Merge branch 'fix/chore-fix' into dev/plugin-deploy

api/core/agent/base_agent_runner.py

@@ -106,16 +106,9 @@ class BaseAgentRunner(AppRunner):
         # check if model supports stream tool call
         llm_model = cast(LargeLanguageModel, model_instance.model_type_instance)
         model_schema = llm_model.get_model_schema(model_instance.model, model_instance.credentials)
-        if model_schema and ModelFeature.STREAM_TOOL_CALL in (model_schema.features or []):
-            self.stream_tool_call = True
-        else:
-            self.stream_tool_call = False
-
-        # check if model supports vision
-        if model_schema and ModelFeature.VISION in (model_schema.features or []):
-            self.files = application_generate_entity.files
-        else:
-            self.files = []
+        features = model_schema.features if model_schema and model_schema.features else []
+        self.stream_tool_call = ModelFeature.STREAM_TOOL_CALL in features
+        self.files = application_generate_entity.files if ModelFeature.VISION in features else []
         self.query = None
         self._current_thoughts: list[PromptMessage] = []
 
@@ -243,7 +236,7 @@ class BaseAgentRunner(AppRunner):
         update prompt message tool
         """
         # try to get tool runtime parameters
-        tool_runtime_parameters = tool.get_runtime_parameters() or []
+        tool_runtime_parameters = tool.get_runtime_parameters()
 
         for parameter in tool_runtime_parameters:
             if parameter.form != ToolParameter.ToolParameterForm.LLM:

api/core/app/task_pipeline/workflow_cycle_manage.py

@@ -381,7 +381,7 @@ class WorkflowCycleManage:
                 id=workflow_run.id,
                 workflow_id=workflow_run.workflow_id,
                 sequence_number=workflow_run.sequence_number,
-                inputs=workflow_run.inputs_dict or {},
+                inputs=workflow_run.inputs_dict,
                 created_at=int(workflow_run.created_at.timestamp()),
             ),
         )
@@ -428,7 +428,7 @@ class WorkflowCycleManage:
                 created_by=created_by,
                 created_at=int(workflow_run.created_at.timestamp()),
                 finished_at=int(workflow_run.finished_at.timestamp()),
-                files=self._fetch_files_from_node_outputs(workflow_run.outputs_dict or {}),
+                files=self._fetch_files_from_node_outputs(workflow_run.outputs_dict),
             ),
         )
 

api/core/indexing_runner.py

@@ -29,6 +29,7 @@ from core.rag.splitter.fixed_text_splitter import (
     FixedRecursiveCharacterTextSplitter,
 )
 from core.rag.splitter.text_splitter import TextSplitter
+from core.tools.utils.rag_web_reader import get_image_upload_file_ids
 from core.tools.utils.text_processing_utils import remove_leading_symbols
 from extensions.ext_database import db
 from extensions.ext_redis import redis_client
@@ -279,6 +280,19 @@ class IndexingRunner:
                 if len(preview_texts) < 5:
                     preview_texts.append(document.page_content)
 
+                # delete image files and related db records
+                image_upload_file_ids = get_image_upload_file_ids(document.page_content)
+                for upload_file_id in image_upload_file_ids:
+                    image_file = db.session.query(UploadFile).filter(UploadFile.id == upload_file_id).first()
+                    try:
+                        storage.delete(image_file.key)
+                    except Exception:
+                        logging.exception(
+                            "Delete image_files failed while indexing_estimate, \
+                                          image_upload_file_is: {}".format(upload_file_id)
+                        )
+                    db.session.delete(image_file)
+
         if doc_form and doc_form == "qa_model":
             if len(preview_texts) > 0:
                 # qa model document

api/core/tools/tool_engine.py

@@ -58,7 +58,7 @@ class ToolEngine:
             # check if this tool has only one parameter
             parameters = [
                 parameter
-                for parameter in tool.get_runtime_parameters() or []
+                for parameter in tool.get_runtime_parameters()
                 if parameter.form == ToolParameter.ToolParameterForm.LLM
             ]
             if parameters and len(parameters) == 1:

api/core/tools/utils/configuration.py

@@ -145,7 +145,7 @@ class ToolParameterConfigurationManager:
         # get tool parameters
         tool_parameters = self.tool_runtime.entity.parameters or []
         # get tool runtime parameters
-        runtime_parameters = self.tool_runtime.get_runtime_parameters() or []
+        runtime_parameters = self.tool_runtime.get_runtime_parameters()
         # override parameters
         current_parameters = tool_parameters.copy()
         for runtime_parameter in runtime_parameters: