chore: bump version to 0.13.2 (#11489)

Signed-off-by: -LAN- <laipz8200@outlook.com>

api/configs/packaging/__init__.py

@@ -9,7 +9,7 @@ class PackagingInfo(BaseSettings):
 
     CURRENT_VERSION: str = Field(
         description="Dify version",
-        default="0.13.1",
+        default="0.13.2",
     )
 
     COMMIT_SHA: str = Field(

api/controllers/console/explore/installed_app.py

@@ -1,5 +1,6 @@
 from datetime import UTC, datetime
 
+from flask import request
 from flask_login import current_user
 from flask_restful import Resource, inputs, marshal_with, reqparse
 from sqlalchemy import and_
@@ -20,8 +21,17 @@ class InstalledAppsListApi(Resource):
     @account_initialization_required
     @marshal_with(installed_app_list_fields)
     def get(self):
+        app_id = request.args.get("app_id", default=None, type=str)
         current_tenant_id = current_user.current_tenant_id
-        installed_apps = db.session.query(InstalledApp).filter(InstalledApp.tenant_id == current_tenant_id).all()
+
+        if app_id:
+            installed_apps = (
+                db.session.query(InstalledApp)
+                .filter(and_(InstalledApp.tenant_id == current_tenant_id, InstalledApp.app_id == app_id))
+                .all()
+            )
+        else:
+            installed_apps = db.session.query(InstalledApp).filter(InstalledApp.tenant_id == current_tenant_id).all()
 
         current_user.role = TenantService.get_user_role(current_user, current_user.current_tenant)
         installed_apps = [

api/controllers/console/workspace/tool_providers.py

@@ -368,6 +368,7 @@ class ToolWorkflowProviderCreateApi(Resource):
             description=args["description"],
             parameters=args["parameters"],
             privacy_policy=args["privacy_policy"],
+            labels=args["labels"],
         )
 
 

api/core/app/apps/base_app_generate_response_converter.py

@@ -82,7 +82,7 @@ class AppGenerateResponseConverter(ABC):
             for resource in metadata["retriever_resources"]:
                 updated_resources.append(
                     {
-                        "segment_id": resource["segment_id"],
+                        "segment_id": resource.get("segment_id", ""),
                         "position": resource["position"],
                         "document_name": resource["document_name"],
                         "score": resource["score"],

api/core/app/entities/queue_entities.py

@@ -2,7 +2,7 @@ from datetime import datetime
 from enum import Enum, StrEnum
 from typing import Any, Optional
 
-from pydantic import BaseModel, field_validator
+from pydantic import BaseModel
 
 from core.model_runtime.entities.llm_entities import LLMResult, LLMResultChunk
 from core.workflow.entities.node_entities import NodeRunMetadataKey
@@ -113,18 +113,6 @@ class QueueIterationNextEvent(AppQueueEvent):
     output: Optional[Any] = None  # output for the current iteration
     duration: Optional[float] = None
 
-    @field_validator("output", mode="before")
-    @classmethod
-    def set_output(cls, v):
-        """
-        Set output
-        """
-        if v is None:
-            return None
-        if isinstance(v, int | float | str | bool | dict | list):
-            return v
-        raise ValueError("output must be a valid type")
-
 
 class QueueIterationCompletedEvent(AppQueueEvent):
     """

api/core/model_runtime/model_providers/google/llm/gemini-exp-1206.yaml

@@ -0,0 +1,38 @@
+model: gemini-exp-1206
+label:
+  en_US: Gemini exp 1206
+model_type: llm
+features:
+  - agent-thought
+  - vision
+  - tool-call
+  - stream-tool-call
+model_properties:
+  mode: chat
+  context_size: 2097152
+parameter_rules:
+  - name: temperature
+    use_template: temperature
+  - name: top_p
+    use_template: top_p
+  - name: top_k
+    label:
+      zh_Hans: 取样数量
+      en_US: Top k
+    type: int
+    help:
+      zh_Hans: 仅从每个后续标记的前 K 个选项中采样。
+      en_US: Only sample from the top K options for each subsequent token.
+    required: false
+  - name: max_output_tokens
+    use_template: max_tokens
+    default: 8192
+    min: 1
+    max: 8192
+  - name: json_schema
+    use_template: json_schema
+pricing:
+  input: '0.00'
+  output: '0.00'
+  unit: '0.000001'
+  currency: USD

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

@@ -181,9 +181,11 @@ class OllamaLargeLanguageModel(LargeLanguageModel):
         # prepare the payload for a simple ping to the model
         data = {"model": model, "stream": stream}
 
-        if "format" in model_parameters:
-            data["format"] = model_parameters["format"]
-            del model_parameters["format"]
+        if format_schema := model_parameters.pop("format", None):
+            try:
+                data["format"] = format_schema if format_schema == "json" else json.loads(format_schema)
+            except json.JSONDecodeError as e:
+                raise InvokeBadRequestError(f"Invalid format schema: {str(e)}")
 
         if "keep_alive" in model_parameters:
             data["keep_alive"] = model_parameters["keep_alive"]
@@ -733,12 +735,12 @@ class OllamaLargeLanguageModel(LargeLanguageModel):
                 ParameterRule(
                     name="format",
                     label=I18nObject(en_US="Format", zh_Hans="返回格式"),
-                    type=ParameterType.STRING,
+                    type=ParameterType.TEXT,
+                    default="json",
                     help=I18nObject(
-                        en_US="the format to return a response in. Currently the only accepted value is json.",
-                        zh_Hans="返回响应的格式。目前唯一接受的值是json。",
+                        en_US="the format to return a response in. Format can be `json` or a JSON schema.",
+                        zh_Hans="返回响应的格式。目前接受的值是字符串`json`或JSON schema.",
                     ),
-                    options=["json"],
                 ),
             ],
             pricing=PriceConfig(

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

@@ -104,13 +104,14 @@ class VertexAiLargeLanguageModel(LargeLanguageModel):
         """
         # use Anthropic official SDK references
         # - https://github.com/anthropics/anthropic-sdk-python
-        service_account_info = json.loads(base64.b64decode(credentials["vertex_service_account_key"]))
+        service_account_key = credentials.get("vertex_service_account_key", "")
         project_id = credentials["vertex_project_id"]
         SCOPES = ["https://www.googleapis.com/auth/cloud-platform"]
         token = ""
 
         # get access token from service account credential
-        if service_account_info:
+        if service_account_key:
+            service_account_info = json.loads(base64.b64decode(service_account_key))
             credentials = service_account.Credentials.from_service_account_info(service_account_info, scopes=SCOPES)
             request = google.auth.transport.requests.Request()
             credentials.refresh(request)
@@ -478,10 +479,11 @@ class VertexAiLargeLanguageModel(LargeLanguageModel):
         if stop:
             config_kwargs["stop_sequences"] = stop
 
-        service_account_info = json.loads(base64.b64decode(credentials["vertex_service_account_key"]))
+        service_account_key = credentials.get("vertex_service_account_key", "")
         project_id = credentials["vertex_project_id"]
         location = credentials["vertex_location"]
-        if service_account_info:
+        if service_account_key:
+            service_account_info = json.loads(base64.b64decode(service_account_key))
             service_accountSA = service_account.Credentials.from_service_account_info(service_account_info)
             aiplatform.init(credentials=service_accountSA, project=project_id, location=location)
         else:

