feat: Intent classify

apps/application/flow/step_node/__init__.py

@@ -24,13 +24,14 @@
 from .tool_lib_node import *
 from .tool_node import *
 from .variable_assign_node import BaseVariableAssignNode
+from .intent_node import *
 
 node_list = [BaseStartStepNode, BaseChatNode, BaseSearchKnowledgeNode, BaseQuestionNode,
              BaseConditionNode, BaseReplyNode,
              BaseToolNodeNode, BaseToolLibNodeNode, BaseRerankerNode, BaseApplicationNode,
              BaseDocumentExtractNode,
              BaseImageUnderstandNode, BaseFormNode, BaseSpeechToTextNode, BaseTextToSpeechNode,
-             BaseImageGenerateNode, BaseVariableAssignNode, BaseMcpNode]
+             BaseImageGenerateNode, BaseVariableAssignNode, BaseMcpNode,BaseIntentNode]
 
 
 def get_node(node_type):

apps/application/flow/step_node/intent_node/__init__.py

@@ -0,0 +1,6 @@
+# coding=utf-8
+
+
+
+
+from .impl import *

apps/application/flow/step_node/intent_node/i_intent_node.py

@@ -0,0 +1,46 @@
+# coding=utf-8
+
+from typing import Type
+
+from django.utils.translation import gettext_lazy as _
+from rest_framework import serializers
+
+from application.flow.i_step_node import INode, NodeResult
+
+
+class IntentBranchSerializer(serializers.Serializer):
+
+    id = serializers.CharField(required=True, label=_("Branch id"))
+    content = serializers.CharField(required=True, label=_("content"))
+    isOther = serializers.BooleanField(required=True, label=_("Branch Type"))
+
+
+class IntentNodeSerializer(serializers.Serializer):
+    model_id = serializers.CharField(required=True, label=_("Model id"))
+    content_list = serializers.ListField(required=True, label=_("Text content"))
+    dialogue_number = serializers.IntegerField(required=True, label=
+    _("Number of multi-round conversations"))
+    model_params_setting = serializers.DictField(required=False,
+                                                 label=_("Model parameter settings"))
+    branch = IntentBranchSerializer(many=True)
+
+class IIntentNode(INode):
+    type = 'intent-node'
+    def save_context(self, details, workflow_manage):
+        pass
+
+    def get_node_params_serializer_class(self) -> Type[serializers.Serializer]:
+        return IntentNodeSerializer
+
+    def _run(self):
+        question = self.workflow_manage.get_reference_field(
+            self.node_params_serializer.data.get('content_list')[0],
+            self.node_params_serializer.data.get('content_list')[1:],
+        )
+
+        return self.execute(**self.node_params_serializer.data, **self.flow_params_serializer.data, user_input=str(question))
+
+
+    def execute(self, model_id, dialogue_number, history_chat_record, user_input, branch,
+                model_params_setting=None, **kwargs) -> NodeResult:
+        pass

