refactor(api): continue decoupling dify_graph from API concerns (#33580)

Signed-off-by: -LAN- <laipz8200@outlook.com>
Co-authored-by: autofix-ci[bot] <114827586+autofix-ci[bot]@users.noreply.github.com>
Co-authored-by: WH-2099 <wh2099@pm.me>

api/dify_graph/nodes/question_classifier/question_classifier_node.py

@@ -3,9 +3,6 @@ import re
 from collections.abc import Mapping, Sequence
 from typing import TYPE_CHECKING, Any
 
-from core.model_manager import ModelInstance
-from core.prompt.simple_prompt_transform import ModelMode
-from core.prompt.utils.prompt_message_util import PromptMessageUtil
 from dify_graph.entities import GraphInitParams
 from dify_graph.entities.graph_config import NodeConfigDict
 from dify_graph.enums import (
@@ -14,7 +11,7 @@ from dify_graph.enums import (
     WorkflowNodeExecutionMetadataKey,
     WorkflowNodeExecutionStatus,
 )
-from dify_graph.model_runtime.entities import LLMUsage, ModelPropertyKey, PromptMessageRole
+from dify_graph.model_runtime.entities import LLMMode, LLMUsage, ModelPropertyKey, PromptMessageRole
 from dify_graph.model_runtime.memory import PromptMessageMemory
 from dify_graph.model_runtime.utils.encoders import jsonable_encoder
 from dify_graph.node_events import ModelInvokeCompletedEvent, NodeRunResult
@@ -27,10 +24,11 @@ from dify_graph.nodes.llm import (
     LLMNodeCompletionModelPromptTemplate,
     llm_utils,
 )
-from dify_graph.nodes.llm.file_saver import FileSaverImpl, LLMFileSaver
-from dify_graph.nodes.llm.protocols import CredentialsProvider, ModelFactory, TemplateRenderer
+from dify_graph.nodes.llm.file_saver import LLMFileSaver
+from dify_graph.nodes.llm.runtime_protocols import PreparedLLMProtocol, PromptMessageSerializerProtocol
 from dify_graph.nodes.protocols import HttpClientProtocol
-from libs.json_in_md_parser import parse_and_check_json_markdown
+from dify_graph.template_rendering import Jinja2TemplateRenderer
+from dify_graph.utils.json_in_md_parser import parse_and_check_json_markdown
 
 from .entities import QuestionClassifierNodeData
 from .exc import InvalidModelTypeError
@@ -49,17 +47,22 @@ if TYPE_CHECKING:
     from dify_graph.runtime import GraphRuntimeState
 
 
+class _PassthroughPromptMessageSerializer:
+    def serialize(self, *, model_mode: Any, prompt_messages: Sequence[Any]) -> Any:
+        _ = model_mode
+        return list(prompt_messages)
+
+
 class QuestionClassifierNode(Node[QuestionClassifierNodeData]):
     node_type = BuiltinNodeTypes.QUESTION_CLASSIFIER
     execution_type = NodeExecutionType.BRANCH
 
     _file_outputs: list["File"]
     _llm_file_saver: LLMFileSaver
-    _credentials_provider: "CredentialsProvider"
-    _model_factory: "ModelFactory"
-    _model_instance: ModelInstance
+    _prompt_message_serializer: PromptMessageSerializerProtocol
+    _model_instance: PreparedLLMProtocol
     _memory: PromptMessageMemory | None
-    _template_renderer: TemplateRenderer
+    _template_renderer: Jinja2TemplateRenderer
 
     def __init__(
         self,
@@ -68,13 +71,14 @@ class QuestionClassifierNode(Node[QuestionClassifierNodeData]):
         graph_init_params: "GraphInitParams",
         graph_runtime_state: "GraphRuntimeState",
         *,
-        credentials_provider: "CredentialsProvider",
-        model_factory: "ModelFactory",
-        model_instance: ModelInstance,
+        credentials_provider: object | None = None,
+        model_factory: object | None = None,
+        model_instance: PreparedLLMProtocol,
         http_client: HttpClientProtocol,
-        template_renderer: TemplateRenderer,
+        template_renderer: Jinja2TemplateRenderer,
         memory: PromptMessageMemory | None = None,
-        llm_file_saver: LLMFileSaver | None = None,
+        llm_file_saver: LLMFileSaver,
+        prompt_message_serializer: PromptMessageSerializerProtocol | None = None,
     ):
         super().__init__(
             id=id,
@@ -85,20 +89,13 @@ class QuestionClassifierNode(Node[QuestionClassifierNodeData]):
         # LLM file outputs, used for MultiModal outputs.
         self._file_outputs = []
 
