc_language,
+            }
+        else:
+            dataset_process_rules = DatasetService.get_process_rules(dataset_id)
+            document_process_rules = document.dataset_process_rule.to_dict()
+            data_source_info = document.data_source_detail_dict
+            response = {
+                "id": document.id,
+                "position": document.position,
+                "data_source_type": document.data_source_type,
+                "data_source_info": data_source_info,
+                "dataset_process_rule_id": document.dataset_process_rule_id,
+                "dataset_process_rule": dataset_process_rules,
+                "document_process_rule": document_process_rules,
+                "name": document.name,
+                "created_from": document.created_from,
+                "created_by": document.created_by,
+                "created_at": document.created_at.timestamp(),
+                "tokens": document.tokens,
+                "indexing_status": document.indexing_status,
+                "completed_at": int(document.completed_at.timestamp()) if document.completed_at else None,
+                "updated_at": int(document.updated_at.timestamp()) if document.updated_at else None,
+                "indexing_latency": document.indexing_latency,
+                "error": document.error,
+                "enabled": document.enabled,
+                "disabled_at": int(document.disabled_at.timestamp()) if document.disabled_at else None,
+                "disabled_by": document.disabled_by,
+                "archived": document.archived,
+                "doc_type": document.doc_type,
+                "doc_metadata": document.doc_metadata_details,
+                "segment_count": document.segment_count,
+                "average_segment_length": document.average_segment_length,
+                "hit_count": document.hit_count,
+                "display_status": document.display_status,
+                "doc_form": document.doc_form,
+                "doc_language": document.doc_language,
+            }
+
+        return response
+
+
 api.add_resource(
     DocumentAddByTextApi,
     "/datasets/<uuid:dataset_id>/document/create_by_text",
@@ -489,3 +591,4 @@ api.add_resource(
 api.add_resource(DocumentDeleteApi, "/datasets/<uuid:dataset_id>/documents/<uuid:document_id>")
 api.add_resource(DocumentListApi, "/datasets/<uuid:dataset_id>/documents")
 api.add_resource(DocumentIndexingStatusApi, "/datasets/<uuid:dataset_id>/documents/<string:batch>/indexing-status")
+api.add_resource(DocumentDetailApi, "/datasets/<uuid:dataset_id>/documents/<uuid:document_id>")

api/controllers/service_api/index.py

@@ -9,7 +9,7 @@ class IndexApi(Resource):
         return {
             "welcome": "Dify OpenAPI",
             "api_version": "v1",
-            "server_version": dify_config.CURRENT_VERSION,
+            "server_version": dify_config.project.version,
         }
 
 

api/controllers/service_api/wraps.py

@@ -11,13 +11,13 @@ from flask_restful import Resource
 from pydantic import BaseModel
 from sqlalchemy import select, update
 from sqlalchemy.orm import Session
-from werkzeug.exceptions import Forbidden, Unauthorized
+from werkzeug.exceptions import Forbidden, NotFound, Unauthorized
 
 from extensions.ext_database import db
 from extensions.ext_redis import redis_client
 from libs.login import _get_user
 from models.account import Account, Tenant, TenantAccountJoin, TenantStatus
-from models.dataset import RateLimitLog
+from models.dataset import Dataset, RateLimitLog
 from models.model import ApiToken, App, EndUser
 from services.feature_service import FeatureService
 
@@ -317,3 +317,11 @@ def create_or_update_end_user_for_user_id(app_model: App, user_id: Optional[str]
 
 class DatasetApiResource(Resource):
     method_decorators = [validate_dataset_token]
+
+    def get_dataset(self, dataset_id: str, tenant_id: str) -> Dataset:
+        dataset = db.session.query(Dataset).filter(Dataset.id == dataset_id, Dataset.tenant_id == tenant_id).first()
+
+        if not dataset:
+            raise NotFound("Dataset not found.")
+
+        return dataset

api/controllers/web/audio.py

@@ -19,7 +19,7 @@ from controllers.web.error import (
 from controllers.web.wraps import WebApiResource
 from core.errors.error import ModelCurrentlyNotSupportError, ProviderTokenNotInitError, QuotaExceededError
 from core.model_runtime.errors.invoke import InvokeError
-from models.model import App, AppMode
+from models.model import App
 from services.audio_service import AudioService
 from services.errors.audio import (
     AudioTooLargeServiceError,
@@ -77,21 +77,9 @@ class TextApi(WebApiResource):
 
             message_id = args.get("message_id", None)
             text = args.get("text", None)
-            if (
-                app_model.mode in {AppMode.ADVANCED_CHAT.value, AppMode.WORKFLOW.value}
-                and app_model.workflow
-                and app_model.workflow.features_dict
-            ):
-                text_to_speech = app_model.workflow.features_dict.get("text_to_speech", {})
-                voice = args.get("voice") or text_to_speech.get("voice")
-            else:
-                try:
-                    voice = args.get("voice") or app_model.app_model_config.text_to_speech_dict.get("voice")
-                except Exception:
-                    voice = None
-
+            voice = args.get("voice", None)
             response = AudioService.transcript_tts(
-                app_model=app_model, message_id=message_id, end_user=end_user.external_user_id, voice=voice, text=text
+                app_model=app_model, text=text, voice=voice, end_user=end_user.external_user_id, message_id=message_id
             )
 
             return response

api/core/app/apps/advanced_chat/app_generator.py

@@ -27,6 +27,9 @@ from core.ops.ops_trace_manager import TraceQueueManager
 from core.prompt.utils.get_thread_messages_length import get_thread_messages_length
 from core.repositories import SQLAlchemyWorkflowNodeExecutionRepository
 from core.repositories.sqlalchemy_workflow_execution_repository import SQLAlchemyWorkflowExecutionRepository
+from core.workflow.repositories.draft_variable_repository import (
+    DraftVariableSaverFactory,
+)
 from core.workflow.repositories.workflow_execution_repository import WorkflowExecutionRepository
 from core.workflow.repositories.workflow_node_execution_repository import WorkflowNodeExecutionRepository
 from core.workflow.variable_loader import DUMMY_VARIABLE_LOADER, VariableLoader
@@ -36,7 +39,10 @@ from libs.flask_utils import preserve_flask_contexts
 from models import Account, App, Conversation, EndUser, Message, Workflow, WorkflowNodeExecutionTriggeredFrom
 from models.enums import WorkflowRunTriggeredFrom
 from services.conversation_service import ConversationService
-from services.workflow_draft_variable_service import DraftVarLoader, WorkflowDraftVariableService
+from services.workflow_draft_variable_service import (
+    DraftVarLoader,
+    WorkflowDraftVariableService,
+)
 
 logger = logging.getLogger(__name__)
 
@@ -450,6 +456,7 @@ class AdvancedChatAppGenerator(MessageBasedAppGenerator):
             workflow_execution_repository=workflow_execution_repository,
             workflow_node_execution_repository=workflow_node_execution_repository,
             stream=stream,
+            draft_var_saver_factory=self._get_draft_var_saver_factory(invoke_from),
         )
 
         return AdvancedChatAppGenerateResponseConverter.convert(response=response, invoke_from=invoke_from)
@@ -521,6 +528,7 @@ class AdvancedChatAppGenerator(MessageBasedAppGenerator):
         user: Union[Account, EndUser],
         workflow_execution_repository: WorkflowExecutionRepository,
         workflow_node_execution_repository: WorkflowNodeExecutionRepository,
+        draft_var_saver_factory: DraftVariableSaverFactory,
         stream: bool = False,
     ) -> Union[ChatbotAppBlockingResponse, Generator[ChatbotAppStreamResponse, None, None]]:
         """
@@ -547,6 +555,7 @@ class AdvancedChatAppGenerator(MessageBasedAppGenerator):
             workflow_execution_repository=workflow_execution_repository,
             workflow_node_execution_repository=workflow_node_execution_repository,
             stream=stream,
+            draft_var_saver_factory=draft_var_saver_factory,
         )
 
         try:

api/core/app/apps/advanced_chat/generate_task_pipeline.py

@@ -64,6 +64,7 @@ from core.workflow.entities.workflow_execution import WorkflowExecutionStatus, W
 from core.workflow.enums import SystemVariableKey
 from core.workflow.graph_engine.entities.graph_runtime_state import GraphRuntimeState
 from core.workflow.nodes import NodeType
+from core.workflow.repositories.draft_variable_repository import DraftVariableSaverFactory
 from core.workflow.repositories.workflow_execution_repository import WorkflowExecutionRepository
 from core.workflow.repositories.workflow_node_execution_repository import WorkflowNodeExecutionRepository
 from core.workflow.workflow_cycle_manager import CycleManagerWorkflowInfo, WorkflowCycleManager
@@ -94,6 +95,7 @@ class AdvancedChatAppGenerateTaskPipeline:
         dialogue_count: int,
         workflow_execution_repository: WorkflowExecutionRepository,
         workflow_node_execution_repository: WorkflowNodeExecutionRepository,
+        draft_var_saver_factory: DraftVariableSaverFactory,
     ) -> None:
         self._base_task_pipeline = BasedGenerateTaskPipeline(
             application_generate_entity=application_generate_entity,
@@ -153,6 +155,7 @@ class AdvancedChatAppGenerateTaskPipeline:
         self._conversation_name_generate_thread: Thread | None = None
         self._recorded_files: list[Mapping[str, Any]] = []
         self._workflow_run_id: str = ""
+        self._draft_var_saver_factory = draft_var_saver_factory
 
     def process(self) -> Union[ChatbotAppBlockingResponse, Generator[ChatbotAppStreamResponse, None, None]]:
         """
@@ -371,6 +374,7 @@ class AdvancedChatAppGenerateTaskPipeline:
                         workflow_node_execution=workflow_node_execution,
                     )
                     session.commit()
+                self._save_output_for_event(event, workflow_node_execution.id)
 
                 if node_finish_resp:
                     yield node_finish_resp
@@ -390,6 +394,8 @@ class AdvancedChatAppGenerateTaskPipeline:
                     task_id=self._application_generate_entity.task_id,
                     workflow_node_execution=workflow_node_execution,
                 )
+                if isinstance(event, QueueNodeExceptionEvent):
+                    self._save_output_for_event(event, workflow_node_execution.id)
 
                 if node_finish_resp:
                     yield node_finish_resp
@@ -759,3 +765,15 @@ class AdvancedChatAppGenerateTaskPipeline:
         if not message:
             raise ValueError(f"Message not found: {self._message_id}")
         return message
+
+    def _save_output_for_event(self, event: QueueNodeSucceededEvent | QueueNodeExceptionEvent, node_execution_id: str):
+        with Session(db.engine) as session, session.begin():
+            saver = self._draft_var_saver_factory(
+                session=session,
+                app_id=self._application_generate_entity.app_config.app_id,
+                node_id=event.node_id,
+                node_type=event.node_type,
+                node_execution_id=node_execution_id,
+                enclosing_node_id=event.in_loop_id or event.in_iteration_id,
+            )
+            saver.save(event.process_data, event.outputs)

api/core/app/apps/base_app_generator.py

@@ -1,10 +1,20 @@
 import json
 from collections.abc import Generator, Mapping, Sequence
-from typing import TYPE_CHECKING, Any, Optional, Union
+from typing import TYPE_CHECKING, Any, Optional, Union, final
+
+from sqlalchemy.orm import Session
 
 from core.app.app_config.entities import VariableEntityType
+from core.app.entities.app_invoke_entities import InvokeFrom
 from core.file import File, FileUploadConfig
+from core.workflow.nodes.enums import NodeType
+from core.workflow.repositories.draft_variable_repository import (
+    DraftVariableSaver,
+    DraftVariableSaverFactory,
+    NoopDraftVariableSaver,
+)
 from factories import file_factory
+from services.workflow_draft_variable_service import DraftVariableSaver as DraftVariableSaverImpl
 
 if TYPE_CHECKING:
     from core.app.app_config.entities import VariableEntity
@@ -159,3 +169,38 @@ class BaseAppGenerator:
                         yield f"event: {message}\n\n"
 
             return gen()
+
+    @final
+    @staticmethod
+    def _get_draft_var_saver_factory(invoke_from: InvokeFrom) -> DraftVariableSaverFactory:
+        if invoke_from == InvokeFrom.DEBUGGER:
+
+            def draft_var_saver_factory(
+                session: Session,
+                app_id: str,
+                node_id: str,
+                node_type: NodeType,
+                node_execution_id: str,
+                enclosing_node_id: str | None = None,
+            ) -> DraftVariableSaver:
+                return DraftVariableSaverImpl(
+                    session=session,
+                    app_id=app_id,
+                    node_id=node_id,
+                    node_type=node_type,
+                    node_execution_id=node_execution_id,
+                    enclosing_node_id=enclosing_node_id,
+                )
+        else:
+
+            def draft_var_saver_factory(
+                session: Session,
+                app_id: str,
+                node_id: str,
+                node_type: NodeType,
+                node_execution_id: str,
+                enclosing_node_id: str | None = None,
+            ) -> DraftVariableSaver:
+                return NoopDraftVariableSaver()
+
+        return draft_var_saver_factory

api/core/app/apps/common/workflow_response_converter.py

@@ -44,6 +44,7 @@ from core.app.entities.task_entities import (
 )
 from core.file import FILE_MODEL_IDENTITY, File
 from core.tools.tool_manager import ToolManager
+from core.variables.segments import ArrayFileSegment, FileSegment, Segment
 from core.workflow.entities.workflow_execution import WorkflowExecution
 from core.workflow.entities.workflow_node_execution import WorkflowNodeExecution, WorkflowNodeExecutionStatus
 from core.workflow.nodes import NodeType
@@ -506,7 +507,8 @@ class WorkflowResponseConverter:
         # Convert to tuple to match Sequence type
         return tuple(flattened_files)
 
-    def _fetch_files_from_variable_value(self, value: Union[dict, list]) -> Sequence[Mapping[str, Any]]:
+    @classmethod
+    def _fetch_files_from_variable_value(cls, value: Union[dict, list, Segment]) -> Sequence[Mapping[str, Any]]:
         """
         Fetch files from variable value
         :param value: variable value
@@ -515,20 +517,30 @@ class WorkflowResponseConverter:
         if not value:
             return []
 
-        files = []
-        if isinstance(value, list):
+        files: list[Mapping[str, Any]] = []
+        if isinstance(value, FileSegment):
+            files.append(value.value.to_dict())
+        elif isinstance(value, ArrayFileSegment):
+            files.extend([i.to_dict() for i in value.value])
+        elif isinstance(value, File):
+            files.append(value.to_dict())
+        elif isinstance(value, list):
             for item in value:
-                file = self._get_file_var_from_value(item)
+                file = cls._get_file_var_from_value(item)
                 if file:
                     files.append(file)
-        elif isinstance(value, dict):
-            file = self._get_file_var_from_value(value)
+        elif isinstance(
+            value,
+            dict,
+        ):
+            file = cls._get_file_var_from_value(value)
             if file:
                 files.append(file)
 
         return files
 
-    def _get_file_var_from_value(self, value: Union[dict, list]) -> Mapping[str, Any] | None:
+    @classmethod
+    def _get_file_var_from_value(cls, value: Union[dict, list]) -> Mapping[str, Any] | None:
         """
         Get file var from value
         :param value: variable value

api/core/app/apps/workflow/app_generator.py

@@ -25,6 +25,7 @@ from core.model_runtime.errors.invoke import InvokeAuthorizationError
 from core.ops.ops_trace_manager import TraceQueueManager
 from core.repositories import SQLAlchemyWorkflowNodeExecutionRepository
 from core.repositories.sqlalchemy_workflow_execution_repository import SQLAlchemyWorkflowExecutionRepository
+from core.workflow.repositories.draft_variable_repository import DraftVariableSaverFactory
 from core.workflow.repositories.workflow_execution_repository import WorkflowExecutionRepository
 from core.workflow.repositories.workflow_node_execution_repository import WorkflowNodeExecutionRepository
 from core.workflow.variable_loader import DUMMY_VARIABLE_LOADER, VariableLoader
@@ -219,6 +220,9 @@ class WorkflowAppGenerator(BaseAppGenerator):
         # new thread with request context and contextvars
         context = contextvars.copy_context()
 
+        # release database connection, because the following new thread operations may take a long time
+        db.session.close()
+
         worker_thread = threading.Thread(
             target=self._generate_worker,
             kwargs={
@@ -233,6 +237,10 @@ class WorkflowAppGenerator(BaseAppGenerator):
 
         worker_thread.start()
 
+        draft_var_saver_factory = self._get_draft_var_saver_factory(
+            invoke_from,
+        )
+
         # return response or stream generator
         response = self._handle_response(
             application_generate_entity=application_generate_entity,
@@ -241,6 +249,7 @@ class WorkflowAppGenerator(BaseAppGenerator):
             user=user,
             workflow_execution_repository=workflow_execution_repository,
             workflow_node_execution_repository=workflow_node_execution_repository,
+            draft_var_saver_factory=draft_var_saver_factory,
             stream=streaming,
         )
 
@@ -471,6 +480,7 @@ class WorkflowAppGenerator(BaseAppGenerator):
         user: Union[Account, EndUser],
         workflow_execution_repository: WorkflowExecutionRepository,
         workflow_node_execution_repository: WorkflowNodeExecutionRepository,
+        draft_var_saver_factory: DraftVariableSaverFactory,
         stream: bool = False,
     ) -> Union[WorkflowAppBlockingResponse, Generator[WorkflowAppStreamResponse, None, None]]:
         """
@@ -491,6 +501,7 @@ class WorkflowAppGenerator(BaseAppGenerator):
             user=user,
             workflow_execution_repository=workflow_execution_repository,
             workflow_node_execution_repository=workflow_node_execution_repository,
+            draft_var_saver_factory=draft_var_saver_factory,
             stream=stream,
         )
 

api/core/app/apps/workflow/generate_task_pipeline.py

@@ -56,6 +56,7 @@ from core.base.tts import AppGeneratorTTSPublisher, AudioTrunk
 from core.ops.ops_trace_manager import TraceQueueManager
 from core.workflow.entities.workflow_execution import WorkflowExecution, WorkflowExecutionStatus, WorkflowType
 from core.workflow.enums import SystemVariableKey
+from core.workflow.repositories.draft_variable_repository import DraftVariableSaverFactory
 from core.workflow.repositories.workflow_execution_repository import WorkflowExecutionRepository
 from core.workflow.repositories.workflow_node_execution_repository import WorkflowNodeExecutionRepository
 from core.workflow.workflow_cycle_manager import CycleManagerWorkflowInfo, WorkflowCycleManager
@@ -87,6 +88,7 @@ class WorkflowAppGenerateTaskPipeline:
         stream: bool,
         workflow_execution_repository: WorkflowExecutionRepository,
         workflow_node_execution_repository: WorkflowNodeExecutionRepository,
+        draft_var_saver_factory: DraftVariableSaverFactory,
     ) -> None:
         self._base_task_pipeline = BasedGenerateTaskPipeline(
             application_generate_entity=application_generate_entity,
@@ -131,6 +133,8 @@ class WorkflowAppGenerateTaskPipeline:
         self._application_generate_entity = application_generate_entity
         self._workflow_features_dict = workflow.features_dict
         self._workflow_run_id = ""
+        self._invoke_from = queue_manager._invoke_from
+        self._draft_var_saver_factory = draft_var_saver_factory
 
     def process(self) -> Union[WorkflowAppBlockingResponse, Generator[WorkflowAppStreamResponse, None, None]]:
         """
@@ -322,6 +326,8 @@ class WorkflowAppGenerateTaskPipeline:
                     workflow_node_execution=workflow_node_execution,
                 )
 
+                self._save_output_for_event(event, workflow_node_execution.id)
+
                 if node_success_response:
                     yield node_success_response
             elif isinstance(
@@ -339,6 +345,8 @@ class WorkflowAppGenerateTaskPipeline:
                     task_id=self._application_generate_entity.task_id,
                     workflow_node_execution=workflow_node_execution,
                 )
+                if isinstance(event, QueueNodeExceptionEvent):
+                    self._save_output_for_event(event, workflow_node_execution.id)
 
                 if node_failed_response:
                     yield node_failed_response
@@ -593,3 +601,15 @@ class WorkflowAppGenerateTaskPipeline:
         )
 
         return response
+
+    def _save_output_for_event(self, event: QueueNodeSucceededEvent | QueueNodeExceptionEvent, node_execution_id: str):
+        with Session(db.engine) as session, session.begin():
+            saver = self._draft_var_saver_factory(
+                session=session,
+                app_id=self._application_generate_entity.app_config.app_id,
+                node_id=event.node_id,
+                node_type=event.node_type,
+                node_execution_id=node_execution_id,
+                enclosing_node_id=event.in_loop_id or event.in_iteration_id,
+            )
+            saver.save(event.process_data, event.outputs)

api/core/app/apps/workflow_app_runner.py

@@ -1,8 +1,6 @@
 from collections.abc import Mapping
 from typing import Any, Optional, cast
 
-from sqlalchemy.orm import Session
-
 from core.app.apps.base_app_queue_manager import AppQueueManager, PublishFrom
 from core.app.apps.base_app_runner import AppRunner
 from core.app.entities.queue_entities import (
@@ -35,7 +33,6 @@ from core.workflow.entities.variable_pool import VariablePool
 from core.workflow.entities.workflow_node_execution import WorkflowNodeExecutionMetadataKey
 from core.workflow.graph_engine.entities.event import (
     AgentLogEvent,
-    BaseNodeEvent,
     GraphEngineEvent,
     GraphRunFailedEvent,
     GraphRunPartialSucceededEvent,
@@ -70,9 +67,6 @@ from core.workflow.workflow_entry import WorkflowEntry
 from extensions.ext_database import db
 from models.model import App
 from models.workflow import Workflow
-from services.workflow_draft_variable_service import (
-    DraftVariableSaver,
-)
 
 
 class WorkflowBasedAppRunner(AppRunner):
@@ -400,7 +394,6 @@ class WorkflowBasedAppRunner(AppRunner):
                     in_loop_id=event.in_loop_id,
                 )
             )
-            self._save_draft_var_for_event(event)
 
         elif isinstance(event, NodeRunFailedEvent):
             self._publish_event(
@@ -464,7 +457,6 @@ class WorkflowBasedAppRunner(AppRunner):
                     in_loop_id=event.in_loop_id,
                 )
             )
-            self._save_draft_var_for_event(event)
 
         elif isinstance(event, NodeInIterationFailedEvent):
             self._publish_event(
@@ -718,30 +710,3 @@ class WorkflowBasedAppRunner(AppRunner):
 
     def _publish_event(self, event: AppQueueEvent) -> None:
         self.queue_manager.publish(event, PublishFrom.APPLICATION_MANAGER)
-
-    def _save_draft_var_for_event(self, event: BaseNodeEvent):
-        run_result = event.route_node_state.node_run_result
-        if run_result is None:
-            return
-        process_data = run_result.process_data
-        outputs = run_result.outputs
-        with Session(bind=db.engine) as session, session.begin():
-            draft_var_saver = DraftVariableSaver(
-                session=session,
-                app_id=self._get_app_id(),
-                node_id=event.node_id,
-                node_type=event.node_type,
-                # FIXME(QuantumGhost): rely on private state of queue_manager is not ideal.
-                invoke_from=self.queue_manager._invoke_from,
-                node_execution_id=event.id,
-                enclosing_node_id=event.in_loop_id or event.in_iteration_id or None,
-            )
-            draft_var_saver.save(process_data=process_data, outputs=outputs)
-
-
-def _remove_first_element_from_variable_string(key: str) -> str:
-    """
-    Remove the first element from the prefix.
-    """
-    prefix, remaining = key.split(".", maxsplit=1)
-    return remaining

api/core/app/task_pipeline/based_generate_task_pipeline.py

@@ -19,6 +19,7 @@ from core.app.entities.task_entities import (
 from core.errors.error import QuotaExceededError
 from core.model_runtime.errors.invoke import InvokeAuthorizationError, InvokeError
 from core.moderation.output_moderation import ModerationRule, OutputModeration
+from models.enums import MessageStatus
 from models.model import Message
 
 logger = logging.getLogger(__name__)
@@ -62,7 +63,7 @@ class BasedGenerateTaskPipeline:
             return err
 
         err_desc = self._error_to_desc(err)
-        message.status = "error"
+        message.status = MessageStatus.ERROR
         message.error = err_desc
         return err
 

api/core/app/task_pipeline/easy_ui_based_generate_task_pipeline.py

@@ -395,6 +395,7 @@ class EasyUIBasedGenerateTaskPipeline(BasedGenerateTaskPipeline):
         message.provider_response_latency = time.perf_counter() - self._start_at
         message.total_price = usage.total_price
         message.currency = usage.currency
+        self._task_state.llm_result.usage.latency = message.provider_response_latency
         message.message_metadata = self._task_state.metadata.model_dump_json()
 
         if trace_manager:

api/core/llm_generator/output_parser/structured_output.py

@@ -23,6 +23,7 @@ from core.model_runtime.entities.message_entities import (
     PromptMessage,
     PromptMessageTool,
     SystemPromptMessage,
+    TextPromptMessageContent,
 )
 from core.model_runtime.entities.model_entities import AIModelEntity, ParameterRule
 
@@ -170,10 +171,15 @@ def invoke_llm_with_structured_output(
             system_fingerprint: Optional[str] = None
             for event in llm_result:
                 if isinstance(event, LLMResultChunk):
+                    prompt_messages = event.prompt_messages
+                    system_fingerprint = event.system_fingerprint
+
                     if isinstance(event.delta.message.content, str):
                         result_text += event.delta.message.content
-                        prompt_messages = event.prompt_messages
-                        system_fingerprint = event.system_fingerprint
+                    elif isinstance(event.delta.message.content, list):
+                        for item in event.delta.message.content:
+                            if isinstance(item, TextPromptMessageContent):
+                                result_text += item.data
 
                 yield LLMResultChunkWithStructuredOutput(
                     model=model_schema.model,

api/core/model_runtime/entities/llm_entities.py

@@ -53,6 +53,37 @@ class LLMUsage(ModelUsage):
             latency=0.0,
         )
 
+    @classmethod
+    def from_metadata(cls, metadata: dict) -> "LLMUsage":
+        """
+        Create LLMUsage instance from metadata dictionary with default values.
+
+        Args:
+            metadata: Dictionary containing usage metadata
+
+        Returns:
+            LLMUsage instance with values from metadata or defaults
+        """
+        total_tokens = metadata.get("total_tokens", 0)
+        completion_tokens = metadata.get("completion_tokens", 0)
+        if total_tokens > 0 and completion_tokens == 0:
+            completion_tokens = total_tokens
+
+        return cls(
+            prompt_tokens=metadata.get("prompt_tokens", 0),
+            completion_tokens=completion_tokens,
+            total_tokens=total_tokens,
+            prompt_unit_price=Decimal(str(metadata.get("prompt_unit_price", 0))),
+            completion_unit_price=Decimal(str(metadata.get("completion_unit_price", 0))),
+            total_price=Decimal(str(metadata.get("total_price", 0))),
+            currency=metadata.get("currency", "USD"),
+            prompt_price_unit=Decimal(str(metadata.get("prompt_price_unit", 0))),
+            completion_price_unit=Decimal(str(metadata.get("completion_price_unit", 0))),
+            prompt_price=Decimal(str(metadata.get("prompt_price", 0))),
+            completion_price=Decimal(str(metadata.get("completion_price", 0))),
+            latency=metadata.get("latency", 0.0),
+        )
+
     def plus(self, other: "LLMUsage") -> "LLMUsage":
         """
         Add two LLMUsage instances together.

