chore: bump version to 1.13.2 (#33681)

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

api/controllers/console/app/mcp_server.py

@@ -103,13 +103,13 @@ class AppMCPServerController(Resource):
             raise NotFound()
 
         description = payload.description
-        if description is None:
-            pass
-        elif not description:
+        if description is None or not description:
             server.description = app_model.description or ""
         else:
             server.description = description
 
+        server.name = app_model.name
+
         server.parameters = json.dumps(payload.parameters, ensure_ascii=False)
         if payload.status:
             try:

api/core/rag/datasource/retrieval_service.py

@@ -68,9 +68,12 @@ class SegmentRecord(TypedDict):
 
 
 class DefaultRetrievalModelDict(TypedDict):
-    search_method: RetrievalMethod | str
+    search_method: RetrievalMethod
     reranking_enable: bool
     reranking_model: RerankingModelDict
+    reranking_mode: NotRequired[str]
+    weights: NotRequired[WeightsDict | None]
+    score_threshold: NotRequired[float]
     top_k: int
     score_threshold_enabled: bool
 

api/core/rag/retrieval/dataset_retrieval.py

@@ -33,7 +33,7 @@ from core.prompt.entities.advanced_prompt_entities import ChatModelMessage, Comp
 from core.prompt.simple_prompt_transform import ModelMode
 from core.rag.data_post_processor.data_post_processor import DataPostProcessor, RerankingModelDict, WeightsDict
 from core.rag.datasource.keyword.jieba.jieba_keyword_table_handler import JiebaKeywordTableHandler
-from core.rag.datasource.retrieval_service import RetrievalService
+from core.rag.datasource.retrieval_service import DefaultRetrievalModelDict, RetrievalService
 from core.rag.entities.citation_metadata import RetrievalSourceMetadata
 from core.rag.entities.context_entities import DocumentContext
 from core.rag.entities.metadata_entities import Condition, MetadataCondition
@@ -87,7 +87,7 @@ from models.enums import CreatorUserRole, DatasetQuerySource
 from services.external_knowledge_service import ExternalDatasetService
 from services.feature_service import FeatureService
 
-default_retrieval_model: dict[str, Any] = {
+default_retrieval_model: DefaultRetrievalModelDict = {
     "search_method": RetrievalMethod.SEMANTIC_SEARCH,
     "reranking_enable": False,
     "reranking_model": {"reranking_provider_name": "", "reranking_model_name": ""},
@@ -666,7 +666,11 @@ class DatasetRetrieval:
                             document_ids_filter = document_ids
                         else:
                             return []
-                    retrieval_model_config = dataset.retrieval_model or default_retrieval_model
+                    retrieval_model_config: DefaultRetrievalModelDict = (
+                        cast(DefaultRetrievalModelDict, dataset.retrieval_model)
+                        if dataset.retrieval_model
+                        else default_retrieval_model
+                    )
 
                     # get top k
                     top_k = retrieval_model_config["top_k"]
@@ -1058,7 +1062,11 @@ class DatasetRetrieval:
                     all_documents.append(document)
             else:
                 # get retrieval model , if the model is not setting , using default
-                retrieval_model = dataset.retrieval_model or default_retrieval_model
+                retrieval_model: DefaultRetrievalModelDict = (
+                    cast(DefaultRetrievalModelDict, dataset.retrieval_model)
+                    if dataset.retrieval_model
+                    else default_retrieval_model
+                )
 
                 if dataset.indexing_technique == "economy":
                     # use keyword table query
@@ -1132,7 +1140,7 @@ class DatasetRetrieval:
 
         if retrieve_config.retrieve_strategy == DatasetRetrieveConfigEntity.RetrieveStrategy.SINGLE:
             # get retrieval model config
-            default_retrieval_model = {
+            default_retrieval_model: DefaultRetrievalModelDict = {
                 "search_method": RetrievalMethod.SEMANTIC_SEARCH,
                 "reranking_enable": False,
                 "reranking_model": {"reranking_provider_name": "", "reranking_model_name": ""},
@@ -1141,7 +1149,11 @@ class DatasetRetrieval:
             }
 
             for dataset in available_datasets:
-                retrieval_model_config = dataset.retrieval_model or default_retrieval_model
+                retrieval_model_config: DefaultRetrievalModelDict = (
+                    cast(DefaultRetrievalModelDict, dataset.retrieval_model)
+                    if dataset.retrieval_model
+                    else default_retrieval_model
+                )
 
                 # get top k
                 top_k = retrieval_model_config["top_k"]

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/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/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": {