chore: bump version to 1.13.2 (#33681)

Co-authored-by: gemini-code-assist[bot] <176961590+gemini-code-assist[bot]@users.noreply.github.com>
Co-authored-by: autofix-ci[bot] <114827586+autofix-ci[bot]@users.noreply.github.com>

api/configs/middleware/cache/redis_config.py

@@ -1,4 +1,4 @@
-from pydantic import Field, NonNegativeInt, PositiveFloat, PositiveInt
+from pydantic import Field, NonNegativeInt, PositiveFloat, PositiveInt, field_validator
 from pydantic_settings import BaseSettings
 
 
@@ -116,3 +116,13 @@ class RedisConfig(BaseSettings):
         description="Maximum connections in the Redis connection pool (unset for library default)",
         default=None,
     )
+
+    @field_validator("REDIS_MAX_CONNECTIONS", mode="before")
+    @classmethod
+    def _empty_string_to_none_for_max_conns(cls, v):
+        """Allow empty string in env/.env to mean 'unset' (None)."""
+        if v is None:
+            return None
+        if isinstance(v, str) and v.strip() == "":
+            return None
+        return v

api/core/rag/datasource/vdb/weaviate/weaviate_vector.py

@@ -5,6 +5,7 @@ This module provides integration with Weaviate vector database for storing and r
 document embeddings used in retrieval-augmented generation workflows.
 """
 
+import atexit
 import datetime
 import json
 import logging
@@ -37,6 +38,32 @@ _weaviate_client: weaviate.WeaviateClient | None = None
 _weaviate_client_lock = threading.Lock()
 
 
+def _shutdown_weaviate_client() -> None:
+    """
+    Best-effort shutdown hook to close the module-level Weaviate client.
+
+    This is registered with atexit so that HTTP/gRPC resources are released
+    when the Python interpreter exits.
+    """
+    global _weaviate_client
+
+    # Ensure thread-safety when accessing the shared client instance
+    with _weaviate_client_lock:
+        client = _weaviate_client
+        _weaviate_client = None
+
+    if client is not None:
+        try:
+            client.close()
+        except Exception:
+            # Best-effort cleanup; log at debug level and ignore errors.
+            logger.debug("Failed to close Weaviate client during shutdown", exc_info=True)
+
+
+# Register the shutdown hook once per process.
+atexit.register(_shutdown_weaviate_client)
+
+
 class WeaviateConfig(BaseModel):
     """
     Configuration model for Weaviate connection settings.
@@ -85,18 +112,6 @@ class WeaviateVector(BaseVector):
         self._client = self._init_client(config)
         self._attributes = attributes
 
-    def __del__(self):
-        """
-        Destructor to properly close the Weaviate client connection.
-        Prevents connection leaks and resource warnings.
-        """
-        if hasattr(self, "_client") and self._client is not None:
-            try:
-                self._client.close()
-            except Exception as e:
-                # Ignore errors during cleanup as object is being destroyed
-                logger.warning("Error closing Weaviate client %s", e, exc_info=True)
-
     def _init_client(self, config: WeaviateConfig) -> weaviate.WeaviateClient:
         """
         Initializes and returns a connected Weaviate client.

api/dify_graph/nodes/http_request/node.py

@@ -101,7 +101,6 @@ class HttpRequestNode(Node[HttpRequestNodeData]):
                 timeout=self._get_request_timeout(self.node_data),
                 variable_pool=self.graph_runtime_state.variable_pool,
                 http_request_config=self._http_request_config,
-                max_retries=0,
                 ssl_verify=self.node_data.ssl_verify,
                 http_client=self._http_client,
                 file_manager=self._file_manager,

api/dify_graph/nodes/llm/llm_utils.py

@@ -256,9 +256,13 @@ def fetch_prompt_messages(
                 ):
                     continue
                 prompt_message_content.append(content_item)
-            if prompt_message_content:
+            if not prompt_message_content:
+                continue
+            if len(prompt_message_content) == 1 and prompt_message_content[0].type == PromptMessageContentType.TEXT:
+                prompt_message.content = prompt_message_content[0].data
+            else:
                 prompt_message.content = prompt_message_content
-                filtered_prompt_messages.append(prompt_message)
+            filtered_prompt_messages.append(prompt_message)
         elif not prompt_message.is_empty():
             filtered_prompt_messages.append(prompt_message)
 

api/models/enums.py

@@ -11,6 +11,13 @@ class CreatorUserRole(StrEnum):
     ACCOUNT = "account"
     END_USER = "end_user"
 