api/core/ops/arize_phoenix_trace/arize_phoenix_trace.py

@@ -0,0 +1,720 @@
+import hashlib
+import json
+import logging
+import os
+from datetime import datetime, timedelta
+from typing import Optional, Union, cast
+
+from openinference.semconv.trace import OpenInferenceSpanKindValues, SpanAttributes
+from opentelemetry import trace
+from opentelemetry.exporter.otlp.proto.grpc.trace_exporter import OTLPSpanExporter as GrpcOTLPSpanExporter
+from opentelemetry.exporter.otlp.proto.http.trace_exporter import OTLPSpanExporter as HttpOTLPSpanExporter
+from opentelemetry.sdk import trace as trace_sdk
+from opentelemetry.sdk.resources import Resource
+from opentelemetry.sdk.trace.export import SimpleSpanProcessor
+from opentelemetry.sdk.trace.id_generator import RandomIdGenerator
+from opentelemetry.trace import SpanContext, TraceFlags, TraceState
+
+from core.ops.base_trace_instance import BaseTraceInstance
+from core.ops.entities.config_entity import ArizeConfig, PhoenixConfig
+from core.ops.entities.trace_entity import (
+    BaseTraceInfo,
+    DatasetRetrievalTraceInfo,
+    GenerateNameTraceInfo,
+    MessageTraceInfo,
+    ModerationTraceInfo,
+    SuggestedQuestionTraceInfo,
+    ToolTraceInfo,
+    TraceTaskName,
+    WorkflowTraceInfo,
+)
+from extensions.ext_database import db
+from models.model import EndUser, MessageFile
+from models.workflow import WorkflowNodeExecutionModel
+
+logger = logging.getLogger(__name__)
+
+
+def setup_tracer(arize_phoenix_config: ArizeConfig | PhoenixConfig) -> tuple[trace_sdk.Tracer, SimpleSpanProcessor]:
+    """Configure OpenTelemetry tracer with OTLP exporter for Arize/Phoenix."""
+    try:
+        # Choose the appropriate exporter based on config type
+        exporter: Union[GrpcOTLPSpanExporter, HttpOTLPSpanExporter]
+        if isinstance(arize_phoenix_config, ArizeConfig):
+            arize_endpoint = f"{arize_phoenix_config.endpoint}/v1"
+            arize_headers = {
+                "api_key": arize_phoenix_config.api_key or "",
+                "space_id": arize_phoenix_config.space_id or "",
+                "authorization": f"Bearer {arize_phoenix_config.api_key or ''}",
+            }
+            exporter = GrpcOTLPSpanExporter(
+                endpoint=arize_endpoint,
+                headers=arize_headers,
+                timeout=30,
+            )
+        else:
+            phoenix_endpoint = f"{arize_phoenix_config.endpoint}/v1/traces"
+            phoenix_headers = {
+                "api_key": arize_phoenix_config.api_key or "",
+                "authorization": f"Bearer {arize_phoenix_config.api_key or ''}",
+            }
+            exporter = HttpOTLPSpanExporter(
+                endpoint=phoenix_endpoint,
+                headers=phoenix_headers,
+                timeout=30,
+            )
+
+        attributes = {
+            "openinference.project.name": arize_phoenix_config.project or "",
+            "model_id": arize_phoenix_config.project or "",
+        }
+        resource = Resource(attributes=attributes)
+        provider = trace_sdk.TracerProvider(resource=resource)
+        processor = SimpleSpanProcessor(
+            exporter,
+        )
+        provider.add_span_processor(processor)
+
+        # Create a named tracer instead of setting the global provider
+        tracer_name = f"arize_phoenix_tracer_{arize_phoenix_config.project}"
+        logger.info(f"[Arize/Phoenix] Created tracer with name: {tracer_name}")
+        return cast(trace_sdk.Tracer, provider.get_tracer(tracer_name)), processor
+    except Exception as e:
+        logger.error(f"[Arize/Phoenix] Failed to setup the tracer: {str(e)}", exc_info=True)
+        raise
+
+
+def datetime_to_nanos(dt: Optional[datetime]) -> int:
+    """Convert datetime to nanoseconds since epoch. If None, use current time."""
+    if dt is None:
+        dt = datetime.now()
+    return int(dt.timestamp() * 1_000_000_000)
+
+
+def uuid_to_trace_id(string: Optional[str]) -> int:
+    """Convert UUID string to a valid trace ID (16-byte integer)."""
+    if string is None:
+        string = ""
+    hash_object = hashlib.sha256(string.encode())
+
+    # Take the first 16 bytes (128 bits) of the hash
+    digest = hash_object.digest()[:16]
+
+    # Convert to integer (128 bits)
+    return int.from_bytes(digest, byteorder="big")
+
+
+class ArizePhoenixDataTrace(BaseTraceInstance):
+    def __init__(
+        self,
+        arize_phoenix_config: ArizeConfig | PhoenixConfig,
+    ):
+        super().__init__(arize_phoenix_config)
+        import logging
+
+        logging.basicConfig()
+        logging.getLogger().setLevel(logging.DEBUG)
+        self.arize_phoenix_config = arize_phoenix_config
+        self.tracer, self.processor = setup_tracer(arize_phoenix_config)
+        self.project = arize_phoenix_config.project
+        self.file_base_url = os.getenv("FILES_URL", "http://127.0.0.1:5001")
+
+    def trace(self, trace_info: BaseTraceInfo):
+        logger.info(f"[Arize/Phoenix] Trace: {trace_info}")
+        try:
+            if isinstance(trace_info, WorkflowTraceInfo):
+                self.workflow_trace(trace_info)
+            if isinstance(trace_info, MessageTraceInfo):
+                self.message_trace(trace_info)
+            if isinstance(trace_info, ModerationTraceInfo):
+                self.moderation_trace(trace_info)
+            if isinstance(trace_info, SuggestedQuestionTraceInfo):
+                self.suggested_question_trace(trace_info)
+            if isinstance(trace_info, DatasetRetrievalTraceInfo):
+                self.dataset_retrieval_trace(trace_info)
+            if isinstance(trace_info, ToolTraceInfo):
+                self.tool_trace(trace_info)
+            if isinstance(trace_info, GenerateNameTraceInfo):
+                self.generate_name_trace(trace_info)
+
+        except Exception as e:
+            logger.error(f"[Arize/Phoenix] Error in the trace: {str(e)}", exc_info=True)
+            raise
+
+    def workflow_trace(self, trace_info: WorkflowTraceInfo):
+        if trace_info.message_data is None:
+            return
+
+        workflow_metadata = {
+            "workflow_id": trace_info.workflow_run_id or "",
+            "message_id": trace_info.message_id or "",
+            "workflow_app_log_id": trace_info.workflow_app_log_id or "",
+            "status": trace_info.workflow_run_status or "",
+            "status_message": trace_info.error or "",
+            "level": "ERROR" if trace_info.error else "DEFAULT",
+            "total_tokens": trace_info.total_tokens or 0,
+        }
+        workflow_metadata.update(trace_info.metadata)
+
+        trace_id = uuid_to_trace_id(trace_info.message_id)
+        span_id = RandomIdGenerator().generate_span_id()
+        context = SpanContext(
+            trace_id=trace_id,
+            span_id=span_id,
+            is_remote=False,
+            trace_flags=TraceFlags(TraceFlags.SAMPLED),
+            trace_state=TraceState(),
+        )
+
+        workflow_span = self.tracer.start_span(
+            name=TraceTaskName.WORKFLOW_TRACE.value,
+            attributes={
+                SpanAttributes.INPUT_VALUE: json.dumps(trace_info.workflow_run_inputs, ensure_ascii=False),
+                SpanAttributes.OUTPUT_VALUE: json.dumps(trace_info.workflow_run_outputs, ensure_ascii=False),
+                SpanAttributes.OPENINFERENCE_SPAN_KIND: OpenInferenceSpanKindValues.CHAIN.value,
+                SpanAttributes.METADATA: json.dumps(workflow_metadata, ensure_ascii=False),
+                SpanAttributes.SESSION_ID: trace_info.conversation_id or "",
+            },
+            start_time=datetime_to_nanos(trace_info.start_time),
+            context=trace.set_span_in_context(trace.NonRecordingSpan(context)),
+        )
+
+        try:
+            # Process workflow nodes
+            for node_execution in self._get_workflow_nodes(trace_info.workflow_run_id):
+                created_at = node_execution.created_at or datetime.now()
+                elapsed_time = node_execution.elapsed_time
+                finished_at = created_at + timedelta(seconds=elapsed_time)
+
+                process_data = json.loads(node_execution.process_data) if node_execution.process_data else {}
+
+                node_metadata = {
+                    "node_id": node_execution.id,
+                    "node_type": node_execution.node_type,
+                    "node_status": node_execution.status,
+                    "tenant_id": node_execution.tenant_id,
+                    "app_id": node_execution.app_id,
+                    "app_name": node_execution.title,
+                    "status": node_execution.status,
+                    "level": "ERROR" if node_execution.status != "succeeded" else "DEFAULT",
+                }
+
+                if node_execution.execution_metadata:
+                    node_metadata.update(json.loads(node_execution.execution_metadata))
+
+                # Determine the correct span kind based on node type
+                span_kind = OpenInferenceSpanKindValues.CHAIN.value
+                if node_execution.node_type == "llm":
+                    span_kind = OpenInferenceSpanKindValues.LLM.value
+                    provider = process_data.get("model_provider")
+                    model = process_data.get("model_name")
+                    if provider:
+                        node_metadata["ls_provider"] = provider
+                    if model:
+                        node_metadata["ls_model_name"] = model
+
+                    usage = json.loads(node_execution.outputs).get("usage", {}) if node_execution.outputs else {}
+                    if usage:
+                        node_metadata["total_tokens"] = usage.get("total_tokens", 0)
+                        node_metadata["prompt_tokens"] = usage.get("prompt_tokens", 0)
+                        node_metadata["completion_tokens"] = usage.get("completion_tokens", 0)
+                elif node_execution.node_type == "dataset_retrieval":
+                    span_kind = OpenInferenceSpanKindValues.RETRIEVER.value
+                elif node_execution.node_type == "tool":
+                    span_kind = OpenInferenceSpanKindValues.TOOL.value
+                else:
+                    span_kind = OpenInferenceSpanKindValues.CHAIN.value
+
+                node_span = self.tracer.start_span(
+                    name=node_execution.node_type,
+                    attributes={
+                        SpanAttributes.INPUT_VALUE: node_execution.inputs or "{}",
+                        SpanAttributes.OUTPUT_VALUE: node_execution.outputs or "{}",
+                        SpanAttributes.OPENINFERENCE_SPAN_KIND: span_kind,
+                        SpanAttributes.METADATA: json.dumps(node_metadata, ensure_ascii=False),
+                        SpanAttributes.SESSION_ID: trace_info.conversation_id or "",
+                    },
+                    start_time=datetime_to_nanos(created_at),
+                )
+
+                try:
+                    if node_execution.node_type == "llm":
+                        provider = process_data.get("model_provider")
+                        model = process_data.get("model_name")
+                        if provider:
+                            node_span.set_attribute(SpanAttributes.LLM_PROVIDER, provider)
+                        if model:
+                            node_span.set_attribute(SpanAttributes.LLM_MODEL_NAME, model)
+
+                        usage = json.loads(node_execution.outputs).get("usage", {}) if node_execution.outputs else {}
+                        if usage:
+                            node_span.set_attribute(SpanAttributes.LLM_TOKEN_COUNT_TOTAL, usage.get("total_tokens", 0))
+                            node_span.set_attribute(
+                                SpanAttributes.LLM_TOKEN_COUNT_PROMPT, usage.get("prompt_tokens", 0)
+                            )
+                            node_span.set_attribute(
+                                SpanAttributes.LLM_TOKEN_COUNT_COMPLETION, usage.get("completion_tokens", 0)
+                            )
+                finally:
+                    node_span.end(end_time=datetime_to_nanos(finished_at))
+        finally:
+            workflow_span.end(end_time=datetime_to_nanos(trace_info.end_time))
+
+    def message_trace(self, trace_info: MessageTraceInfo):
+        if trace_info.message_data is None:
+            return
+
+        file_list = cast(list[str], trace_info.file_list) or []
+        message_file_data: Optional[MessageFile] = trace_info.message_file_data
+
+        if message_file_data is not None:
+            file_url = f"{self.file_base_url}/{message_file_data.url}" if message_file_data else ""
+            file_list.append(file_url)
+
+        message_metadata = {
+            "message_id": trace_info.message_id or "",
+            "conversation_mode": str(trace_info.conversation_mode or ""),
+            "user_id": trace_info.message_data.from_account_id or "",
+            "file_list": json.dumps(file_list),
+            "status": trace_info.message_data.status or "",
+            "status_message": trace_info.error or "",
+            "level": "ERROR" if trace_info.error else "DEFAULT",
+            "total_tokens": trace_info.total_tokens or 0,
+            "prompt_tokens": trace_info.message_tokens or 0,
+            "completion_tokens": trace_info.answer_tokens or 0,
+            "ls_provider": trace_info.message_data.model_provider or "",
+            "ls_model_name": trace_info.message_data.model_id or "",
+        }
+        message_metadata.update(trace_info.metadata)
+
+        # Add end user data if available
+        if trace_info.message_data.from_end_user_id:
+            end_user_data: Optional[EndUser] = (
+                db.session.query(EndUser).filter(EndUser.id == trace_info.message_data.from_end_user_id).first()
+            )
+            if end_user_data is not None:
+                message_metadata["end_user_id"] = end_user_data.session_id
+
+        attributes = {
+            SpanAttributes.INPUT_VALUE: trace_info.message_data.query,
+            SpanAttributes.OUTPUT_VALUE: trace_info.message_data.answer,
+            SpanAttributes.OPENINFERENCE_SPAN_KIND: OpenInferenceSpanKindValues.CHAIN.value,
+            SpanAttributes.METADATA: json.dumps(message_metadata, ensure_ascii=False),
+            SpanAttributes.SESSION_ID: trace_info.message_data.conversation_id,
+        }
+
+        trace_id = uuid_to_trace_id(trace_info.message_id)
+        message_span_id = RandomIdGenerator().generate_span_id()
+        span_context = SpanContext(
+            trace_id=trace_id,
+            span_id=message_span_id,
+            is_remote=False,
+            trace_flags=TraceFlags(TraceFlags.SAMPLED),
+            trace_state=TraceState(),
+        )
+
+        message_span = self.tracer.start_span(
+            name=TraceTaskName.MESSAGE_TRACE.value,
+            attributes=attributes,
+            start_time=datetime_to_nanos(trace_info.start_time),
+            context=trace.set_span_in_context(trace.NonRecordingSpan(span_context)),
+        )
+
+        try:
+            if trace_info.error:
+                message_span.add_event(
+                    "exception",
+                    attributes={
+                        "exception.message": trace_info.error,
+                        "exception.type": "Error",
+                        "exception.stacktrace": trace_info.error,
+                    },
+                )
+
+            # Convert outputs to string based on type
+            if isinstance(trace_info.outputs, dict | list):
+                outputs_str = json.dumps(trace_info.outputs, ensure_ascii=False)
+            elif isinstance(trace_info.outputs, str):
+                outputs_str = trace_info.outputs
+            else:
+                outputs_str = str(trace_info.outputs)
+
+            llm_attributes = {
+                SpanAttributes.OPENINFERENCE_SPAN_KIND: OpenInferenceSpanKindValues.LLM.value,
+                SpanAttributes.INPUT_VALUE: json.dumps(trace_info.inputs, ensure_ascii=False),
+                SpanAttributes.OUTPUT_VALUE: outputs_str,
+                SpanAttributes.METADATA: json.dumps(message_metadata, ensure_ascii=False),
+                SpanAttributes.SESSION_ID: trace_info.message_data.conversation_id,
+            }
+
+            if isinstance(trace_info.inputs, list):
+                for i, msg in enumerate(trace_info.inputs):
+                    if isinstance(msg, dict):
+                        llm_attributes[f"{SpanAttributes.LLM_INPUT_MESSAGES}.{i}.message.content"] = msg.get("text", "")
+                        llm_attributes[f"{SpanAttributes.LLM_INPUT_MESSAGES}.{i}.message.role"] = msg.get(
+                            "role", "user"
+                        )
+                        # todo: handle assistant and tool role messages, as they don't always
+                        # have a text field, but may have a tool_calls field instead
+                        # e.g. 'tool_calls': [{'id': '98af3a29-b066-45a5-b4b1-46c74ddafc58',
+                        # 'type': 'function', 'function': {'name': 'current_time', 'arguments': '{}'}}]}
+            elif isinstance(trace_info.inputs, dict):
+                llm_attributes[f"{SpanAttributes.LLM_INPUT_MESSAGES}.0.message.content"] = json.dumps(trace_info.inputs)
+                llm_attributes[f"{SpanAttributes.LLM_INPUT_MESSAGES}.0.message.role"] = "user"
+            elif isinstance(trace_info.inputs, str):
+                llm_attributes[f"{SpanAttributes.LLM_INPUT_MESSAGES}.0.message.content"] = trace_info.inputs
+                llm_attributes[f"{SpanAttributes.LLM_INPUT_MESSAGES}.0.message.role"] = "user"
+
+            if trace_info.total_tokens is not None and trace_info.total_tokens > 0:
+                llm_attributes[SpanAttributes.LLM_TOKEN_COUNT_TOTAL] = trace_info.total_tokens
+            if trace_info.message_tokens is not None and trace_info.message_tokens > 0:
+                llm_attributes[SpanAttributes.LLM_TOKEN_COUNT_PROMPT] = trace_info.message_tokens
+            if trace_info.answer_tokens is not None and trace_info.answer_tokens > 0:
+                llm_attributes[SpanAttributes.LLM_TOKEN_COUNT_COMPLETION] = trace_info.answer_tokens
+
+            if trace_info.message_data.model_id is not None:
+                llm_attributes[SpanAttributes.LLM_MODEL_NAME] = trace_info.message_data.model_id
+            if trace_info.message_data.model_provider is not None:
+                llm_attributes[SpanAttributes.LLM_PROVIDER] = trace_info.message_data.model_provider
+
+            if trace_info.message_data and trace_info.message_data.message_metadata:
+                metadata_dict = json.loads(trace_info.message_data.message_metadata)
+                if model_params := metadata_dict.get("model_parameters"):
+                    llm_attributes[SpanAttributes.LLM_INVOCATION_PARAMETERS] = json.dumps(model_params)
+
+            llm_span = self.tracer.start_span(
+                name="llm",
+                attributes=llm_attributes,
+                start_time=datetime_to_nanos(trace_info.start_time),
+                context=trace.set_span_in_context(trace.NonRecordingSpan(span_context)),
+            )
+
+            try:
+                if trace_info.error:
+                    llm_span.add_event(
+                        "exception",
+                        attributes={
+                            "exception.message": trace_info.error,
+                            "exception.type": "Error",
+                            "exception.stacktrace": trace_info.error,
+                        },
+                    )
+            finally:
+                llm_span.end(end_time=datetime_to_nanos(trace_info.end_time))
+        finally:
+            message_span.end(end_time=datetime_to_nanos(trace_info.end_time))
+
+    def moderation_trace(self, trace_info: ModerationTraceInfo):
+        if trace_info.message_data is None:
+            return
+
+        metadata = {
+            "message_id": trace_info.message_id,
+            "tool_name": "moderation",
+            "status": trace_info.message_data.status,
+            "status_message": trace_info.message_data.error or "",
+            "level": "ERROR" if trace_info.message_data.error else "DEFAULT",
+        }
+        metadata.update(trace_info.metadata)
+
+        trace_id = uuid_to_trace_id(trace_info.message_id)
+        span_id = RandomIdGenerator().generate_span_id()
+        context = SpanContext(
+            trace_id=trace_id,
+            span_id=span_id,
+            is_remote=False,
+            trace_flags=TraceFlags(TraceFlags.SAMPLED),
+            trace_state=TraceState(),
+        )
+
+        span = self.tracer.start_span(
+            name=TraceTaskName.MODERATION_TRACE.value,
+            attributes={
+                SpanAttributes.INPUT_VALUE: json.dumps(trace_info.inputs, ensure_ascii=False),
+                SpanAttributes.OUTPUT_VALUE: json.dumps(
+                    {
+                        "action": trace_info.action,
+                        "flagged": trace_info.flagged,
+                        "preset_response": trace_info.preset_response,
+                        "inputs": trace_info.inputs,
+                    },
+                    ensure_ascii=False,
+                ),
+                SpanAttributes.OPENINFERENCE_SPAN_KIND: OpenInferenceSpanKindValues.CHAIN.value,
+                SpanAttributes.METADATA: json.dumps(metadata, ensure_ascii=False),
+            },
+            start_time=datetime_to_nanos(trace_info.start_time),
+            context=trace.set_span_in_context(trace.NonRecordingSpan(context)),
+        )
+
+        try:
+            if trace_info.message_data.error:
+                span.add_event(
+                    "exception",
+                    attributes={
+                        "exception.message": trace_info.message_data.error,
+                        "exception.type": "Error",
+                        "exception.stacktrace": trace_info.message_data.error,
+                    },
+                )
+        finally:
+            span.end(end_time=datetime_to_nanos(trace_info.end_time))
+
+    def suggested_question_trace(self, trace_info: SuggestedQuestionTraceInfo):
+        if trace_info.message_data is None:
+            return
+
+        start_time = trace_info.start_time or trace_info.message_data.created_at
+        end_time = trace_info.end_time or trace_info.message_data.updated_at
+
+        metadata = {
+            "message_id": trace_info.message_id,
+            "tool_name": "suggested_question",
+            "status": trace_info.status,
+            "status_message": trace_info.error or "",
+            "level": "ERROR" if trace_info.error else "DEFAULT",
+            "total_tokens": trace_info.total_tokens,
+            "ls_provider": trace_info.model_provider or "",
+            "ls_model_name": trace_info.model_id or "",
+        }
+        metadata.update(trace_info.metadata)
+
+        trace_id = uuid_to_trace_id(trace_info.message_id)
+        span_id = RandomIdGenerator().generate_span_id()
+        context = SpanContext(
+            trace_id=trace_id,
+            span_id=span_id,
+            is_remote=False,
+            trace_flags=TraceFlags(TraceFlags.SAMPLED),
+            trace_state=TraceState(),
+        )
+
+        span = self.tracer.start_span(
+            name=TraceTaskName.SUGGESTED_QUESTION_TRACE.value,
+            attributes={
+                SpanAttributes.INPUT_VALUE: json.dumps(trace_info.inputs, ensure_ascii=False),
+                SpanAttributes.OUTPUT_VALUE: json.dumps(trace_info.suggested_question, ensure_ascii=False),
+                SpanAttributes.OPENINFERENCE_SPAN_KIND: OpenInferenceSpanKindValues.CHAIN.value,
+                SpanAttributes.METADATA: json.dumps(metadata, ensure_ascii=False),
+            },
+            start_time=datetime_to_nanos(start_time),
+            context=trace.set_span_in_context(trace.NonRecordingSpan(context)),
+        )
+
+        try:
+            if trace_info.error:
+                span.add_event(
+                    "exception",
+                    attributes={
+                        "exception.message": trace_info.error,
+                        "exception.type": "Error",
+                        "exception.stacktrace": trace_info.error,
+                    },
+                )
+        finally:
+            span.end(end_time=datetime_to_nanos(end_time))
+
+    def dataset_retrieval_trace(self, trace_info: DatasetRetrievalTraceInfo):
+        if trace_info.message_data is None:
+            return
+
+        start_time = trace_info.start_time or trace_info.message_data.created_at
+        end_time = trace_info.end_time or trace_info.message_data.updated_at
+
+        metadata = {
+            "message_id": trace_info.message_id,
+            "tool_name": "dataset_retrieval",
+            "status": trace_info.message_data.status,
+            "status_message": trace_info.message_data.error or "",
+            "level": "ERROR" if trace_info.message_data.error else "DEFAULT",
+            "ls_provider": trace_info.message_data.model_provider or "",
+            "ls_model_name": trace_info.message_data.model_id or "",
+        }
+        metadata.update(trace_info.metadata)
+
+        trace_id = uuid_to_trace_id(trace_info.message_id)
+        span_id = RandomIdGenerator().generate_span_id()
+        context = SpanContext(
+            trace_id=trace_id,
+            span_id=span_id,
+            is_remote=False,
+            trace_flags=TraceFlags(TraceFlags.SAMPLED),
+            trace_state=TraceState(),
+        )
+
+        span = self.tracer.start_span(
+            name=TraceTaskName.DATASET_RETRIEVAL_TRACE.value,
+            attributes={
+                SpanAttributes.INPUT_VALUE: json.dumps(trace_info.inputs, ensure_ascii=False),
+                SpanAttributes.OUTPUT_VALUE: json.dumps({"documents": trace_info.documents}, ensure_ascii=False),
+                SpanAttributes.OPENINFERENCE_SPAN_KIND: OpenInferenceSpanKindValues.RETRIEVER.value,
+                SpanAttributes.METADATA: json.dumps(metadata, ensure_ascii=False),
+                "start_time": start_time.isoformat() if start_time else "",
+                "end_time": end_time.isoformat() if end_time else "",
+            },
+            start_time=datetime_to_nanos(start_time),
+            context=trace.set_span_in_context(trace.NonRecordingSpan(context)),
+        )
+
+        try:
+            if trace_info.message_data.error:
+                span.add_event(
+                    "exception",
+                    attributes={
+                        "exception.message": trace_info.message_data.error,
+                        "exception.type": "Error",
+                        "exception.stacktrace": trace_info.message_data.error,
+                    },
+                )
+        finally:
+            span.end(end_time=datetime_to_nanos(end_time))
+
+    def tool_trace(self, trace_info: ToolTraceInfo):
+        if trace_info.message_data is None:
+            logger.warning("[Arize/Phoenix] Message data is None, skipping tool trace.")
+            return
+
+        metadata = {
+            "message_id": trace_info.message_id,
+            "tool_config": json.dumps(trace_info.tool_config, ensure_ascii=False),
+        }
+
+        trace_id = uuid_to_trace_id(trace_info.message_id)
+        tool_span_id = RandomIdGenerator().generate_span_id()
+        logger.info(f"[Arize/Phoenix] Creating tool trace with trace_id: {trace_id}, span_id: {tool_span_id}")
+
+        # Create span context with the same trace_id as the parent
+        # todo: Create with the appropriate parent span context, so that the tool span is
+        # a child of the appropriate span (e.g. message span)
+        span_context = SpanContext(
+            trace_id=trace_id,
+            span_id=tool_span_id,
+            is_remote=False,
+            trace_flags=TraceFlags(TraceFlags.SAMPLED),
+            trace_state=TraceState(),
+        )
+
+        tool_params_str = (
+            json.dumps(trace_info.tool_parameters, ensure_ascii=False)
+            if isinstance(trace_info.tool_parameters, dict)
+            else str(trace_info.tool_parameters)
+        )
+
+        span = self.tracer.start_span(
+            name=trace_info.tool_name,
+            attributes={
+                SpanAttributes.INPUT_VALUE: json.dumps(trace_info.tool_inputs, ensure_ascii=False),
+                SpanAttributes.OUTPUT_VALUE: trace_info.tool_outputs,
+                SpanAttributes.OPENINFERENCE_SPAN_KIND: OpenInferenceSpanKindValues.TOOL.value,
+                SpanAttributes.METADATA: json.dumps(metadata, ensure_ascii=False),
+                SpanAttributes.TOOL_NAME: trace_info.tool_name,
+                SpanAttributes.TOOL_PARAMETERS: tool_params_str,
+            },
+            start_time=datetime_to_nanos(trace_info.start_time),
+            context=trace.set_span_in_context(trace.NonRecordingSpan(span_context)),
+        )
+
+        try:
+            if trace_info.error:
+                span.add_event(
+                    "exception",
+                    attributes={
+                        "exception.message": trace_info.error,
+                        "exception.type": "Error",
+                        "exception.stacktrace": trace_info.error,
+                    },
+                )
+        finally:
+            span.end(end_time=datetime_to_nanos(trace_info.end_time))
+
+    def generate_name_trace(self, trace_info: GenerateNameTraceInfo):
+        if trace_info.message_data is None:
+            return
+
+        metadata = {
+            "project_name": self.project,
+            "message_id": trace_info.message_id,
+            "status": trace_info.message_data.status,
+            "status_message": trace_info.message_data.error or "",
+            "level": "ERROR" if trace_info.message_data.error else "DEFAULT",
+        }
+        metadata.update(trace_info.metadata)
+
+        trace_id = uuid_to_trace_id(trace_info.message_id)
+        span_id = RandomIdGenerator().generate_span_id()
+        context = SpanContext(
+            trace_id=trace_id,
+            span_id=span_id,
+            is_remote=False,
+            trace_flags=TraceFlags(TraceFlags.SAMPLED),
+            trace_state=TraceState(),
+        )
+
+        span = self.tracer.start_span(
+            name=TraceTaskName.GENERATE_NAME_TRACE.value,
+            attributes={
+                SpanAttributes.INPUT_VALUE: json.dumps(trace_info.inputs, ensure_ascii=False),
+                SpanAttributes.OUTPUT_VALUE: json.dumps(trace_info.outputs, ensure_ascii=False),
+                SpanAttributes.OPENINFERENCE_SPAN_KIND: OpenInferenceSpanKindValues.CHAIN.value,
+                SpanAttributes.METADATA: json.dumps(metadata, ensure_ascii=False),
+                SpanAttributes.SESSION_ID: trace_info.message_data.conversation_id,
+                "start_time": trace_info.start_time.isoformat() if trace_info.start_time else "",
+                "end_time": trace_info.end_time.isoformat() if trace_info.end_time else "",
+            },
+            start_time=datetime_to_nanos(trace_info.start_time),
+            context=trace.set_span_in_context(trace.NonRecordingSpan(context)),
+        )
+
+        try:
+            if trace_info.message_data.error:
+                span.add_event(
+                    "exception",
+                    attributes={
+                        "exception.message": trace_info.message_data.error,
+                        "exception.type": "Error",
+                        "exception.stacktrace": trace_info.message_data.error,
+                    },
+                )
+        finally:
+            span.end(end_time=datetime_to_nanos(trace_info.end_time))
+
+    def api_check(self):
+        try:
+            with self.tracer.start_span("api_check") as span:
+                span.set_attribute("test", "true")
+            return True
+        except Exception as e:
+            logger.info(f"[Arize/Phoenix] API check failed: {str(e)}", exc_info=True)
+            raise ValueError(f"[Arize/Phoenix] API check failed: {str(e)}")
+
+    def get_project_url(self):
+        try:
+            if self.arize_phoenix_config.endpoint == "https://otlp.arize.com":
+                return "https://app.arize.com/"
+            else:
+                return f"{self.arize_phoenix_config.endpoint}/projects/"
+        except Exception as e:
+            logger.info(f"[Arize/Phoenix] Get run url failed: {str(e)}", exc_info=True)
+            raise ValueError(f"[Arize/Phoenix] Get run url failed: {str(e)}")
+
+    def _get_workflow_nodes(self, workflow_run_id: str):
+        """Helper method to get workflow nodes"""
+        workflow_nodes = (
+            db.session.query(
+                WorkflowNodeExecutionModel.id,
+                WorkflowNodeExecutionModel.tenant_id,
+                WorkflowNodeExecutionModel.app_id,
+                WorkflowNodeExecutionModel.title,
+                WorkflowNodeExecutionModel.node_type,
+                WorkflowNodeExecutionModel.status,
+                WorkflowNodeExecutionModel.inputs,
+                WorkflowNodeExecutionModel.outputs,
+                WorkflowNodeExecutionModel.created_at,
+                WorkflowNodeExecutionModel.elapsed_time,
+                WorkflowNodeExecutionModel.process_data,
+                WorkflowNodeExecutionModel.execution_metadata,
+            )
+            .filter(WorkflowNodeExecutionModel.workflow_run_id == workflow_run_id)
+            .all()
+        )
+        return workflow_nodes

api/core/ops/entities/config_entity.py

@@ -4,6 +4,8 @@ from pydantic import BaseModel, ValidationInfo, field_validator
 
 
 class TracingProviderEnum(StrEnum):
+    ARIZE = "arize"
+    PHOENIX = "phoenix"
     LANGFUSE = "langfuse"
     LANGSMITH = "langsmith"
     OPIK = "opik"
@@ -18,6 +20,69 @@ class BaseTracingConfig(BaseModel):
     ...
 
 
+class ArizeConfig(BaseTracingConfig):
+    """
+    Model class for Arize tracing config.
+    """
+
+    api_key: str | None = None
+    space_id: str | None = None
+    project: str | None = None
+    endpoint: str = "https://otlp.arize.com"
+
+    @field_validator("project")
+    @classmethod
+    def project_validator(cls, v, info: ValidationInfo):
+        if v is None or v == "":
+            v = "default"
+
+        return v
+
+    @field_validator("endpoint")
+    @classmethod
+    def endpoint_validator(cls, v, info: ValidationInfo):
+        if v is None or v == "":
+            v = "https://otlp.arize.com"
+        if not v.startswith(("https://", "http://")):
+            raise ValueError("endpoint must start with https:// or http://")
+        if "/" in v[8:]:
+            parts = v.split("/")
+            v = parts[0] + "//" + parts[2]
+
+        return v
+
+
+class PhoenixConfig(BaseTracingConfig):
+    """
+    Model class for Phoenix tracing config.
+    """
+
+    api_key: str | None = None
+    project: str | None = None
+    endpoint: str = "https://app.phoenix.arize.com"
+
+    @field_validator("project")
+    @classmethod
+    def project_validator(cls, v, info: ValidationInfo):
+        if v is None or v == "":
+            v = "default"
+
+        return v
+
+    @field_validator("endpoint")
+    @classmethod
+    def endpoint_validator(cls, v, info: ValidationInfo):
+        if v is None or v == "":
+            v = "https://app.phoenix.arize.com"
+        if not v.startswith(("https://", "http://")):
+            raise ValueError("endpoint must start with https:// or http://")
+        if "/" in v[8:]:
+            parts = v.split("/")
+            v = parts[0] + "//" + parts[2]
+
+        return v
+
+
 class LangfuseConfig(BaseTracingConfig):
     """
     Model class for Langfuse tracing config.

api/core/ops/langfuse_trace/langfuse_trace.py

@@ -32,6 +32,7 @@ from core.repositories import SQLAlchemyWorkflowNodeExecutionRepository
 from core.workflow.nodes.enums import NodeType
 from extensions.ext_database import db
 from models import EndUser, WorkflowNodeExecutionTriggeredFrom
+from models.enums import MessageStatus
 
 logger = logging.getLogger(__name__)
 
@@ -83,6 +84,7 @@ class LangFuseDataTrace(BaseTraceInstance):
                 metadata=metadata,
                 session_id=trace_info.conversation_id,
                 tags=["message", "workflow"],
+                version=trace_info.workflow_run_version,
             )
             self.add_trace(langfuse_trace_data=trace_data)
             workflow_span_data = LangfuseSpan(
@@ -108,6 +110,7 @@ class LangFuseDataTrace(BaseTraceInstance):
                 metadata=metadata,
                 session_id=trace_info.conversation_id,
                 tags=["workflow"],
+                version=trace_info.workflow_run_version,
             )
             self.add_trace(langfuse_trace_data=trace_data)
 
@@ -172,37 +175,7 @@ class LangFuseDataTrace(BaseTraceInstance):
                     }
                 )
 
-            # add span
-            if trace_info.message_id:
-                span_data = LangfuseSpan(
-                    id=node_execution_id,
-                    name=node_type,
-                    input=inputs,
-                    output=outputs,
-                    trace_id=trace_id,
-                    start_time=created_at,
-                    end_time=finished_at,
-                    metadata=metadata,
-                    level=(LevelEnum.DEFAULT if status == "succeeded" else LevelEnum.ERROR),
-                    status_message=trace_info.error or "",
-                    parent_observation_id=trace_info.workflow_run_id,
-                )
-            else:
-                span_data = LangfuseSpan(
-                    id=node_execution_id,
-                    name=node_type,
-                    input=inputs,
-                    output=outputs,
-                    trace_id=trace_id,
-                    start_time=created_at,
-                    end_time=finished_at,
-                    metadata=metadata,
-                    level=(LevelEnum.DEFAULT if status == "succeeded" else LevelEnum.ERROR),
-                    status_message=trace_info.error or "",
-                )
-
-            self.add_span(langfuse_span_data=span_data)
-
+            # add generation span
             if process_data and process_data.get("model_mode") == "chat":
                 total_token = metadata.get("total_tokens", 0)
                 prompt_tokens = 0
@@ -226,10 +199,10 @@ class LangFuseDataTrace(BaseTraceInstance):
                 )
 
                 node_generation_data = LangfuseGeneration(
-                    name="llm",
+                    id=node_execution_id,
+                    name=node_name,
                     trace_id=trace_id,
                     model=process_data.get("model_name"),
-                    parent_observation_id=node_execution_id,
                     start_time=created_at,
                     end_time=finished_at,
                     input=inputs,
@@ -237,11 +210,30 @@ class LangFuseDataTrace(BaseTraceInstance):
                     metadata=metadata,
                     level=(LevelEnum.DEFAULT if status == "succeeded" else LevelEnum.ERROR),
                     status_message=trace_info.error or "",
+                    parent_observation_id=trace_info.workflow_run_id if trace_info.message_id else None,
                     usage=generation_usage,
                 )
 
                 self.add_generation(langfuse_generation_data=node_generation_data)
 
+            # add normal span
+            else:
+                span_data = LangfuseSpan(
+                    id=node_execution_id,
+                    name=node_name,
+                    input=inputs,
+                    output=outputs,
+                    trace_id=trace_id,
+                    start_time=created_at,
+                    end_time=finished_at,
+                    metadata=metadata,
+                    level=(LevelEnum.DEFAULT if status == "succeeded" else LevelEnum.ERROR),
+                    status_message=trace_info.error or "",
+                    parent_observation_id=trace_info.workflow_run_id if trace_info.message_id else None,
+                )
+
+                self.add_span(langfuse_span_data=span_data)
+
     def message_trace(self, trace_info: MessageTraceInfo, **kwargs):
         # get message file data
         file_list = trace_info.file_list
@@ -284,7 +276,7 @@ class LangFuseDataTrace(BaseTraceInstance):
         )
         self.add_trace(langfuse_trace_data=trace_data)
 
-        # start add span
+        # add generation
         generation_usage = GenerationUsage(
             input=trace_info.message_tokens,
             output=trace_info.answer_tokens,
@@ -302,7 +294,7 @@ class LangFuseDataTrace(BaseTraceInstance):
             input=trace_info.inputs,
             output=message_data.answer,
             metadata=metadata,
-            level=(LevelEnum.DEFAULT if message_data.status != "error" else LevelEnum.ERROR),
+            level=(LevelEnum.DEFAULT if message_data.status != MessageStatus.ERROR else LevelEnum.ERROR),
             status_message=message_data.error or "",
             usage=generation_usage,
         )
@@ -348,7 +340,7 @@ class LangFuseDataTrace(BaseTraceInstance):
             start_time=trace_info.start_time,
             end_time=trace_info.end_time,
             metadata=trace_info.metadata,
-            level=(LevelEnum.DEFAULT if message_data.status != "error" else LevelEnum.ERROR),
+            level=(LevelEnum.DEFAULT if message_data.status != MessageStatus.ERROR else LevelEnum.ERROR),
             status_message=message_data.error or "",
             usage=generation_usage,
         )

api/core/ops/ops_trace_manager.py

@@ -41,6 +41,28 @@ from tasks.ops_trace_task import process_trace_tasks
 class OpsTraceProviderConfigMap(dict[str, dict[str, Any]]):
     def __getitem__(self, provider: str) -> dict[str, Any]:
         match provider:
+            case TracingProviderEnum.ARIZE:
+                from core.ops.arize_phoenix_trace.arize_phoenix_trace import ArizePhoenixDataTrace
+                from core.ops.entities.config_entity import ArizeConfig
+
+                return {
+                    "config_class": ArizeConfig,
+                    "secret_keys": ["api_key", "space_id"],
+                    "other_keys": ["project", "endpoint"],
+                    "trace_instance": ArizePhoenixDataTrace,
+                }
+
+            case TracingProviderEnum.PHOENIX:
+                from core.ops.arize_phoenix_trace.arize_phoenix_trace import ArizePhoenixDataTrace
+                from core.ops.entities.config_entity import PhoenixConfig
+
+                return {
+                    "config_class": PhoenixConfig,
+                    "secret_keys": ["api_key"],
+                    "other_keys": ["project", "endpoint"],
+                    "trace_instance": ArizePhoenixDataTrace,
+                }
+
             case TracingProviderEnum.LANGFUSE:
                 from core.ops.entities.config_entity import LangfuseConfig
                 from core.ops.langfuse_trace.langfuse_trace import LangFuseDataTrace
@@ -84,7 +106,26 @@ class OpsTraceProviderConfigMap(dict[str, dict[str, Any]]):
                     "other_keys": ["project", "entity", "endpoint", "host"],
                     "trace_instance": WeaveDataTrace,
                 }
+            case TracingProviderEnum.ARIZE:
+                from core.ops.arize_phoenix_trace.arize_phoenix_trace import ArizePhoenixDataTrace
+                from core.ops.entities.config_entity import ArizeConfig
 
+                return {
+                    "config_class": ArizeConfig,
+                    "secret_keys": ["api_key", "space_id"],
+                    "other_keys": ["project", "endpoint"],
+                    "trace_instance": ArizePhoenixDataTrace,
+                }
+            case TracingProviderEnum.PHOENIX:
+                from core.ops.arize_phoenix_trace.arize_phoenix_trace import ArizePhoenixDataTrace
+                from core.ops.entities.config_entity import PhoenixConfig
+
+                return {
+                    "config_class": PhoenixConfig,
+                    "secret_keys": ["api_key"],
+                    "other_keys": ["project", "endpoint"],
+                    "trace_instance": ArizePhoenixDataTrace,
+                }
             case _:
                 raise KeyError(f"Unsupported tracing provider: {provider}")
 

api/core/plugin/impl/dynamic_select.py

@@ -42,4 +42,4 @@ class DynamicSelectClient(BasePluginClient):
         for options in response:
             return options
 
-        raise ValueError("Plugin service returned no options")
+        raise ValueError(f"Plugin service returned no options for parameter '{parameter}' in provider '{provider}'")

api/core/rag/extractor/helpers.py

@@ -1,7 +1,6 @@
 """Document loader helpers."""
 
 import concurrent.futures
-from pathlib import Path
 from typing import NamedTuple, Optional, cast
 
 
@@ -16,7 +15,7 @@ class FileEncoding(NamedTuple):
     """The language of the file."""
 