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

@@ -48,10 +48,11 @@ class VertexAiTextEmbeddingModel(_CommonVertexAi, TextEmbeddingModel):
         :param input_type: input type
         :return: embeddings result
         """
-        service_account_info = json.loads(base64.b64decode(credentials["vertex_service_account_key"]))
+        service_account_key = credentials.get("vertex_service_account_key", "")
         project_id = credentials["vertex_project_id"]
         location = credentials["vertex_location"]
-        if service_account_info:
+        if service_account_key:
+            service_account_info = json.loads(base64.b64decode(service_account_key))
             service_accountSA = service_account.Credentials.from_service_account_info(service_account_info)
             aiplatform.init(credentials=service_accountSA, project=project_id, location=location)
         else:
@@ -100,10 +101,11 @@ class VertexAiTextEmbeddingModel(_CommonVertexAi, TextEmbeddingModel):
         :return:
         """
         try:
-            service_account_info = json.loads(base64.b64decode(credentials["vertex_service_account_key"]))
+            service_account_key = credentials.get("vertex_service_account_key", "")
             project_id = credentials["vertex_project_id"]
             location = credentials["vertex_location"]
-            if service_account_info:
+            if service_account_key:
+                service_account_info = json.loads(base64.b64decode(service_account_key))
                 service_accountSA = service_account.Credentials.from_service_account_info(service_account_info)
                 aiplatform.init(credentials=service_accountSA, project=project_id, location=location)
             else:

api/core/model_runtime/model_providers/zhipuai/llm/glm_4v_flash.yaml

@@ -0,0 +1,52 @@
+model: glm-4v-flash
+label:
+  en_US: glm-4v-flash
+model_type: llm
+model_properties:
+  mode: chat
+  context_size: 2048
+features:
+  - vision
+parameter_rules:
+  - name: temperature
+    use_template: temperature
+    default: 0.95
+    min: 0.0
+    max: 1.0
+    help:
+      zh_Hans: 采样温度，控制输出的随机性，必须为正数取值范围是：(0.0,1.0]，不能等于 0,默认值为 0.95 值越大，会使输出更随机，更具创造性；值越小，输出会更加稳定或确定建议您根据应用场景调整 top_p 或 temperature 参数，但不要同时调整两个参数。
+      en_US: Sampling temperature, controls the randomness of the output, must be a positive number. The value range is (0.0,1.0], which cannot be equal to 0. The default value is 0.95. The larger the value, the more random and creative the output will be; the smaller the value, The output will be more stable or certain. It is recommended that you adjust the top_p or temperature parameters according to the application scenario, but do not adjust both parameters at the same time.
+  - name: top_p
+    use_template: top_p
+    default: 0.6
+    help:
+      zh_Hans: 用温度取样的另一种方法，称为核取样取值范围是：(0.0, 1.0) 开区间，不能等于 0 或 1，默认值为 0.7 模型考虑具有 top_p 概率质量tokens的结果例如：0.1 意味着模型解码器只考虑从前 10% 的概率的候选集中取 tokens 建议您根据应用场景调整 top_p 或 temperature 参数，但不要同时调整两个参数。
+      en_US: Another method of temperature sampling is called kernel sampling. The value range is (0.0, 1.0) open interval, which cannot be equal to 0 or 1. The default value is 0.7. The model considers the results with top_p probability mass tokens. For example 0.1 means The model decoder only considers tokens from the candidate set with the top 10% probability. It is recommended that you adjust the top_p or temperature parameters according to the application scenario, but do not adjust both parameters at the same time.
+  - name: do_sample
+    label:
+      zh_Hans: 采样策略
+      en_US: Sampling strategy
+    type: boolean
+    help:
+      zh_Hans: do_sample 为 true 时启用采样策略，do_sample 为 false 时采样策略 temperature、top_p 将不生效。默认值为 true。
+      en_US: When `do_sample` is set to true, the sampling strategy is enabled. When `do_sample` is set to false, the sampling strategies such as `temperature` and `top_p` will not take effect. The default value is true.
+    default: true
+  - name: max_tokens
+    use_template: max_tokens
+    default: 1024
+    min: 1
+    max: 1024
+  - name: web_search
+    type: boolean
+    label:
+      zh_Hans: 联网搜索
+      en_US: Web Search
+    default: false
+    help:
+      zh_Hans: 模型内置了互联网搜索服务，该参数控制模型在生成文本时是否参考使用互联网搜索结果。启用互联网搜索，模型会将搜索结果作为文本生成过程中的参考信息，但模型会基于其内部逻辑“自行判断”是否使用互联网搜索结果。
+      en_US: The model has a built-in Internet search service. This parameter controls whether the model refers to Internet search results when generating text. When Internet search is enabled, the model will use the search results as reference information in the text generation process, but the model will "judge" whether to use Internet search results based on its internal logic.
+pricing:
+  input: '0.00'
+  output: '0.00'
+  unit: '0.000001'
+  currency: RMB

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

@@ -144,7 +144,7 @@ class ZhipuAILargeLanguageModel(_CommonZhipuaiAI, LargeLanguageModel):
             if copy_prompt_message.role in {PromptMessageRole.USER, PromptMessageRole.SYSTEM, PromptMessageRole.TOOL}:
                 if isinstance(copy_prompt_message.content, list):
                     # check if model is 'glm-4v'
-                    if model not in {"glm-4v", "glm-4v-plus"}:
+                    if not model.startswith("glm-4v"):
                         # not support list message
                         continue
                     # get image and
@@ -188,7 +188,7 @@ class ZhipuAILargeLanguageModel(_CommonZhipuaiAI, LargeLanguageModel):
             else:
                 model_parameters["tools"] = [web_search_params]
 
-        if model in {"glm-4v", "glm-4v-plus"}:
+        if model.startswith("glm-4v"):
             params = self._construct_glm_4v_parameter(model, new_prompt_messages, model_parameters)
         else:
             params = {"model": model, "messages": [], **model_parameters}
@@ -412,6 +412,8 @@ class ZhipuAILargeLanguageModel(_CommonZhipuaiAI, LargeLanguageModel):
         human_prompt = "\n\nHuman:"
         ai_prompt = "\n\nAssistant:"
         content = message.content
+        if isinstance(content, list):
+            content = "".join(c.data for c in content if c.type == PromptMessageContentType.TEXT)
 
         if isinstance(message, UserPromptMessage):
             message_text = f"{human_prompt} {content}"

api/core/rag/datasource/vdb/tidb_on_qdrant/tidb_service.py

@@ -162,7 +162,7 @@ class TidbService:
         clusters = []
         tidb_serverless_list_map = {item.cluster_id: item for item in tidb_serverless_list}
         cluster_ids = [item.cluster_id for item in tidb_serverless_list]
-        params = {"clusterIds": cluster_ids, "view": "FULL"}
+        params = {"clusterIds": cluster_ids, "view": "BASIC"}
         response = requests.get(
             f"{api_url}/clusters:batchGet", params=params, auth=HTTPDigestAuth(public_key, private_key)
         )

api/core/workflow/graph_engine/entities/event.py

@@ -1,3 +1,4 @@
+from collections.abc import Mapping
 from datetime import datetime
 from typing import Any, Optional
 
@@ -140,8 +141,8 @@ class BaseIterationEvent(GraphEngineEvent):
 
 class IterationRunStartedEvent(BaseIterationEvent):
     start_at: datetime = Field(..., description="start at")
-    inputs: Optional[dict[str, Any]] = None
-    metadata: Optional[dict[str, Any]] = None
+    inputs: Optional[Mapping[str, Any]] = None
+    metadata: Optional[Mapping[str, Any]] = None
     predecessor_node_id: Optional[str] = None
 