+    @classmethod
+    def _missing_(cls, value):
+        if value == "end-user":
+            return cls.END_USER
+        else:
+            return super()._missing_(value)
+
 
 class WorkflowRunTriggeredFrom(StrEnum):
     DEBUGGING = "debugging"

api/pyproject.toml

@@ -1,6 +1,6 @@
 [project]
 name = "dify-api"
-version = "1.13.1"
+version = "1.13.2"
 requires-python = ">=3.11,<3.13"
 
 dependencies = [

api/tests/unit_tests/core/workflow/nodes/llm/test_llm_utils.py

@@ -0,0 +1,106 @@
+from unittest import mock
+
+import pytest
+
+from core.model_manager import ModelInstance
+from dify_graph.model_runtime.entities import ImagePromptMessageContent, PromptMessageRole, TextPromptMessageContent
+from dify_graph.model_runtime.entities.message_entities import SystemPromptMessage
+from dify_graph.nodes.llm import llm_utils
+from dify_graph.nodes.llm.entities import LLMNodeChatModelMessage
+from dify_graph.nodes.llm.exc import NoPromptFoundError
+from dify_graph.runtime import VariablePool
+
+
+def _fetch_prompt_messages_with_mocked_content(content):
+    variable_pool = VariablePool.empty()
+    model_instance = mock.MagicMock(spec=ModelInstance)
+    prompt_template = [
+        LLMNodeChatModelMessage(
+            text="You are a classifier.",
+            role=PromptMessageRole.SYSTEM,
+            edition_type="basic",
+        )
+    ]
+
+    with (
+        mock.patch(
+            "dify_graph.nodes.llm.llm_utils.fetch_model_schema",
+            return_value=mock.MagicMock(features=[]),
+        ),
+        mock.patch(
+            "dify_graph.nodes.llm.llm_utils.handle_list_messages",
+            return_value=[SystemPromptMessage(content=content)],
+        ),
+        mock.patch(
+            "dify_graph.nodes.llm.llm_utils.handle_memory_chat_mode",
+            return_value=[],
+        ),
+    ):
+        return llm_utils.fetch_prompt_messages(
+            sys_query=None,
+            sys_files=[],
+            context=None,
+            memory=None,
+            model_instance=model_instance,
+            prompt_template=prompt_template,
+            stop=["END"],
+            memory_config=None,
+            vision_enabled=False,
+            vision_detail=ImagePromptMessageContent.DETAIL.HIGH,
+            variable_pool=variable_pool,
+            jinja2_variables=[],
+            template_renderer=None,
+        )
+
+
+def test_fetch_prompt_messages_skips_messages_when_all_contents_are_filtered_out():
+    with pytest.raises(NoPromptFoundError):
+        _fetch_prompt_messages_with_mocked_content(
+            [
+                ImagePromptMessageContent(
+                    format="url",
+                    url="https://example.com/image.png",
+                    mime_type="image/png",
+                ),
+            ]
+        )
+
+
+def test_fetch_prompt_messages_flattens_single_text_content_after_filtering_unsupported_multimodal_items():
+    prompt_messages, stop = _fetch_prompt_messages_with_mocked_content(
+        [
+            TextPromptMessageContent(data="You are a classifier."),
+            ImagePromptMessageContent(
+                format="url",
+                url="https://example.com/image.png",
+                mime_type="image/png",
+            ),
+        ]
+    )
+
+    assert stop == ["END"]
+    assert prompt_messages == [SystemPromptMessage(content="You are a classifier.")]
+
+
+def test_fetch_prompt_messages_keeps_list_content_when_multiple_supported_items_remain():
+    prompt_messages, stop = _fetch_prompt_messages_with_mocked_content(
+        [
+            TextPromptMessageContent(data="You are"),
+            TextPromptMessageContent(data=" a classifier."),
+            ImagePromptMessageContent(
+                format="url",
+                url="https://example.com/image.png",
+                mime_type="image/png",
+            ),
+        ]
+    )
+
+    assert stop == ["END"]
+    assert prompt_messages == [
+        SystemPromptMessage(
+            content=[
+                TextPromptMessageContent(data="You are"),
+                TextPromptMessageContent(data=" a classifier."),
+            ]
+        )
+    ]