apps/application/flow/step_node/intent_node/impl/__init__.py

@@ -0,0 +1,3 @@
+
+
+from .base_intent_node import BaseIntentNode

apps/application/flow/step_node/intent_node/impl/base_intent_node.py

@@ -0,0 +1,242 @@
+# coding=utf-8
+import json
+import re
+import time
+from typing import List, Dict, Any
+from functools import reduce
+
+from django.db.models import QuerySet
+from langchain.schema import HumanMessage, SystemMessage
+
+from application.flow.i_step_node import INode, NodeResult
+from application.flow.step_node.intent_node.i_intent_node import IIntentNode
+from models_provider.models import Model
+from models_provider.tools import get_model_instance_by_model_workspace_id, get_model_credential
+from .prompt_template import PROMPT_TEMPLATE
+
+def get_default_model_params_setting(model_id):
+
+    model = QuerySet(Model).filter(id=model_id).first()
+    credential = get_model_credential(model.provider, model.model_type, model.model_name)
+    model_params_setting = credential.get_model_params_setting_form(
+        model.model_name).get_default_form_data()
+    return model_params_setting
+
+
+def _write_context(node_variable: Dict, workflow_variable: Dict, node: INode, workflow, answer: str):
+
+    chat_model = node_variable.get('chat_model')
+    message_tokens = chat_model.get_num_tokens_from_messages(node_variable.get('message_list'))
+    answer_tokens = chat_model.get_num_tokens(answer)
+
+    node.context['message_tokens'] = message_tokens
+    node.context['answer_tokens'] = answer_tokens
+    node.context['answer'] = answer
+    node.context['history_message'] = node_variable['history_message']
+    node.context['user_input'] = node_variable['user_input']
+    node.context['branch_id'] = node_variable.get('branch_id')
+    node.context['reason'] = node_variable.get('reason')
+    node.context['category'] = node_variable.get('category')
+    node.context['run_time'] = time.time() - node.context['start_time']
+
+
+def write_context(node_variable: Dict, workflow_variable: Dict, node: INode, workflow):
+
+    response = node_variable.get('result')
+    answer = response.content
+    _write_context(node_variable, workflow_variable, node, workflow, answer)
+
+
+class BaseIntentNode(IIntentNode):
+
+
+    def save_context(self, details, workflow_manage):
+
+        self.context['branch_id'] = details.get('branch_id')
+        self.context['category'] = details.get('category')
+
+
+    def execute(self, model_id, dialogue_number, history_chat_record, user_input, branch,
+                model_params_setting=None, **kwargs) -> NodeResult:
+
+        # 设置默认模型参数
+        if model_params_setting is None:
+            model_params_setting = get_default_model_params_setting(model_id)
+
+        # 获取模型实例
+        workspace_id = self.workflow_manage.get_body().get('workspace_id')
+        chat_model = get_model_instance_by_model_workspace_id(
+            model_id, workspace_id, **model_params_setting
+        )
+
+        # 获取历史对话
+        history_message = self.get_history_message(history_chat_record, dialogue_number)
+        self.context['history_message'] = history_message
+
+        # 保存问题到上下文
+        self.context['user_input'] = user_input
+
+        # 构建分类提示词
+        prompt = self.build_classification_prompt(user_input, branch)
+
+
+        # 生成消息列表
+        system = self.build_system_prompt()
+        message_list = self.generate_message_list(system, prompt, history_message)
+        self.context['message_list'] = message_list
+
+        # 调用模型进行分类
+        try:
+            r = chat_model.invoke(message_list)
+            classification_result = r.content.strip()
+
+            # 解析分类结果获取分支信息
+            matched_branch = self.parse_classification_result(classification_result, branch)
+
+            #  返回结果
+            return NodeResult({
+                'result': r,
+                'chat_model': chat_model,
+                'message_list': message_list,
+                'history_message': history_message,
+                'user_input': user_input,
+                'branch_id': matched_branch['id'],
+                'reason': json.loads(r.content).get('reason'),
+                'category': matched_branch.get('content', matched_branch['id'])
+            }, {}, _write_context=write_context)
+
+        except Exception as e:
+            # 错误处理：返回"其他"分支
+            other_branch = self.find_other_branch(branch)
+            if other_branch:
+                return NodeResult({
+                    'branch_id': other_branch['id'],
+                    'category': other_branch.get('content', other_branch['id']),
+                    'error': str(e)
+                }, {})
+            else:
+                raise Exception(f"error: {str(e)}")
+
+    @staticmethod
+    def get_history_message(history_chat_record, dialogue_number):
+        """获取历史消息"""
+        start_index = len(history_chat_record) - dialogue_number
+        history_message = reduce(lambda x, y: [*x, *y], [
+            [history_chat_record[index].get_human_message(), history_chat_record[index].get_ai_message()]
+            for index in
+            range(start_index if start_index > 0 else 0, len(history_chat_record))], [])
+
+        for message in history_message:
+            if isinstance(message.content, str):
+                message.content = re.sub('<form_rander>[\d\D]*?<\/form_rander>', '', message.content)
+        return history_message
+
+
+    def build_system_prompt(self) -> str:
+        """构建系统提示词"""
+        return "你是一个专业的意图识别助手，请根据用户输入和意图选项，准确识别用户的真实意图。"
+
+    def build_classification_prompt(self, user_input: str, branch: List[Dict]) -> str:
+        """构建分类提示词"""
+
+        classification_list = []
+
+        other_branch = self.find_other_branch(branch)
+        # 添加其他分支
+        if other_branch:
+            classification_list.append({
+                "classificationId": 0,
+                "content": other_branch.get('content')
+            })
+        # 添加正常分支
+        classification_id = 1
+        for b in branch:
+            if not b.get('isOther'):
+                classification_list.append({
+                    "classificationId": classification_id,
+                    "content": b['content']
+                })
+                classification_id += 1
+
+        return PROMPT_TEMPLATE.format(
+            classification_list=classification_list,
+            user_input=user_input
+        )
+
+
+    def generate_message_list(self, system: str, prompt: str, history_message):
+        """生成消息列表"""
+        if system is None or len(system) == 0:
+            return [*history_message, HumanMessage(self.workflow_manage.generate_prompt(prompt))]
+        else:
+            return [SystemMessage(self.workflow_manage.generate_prompt(system)), *history_message,
+                    HumanMessage(self.workflow_manage.generate_prompt(prompt))]
+
+    def parse_classification_result(self, result: str, branch: List[Dict]) -> Dict[str, Any]:
+        """解析分类结果"""
+
+        other_branch = self.find_other_branch(branch)
+        normal_intents = [
+            b
+            for b in branch
+            if not b.get('isOther')
+        ]
+
+        def get_branch_by_id(category_id: int):
+            if category_id == 0:
+                return other_branch
+            elif 1 <= category_id <= len(normal_intents):
+                return normal_intents[category_id - 1]
+            return None
+
+        try:
+            result_json = json.loads(result)
+            classification_id = result_json.get('classificationId', 0) # 0 兜底
+            # 如果是 0 ，返回其他分支
+            matched_branch = get_branch_by_id(classification_id)
+            if matched_branch:
+                return matched_branch
+
+        except Exception as e:
+            # json 解析失败，re 提取
+            numbers = re.findall(r'"classificationId":\s*(\d+)', result)
+            if numbers:
+                classification_id = int(numbers[0])
+
+                matched_branch = get_branch_by_id(classification_id)
+                if matched_branch:
+                    return matched_branch
+
+        # 如果都解析失败，返回“other”
+        return other_branch or (normal_intents[0] if normal_intents else {'id': 'unknown', 'content': 'unknown'})
+
+
+    def find_other_branch(self, branch: List[Dict]) -> Dict[str, Any] | None:
+        """查找其他分支"""
+        for b in branch:
+            if b.get('isOther'):
+                return b
+        return None
+
+
+    def get_details(self, index: int, **kwargs):
+        """获取节点执行详情"""
+        return {
+            'name': self.node.properties.get('stepName'),
+            'index': index,
+            'run_time': self.context.get('run_time'),
+            'system': self.context.get('system'),
+            'history_message': [
+                {'content': message.content, 'role': message.type}
+                for message in (self.context.get('history_message') or [])
+            ],
+            'user_input': self.context.get('user_input'),
+            'answer': self.context.get('answer'),
+            'branch_id': self.context.get('branch_id'),
+            'category': self.context.get('category'),
+            'type': self.node.type,
+            'message_tokens': self.context.get('message_tokens'),
+            'answer_tokens': self.context.get('answer_tokens'),
+            'status': self.status,
+            'err_message': self.err_message
+        }