 
@@ -153,18 +154,18 @@ class IterationRunNextEvent(BaseIterationEvent):
 
 class IterationRunSucceededEvent(BaseIterationEvent):
     start_at: datetime = Field(..., description="start at")
-    inputs: Optional[dict[str, Any]] = None
-    outputs: Optional[dict[str, Any]] = None
-    metadata: Optional[dict[str, Any]] = None
+    inputs: Optional[Mapping[str, Any]] = None
+    outputs: Optional[Mapping[str, Any]] = None
+    metadata: Optional[Mapping[str, Any]] = None
     steps: int = 0
     iteration_duration_map: Optional[dict[str, float]] = None
 
 
 class IterationRunFailedEvent(BaseIterationEvent):
     start_at: datetime = Field(..., description="start at")
-    inputs: Optional[dict[str, Any]] = None
-    outputs: Optional[dict[str, Any]] = None
-    metadata: Optional[dict[str, Any]] = None
+    inputs: Optional[Mapping[str, Any]] = None
+    outputs: Optional[Mapping[str, Any]] = None
+    metadata: Optional[Mapping[str, Any]] = None
     steps: int = 0
     error: str = Field(..., description="failed reason")
 

api/core/workflow/nodes/document_extractor/node.py

@@ -1,6 +1,8 @@
 import csv
 import io
 import json
+import os
+import tempfile
 
 import docx
 import pandas as pd
@@ -264,14 +266,20 @@ def _extract_text_from_ppt(file_content: bytes) -> str:
 
 def _extract_text_from_pptx(file_content: bytes) -> str:
     try:
-        with io.BytesIO(file_content) as file:
-            if dify_config.UNSTRUCTURED_API_URL and dify_config.UNSTRUCTURED_API_KEY:
-                elements = partition_via_api(
-                    file=file,
-                    api_url=dify_config.UNSTRUCTURED_API_URL,
-                    api_key=dify_config.UNSTRUCTURED_API_KEY,
-                )
-            else:
+        if dify_config.UNSTRUCTURED_API_URL and dify_config.UNSTRUCTURED_API_KEY:
+            with tempfile.NamedTemporaryFile(suffix=".pptx", delete=False) as temp_file:
+                temp_file.write(file_content)
+                temp_file.flush()
+                with open(temp_file.name, "rb") as file:
+                    elements = partition_via_api(
+                        file=file,
+                        metadata_filename=temp_file.name,
+                        api_url=dify_config.UNSTRUCTURED_API_URL,
+                        api_key=dify_config.UNSTRUCTURED_API_KEY,
+                    )
+                os.unlink(temp_file.name)
+        else:
+            with io.BytesIO(file_content) as file:
                 elements = partition_pptx(file=file)
         return "\n".join([getattr(element, "text", "") for element in elements])
     except Exception as e:

api/core/workflow/nodes/iteration/iteration_node.py

@@ -9,7 +9,7 @@ from typing import TYPE_CHECKING, Any, Optional, cast
 from flask import Flask, current_app
 
 from configs import dify_config
-from core.model_runtime.utils.encoders import jsonable_encoder
+from core.variables import IntegerVariable
 from core.workflow.entities.node_entities import (
     NodeRunMetadataKey,
     NodeRunResult,
@@ -155,32 +155,34 @@ class IterationNode(BaseNode[IterationNodeData]):
             iteration_node_data=self.node_data,
             index=0,
             pre_iteration_output=None,
+            duration=None,
         )
         iter_run_map: dict[str, float] = {}
         outputs: list[Any] = [None] * len(iterator_list_value)
         try:
             if self.node_data.is_parallel:
                 futures: list[Future] = []
-                q = Queue()
+                q: Queue = Queue()
                 thread_pool = GraphEngineThreadPool(max_workers=self.node_data.parallel_nums, max_submit_count=100)
                 for index, item in enumerate(iterator_list_value):
                     future: Future = thread_pool.submit(
                         self._run_single_iter_parallel,
-                        current_app._get_current_object(),
-                        q,
-                        iterator_list_value,
-                        inputs,
-                        outputs,
-                        start_at,
-                        graph_engine,
-                        iteration_graph,
-                        index,
-                        item,
-                        iter_run_map,
+                        flask_app=current_app._get_current_object(),  # type: ignore
+                        q=q,
+                        iterator_list_value=iterator_list_value,
+                        inputs=inputs,
+                        outputs=outputs,
+                        start_at=start_at,
+                        graph_engine=graph_engine,
+                        iteration_graph=iteration_graph,
+                        index=index,
+                        item=item,
+                        iter_run_map=iter_run_map,
                     )
                     future.add_done_callback(thread_pool.task_done_callback)
                     futures.append(future)
                 succeeded_count = 0
+                empty_count = 0
                 while True:
                     try:
                         event = q.get(timeout=1)
@@ -208,17 +210,22 @@ class IterationNode(BaseNode[IterationNodeData]):
             else:
                 for _ in range(len(iterator_list_value)):
                     yield from self._run_single_iter(
-                        iterator_list_value,
-                        variable_pool,
-                        inputs,
-                        outputs,
-                        start_at,
-                        graph_engine,
-                        iteration_graph,
-                        iter_run_map,
+                        iterator_list_value=iterator_list_value,
+                        variable_pool=variable_pool,
+                        inputs=inputs,
+                        outputs=outputs,
+                        start_at=start_at,
+                        graph_engine=graph_engine,
+                        iteration_graph=iteration_graph,
+                        iter_run_map=iter_run_map,
                     )
             if self.node_data.error_handle_mode == ErrorHandleMode.REMOVE_ABNORMAL_OUTPUT:
                 outputs = [output for output in outputs if output is not None]
+
+            # Flatten the list of lists
+            if isinstance(outputs, list) and all(isinstance(output, list) for output in outputs):
+                outputs = [item for sublist in outputs for item in sublist]
+
             yield IterationRunSucceededEvent(
                 iteration_id=self.id,
                 iteration_node_id=self.node_id,
@@ -226,7 +233,7 @@ class IterationNode(BaseNode[IterationNodeData]):
                 iteration_node_data=self.node_data,
                 start_at=start_at,
                 inputs=inputs,
-                outputs={"output": jsonable_encoder(outputs)},
+                outputs={"output": outputs},
                 steps=len(iterator_list_value),
                 metadata={"total_tokens": graph_engine.graph_runtime_state.total_tokens},
             )
@@ -234,8 +241,11 @@ class IterationNode(BaseNode[IterationNodeData]):
             yield RunCompletedEvent(
                 run_result=NodeRunResult(
                     status=WorkflowNodeExecutionStatus.SUCCEEDED,
-                    outputs={"output": jsonable_encoder(outputs)},
-                    metadata={NodeRunMetadataKey.ITERATION_DURATION_MAP: iter_run_map},
+                    outputs={"output": outputs},
+                    metadata={
+                        NodeRunMetadataKey.ITERATION_DURATION_MAP: iter_run_map,
+                        NodeRunMetadataKey.TOTAL_TOKENS: graph_engine.graph_runtime_state.total_tokens,
+                    },
                 )
             )
         except IterationNodeError as e:
@@ -248,7 +258,7 @@ class IterationNode(BaseNode[IterationNodeData]):
                 iteration_node_data=self.node_data,
                 start_at=start_at,
                 inputs=inputs,
-                outputs={"output": jsonable_encoder(outputs)},
+                outputs={"output": outputs},
                 steps=len(iterator_list_value),
                 metadata={"total_tokens": graph_engine.graph_runtime_state.total_tokens},
                 error=str(e),
@@ -280,7 +290,7 @@ class IterationNode(BaseNode[IterationNodeData]):
         :param node_data: node data
         :return:
         """
-        variable_mapping = {
+        variable_mapping: dict[str, Sequence[str]] = {
             f"{node_id}.input_selector": node_data.iterator_selector,
         }
 
@@ -308,7 +318,7 @@ class IterationNode(BaseNode[IterationNodeData]):
                 sub_node_variable_mapping = node_cls.extract_variable_selector_to_variable_mapping(
                     graph_config=graph_config, config=sub_node_config
                 )
-                sub_node_variable_mapping = cast(dict[str, list[str]], sub_node_variable_mapping)
+                sub_node_variable_mapping = cast(dict[str, Sequence[str]], sub_node_variable_mapping)
             except NotImplementedError:
                 sub_node_variable_mapping = {}
 
@@ -329,8 +339,12 @@ class IterationNode(BaseNode[IterationNodeData]):
         return variable_mapping
 
     def _handle_event_metadata(
-        self, event: BaseNodeEvent, iter_run_index: str, parallel_mode_run_id: str
-    ) -> NodeRunStartedEvent | BaseNodeEvent:
+        self,
+        *,
+        event: BaseNodeEvent | InNodeEvent,
+        iter_run_index: int,
+        parallel_mode_run_id: str | None,
+    ) -> NodeRunStartedEvent | BaseNodeEvent | InNodeEvent:
         """
         add iteration metadata to event.
         """
@@ -355,9 +369,10 @@ class IterationNode(BaseNode[IterationNodeData]):
 
     def _run_single_iter(
         self,
-        iterator_list_value: list[str],
+        *,
+        iterator_list_value: Sequence[str],
         variable_pool: VariablePool,
-        inputs: dict[str, list],
+        inputs: Mapping[str, list],
         outputs: list,
         start_at: datetime,
         graph_engine: "GraphEngine",
@@ -373,12 +388,12 @@ class IterationNode(BaseNode[IterationNodeData]):
         try:
             rst = graph_engine.run()
             # get current iteration index
-            current_index = variable_pool.get([self.node_id, "index"]).value
+            index_variable = variable_pool.get([self.node_id, "index"])
+            if not isinstance(index_variable, IntegerVariable):
+                raise IterationIndexNotFoundError(f"iteration {self.node_id} current index not found")
+            current_index = index_variable.value
             iteration_run_id = parallel_mode_run_id if parallel_mode_run_id is not None else f"{current_index}"
             next_index = int(current_index) + 1
-
-            if current_index is None:
-                raise IterationIndexNotFoundError(f"iteration {self.node_id} current index not found")
             for event in rst:
                 if isinstance(event, (BaseNodeEvent | BaseParallelBranchEvent)) and not event.in_iteration_id:
                     event.in_iteration_id = self.node_id
@@ -391,7 +406,9 @@ class IterationNode(BaseNode[IterationNodeData]):
                     continue
 
                 if isinstance(event, NodeRunSucceededEvent):
-                    yield self._handle_event_metadata(event, current_index, parallel_mode_run_id)
+                    yield self._handle_event_metadata(
+                        event=event, iter_run_index=current_index, parallel_mode_run_id=parallel_mode_run_id
+                    )
                 elif isinstance(event, BaseGraphEvent):
                     if isinstance(event, GraphRunFailedEvent):
                         # iteration run failed
@@ -404,7 +421,7 @@ class IterationNode(BaseNode[IterationNodeData]):
                                 parallel_mode_run_id=parallel_mode_run_id,
                                 start_at=start_at,
                                 inputs=inputs,
-                                outputs={"output": jsonable_encoder(outputs)},
+                                outputs={"output": outputs},
                                 steps=len(iterator_list_value),
                                 metadata={"total_tokens": graph_engine.graph_runtime_state.total_tokens},
                                 error=event.error,
@@ -417,7 +434,7 @@ class IterationNode(BaseNode[IterationNodeData]):
                                 iteration_node_data=self.node_data,
                                 start_at=start_at,
                                 inputs=inputs,
-                                outputs={"output": jsonable_encoder(outputs)},
+                                outputs={"output": outputs},
                                 steps=len(iterator_list_value),
                                 metadata={"total_tokens": graph_engine.graph_runtime_state.total_tokens},
                                 error=event.error,
@@ -429,9 +446,11 @@ class IterationNode(BaseNode[IterationNodeData]):
                             )
                         )
                         return
-                else:
-                    event = cast(InNodeEvent, event)
-                    metadata_event = self._handle_event_metadata(event, current_index, parallel_mode_run_id)
+                elif isinstance(event, InNodeEvent):
+                    # event = cast(InNodeEvent, event)
+                    metadata_event = self._handle_event_metadata(
+                        event=event, iter_run_index=current_index, parallel_mode_run_id=parallel_mode_run_id
+                    )
                     if isinstance(event, NodeRunFailedEvent):
                         if self.node_data.error_handle_mode == ErrorHandleMode.CONTINUE_ON_ERROR:
                             yield NodeInIterationFailedEvent(
@@ -513,7 +532,7 @@ class IterationNode(BaseNode[IterationNodeData]):
                 iteration_node_data=self.node_data,
                 index=next_index,
                 parallel_mode_run_id=parallel_mode_run_id,
-                pre_iteration_output=jsonable_encoder(current_iteration_output) if current_iteration_output else None,
+                pre_iteration_output=current_iteration_output or None,
                 duration=duration,
             )
 
@@ -540,10 +559,11 @@ class IterationNode(BaseNode[IterationNodeData]):
 
     def _run_single_iter_parallel(
         self,
+        *,
         flask_app: Flask,
         q: Queue,
-        iterator_list_value: list[str],
-        inputs: dict[str, list],
+        iterator_list_value: Sequence[str],
+        inputs: Mapping[str, list],
         outputs: list,
         start_at: datetime,
         graph_engine: "GraphEngine",
@@ -551,7 +571,7 @@ class IterationNode(BaseNode[IterationNodeData]):
         index: int,
         item: Any,
         iter_run_map: dict[str, float],
-    ) -> Generator[NodeEvent | InNodeEvent, None, None]:
+    ):
         """
         run single iteration in parallel mode
         """

api/libs/oauth_data_source.py

@@ -253,6 +253,8 @@ class NotionOAuth(OAuthDataSource):
         }
         response = requests.get(url=f"{self._NOTION_BLOCK_SEARCH}/{block_id}", headers=headers)
         response_json = response.json()
+        if response.status_code != 200:
+            raise ValueError(f"Error fetching block parent page ID: {response_json.message}")
         parent = response_json["parent"]
         parent_type = parent["type"]
         if parent_type == "block_id":

api/schedule/clean_messages.py

@@ -36,14 +36,16 @@ def clean_messages():
                 db.session.query(Message)
                 .filter(Message.created_at < plan_sandbox_clean_message_day)
                 .order_by(Message.created_at.desc())
-                .paginate(page=page, per_page=100)
+                .limit(100)
+                .all()
             )
 
         except NotFound:
             break
-        if messages.items is None or len(messages.items) == 0:
+        if not messages:
             break
-        for message in messages.items:
+        for message in messages:
+            plan_sandbox_clean_message_day = message.created_at
             app = App.query.filter_by(id=message.app_id).first()
             features_cache_key = f"features:{app.tenant_id}"
             plan_cache = redis_client.get(features_cache_key)

api/services/tools/workflow_tools_manage_service.py

@@ -81,6 +81,10 @@ class WorkflowToolManageService:
         db.session.add(workflow_tool_provider)
         db.session.commit()
 
+        if labels is not None:
+            ToolLabelManager.update_tool_labels(
+                ToolTransformService.workflow_provider_to_controller(workflow_tool_provider), labels
+            )
         return {"result": "success"}
 