-        self._credentials_provider = credentials_provider
-        self._model_factory = model_factory
+        _ = credentials_provider, model_factory, http_client
         self._model_instance = model_instance
         self._memory = memory
         self._template_renderer = template_renderer
 
-        if llm_file_saver is None:
-            dify_ctx = self.require_dify_context()
-            llm_file_saver = FileSaverImpl(
-                user_id=dify_ctx.user_id,
-                tenant_id=dify_ctx.tenant_id,
-                http_client=http_client,
-            )
         self._llm_file_saver = llm_file_saver
+        self._prompt_message_serializer = prompt_message_serializer or _PassthroughPromptMessageSerializer()
 
     @classmethod
     def version(cls):
@@ -173,7 +170,6 @@ class QuestionClassifierNode(Node[QuestionClassifierNodeData]):
                 model_instance=model_instance,
                 prompt_messages=prompt_messages,
                 stop=stop,
-                user_id=self.require_dify_context().user_id,
                 structured_output_enabled=False,
                 structured_output=None,
                 file_saver=self._llm_file_saver,
@@ -209,7 +205,7 @@ class QuestionClassifierNode(Node[QuestionClassifierNodeData]):
                     category_id = category_id_result
             process_data = {
                 "model_mode": node_data.model.mode,
-                "prompts": PromptMessageUtil.prompt_messages_to_prompt_for_saving(
+                "prompts": self._prompt_message_serializer.serialize(
                     model_mode=node_data.model.mode, prompt_messages=prompt_messages
                 ),
                 "usage": jsonable_encoder(usage),
@@ -251,7 +247,7 @@ class QuestionClassifierNode(Node[QuestionClassifierNodeData]):
             )
 
     @property
-    def model_instance(self) -> ModelInstance:
+    def model_instance(self) -> PreparedLLMProtocol:
         return self._model_instance
 
     @classmethod
@@ -289,7 +285,7 @@ class QuestionClassifierNode(Node[QuestionClassifierNodeData]):
         self,
         node_data: QuestionClassifierNodeData,
         query: str,
-        model_instance: ModelInstance,
+        model_instance: PreparedLLMProtocol,
         context: str | None,
     ) -> int:
         model_schema = llm_utils.fetch_model_schema(model_instance=model_instance)
@@ -299,7 +295,7 @@ class QuestionClassifierNode(Node[QuestionClassifierNodeData]):
             prompt_template=prompt_template,
             sys_query="",
             sys_files=[],
-            context=context,
+            context=context or "",
             memory=None,
             model_instance=model_instance,
             stop=model_instance.stop,
@@ -338,7 +334,7 @@ class QuestionClassifierNode(Node[QuestionClassifierNodeData]):
         memory: PromptMessageMemory | None,
         max_token_limit: int = 2000,
     ):
-        model_mode = ModelMode(node_data.model.mode)
+        model_mode = LLMMode(node_data.model.mode)
         classes = node_data.classes
         categories = []
         for class_ in classes:
@@ -354,7 +350,7 @@ class QuestionClassifierNode(Node[QuestionClassifierNodeData]):
                 message_limit=node_data.memory.window.size if node_data.memory and node_data.memory.window else None,
             )
         prompt_messages: list[LLMNodeChatModelMessage] = []
-        if model_mode == ModelMode.CHAT:
+        if model_mode == LLMMode.CHAT:
             system_prompt_messages = LLMNodeChatModelMessage(
                 role=PromptMessageRole.SYSTEM, text=QUESTION_CLASSIFIER_SYSTEM_PROMPT.format(histories=memory_str)
             )
@@ -385,7 +381,7 @@ class QuestionClassifierNode(Node[QuestionClassifierNodeData]):
             )
             prompt_messages.append(user_prompt_message_3)
             return prompt_messages
-        elif model_mode == ModelMode.COMPLETION:
+        elif model_mode == LLMMode.COMPLETION:
             return LLMNodeCompletionModelPromptTemplate(
                 text=QUESTION_CLASSIFIER_COMPLETION_PROMPT.format(
                     histories=memory_str,