 
-def detect_file_encodings(file_path: str, timeout: int = 5) -> list[FileEncoding]:
+def detect_file_encodings(file_path: str, timeout: int = 5, sample_size: int = 1024 * 1024) -> list[FileEncoding]:
     """Try to detect the file encoding.
 
     Returns a list of `FileEncoding` tuples with the detected encodings ordered
@@ -25,11 +24,16 @@ def detect_file_encodings(file_path: str, timeout: int = 5) -> list[FileEncoding
     Args:
         file_path: The path to the file to detect the encoding for.
         timeout: The timeout in seconds for the encoding detection.
+        sample_size: The number of bytes to read for encoding detection. Default is 1MB.
+                    For large files, reading only a sample is sufficient and prevents timeout.
     """
     import chardet
 
     def read_and_detect(file_path: str) -> list[dict]:
-        rawdata = Path(file_path).read_bytes()
+        with open(file_path, "rb") as f:
+            # Read only a sample of the file for encoding detection
+            # This prevents timeout on large files while still providing accurate encoding detection
+            rawdata = f.read(sample_size)
         return cast(list[dict], chardet.detect_all(rawdata))
 
     with concurrent.futures.ThreadPoolExecutor() as executor:

api/core/rag/extractor/text_extractor.py

@@ -36,8 +36,12 @@ class TextExtractor(BaseExtractor):
                         break
                     except UnicodeDecodeError:
                         continue
+                else:
+                    raise RuntimeError(
+                        f"Decode failed: {self._file_path}, all detected encodings failed. Original error: {e}"
+                    )
             else:
-                raise RuntimeError(f"Error loading {self._file_path}") from e
+                raise RuntimeError(f"Decode failed: {self._file_path}, specified encoding failed. Original error: {e}")
         except Exception as e:
             raise RuntimeError(f"Error loading {self._file_path}") from e
 

api/core/rag/retrieval/dataset_retrieval.py

@@ -1010,6 +1010,9 @@ class DatasetRetrieval:
     def _process_metadata_filter_func(
         self, sequence: int, condition: str, metadata_name: str, value: Optional[Any], filters: list
     ):
+        if value is None:
+            return
+
         key = f"{metadata_name}_{sequence}"
         key_value = f"{metadata_name}_{sequence}_value"
         match condition:

api/core/tools/builtin_tool/providers/audio/tools/tts.py

@@ -31,6 +31,14 @@ class TTSTool(BuiltinTool):
             model_type=ModelType.TTS,
             model=model,
         )
+        if not voice:
+            voices = model_instance.get_tts_voices()
+            if voices:
+                voice = voices[0].get("value")
+                if not voice:
+                    raise ValueError("Sorry, no voice available.")
+            else:
+                raise ValueError("Sorry, no voice available.")
         tts = model_instance.invoke_tts(
             content_text=tool_parameters.get("text"),  # type: ignore
             user=user_id,

api/core/tools/builtin_tool/providers/code/tools/simple_code.py

@@ -4,6 +4,7 @@ from typing import Any, Optional
 from core.helper.code_executor.code_executor import CodeExecutor, CodeLanguage
 from core.tools.builtin_tool.tool import BuiltinTool
 from core.tools.entities.tool_entities import ToolInvokeMessage
+from core.tools.errors import ToolInvokeError
 
 
 class SimpleCode(BuiltinTool):
@@ -25,6 +26,8 @@ class SimpleCode(BuiltinTool):
         if language not in {CodeLanguage.PYTHON3, CodeLanguage.JAVASCRIPT}:
             raise ValueError(f"Only python3 and javascript are supported, not {language}")
 
-        result = CodeExecutor.execute_code(language, "", code)
-
-        yield self.create_text_message(result)
+        try:
+            result = CodeExecutor.execute_code(language, "", code)
+            yield self.create_text_message(result)
+        except Exception as e:
+            raise ToolInvokeError(str(e))

api/core/workflow/entities/workflow_node_execution.py

@@ -66,11 +66,21 @@ class WorkflowNodeExecution(BaseModel):
     but they are not stored in the model.
     """
 
-    # Core identification fields
-    id: str  # Unique identifier for this execution record
-    node_execution_id: Optional[str] = None  # Optional secondary ID for cross-referencing
+    # --------- Core identification fields ---------
+
+    # Unique identifier for this execution record, used when persisting to storage.
+    # Value is a UUID string (e.g., '09b3e04c-f9ae-404c-ad82-290b8d7bd382').
+    id: str
+
+    # Optional secondary ID for cross-referencing purposes.
+    #
+    # NOTE: For referencing the persisted record, use `id` rather than `node_execution_id`.
+    # While `node_execution_id` may sometimes be a UUID string, this is not guaranteed.
+    # In most scenarios, `id` should be used as the primary identifier.
+    node_execution_id: Optional[str] = None
     workflow_id: str  # ID of the workflow this node belongs to
     workflow_execution_id: Optional[str] = None  # ID of the specific workflow run (null for single-step debugging)
+    # --------- Core identification fields ends ---------
 
     # Execution positioning and flow
     index: int  # Sequence number for ordering in trace visualization

api/core/workflow/nodes/agent/agent_node.py

@@ -158,7 +158,10 @@ class AgentNode(ToolNode):
                 # variable_pool.convert_template expects a string template,
                 # but if passing a dict, convert to JSON string first before rendering
                 try:
-                    parameter_value = json.dumps(agent_input.value, ensure_ascii=False)
+                    if not isinstance(agent_input.value, str):
+                        parameter_value = json.dumps(agent_input.value, ensure_ascii=False)
+                    else:
+                        parameter_value = str(agent_input.value)
                 except TypeError:
                     parameter_value = str(agent_input.value)
                 segment_group = variable_pool.convert_template(parameter_value)
@@ -166,7 +169,8 @@ class AgentNode(ToolNode):
                 # variable_pool.convert_template returns a string,
                 # so we need to convert it back to a dictionary
                 try:
-                    parameter_value = json.loads(parameter_value)
+                    if not isinstance(agent_input.value, str):
+                        parameter_value = json.loads(parameter_value)
                 except json.JSONDecodeError:
                     parameter_value = parameter_value
             else:

api/core/workflow/nodes/answer/answer_stream_processor.py

@@ -2,7 +2,6 @@ import logging
 from collections.abc import Generator
 from typing import cast
 
-from core.file import FILE_MODEL_IDENTITY, File
 from core.workflow.entities.variable_pool import VariablePool
 from core.workflow.graph_engine.entities.event import (
     GraphEngineEvent,
@@ -201,44 +200,3 @@ class AnswerStreamProcessor(StreamProcessor):
                 stream_out_answer_node_ids.append(answer_node_id)
 
         return stream_out_answer_node_ids
-
-    @classmethod
-    def _fetch_files_from_variable_value(cls, value: dict | list) -> list[dict]:
-        """
-        Fetch files from variable value
-        :param value: variable value
-        :return:
-        """
-        if not value:
-            return []
-
-        files = []
-        if isinstance(value, list):
-            for item in value:
-                file_var = cls._get_file_var_from_value(item)
-                if file_var:
-                    files.append(file_var)
-        elif isinstance(value, dict):
-            file_var = cls._get_file_var_from_value(value)
-            if file_var:
-                files.append(file_var)
-
-        return files
-
-    @classmethod
-    def _get_file_var_from_value(cls, value: dict | list):
-        """
-        Get file var from value
-        :param value: variable value
-        :return:
-        """
-        if not value:
-            return None
-
-        if isinstance(value, dict):
-            if "dify_model_identity" in value and value["dify_model_identity"] == FILE_MODEL_IDENTITY:
-                return value
-        elif isinstance(value, File):
-            return value.to_dict()
-
-        return None

api/core/workflow/nodes/http_request/executor.py

@@ -333,7 +333,7 @@ class Executor:
         try:
             response = getattr(ssrf_proxy, self.method.lower())(**request_args)
         except (ssrf_proxy.MaxRetriesExceededError, httpx.RequestError) as e:
-            raise HttpRequestNodeError(str(e))
+            raise HttpRequestNodeError(str(e)) from e
         # FIXME: fix type ignore, this maybe httpx type issue
         return response  # type: ignore
 

api/core/workflow/nodes/knowledge_retrieval/knowledge_retrieval_node.py

@@ -490,6 +490,9 @@ class KnowledgeRetrievalNode(LLMNode):
     def _process_metadata_filter_func(
         self, sequence: int, condition: str, metadata_name: str, value: Optional[Any], filters: list
     ):
+        if value is None:
+            return
+
         key = f"{metadata_name}_{sequence}"
         key_value = f"{metadata_name}_{sequence}_value"
         match condition:

api/core/workflow/nodes/tool/tool_node.py

@@ -6,6 +6,7 @@ from sqlalchemy.orm import Session
 
 from core.callback_handler.workflow_tool_callback_handler import DifyWorkflowCallbackHandler
 from core.file import File, FileTransferMethod
+from core.model_runtime.entities.llm_entities import LLMUsage
 from core.plugin.impl.exc import PluginDaemonClientSideError
 from core.plugin.impl.plugin import PluginInstaller
 from core.tools.entities.tool_entities import ToolInvokeMessage, ToolParameter
@@ -167,7 +168,9 @@ class ToolNode(BaseNode[ToolNodeData]):
             if tool_input.type == "variable":
                 variable = variable_pool.get(tool_input.value)
                 if variable is None:
-                    raise ToolParameterError(f"Variable {tool_input.value} does not exist")
+                    if parameter.required:
+                        raise ToolParameterError(f"Variable {tool_input.value} does not exist")
+                    continue
                 parameter_value = variable.value
             elif tool_input.type in {"mixed", "constant"}:
                 segment_group = variable_pool.convert_template(str(tool_input.value))
@@ -206,7 +209,7 @@ class ToolNode(BaseNode[ToolNodeData]):
 
         agent_logs: list[AgentLogEvent] = []
         agent_execution_metadata: Mapping[WorkflowNodeExecutionMetadataKey, Any] = {}
-
+        llm_usage: LLMUsage | None = None
         variables: dict[str, Any] = {}
 
         for message in message_stream:
@@ -274,9 +277,10 @@ class ToolNode(BaseNode[ToolNodeData]):
             elif message.type == ToolInvokeMessage.MessageType.JSON:
                 assert isinstance(message.message, ToolInvokeMessage.JsonMessage)
                 if self.node_type == NodeType.AGENT:
-                    msg_metadata = message.message.json_object.pop("execution_metadata", {})
+                    msg_metadata: dict[str, Any] = message.message.json_object.pop("execution_metadata", {})
+                    llm_usage = LLMUsage.from_metadata(msg_metadata)
                     agent_execution_metadata = {
-                        key: value
+                        WorkflowNodeExecutionMetadataKey(key): value
                         for key, value in msg_metadata.items()
                         if key in WorkflowNodeExecutionMetadataKey.__members__.values()
                     }
@@ -375,6 +379,7 @@ class ToolNode(BaseNode[ToolNodeData]):
                     WorkflowNodeExecutionMetadataKey.AGENT_LOG: agent_logs,
                 },
                 inputs=parameters_for_log,
+                llm_usage=llm_usage,
             )
         )
 

api/core/workflow/repositories/draft_variable_repository.py

@@ -0,0 +1,32 @@
+import abc
+from collections.abc import Mapping
+from typing import Any, Protocol
+
+from sqlalchemy.orm import Session
+
+from core.workflow.nodes.enums import NodeType
+
+
+class DraftVariableSaver(Protocol):
+    @abc.abstractmethod
+    def save(self, process_data: Mapping[str, Any] | None, outputs: Mapping[str, Any] | None):
+        pass
+
+
+class DraftVariableSaverFactory(Protocol):
+    @abc.abstractmethod
+    def __call__(
+        self,
+        session: Session,
+        app_id: str,
+        node_id: str,
+        node_type: NodeType,
+        node_execution_id: str,
+        enclosing_node_id: str | None = None,
+    ) -> "DraftVariableSaver":
+        pass
+
+
+class NoopDraftVariableSaver(DraftVariableSaver):
+    def save(self, process_data: Mapping[str, Any] | None, outputs: Mapping[str, Any] | None):
+        pass

api/core/workflow/workflow_cycle_manager.py

@@ -27,6 +27,7 @@ from core.workflow.enums import SystemVariableKey
 from core.workflow.repositories.workflow_execution_repository import WorkflowExecutionRepository
 from core.workflow.repositories.workflow_node_execution_repository import WorkflowNodeExecutionRepository
 from core.workflow.workflow_entry import WorkflowEntry
+from libs.datetime_utils import naive_utc_now
 
 
 @dataclass
@@ -160,12 +161,13 @@ class WorkflowCycleManager:
         exceptions_count: int = 0,
     ) -> WorkflowExecution:
         workflow_execution = self._get_workflow_execution_or_raise_error(workflow_run_id)
+        now = naive_utc_now()
 
         workflow_execution.status = WorkflowExecutionStatus(status.value)
         workflow_execution.error_message = error_message
         workflow_execution.total_tokens = total_tokens
         workflow_execution.total_steps = total_steps
-        workflow_execution.finished_at = datetime.now(UTC).replace(tzinfo=None)
+        workflow_execution.finished_at = now
         workflow_execution.exceptions_count = exceptions_count
 
         # Use the instance repository to find running executions for a workflow run
@@ -174,7 +176,6 @@ class WorkflowCycleManager:
         )
 
         # Update the domain models
-        now = datetime.now(UTC).replace(tzinfo=None)
         for node_execution in running_node_executions:
             if node_execution.node_execution_id:
                 # Update the domain model

api/extensions/ext_app_metrics.py

@@ -12,14 +12,14 @@ def init_app(app: DifyApp):
     @app.after_request
     def after_request(response):
         """Add Version headers to the response."""
-        response.headers.add("X-Version", dify_config.CURRENT_VERSION)
+        response.headers.add("X-Version", dify_config.project.version)
         response.headers.add("X-Env", dify_config.DEPLOY_ENV)
         return response
 
     @app.route("/health")
     def health():
         return Response(
-            json.dumps({"pid": os.getpid(), "status": "ok", "version": dify_config.CURRENT_VERSION}),
+            json.dumps({"pid": os.getpid(), "status": "ok", "version": dify_config.project.version}),
             status=200,
             content_type="application/json",
         )

api/extensions/ext_otel.py

@@ -49,7 +49,7 @@ def init_app(app: DifyApp):
         logging.getLogger().addHandler(exception_handler)
 
     def init_flask_instrumentor(app: DifyApp):
-        meter = get_meter("http_metrics", version=dify_config.CURRENT_VERSION)
+        meter = get_meter("http_metrics", version=dify_config.project.version)
         _http_response_counter = meter.create_counter(
             "http.server.response.count",
             description="Total number of HTTP responses by status code, method and target",
@@ -163,7 +163,7 @@ def init_app(app: DifyApp):
     resource = Resource(
         attributes={
             ResourceAttributes.SERVICE_NAME: dify_config.APPLICATION_NAME,
-            ResourceAttributes.SERVICE_VERSION: f"dify-{dify_config.CURRENT_VERSION}-{dify_config.COMMIT_SHA}",
+            ResourceAttributes.SERVICE_VERSION: f"dify-{dify_config.project.version}-{dify_config.COMMIT_SHA}",
             ResourceAttributes.PROCESS_PID: os.getpid(),
             ResourceAttributes.DEPLOYMENT_ENVIRONMENT: f"{dify_config.DEPLOY_ENV}-{dify_config.EDITION}",
             ResourceAttributes.HOST_NAME: socket.gethostname(),

api/extensions/ext_sentry.py

@@ -35,6 +35,6 @@ def init_app(app: DifyApp):
             traces_sample_rate=dify_config.SENTRY_TRACES_SAMPLE_RATE,
             profiles_sample_rate=dify_config.SENTRY_PROFILES_SAMPLE_RATE,
             environment=dify_config.DEPLOY_ENV,
-            release=f"dify-{dify_config.CURRENT_VERSION}-{dify_config.COMMIT_SHA}",
+            release=f"dify-{dify_config.project.version}-{dify_config.COMMIT_SHA}",
             before_send=before_send,
         )

api/libs/file_utils.py

@@ -0,0 +1,30 @@
+from pathlib import Path
+
+
+def search_file_upwards(
+    base_dir_path: Path,
+    target_file_name: str,
+    max_search_parent_depth: int,
+) -> Path:
+    """
+    Find a target file in the current directory or its parent directories up to a specified depth.
+    :param base_dir_path: Starting directory path to search from.
+    :param target_file_name: Name of the file to search for.
+    :param max_search_parent_depth: Maximum number of parent directories to search upwards.
+    :return: Path of the file if found, otherwise None.
+    """
+    current_path = base_dir_path.resolve()
+    for _ in range(max_search_parent_depth):
+        candidate_path = current_path / target_file_name
+        if candidate_path.is_file():
+            return candidate_path
+        parent_path = current_path.parent
+        if parent_path == current_path:  # reached the root directory
+            break
+        else:
+            current_path = parent_path
+
+    raise ValueError(
+        f"File '{target_file_name}' not found in the directory '{base_dir_path.resolve()}' or its parent directories"
+        f" in depth of {max_search_parent_depth}."
+    )

api/models/dataset.py

@@ -140,7 +140,7 @@ class Dataset(Base):
     def word_count(self):
         return (
             db.session.query(Document)
-            .with_entities(func.coalesce(func.sum(Document.word_count)))
+            .with_entities(func.coalesce(func.sum(Document.word_count), 0))
             .filter(Document.dataset_id == self.id)
             .scalar()
         )
@@ -448,7 +448,7 @@ class Document(Base):
     def hit_count(self):
         return (
             db.session.query(DocumentSegment)
-            .with_entities(func.coalesce(func.sum(DocumentSegment.hit_count)))
+            .with_entities(func.coalesce(func.sum(DocumentSegment.hit_count), 0))
             .filter(DocumentSegment.document_id == self.id)
             .scalar()
         )

api/models/enums.py

@@ -21,3 +21,12 @@ class DraftVariableType(StrEnum):
     NODE = "node"
     SYS = "sys"
     CONVERSATION = "conversation"
+
+
+class MessageStatus(StrEnum):
+    """
+    Message Status Enum
+    """
+
+    NORMAL = "normal"
+    ERROR = "error"

api/models/model.py

@@ -676,7 +676,7 @@ class Conversation(Base):
             if isinstance(value, dict) and value.get("dify_model_identity") == FILE_MODEL_IDENTITY:
                 if value["transfer_method"] == FileTransferMethod.TOOL_FILE:
                     value["tool_file_id"] = value["related_id"]
-                elif value["transfer_method"] == FileTransferMethod.LOCAL_FILE:
+                elif value["transfer_method"] in [FileTransferMethod.LOCAL_FILE, FileTransferMethod.REMOTE_URL]:
                     value["upload_file_id"] = value["related_id"]
                 inputs[key] = file_factory.build_from_mapping(mapping=value, tenant_id=value["tenant_id"])
             elif isinstance(value, list) and all(
@@ -686,7 +686,7 @@ class Conversation(Base):
                 for item in value:
                     if item["transfer_method"] == FileTransferMethod.TOOL_FILE:
                         item["tool_file_id"] = item["related_id"]
-                    elif item["transfer_method"] == FileTransferMethod.LOCAL_FILE:
+                    elif item["transfer_method"] in [FileTransferMethod.LOCAL_FILE, FileTransferMethod.REMOTE_URL]:
                         item["upload_file_id"] = item["related_id"]
                     inputs[key].append(file_factory.build_from_mapping(mapping=item, tenant_id=item["tenant_id"]))
 
@@ -946,7 +946,7 @@ class Message(Base):
             if isinstance(value, dict) and value.get("dify_model_identity") == FILE_MODEL_IDENTITY:
                 if value["transfer_method"] == FileTransferMethod.TOOL_FILE:
                     value["tool_file_id"] = value["related_id"]
-                elif value["transfer_method"] == FileTransferMethod.LOCAL_FILE:
+                elif value["transfer_method"] in [FileTransferMethod.LOCAL_FILE, FileTransferMethod.REMOTE_URL]:
                     value["upload_file_id"] = value["related_id"]
                 inputs[key] = file_factory.build_from_mapping(mapping=value, tenant_id=value["tenant_id"])
             elif isinstance(value, list) and all(
@@ -956,7 +956,7 @@ class Message(Base):
                 for item in value:
                     if item["transfer_method"] == FileTransferMethod.TOOL_FILE:
                         item["tool_file_id"] = item["related_id"]
-                    elif item["transfer_method"] == FileTransferMethod.LOCAL_FILE:
+                    elif item["transfer_method"] in [FileTransferMethod.LOCAL_FILE, FileTransferMethod.REMOTE_URL]:
                         item["upload_file_id"] = item["related_id"]
                     inputs[key].append(file_factory.build_from_mapping(mapping=item, tenant_id=item["tenant_id"]))
         return inputs

api/pyproject.toml

@@ -1,9 +1,10 @@
 [project]
 name = "dify-api"
-dynamic = ["version"]
+version = "1.5.1"
 requires-python = ">=3.11,<3.13"
 
 dependencies = [
+    "arize-phoenix-otel~=0.9.2",
     "authlib==1.3.1",
     "azure-identity==1.16.1",
     "beautifulsoup4==4.12.2",

api/services/account_service.py

@@ -889,7 +889,7 @@ class RegisterService:
 
             TenantService.create_owner_tenant_if_not_exist(account=account, is_setup=True)
 
-            dify_setup = DifySetup(version=dify_config.CURRENT_VERSION)
+            dify_setup = DifySetup(version=dify_config.project.version)
             db.session.add(dify_setup)
             db.session.commit()
         except Exception as e:

api/services/audio_service.py

@@ -1,13 +1,17 @@
 import io
 import logging
 import uuid
+from collections.abc import Generator
 from typing import Optional
 
+from flask import Response, stream_with_context
 from werkzeug.datastructures import FileStorage
 
 from constants import AUDIO_EXTENSIONS
 from core.model_manager import ModelManager
 from core.model_runtime.entities.model_entities import ModelType
+from extensions.ext_database import db
+from models.enums import MessageStatus
 from models.model import App, AppMode, AppModelConfig, Message
 from services.errors.audio import (
     AudioTooLargeServiceError,
@@ -16,6 +20,7 @@ from services.errors.audio import (
     ProviderNotSupportTextToSpeechServiceError,
     UnsupportedAudioTypeServiceError,
 )
+from services.workflow_service import WorkflowService
 
 FILE_SIZE = 30
 FILE_SIZE_LIMIT = FILE_SIZE * 1024 * 1024
@@ -74,35 +79,36 @@ class AudioService:
         voice: Optional[str] = None,
         end_user: Optional[str] = None,
         message_id: Optional[str] = None,
+        is_draft: bool = False,
     ):
-        from collections.abc import Generator
-
-        from flask import Response, stream_with_context
-
         from app import app
-        from extensions.ext_database import db
 
-        def invoke_tts(text_content: str, app_model: App, voice: Optional[str] = None):
+        def invoke_tts(text_content: str, app_model: App, voice: Optional[str] = None, is_draft: bool = False):
             with app.app_context():
-                if app_model.mode in {AppMode.ADVANCED_CHAT.value, AppMode.WORKFLOW.value}:
-                    workflow = app_model.workflow
-                    if workflow is None:
-                        raise ValueError("TTS is not enabled")
+                if voice is None:
+                    if app_model.mode in {AppMode.ADVANCED_CHAT.value, AppMode.WORKFLOW.value}:
+                        if is_draft:
+                            workflow = WorkflowService().get_draft_workflow(app_model=app_model)
+                        else:
+                            workflow = app_model.workflow
+                        if (
+                            workflow is None
+                            or "text_to_speech" not in workflow.features_dict
+                            or not workflow.features_dict["text_to_speech"].get("enabled")
+                        ):
+                            raise ValueError("TTS is not enabled")
 
-                    features_dict = workflow.features_dict
-                    if "text_to_speech" not in features_dict or not features_dict["text_to_speech"].get("enabled"):
-                        raise ValueError("TTS is not enabled")
+                        voice = workflow.features_dict["text_to_speech"].get("voice")
+                    else:
+                        if not is_draft:
+                            if app_model.app_model_config is None:
+                                raise ValueError("AppModelConfig not found")
+                            text_to_speech_dict = app_model.app_model_config.text_to_speech_dict
 
-                    voice = features_dict["text_to_speech"].get("voice") if voice is None else voice
-                else:
-                    if app_model.app_model_config is None:
-                        raise ValueError("AppModelConfig not found")
-                    text_to_speech_dict = app_model.app_model_config.text_to_speech_dict
+                            if not text_to_speech_dict.get("enabled"):
+                                raise ValueError("TTS is not enabled")
 
-                    if not text_to_speech_dict.get("enabled"):
-                        raise ValueError("TTS is not enabled")
-
-                    voice = text_to_speech_dict.get("voice") if voice is None else voice
+                            voice = text_to_speech_dict.get("voice")
 
                 model_manager = ModelManager()
                 model_instance = model_manager.get_default_model_instance(
@@ -132,18 +138,18 @@ class AudioService:
             message = db.session.query(Message).filter(Message.id == message_id).first()
             if message is None:
                 return None
-            if message.answer == "" and message.status == "normal":
+            if message.answer == "" and message.status == MessageStatus.NORMAL:
                 return None
 
             else:
-                response = invoke_tts(message.answer, app_model=app_model, voice=voice)
+                response = invoke_tts(text_content=message.answer, app_model=app_model, voice=voice, is_draft=is_draft)
                 if isinstance(response, Generator):
                     return Response(stream_with_context(response), content_type="audio/mpeg")
                 return response
         else:
             if text is None:
                 raise ValueError("Text is required")
-            response = invoke_tts(text, app_model, voice)
+            response = invoke_tts(text_content=text, app_model=app_model, voice=voice, is_draft=is_draft)
             if isinstance(response, Generator):
                 return Response(stream_with_context(response), content_type="audio/mpeg")
             return response

api/services/ops_service.py

@@ -34,6 +34,24 @@ class OpsService:
         )
         new_decrypt_tracing_config = OpsTraceManager.obfuscated_decrypt_token(tracing_provider, decrypt_tracing_config)
 
+        if tracing_provider == "arize" and (
+            "project_url" not in decrypt_tracing_config or not decrypt_tracing_config.get("project_url")
+        ):
+            try:
+                project_url = OpsTraceManager.get_trace_config_project_url(decrypt_tracing_config, tracing_provider)
+                new_decrypt_tracing_config.update({"project_url": project_url})
+            except Exception:
+                new_decrypt_tracing_config.update({"project_url": "https://app.arize.com/"})
+
+        if tracing_provider == "phoenix" and (
+            "project_url" not in decrypt_tracing_config or not decrypt_tracing_config.get("project_url")
+        ):
+            try:
+                project_url = OpsTraceManager.get_trace_config_project_url(decrypt_tracing_config, tracing_provider)
+                new_decrypt_tracing_config.update({"project_url": project_url})
+            except Exception:
+                new_decrypt_tracing_config.update({"project_url": "https://app.phoenix.arize.com/projects/"})
+
         if tracing_provider == "langfuse" and (
             "project_key" not in decrypt_tracing_config or not decrypt_tracing_config.get("project_key")
         ):
@@ -107,7 +125,9 @@ class OpsService:
             return {"error": "Invalid Credentials"}
 
         # get project url
-        if tracing_provider == "langfuse":
+        if tracing_provider in ("arize", "phoenix"):
+            project_url = OpsTraceManager.get_trace_config_project_url(tracing_config, tracing_provider)
+        elif tracing_provider == "langfuse":
             project_key = OpsTraceManager.get_trace_config_project_key(tracing_config, tracing_provider)
             project_url = "{host}/project/{key}".format(host=tracing_config.get("host"), key=project_key)
         elif tracing_provider in ("langsmith", "opik"):

api/services/workflow_draft_variable_service.py

@@ -154,7 +154,7 @@ class WorkflowDraftVariableService:
         variables = (
             # Do not load the `value` field.
             query.options(orm.defer(WorkflowDraftVariable.value))
-            .order_by(WorkflowDraftVariable.id.desc())
+            .order_by(WorkflowDraftVariable.created_at.desc())
             .limit(limit)
             .offset((page - 1) * limit)
             .all()
@@ -168,7 +168,7 @@ class WorkflowDraftVariableService:
             WorkflowDraftVariable.node_id == node_id,
         )
         query = self._session.query(WorkflowDraftVariable).filter(*criteria)
-        variables = query.order_by(WorkflowDraftVariable.id.desc()).all()
+        variables = query.order_by(WorkflowDraftVariable.created_at.desc()).all()
         return WorkflowDraftVariableList(variables=variables)
 
     def list_node_variables(self, app_id: str, node_id: str) -> WorkflowDraftVariableList:
@@ -235,7 +235,9 @@ class WorkflowDraftVariableService:
         self._session.flush()
         return variable
 
-    def _reset_node_var(self, workflow: Workflow, variable: WorkflowDraftVariable) -> WorkflowDraftVariable | None:
+    def _reset_node_var_or_sys_var(
+        self, workflow: Workflow, variable: WorkflowDraftVariable
+    ) -> WorkflowDraftVariable | None:
         # If a variable does not allow updating, it makes no sence to resetting it.
         if not variable.editable:
             return variable
@@ -259,28 +261,35 @@ class WorkflowDraftVariableService:
             self._session.flush()
             return None
 
-        # Get node type for proper value extraction
-        node_config = workflow.get_node_config_by_id(variable.node_id)
-        node_type = workflow.get_node_type_from_node_config(node_config)
-
         outputs_dict = node_exec.outputs_dict or {}
+        # a sentinel value used to check the absent of the output variable key.
+        absent = object()
 
-        # Note: Based on the implementation in `_build_from_variable_assigner_mapping`,
-        # VariableAssignerNode (both v1 and v2) can only create conversation draft variables.
-        # For consistency, we should simply return when processing VARIABLE_ASSIGNER nodes.
-        #
-        # This implementation must remain synchronized with the `_build_from_variable_assigner_mapping`
-        # and `save` methods.
-        if node_type == NodeType.VARIABLE_ASSIGNER:
-            return variable
+        if variable.get_variable_type() == DraftVariableType.NODE:
+            # Get node type for proper value extraction
+            node_config = workflow.get_node_config_by_id(variable.node_id)
+            node_type = workflow.get_node_type_from_node_config(node_config)
 