     @classmethod

api/tests/unit_tests/configs/test_dify_config.py

@@ -37,7 +37,11 @@ def test_dify_config_undefined_entry(example_env_file):
         assert config["LOG_LEVEL"] == "INFO"
 
 
+# NOTE: If there is a `.env` file in your Workspace, this test might not succeed as expected.
+# This is due to `pymilvus` loading all the variables from the `.env` file into `os.environ`.
 def test_dify_config(example_env_file):
+    # clear system environment variables
+    os.environ.clear()
     # load dotenv file with pydantic-settings
     config = DifyConfig(_env_file=example_env_file)
 

docker-legacy/docker-compose.yaml

@@ -2,7 +2,7 @@ version: '3'
 services:
   # API service
   api:
-    image: langgenius/dify-api:0.13.1
+    image: langgenius/dify-api:0.13.2
     restart: always
     environment:
       # Startup mode, 'api' starts the API server.
@@ -227,7 +227,7 @@ services:
   # worker service
   # The Celery worker for processing the queue.
   worker:
-    image: langgenius/dify-api:0.13.1
+    image: langgenius/dify-api:0.13.2
     restart: always
     environment:
       CONSOLE_WEB_URL: ''
@@ -397,7 +397,7 @@ services:
 
   # Frontend web application.
   web:
-    image: langgenius/dify-web:0.13.1
+    image: langgenius/dify-web:0.13.2
     restart: always
     environment:
       # The base URL of console application api server, refers to the Console base URL of WEB service if console domain is

docker/docker-compose.yaml

@@ -292,7 +292,7 @@ x-shared-env: &shared-api-worker-env
 services:
   # API service
   api:
-    image: langgenius/dify-api:0.13.1
+    image: langgenius/dify-api:0.13.2
     restart: always
     environment:
       # Use the shared environment variables.
@@ -312,7 +312,7 @@ services:
   # worker service
   # The Celery worker for processing the queue.
   worker:
-    image: langgenius/dify-api:0.13.1
+    image: langgenius/dify-api:0.13.2
     restart: always
     environment:
       # Use the shared environment variables.
@@ -331,7 +331,7 @@ services:
 
   # Frontend web application.
   web:
-    image: langgenius/dify-web:0.13.1
+    image: langgenius/dify-web:0.13.2
     restart: always
     environment:
       CONSOLE_API_URL: ${CONSOLE_API_URL:-}

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

@@ -9,7 +9,7 @@ import s from './style.module.css'
 import cn from '@/utils/classnames'
 import type { App } from '@/types/app'
 import Confirm from '@/app/components/base/confirm'
-import { ToastContext } from '@/app/components/base/toast'
+import Toast, { ToastContext } from '@/app/components/base/toast'
 import { copyApp, deleteApp, exportAppConfig, updateAppInfo } from '@/service/apps'
 import DuplicateAppModal from '@/app/components/app/duplicate-modal'
 import type { DuplicateAppModalProps } from '@/app/components/app/duplicate-modal'
@@ -31,6 +31,7 @@ import TagSelector from '@/app/components/base/tag-management/selector'
 import type { EnvironmentVariable } from '@/app/components/workflow/types'
 import DSLExportConfirmModal from '@/app/components/workflow/dsl-export-confirm-modal'
 import { fetchWorkflowDraft } from '@/service/workflow'
+import { fetchInstalledAppList } from '@/service/explore'
 
 export type AppCardProps = {
   app: App
@@ -209,6 +210,21 @@ const AppCard = ({ app, onRefresh }: AppCardProps) => {
       e.preventDefault()
       setShowConfirmDelete(true)
     }
+    const onClickInstalledApp = async (e: React.MouseEvent<HTMLButtonElement>) => {
+      e.stopPropagation()
+      props.onClick?.()
+      e.preventDefault()
+      try {
+        const { installed_apps }: any = await fetchInstalledAppList(app.id) || {}
+        if (installed_apps?.length > 0)
+          window.open(`/explore/installed/${installed_apps[0].id}`, '_blank')
+        else
+          throw new Error('No app found in Explore')
+      }
+      catch (e: any) {
+        Toast.notify({ type: 'error', message: `${e.message || e}` })
+      }
+    }
     return (
       <div className="relative w-full py-1" onMouseLeave={onMouseLeave}>
         <button className={s.actionItem} onClick={onClickSettings}>
@@ -233,6 +249,10 @@ const AppCard = ({ app, onRefresh }: AppCardProps) => {
           </>
         )}
         <Divider className="!my-1" />
+        <button className={s.actionItem} onClick={onClickInstalledApp}>
+          <span className={s.actionName}>{t('app.openInExplore')}</span>
+        </button>
+        <Divider className="!my-1" />
         <div
           className={cn(s.actionItem, s.deleteActionItem, 'group')}
           onClick={onClickDelete}
@@ -353,10 +373,10 @@ const AppCard = ({ app, onRefresh }: AppCardProps) => {
                   }
                   popupClassName={
                     (app.mode === 'completion' || app.mode === 'chat')
-                      ? '!w-[238px] translate-x-[-110px]'
-                      : ''
+                      ? '!w-[256px] translate-x-[-224px]'
+                      : '!w-[160px] translate-x-[-128px]'
                   }
-                  className={'!w-[128px] h-fit !z-20'}
+                  className={'h-fit !z-20'}
                 />
               </div>
             </>

web/app/components/app/app-publisher/index.tsx

@@ -5,7 +5,8 @@ import {
 } from 'react'
 import { useTranslation } from 'react-i18next'
 import dayjs from 'dayjs'
-import { RiArrowDownSLine } from '@remixicon/react'
+import { RiArrowDownSLine, RiPlanetLine } from '@remixicon/react'
+import Toast from '../../base/toast'
 import type { ModelAndParameter } from '../configuration/debug/types'
 import SuggestedAction from './suggested-action'
 import PublishWithMultipleModel from './publish-with-multiple-model'
@@ -15,6 +16,7 @@ import {
   PortalToFollowElemContent,
   PortalToFollowElemTrigger,
 } from '@/app/components/base/portal-to-follow-elem'
+import { fetchInstalledAppList } from '@/service/explore'
 import EmbeddedModal from '@/app/components/app/overview/embedded'
 import { useStore as useAppStore } from '@/app/components/app/store'
 import { useGetLanguage } from '@/context/i18n'
@@ -105,6 +107,19 @@ const AppPublisher = ({
       setPublished(false)
   }, [disabled, onToggle, open])
 
+  const handleOpenInExplore = useCallback(async () => {
+    try {
+      const { installed_apps }: any = await fetchInstalledAppList(appDetail?.id) || {}
+      if (installed_apps?.length > 0)
+        window.open(`/explore/installed/${installed_apps[0].id}`, '_blank')
+      else
+        throw new Error('No app found in Explore')
+    }
+    catch (e: any) {
+      Toast.notify({ type: 'error', message: `${e.message || e}` })
+    }
+  }, [appDetail?.id])
+
   const [embeddingModalOpen, setEmbeddingModalOpen] = useState(false)
 
   return (
@@ -205,6 +220,15 @@ const AppPublisher = ({
                   {t('workflow.common.embedIntoSite')}
                 </SuggestedAction>
               )}
+            <SuggestedAction
+              onClick={() => {
+                handleOpenInExplore()
+              }}
+              disabled={!publishedAt}
+              icon={<RiPlanetLine className='w-4 h-4' />}
+            >
+              {t('workflow.common.openInExplore')}
+            </SuggestedAction>
             <SuggestedAction disabled={!publishedAt} link='./develop' icon={<FileText className='w-4 h-4' />}>{t('workflow.common.accessAPIReference')}</SuggestedAction>
             {appDetail?.mode === 'workflow' && (
               <WorkflowToolConfigureButton

web/app/components/base/app-icon-picker/ImageInput.tsx

@@ -11,16 +11,19 @@ import { useDraggableUploader } from './hooks'
 import { checkIsAnimatedImage } from './utils'
 import { ALLOW_FILE_EXTENSIONS } from '@/types/app'
 