api/tests/unit_tests/models/test_enums_creator_user_role.py

@@ -0,0 +1,19 @@
+import pytest
+
+from models.enums import CreatorUserRole
+
+
+def test_creator_user_role_missing_maps_hyphen_to_enum():
+    # given an alias with hyphen
+    value = "end-user"
+
+    # when converting to enum (invokes StrEnum._missing_ override)
+    role = CreatorUserRole(value)
+
+    # then it should map to END_USER
+    assert role is CreatorUserRole.END_USER
+
+
+def test_creator_user_role_missing_raises_for_unknown():
+    with pytest.raises(ValueError):
+        CreatorUserRole("unknown")

api/uv.lock

@@ -1533,7 +1533,7 @@ wheels = [
 
 [[package]]
 name = "dify-api"
-version = "1.13.1"
+version = "1.13.2"
 source = { virtual = "." }
 dependencies = [
     { name = "aliyun-log-python-sdk" },

docker/docker-compose-template.yaml

@@ -21,7 +21,7 @@ services:
 
   # API service
   api:
-    image: langgenius/dify-api:1.13.1
+    image: langgenius/dify-api:1.13.2
     restart: always
     environment:
       # Use the shared environment variables.
@@ -63,7 +63,7 @@ services:
   # worker service
   # The Celery worker for processing all queues (dataset, workflow, mail, etc.)
   worker:
-    image: langgenius/dify-api:1.13.1
+    image: langgenius/dify-api:1.13.2
     restart: always
     environment:
       # Use the shared environment variables.
@@ -102,7 +102,7 @@ services:
   # worker_beat service
   # Celery beat for scheduling periodic tasks.
   worker_beat:
-    image: langgenius/dify-api:1.13.1
+    image: langgenius/dify-api:1.13.2
     restart: always
     environment:
       # Use the shared environment variables.
@@ -132,7 +132,7 @@ services:
 
   # Frontend web application.
   web:
-    image: langgenius/dify-web:1.13.1
+    image: langgenius/dify-web:1.13.2
     restart: always
     environment:
       CONSOLE_API_URL: ${CONSOLE_API_URL:-}

docker/docker-compose.yaml

@@ -728,7 +728,7 @@ services:
 
   # API service
   api:
-    image: langgenius/dify-api:1.13.1
+    image: langgenius/dify-api:1.13.2
     restart: always
     environment:
       # Use the shared environment variables.
@@ -770,7 +770,7 @@ services:
   # worker service
   # The Celery worker for processing all queues (dataset, workflow, mail, etc.)
   worker:
-    image: langgenius/dify-api:1.13.1
+    image: langgenius/dify-api:1.13.2
     restart: always
     environment:
       # Use the shared environment variables.
@@ -809,7 +809,7 @@ services:
   # worker_beat service
   # Celery beat for scheduling periodic tasks.
   worker_beat:
-    image: langgenius/dify-api:1.13.1
+    image: langgenius/dify-api:1.13.2
     restart: always
     environment:
       # Use the shared environment variables.
@@ -839,7 +839,7 @@ services:
 
   # Frontend web application.
   web:
-    image: langgenius/dify-web:1.13.1
+    image: langgenius/dify-web:1.13.2
     restart: always
     environment:
       CONSOLE_API_URL: ${CONSOLE_API_URL:-}

web/package.json

@@ -1,7 +1,7 @@
 {
   "name": "dify-web",
   "type": "module",
-  "version": "1.13.1",
+  "version": "1.13.2",
   "private": true,
   "packageManager": "pnpm@10.32.1",
   "imports": {