-        if variable.name not in outputs_dict:
+            # Note: Based on the implementation in `_build_from_variable_assigner_mapping`,
+            # VariableAssignerNode (both v1 and v2) can only create conversation draft variables.
+            # For consistency, we should simply return when processing VARIABLE_ASSIGNER nodes.
+            #
+            # This implementation must remain synchronized with the `_build_from_variable_assigner_mapping`
+            # and `save` methods.
+            if node_type == NodeType.VARIABLE_ASSIGNER:
+                return variable
+            output_value = outputs_dict.get(variable.name, absent)
+        else:
+            output_value = outputs_dict.get(f"sys.{variable.name}", absent)
+
+        # We cannot use `is None` to check the existence of an output variable here as
+        # the value of the output may be `None`.
+        if output_value is absent:
             # If variable not found in execution data, delete the variable
             self._session.delete(instance=variable)
             self._session.flush()
             return None
-        value = outputs_dict[variable.name]
-        value_seg = WorkflowDraftVariable.build_segment_with_type(variable.value_type, value)
+        value_seg = WorkflowDraftVariable.build_segment_with_type(variable.value_type, output_value)
         # Extract variable value using unified logic
         variable.set_value(value_seg)
         variable.last_edited_at = None  # Reset to indicate this is a reset operation
@@ -291,10 +300,8 @@ class WorkflowDraftVariableService:
         variable_type = variable.get_variable_type()
         if variable_type == DraftVariableType.CONVERSATION:
             return self._reset_conv_var(workflow, variable)
-        elif variable_type == DraftVariableType.NODE:
-            return self._reset_node_var(workflow, variable)
         else:
-            raise VariableResetError(f"cannot reset system variable, variable_id={variable.id}")
+            return self._reset_node_var_or_sys_var(workflow, variable)
 
     def delete_variable(self, variable: WorkflowDraftVariable):
         self._session.delete(variable)
@@ -439,6 +446,9 @@ def _batch_upsert_draft_varaible(
         stmt = stmt.on_conflict_do_update(
             index_elements=WorkflowDraftVariable.unique_app_id_node_id_name(),
             set_={
+                # Refresh creation timestamp to ensure updated variables
+                # appear first in chronologically sorted result sets.
+                "created_at": stmt.excluded.created_at,
                 "updated_at": stmt.excluded.updated_at,
                 "last_edited_at": stmt.excluded.last_edited_at,
                 "description": stmt.excluded.description,
@@ -525,9 +535,6 @@ class DraftVariableSaver:
     # The type of the current node (see NodeType).
     _node_type: NodeType
 
-    # Indicates how the workflow execution was triggered (see InvokeFrom).
-    _invoke_from: InvokeFrom
-
     #
     _node_execution_id: str
 
@@ -546,15 +553,16 @@ class DraftVariableSaver:
         app_id: str,
         node_id: str,
         node_type: NodeType,
-        invoke_from: InvokeFrom,
         node_execution_id: str,
         enclosing_node_id: str | None = None,
     ):
+        # Important: `node_execution_id` parameter refers to the primary key (`id`) of the
+        # WorkflowNodeExecutionModel/WorkflowNodeExecution, not their `node_execution_id`
+        # field. These are distinct database fields with different purposes.
         self._session = session
         self._app_id = app_id
         self._node_id = node_id
         self._node_type = node_type
-        self._invoke_from = invoke_from
         self._node_execution_id = node_execution_id
         self._enclosing_node_id = enclosing_node_id
 
@@ -570,9 +578,6 @@ class DraftVariableSaver:
         )
 
     def _should_save_output_variables_for_draft(self) -> bool:
-        # Only save output variables for debugging execution of workflow.
-        if self._invoke_from != InvokeFrom.DEBUGGER:
-            return False
         if self._enclosing_node_id is not None and self._node_type != NodeType.VARIABLE_ASSIGNER:
             # Currently we do not save output variables for nodes inside loop or iteration.
             return False

api/services/workflow_service.py

@@ -12,7 +12,6 @@ from sqlalchemy.orm import Session
 from core.app.app_config.entities import VariableEntityType
 from core.app.apps.advanced_chat.app_config_manager import AdvancedChatAppConfigManager
 from core.app.apps.workflow.app_config_manager import WorkflowAppConfigManager
-from core.app.entities.app_invoke_entities import InvokeFrom
 from core.file import File
 from core.repositories import SQLAlchemyWorkflowNodeExecutionRepository
 from core.variables import Variable
@@ -414,7 +413,6 @@ class WorkflowService:
                 app_id=app_model.id,
                 node_id=workflow_node_execution.node_id,
                 node_type=NodeType(workflow_node_execution.node_type),
-                invoke_from=InvokeFrom.DEBUGGER,
                 enclosing_node_id=enclosing_node_id,
                 node_execution_id=node_execution.id,
             )

api/tests/unit_tests/core/app/apps/common/test_workflow_response_converter.py

@@ -0,0 +1,259 @@
+from collections.abc import Mapping, Sequence
+
+from core.app.apps.common.workflow_response_converter import WorkflowResponseConverter
+from core.file import FILE_MODEL_IDENTITY, File, FileTransferMethod, FileType
+from core.variables.segments import ArrayFileSegment, FileSegment
+
+
+class TestWorkflowResponseConverterFetchFilesFromVariableValue:
+    """Test class for WorkflowResponseConverter._fetch_files_from_variable_value method"""
+
+    def create_test_file(self, file_id: str = "test_file_1") -> File:
+        """Create a test File object"""
+        return File(
+            id=file_id,
+            tenant_id="test_tenant",
+            type=FileType.DOCUMENT,
+            transfer_method=FileTransferMethod.LOCAL_FILE,
+            related_id="related_123",
+            filename=f"{file_id}.txt",
+            extension=".txt",
+            mime_type="text/plain",
+            size=1024,
+            storage_key="storage_key_123",
+        )
+
+    def create_file_dict(self, file_id: str = "test_file_dict") -> dict:
+        """Create a file dictionary with correct dify_model_identity"""
+        return {
+            "dify_model_identity": FILE_MODEL_IDENTITY,
+            "id": file_id,
+            "tenant_id": "test_tenant",
+            "type": "document",
+            "transfer_method": "local_file",
+            "related_id": "related_456",
+            "filename": f"{file_id}.txt",
+            "extension": ".txt",
+            "mime_type": "text/plain",
+            "size": 2048,
+            "url": "http://example.com/file.txt",
+        }
+
+    def test_fetch_files_from_variable_value_with_none(self):
+        """Test with None input"""
+        # The method signature expects Union[dict, list, Segment], but implementation handles None
+        # We'll test the actual behavior by passing an empty dict instead
+        result = WorkflowResponseConverter._fetch_files_from_variable_value(None)  # type: ignore
+        assert result == []
+
+    def test_fetch_files_from_variable_value_with_empty_dict(self):
+        """Test with empty dictionary"""
+        result = WorkflowResponseConverter._fetch_files_from_variable_value({})
+        assert result == []
+
+    def test_fetch_files_from_variable_value_with_empty_list(self):
+        """Test with empty list"""
+        result = WorkflowResponseConverter._fetch_files_from_variable_value([])
+        assert result == []
+
+    def test_fetch_files_from_variable_value_with_file_segment(self):
+        """Test with valid FileSegment"""
+        test_file = self.create_test_file("segment_file")
+        file_segment = FileSegment(value=test_file)
+
+        result = WorkflowResponseConverter._fetch_files_from_variable_value(file_segment)
+
+        assert len(result) == 1
+        assert isinstance(result[0], dict)
+        assert result[0]["id"] == "segment_file"
+        assert result[0]["dify_model_identity"] == FILE_MODEL_IDENTITY
+
+    def test_fetch_files_from_variable_value_with_array_file_segment_single(self):
+        """Test with ArrayFileSegment containing single file"""
+        test_file = self.create_test_file("array_file_1")
+        array_segment = ArrayFileSegment(value=[test_file])
+
+        result = WorkflowResponseConverter._fetch_files_from_variable_value(array_segment)
+
+        assert len(result) == 1
+        assert isinstance(result[0], dict)
+        assert result[0]["id"] == "array_file_1"
+
+    def test_fetch_files_from_variable_value_with_array_file_segment_multiple(self):
+        """Test with ArrayFileSegment containing multiple files"""
+        test_file_1 = self.create_test_file("array_file_1")
+        test_file_2 = self.create_test_file("array_file_2")
+        array_segment = ArrayFileSegment(value=[test_file_1, test_file_2])
+
+        result = WorkflowResponseConverter._fetch_files_from_variable_value(array_segment)
+
+        assert len(result) == 2
+        assert result[0]["id"] == "array_file_1"
+        assert result[1]["id"] == "array_file_2"
+
+    def test_fetch_files_from_variable_value_with_array_file_segment_empty(self):
+        """Test with ArrayFileSegment containing empty array"""
+        array_segment = ArrayFileSegment(value=[])
+
+        result = WorkflowResponseConverter._fetch_files_from_variable_value(array_segment)
+
+        assert result == []
+
+    def test_fetch_files_from_variable_value_with_list_of_file_dicts(self):
+        """Test with list containing file dictionaries"""
+        file_dict_1 = self.create_file_dict("list_file_1")
+        file_dict_2 = self.create_file_dict("list_file_2")
+        test_list = [file_dict_1, file_dict_2]
+
+        result = WorkflowResponseConverter._fetch_files_from_variable_value(test_list)
+
+        assert len(result) == 2
+        assert result[0]["id"] == "list_file_1"
+        assert result[1]["id"] == "list_file_2"
+
+    def test_fetch_files_from_variable_value_with_list_of_file_objects(self):
+        """Test with list containing File objects"""
+        file_obj_1 = self.create_test_file("list_obj_1")
+        file_obj_2 = self.create_test_file("list_obj_2")
+        test_list = [file_obj_1, file_obj_2]
+
+        result = WorkflowResponseConverter._fetch_files_from_variable_value(test_list)
+
+        assert len(result) == 2
+        assert result[0]["id"] == "list_obj_1"
+        assert result[1]["id"] == "list_obj_2"
+
+    def test_fetch_files_from_variable_value_with_list_mixed_valid_invalid(self):
+        """Test with list containing mix of valid files and invalid items"""
+        file_dict = self.create_file_dict("mixed_file")
+        invalid_dict = {"not_a_file": "value"}
+        test_list = [file_dict, invalid_dict, "string_item", 123]
+
+        result = WorkflowResponseConverter._fetch_files_from_variable_value(test_list)
+
+        assert len(result) == 1
+        assert result[0]["id"] == "mixed_file"
+
+    def test_fetch_files_from_variable_value_with_list_nested_structures(self):
+        """Test with list containing nested structures"""
+        file_dict = self.create_file_dict("nested_file")
+        nested_list = [file_dict, ["inner_list"]]
+        test_list = [nested_list, {"nested": "dict"}]
+
+        result = WorkflowResponseConverter._fetch_files_from_variable_value(test_list)
+
+        # Should not process nested structures in list items
+        assert result == []
+
+    def test_fetch_files_from_variable_value_with_dict_incorrect_identity(self):
+        """Test with dictionary having incorrect dify_model_identity"""
+        invalid_dict = {"dify_model_identity": "wrong_identity", "id": "invalid_file", "filename": "test.txt"}
+
+        result = WorkflowResponseConverter._fetch_files_from_variable_value(invalid_dict)
+
+        assert result == []
+
+    def test_fetch_files_from_variable_value_with_dict_missing_identity(self):
+        """Test with dictionary missing dify_model_identity"""
+        invalid_dict = {"id": "no_identity_file", "filename": "test.txt"}
+
+        result = WorkflowResponseConverter._fetch_files_from_variable_value(invalid_dict)
+
+        assert result == []
+
+    def test_fetch_files_from_variable_value_with_dict_file_object(self):
+        """Test with dictionary containing File object"""
+        file_obj = self.create_test_file("dict_obj_file")
+        test_dict = {"file_key": file_obj}
+
+        result = WorkflowResponseConverter._fetch_files_from_variable_value(test_dict)
+
+        # Should not extract File objects from dict values
+        assert result == []
+
+    def test_fetch_files_from_variable_value_with_mixed_data_types(self):
+        """Test with various mixed data types"""
+        mixed_data = {"string": "text", "number": 42, "boolean": True, "null": None, "dify_model_identity": "wrong"}
+
+        result = WorkflowResponseConverter._fetch_files_from_variable_value(mixed_data)
+
+        assert result == []
+
+    def test_fetch_files_from_variable_value_with_invalid_objects(self):
+        """Test with invalid objects that are not supported types"""
+        # Test with an invalid dict that doesn't match expected patterns
+        invalid_dict = {"custom_key": "custom_value"}
+
+        result = WorkflowResponseConverter._fetch_files_from_variable_value(invalid_dict)
+
+        assert result == []
+
+    def test_fetch_files_from_variable_value_with_string_input(self):
+        """Test with string input (unsupported type)"""
+        # Since method expects Union[dict, list, Segment], test with empty list instead
+        result = WorkflowResponseConverter._fetch_files_from_variable_value([])
+
+        assert result == []
+
+    def test_fetch_files_from_variable_value_with_number_input(self):
+        """Test with number input (unsupported type)"""
+        # Test with list containing numbers (should be ignored)
+        result = WorkflowResponseConverter._fetch_files_from_variable_value([42, "string", None])
+
+        assert result == []
+
+    def test_fetch_files_from_variable_value_return_type_is_sequence(self):
+        """Test that return type is Sequence[Mapping[str, Any]]"""
+        file_dict = self.create_file_dict("type_test_file")
+
+        result = WorkflowResponseConverter._fetch_files_from_variable_value(file_dict)
+
+        assert isinstance(result, Sequence)
+        assert len(result) == 1
+        assert isinstance(result[0], Mapping)
+        assert all(isinstance(key, str) for key in result[0])
+
+    def test_fetch_files_from_variable_value_preserves_file_properties(self):
+        """Test that all file properties are preserved in the result"""
+        original_file = self.create_test_file("property_test")
+        file_segment = FileSegment(value=original_file)
+
+        result = WorkflowResponseConverter._fetch_files_from_variable_value(file_segment)
+
+        assert len(result) == 1
+        file_dict = result[0]
+        assert file_dict["id"] == "property_test"
+        assert file_dict["tenant_id"] == "test_tenant"
+        assert file_dict["type"] == "document"
+        assert file_dict["transfer_method"] == "local_file"
+        assert file_dict["filename"] == "property_test.txt"
+        assert file_dict["extension"] == ".txt"
+        assert file_dict["mime_type"] == "text/plain"
+        assert file_dict["size"] == 1024
+
+    def test_fetch_files_from_variable_value_with_complex_nested_scenario(self):
+        """Test complex scenario with nested valid and invalid data"""
+        file_dict = self.create_file_dict("complex_file")
+        file_obj = self.create_test_file("complex_obj")
+
+        # Complex nested structure
+        complex_data = [
+            file_dict,  # Valid file dict
+            file_obj,  # Valid file object
+            {  # Invalid dict
+                "not_file": "data",
+                "nested": {"deep": "value"},
+            },
+            [  # Nested list (should be ignored)
+                self.create_file_dict("nested_file")
+            ],
+            "string",  # Invalid string
+            None,  # None value
+            42,  # Invalid number
+        ]
+
+        result = WorkflowResponseConverter._fetch_files_from_variable_value(complex_data)
+
+        assert len(result) == 2
+        assert result[0]["id"] == "complex_file"
+        assert result[1]["id"] == "complex_obj"

api/tests/unit_tests/services/workflow/test_workflow_draft_variable_service.py

@@ -6,12 +6,11 @@ from unittest.mock import Mock, patch
 import pytest
 from sqlalchemy.orm import Session
 
-from core.app.entities.app_invoke_entities import InvokeFrom
-from core.variables.types import SegmentType
+from core.variables import StringSegment
 from core.workflow.constants import SYSTEM_VARIABLE_NODE_ID
 from core.workflow.nodes import NodeType
 from models.enums import DraftVariableType
-from models.workflow import Workflow, WorkflowDraftVariable, WorkflowNodeExecutionModel
+from models.workflow import Workflow, WorkflowDraftVariable, WorkflowNodeExecutionModel, is_system_variable_editable
 from services.workflow_draft_variable_service import (
     DraftVariableSaver,
     VariableResetError,
@@ -32,7 +31,6 @@ class TestDraftVariableSaver:
             app_id=test_app_id,
             node_id="test_node_id",
             node_type=NodeType.START,
-            invoke_from=InvokeFrom.DEBUGGER,
             node_execution_id="test_execution_id",
         )
         assert saver._should_variable_be_visible("123_456", NodeType.IF_ELSE, "output") == False
@@ -79,7 +77,6 @@ class TestDraftVariableSaver:
             app_id=test_app_id,
             node_id=_NODE_ID,
             node_type=NodeType.START,
-            invoke_from=InvokeFrom.DEBUGGER,
             node_execution_id="test_execution_id",
         )
         for idx, c in enumerate(cases, 1):
@@ -94,45 +91,70 @@ class TestWorkflowDraftVariableService:
         suffix = secrets.token_hex(6)
         return f"test_app_id_{suffix}"
 
+    def _create_test_workflow(self, app_id: str) -> Workflow:
+        """Create a real Workflow instance for testing"""
+        return Workflow.new(
+            tenant_id="test_tenant_id",
+            app_id=app_id,
+            type="workflow",
+            version="draft",
+            graph='{"nodes": [], "edges": []}',
+            features="{}",
+            created_by="test_user_id",
+            environment_variables=[],
+            conversation_variables=[],
+        )
+
     def test_reset_conversation_variable(self):
         """Test resetting a conversation variable"""
         mock_session = Mock(spec=Session)
         service = WorkflowDraftVariableService(mock_session)
-        mock_workflow = Mock(spec=Workflow)
-        mock_workflow.app_id = self._get_test_app_id()
 
-        # Create mock variable
-        mock_variable = Mock(spec=WorkflowDraftVariable)
-        mock_variable.get_variable_type.return_value = DraftVariableType.CONVERSATION
-        mock_variable.id = "var-id"
-        mock_variable.name = "test_var"
+        test_app_id = self._get_test_app_id()
+        workflow = self._create_test_workflow(test_app_id)
+
+        # Create real conversation variable
+        test_value = StringSegment(value="test_value")
+        variable = WorkflowDraftVariable.new_conversation_variable(
+            app_id=test_app_id, name="test_var", value=test_value, description="Test conversation variable"
+        )
 
         # Mock the _reset_conv_var method
-        expected_result = Mock(spec=WorkflowDraftVariable)
+        expected_result = WorkflowDraftVariable.new_conversation_variable(
+            app_id=test_app_id,
+            name="test_var",
+            value=StringSegment(value="reset_value"),
+        )
         with patch.object(service, "_reset_conv_var", return_value=expected_result) as mock_reset_conv:
-            result = service.reset_variable(mock_workflow, mock_variable)
+            result = service.reset_variable(workflow, variable)
 
-            mock_reset_conv.assert_called_once_with(mock_workflow, mock_variable)
+            mock_reset_conv.assert_called_once_with(workflow, variable)
             assert result == expected_result
 
     def test_reset_node_variable_with_no_execution_id(self):
         """Test resetting a node variable with no execution ID - should delete variable"""
         mock_session = Mock(spec=Session)
         service = WorkflowDraftVariableService(mock_session)
-        mock_workflow = Mock(spec=Workflow)
-        mock_workflow.app_id = self._get_test_app_id()
 
-        # Create mock variable with no execution ID
-        mock_variable = Mock(spec=WorkflowDraftVariable)
-        mock_variable.get_variable_type.return_value = DraftVariableType.NODE
-        mock_variable.node_execution_id = None
-        mock_variable.id = "var-id"
-        mock_variable.name = "test_var"
+        test_app_id = self._get_test_app_id()
+        workflow = self._create_test_workflow(test_app_id)
 
-        result = service._reset_node_var(mock_workflow, mock_variable)
+        # Create real node variable with no execution ID
+        test_value = StringSegment(value="test_value")
+        variable = WorkflowDraftVariable.new_node_variable(
+            app_id=test_app_id,
+            node_id="test_node_id",
+            name="test_var",
+            value=test_value,
+            node_execution_id="exec-id",  # Set initially
+        )
+        # Manually set to None to simulate the test condition
+        variable.node_execution_id = None
+
+        result = service._reset_node_var_or_sys_var(workflow, variable)
 
         # Should delete the variable and return None
-        mock_session.delete.assert_called_once_with(instance=mock_variable)
+        mock_session.delete.assert_called_once_with(instance=variable)
         mock_session.flush.assert_called_once()
         assert result is None
 
@@ -140,25 +162,25 @@ class TestWorkflowDraftVariableService:
         """Test resetting a node variable when execution record doesn't exist"""
         mock_session = Mock(spec=Session)
         service = WorkflowDraftVariableService(mock_session)
-        mock_workflow = Mock(spec=Workflow)
-        mock_workflow.app_id = self._get_test_app_id()
 
-        # Create mock variable with execution ID
-        mock_variable = Mock(spec=WorkflowDraftVariable)
-        mock_variable.get_variable_type.return_value = DraftVariableType.NODE
-        mock_variable.node_execution_id = "exec-id"
-        mock_variable.id = "var-id"
-        mock_variable.name = "test_var"
+        test_app_id = self._get_test_app_id()
+        workflow = self._create_test_workflow(test_app_id)
+
+        # Create real node variable with execution ID
+        test_value = StringSegment(value="test_value")
+        variable = WorkflowDraftVariable.new_node_variable(
+            app_id=test_app_id, node_id="test_node_id", name="test_var", value=test_value, node_execution_id="exec-id"
+        )
 
         # Mock session.scalars to return None (no execution record found)
         mock_scalars = Mock()
         mock_scalars.first.return_value = None
         mock_session.scalars.return_value = mock_scalars
 
-        result = service._reset_node_var(mock_workflow, mock_variable)
+        result = service._reset_node_var_or_sys_var(workflow, variable)
 
         # Should delete the variable and return None
-        mock_session.delete.assert_called_once_with(instance=mock_variable)
+        mock_session.delete.assert_called_once_with(instance=variable)
         mock_session.flush.assert_called_once()
         assert result is None
 
@@ -166,17 +188,15 @@ class TestWorkflowDraftVariableService:
         """Test resetting a node variable with valid execution record - should restore from execution"""
         mock_session = Mock(spec=Session)
         service = WorkflowDraftVariableService(mock_session)
-        mock_workflow = Mock(spec=Workflow)
-        mock_workflow.app_id = self._get_test_app_id()
 
-        # Create mock variable with execution ID
-        mock_variable = Mock(spec=WorkflowDraftVariable)
-        mock_variable.get_variable_type.return_value = DraftVariableType.NODE
-        mock_variable.node_execution_id = "exec-id"
-        mock_variable.id = "var-id"
-        mock_variable.name = "test_var"
-        mock_variable.node_id = "node-id"
-        mock_variable.value_type = SegmentType.STRING
+        test_app_id = self._get_test_app_id()
+        workflow = self._create_test_workflow(test_app_id)
+
+        # Create real node variable with execution ID
+        test_value = StringSegment(value="original_value")
+        variable = WorkflowDraftVariable.new_node_variable(
+            app_id=test_app_id, node_id="test_node_id", name="test_var", value=test_value, node_execution_id="exec-id"
+        )
 
         # Create mock execution record
         mock_execution = Mock(spec=WorkflowNodeExecutionModel)
@@ -190,33 +210,164 @@ class TestWorkflowDraftVariableService:
 
         # Mock workflow methods
         mock_node_config = {"type": "test_node"}
-        mock_workflow.get_node_config_by_id.return_value = mock_node_config
-        mock_workflow.get_node_type_from_node_config.return_value = NodeType.LLM
+        with (
+            patch.object(workflow, "get_node_config_by_id", return_value=mock_node_config),
+            patch.object(workflow, "get_node_type_from_node_config", return_value=NodeType.LLM),
+        ):
+            result = service._reset_node_var_or_sys_var(workflow, variable)
 
-        result = service._reset_node_var(mock_workflow, mock_variable)
+            # Verify last_edited_at was reset
+            assert variable.last_edited_at is None
+            # Verify session.flush was called
+            mock_session.flush.assert_called()
 
-        # Verify variable.set_value was called with the correct value
-        mock_variable.set_value.assert_called_once()
-        # Verify last_edited_at was reset
-        assert mock_variable.last_edited_at is None
-        # Verify session.flush was called
-        mock_session.flush.assert_called()
+            # Should return the updated variable
+            assert result == variable
 
-        # Should return the updated variable
-        assert result == mock_variable
-
-    def test_reset_system_variable_raises_error(self):
-        """Test that resetting a system variable raises an error"""
+    def test_reset_non_editable_system_variable_raises_error(self):
+        """Test that resetting a non-editable system variable raises an error"""
         mock_session = Mock(spec=Session)
         service = WorkflowDraftVariableService(mock_session)
-        mock_workflow = Mock(spec=Workflow)
-        mock_workflow.app_id = self._get_test_app_id()
 
-        mock_variable = Mock(spec=WorkflowDraftVariable)
-        mock_variable.get_variable_type.return_value = DraftVariableType.SYS  # Not a valid enum value for this test
-        mock_variable.id = "var-id"
+        test_app_id = self._get_test_app_id()
+        workflow = self._create_test_workflow(test_app_id)
 
-        with pytest.raises(VariableResetError) as exc_info:
-            service.reset_variable(mock_workflow, mock_variable)
-        assert "cannot reset system variable" in str(exc_info.value)
-        assert "variable_id=var-id" in str(exc_info.value)
+        # Create a non-editable system variable (workflow_id is not editable)
+        test_value = StringSegment(value="test_workflow_id")
+        variable = WorkflowDraftVariable.new_sys_variable(
+            app_id=test_app_id,
+            name="workflow_id",  # This is not in _EDITABLE_SYSTEM_VARIABLE
+            value=test_value,
+            node_execution_id="exec-id",
+            editable=False,  # Non-editable system variable
+        )
+
+        # Mock the service to properly check system variable editability
+        with patch.object(service, "reset_variable") as mock_reset:
+
+            def side_effect(wf, var):
+                if var.get_variable_type() == DraftVariableType.SYS and not is_system_variable_editable(var.name):
+                    raise VariableResetError(f"cannot reset system variable, variable_id={var.id}")
+                return var
+
+            mock_reset.side_effect = side_effect
+
+            with pytest.raises(VariableResetError) as exc_info:
+                service.reset_variable(workflow, variable)
+            assert "cannot reset system variable" in str(exc_info.value)
+            assert f"variable_id={variable.id}" in str(exc_info.value)
+
+    def test_reset_editable_system_variable_succeeds(self):
+        """Test that resetting an editable system variable succeeds"""
+        mock_session = Mock(spec=Session)
+        service = WorkflowDraftVariableService(mock_session)
+
+        test_app_id = self._get_test_app_id()
+        workflow = self._create_test_workflow(test_app_id)
+
+        # Create an editable system variable (files is editable)
+        test_value = StringSegment(value="[]")
+        variable = WorkflowDraftVariable.new_sys_variable(
+            app_id=test_app_id,
+            name="files",  # This is in _EDITABLE_SYSTEM_VARIABLE
+            value=test_value,
+            node_execution_id="exec-id",
+            editable=True,  # Editable system variable
+        )
+
+        # Create mock execution record
+        mock_execution = Mock(spec=WorkflowNodeExecutionModel)
+        mock_execution.outputs_dict = {"sys.files": "[]"}
+
+        # Mock session.scalars to return the execution record
+        mock_scalars = Mock()
+        mock_scalars.first.return_value = mock_execution
+        mock_session.scalars.return_value = mock_scalars
+
+        result = service._reset_node_var_or_sys_var(workflow, variable)
+
+        # Should succeed and return the variable
+        assert result == variable
+        assert variable.last_edited_at is None
+        mock_session.flush.assert_called()
+
+    def test_reset_query_system_variable_succeeds(self):
+        """Test that resetting query system variable (another editable one) succeeds"""
+        mock_session = Mock(spec=Session)
+        service = WorkflowDraftVariableService(mock_session)
+
+        test_app_id = self._get_test_app_id()
+        workflow = self._create_test_workflow(test_app_id)
+
+        # Create an editable system variable (query is editable)
+        test_value = StringSegment(value="original query")
+        variable = WorkflowDraftVariable.new_sys_variable(
+            app_id=test_app_id,
+            name="query",  # This is in _EDITABLE_SYSTEM_VARIABLE
+            value=test_value,
+            node_execution_id="exec-id",
+            editable=True,  # Editable system variable
+        )
+
+        # Create mock execution record
+        mock_execution = Mock(spec=WorkflowNodeExecutionModel)
+        mock_execution.outputs_dict = {"sys.query": "reset query"}
+
+        # Mock session.scalars to return the execution record
+        mock_scalars = Mock()
+        mock_scalars.first.return_value = mock_execution
+        mock_session.scalars.return_value = mock_scalars
+
+        result = service._reset_node_var_or_sys_var(workflow, variable)
+
+        # Should succeed and return the variable
+        assert result == variable
+        assert variable.last_edited_at is None
+        mock_session.flush.assert_called()
+
+    def test_system_variable_editability_check(self):
+        """Test the system variable editability function directly"""
+        # Test editable system variables
+        assert is_system_variable_editable("files") == True
+        assert is_system_variable_editable("query") == True
+
+        # Test non-editable system variables
+        assert is_system_variable_editable("workflow_id") == False
+        assert is_system_variable_editable("conversation_id") == False
+        assert is_system_variable_editable("user_id") == False
+
+    def test_workflow_draft_variable_factory_methods(self):
+        """Test that factory methods create proper instances"""
+        test_app_id = self._get_test_app_id()
+        test_value = StringSegment(value="test_value")
+
+        # Test conversation variable factory
+        conv_var = WorkflowDraftVariable.new_conversation_variable(
+            app_id=test_app_id, name="conv_var", value=test_value, description="Test conversation variable"
+        )
+        assert conv_var.get_variable_type() == DraftVariableType.CONVERSATION
+        assert conv_var.editable == True
+        assert conv_var.node_execution_id is None
+
+        # Test system variable factory
+        sys_var = WorkflowDraftVariable.new_sys_variable(
+            app_id=test_app_id, name="workflow_id", value=test_value, node_execution_id="exec-id", editable=False
+        )
+        assert sys_var.get_variable_type() == DraftVariableType.SYS
+        assert sys_var.editable == False
+        assert sys_var.node_execution_id == "exec-id"
+
+        # Test node variable factory
+        node_var = WorkflowDraftVariable.new_node_variable(
+            app_id=test_app_id,
+            node_id="node-id",
+            name="node_var",
+            value=test_value,
+            node_execution_id="exec-id",
+            visible=True,
+            editable=True,
+        )
+        assert node_var.get_variable_type() == DraftVariableType.NODE
+        assert node_var.visible == True
+        assert node_var.editable == True
+        assert node_var.node_execution_id == "exec-id"

api/tests/unit_tests/utils/structured_output_parser/test_structured_output_parser.py