-type UploaderProps = {
-  className?: string
-  onImageCropped?: (tempUrl: string, croppedAreaPixels: Area, fileName: string) => void
-  onUpload?: (file?: File) => void
+export type OnImageInput = {
+  (isCropped: true, tempUrl: string, croppedAreaPixels: Area, fileName: string): void
+  (isCropped: false, file: File): void
 }
 
-const Uploader: FC<UploaderProps> = ({
+type UploaderProps = {
+  className?: string
+  onImageInput?: OnImageInput
+}
+
+const ImageInput: FC<UploaderProps> = ({
   className,
-  onImageCropped,
-  onUpload,
+  onImageInput,
 }) => {
   const [inputImage, setInputImage] = useState<{ file: File; url: string }>()
   const [isAnimatedImage, setIsAnimatedImage] = useState<boolean>(false)
@@ -37,8 +40,7 @@ const Uploader: FC<UploaderProps> = ({
   const onCropComplete = async (_: Area, croppedAreaPixels: Area) => {
     if (!inputImage)
       return
-    onImageCropped?.(inputImage.url, croppedAreaPixels, inputImage.file.name)
-    onUpload?.(undefined)
+    onImageInput?.(true, inputImage.url, croppedAreaPixels, inputImage.file.name)
   }
 
   const handleLocalFileInput = (e: ChangeEvent<HTMLInputElement>) => {
@@ -48,7 +50,7 @@ const Uploader: FC<UploaderProps> = ({
       checkIsAnimatedImage(file).then((isAnimatedImage) => {
         setIsAnimatedImage(!!isAnimatedImage)
         if (isAnimatedImage)
-          onUpload?.(file)
+          onImageInput?.(false, file)
       })
     }
   }
@@ -117,4 +119,4 @@ const Uploader: FC<UploaderProps> = ({
   )
 }
 
-export default Uploader
+export default ImageInput

web/app/components/base/app-icon-picker/index.tsx

@@ -8,12 +8,14 @@ import Button from '../button'
 import { ImagePlus } from '../icons/src/vender/line/images'
 import { useLocalFileUploader } from '../image-uploader/hooks'
 import EmojiPickerInner from '../emoji-picker/Inner'
-import Uploader from './Uploader'
+import type { OnImageInput } from './ImageInput'
+import ImageInput from './ImageInput'
 import s from './style.module.css'
 import getCroppedImg from './utils'
 import type { AppIconType, ImageFile } from '@/types/app'
 import cn from '@/utils/classnames'
 import { DISABLE_UPLOAD_IMAGE_AS_ICON } from '@/config'
+
 export type AppIconEmojiSelection = {
   type: 'emoji'
   icon: string
@@ -69,14 +71,15 @@ const AppIconPicker: FC<AppIconPickerProps> = ({
     },
   })
 
-  const [imageCropInfo, setImageCropInfo] = useState<{ tempUrl: string; croppedAreaPixels: Area; fileName: string }>()
-  const handleImageCropped = async (tempUrl: string, croppedAreaPixels: Area, fileName: string) => {
-    setImageCropInfo({ tempUrl, croppedAreaPixels, fileName })
-  }
+  type InputImageInfo = { file: File } | { tempUrl: string; croppedAreaPixels: Area; fileName: string }
+  const [inputImageInfo, setInputImageInfo] = useState<InputImageInfo>()
 
-  const [uploadImageInfo, setUploadImageInfo] = useState<{ file?: File }>()
-  const handleUpload = async (file?: File) => {
-    setUploadImageInfo({ file })
+  const handleImageInput: OnImageInput = async (isCropped: boolean, fileOrTempUrl: string | File, croppedAreaPixels?: Area, fileName?: string) => {
+    setInputImageInfo(
+      isCropped
+        ? { tempUrl: fileOrTempUrl as string, croppedAreaPixels: croppedAreaPixels!, fileName: fileName! }
+        : { file: fileOrTempUrl as File },
+    )
   }
 
   const handleSelect = async () => {
@@ -90,15 +93,15 @@ const AppIconPicker: FC<AppIconPickerProps> = ({
       }
     }
     else {
-      if (!imageCropInfo && !uploadImageInfo)
+      if (!inputImageInfo)
         return
       setUploading(true)
-      if (imageCropInfo.file) {
-        handleLocalFileUpload(imageCropInfo.file)
+      if ('file' in inputImageInfo) {
+        handleLocalFileUpload(inputImageInfo.file)
         return
       }
-      const blob = await getCroppedImg(imageCropInfo.tempUrl, imageCropInfo.croppedAreaPixels, imageCropInfo.fileName)
-      const file = new File([blob], imageCropInfo.fileName, { type: blob.type })
+      const blob = await getCroppedImg(inputImageInfo.tempUrl, inputImageInfo.croppedAreaPixels, inputImageInfo.fileName)
+      const file = new File([blob], inputImageInfo.fileName, { type: blob.type })
       handleLocalFileUpload(file)
     }
   }
@@ -127,10 +130,8 @@ const AppIconPicker: FC<AppIconPickerProps> = ({
       </div>
     </div>}
 
-    <Divider className='m-0' />
-
-    <EmojiPickerInner className={activeTab === 'emoji' ? 'block' : 'hidden'} onSelect={handleSelectEmoji} />
-    <Uploader className={activeTab === 'image' ? 'block' : 'hidden'} onImageCropped={handleImageCropped} onUpload={handleUpload}/>
+    <EmojiPickerInner className={cn(activeTab === 'emoji' ? 'block' : 'hidden', 'pt-2')} onSelect={handleSelectEmoji} />
+    <ImageInput className={activeTab === 'image' ? 'block' : 'hidden'} onImageInput={handleImageInput} />
 
     <Divider className='m-0' />
     <div className='w-full flex items-center justify-center p-3 gap-2'>

web/app/components/base/app-icon-picker/utils.ts

@@ -116,12 +116,12 @@ export default async function getCroppedImg(
   })
 }
 
-export function checkIsAnimatedImage(file) {
+export function checkIsAnimatedImage(file: File): Promise<boolean> {
   return new Promise((resolve, reject) => {
     const fileReader = new FileReader()
 
     fileReader.onload = function (e) {
-      const arr = new Uint8Array(e.target.result)
+      const arr = new Uint8Array(e.target?.result as ArrayBuffer)
 
       // Check file extension
       const fileName = file.name.toLowerCase()
@@ -148,7 +148,7 @@ export function checkIsAnimatedImage(file) {
 }
 
 // Function to check for WebP signature
-function isWebP(arr) {
+function isWebP(arr: Uint8Array) {
   return (
     arr[0] === 0x52 && arr[1] === 0x49 && arr[2] === 0x46 && arr[3] === 0x46
     && arr[8] === 0x57 && arr[9] === 0x45 && arr[10] === 0x42 && arr[11] === 0x50
@@ -156,7 +156,7 @@ function isWebP(arr) {
 }
 