apps/application/flow/step_node/intent_node/impl/prompt_template.py

@@ -0,0 +1,30 @@
+
+
+
+
+PROMPT_TEMPLATE = """# Role
+        You are an intention classification expert, good at being able to judge which classification the user's input belongs to.
+
+        ## Skills
+        Skill 1: Clearly determine which of the following intention classifications the user's input belongs to.
+        Intention classification list:
+        {classification_list}
+
+        Note:
+        - Please determine the match only between the user's input content and the Intention classification list content, without judging or categorizing the match with the classification ID.
+
+        ## User Input
+        {user_input}
+
+        ## Reply requirements
+        - The answer must be returned in JSON format.
+        - Strictly ensure that the output is in a valid JSON format.
+        - Do not add prefix ```json or suffix ```
+        - The answer needs to include the following fields such as:
+        {{
+        "classificationId": 0,
+        "reason": ""
+        }}
+
+        ## Limit
+        - Please do not reply in text."""

ui/src/enums/application.ts

@@ -24,4 +24,5 @@ export enum WorkflowType {
   SpeechToTextNode = 'speech-to-text-node',
   ImageGenerateNode = 'image-generate-node',
   McpNode = 'mcp-node',
+  IntentNode = 'intent-node',
 }

ui/src/locales/lang/en-US/common.ts

@@ -47,6 +47,8 @@ export default {
   noData: 'No data',
   result: 'Result',
   remove: 'Remove',
+  classify: 'Classify',
+  reason: 'Reason',
   removeSuccess: 'Successful',
   searchBar: {
     placeholder: 'Search by name',