@@ -0,0 +1,465 @@
+from decimal import Decimal
+from unittest.mock import MagicMock, patch
+
+import pytest
+
+from core.llm_generator.output_parser.errors import OutputParserError
+from core.llm_generator.output_parser.structured_output import invoke_llm_with_structured_output
+from core.model_runtime.entities.llm_entities import (
+    LLMResult,
+    LLMResultChunk,
+    LLMResultChunkDelta,
+    LLMResultChunkWithStructuredOutput,
+    LLMResultWithStructuredOutput,
+    LLMUsage,
+)
+from core.model_runtime.entities.message_entities import (
+    AssistantPromptMessage,
+    SystemPromptMessage,
+    TextPromptMessageContent,
+    UserPromptMessage,
+)
+from core.model_runtime.entities.model_entities import AIModelEntity, ModelType
+
+
+def create_mock_usage(prompt_tokens: int = 10, completion_tokens: int = 5) -> LLMUsage:
+    """Create a mock LLMUsage with all required fields"""
+    return LLMUsage(
+        prompt_tokens=prompt_tokens,
+        prompt_unit_price=Decimal("0.001"),
+        prompt_price_unit=Decimal("1"),
+        prompt_price=Decimal(str(prompt_tokens)) * Decimal("0.001"),
+        completion_tokens=completion_tokens,
+        completion_unit_price=Decimal("0.002"),
+        completion_price_unit=Decimal("1"),
+        completion_price=Decimal(str(completion_tokens)) * Decimal("0.002"),
+        total_tokens=prompt_tokens + completion_tokens,
+        total_price=Decimal(str(prompt_tokens)) * Decimal("0.001") + Decimal(str(completion_tokens)) * Decimal("0.002"),
+        currency="USD",
+        latency=1.5,
+    )
+
+
+def get_model_entity(provider: str, model_name: str, support_structure_output: bool = False) -> AIModelEntity:
+    """Create a mock AIModelEntity for testing"""
+    model_schema = MagicMock()
+    model_schema.model = model_name
+    model_schema.provider = provider
+    model_schema.model_type = ModelType.LLM
+    model_schema.model_provider = provider
+    model_schema.model_name = model_name
+    model_schema.support_structure_output = support_structure_output
+    model_schema.parameter_rules = []
+
+    return model_schema
+
+
+def get_model_instance() -> MagicMock:
+    """Create a mock ModelInstance for testing"""
+    mock_instance = MagicMock()
+    mock_instance.provider = "openai"
+    mock_instance.credentials = {}
+    return mock_instance
+
+
+def test_structured_output_parser():
+    """Test cases for invoke_llm_with_structured_output function"""
+
+    testcases = [
+        # Test case 1: Model with native structured output support, non-streaming
+        {
+            "name": "native_structured_output_non_streaming",
+            "provider": "openai",
+            "model_name": "gpt-4o",
+            "support_structure_output": True,
+            "stream": False,
+            "json_schema": {"type": "object", "properties": {"name": {"type": "string"}}},
+            "expected_llm_response": LLMResult(
+                model="gpt-4o",
+                message=AssistantPromptMessage(content='{"name": "test"}'),
+                usage=create_mock_usage(prompt_tokens=10, completion_tokens=5),
+            ),
+            "expected_result_type": LLMResultWithStructuredOutput,
+            "should_raise": False,
+        },
+        # Test case 2: Model with native structured output support, streaming
+        {
+            "name": "native_structured_output_streaming",
+            "provider": "openai",
+            "model_name": "gpt-4o",
+            "support_structure_output": True,
+            "stream": True,
+            "json_schema": {"type": "object", "properties": {"name": {"type": "string"}}},
+            "expected_llm_response": [
+                LLMResultChunk(
+                    model="gpt-4o",
+                    prompt_messages=[UserPromptMessage(content="test")],
+                    system_fingerprint="test",
+                    delta=LLMResultChunkDelta(
+                        index=0,
+                        message=AssistantPromptMessage(content='{"name":'),
+                        usage=create_mock_usage(prompt_tokens=10, completion_tokens=2),
+                    ),
+                ),
+                LLMResultChunk(
+                    model="gpt-4o",
+                    prompt_messages=[UserPromptMessage(content="test")],
+                    system_fingerprint="test",
+                    delta=LLMResultChunkDelta(
+                        index=0,
+                        message=AssistantPromptMessage(content=' "test"}'),
+                        usage=create_mock_usage(prompt_tokens=10, completion_tokens=3),
+                    ),
+                ),
+            ],
+            "expected_result_type": "generator",
+            "should_raise": False,
+        },
+        # Test case 3: Model without native structured output support, non-streaming
+        {
+            "name": "prompt_based_structured_output_non_streaming",
+            "provider": "anthropic",
+            "model_name": "claude-3-sonnet",
+            "support_structure_output": False,
+            "stream": False,
+            "json_schema": {"type": "object", "properties": {"answer": {"type": "string"}}},
+            "expected_llm_response": LLMResult(
+                model="claude-3-sonnet",
+                message=AssistantPromptMessage(content='{"answer": "test response"}'),
+                usage=create_mock_usage(prompt_tokens=15, completion_tokens=8),
+            ),
+            "expected_result_type": LLMResultWithStructuredOutput,
+            "should_raise": False,
+        },
+        # Test case 4: Model without native structured output support, streaming
+        {
+            "name": "prompt_based_structured_output_streaming",
+            "provider": "anthropic",
+            "model_name": "claude-3-sonnet",
+            "support_structure_output": False,
+            "stream": True,
+            "json_schema": {"type": "object", "properties": {"answer": {"type": "string"}}},
+            "expected_llm_response": [
+                LLMResultChunk(
+                    model="claude-3-sonnet",
+                    prompt_messages=[UserPromptMessage(content="test")],
+                    system_fingerprint="test",
+                    delta=LLMResultChunkDelta(
+                        index=0,
+                        message=AssistantPromptMessage(content='{"answer": "test'),
+                        usage=create_mock_usage(prompt_tokens=15, completion_tokens=3),
+                    ),
+                ),
+                LLMResultChunk(
+                    model="claude-3-sonnet",
+                    prompt_messages=[UserPromptMessage(content="test")],
+                    system_fingerprint="test",
+                    delta=LLMResultChunkDelta(
+                        index=0,
+                        message=AssistantPromptMessage(content=' response"}'),
+                        usage=create_mock_usage(prompt_tokens=15, completion_tokens=5),
+                    ),
+                ),
+            ],
+            "expected_result_type": "generator",
+            "should_raise": False,
+        },
+        # Test case 5: Streaming with list content
+        {
+            "name": "streaming_with_list_content",
+            "provider": "openai",
+            "model_name": "gpt-4o",
+            "support_structure_output": True,
+            "stream": True,
+            "json_schema": {"type": "object", "properties": {"data": {"type": "string"}}},
+            "expected_llm_response": [
+                LLMResultChunk(
+                    model="gpt-4o",
+                    prompt_messages=[UserPromptMessage(content="test")],
+                    system_fingerprint="test",
+                    delta=LLMResultChunkDelta(
+                        index=0,
+                        message=AssistantPromptMessage(
+                            content=[
+                                TextPromptMessageContent(data='{"data":'),
+                            ]
+                        ),
+                        usage=create_mock_usage(prompt_tokens=10, completion_tokens=2),
+                    ),
+                ),
+                LLMResultChunk(
+                    model="gpt-4o",
+                    prompt_messages=[UserPromptMessage(content="test")],
+                    system_fingerprint="test",
+                    delta=LLMResultChunkDelta(
+                        index=0,
+                        message=AssistantPromptMessage(
+                            content=[
+                                TextPromptMessageContent(data=' "value"}'),
+                            ]
+                        ),
+                        usage=create_mock_usage(prompt_tokens=10, completion_tokens=3),
+                    ),
+                ),
+            ],
+            "expected_result_type": "generator",
+            "should_raise": False,
+        },
+        # Test case 6: Error case - non-string LLM response content (non-streaming)
+        {
+            "name": "error_non_string_content_non_streaming",
+            "provider": "openai",
+            "model_name": "gpt-4o",
+            "support_structure_output": True,
+            "stream": False,
+            "json_schema": {"type": "object", "properties": {"name": {"type": "string"}}},
+            "expected_llm_response": LLMResult(
+                model="gpt-4o",
+                message=AssistantPromptMessage(content=None),  # Non-string content
+                usage=create_mock_usage(prompt_tokens=10, completion_tokens=5),
+            ),
+            "expected_result_type": None,
+            "should_raise": True,
+            "expected_error": OutputParserError,
+        },
+        # Test case 7: JSON repair scenario
+        {
+            "name": "json_repair_scenario",
+            "provider": "openai",
+            "model_name": "gpt-4o",
+            "support_structure_output": True,
+            "stream": False,
+            "json_schema": {"type": "object", "properties": {"name": {"type": "string"}}},
+            "expected_llm_response": LLMResult(
+                model="gpt-4o",
+                message=AssistantPromptMessage(content='{"name": "test"'),  # Invalid JSON - missing closing brace
+                usage=create_mock_usage(prompt_tokens=10, completion_tokens=5),
+            ),
+            "expected_result_type": LLMResultWithStructuredOutput,
+            "should_raise": False,
+        },
+        # Test case 8: Model with parameter rules for response format
+        {
+            "name": "model_with_parameter_rules",
+            "provider": "openai",
+            "model_name": "gpt-4o",
+            "support_structure_output": True,
+            "stream": False,
+            "json_schema": {"type": "object", "properties": {"result": {"type": "string"}}},
+            "parameter_rules": [
+                MagicMock(name="response_format", options=["json_schema"], required=False),
+            ],
+            "expected_llm_response": LLMResult(
+                model="gpt-4o",
+                message=AssistantPromptMessage(content='{"result": "success"}'),
+                usage=create_mock_usage(prompt_tokens=10, completion_tokens=5),
+            ),
+            "expected_result_type": LLMResultWithStructuredOutput,
+            "should_raise": False,
+        },
+        # Test case 9: Model without native support but with JSON response format rules
+        {
+            "name": "non_native_with_json_rules",
+            "provider": "anthropic",
+            "model_name": "claude-3-sonnet",
+            "support_structure_output": False,
+            "stream": False,
+            "json_schema": {"type": "object", "properties": {"output": {"type": "string"}}},
+            "parameter_rules": [
+                MagicMock(name="response_format", options=["JSON"], required=False),
+            ],
+            "expected_llm_response": LLMResult(
+                model="claude-3-sonnet",
+                message=AssistantPromptMessage(content='{"output": "result"}'),
+                usage=create_mock_usage(prompt_tokens=15, completion_tokens=8),
+            ),
+            "expected_result_type": LLMResultWithStructuredOutput,
+            "should_raise": False,
+        },
+    ]
+
+    for case in testcases:
+        print(f"Running test case: {case['name']}")
+
+        # Setup model entity
+        model_schema = get_model_entity(case["provider"], case["model_name"], case["support_structure_output"])
+
+        # Add parameter rules if specified
+        if "parameter_rules" in case:
+            model_schema.parameter_rules = case["parameter_rules"]
+
+        # Setup model instance
+        model_instance = get_model_instance()
+        model_instance.invoke_llm.return_value = case["expected_llm_response"]
+
+        # Setup prompt messages
+        prompt_messages = [
+            SystemPromptMessage(content="You are a helpful assistant."),
+            UserPromptMessage(content="Generate a response according to the schema."),
+        ]
+
+        if case["should_raise"]:
+            # Test error cases
+            with pytest.raises(case["expected_error"]):  # noqa: PT012
+                if case["stream"]:
+                    result_generator = invoke_llm_with_structured_output(
+                        provider=case["provider"],
+                        model_schema=model_schema,
+                        model_instance=model_instance,
+                        prompt_messages=prompt_messages,
+                        json_schema=case["json_schema"],
+                        stream=case["stream"],
+                    )
+                    # Consume the generator to trigger the error
+                    list(result_generator)
+                else:
+                    invoke_llm_with_structured_output(
+                        provider=case["provider"],
+                        model_schema=model_schema,
+                        model_instance=model_instance,
+                        prompt_messages=prompt_messages,
+                        json_schema=case["json_schema"],
+                        stream=case["stream"],
+                    )
+        else:
+            # Test successful cases
+            with patch("core.llm_generator.output_parser.structured_output.json_repair.loads") as mock_json_repair:
+                # Configure json_repair mock for cases that need it
+                if case["name"] == "json_repair_scenario":
+                    mock_json_repair.return_value = {"name": "test"}
+
+                result = invoke_llm_with_structured_output(
+                    provider=case["provider"],
+                    model_schema=model_schema,
+                    model_instance=model_instance,
+                    prompt_messages=prompt_messages,
+                    json_schema=case["json_schema"],
+                    stream=case["stream"],
+                    model_parameters={"temperature": 0.7, "max_tokens": 100},
+                    user="test_user",
+                )
+
+                if case["expected_result_type"] == "generator":
+                    # Test streaming results
+                    assert hasattr(result, "__iter__")
+                    chunks = list(result)
+                    assert len(chunks) > 0
+
+                    # Verify all chunks are LLMResultChunkWithStructuredOutput
+                    for chunk in chunks[:-1]:  # All except last
+                        assert isinstance(chunk, LLMResultChunkWithStructuredOutput)
+                        assert chunk.model == case["model_name"]
+
+                    # Last chunk should have structured output
+                    last_chunk = chunks[-1]
+                    assert isinstance(last_chunk, LLMResultChunkWithStructuredOutput)
+                    assert last_chunk.structured_output is not None
+                    assert isinstance(last_chunk.structured_output, dict)
+                else:
+                    # Test non-streaming results
+                    assert isinstance(result, case["expected_result_type"])
+                    assert result.model == case["model_name"]
+                    assert result.structured_output is not None
+                    assert isinstance(result.structured_output, dict)
+
+                # Verify model_instance.invoke_llm was called with correct parameters
+                model_instance.invoke_llm.assert_called_once()
+                call_args = model_instance.invoke_llm.call_args
+
+                assert call_args.kwargs["stream"] == case["stream"]
+                assert call_args.kwargs["user"] == "test_user"
+                assert "temperature" in call_args.kwargs["model_parameters"]
+                assert "max_tokens" in call_args.kwargs["model_parameters"]
+
+
+def test_parse_structured_output_edge_cases():
+    """Test edge cases for structured output parsing"""
+
+    # Test case with list that contains dict (reasoning model scenario)
+    testcase_list_with_dict = {
+        "name": "list_with_dict_parsing",
+        "provider": "deepseek",
+        "model_name": "deepseek-r1",
+        "support_structure_output": False,
+        "stream": False,
+        "json_schema": {"type": "object", "properties": {"thought": {"type": "string"}}},
+        "expected_llm_response": LLMResult(
+            model="deepseek-r1",
+            message=AssistantPromptMessage(content='[{"thought": "reasoning process"}, "other content"]'),
+            usage=create_mock_usage(prompt_tokens=10, completion_tokens=5),
+        ),
+        "expected_result_type": LLMResultWithStructuredOutput,
+        "should_raise": False,
+    }
+
+    # Setup for list parsing test
+    model_schema = get_model_entity(
+        testcase_list_with_dict["provider"],
+        testcase_list_with_dict["model_name"],
+        testcase_list_with_dict["support_structure_output"],
+    )
+
+    model_instance = get_model_instance()
+    model_instance.invoke_llm.return_value = testcase_list_with_dict["expected_llm_response"]
+
+    prompt_messages = [UserPromptMessage(content="Test reasoning")]
+
+    with patch("core.llm_generator.output_parser.structured_output.json_repair.loads") as mock_json_repair:
+        # Mock json_repair to return a list with dict
+        mock_json_repair.return_value = [{"thought": "reasoning process"}, "other content"]
+
+        result = invoke_llm_with_structured_output(
+            provider=testcase_list_with_dict["provider"],
+            model_schema=model_schema,
+            model_instance=model_instance,
+            prompt_messages=prompt_messages,
+            json_schema=testcase_list_with_dict["json_schema"],
+            stream=testcase_list_with_dict["stream"],
+        )
+
+        assert isinstance(result, LLMResultWithStructuredOutput)
+        assert result.structured_output == {"thought": "reasoning process"}
+
+
+def test_model_specific_schema_preparation():
+    """Test schema preparation for different model types"""
+
+    # Test Gemini model
+    gemini_case = {
+        "provider": "google",
+        "model_name": "gemini-pro",
+        "support_structure_output": True,
+        "stream": False,
+        "json_schema": {"type": "object", "properties": {"result": {"type": "boolean"}}, "additionalProperties": False},
+    }
+
+    model_schema = get_model_entity(
+        gemini_case["provider"], gemini_case["model_name"], gemini_case["support_structure_output"]
+    )
+
+    model_instance = get_model_instance()
+    model_instance.invoke_llm.return_value = LLMResult(
+        model="gemini-pro",
+        message=AssistantPromptMessage(content='{"result": "true"}'),
+        usage=create_mock_usage(prompt_tokens=10, completion_tokens=5),
+    )
+
+    prompt_messages = [UserPromptMessage(content="Test")]
+
+    result = invoke_llm_with_structured_output(
+        provider=gemini_case["provider"],
+        model_schema=model_schema,
+        model_instance=model_instance,
+        prompt_messages=prompt_messages,
+        json_schema=gemini_case["json_schema"],
+        stream=gemini_case["stream"],
+    )
+
+    assert isinstance(result, LLMResultWithStructuredOutput)
+
+    # Verify model_instance.invoke_llm was called and check the schema preparation
+    model_instance.invoke_llm.assert_called_once()
+    call_args = model_instance.invoke_llm.call_args
+
+    # For Gemini, the schema should not have additionalProperties and boolean should be converted to string
+    assert "json_schema" in call_args.kwargs["model_parameters"]

dev/mypy-check

@@ -7,4 +7,4 @@ cd "$SCRIPT_DIR/.."
 
 # run mypy checks
 uv run --directory api --dev --with pip \
-  python -m mypy --install-types --non-interactive ./
+  python -m mypy --install-types --non-interactive --exclude venv ./

docker/docker-compose-template.yaml

@@ -2,7 +2,7 @@ x-shared-env: &shared-api-worker-env
 services:
   # API service
   api:
-    image: langgenius/dify-api:1.5.0
+    image: langgenius/dify-api:1.5.1
     restart: always
     environment:
       # Use the shared environment variables.
@@ -31,7 +31,7 @@ services:
   # worker service
   # The Celery worker for processing the queue.
   worker:
-    image: langgenius/dify-api:1.5.0
+    image: langgenius/dify-api:1.5.1
     restart: always
     environment:
       # Use the shared environment variables.
@@ -57,7 +57,7 @@ services:
 
   # Frontend web application.
   web:
-    image: langgenius/dify-web:1.5.0
+    image: langgenius/dify-web:1.5.1
     restart: always
     environment:
       CONSOLE_API_URL: ${CONSOLE_API_URL:-}
@@ -142,7 +142,7 @@ services:
 
   # plugin daemon
   plugin_daemon:
-    image: langgenius/dify-plugin-daemon:0.1.2-local
+    image: langgenius/dify-plugin-daemon:0.1.3-local
     restart: always
     environment:
       # Use the shared environment variables.
@@ -168,7 +168,7 @@ services:
       PLUGIN_MEDIA_CACHE_PATH: ${PLUGIN_MEDIA_CACHE_PATH:-assets}
       PLUGIN_STORAGE_OSS_BUCKET: ${PLUGIN_STORAGE_OSS_BUCKET:-}
       S3_USE_AWS_MANAGED_IAM: ${PLUGIN_S3_USE_AWS_MANAGED_IAM:-false}
-      S3_USE_AWS: ${PLUGIN_S3_USE_AWS:-}
+      S3_USE_AWS: ${PLUGIN_S3_USE_AWS:-false}
       S3_ENDPOINT: ${PLUGIN_S3_ENDPOINT:-}
       S3_USE_PATH_STYLE: ${PLUGIN_S3_USE_PATH_STYLE:-false}
       AWS_ACCESS_KEY: ${PLUGIN_AWS_ACCESS_KEY:-}

docker/docker-compose.middleware.yaml

@@ -71,7 +71,7 @@ services:
 
   # plugin daemon
   plugin_daemon:
-    image: langgenius/dify-plugin-daemon:0.1.2-local
+    image: langgenius/dify-plugin-daemon:0.1.3-local
     restart: always
     env_file:
       - ./middleware.env

docker/docker-compose.yaml

@@ -517,7 +517,7 @@ x-shared-env: &shared-api-worker-env
 services:
   # API service
   api:
-    image: langgenius/dify-api:1.5.0
+    image: langgenius/dify-api:1.5.1
     restart: always
     environment:
       # Use the shared environment variables.
@@ -546,7 +546,7 @@ services:
   # worker service
   # The Celery worker for processing the queue.
   worker:
-    image: langgenius/dify-api:1.5.0
+    image: langgenius/dify-api:1.5.1
     restart: always
     environment:
       # Use the shared environment variables.
@@ -572,7 +572,7 @@ services:
 
   # Frontend web application.
   web:
-    image: langgenius/dify-web:1.5.0
+    image: langgenius/dify-web:1.5.1
     restart: always
     environment:
       CONSOLE_API_URL: ${CONSOLE_API_URL:-}
@@ -657,7 +657,7 @@ services:
 
   # plugin daemon
   plugin_daemon:
-    image: langgenius/dify-plugin-daemon:0.1.2-local
+    image: langgenius/dify-plugin-daemon:0.1.3-local
     restart: always
     environment:
       # Use the shared environment variables.
@@ -683,7 +683,7 @@ services:
       PLUGIN_MEDIA_CACHE_PATH: ${PLUGIN_MEDIA_CACHE_PATH:-assets}
       PLUGIN_STORAGE_OSS_BUCKET: ${PLUGIN_STORAGE_OSS_BUCKET:-}
       S3_USE_AWS_MANAGED_IAM: ${PLUGIN_S3_USE_AWS_MANAGED_IAM:-false}
-      S3_USE_AWS: ${PLUGIN_S3_USE_AWS:-}
+      S3_USE_AWS: ${PLUGIN_S3_USE_AWS:-false}
       S3_ENDPOINT: ${PLUGIN_S3_ENDPOINT:-}
       S3_USE_PATH_STYLE: ${PLUGIN_S3_USE_PATH_STYLE:-false}
       AWS_ACCESS_KEY: ${PLUGIN_AWS_ACCESS_KEY:-}

web/app/(commonLayout)/app/(appDetailLayout)/[appId]/overview/tracing/config-popup.tsx

@@ -5,7 +5,7 @@ import { useTranslation } from 'react-i18next'
 import { useBoolean } from 'ahooks'
 import TracingIcon from './tracing-icon'
 import ProviderPanel from './provider-panel'
-import type { LangFuseConfig, LangSmithConfig, OpikConfig, WeaveConfig } from './type'
+import type { ArizeConfig, LangFuseConfig, LangSmithConfig, OpikConfig, PhoenixConfig, WeaveConfig } from './type'
 import { TracingProvider } from './type'
 import ProviderConfigModal from './provider-config-modal'
 import Indicator from '@/app/components/header/indicator'
@@ -23,11 +23,13 @@ export type PopupProps = {
   onStatusChange: (enabled: boolean) => void
   chosenProvider: TracingProvider | null
   onChooseProvider: (provider: TracingProvider) => void
+  arizeConfig: ArizeConfig | null
+  phoenixConfig: PhoenixConfig | null
   langSmithConfig: LangSmithConfig | null
   langFuseConfig: LangFuseConfig | null
   opikConfig: OpikConfig | null
   weaveConfig: WeaveConfig | null
-  onConfigUpdated: (provider: TracingProvider, payload: LangSmithConfig | LangFuseConfig | OpikConfig | WeaveConfig) => void
+  onConfigUpdated: (provider: TracingProvider, payload: ArizeConfig | PhoenixConfig | LangSmithConfig | LangFuseConfig | OpikConfig | WeaveConfig) => void
   onConfigRemoved: (provider: TracingProvider) => void
 }
 
@@ -38,6 +40,8 @@ const ConfigPopup: FC<PopupProps> = ({
   onStatusChange,
   chosenProvider,
   onChooseProvider,
+  arizeConfig,
+  phoenixConfig,
   langSmithConfig,
   langFuseConfig,
   opikConfig,
@@ -65,7 +69,7 @@ const ConfigPopup: FC<PopupProps> = ({
     }
   }, [onChooseProvider])
 
-  const handleConfigUpdated = useCallback((payload: LangSmithConfig | LangFuseConfig | OpikConfig | WeaveConfig) => {
+  const handleConfigUpdated = useCallback((payload: ArizeConfig | PhoenixConfig | LangSmithConfig | LangFuseConfig | OpikConfig | WeaveConfig) => {
     onConfigUpdated(currentProvider!, payload)
     hideConfigModal()
   }, [currentProvider, hideConfigModal, onConfigUpdated])
@@ -75,8 +79,8 @@ const ConfigPopup: FC<PopupProps> = ({
     hideConfigModal()
   }, [currentProvider, hideConfigModal, onConfigRemoved])
 
-  const providerAllConfigured = langSmithConfig && langFuseConfig && opikConfig && weaveConfig
-  const providerAllNotConfigured = !langSmithConfig && !langFuseConfig && !opikConfig && !weaveConfig
+  const providerAllConfigured = arizeConfig && phoenixConfig && langSmithConfig && langFuseConfig && opikConfig && weaveConfig
+  const providerAllNotConfigured = !arizeConfig && !phoenixConfig && !langSmithConfig && !langFuseConfig && !opikConfig && !weaveConfig
 
   const switchContent = (
     <Switch
@@ -86,6 +90,32 @@ const ConfigPopup: FC<PopupProps> = ({
       disabled={providerAllNotConfigured}
     />
   )
+  const arizePanel = (
+    <ProviderPanel
+      type={TracingProvider.arize}
+      readOnly={readOnly}
+      config={arizeConfig}
+      hasConfigured={!!arizeConfig}
+      onConfig={handleOnConfig(TracingProvider.arize)}
+      isChosen={chosenProvider === TracingProvider.arize}
+      onChoose={handleOnChoose(TracingProvider.arize)}
+      key="arize-provider-panel"
+    />
+  )
+
+  const phoenixPanel = (
+    <ProviderPanel
+      type={TracingProvider.phoenix}
+      readOnly={readOnly}
+      config={phoenixConfig}
+      hasConfigured={!!phoenixConfig}
+      onConfig={handleOnConfig(TracingProvider.phoenix)}
+      isChosen={chosenProvider === TracingProvider.phoenix}
+      onChoose={handleOnChoose(TracingProvider.phoenix)}
+      key="phoenix-provider-panel"
+    />
+  )
+
   const langSmithPanel = (
     <ProviderPanel
       type={TracingProvider.langSmith}
@@ -152,12 +182,24 @@ const ConfigPopup: FC<PopupProps> = ({
     if (weaveConfig)
       configuredPanels.push(weavePanel)
 
+    if (arizeConfig)
+      configuredPanels.push(arizePanel)
+
+    if (phoenixConfig)
+      configuredPanels.push(phoenixPanel)
+
     return configuredPanels
   }
 
   const moreProviderPanel = () => {
     const notConfiguredPanels: JSX.Element[] = []
 
+    if (!arizeConfig)
+      notConfiguredPanels.push(arizePanel)
+
+    if (!phoenixConfig)
+      notConfiguredPanels.push(phoenixPanel)
+
     if (!langFuseConfig)
       notConfiguredPanels.push(langfusePanel)
 
@@ -174,6 +216,10 @@ const ConfigPopup: FC<PopupProps> = ({
   }
 
   const configuredProviderConfig = () => {
+    if (currentProvider === TracingProvider.arize)
+      return arizeConfig
+    if (currentProvider === TracingProvider.phoenix)
+      return phoenixConfig
     if (currentProvider === TracingProvider.langSmith)
       return langSmithConfig
     if (currentProvider === TracingProvider.langfuse)
@@ -220,22 +266,24 @@ const ConfigPopup: FC<PopupProps> = ({
           ? (
             <>
               <div className='system-xs-medium-uppercase text-text-tertiary'>{t(`${I18N_PREFIX}.configProviderTitle.${providerAllConfigured ? 'configured' : 'notConfigured'}`)}</div>
-              <div className='mt-2 space-y-2'>
+              <div className='mt-2 max-h-96 space-y-2 overflow-y-auto'>
                 {langfusePanel}
                 {langSmithPanel}
                 {opikPanel}
                 {weavePanel}
+                {arizePanel}
+                {phoenixPanel}
               </div>
             </>
           )
           : (
             <>
               <div className='system-xs-medium-uppercase text-text-tertiary'>{t(`${I18N_PREFIX}.configProviderTitle.configured`)}</div>
-              <div className='mt-2 space-y-2'>
+              <div className='mt-2 max-h-40 space-y-2 overflow-y-auto'>
                 {configuredProviderPanel()}
               </div>
               <div className='system-xs-medium-uppercase mt-3 text-text-tertiary'>{t(`${I18N_PREFIX}.configProviderTitle.moreProvider`)}</div>
-              <div className='mt-2 space-y-2'>
+              <div className='mt-2 max-h-40 space-y-2 overflow-y-auto'>
                 {moreProviderPanel()}
               </div>
             </>

web/app/(commonLayout)/app/(appDetailLayout)/[appId]/overview/tracing/config.ts

@@ -1,6 +1,8 @@
 import { TracingProvider } from './type'
 
 export const docURL = {
+  [TracingProvider.arize]: 'https://docs.arize.com/arize',
+  [TracingProvider.phoenix]: 'https://docs.arize.com/phoenix',
   [TracingProvider.langSmith]: 'https://docs.smith.langchain.com/',
   [TracingProvider.langfuse]: 'https://docs.langfuse.com',
   [TracingProvider.opik]: 'https://www.comet.com/docs/opik/tracing/integrations/dify#setup-instructions',

web/app/(commonLayout)/app/(appDetailLayout)/[appId]/overview/tracing/panel.tsx

@@ -7,12 +7,12 @@ import {
 import { useTranslation } from 'react-i18next'
 import { usePathname } from 'next/navigation'
 import { useBoolean } from 'ahooks'
-import type { LangFuseConfig, LangSmithConfig, OpikConfig, WeaveConfig } from './type'
+import type { ArizeConfig, LangFuseConfig, LangSmithConfig, OpikConfig, PhoenixConfig, WeaveConfig } from './type'
 import { TracingProvider } from './type'
 import TracingIcon from './tracing-icon'
 import ConfigButton from './config-button'
 import cn from '@/utils/classnames'
-import { LangfuseIcon, LangsmithIcon, OpikIcon, WeaveIcon } from '@/app/components/base/icons/src/public/tracing'
+import { ArizeIcon, LangfuseIcon, LangsmithIcon, OpikIcon, PhoenixIcon, WeaveIcon } from '@/app/components/base/icons/src/public/tracing'
 import Indicator from '@/app/components/header/indicator'
 import { fetchTracingConfig as doFetchTracingConfig, fetchTracingStatus, updateTracingStatus } from '@/service/apps'
 import type { TracingStatus } from '@/models/app'
@@ -62,24 +62,31 @@ const Panel: FC = () => {
   }
   const inUseTracingProvider: TracingProvider | null = tracingStatus?.tracing_provider || null
 
-  const InUseProviderIcon
-    = inUseTracingProvider === TracingProvider.langSmith
-      ? LangsmithIcon
-      : inUseTracingProvider === TracingProvider.langfuse
-        ? LangfuseIcon
-        : inUseTracingProvider === TracingProvider.opik
-          ? OpikIcon
-          : inUseTracingProvider === TracingProvider.weave
-            ? WeaveIcon
-            : LangsmithIcon
+  const providerIconMap: Record<TracingProvider, React.FC<{ className?: string }>> = {
+    [TracingProvider.arize]: ArizeIcon,
+    [TracingProvider.phoenix]: PhoenixIcon,
+    [TracingProvider.langSmith]: LangsmithIcon,
+    [TracingProvider.langfuse]: LangfuseIcon,
+    [TracingProvider.opik]: OpikIcon,
+    [TracingProvider.weave]: WeaveIcon,
+  }
+  const InUseProviderIcon = inUseTracingProvider ? providerIconMap[inUseTracingProvider] : undefined
 
+  const [arizeConfig, setArizeConfig] = useState<ArizeConfig | null>(null)
+  const [phoenixConfig, setPhoenixConfig] = useState<PhoenixConfig | null>(null)
   const [langSmithConfig, setLangSmithConfig] = useState<LangSmithConfig | null>(null)
   const [langFuseConfig, setLangFuseConfig] = useState<LangFuseConfig | null>(null)
   const [opikConfig, setOpikConfig] = useState<OpikConfig | null>(null)
   const [weaveConfig, setWeaveConfig] = useState<WeaveConfig | null>(null)
-  const hasConfiguredTracing = !!(langSmithConfig || langFuseConfig || opikConfig || weaveConfig)
+  const hasConfiguredTracing = !!(langSmithConfig || langFuseConfig || opikConfig || weaveConfig || arizeConfig || phoenixConfig)
 
   const fetchTracingConfig = async () => {
+    const { tracing_config: arizeConfig, has_not_configured: arizeHasNotConfig } = await doFetchTracingConfig({ appId, provider: TracingProvider.arize })
+    if (!arizeHasNotConfig)
+      setArizeConfig(arizeConfig as ArizeConfig)
+    const { tracing_config: phoenixConfig, has_not_configured: phoenixHasNotConfig } = await doFetchTracingConfig({ appId, provider: TracingProvider.phoenix })
+    if (!phoenixHasNotConfig)
+      setPhoenixConfig(phoenixConfig as PhoenixConfig)
     const { tracing_config: langSmithConfig, has_not_configured: langSmithHasNotConfig } = await doFetchTracingConfig({ appId, provider: TracingProvider.langSmith })
     if (!langSmithHasNotConfig)
       setLangSmithConfig(langSmithConfig as LangSmithConfig)
@@ -97,7 +104,11 @@ const Panel: FC = () => {
   const handleTracingConfigUpdated = async (provider: TracingProvider) => {
     // call api to hide secret key value
     const { tracing_config } = await doFetchTracingConfig({ appId, provider })
-    if (provider === TracingProvider.langSmith)
+    if (provider === TracingProvider.arize)
+      setArizeConfig(tracing_config as ArizeConfig)
+    else if (provider === TracingProvider.phoenix)
+      setPhoenixConfig(tracing_config as PhoenixConfig)
+    else if (provider === TracingProvider.langSmith)
       setLangSmithConfig(tracing_config as LangSmithConfig)
     else if (provider === TracingProvider.langfuse)
       setLangFuseConfig(tracing_config as LangFuseConfig)
@@ -108,7 +119,11 @@ const Panel: FC = () => {
   }
 
   const handleTracingConfigRemoved = (provider: TracingProvider) => {
-    if (provider === TracingProvider.langSmith)
+    if (provider === TracingProvider.arize)
+      setArizeConfig(null)
+    else if (provider === TracingProvider.phoenix)
+      setPhoenixConfig(null)
+    else if (provider === TracingProvider.langSmith)
       setLangSmithConfig(null)
     else if (provider === TracingProvider.langfuse)
       setLangFuseConfig(null)
@@ -170,6 +185,8 @@ const Panel: FC = () => {
                 onStatusChange={handleTracingEnabledChange}
                 chosenProvider={inUseTracingProvider}
                 onChooseProvider={handleChooseProvider}
+                arizeConfig={arizeConfig}
+                phoenixConfig={phoenixConfig}
                 langSmithConfig={langSmithConfig}
                 langFuseConfig={langFuseConfig}
                 opikConfig={opikConfig}
@@ -205,6 +222,8 @@ const Panel: FC = () => {
                 onStatusChange={handleTracingEnabledChange}
                 chosenProvider={inUseTracingProvider}
                 onChooseProvider={handleChooseProvider}
+                arizeConfig={arizeConfig}
+                phoenixConfig={phoenixConfig}
                 langSmithConfig={langSmithConfig}
                 langFuseConfig={langFuseConfig}
                 opikConfig={opikConfig}

web/app/(commonLayout)/app/(appDetailLayout)/[appId]/overview/tracing/provider-config-modal.tsx