 // Function to check if the WebP is animated (contains ANIM chunk)
-function checkWebPAnimation(arr) {
+function checkWebPAnimation(arr: Uint8Array) {
   // Search for the ANIM chunk in WebP to determine if it's animated
   for (let i = 12; i < arr.length - 4; i++) {
     if (arr[i] === 0x41 && arr[i + 1] === 0x4E && arr[i + 2] === 0x49 && arr[i + 3] === 0x4D)

web/app/components/base/emoji-picker/Inner.tsx

@@ -68,7 +68,7 @@ const EmojiPickerInner: FC<IEmojiPickerInnerProps> = ({
   }, [onSelect, selectedEmoji, selectedBackground])
 
   return <div className={cn(className)}>
-    <div className='flex flex-col items-center w-full px-3'>
+    <div className='flex flex-col items-center w-full px-3 pb-2'>
       <div className="relative w-full">
         <div className="absolute inset-y-0 left-0 flex items-center pl-3 pointer-events-none">
           <MagnifyingGlassIcon className="w-5 h-5 text-gray-400" aria-hidden="true" />

web/app/components/base/file-uploader/utils.ts

@@ -158,13 +158,13 @@ export const isAllowedFileExtension = (fileName: string, fileMimetype: string, a
 
 export const getFilesInLogs = (rawData: any) => {
   const result = Object.keys(rawData || {}).map((key) => {
-    if (typeof rawData[key] === 'object' && rawData[key].dify_model_identity === '__dify__file__') {
+    if (typeof rawData[key] === 'object' && rawData[key]?.dify_model_identity === '__dify__file__') {
       return {
         varName: key,
         list: getProcessedFilesFromResponse([rawData[key]]),
       }
     }
-    if (Array.isArray(rawData[key]) && rawData[key].some(item => item.dify_model_identity === '__dify__file__')) {
+    if (Array.isArray(rawData[key]) && rawData[key].some(item => item?.dify_model_identity === '__dify__file__')) {
       return {
         varName: key,
         list: getProcessedFilesFromResponse(rawData[key]),

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

@@ -1,7 +1,6 @@
 import React, { useCallback, useEffect, useRef, useState } from 'react'
 import mermaid from 'mermaid'
 import { usePrevious } from 'ahooks'
-import CryptoJS from 'crypto-js'
 import { useTranslation } from 'react-i18next'
 import { ExclamationTriangleIcon } from '@heroicons/react/24/outline'
 import LoadingAnim from '@/app/components/base/chat/chat/loading-anim'
@@ -14,12 +13,6 @@ mermaidAPI = null
 if (typeof window !== 'undefined')
   mermaidAPI = mermaid.mermaidAPI
 
-const style = {
-  minWidth: '480px',
-  height: 'auto',
-  overflow: 'auto',
-}
-
 const svgToBase64 = (svgGraph: string) => {
   const svgBytes = new TextEncoder().encode(svgGraph)
   const blob = new Blob([svgBytes], { type: 'image/svg+xml;charset=utf-8' })
@@ -38,7 +31,6 @@ const Flowchart = React.forwardRef((props: {
   const [svgCode, setSvgCode] = useState(null)
   const [look, setLook] = useState<'classic' | 'handDrawn'>('classic')
 
-  const chartId = useRef(`flowchart_${CryptoJS.MD5(props.PrimitiveCode).toString()}`)
   const prevPrimitiveCode = usePrevious(props.PrimitiveCode)
   const [isLoading, setIsLoading] = useState(true)
   const timeRef = useRef<NodeJS.Timeout>()
@@ -51,12 +43,10 @@ const Flowchart = React.forwardRef((props: {
 
     try {
       if (typeof window !== 'undefined' && mermaidAPI) {
-        const svgGraph = await mermaidAPI.render(chartId.current, PrimitiveCode)
+        const svgGraph = await mermaidAPI.render('flowchart', PrimitiveCode)
         const base64Svg: any = await svgToBase64(svgGraph.svg)
         setSvgCode(base64Svg)
         setIsLoading(false)
-        if (chartId.current && base64Svg)
-          localStorage.setItem(chartId.current, base64Svg)
       }
     }
     catch (error) {
@@ -79,19 +69,11 @@ const Flowchart = React.forwardRef((props: {
         },
       })
 
-      localStorage.removeItem(chartId.current)
       renderFlowchart(props.PrimitiveCode)
     }
   }, [look])
 
   useEffect(() => {
-    const cachedSvg: any = localStorage.getItem(chartId.current)
-
-    if (cachedSvg) {
-      setSvgCode(cachedSvg)
-      setIsLoading(false)
-      return
-    }
     if (timeRef.current)
       clearTimeout(timeRef.current)
 
@@ -130,8 +112,8 @@ const Flowchart = React.forwardRef((props: {
       </div>
       {
         svgCode
-            && <div className="mermaid cursor-pointer" style={style} onClick={() => setImagePreviewUrl(svgCode)}>
-              {svgCode && <img src={svgCode} style={{ width: '100%', height: 'auto' }} alt="mermaid_chart" />}
+            && <div className="mermaid cursor-pointer h-auto w-full object-fit: cover" onClick={() => setImagePreviewUrl(svgCode)}>
+              {svgCode && <img src={svgCode} alt="mermaid_chart" />}
             </div>
       }
       {isLoading

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

@@ -123,11 +123,25 @@ Toast.notify = ({
     const holder = document.createElement('div')
     const root = createRoot(holder)
 
-    root.render(<Toast type={type} size={size} message={message} duration={duration} className={className} />)
+    root.render(
+      <ToastContext.Provider value={{
+        notify: () => {},
+        close: () => {
+          if (holder) {
+            root.unmount()
+            holder.remove()
+          }
+        },
+      }}>
+        <Toast type={type} size={size} message={message} duration={duration} className={className} />
+      </ToastContext.Provider>,
+    )
     document.body.appendChild(holder)
     setTimeout(() => {
-      if (holder)
+      if (holder) {
+        root.unmount()
         holder.remove()
+      }
     }, duration || defaultDuring)
   }
 }

web/app/components/workflow/nodes/_base/components/variable-tag.tsx

@@ -72,7 +72,7 @@ const VariableTag = ({
         {isEnv && <Env className='shrink-0 mr-0.5 w-3.5 h-3.5 text-util-colors-violet-violet-600' />}
         {isChatVar && <BubbleX className='w-3.5 h-3.5 text-util-colors-teal-teal-700' />}
         <div
-          className={cn('truncate text-text-accent font-medium', (isEnv || isChatVar) && 'text-text-secondary')}
+          className={cn('truncate ml-0.5 text-text-accent font-medium', (isEnv || isChatVar) && 'text-text-secondary')}
           title={variableName}
         >
           {variableName}

web/app/components/workflow/nodes/_base/components/variable/var-reference-vars.tsx

@@ -274,7 +274,7 @@ const VarReferenceVars: FC<Props> = ({
       {
         !hideSearch && (
           <>
-            <div className={cn('mb-2 mx-1', searchBoxClassName)} onClick={e => e.stopPropagation()}>
+            <div className={cn('mb-1 mx-2 mt-2', searchBoxClassName)} onClick={e => e.stopPropagation()}>
               <Input
                 showLeftIcon
                 showClearIcon

web/app/components/workflow/nodes/if-else/components/condition-list/condition-item.tsx