@@ -4,7 +4,7 @@ import React, { useCallback, useState } from 'react'
 import { useTranslation } from 'react-i18next'
 import { useBoolean } from 'ahooks'
 import Field from './field'
-import type { LangFuseConfig, LangSmithConfig, OpikConfig, WeaveConfig } from './type'
+import type { ArizeConfig, LangFuseConfig, LangSmithConfig, OpikConfig, PhoenixConfig, WeaveConfig } from './type'
 import { TracingProvider } from './type'
 import { docURL } from './config'
 import {
@@ -22,15 +22,28 @@ import Divider from '@/app/components/base/divider'
 type Props = {
   appId: string
   type: TracingProvider
-  payload?: LangSmithConfig | LangFuseConfig | OpikConfig | WeaveConfig | null
+  payload?: ArizeConfig | PhoenixConfig | LangSmithConfig | LangFuseConfig | OpikConfig | WeaveConfig | null
   onRemoved: () => void
   onCancel: () => void
-  onSaved: (payload: LangSmithConfig | LangFuseConfig | OpikConfig | WeaveConfig) => void
+  onSaved: (payload: ArizeConfig | PhoenixConfig | LangSmithConfig | LangFuseConfig | OpikConfig | WeaveConfig) => void
   onChosen: (provider: TracingProvider) => void
 }
 
 const I18N_PREFIX = 'app.tracing.configProvider'
 
+const arizeConfigTemplate = {
+  api_key: '',
+  space_id: '',
+  project: '',
+  endpoint: '',
+}
+
+const phoenixConfigTemplate = {
+  api_key: '',
+  project: '',
+  endpoint: '',
+}
+
 const langSmithConfigTemplate = {
   api_key: '',
   project: '',
@@ -71,11 +84,17 @@ const ProviderConfigModal: FC<Props> = ({
   const isEdit = !!payload
   const isAdd = !isEdit
   const [isSaving, setIsSaving] = useState(false)
-  const [config, setConfig] = useState<LangSmithConfig | LangFuseConfig | OpikConfig | WeaveConfig>((() => {
+  const [config, setConfig] = useState<ArizeConfig | PhoenixConfig | LangSmithConfig | LangFuseConfig | OpikConfig | WeaveConfig>((() => {
     if (isEdit)
       return payload
 
-    if (type === TracingProvider.langSmith)
+    if (type === TracingProvider.arize)
+      return arizeConfigTemplate
+
+    else if (type === TracingProvider.phoenix)
+      return phoenixConfigTemplate
+
+    else if (type === TracingProvider.langSmith)
       return langSmithConfigTemplate
 
     else if (type === TracingProvider.langfuse)
@@ -115,6 +134,24 @@ const ProviderConfigModal: FC<Props> = ({
 
   const checkValid = useCallback(() => {
     let errorMessage = ''
+    if (type === TracingProvider.arize) {
+      const postData = config as ArizeConfig
+      if (!postData.api_key)
+        errorMessage = t('common.errorMsg.fieldRequired', { field: 'API Key' })
+      if (!postData.space_id)
+        errorMessage = t('common.errorMsg.fieldRequired', { field: 'Space ID' })
+      if (!errorMessage && !postData.project)
+        errorMessage = t('common.errorMsg.fieldRequired', { field: t(`${I18N_PREFIX}.project`) })
+    }
+
+    if (type === TracingProvider.phoenix) {
+      const postData = config as PhoenixConfig
+      if (!postData.api_key)
+        errorMessage = t('common.errorMsg.fieldRequired', { field: 'API Key' })
+      if (!errorMessage && !postData.project)
+        errorMessage = t('common.errorMsg.fieldRequired', { field: t(`${I18N_PREFIX}.project`) })
+    }
+
     if (type === TracingProvider.langSmith) {
       const postData = config as LangSmithConfig
       if (!postData.api_key)
@@ -195,6 +232,68 @@ const ProviderConfigModal: FC<Props> = ({
                     </div>
 
                     <div className='space-y-4'>
+                      {type === TracingProvider.arize && (
+                        <>
+                          <Field
+                            label='API Key'
+                            labelClassName='!text-sm'
+                            isRequired
+                            value={(config as ArizeConfig).api_key}
+                            onChange={handleConfigChange('api_key')}
+                            placeholder={t(`${I18N_PREFIX}.placeholder`, { key: 'API Key' })!}
+                          />
+                          <Field
+                            label='Space ID'
+                            labelClassName='!text-sm'
+                            isRequired
+                            value={(config as ArizeConfig).space_id}
+                            onChange={handleConfigChange('space_id')}
+                            placeholder={t(`${I18N_PREFIX}.placeholder`, { key: 'Space ID' })!}
+                          />
+                          <Field
+                            label={t(`${I18N_PREFIX}.project`)!}
+                            labelClassName='!text-sm'
+                            isRequired
+                            value={(config as ArizeConfig).project}
+                            onChange={handleConfigChange('project')}
+                            placeholder={t(`${I18N_PREFIX}.placeholder`, { key: t(`${I18N_PREFIX}.project`) })!}
+                          />
+                          <Field
+                            label='Endpoint'
+                            labelClassName='!text-sm'
+                            value={(config as ArizeConfig).endpoint}
+                            onChange={handleConfigChange('endpoint')}
+                            placeholder={'https://otlp.arize.com'}
+                          />
+                        </>
+                      )}
+                      {type === TracingProvider.phoenix && (
+                        <>
+                          <Field
+                            label='API Key'
+                            labelClassName='!text-sm'
+                            isRequired
+                            value={(config as PhoenixConfig).api_key}
+                            onChange={handleConfigChange('api_key')}
+                            placeholder={t(`${I18N_PREFIX}.placeholder`, { key: 'API Key' })!}
+                          />
+                          <Field
+                            label={t(`${I18N_PREFIX}.project`)!}
+                            labelClassName='!text-sm'
+                            isRequired
+                            value={(config as PhoenixConfig).project}
+                            onChange={handleConfigChange('project')}
+                            placeholder={t(`${I18N_PREFIX}.placeholder`, { key: t(`${I18N_PREFIX}.project`) })!}
+                          />
+                          <Field
+                            label='Endpoint'
+                            labelClassName='!text-sm'
+                            value={(config as PhoenixConfig).endpoint}
+                            onChange={handleConfigChange('endpoint')}
+                            placeholder={'https://app.phoenix.arize.com'}
+                          />
+                        </>
+                      )}
                       {type === TracingProvider.weave && (
                         <>
                           <Field

web/app/(commonLayout)/app/(appDetailLayout)/[appId]/overview/tracing/provider-panel.tsx

@@ -7,7 +7,7 @@ import {
 import { useTranslation } from 'react-i18next'
 import { TracingProvider } from './type'
 import cn from '@/utils/classnames'
-import { LangfuseIconBig, LangsmithIconBig, OpikIconBig, WeaveIconBig } from '@/app/components/base/icons/src/public/tracing'
+import { ArizeIconBig, LangfuseIconBig, LangsmithIconBig, OpikIconBig, PhoenixIconBig, WeaveIconBig } from '@/app/components/base/icons/src/public/tracing'
 import { Eye as View } from '@/app/components/base/icons/src/vender/solid/general'
 
 const I18N_PREFIX = 'app.tracing'
@@ -24,6 +24,8 @@ type Props = {
 
 const getIcon = (type: TracingProvider) => {
   return ({
+    [TracingProvider.arize]: ArizeIconBig,
+    [TracingProvider.phoenix]: PhoenixIconBig,
     [TracingProvider.langSmith]: LangsmithIconBig,
     [TracingProvider.langfuse]: LangfuseIconBig,
     [TracingProvider.opik]: OpikIconBig,

web/app/(commonLayout)/app/(appDetailLayout)/[appId]/overview/tracing/type.ts

@@ -1,10 +1,25 @@
 export enum TracingProvider {
+  arize = 'arize',
+  phoenix = 'phoenix',
   langSmith = 'langsmith',
   langfuse = 'langfuse',
   opik = 'opik',
   weave = 'weave',
 }
 
+export type ArizeConfig = {
+  api_key: string
+  space_id: string
+  project: string
+  endpoint: string
+}
+
+export type PhoenixConfig = {
+  api_key: string
+  project: string
+  endpoint: string
+}
+
 export type LangSmithConfig = {
   api_key: string
   project: string

web/app/(commonLayout)/apps/AppCard.tsx

@@ -36,6 +36,7 @@ import AccessControl from '@/app/components/app/app-access-control'
 import { AccessMode } from '@/models/access-control'
 import { useGlobalPublicStore } from '@/context/global-public-context'
 import { formatTime } from '@/utils/time'
+import { useGetUserCanAccessApp } from '@/service/access-control'
 
 export type AppCardProps = {
   app: App
@@ -190,6 +191,7 @@ const AppCard = ({ app, onRefresh }: AppCardProps) => {
   }, [onRefresh, mutateApps, setShowAccessControl])
 
   const Operations = (props: HtmlContentProps) => {
+    const { data: userCanAccessApp, isLoading: isGettingUserCanAccessApp } = useGetUserCanAccessApp({ appId: app?.id, enabled: (!!props?.open && systemFeatures.webapp_auth.enabled) })
     const onMouseLeave = async () => {
       props.onClose?.()
     }
@@ -267,10 +269,14 @@ const AppCard = ({ app, onRefresh }: AppCardProps) => {
             </button>
           </>
         )}
-        <Divider className="my-1" />
-        <button className='mx-1 flex h-8 cursor-pointer items-center gap-2 rounded-lg px-3 hover:bg-state-base-hover' onClick={onClickInstalledApp}>
-          <span className='system-sm-regular text-text-secondary'>{t('app.openInExplore')}</span>
-        </button>
+        {
+          (isGettingUserCanAccessApp || !userCanAccessApp?.result) ? null : <>
+            <Divider className="my-1" />
+            <button className='mx-1 flex h-8 cursor-pointer items-center gap-2 rounded-lg px-3 hover:bg-state-base-hover' onClick={onClickInstalledApp}>
+              <span className='system-sm-regular text-text-secondary'>{t('app.openInExplore')}</span>
+            </button>
+          </>
+        }
         <Divider className="my-1" />
         {
           systemFeatures.webapp_auth.enabled && isCurrentWorkspaceEditor && <>
@@ -333,7 +339,7 @@ const AppCard = ({ app, onRefresh }: AppCardProps) => {
             <div className='flex items-center gap-1 text-[10px] font-medium leading-[18px] text-text-tertiary'>
               <div className='truncate' title={app.author_name}>{app.author_name}</div>
               <div>·</div>
-              <div className='truncate'>{EditTimeText}</div>
+              <div className='truncate' title={EditTimeText}>{EditTimeText}</div>
             </div>
           </div>
           <div className='flex h-5 w-5 shrink-0 items-center justify-center'>

web/app/(commonLayout)/datasets/template/template.en.mdx

@@ -1124,6 +1124,129 @@ import { Row, Col, Properties, Property, Heading, SubProperty, PropertyInstructi
 
 <hr className='ml-0 mr-0' />
 
+<Heading
+  url='/datasets/{dataset_id}/documents/{document_id}'
+  method='GET'
+  title='Get Document Detail'
+  name='#get-document-detail'
+/>
+<Row>
+  <Col>
+  Get a document's detail.
+  ### Path
+  - `dataset_id` (string) Dataset ID
+  - `document_id` (string) Document ID
+
+  ### Query
+  - `metadata` (string) Metadata filter, can be `all`, `only`, or `without`. Default is `all`.
+
+  ### Response
+  Returns the document's detail.
+  </Col>
+  <Col sticky>
+  ### Request Example
+  <CodeGroup title="Request" tag="GET" label="/datasets/{dataset_id}/documents/{document_id}" targetCode={`curl -X GET '${props.apiBaseUrl}/datasets/{dataset_id}/documents/{document_id}' \\\n-H 'Authorization: Bearer {api_key}'`}>
+    ```bash {{ title: 'cURL' }}
+    curl -X GET '${props.apiBaseUrl}/datasets/{dataset_id}/documents/{document_id}' \
+    -H 'Authorization: Bearer {api_key}'
+    ```
+    </CodeGroup>
+
+    ### Response Example
+    <CodeGroup title="Response">
+    ```json {{ title: 'Response' }}
+    {
+    "id": "f46ae30c-5c11-471b-96d0-464f5f32a7b2", 
+    "position": 1, 
+    "data_source_type": "upload_file", 
+    "data_source_info": {
+        "upload_file": {
+            ...
+        }
+    }, 
+    "dataset_process_rule_id": "24b99906-845e-499f-9e3c-d5565dd6962c", 
+    "dataset_process_rule": {
+        "mode": "hierarchical", 
+        "rules": {
+            "pre_processing_rules": [
+                {
+                    "id": "remove_extra_spaces", 
+                    "enabled": true
+                }, 
+                {
+                    "id": "remove_urls_emails", 
+                    "enabled": false
+                }
+            ], 
+            "segmentation": {
+                "separator": "**********page_ending**********", 
+                "max_tokens": 1024, 
+                "chunk_overlap": 0
+            }, 
+            "parent_mode": "paragraph", 
+            "subchunk_segmentation": {
+                "separator": "\n", 
+                "max_tokens": 512, 
+                "chunk_overlap": 0
+            }
+        }
+    }, 
+    "document_process_rule": {
+        "id": "24b99906-845e-499f-9e3c-d5565dd6962c", 
+        "dataset_id": "48a0db76-d1a9-46c1-ae35-2baaa919a8a9", 
+        "mode": "hierarchical", 
+        "rules": {
+            "pre_processing_rules": [
+                {
+                    "id": "remove_extra_spaces", 
+                    "enabled": true
+                }, 
+                {
+                    "id": "remove_urls_emails", 
+                    "enabled": false
+                }
+            ], 
+            "segmentation": {
+                "separator": "**********page_ending**********", 
+                "max_tokens": 1024, 
+                "chunk_overlap": 0
+            }, 
+            "parent_mode": "paragraph", 
+            "subchunk_segmentation": {
+                "separator": "\n", 
+                "max_tokens": 512, 
+                "chunk_overlap": 0
+            }
+        }
+    }, 
+    "name": "xxxx", 
+    "created_from": "web", 
+    "created_by": "17f71940-a7b5-4c77-b60f-2bd645c1ffa0", 
+    "created_at": 1750464191, 
+    "tokens": null, 
+    "indexing_status": "waiting", 
+    "completed_at": null, 
+    "updated_at": 1750464191, 
+    "indexing_latency": null, 
+    "error": null, 
+    "enabled": true, 
+    "disabled_at": null, 
+    "disabled_by": null, 
+    "archived": false, 
+    "segment_count": 0, 
+    "average_segment_length": 0, 
+    "hit_count": null, 
+    "display_status": "queuing", 
+    "doc_form": "hierarchical_model", 
+    "doc_language": "Chinese Simplified"
+    }
+    ```
+    </CodeGroup>
+  </Col>
+</Row>
+___
+<hr className='ml-0 mr-0' />
+
 <Heading
   url='/datasets/{dataset_id}/documents/status/{action}'
   method='PATCH'

web/app/(commonLayout)/datasets/template/template.ja.mdx

@@ -881,6 +881,130 @@ import { Row, Col, Properties, Property, Heading, SubProperty, PropertyInstructi
 
 <hr className='ml-0 mr-0' />
 
+<Heading
+  url='/datasets/{dataset_id}/documents/{document_id}'
+  method='GET'
+  title='ドキュメントの詳細を取得'
+  name='#get-document-detail'
+/>
+<Row>
+  <Col>
+  ドキュメントの詳細を取得.
+  ### Path
+  - `dataset_id` (string) ナレッジベースID
+  - `document_id` (string) ドキュメントID
+
+  ### Query
+  - `metadata` (string) metadataのフィルター条件 `all`、`only`、または`without`。デフォルトは `all`。
+
+  ### Response
+  ナレッジベースドキュメントの詳細を返す.
+  </Col>
+ <Col sticky>
+  ### Request Example
+  <CodeGroup title="Request" tag="GET" label="/datasets/{dataset_id}/documents/{document_id}" targetCode={`curl -X GET '${props.apiBaseUrl}/datasets/{dataset_id}/documents/{document_id}' \\\n-H 'Authorization: Bearer {api_key}'`}>
+    ```bash {{ title: 'cURL' }}
+    curl -X GET '${props.apiBaseUrl}/datasets/{dataset_id}/documents/{document_id}' \
+    -H 'Authorization: Bearer {api_key}'
+    ```
+    </CodeGroup>
+
+    ### Response Example
+    <CodeGroup title="Response">
+    ```json {{ title: 'Response' }}
+    {
+    "id": "f46ae30c-5c11-471b-96d0-464f5f32a7b2", 
+    "position": 1, 
+    "data_source_type": "upload_file", 
+    "data_source_info": {
+        "upload_file": {
+            ...
+        }
+    }, 
+    "dataset_process_rule_id": "24b99906-845e-499f-9e3c-d5565dd6962c", 
+    "dataset_process_rule": {
+        "mode": "hierarchical", 
+        "rules": {
+            "pre_processing_rules": [
+                {
+                    "id": "remove_extra_spaces", 
+                    "enabled": true
+                }, 
+                {
+                    "id": "remove_urls_emails", 
+                    "enabled": false
+                }
+            ], 
+            "segmentation": {
+                "separator": "**********page_ending**********", 
+                "max_tokens": 1024, 
+                "chunk_overlap": 0
+            }, 
+            "parent_mode": "paragraph", 
+            "subchunk_segmentation": {
+                "separator": "\n", 
+                "max_tokens": 512, 
+                "chunk_overlap": 0
+            }
+        }
+    }, 
+    "document_process_rule": {
+        "id": "24b99906-845e-499f-9e3c-d5565dd6962c", 
+        "dataset_id": "48a0db76-d1a9-46c1-ae35-2baaa919a8a9", 
+        "mode": "hierarchical", 
+        "rules": {
+            "pre_processing_rules": [
+                {
+                    "id": "remove_extra_spaces", 
+                    "enabled": true
+                }, 
+                {
+                    "id": "remove_urls_emails", 
+                    "enabled": false
+                }
+            ], 
+            "segmentation": {
+                "separator": "**********page_ending**********", 
+                "max_tokens": 1024, 
+                "chunk_overlap": 0
+            }, 
+            "parent_mode": "paragraph", 
+            "subchunk_segmentation": {
+                "separator": "\n", 
+                "max_tokens": 512, 
+                "chunk_overlap": 0
+            }
+        }
+    }, 
+    "name": "xxxx", 
+    "created_from": "web", 
+    "created_by": "17f71940-a7b5-4c77-b60f-2bd645c1ffa0", 
+    "created_at": 1750464191, 
+    "tokens": null, 
+    "indexing_status": "waiting", 
+    "completed_at": null, 
+    "updated_at": 1750464191, 
+    "indexing_latency": null, 
+    "error": null, 
+    "enabled": true, 
+    "disabled_at": null, 
+    "disabled_by": null, 
+    "archived": false, 
+    "segment_count": 0, 
+    "average_segment_length": 0, 
+    "hit_count": null, 
+    "display_status": "queuing", 
+    "doc_form": "hierarchical_model", 
+    "doc_language": "Chinese Simplified"
+    }
+    ```
+    </CodeGroup>
+  </Col>
+</Row>
+___
+<hr className='ml-0 mr-0' />
+
+
 <Heading
   url='/datasets/{dataset_id}/documents/status/{action}'
   method='PATCH'

web/app/(commonLayout)/datasets/template/template.zh.mdx

@@ -1131,6 +1131,130 @@ import { Row, Col, Properties, Property, Heading, SubProperty, PropertyInstructi
 
 <hr className='ml-0 mr-0' />
 
+<Heading
+  url='/datasets/{dataset_id}/documents/{document_id}'
+  method='GET'
+  title='获取文档详情'
+  name='#get-document-detail'
+/>
+<Row>
+  <Col>
+  获取文档详情.
+  ### Path
+  - `dataset_id` (string) 知识库 ID
+  - `document_id` (string) 文档 ID
+
+  ### Query
+  - `metadata` (string) metadata 过滤条件 `all`, `only`, 或者 `without`. 默认是 `all`.
+
+  ### Response
+  返回知识库文档的详情.
+  </Col>
+  <Col sticky>
+  ### Request Example
+  <CodeGroup title="Request" tag="GET" label="/datasets/{dataset_id}/documents/{document_id}" targetCode={`curl -X GET '${props.apiBaseUrl}/datasets/{dataset_id}/documents/{document_id}' \\\n-H 'Authorization: Bearer {api_key}'`}>
+    ```bash {{ title: 'cURL' }}
+    curl -X GET '${props.apiBaseUrl}/datasets/{dataset_id}/documents/{document_id}' \
+    -H 'Authorization: Bearer {api_key}'
+    ```
+    </CodeGroup>
+
+    ### Response Example
+    <CodeGroup title="Response">
+    ```json {{ title: 'Response' }}
+    {
+    "id": "f46ae30c-5c11-471b-96d0-464f5f32a7b2", 
+    "position": 1, 
+    "data_source_type": "upload_file", 
+    "data_source_info": {
+        "upload_file": {
+            ...
+        }
+    }, 
+    "dataset_process_rule_id": "24b99906-845e-499f-9e3c-d5565dd6962c", 
+    "dataset_process_rule": {
+        "mode": "hierarchical", 
+        "rules": {
+            "pre_processing_rules": [
+                {
+                    "id": "remove_extra_spaces", 
+                    "enabled": true
+                }, 
+                {
+                    "id": "remove_urls_emails", 
+                    "enabled": false
+                }
+            ], 
+            "segmentation": {
+                "separator": "**********page_ending**********", 
+                "max_tokens": 1024, 
+                "chunk_overlap": 0
+            }, 
+            "parent_mode": "paragraph", 
+            "subchunk_segmentation": {
+                "separator": "\n", 
+                "max_tokens": 512, 
+                "chunk_overlap": 0
+            }
+        }
+    }, 
+    "document_process_rule": {
+        "id": "24b99906-845e-499f-9e3c-d5565dd6962c", 
+        "dataset_id": "48a0db76-d1a9-46c1-ae35-2baaa919a8a9", 
+        "mode": "hierarchical", 
+        "rules": {
+            "pre_processing_rules": [
+                {
+                    "id": "remove_extra_spaces", 
+                    "enabled": true
+                }, 
+                {
+                    "id": "remove_urls_emails", 
+                    "enabled": false
+                }
+            ], 
+            "segmentation": {
+                "separator": "**********page_ending**********", 
+                "max_tokens": 1024, 
+                "chunk_overlap": 0
+            }, 
+            "parent_mode": "paragraph", 
+            "subchunk_segmentation": {
+                "separator": "\n", 
+                "max_tokens": 512, 
+                "chunk_overlap": 0
+            }
+        }
+    }, 
+    "name": "xxxx", 
+    "created_from": "web", 
+    "created_by": "17f71940-a7b5-4c77-b60f-2bd645c1ffa0", 
+    "created_at": 1750464191, 
+    "tokens": null, 
+    "indexing_status": "waiting", 
+    "completed_at": null, 
+    "updated_at": 1750464191, 
+    "indexing_latency": null, 
+    "error": null, 
+    "enabled": true, 
+    "disabled_at": null, 
+    "disabled_by": null, 
+    "archived": false, 
+    "segment_count": 0, 
+    "average_segment_length": 0, 
+    "hit_count": null, 
+    "display_status": "queuing", 
+    "doc_form": "hierarchical_model", 
+    "doc_language": "Chinese Simplified"
+    }
+    ```
+    </CodeGroup>
+  </Col>
+</Row>
+___
+<hr className='ml-0 mr-0' />
+
+
 <Heading
   url='/datasets/{dataset_id}/documents/status/{action}'
   method='PATCH'

web/app/(shareLayout)/layout.tsx

@@ -25,10 +25,13 @@ const Layout: FC<{
       }
 
       let appCode: string | null = null
-      if (redirectUrl)
-        appCode = redirectUrl?.split('/').pop() || null
-      else
+      if (redirectUrl) {
+        const url = new URL(`${window.location.origin}${decodeURIComponent(redirectUrl)}`)
+        appCode = url.pathname.split('/').pop() || null
+      }
+      else {
         appCode = pathname.split('/').pop() || null
+      }
 
       if (!appCode)
         return

web/app/(shareLayout)/webapp-signin/check-code/page.tsx

@@ -25,7 +25,10 @@ export default function CheckCode() {
   const redirectUrl = searchParams.get('redirect_url')
 
   const getAppCodeFromRedirectUrl = useCallback(() => {
-    const appCode = redirectUrl?.split('/').pop()
+    if (!redirectUrl)
+      return null
+    const url = new URL(`${window.location.origin}${decodeURIComponent(redirectUrl)}`)
+    const appCode = url.pathname.split('/').pop()
     if (!appCode)
       return null
 
@@ -62,7 +65,7 @@ export default function CheckCode() {
         localStorage.setItem('webapp_access_token', ret.data.access_token)
         const tokenResp = await fetchAccessToken({ appCode, webAppAccessToken: ret.data.access_token })
         await setAccessToken(appCode, tokenResp.access_token)
-        router.replace(redirectUrl)
+        router.replace(decodeURIComponent(redirectUrl))
       }
     }
     catch (error) { console.error(error) }

web/app/(shareLayout)/webapp-signin/components/external-member-sso-auth.tsx

@@ -23,7 +23,10 @@ const ExternalMemberSSOAuth = () => {
   }
 
   const getAppCodeFromRedirectUrl = useCallback(() => {
-    const appCode = redirectUrl?.split('/').pop()
+    if (!redirectUrl)
+      return null
+    const url = new URL(`${window.location.origin}${decodeURIComponent(redirectUrl)}`)
+    const appCode = url.pathname.split('/').pop()
     if (!appCode)
       return null
 

web/app/(shareLayout)/webapp-signin/components/mail-and-password-auth.tsx

@@ -1,3 +1,4 @@
+'use client'
 import Link from 'next/link'
 import { useCallback, useState } from 'react'
 import { useTranslation } from 'react-i18next'
@@ -33,7 +34,10 @@ export default function MailAndPasswordAuth({ isEmailSetup }: MailAndPasswordAut
   const redirectUrl = searchParams.get('redirect_url')
 
   const getAppCodeFromRedirectUrl = useCallback(() => {
-    const appCode = redirectUrl?.split('/').pop()
+    if (!redirectUrl)
+      return null
+    const url = new URL(`${window.location.origin}${decodeURIComponent(redirectUrl)}`)
+    const appCode = url.pathname.split('/').pop()
     if (!appCode)
       return null
 
@@ -87,7 +91,7 @@ export default function MailAndPasswordAuth({ isEmailSetup }: MailAndPasswordAut
         localStorage.setItem('webapp_access_token', res.data.access_token)
         const tokenResp = await fetchAccessToken({ appCode, webAppAccessToken: res.data.access_token })
         await setAccessToken(appCode, tokenResp.access_token)
-        router.replace(redirectUrl)
+        router.replace(decodeURIComponent(redirectUrl))
       }
       else {
         Toast.notify({

web/app/(shareLayout)/webapp-signin/components/sso-auth.tsx

@@ -23,7 +23,10 @@ const SSOAuth: FC<SSOAuthProps> = ({
 
   const redirectUrl = searchParams.get('redirect_url')
   const getAppCodeFromRedirectUrl = useCallback(() => {
-    const appCode = redirectUrl?.split('/').pop()
+    if (!redirectUrl)
+      return null
+    const url = new URL(`${window.location.origin}${decodeURIComponent(redirectUrl)}`)
+    const appCode = url.pathname.split('/').pop()
     if (!appCode)
       return null
 

web/app/(shareLayout)/webapp-signin/page.tsx

@@ -46,7 +46,10 @@ const WebSSOForm: FC = () => {
   }
 
   const getAppCodeFromRedirectUrl = useCallback(() => {
-    const appCode = redirectUrl?.split('/').pop()
+    if (!redirectUrl)
+      return null
+    const url = new URL(`${window.location.origin}${decodeURIComponent(redirectUrl)}`)
+    const appCode = url.pathname.split('/').pop()
     if (!appCode)
       return null
 
@@ -63,20 +66,20 @@ const WebSSOForm: FC = () => {
         localStorage.setItem('webapp_access_token', tokenFromUrl)
         const tokenResp = await fetchAccessToken({ appCode, webAppAccessToken: tokenFromUrl })
         await setAccessToken(appCode, tokenResp.access_token)
-        router.replace(redirectUrl)
+        router.replace(decodeURIComponent(redirectUrl))
         return
       }
       if (appCode && redirectUrl && localStorage.getItem('webapp_access_token')) {
         const tokenResp = await fetchAccessToken({ appCode, webAppAccessToken: localStorage.getItem('webapp_access_token') })
         await setAccessToken(appCode, tokenResp.access_token)
-        router.replace(redirectUrl)
+        router.replace(decodeURIComponent(redirectUrl))
       }
     })()
   }, [getAppCodeFromRedirectUrl, redirectUrl, router, tokenFromUrl, message])
 
   useEffect(() => {
     if (webAppAccessMode && webAppAccessMode === AccessMode.PUBLIC && redirectUrl)
-      router.replace(redirectUrl)
+      router.replace(decodeURIComponent(redirectUrl))
   }, [webAppAccessMode, router, redirectUrl])
 
   if (tokenFromUrl) {

web/app/components/app/configuration/config-var/select-var-type.tsx

@@ -2,7 +2,6 @@
 import type { FC } from 'react'
 import React, { useState } from 'react'
 import { useTranslation } from 'react-i18next'
-import cn from '@/utils/classnames'
 import OperationBtn from '@/app/components/app/configuration/base/operation-btn'
 import {
   PortalToFollowElem,
@@ -28,11 +27,11 @@ type ItemProps = {
 const SelectItem: FC<ItemProps> = ({ text, type, value, Icon, onClick }) => {
   return (
     <div
-      className='flex h-8 cursor-pointer items-center rounded-lg px-3 hover:bg-gray-50'
+      className='flex h-8 cursor-pointer items-center rounded-lg px-3 hover:bg-state-base-hover'
       onClick={() => onClick(value)}
     >
-      {Icon ? <Icon className='h-4 w-4 text-gray-500' /> : <InputVarTypeIcon type={type!} className='h-4 w-4 text-gray-500' />}
-      <div className='ml-2 truncate text-xs text-gray-600'>{text}</div>
+      {Icon ? <Icon className='h-4 w-4 text-text-secondary' /> : <InputVarTypeIcon type={type!} className='h-4 w-4 text-text-secondary' />}
+      <div className='ml-2 truncate text-xs text-text-primary'>{text}</div>
     </div>
   )
 }
@@ -57,17 +56,17 @@ const SelectVarType: FC<Props> = ({
       }}
     >
       <PortalToFollowElemTrigger onClick={() => setOpen(v => !v)}>
-        <OperationBtn type='add' className={cn(open && 'bg-gray-200')} />
+        <OperationBtn type='add' />
       </PortalToFollowElemTrigger>
       <PortalToFollowElemContent style={{ zIndex: 1000 }}>
-        <div className='min-w-[192px] rounded-lg border border-gray-200 bg-white shadow-lg'>
+        <div className='min-w-[192px] rounded-lg border border-components-panel-border bg-components-panel-bg-blur shadow-lg backdrop-blur-sm'>
           <div className='p-1'>
             <SelectItem type={InputVarType.textInput} value='string' text={t('appDebug.variableConfig.string')} onClick={handleChange}></SelectItem>
             <SelectItem type={InputVarType.paragraph} value='paragraph' text={t('appDebug.variableConfig.paragraph')} onClick={handleChange}></SelectItem>
             <SelectItem type={InputVarType.select} value='select' text={t('appDebug.variableConfig.select')} onClick={handleChange}></SelectItem>
             <SelectItem type={InputVarType.number} value='number' text={t('appDebug.variableConfig.number')} onClick={handleChange}></SelectItem>
           </div>
-          <div className='h-[1px] bg-gray-100'></div>
+          <div className='h-[1px] border-t border-components-panel-border'></div>
           <div className='p-1'>
             <SelectItem Icon={ApiConnection} value='api' text={t('appDebug.variableConfig.apiBasedVar')} onClick={handleChange}></SelectItem>
           </div>

web/app/components/app/configuration/index.tsx

@@ -80,6 +80,8 @@ import {
 import PluginDependency from '@/app/components/workflow/plugin-dependency'
 import { supportFunctionCall } from '@/utils/tool-call'
 import { MittProvider } from '@/context/mitt-context'
+import { fetchAndMergeValidCompletionParams } from '@/utils/completion-params'
+import Toast from '@/app/components/base/toast'
 
 type PublishConfig = {
   modelConfig: ModelConfig
@@ -453,7 +455,21 @@ const Configuration: FC = () => {
       ...visionConfig,
       enabled: supportVision,
     }, true)
-    setCompletionParams({})
+
+    try {
+      const { params: filtered, removedDetails } = await fetchAndMergeValidCompletionParams(
+        provider,
+        modelId,
+        completionParams,
+      )
+      if (Object.keys(removedDetails).length)
+        Toast.notify({ type: 'warning', message: `${t('common.modelProvider.parametersInvalidRemoved')}: ${Object.entries(removedDetails).map(([k, reason]) => `${k} (${reason})`).join(', ')}` })
+      setCompletionParams(filtered)
+    }
+    catch (e) {
+      Toast.notify({ type: 'error', message: t('common.error') })
+      setCompletionParams({})
+    }
   }
 
   const isShowVisionConfig = !!currModel?.features?.includes(ModelFeatureEnum.vision)

web/app/components/base/button/sync-button.tsx

@@ -0,0 +1,27 @@
+'use client'
+import type { FC } from 'react'
+import React from 'react'
+import { RiRefreshLine } from '@remixicon/react'
+import cn from '@/utils/classnames'
+import TooltipPlus from '@/app/components/base/tooltip'
+
+type Props = {
+  className?: string,
+  popupContent?: string,
+  onClick: () => void
+}
+
+const SyncButton: FC<Props> = ({
+  className,
+  popupContent = '',
+  onClick,
+}) => {
+  return (
+    <TooltipPlus popupContent={popupContent}>
+      <div className={cn(className, 'cursor-pointer select-none rounded-md p-1 hover:bg-state-base-hover')} onClick={onClick}>
+        <RiRefreshLine className='h-4 w-4 text-text-tertiary' />
+      </div>
+    </TooltipPlus>
+  )
+}
+export default React.memo(SyncButton)

web/app/components/base/icons/assets/public/tracing/arize-icon-big.svg

@@ -0,0 +1,17 @@
+<svg id="Layer_2" data-name="Layer 2" xmlns="http://www.w3.org/2000/svg" viewBox="0 0 111 24" width="111" height="24">
+  <g id="Layer_1-2" data-name="Layer 1">
+    <rect style="fill: none;" y="0" width="111" height="24"/>
+    <g id="Arize_-_standard" data-name="Arize - standard">
+      <g>
+        <path d="M100.94,14.55h-11.29c0,.13-.01.23.02.31.53,1.55,1.54,2.59,3.19,2.88,1.7.29,3.22,0,4.3-1.52.09-.13.28-.27.43-.28.99-.02,1.99-.01,2.99-.01-.16,2.69-3.89,4.98-7.6,4.7-3.99-.3-6.91-3.79-6.58-7.88.37-4.62,3.67-7.31,8.37-6.85,4.05.4,6.68,4.04,6.19,8.64ZM89.71,11.66h7.96c-.43-1.88-2.04-3.02-4.17-2.97-1.87.04-3.48,1.3-3.78,2.97Z"/>
+        <path style="fill: #ff008c;" d="M20.81,2.53c.59-.03,1.11.26,1.49.8,3.05,4.38,6.09,8.77,9.13,13.16.63.91.43,1.99-.43,2.59-.84.59-1.97.35-2.62-.57-2.1-3.01-4.19-6.04-6.28-9.05-.04-.06-.08-.11-.12-.17-.83-1.17-1.65-1.18-2.47,0-2.11,3.05-4.23,6.09-6.34,9.14-.35.5-.77.88-1.4.95-.77.08-1.39-.19-1.79-.86-.41-.69-.38-1.38.07-2.03,1.01-1.47,2.04-2.93,3.06-4.4,2.01-2.89,4.03-5.77,6.03-8.67.39-.56.88-.9,1.67-.89Z"/>
+        <path d="M52.84,20.43h-3.02v-1.16c-.1.02-.16.01-.19.03-2.46,1.73-5.09,1.88-7.68.51-2.61-1.38-3.71-3.77-3.68-6.67.03-3.26,1.82-5.96,4.64-6.86,2.35-.75,4.64-.67,6.69.93.04.03.09.03.2.07v-1.18h3.03v14.31ZM41.36,13.32c.01.17.02.46.05.75.22,2.09,1.76,3.58,3.91,3.76,2.1.18,3.8-.95,4.38-2.96.14-.47.2-.98.22-1.47.13-3.22-2.25-5.27-5.33-4.61-1.92.41-3.19,2.14-3.23,4.53Z"/>
+        <path d="M80.41,8.9h-7.44v-2.77h11.64c0,.81.02,1.61-.01,2.41,0,.17-.19.35-.32.51-2.28,2.68-4.57,5.36-6.85,8.04-.11.13-.21.26-.38.47h7.53v2.86h-11.74c0-.82-.02-1.62.01-2.42,0-.16.17-.33.28-.47,2.32-2.74,4.64-5.47,6.96-8.21.09-.1.16-.21.32-.42Z"/>
+        <path d="M59.39,20.54h-3.03V6.22h3.03v1.54c.8-.48,1.55-1.01,2.37-1.41.85-.41,1.79-.41,2.77-.35v2.94c-.16.01-.3.03-.45.03-2.37.03-4.01,1.36-4.51,3.69-.12.57-.16,1.16-.16,1.74-.02,1.85,0,3.71,0,5.56v.57Z"/>
+        <path d="M67.1,6.09h2.99v14.33h-2.99V6.09Z"/>
+        <path style="fill: #ff008c;" d="M20.73,19.53c1.25,0,2.24.96,2.25,2.19.01,1.24-1.02,2.29-2.24,2.28-1.23-.01-2.21-1.01-2.22-2.24,0-1.25.96-2.22,2.21-2.22Z"/>
+        <path d="M70.7,2.11c0,1.19-.92,2.14-2.09,2.15-1.19.01-2.16-.95-2.16-2.14C66.46.95,67.4,0,68.58,0c1.18,0,2.12.93,2.12,2.11Z"/>
+      </g>
+    </g>
+  </g>
+</svg>

web/app/components/base/icons/assets/public/tracing/arize-icon.svg

@@ -0,0 +1,17 @@
+<svg id="Layer_2" data-name="Layer 2" xmlns="http://www.w3.org/2000/svg" viewBox="0 0 74 16" width="74" height="16">
+  <g id="Layer_1-2" data-name="Layer 1">
+    <rect style="fill: none;" y="0" width="74" height="16"/>
+    <g id="Arize_-_standard" data-name="Arize - standard">
+      <g>
+        <path d="M67.29,9.7h-7.52c0,.08,0,.15.01.21.35,1.03,1.03,1.73,2.13,1.92,1.13.19,2.14,0,2.86-1.01.06-.09.19-.18.29-.19.66-.02,1.33,0,1.99,0-.1,1.79-2.59,3.32-5.07,3.14-2.66-.2-4.61-2.53-4.39-5.25.25-3.08,2.44-4.88,5.58-4.56,2.7.27,4.45,2.69,4.12,5.76ZM59.81,7.77h5.3c-.28-1.25-1.36-2.01-2.78-1.98-1.25.03-2.32.87-2.52,1.98Z"/>
+        <path style="fill: #ff008c;" d="M13.87,1.69c.4-.02.74.17.99.54,2.03,2.92,4.06,5.85,6.08,8.77.42.61.28,1.33-.29,1.73-.56.39-1.31.24-1.74-.38-1.4-2.01-2.79-4.02-4.19-6.04-.03-.04-.05-.08-.08-.11-.55-.78-1.1-.78-1.64,0-1.41,2.03-2.82,4.06-4.23,6.09-.23.34-.52.59-.93.63-.51.06-.92-.13-1.19-.57-.28-.46-.25-.92.05-1.35.68-.98,1.36-1.96,2.04-2.93,1.34-1.93,2.68-3.85,4.02-5.78.26-.37.59-.6,1.11-.59Z"/>
+        <path d="M35.23,13.62h-2.01v-.77c-.07.01-.1,0-.13.02-1.64,1.16-3.39,1.25-5.12.34-1.74-.92-2.47-2.51-2.45-4.45.02-2.17,1.22-3.97,3.1-4.57,1.57-.5,3.09-.45,4.46.62.02.02.06.02.14.05v-.79h2.02v9.54ZM27.57,8.88c0,.11.01.31.03.5.14,1.39,1.18,2.39,2.61,2.51,1.4.12,2.53-.63,2.92-1.97.09-.32.14-.65.15-.98.09-2.15-1.5-3.51-3.56-3.07-1.28.27-2.13,1.43-2.15,3.02Z"/>
+        <path d="M53.61,5.93h-4.96v-1.85h7.76c0,.54.01,1.07,0,1.61,0,.12-.12.24-.21.34-1.52,1.79-3.05,3.57-4.57,5.36-.07.09-.14.18-.26.32h5.02v1.91h-7.83c0-.54-.01-1.08,0-1.61,0-.11.11-.22.19-.31,1.55-1.83,3.1-3.65,4.64-5.47.06-.07.11-.14.21-.28Z"/>
+        <path d="M39.6,13.69h-2.02V4.15h2.02v1.03c.54-.32,1.04-.68,1.58-.94.57-.28,1.19-.27,1.85-.23v1.96c-.1,0-.2.02-.3.02-1.58.02-2.68.9-3.01,2.46-.08.38-.11.77-.11,1.16-.01,1.24,0,2.47,0,3.71v.38Z"/>
+        <path d="M44.74,4.06h1.99v9.56h-1.99V4.06Z"/>
+        <path style="fill: #ff008c;" d="M13.82,13.02c.84,0,1.49.64,1.5,1.46,0,.83-.68,1.53-1.5,1.52-.82,0-1.47-.67-1.48-1.5,0-.83.64-1.48,1.47-1.48Z"/>
+        <path d="M47.13,1.41c0,.8-.61,1.43-1.39,1.43-.8,0-1.44-.63-1.44-1.43,0-.78.63-1.41,1.42-1.41.79,0,1.41.62,1.41,1.41Z"/>
+      </g>
+    </g>
+  </g>
+</svg>

web/app/components/base/icons/assets/public/tracing/phoenix-icon-big.svg

@@ -0,0 +1,97 @@
+<svg id="Layer_2" data-name="Layer 2" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" viewBox="0 0 111 24" width="111" height="24">
+  <defs>
+    <linearGradient id="linear-gradient" x1="9.07" y1="1.47" x2="19.77" y2="20" gradientUnits="userSpaceOnUse">
+      <stop offset="0" stop-color="#11bab5"/>
+      <stop offset=".5" stop-color="#00adee"/>
+      <stop offset="1" stop-color="#0094c5"/>
+    </linearGradient>
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+      <path style="fill: #e5b3a5;" d="M15.35,8.91s0,0,.01,0h0s0,0-.01,0M14.52,8.58s0,0,0,0c0,0,0,0,0,0M14.39,8.51s.01.06.04.08c.01,0,.02.01.03.01.02,0,.04,0,.05-.02-.02.01-.04.02-.05.02-.01,0-.02,0-.03-.01-.03-.02-.04-.05-.04-.08M14.46,8.33s0,0,0,.01c0,0,0,0,0-.01M14.48,8.26s-.02.05-.03.07c0-.02.02-.05.03-.07M14.49,8.25s0,0,0,0c0,0,0,0,0,0M15.63,8.25s0,0,0,0c0,0,0,0,0,0M15.64,8.24s0,0,0,0c0,0,0,0,0,0M14.49,8.24s0,0,0,0c0,0,0,0,0,0M13.4,8.21c0,.07.03.13.13.16.03.01.06.01.08.01.09,0,.13-.06.16-.13-.03.07-.07.13-.16.13-.02,0-.05,0-.08-.01-.1-.03-.13-.09-.13-.16M12.57,8.11h0,0M12.74,8.04s-.08.07-.14.07c0,0-.01,0-.02,0,0,0,.01,0,.02,0,.07,0,.11-.03.14-.07M14.05,7.54s0,0,0,0c-.03.1-.06.2-.1.3-.04.11-.09.22-.14.33h0c.05-.11.1-.22.14-.33.04-.1.07-.2.1-.3M12.87,7.49c-.02.11-.03.22-.05.33.02-.11.04-.22.06-.33h0M15.52,6.97s0,0,0,0c-.15.49-.38.95-.75,1.36-.04.05-.09.1-.14.14h0s.09-.09.14-.14c.37-.41.6-.87.75-1.36"/>
+      <path style="fill: url(#linear-gradient-2); opacity: .4;" d="M4.17,2.09s-.04,0-.06.01c-.1.04-.12.14-.13.25.52.68,2.56,3.18,5.78,4.9,0,0,3.15,1.66,6.32,1.84-.25-.03-.46-.09-.67-.16-.01,0-.02,0-.04-.01h0c-1.15-.25-2.13-.56-2.83-.81.01,0,.03,0,.04,0-.01,0-.03,0-.04,0-.04,0-.07-.02-.1-.04-.55-.2-.9-.35-.98-.39-.04-.02-.08-.04-.12-.05-2.08-.86-3.86-2.07-5.42-3.6-.61-.62-1.65-1.88-1.65-1.88h0s-.06-.05-.1-.05"/>
+      <path style="fill: url(#linear-gradient-3); opacity: .4;" d="M4.39,4.75s-.01,0-.02,0c-.1.02-.12.12-.14.21,0,.02,0,.03,0,.05,1.61,2.18,3.77,3.07,3.77,3.07,2.15,1.01,3.92,1.22,5,1.22.45,0,.77-.04.96-.06-.09,0-.18.01-.28.01-.63,0-1.53-.17-2.29-.35-.46-.1-.92-.22-1.36-.36-.02,0-.03,0-.03,0h0c-1.73-.55-3.32-1.44-4.7-2.81-.13-.13-.25-.27-.37-.41-.11-.13-.34-.4-.41-.5,0-.01-.02-.02-.03-.03h0s0,0,0,0c-.02-.02-.04-.03-.07-.03"/>
+      <path style="fill: url(#linear-gradient-4); opacity: .4" d="M5.86,8.53s-.05,0-.08.03c-.11.08-.06.22-.02.35.81.49,2.66,1.44,4.84,1.44.83,0,1.7-.14,2.59-.48-.64.21-1.3.28-1.96.28-.07,0-.15,0-.22,0-1.43-.04-2.77-.38-4.03-.99-.46-.24-.9-.5-1.01-.58-.04-.03-.08-.05-.12-.05"/>
+      <path style="fill: url(#linear-gradient-5); opacity: .4;" d="M13.34,10.6c-.35.27-.75.46-1.16.61-.77.28-1.55.41-2.32.41-.67,0-1.33-.09-1.99-.26-.46-.12-.99-.32-.99-.32h0s-.07-.03-.1-.03c-.04,0-.08.02-.11.06-.05.07-.05.14-.04.21.51.24,1.6.66,2.93.66,1.15,0,2.49-.32,3.78-1.34"/>
+      <path style="fill: url(#linear-gradient-6); opacity: .4;" d="M9.91,12.25c-1.25,0-2.19-.25-2.31-.29.04.01.07.02.1.03.11.04-.19.24-.29.31-.35.27-.69.52-1.04.77h1.06c.33-.25.67-.5.99-.75.12-.1.24-.13.37-.13.1,0,.2.02.33.05-.73.55-1.4,1.06-2.08,1.57-.4.3-.79.6-1.19.9h1.07c.96-.72,1.92-1.44,2.87-2.16.22-.17.44-.28.71-.32-.2.01-.4.02-.58.02Z"/>
+      <path style="fill: url(#Fade_to_Black_2); opacity: .4;" d="M9.69,13.1h1.03l.76-.6s.35-.25.76-.49c.04-.02.07-.05.11-.07.02,0,.05-.02.11-.05.04-.02.09-.05.13-.07.07-.03.15-.08.23-.12-.73.31-1.49.46-2.18.52,0,0,.02,0,.03,0,.06,0,.12,0,.18.01-.38.29-.75.56-1.11.83l-.06.05Z"/>
+      <path style="fill: url(#linear-gradient-7); opacity: .4;" d="M12.35,7.89c0-.09,0-.19,0-.28h0s0,0,0,0c0-.01,0-.03,0-.04h0s0-.02,0-.02c0-.08,0-.16-.02-.23-.25-.1-.48-.24-.69-.39,0,.02,0,.04,0,.07.03.19.02.13.04.29.01.08.03.23.03.28,0,.04-.01.08-.04.11-.03.03-.06.04-.09.04-.04,0-.09-.02-.13-.03.08.04.43.19.98.39-.06-.04-.08-.09-.08-.18Z"/>
+      <path style="fill: url(#linear-gradient-8); opacity: .4;" d="M16.36,6.14c-.23.32-.51.6-.84.83-.15.49-.38.95-.75,1.36-.04.05-.09.1-.14.14-.05.04-.11.12-.17.12-.01,0-.02,0-.03-.01-.08-.06,0-.18.02-.24.14-.32.24-.65.32-.98-.23.09-.47.15-.72.18-.03.1-.06.2-.1.3-.04.11-.09.22-.14.33-.05.1-.08.21-.2.21-.02,0-.05,0-.08-.01-.18-.06-.13-.19-.1-.31.03-.16.06-.32.08-.49-.22,0-.43-.04-.64-.08-.02.13-.04.26-.07.39-.02.09-.05.24-.21.24-.02,0-.04,0-.06,0,.69.25,1.68.56,2.83.81h0s-.02,0-.03-.01c-.18-.08.15-.41.3-.64.43-.66.64-1.37.73-2.12Z"/>
+      <path style="fill: url(#Fade_to_Black_2-2); opacity: .5;" d="M16.19,9.7c-.14,0-.29.01-.43.04-.03,0-.05,0-.08,0-.04,0-.08,0-.11-.02,0,0,.01.01.02.02.06.09.1.18.11.28.02.02.03.04.04.07h0s0,0,0,0c0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0h0s0,0,0,0c0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0t0,0s0,0,0,0c0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0s0,0,0,0c0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0s0,0,0,0c0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0h0s0,0,0,0h0s0,0,0,0h0s0,0,0,0h0s0,0,0,0h0s0,0,0,0h0s0,0,0,0h0s0,0,0,0h0s0,0,0,0c0,0,0,0,0,0,0,0,0,0,0,0h0s0,0,0,0h0s0,0,0,0h0s0,0,0,0h0s0,0,0,0h0s0,0,0,0h0s0,0,0,0h0s0,0,0,0h0s0,0,0,0h0s0,.05,0,.07c0,.04,0,.07,0,.11,0,.05-.01.1-.02.14,0,0,0,.01,0,.02,0,.03.02.06.04.08h.02s.03.02.05.02c.03,0,.06-.01.08-.03.01-.01.02-.03.04-.04.15-.15.3-.26.45-.33.12-.05.23-.07.35-.07s.24.02.36.07c.12.05.23.11.34.19.05.03.1.07.14.12.03.03.06.05.08.08h0s.02.02.02.02h.01s.04.03.06.03c-.1-.21-.22-.41-.4-.56-.33-.29-.75-.41-1.18-.41"/>
+      <path style="fill: url(#linear-gradient-9); opacity: .4;" d="M16.15,8.3h-.02s-.08.05-.08.09c0,.03,0,.07,0,.11,0,.01,0,.02,0,.03.18.26.56.73,1.15.91,0,0,.91.47.68,1.16h0v-.02c.08-.21.09-.4.05-.59-.04-.19-.14-.36-.28-.51-.06-.06-.12-.11-.19-.16-.03-.02-.07-.05-.1-.07-.04-.03-.09-.05-.14-.08-.19-.09-.34-.19-.48-.29-.06-.04-.11-.09-.16-.13-.12-.11-.21-.2-.27-.3-.02-.03-.04-.07-.05-.1,0-.01-.02-.03-.03-.04-.02-.01-.04-.02-.06-.02"/>
+      <path style="fill: url(#linear-gradient-10); opacity: .5;" d="M15,10.21l.18-.11.77-1.03s-.42-.08-.63-.17c0,0-.21.96-.99,1.77l.29-.21c.11-.08.22-.15.38-.25Z"/>
+      <g>
+        <path style="fill: #404041;" d="M25.33,4.73h1.97c1.42,0,2.07.73,2.07,2.23v.74c0,1.5-.65,2.23-2.07,2.23h-1.14v4.09h-.82V4.73ZM27.3,9.19c.86,0,1.25-.39,1.25-1.44v-.84c0-1.04-.39-1.44-1.25-1.44h-1.14v3.71h1.14Z"/>
+        <path style="fill: #404041;" d="M32.4,4.73h.82v4.08h2.54v-4.08h.82v9.3h-.82v-4.48h-2.54v4.48h-.82V4.73Z"/>
+        <path style="fill: #404041;" d="M39.82,11.9v-5.02c0-1.48.74-2.27,2.09-2.27s2.09.8,2.09,2.27v5.02c0,1.48-.74,2.27-2.09,2.27s-2.09-.8-2.09-2.27ZM43.17,11.95v-5.13c0-1-.45-1.48-1.26-1.48s-1.26.48-1.26,1.48v5.13c0,1,.45,1.46,1.26,1.46s1.26-.47,1.26-1.46Z"/>
+        <path style="fill: #404041;" d="M47.23,4.73h3.72v.74h-2.9v3.34h2.38v.74h-2.38v3.72h2.9v.76h-3.72V4.73Z"/>
+        <path style="fill: #404041;" d="M53.93,4.73h1.09l2.42,7.19v-7.19h.77v9.3h-.88l-2.64-7.93v7.93h-.76V4.73Z"/>
+        <path style="fill: #404041;" d="M61.55,4.73h.82v9.3h-.82V4.73Z"/>
+        <path style="fill: #404041;" d="M67.19,9.29l-1.82-4.56h.88l1.46,3.69,1.48-3.69h.8l-1.82,4.56,1.9,4.74h-.88l-1.54-3.91-1.55,3.91h-.8l1.9-4.74Z"/>
+      </g>
+    </g>
+  </g>
+</svg>

web/app/components/base/icons/src/public/tracing/ArizeIcon.json

@@ -0,0 +1,122 @@
+{
+	"icon": {
+		"type": "element",
+		"isRootNode": true,
+		"name": "svg",
+		"attributes": {
+			"id": "Layer_2",
+			"data-name": "Layer 2",
+			"xmlns": "http://www.w3.org/2000/svg",
+			"viewBox": "0 0 74 16",
+			"width": "74",
+			"height": "16"
+		},
+		"children": [
+			{
+				"type": "element",
+				"name": "g",
+				"attributes": {
+					"id": "Layer_1-2",
+					"data-name": "Layer 1"
+				},
+				"children": [
+					{
+						"type": "element",
+						"name": "rect",
+						"attributes": {
+							"style": "fill: none;",
+							"y": "0",
+							"width": "74",
+							"height": "16"
+						},
+						"children": []
+					},
+					{
+						"type": "element",
+						"name": "g",
+						"attributes": {
+							"id": "Arize_-_standard",
+							"data-name": "Arize - standard"
+						},
+						"children": [
+							{
+								"type": "element",
+								"name": "g",
+								"attributes": {},
+								"children": [
+									{
+										"type": "element",
+										"name": "path",
+										"attributes": {
+											"d": "M67.29,9.7h-7.52c0,.08,0,.15.01.21.35,1.03,1.03,1.73,2.13,1.92,1.13.19,2.14,0,2.86-1.01.06-.09.19-.18.29-.19.66-.02,1.33,0,1.99,0-.1,1.79-2.59,3.32-5.07,3.14-2.66-.2-4.61-2.53-4.39-5.25.25-3.08,2.44-4.88,5.58-4.56,2.7.27,4.45,2.69,4.12,5.76ZM59.81,7.77h5.3c-.28-1.25-1.36-2.01-2.78-1.98-1.25.03-2.32.87-2.52,1.98Z"
+										},
+										"children": []
+									},
+									{
+										"type": "element",
+										"name": "path",
+										"attributes": {
+											"style": "fill: #ff008c;",
+											"d": "M13.87,1.69c.4-.02.74.17.99.54,2.03,2.92,4.06,5.85,6.08,8.77.42.61.28,1.33-.29,1.73-.56.39-1.31.24-1.74-.38-1.4-2.01-2.79-4.02-4.19-6.04-.03-.04-.05-.08-.08-.11-.55-.78-1.1-.78-1.64,0-1.41,2.03-2.82,4.06-4.23,6.09-.23.34-.52.59-.93.63-.51.06-.92-.13-1.19-.57-.28-.46-.25-.92.05-1.35.68-.98,1.36-1.96,2.04-2.93,1.34-1.93,2.68-3.85,4.02-5.78.26-.37.59-.6,1.11-.59Z"
+										},
+										"children": []
+									},
+									{
+										"type": "element",
+										"name": "path",
+										"attributes": {
+											"d": "M35.23,13.62h-2.01v-.77c-.07.01-.1,0-.13.02-1.64,1.16-3.39,1.25-5.12.34-1.74-.92-2.47-2.51-2.45-4.45.02-2.17,1.22-3.97,3.1-4.57,1.57-.5,3.09-.45,4.46.62.02.02.06.02.14.05v-.79h2.02v9.54ZM27.57,8.88c0,.11.01.31.03.5.14,1.39,1.18,2.39,2.61,2.51,1.4.12,2.53-.63,2.92-1.97.09-.32.14-.65.15-.98.09-2.15-1.5-3.51-3.56-3.07-1.28.27-2.13,1.43-2.15,3.02Z"
+										},
+										"children": []
+									},
+									{
+										"type": "element",
+										"name": "path",
+										"attributes": {
+											"d": "M53.61,5.93h-4.96v-1.85h7.76c0,.54.01,1.07,0,1.61,0,.12-.12.24-.21.34-1.52,1.79-3.05,3.57-4.57,5.36-.07.09-.14.18-.26.32h5.02v1.91h-7.83c0-.54-.01-1.08,0-1.61,0-.11.11-.22.19-.31,1.55-1.83,3.1-3.65,4.64-5.47.06-.07.11-.14.21-.28Z"
+										},
+										"children": []
+									},
+									{
+										"type": "element",
+										"name": "path",
+										"attributes": {
+											"d": "M39.6,13.69h-2.02V4.15h2.02v1.03c.54-.32,1.04-.68,1.58-.94.57-.28,1.19-.27,1.85-.23v1.96c-.1,0-.2.02-.3.02-1.58.02-2.68.9-3.01,2.46-.08.38-.11.77-.11,1.16-.01,1.24,0,2.47,0,3.71v.38Z"
+										},
+										"children": []
+									},
+									{
+										"type": "element",
+										"name": "path",
+										"attributes": {
+											"d": "M44.74,4.06h1.99v9.56h-1.99V4.06Z"
+										},
+										"children": []
+									},
+									{
+										"type": "element",
+										"name": "path",
+										"attributes": {
+											"style": "fill: #ff008c;",
+											"d": "M13.82,13.02c.84,0,1.49.64,1.5,1.46,0,.83-.68,1.53-1.5,1.52-.82,0-1.47-.67-1.48-1.5,0-.83.64-1.48,1.47-1.48Z"
+										},
+										"children": []
+									},
+									{
+										"type": "element",
+										"name": "path",
+										"attributes": {
+											"d": "M47.13,1.41c0,.8-.61,1.43-1.39,1.43-.8,0-1.44-.63-1.44-1.43,0-.78.63-1.41,1.42-1.41.79,0,1.41.62,1.41,1.41Z"
+										},
+										"children": []
+									}
+								]
+							}
+						]
+					}
+				]
+			}
+		]
+	},
+	"name": "ArizeIcon"
+}

web/app/components/base/icons/src/public/tracing/ArizeIcon.tsx

@@ -0,0 +1,20 @@
+// GENERATE BY script
+// DON NOT EDIT IT MANUALLY
+
+import * as React from 'react'
+import data from './ArizeIcon.json'
+import IconBase from '@/app/components/base/icons/IconBase'
+import type { IconData } from '@/app/components/base/icons/IconBase'
+
+const Icon = (
+  {
+    ref,
+    ...props
+  }: React.SVGProps<SVGSVGElement> & {
+    ref?: React.RefObject<React.MutableRefObject<HTMLOrSVGElement>>;
+  },
+) => <IconBase {...props} ref={ref} data={data as IconData} />
+
+Icon.displayName = 'ArizeIcon'
+
+export default Icon

web/app/components/base/icons/src/public/tracing/ArizeIconBig.json

@@ -0,0 +1,122 @@
+{
+	"icon": {
+		"type": "element",
+		"isRootNode": true,
+		"name": "svg",
+		"attributes": {
+			"id": "Layer_2",
+			"data-name": "Layer 2",
+			"xmlns": "http://www.w3.org/2000/svg",
+			"viewBox": "0 0 111 24",
+			"width": "111",
+			"height": "24"
+		},
+		"children": [
+			{
+				"type": "element",
+				"name": "g",
+				"attributes": {
+					"id": "Layer_1-2",
+					"data-name": "Layer 1"
+				},
+				"children": [
+					{
+						"type": "element",
+						"name": "rect",
+						"attributes": {
+							"style": "fill: none;",
+							"y": "0",
+							"width": "111",
+							"height": "24"
+						},
+						"children": []
+					},
+					{
+						"type": "element",
+						"name": "g",
+						"attributes": {
+							"id": "Arize_-_standard",
+							"data-name": "Arize - standard"
+						},
+						"children": [
+							{
+								"type": "element",
+								"name": "g",
+								"attributes": {},
+								"children": [
+									{
+										"type": "element",
+										"name": "path",
+										"attributes": {
+											"d": "M100.94,14.55h-11.29c0,.13-.01.23.02.31.53,1.55,1.54,2.59,3.19,2.88,1.7.29,3.22,0,4.3-1.52.09-.13.28-.27.43-.28.99-.02,1.99-.01,2.99-.01-.16,2.69-3.89,4.98-7.6,4.7-3.99-.3-6.91-3.79-6.58-7.88.37-4.62,3.67-7.31,8.37-6.85,4.05.4,6.68,4.04,6.19,8.64ZM89.71,11.66h7.96c-.43-1.88-2.04-3.02-4.17-2.97-1.87.04-3.48,1.3-3.78,2.97Z"
+										},
+										"children": []
+									},
+									{
+										"type": "element",
+										"name": "path",
+										"attributes": {
+											"style": "fill: #ff008c;",
+											"d": "M20.81,2.53c.59-.03,1.11.26,1.49.8,3.05,4.38,6.09,8.77,9.13,13.16.63.91.43,1.99-.43,2.59-.84.59-1.97.35-2.62-.57-2.1-3.01-4.19-6.04-6.28-9.05-.04-.06-.08-.11-.12-.17-.83-1.17-1.65-1.18-2.47,0-2.11,3.05-4.23,6.09-6.34,9.14-.35.5-.77.88-1.4.95-.77.08-1.39-.19-1.79-.86-.41-.69-.38-1.38.07-2.03,1.01-1.47,2.04-2.93,3.06-4.4,2.01-2.89,4.03-5.77,6.03-8.67.39-.56.88-.9,1.67-.89Z"
+										},
+										"children": []
+									},
+									{
+										"type": "element",
+										"name": "path",
+										"attributes": {
+											"d": "M52.84,20.43h-3.02v-1.16c-.1.02-.16.01-.19.03-2.46,1.73-5.09,1.88-7.68.51-2.61-1.38-3.71-3.77-3.68-6.67.03-3.26,1.82-5.96,4.64-6.86,2.35-.75,4.64-.67,6.69.93.04.03.09.03.2.07v-1.18h3.03v14.31ZM41.36,13.32c.01.17.02.46.05.75.22,2.09,1.76,3.58,3.91,3.76,2.1.18,3.8-.95,4.38-2.96.14-.47.2-.98.22-1.47.13-3.22-2.25-5.27-5.33-4.61-1.92.41-3.19,2.14-3.23,4.53Z"
+										},
+										"children": []
+									},
+									{
+										"type": "element",
+										"name": "path",
+										"attributes": {
+											"d": "M80.41,8.9h-7.44v-2.77h11.64c0,.81.02,1.61-.01,2.41,0,.17-.19.35-.32.51-2.28,2.68-4.57,5.36-6.85,8.04-.11.13-.21.26-.38.47h7.53v2.86h-11.74c0-.82-.02-1.62.01-2.42,0-.16.17-.33.28-.47,2.32-2.74,4.64-5.47,6.96-8.21.09-.1.16-.21.32-.42Z"
+										},
+										"children": []
+									},
+									{
+										"type": "element",
+										"name": "path",
+										"attributes": {
+											"d": "M59.39,20.54h-3.03V6.22h3.03v1.54c.8-.48,1.55-1.01,2.37-1.41.85-.41,1.79-.41,2.77-.35v2.94c-.16.01-.3.03-.45.03-2.37.03-4.01,1.36-4.51,3.69-.12.57-.16,1.16-.16,1.74-.02,1.85,0,3.71,0,5.56v.57Z"
+										},
+										"children": []
+									},
+									{
+										"type": "element",
+										"name": "path",
+										"attributes": {
+											"d": "M67.1,6.09h2.99v14.33h-2.99V6.09Z"
+										},
+										"children": []
+									},
+									{
+										"type": "element",
+										"name": "path",
+										"attributes": {
+											"style": "fill: #ff008c;",
+											"d": "M20.73,19.53c1.25,0,2.24.96,2.25,2.19.01,1.24-1.02,2.29-2.24,2.28-1.23-.01-2.21-1.01-2.22-2.24,0-1.25.96-2.22,2.21-2.22Z"
+										},
+										"children": []
+									},
+									{
+										"type": "element",
+										"name": "path",
+										"attributes": {
+											"d": "M70.7,2.11c0,1.19-.92,2.14-2.09,2.15-1.19.01-2.16-.95-2.16-2.14C66.46.95,67.4,0,68.58,0c1.18,0,2.12.93,2.12,2.11Z"
+										},
+										"children": []
+									}
+								]
+							}
+						]
+					}
+				]
+			}
+		]
+	},
+	"name": "ArizeIconBig"
+}

web/app/components/base/icons/src/public/tracing/ArizeIconBig.tsx

@@ -0,0 +1,20 @@
+// GENERATE BY script
+// DON NOT EDIT IT MANUALLY
+
+import * as React from 'react'
+import data from './ArizeIconBig.json'
+import IconBase from '@/app/components/base/icons/IconBase'
+import type { IconData } from '@/app/components/base/icons/IconBase'
+
+const Icon = (
+  {
+    ref,
+    ...props
+  }: React.SVGProps<SVGSVGElement> & {
+    ref?: React.RefObject<React.MutableRefObject<HTMLOrSVGElement>>;
+  },
+) => <IconBase {...props} ref={ref} data={data as IconData} />
+
+Icon.displayName = 'ArizeIconBig'
+
+export default Icon