@@ -25,10 +25,12 @@ import { FILE_TYPE_OPTIONS, SUB_VARIABLES, TRANSFER_METHOD } from '../../default
 import ConditionWrap from '../condition-wrap'
 import ConditionOperator from './condition-operator'
 import ConditionInput from './condition-input'
-import VariableTag from '@/app/components/workflow/nodes/_base/components/variable-tag'
+
+import ConditionVarSelector from './condition-var-selector'
 import type {
   Node,
   NodeOutPutVar,
+  ValueSelector,
   Var,
 } from '@/app/components/workflow/types'
 import { VarType } from '@/app/components/workflow/types'
@@ -82,6 +84,7 @@ const ConditionItem = ({
   const { t } = useTranslation()
 
   const [isHovered, setIsHovered] = useState(false)
+  const [open, setOpen] = useState(false)
 
   const doUpdateCondition = useCallback((newCondition: Condition) => {
     if (isSubVariableKey)
@@ -190,6 +193,17 @@ const ConditionItem = ({
       onRemoveCondition?.(caseId, condition.id)
   }, [caseId, condition, conditionId, isSubVariableKey, onRemoveCondition, onRemoveSubVariableCondition])
 
+  const handleVarChange = useCallback((valueSelector: ValueSelector, varItem: Var) => {
+    const newCondition = produce(condition, (draft) => {
+      draft.variable_selector = valueSelector
+      draft.varType = varItem.type
+      draft.value = ''
+      draft.comparison_operator = getOperators(varItem.type)[0]
+    })
+    doUpdateCondition(newCondition)
+    setOpen(false)
+  }, [condition, doUpdateCondition])
+
   return (
     <div className={cn('flex mb-1 last-of-type:mb-0', className)}>
       <div className={cn(
@@ -221,11 +235,14 @@ const ConditionItem = ({
                 />
               )
               : (
-                <VariableTag
+                <ConditionVarSelector
+                  open={open}
+                  onOpenChange={setOpen}
                   valueSelector={condition.variable_selector || []}
                   varType={condition.varType}
                   availableNodes={availableNodes}
-                  isShort
+                  nodesOutputVars={nodesOutputVars}
+                  onChange={handleVarChange}
                 />
               )}
 

web/app/components/workflow/nodes/if-else/components/condition-list/condition-var-selector.tsx

@@ -0,0 +1,58 @@
+import { PortalToFollowElem, PortalToFollowElemContent, PortalToFollowElemTrigger } from '@/app/components/base/portal-to-follow-elem'
+import VariableTag from '@/app/components/workflow/nodes/_base/components/variable-tag'
+import VarReferenceVars from '@/app/components/workflow/nodes/_base/components/variable/var-reference-vars'
+import type { Node, NodeOutPutVar, ValueSelector, Var, VarType } from '@/app/components/workflow/types'
+
+type ConditionVarSelectorProps = {
+  open: boolean
+  onOpenChange: (open: boolean) => void
+  valueSelector: ValueSelector
+  varType: VarType
+  availableNodes: Node[]
+  nodesOutputVars: NodeOutPutVar[]
+  onChange: (valueSelector: ValueSelector, varItem: Var) => void
+}
+
+const ConditionVarSelector = ({
+  open,
+  onOpenChange,
+  valueSelector,
+  varType,
+  availableNodes,
+  nodesOutputVars,
+  onChange,
+}: ConditionVarSelectorProps) => {
+  return (
+    <PortalToFollowElem
+      open={open}
+      onOpenChange={onOpenChange}
+      placement='bottom-start'
+      offset={{
+        mainAxis: 4,
+        crossAxis: 0,
+      }}
+    >
+      <PortalToFollowElemTrigger onClick={() => onOpenChange(!open)}>
+        <div className="cursor-pointer">
+          <VariableTag
+            valueSelector={valueSelector}
+            varType={varType}
+            availableNodes={availableNodes}
+            isShort
+          />
+        </div>
+      </PortalToFollowElemTrigger>
+      <PortalToFollowElemContent className='z-[1000]'>
+        <div className='w-[296px] bg-components-panel-bg-blur rounded-lg border-[0.5px] border-components-panel-border shadow-lg'>
+          <VarReferenceVars
+            vars={nodesOutputVars}
+            isSupportFileVar
+            onChange={onChange}
+          />
+        </div>
+      </PortalToFollowElemContent>
+    </PortalToFollowElem>
+  )
+}
+
+export default ConditionVarSelector

web/app/components/workflow/nodes/if-else/components/condition-value.tsx

@@ -73,7 +73,7 @@ const ConditionValue = ({
 
       <div
         className={cn(
-          'shrink-0  truncate text-xs font-medium text-text-accent',
+          'shrink-0 ml-0.5 truncate text-xs font-medium text-text-accent',
           !notHasValue && 'max-w-[70px]',
         )}
         title={variableName}

web/app/components/workflow/run/output-panel.tsx

@@ -35,12 +35,12 @@ const OutputPanel: FC<OutputPanelProps> = ({
     for (const key in outputs) {
       if (Array.isArray(outputs[key])) {
         outputs[key].map((output: any) => {
-          if (output.dify_model_identity === '__dify__file__')
+          if (output?.dify_model_identity === '__dify__file__')
             fileList.push(output)
           return null
         })
       }
-      else if (outputs[key].dify_model_identity === '__dify__file__') {
+      else if (outputs[key]?.dify_model_identity === '__dify__file__') {
         fileList.push(outputs[key])
       }
     }

web/i18n/en-US/app.ts

@@ -101,6 +101,7 @@ const translation = {
   switchLabel: 'The app copy to be created',
   removeOriginal: 'Delete the original app',
   switchStart: 'Start switch',
+  openInExplore: 'Open in Explore',
   typeSelector: {
     all: 'ALL Types',
     chatbot: 'Chatbot',

web/i18n/en-US/workflow.ts

@@ -32,6 +32,7 @@ const translation = {
     restore: 'Restore',
     runApp: 'Run App',
     batchRunApp: 'Batch Run App',
+    openInExplore: 'Open in Explore',
     accessAPIReference: 'Access API Reference',
     embedIntoSite: 'Embed Into Site',
     addTitle: 'Add title...',

web/i18n/ja-JP/app-log.ts

@@ -80,7 +80,7 @@ const translation = {
     title: '会話ログ',
     workflowTitle: 'ログの詳細',
     fileListLabel: 'ファイルの詳細',
-    fileListDetail: 'ディテール',
+    fileListDetail: '詳細',
   },
   promptLog: 'プロンプトログ',
   agentLog: 'エージェントログ',

web/i18n/ja-JP/app.ts

@@ -93,6 +93,7 @@ const translation = {
   switchLabel: '作成されるアプリのコピー',
   removeOriginal: '元のアプリを削除する',
   switchStart: '切り替えを開始する',
+  openInExplore: '"探索" で開く',
   typeSelector: {
     all: 'すべてのタイプ',
     chatbot: 'チャットボット',

web/i18n/ja-JP/workflow.ts

@@ -32,6 +32,7 @@ const translation = {
     restore: '復元',
     runApp: 'アプリを実行',
     batchRunApp: 'バッチでアプリを実行',
+    openInExplore: '"探索" で開く',
     accessAPIReference: 'APIリファレンスにアクセス',
     embedIntoSite: 'サイトに埋め込む',
     addTitle: 'タイトルを追加...',

web/package.json

@@ -1,6 +1,6 @@
 {
   "name": "dify-web",
-  "version": "0.13.1",
+  "version": "0.13.2",
   "private": true,
   "engines": {
     "node": ">=18.17.0"

web/service/explore.ts

@@ -12,8 +12,8 @@ export const fetchAppDetail = (id: string): Promise<any> => {
   return get(`/explore/apps/${id}`)
 }
 
-export const fetchInstalledAppList = () => {
-  return get('/installed-apps')
+export const fetchInstalledAppList = (app_id?: string | null) => {
+  return get(`/installed-apps${app_id ? `?app_id=${app_id}` : ''}`)
 }
 
 export const installApp = (id: string) => {