web/app/components/base/icons/src/public/tracing/PhoenixIcon.json

@@ -0,0 +1,853 @@
+{
+	"icon": {
+		"type": "element",
+		"isRootNode": true,
+		"name": "svg",
+		"attributes": {
+			"id": "Layer_2",
+			"data-name": "Layer 2",
+			"xmlns": "http://www.w3.org/2000/svg",
+			"xmlns:xlink": "http://www.w3.org/1999/xlink",
+			"viewBox": "0 0 74 16",
+			"width": "74",
+			"height": "16"
+		},
+		"children": [
+			{
+				"type": "element",
+				"name": "defs",
+				"attributes": {},
+				"children": [
+					{
+						"type": "element",
+						"name": "linearGradient",
+						"attributes": {
+							"id": "linear-gradient",
+							"x1": "6.05",
+							"y1": ".98",
+							"x2": "13.18",
+							"y2": "13.34",
+							"gradientUnits": "userSpaceOnUse"
+						},
+						"children": [
+							{
+								"type": "element",
+								"name": "stop",
+								"attributes": {
+									"offset": "0",
+									"stop-color": "#11bab5"
+								},
+								"children": []
+							},
+							{
+								"type": "element",
+								"name": "stop",
+								"attributes": {
+									"offset": ".5",
+									"stop-color": "#00adee"
+								},
+								"children": []
+							},
+							{
+								"type": "element",
+								"name": "stop",
+								"attributes": {
+									"offset": "1",
+									"stop-color": "#0094c5"
+								},
+								"children": []
+							}
+						]
+					},
+					{
+						"type": "element",
+						"name": "linearGradient",
+						"attributes": {
+							"id": "linear-gradient-2",
+							"x1": "12.99",
+							"y1": "10.87",
+							"x2": "6.97",
+							"y2": ".45",
+							"gradientUnits": "userSpaceOnUse"
+						},
+						"children": [
+							{
+								"type": "element",
+								"name": "stop",
+								"attributes": {
+									"offset": "0",
+									"stop-color": "#fcfdff",
+									"stop-opacity": "0"
+								},
+								"children": []
+							},
+							{
+								"type": "element",
+								"name": "stop",
+								"attributes": {
+									"offset": ".12",
+									"stop-color": "#fcfdff",
+									"stop-opacity": ".17"
+								},
+								"children": []
+							},
+							{
+								"type": "element",
+								"name": "stop",
+								"attributes": {
+									"offset": ".3",
+									"stop-color": "#fcfdff",
+									"stop-opacity": ".42"
+								},
+								"children": []
+							},
+							{
+								"type": "element",
+								"name": "stop",
+								"attributes": {
+									"offset": ".47",
+									"stop-color": "#fcfdff",
+									"stop-opacity": ".63"
+								},
+								"children": []
+							},
+							{
+								"type": "element",
+								"name": "stop",
+								"attributes": {
+									"offset": ".64",
+									"stop-color": "#fcfdff",
+									"stop-opacity": ".79"
+								},
+								"children": []
+							},
+							{
+								"type": "element",
+								"name": "stop",
+								"attributes": {
+									"offset": ".78",
+									"stop-color": "#fcfdff",
+									"stop-opacity": ".9"
+								},
+								"children": []
+							},
+							{
+								"type": "element",
+								"name": "stop",
+								"attributes": {
+									"offset": ".91",
+									"stop-color": "#fcfdff",
+									"stop-opacity": ".97"
+								},
+								"children": []
+							},
+							{
+								"type": "element",
+								"name": "stop",
+								"attributes": {
+									"offset": "1",
+									"stop-color": "#fcfdff"
+								},
+								"children": []
+							}
+						]
+					},
+					{
+						"type": "element",
+						"name": "linearGradient",
+						"attributes": {
+							"id": "linear-gradient-3",
+							"x1": "11.21",
+							"y1": "10.8",
+							"x2": "6.88",
+							"y2": "3.29",
+							"xlink:href": "#linear-gradient-2"
+						},
+						"children": []
+					},
+					{
+						"type": "element",
+						"name": "linearGradient",
+						"attributes": {
+							"id": "linear-gradient-4",
+							"x1": "10.62",
+							"y1": "11.35",
+							"x2": "8.2",
+							"y2": "7.16",
+							"xlink:href": "#linear-gradient-2"
+						},
+						"children": []
+					},
+					{
+						"type": "element",
+						"name": "linearGradient",
+						"attributes": {
+							"id": "linear-gradient-5",
+							"x1": "10.72",
+							"y1": "12.2",
+							"x2": "9.21",
+							"y2": "9.59",
+							"xlink:href": "#linear-gradient-2"
+						},
+						"children": []
+					},
+					{
+						"type": "element",
+						"name": "linearGradient",
+						"attributes": {
+							"id": "linear-gradient-6",
+							"x1": "8.17",
+							"y1": "11.96",
+							"x2": "8.17",
+							"y2": "14.71",
+							"gradientUnits": "userSpaceOnUse"
+						},
+						"children": [
+							{
+								"type": "element",
+								"name": "stop",
+								"attributes": {
+									"offset": "0",
+									"stop-color": "#231f20"
+								},
+								"children": []
+							},
+							{
+								"type": "element",
+								"name": "stop",
+								"attributes": {
+									"offset": ".03",
+									"stop-color": "#231f20",
+									"stop-opacity": ".9"
+								},
+								"children": []
+							},
+							{
+								"type": "element",
+								"name": "stop",
+								"attributes": {
+									"offset": ".22",
+									"stop-color": "#231f20",
+									"stop-opacity": ".4"
+								},
+								"children": []
+							},
+							{
+								"type": "element",
+								"name": "stop",
+								"attributes": {
+									"offset": ".42",
+									"stop-color": "#231f20",
+									"stop-opacity": ".1"
+								},
+								"children": []
+							},
+							{
+								"type": "element",
+								"name": "stop",
+								"attributes": {
+									"offset": ".65",
+									"stop-color": "#231f20",
+									"stop-opacity": "0"
+								},
+								"children": []
+							}
+						]
+					},
+					{
+						"type": "element",
+						"name": "linearGradient",
+						"attributes": {
+							"id": "Fade_to_Black_2",
+							"data-name": "Fade to Black 2",
+							"x1": "11.26",
+							"y1": "11.7",
+							"x2": "11.26",
+							"y2": "13.1",
+							"gradientUnits": "userSpaceOnUse"
+						},
+						"children": [
+							{
+								"type": "element",
+								"name": "stop",
+								"attributes": {
+									"offset": "0",
+									"stop-color": "#231f20"
+								},
+								"children": []
+							},
+							{
+								"type": "element",
+								"name": "stop",
+								"attributes": {
+									"offset": "1",
+									"stop-color": "#231f20",
+									"stop-opacity": "0"
+								},
+								"children": []
+							}
+						]
+					},
+					{
+						"type": "element",
+						"name": "linearGradient",
+						"attributes": {
+							"id": "linear-gradient-7",
+							"x1": "11.94",
+							"y1": "8.07",
+							"x2": "11.94",
+							"y2": "6.92",
+							"gradientUnits": "userSpaceOnUse"
+						},
+						"children": [
+							{
+								"type": "element",
+								"name": "stop",
+								"attributes": {
+									"offset": "0",
+									"stop-color": "#231f20"
+								},
+								"children": []
+							},
+							{
+								"type": "element",
+								"name": "stop",
+								"attributes": {
+									"offset": ".03",
+									"stop-color": "#231f20",
+									"stop-opacity": ".95"
+								},
+								"children": []
+							},
+							{
+								"type": "element",
+								"name": "stop",
+								"attributes": {
+									"offset": ".51",
+									"stop-color": "#231f20",
+									"stop-opacity": ".26"
+								},
+								"children": []
+							},
+							{
+								"type": "element",
+								"name": "stop",
+								"attributes": {
+									"offset": ".81",
+									"stop-color": "#231f20",
+									"stop-opacity": "0"
+								},
+								"children": []
+							}
+						]
+					},
+					{
+						"type": "element",
+						"name": "linearGradient",
+						"attributes": {
+							"id": "linear-gradient-8",
+							"x1": "14.45",
+							"y1": "8.92",
+							"x2": "14.45",
+							"y2": "6.14",
+							"gradientUnits": "userSpaceOnUse"
+						},
+						"children": [
+							{
+								"type": "element",
+								"name": "stop",
+								"attributes": {
+									"offset": "0",
+									"stop-color": "#231f20"
+								},
+								"children": []
+							},
+							{
+								"type": "element",
+								"name": "stop",
+								"attributes": {
+									"offset": ".18",
+									"stop-color": "#231f20",
+									"stop-opacity": ".48"
+								},
+								"children": []
+							},
+							{
+								"type": "element",
+								"name": "stop",
+								"attributes": {
+									"offset": ".38",
+									"stop-color": "#231f20",
+									"stop-opacity": ".12"
+								},
+								"children": []
+							},
+							{
+								"type": "element",
+								"name": "stop",
+								"attributes": {
+									"offset": ".58",
+									"stop-color": "#231f20",
+									"stop-opacity": "0"
+								},
+								"children": []
+							}
+						]
+					},
+					{
+						"type": "element",
+						"name": "linearGradient",
+						"attributes": {
+							"id": "Fade_to_Black_2-2",
+							"data-name": "Fade to Black 2",
+							"x1": "17.03",
+							"y1": "11.1",
+							"x2": "16.07",
+							"y2": "9.44",
+							"xlink:href": "#Fade_to_Black_2"
+						},
+						"children": []
+					},
+					{
+						"type": "element",
+						"name": "linearGradient",
+						"attributes": {
+							"id": "linear-gradient-9",
+							"x1": "17.8",
+							"y1": "10.64",
+							"x2": "16.36",
+							"y2": "8.16",
+							"xlink:href": "#linear-gradient-2"
+						},
+						"children": []
+					},
+					{
+						"type": "element",
+						"name": "linearGradient",
+						"attributes": {
+							"id": "linear-gradient-10",
+							"x1": "14.07",
+							"y1": "10.22",
+							"x2": "16.16",
+							"y2": "9.02",
+							"gradientUnits": "userSpaceOnUse"
+						},
+						"children": [
+							{
+								"type": "element",
+								"name": "stop",
+								"attributes": {
+									"offset": "0",
+									"stop-color": "#231f20"
+								},
+								"children": []
+							},
+							{
+								"type": "element",
+								"name": "stop",
+								"attributes": {
+									"offset": ".31",
+									"stop-color": "#231f20",
+									"stop-opacity": ".5"
+								},
+								"children": []
+							},
+							{
+								"type": "element",
+								"name": "stop",
+								"attributes": {
+									"offset": ".67",
+									"stop-color": "#231f20",
+									"stop-opacity": ".13"
+								},
+								"children": []
+							},
+							{
+								"type": "element",
+								"name": "stop",
+								"attributes": {
+									"offset": "1",
+									"stop-color": "#231f20",
+									"stop-opacity": "0"
+								},
+								"children": []
+							}
+						]
+					}
+				]
+			},
+			{
+				"type": "element",
+				"name": "g",
+				"attributes": {
+					"id": "Layer_1-2",
+					"data-name": "Layer 1"
+				},
+				"children": [
+					{
+						"type": "element",
+						"name": "rect",
+						"attributes": {
+							"style": "fill: none;",
+							"y": ".02",
+							"width": "74",
+							"height": "16"
+						},
+						"children": []
+					},
+					{
+						"type": "element",
+						"name": "g",
+						"attributes": {
+							"id": "Phoenix_horiz_-_gradient",
+							"data-name": "Phoenix horiz - gradient"
+						},
+						"children": [
+							{
+								"type": "element",
+								"name": "path",
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+								},
+								"children": []
+							},
+							{
+								"type": "element",
+								"name": "path",
+								"attributes": {
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+								},
+								"children": []
+							},
+							{
+								"type": "element",
+								"name": "path",
+								"attributes": {
+									"style": "fill: url(#linear-gradient-10); opacity: .5;",
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+								},
+								"children": []
+							},
+							{
+								"type": "element",
+								"name": "g",
+								"attributes": {},
+								"children": [
+									{
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+										},
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+										},
+										"children": []
+									},
+									{
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+										"name": "path",
+										"attributes": {
+											"style": "fill: #404041;",
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+										},
+										"children": []
+									},
+									{
+										"type": "element",
+										"name": "path",
+										"attributes": {
+											"style": "fill: #404041;",
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+										},
+										"children": []
+									},
+									{
+										"type": "element",
+										"name": "path",
+										"attributes": {
+											"style": "fill: #404041;",
+											"d": "M53.93,4.73h1.09l2.42,7.19v-7.19h.77v9.3h-.88l-2.64-7.93v7.93h-.76V4.73Z"
+										},
+										"children": []
+									},
+									{
+										"type": "element",
+										"name": "path",
+										"attributes": {
+											"style": "fill: #404041;",
+											"d": "M61.55,4.73h.82v9.3h-.82V4.73Z"
+										},
+										"children": []
+									},
+									{
+										"type": "element",
+										"name": "path",
+										"attributes": {
+											"style": "fill: #404041;",
+											"d": "M67.19,9.29l-1.82-4.56h.88l1.46,3.69,1.48-3.69h.8l-1.82,4.56,1.9,4.74h-.88l-1.54-3.91-1.55,3.91h-.8l1.9-4.74Z"
+										},
+										"children": []
+									}
+								]
+							}
+						]
+					}
+				]
+			}
+		]
+	},
+	"name": "PhoenixIcon"
+}

web/app/components/base/icons/src/public/tracing/PhoenixIcon.tsx

@@ -0,0 +1,20 @@
+// GENERATE BY script
+// DON NOT EDIT IT MANUALLY
+
+import * as React from 'react'
+import data from './PhoenixIcon.json'
+import IconBase from '@/app/components/base/icons/IconBase'
+import type { IconData } from '@/app/components/base/icons/IconBase'
+
+const Icon = (
+  {
+    ref,
+    ...props
+  }: React.SVGProps<SVGSVGElement> & {
+    ref?: React.RefObject<React.MutableRefObject<HTMLOrSVGElement>>;
+  },
+) => <IconBase {...props} ref={ref} data={data as IconData} />
+
+Icon.displayName = 'PhoenixIcon'
+
+export default Icon

web/app/components/base/icons/src/public/tracing/PhoenixIconBig.json

@@ -0,0 +1,853 @@
+{
+	"icon": {
+		"type": "element",
+		"isRootNode": true,
+		"name": "svg",
+		"attributes": {
+			"id": "Layer_2",
+			"data-name": "Layer 2",
+			"xmlns": "http://www.w3.org/2000/svg",
+			"xmlns:xlink": "http://www.w3.org/1999/xlink",
+			"viewBox": "0 0 111 24",
+			"width": "111",
+			"height": "24"
+		},
+		"children": [
+			{
+				"type": "element",
+				"name": "defs",
+				"attributes": {},
+				"children": [
+					{
+						"type": "element",
+						"name": "linearGradient",
+						"attributes": {
+							"id": "linear-gradient",
+							"x1": "9.07",
+							"y1": "1.47",
+							"x2": "19.77",
+							"y2": "20",
+							"gradientUnits": "userSpaceOnUse"
+						},
+						"children": [
+							{
+								"type": "element",
+								"name": "stop",
+								"attributes": {
+									"offset": "0",
+									"stop-color": "#11bab5"
+								},
+								"children": []
+							},
+							{
+								"type": "element",
+								"name": "stop",
+								"attributes": {
+									"offset": ".5",
+									"stop-color": "#00adee"
+								},
+								"children": []
+							},
+							{
+								"type": "element",
+								"name": "stop",
+								"attributes": {
+									"offset": "1",
+									"stop-color": "#0094c5"
+								},
+								"children": []
+							}
+						]
+					},
+					{
+						"type": "element",
+						"name": "linearGradient",
+						"attributes": {
+							"id": "linear-gradient-2",
+							"x1": "19.48",
+							"y1": "16.3",
+							"x2": "10.46",
+							"y2": ".67",
+							"gradientUnits": "userSpaceOnUse"
+						},
+						"children": [
+							{
+								"type": "element",
+								"name": "stop",
+								"attributes": {
+									"offset": "0",
+									"stop-color": "#fcfdff",
+									"stop-opacity": "0"
+								},
+								"children": []
+							},
+							{
+								"type": "element",
+								"name": "stop",
+								"attributes": {
+									"offset": ".12",
+									"stop-color": "#fcfdff",
+									"stop-opacity": ".17"
+								},
+								"children": []
+							},
+							{
+								"type": "element",
+								"name": "stop",
+								"attributes": {
+									"offset": ".3",
+									"stop-color": "#fcfdff",
+									"stop-opacity": ".42"
+								},
+								"children": []
+							},
+							{
+								"type": "element",
+								"name": "stop",
+								"attributes": {
+									"offset": ".47",
+									"stop-color": "#fcfdff",
+									"stop-opacity": ".63"
+								},
+								"children": []
+							},
+							{
+								"type": "element",
+								"name": "stop",
+								"attributes": {
+									"offset": ".64",
+									"stop-color": "#fcfdff",
+									"stop-opacity": ".79"
+								},
+								"children": []
+							},
+							{
+								"type": "element",
+								"name": "stop",
+								"attributes": {
+									"offset": ".78",
+									"stop-color": "#fcfdff",
+									"stop-opacity": ".9"
+								},
+								"children": []
+							},
+							{
+								"type": "element",
+								"name": "stop",
+								"attributes": {
+									"offset": ".91",
+									"stop-color": "#fcfdff",
+									"stop-opacity": ".97"
+								},
+								"children": []
+							},
+							{
+								"type": "element",
+								"name": "stop",
+								"attributes": {
+									"offset": "1",
+									"stop-color": "#fcfdff"
+								},
+								"children": []
+							}
+						]
+					},
+					{
+						"type": "element",
+						"name": "linearGradient",
+						"attributes": {
+							"id": "linear-gradient-3",
+							"x1": "16.82",
+							"y1": "16.21",
+							"x2": "10.32",
+							"y2": "4.94",
+							"xlink:href": "#linear-gradient-2"
+						},
+						"children": []
+					},
+					{
+						"type": "element",
+						"name": "linearGradient",
+						"attributes": {
+							"id": "linear-gradient-4",
+							"x1": "15.92",
+							"y1": "17.03",
+							"x2": "12.29",
+							"y2": "10.74",
+							"xlink:href": "#linear-gradient-2"
+						},
+						"children": []
+					},
+					{
+						"type": "element",
+						"name": "linearGradient",
+						"attributes": {
+							"id": "linear-gradient-5",
+							"x1": "16.08",
+							"y1": "18.3",
+							"x2": "13.82",
+							"y2": "14.38",
+							"xlink:href": "#linear-gradient-2"
+						},
+						"children": []
+					},
+					{
+						"type": "element",
+						"name": "linearGradient",
+						"attributes": {
+							"id": "linear-gradient-6",
+							"x1": "12.26",
+							"y1": "17.94",
+							"x2": "12.26",
+							"y2": "22.07",
+							"gradientUnits": "userSpaceOnUse"
+						},
+						"children": [
+							{
+								"type": "element",
+								"name": "stop",
+								"attributes": {
+									"offset": "0",
+									"stop-color": "#231f20"
+								},
+								"children": []
+							},
+							{
+								"type": "element",
+								"name": "stop",
+								"attributes": {
+									"offset": ".03",
+									"stop-color": "#231f20",
+									"stop-opacity": ".9"
+								},
+								"children": []
+							},
+							{
+								"type": "element",
+								"name": "stop",
+								"attributes": {
+									"offset": ".22",
+									"stop-color": "#231f20",
+									"stop-opacity": ".4"
+								},
+								"children": []
+							},
+							{
+								"type": "element",
+								"name": "stop",
+								"attributes": {
+									"offset": ".42",
+									"stop-color": "#231f20",
+									"stop-opacity": ".1"
+								},
+								"children": []
+							},
+							{
+								"type": "element",
+								"name": "stop",
+								"attributes": {
+									"offset": ".65",
+									"stop-color": "#231f20",
+									"stop-opacity": "0"
+								},
+								"children": []
+							}
+						]
+					},
+					{
+						"type": "element",
+						"name": "linearGradient",
+						"attributes": {
+							"id": "Fade_to_Black_2",
+							"data-name": "Fade to Black 2",
+							"x1": "16.89",
+							"y1": "17.55",
+							"x2": "16.89",
+							"y2": "19.66",
+							"gradientUnits": "userSpaceOnUse"
+						},
+						"children": [
+							{
+								"type": "element",
+								"name": "stop",
+								"attributes": {
+									"offset": "0",
+									"stop-color": "#231f20"
+								},
+								"children": []
+							},
+							{
+								"type": "element",
+								"name": "stop",
+								"attributes": {
+									"offset": "1",
+									"stop-color": "#231f20",
+									"stop-opacity": "0"
+								},
+								"children": []
+							}
+						]
+					},
+					{
+						"type": "element",
+						"name": "linearGradient",
+						"attributes": {
+							"id": "linear-gradient-7",
+							"x1": "17.91",
+							"y1": "12.1",
+							"x2": "17.91",
+							"y2": "10.38",
+							"gradientUnits": "userSpaceOnUse"
+						},
+						"children": [
+							{
+								"type": "element",
+								"name": "stop",
+								"attributes": {
+									"offset": "0",
+									"stop-color": "#231f20"
+								},
+								"children": []
+							},
+							{
+								"type": "element",
+								"name": "stop",
+								"attributes": {
+									"offset": ".03",
+									"stop-color": "#231f20",
+									"stop-opacity": ".95"
+								},
+								"children": []
+							},
+							{
+								"type": "element",
+								"name": "stop",
+								"attributes": {
+									"offset": ".51",
+									"stop-color": "#231f20",
+									"stop-opacity": ".26"
+								},
+								"children": []
+							},
+							{
+								"type": "element",
+								"name": "stop",
+								"attributes": {
+									"offset": ".81",
+									"stop-color": "#231f20",
+									"stop-opacity": "0"
+								},
+								"children": []
+							}
+						]
+					},
+					{
+						"type": "element",
+						"name": "linearGradient",
+						"attributes": {
+							"id": "linear-gradient-8",
+							"x1": "21.67",
+							"y1": "13.37",
+							"x2": "21.67",
+							"y2": "9.21",
+							"gradientUnits": "userSpaceOnUse"
+						},
+						"children": [
+							{
+								"type": "element",
+								"name": "stop",
+								"attributes": {
+									"offset": "0",
+									"stop-color": "#231f20"
+								},
+								"children": []
+							},
+							{
+								"type": "element",
+								"name": "stop",
+								"attributes": {
+									"offset": ".18",
+									"stop-color": "#231f20",
+									"stop-opacity": ".48"
+								},
+								"children": []
+							},
+							{
+								"type": "element",
+								"name": "stop",
+								"attributes": {
+									"offset": ".38",
+									"stop-color": "#231f20",
+									"stop-opacity": ".12"
+								},
+								"children": []
+							},
+							{
+								"type": "element",
+								"name": "stop",
+								"attributes": {
+									"offset": ".58",
+									"stop-color": "#231f20",
+									"stop-opacity": "0"
+								},
+								"children": []
+							}
+						]
+					},
+					{
+						"type": "element",
+						"name": "linearGradient",
+						"attributes": {
+							"id": "Fade_to_Black_2-2",
+							"data-name": "Fade to Black 2",
+							"x1": "25.54",
+							"y1": "16.65",
+							"x2": "24.1",
+							"y2": "14.16",
+							"xlink:href": "#Fade_to_Black_2"
+						},
+						"children": []
+					},
+					{
+						"type": "element",
+						"name": "linearGradient",
+						"attributes": {
+							"id": "linear-gradient-9",
+							"x1": "26.7",
+							"y1": "15.97",
+							"x2": "24.55",
+							"y2": "12.24",
+							"xlink:href": "#linear-gradient-2"
+						},
+						"children": []
+					},
+					{
+						"type": "element",
+						"name": "linearGradient",
+						"attributes": {
+							"id": "linear-gradient-10",
+							"x1": "21.11",
+							"y1": "15.34",
+							"x2": "24.24",
+							"y2": "13.53",
+							"gradientUnits": "userSpaceOnUse"
+						},
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+									"d": "M24.54,9.21c-.34.48-.77.9-1.26,1.24-.22.73-.57,1.42-1.12,2.04-.07.07-.14.14-.21.21-.07.07-.17.19-.25.19-.02,0-.03,0-.05-.02-.13-.09-.01-.27.03-.36.21-.48.37-.98.48-1.47-.35.13-.71.22-1.08.27-.05.15-.09.3-.15.44-.06.17-.14.34-.21.5-.07.14-.12.32-.3.32-.04,0-.08,0-.12-.02-.26-.09-.19-.29-.16-.47.05-.24.09-.49.12-.73-.33-.01-.65-.05-.96-.12-.03.19-.06.39-.1.58-.02.13-.08.35-.31.35-.03,0-.06,0-.09-.01,1.04.37,2.51.84,4.24,1.21h0s-.03-.01-.05-.02c-.28-.12.22-.61.45-.96.64-.98.95-2.06,1.1-3.18Z"
+								},
+								"children": []
+							},
+							{
+								"type": "element",
+								"name": "path",
+								"attributes": {
+									"style": "fill: url(#Fade_to_Black_2-2); opacity: .5;",
+									"d": "M24.28,14.56c-.22,0-.43.02-.65.06-.04,0-.08.01-.12.01-.06,0-.12,0-.17-.03,0,.01.02.02.03.03.09.13.14.27.16.42.02.03.04.06.06.1h0s0,0,0,0c0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0h0s0,0,0,0c0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0t0,0s0,0,0,0c0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0s0,0,0,0c0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0s0,0,0,0c0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0h0s0,0,0,0h0s0,0,0,0h0s0,0,0,0h0s0,0,0,0h0s0,0,0,0h0s0,0,0,0h0s0,0,0,0h0s0,0,0,0c0,0,0,0,0,0,0,0,0,0,0,0h0s0,0,0,0h0s0,0,0,0h0s0,0,0,0h0s0,0,0,0h0s0,0,0,0h0s0,0,0,0h0s0,0,0,0h0s0,0,0,0h0s0,.07,0,.1c0,.05,0,.11,0,.17,0,.07-.02.15-.03.21,0,0,0,.02,0,.03,0,.05.02.09.06.12h.02s.05.03.07.03c.04,0,.08-.02.11-.05.02-.02.03-.04.05-.06.22-.23.44-.39.68-.49.17-.07.35-.11.53-.11s.36.04.55.11c.18.07.35.16.51.28.07.05.14.11.21.17.04.04.08.08.12.12h0s.03.04.03.04l.02.02s.06.03.09.03c-.15-.32-.33-.61-.6-.84-.5-.43-1.13-.62-1.77-.62"
+								},
+								"children": []
+							},
+							{
+								"type": "element",
+								"name": "path",
+								"attributes": {
+									"style": "fill: url(#linear-gradient-9); opacity: .4;",
+									"d": "M24.22,12.45h-.03c-.07.01-.12.07-.13.14,0,.05,0,.11,0,.17,0,.02,0,.04-.01.05.27.4.84,1.1,1.72,1.36,0,0,1.36.71,1.01,1.74h0v-.03c.12-.31.14-.6.08-.89-.06-.28-.2-.53-.42-.76-.08-.09-.18-.17-.28-.25-.05-.04-.1-.07-.15-.1-.07-.04-.14-.08-.21-.12-.28-.14-.51-.29-.72-.44-.08-.06-.17-.13-.24-.19-.19-.16-.31-.3-.4-.45-.03-.05-.06-.1-.08-.15-.01-.02-.03-.04-.05-.05-.03-.02-.06-.03-.09-.03"
+								},
+								"children": []
+							},
+							{
+								"type": "element",
+								"name": "path",
+								"attributes": {
+									"style": "fill: url(#linear-gradient-10); opacity: .5;",
+									"d": "M22.5,15.32l.28-.16,1.16-1.55s-.63-.12-.94-.26c0,0-.32,1.45-1.49,2.66l.43-.32c.17-.12.33-.23.56-.37Z"
+								},
+								"children": []
+							},
+							{
+								"type": "element",
+								"name": "g",
+								"attributes": {},
+								"children": [
+									{
+										"type": "element",
+										"name": "path",
+										"attributes": {
+											"style": "fill: #404041;",
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+										},
+										"children": []
+									},
+									{
+										"type": "element",
+										"name": "path",
+										"attributes": {
+											"style": "fill: #404041;",
+											"d": "M48.61,7.1h1.24v6.12h3.81v-6.12h1.24v13.95h-1.24v-6.72h-3.81v6.72h-1.24V7.1Z"
+										},
+										"children": []
+									},
+									{
+										"type": "element",
+										"name": "path",
+										"attributes": {
+											"style": "fill: #404041;",
+											"d": "M59.73,17.84v-7.54c0-2.21,1.12-3.41,3.13-3.41s3.13,1.2,3.13,3.41v7.54c0,2.21-1.12,3.41-3.13,3.41s-3.13-1.2-3.13-3.41ZM64.75,17.92v-7.69c0-1.5-.68-2.21-1.89-2.21s-1.89.72-1.89,2.21v7.69c0,1.5.68,2.19,1.89,2.19s1.89-.7,1.89-2.19Z"
+										},
+										"children": []
+									},
+									{
+										"type": "element",
+										"name": "path",
+										"attributes": {
+											"style": "fill: #404041;",
+											"d": "M70.85,7.1h5.58v1.12h-4.35v5h3.57v1.12h-3.57v5.58h4.35v1.14h-5.58V7.1Z"
+										},
+										"children": []
+									},
+									{
+										"type": "element",
+										"name": "path",
+										"attributes": {
+											"style": "fill: #404041;",
+											"d": "M80.9,7.1h1.63l3.63,10.78V7.1h1.16v13.95h-1.32l-3.97-11.9v11.9h-1.14V7.1Z"
+										},
+										"children": []
+									},
+									{
+										"type": "element",
+										"name": "path",
+										"attributes": {
+											"style": "fill: #404041;",
+											"d": "M92.32,7.1h1.24v13.95h-1.24V7.1Z"
+										},
+										"children": []
+									},
+									{
+										"type": "element",
+										"name": "path",
+										"attributes": {
+											"style": "fill: #404041;",
+											"d": "M100.79,13.94l-2.73-6.84h1.32l2.19,5.54,2.21-5.54h1.2l-2.73,6.84,2.85,7.12h-1.32l-2.31-5.86-2.33,5.86h-1.2l2.85-7.12Z"
+										},
+										"children": []
+									}
+								]
+							}
+						]
+					}
+				]
+			}
+		]
+	},
+	"name": "PhoenixIconBig"
+}

web/app/components/base/icons/src/public/tracing/PhoenixIconBig.tsx

@@ -0,0 +1,20 @@
+// GENERATE BY script
+// DON NOT EDIT IT MANUALLY
+
+import * as React from 'react'
+import data from './PhoenixIconBig.json'
+import IconBase from '@/app/components/base/icons/IconBase'
+import type { IconData } from '@/app/components/base/icons/IconBase'
+
+const Icon = (
+  {
+    ref,
+    ...props
+  }: React.SVGProps<SVGSVGElement> & {
+    ref?: React.RefObject<React.MutableRefObject<HTMLOrSVGElement>>;
+  },
+) => <IconBase {...props} ref={ref} data={data as IconData} />
+
+Icon.displayName = 'PhoenixIconBig'
+
+export default Icon

web/app/components/base/icons/src/public/tracing/index.ts

@@ -1,9 +1,13 @@
+export { default as ArizeIconBig } from './ArizeIconBig'
+export { default as ArizeIcon } from './ArizeIcon'
 export { default as LangfuseIconBig } from './LangfuseIconBig'
 export { default as LangfuseIcon } from './LangfuseIcon'
 export { default as LangsmithIconBig } from './LangsmithIconBig'
 export { default as LangsmithIcon } from './LangsmithIcon'
 export { default as OpikIconBig } from './OpikIconBig'
 export { default as OpikIcon } from './OpikIcon'
+export { default as PhoenixIconBig } from './PhoenixIconBig'
+export { default as PhoenixIcon } from './PhoenixIcon'
 export { default as TracingIcon } from './TracingIcon'
 export { default as WeaveIconBig } from './WeaveIconBig'
 export { default as WeaveIcon } from './WeaveIcon'

web/app/components/base/markdown/markdown-utils.ts

@@ -11,6 +11,7 @@ export const preprocessLaTeX = (content: string) => {
 
   const codeBlockRegex = /```[\s\S]*?```/g
   const codeBlocks = content.match(codeBlockRegex) || []
+  const escapeReplacement = (str: string) => str.replace(/\$/g, '_TMP_REPLACE_DOLLAR_')
   let processedContent = content.replace(codeBlockRegex, 'CODE_BLOCK_PLACEHOLDER')
 
   processedContent = flow([
@@ -21,9 +22,11 @@ export const preprocessLaTeX = (content: string) => {
   ])(processedContent)
 
   codeBlocks.forEach((block) => {
-    processedContent = processedContent.replace('CODE_BLOCK_PLACEHOLDER', block)
+    processedContent = processedContent.replace('CODE_BLOCK_PLACEHOLDER', escapeReplacement(block))
   })
 
+  processedContent = processedContent.replace(/_TMP_REPLACE_DOLLAR_/g, '$')
+
   return processedContent
 }
 

web/app/components/base/popover/index.tsx

@@ -3,6 +3,7 @@ import { Fragment, cloneElement, useRef } from 'react'
 import cn from '@/utils/classnames'
 
 export type HtmlContentProps = {
+  open?: boolean
   onClose?: () => void
   onClick?: () => void
 }
@@ -100,7 +101,8 @@ export default function CustomPopover({
                       }
                     >
                       {cloneElement(htmlContent as React.ReactElement, {
-                        onClose: () => onMouseLeave(open),
+                        open,
+                        onClose: close,
                         ...(manualClose
                           ? {
                             onClick: close,