Merge branch 'refs/heads/main' into feat/workflow-parallel-support

# Conflicts:
#	api/core/workflow/workflow_entry.py

.github/workflows/api-tests.yml

@@ -89,6 +89,5 @@ jobs:
             pgvecto-rs
             pgvector
             chroma
-            myscale
       - name: Test Vector Stores
         run: poetry run -C api bash dev/pytest/pytest_vdb.sh

api/README.md

@@ -12,7 +12,8 @@
    ```bash
    cd ../docker
    cp middleware.env.example middleware.env
-   docker compose -f docker-compose.middleware.yaml -p dify up -d
+   # change the profile to other vector database if you are not using weaviate
+   docker compose -f docker-compose.middleware.yaml --profile weaviate -p dify up -d
    cd ../api
    ```
 

api/configs/packaging/__init__.py

@@ -9,7 +9,7 @@ class PackagingInfo(BaseSettings):
 
     CURRENT_VERSION: str = Field(
         description='Dify version',
-        default='0.6.14',
+        default='0.6.15',
     )
 
     COMMIT_SHA: str = Field(

api/controllers/console/app/conversation.py

@@ -22,7 +22,7 @@ from fields.conversation_fields import (
 )
 from libs.helper import datetime_string
 from libs.login import login_required
-from models.model import AppMode, Conversation, Message, MessageAnnotation
+from models.model import AppMode, Conversation, EndUser, Message, MessageAnnotation
 
 
 class CompletionConversationApi(Resource):
@@ -156,19 +156,31 @@ class ChatConversationApi(Resource):
         parser.add_argument('limit', type=int_range(1, 100), required=False, default=20, location='args')
         args = parser.parse_args()
 
+        subquery = (
+            db.session.query(
+                Conversation.id.label('conversation_id'),
+                EndUser.session_id.label('from_end_user_session_id')
+            )
+            .outerjoin(EndUser, Conversation.from_end_user_id == EndUser.id)
+            .subquery()
+        )
+
         query = db.select(Conversation).where(Conversation.app_id == app_model.id)
 
         if args['keyword']:
+            keyword_filter = '%{}%'.format(args['keyword'])
             query = query.join(
-                Message, Message.conversation_id == Conversation.id
+                Message, Message.conversation_id == Conversation.id,
+            ).join(
+                subquery, subquery.c.conversation_id == Conversation.id
             ).filter(
                 or_(
-                    Message.query.ilike('%{}%'.format(args['keyword'])),
-                    Message.answer.ilike('%{}%'.format(args['keyword'])),
-                    Conversation.name.ilike('%{}%'.format(args['keyword'])),
-                    Conversation.introduction.ilike('%{}%'.format(args['keyword'])),
+                    Message.query.ilike(keyword_filter),
+                    Message.answer.ilike(keyword_filter),
+                    Conversation.name.ilike(keyword_filter),
+                    Conversation.introduction.ilike(keyword_filter),
+                    subquery.c.from_end_user_session_id.ilike(keyword_filter)
                 ),
-
             )
 
         account = current_user

api/controllers/console/app/generator.py

@@ -22,17 +22,19 @@ class RuleGenerateApi(Resource):
     @account_initialization_required
     def post(self):
         parser = reqparse.RequestParser()
-        parser.add_argument('audiences', type=str, required=True, nullable=False, location='json')
-        parser.add_argument('hoping_to_solve', type=str, required=True, nullable=False, location='json')
+        parser.add_argument('instruction', type=str, required=True, nullable=False, location='json')
+        parser.add_argument('model_config', type=dict, required=True, nullable=False, location='json')
+        parser.add_argument('no_variable', type=bool, required=True, default=False, location='json')
         args = parser.parse_args()
 
         account = current_user
 
         try:
             rules = LLMGenerator.generate_rule_config(
-                account.current_tenant_id,
-                args['audiences'],
-                args['hoping_to_solve']
+                tenant_id=account.current_tenant_id,
+                instruction=args['instruction'],
+                model_config=args['model_config'],
+                no_variable=args['no_variable']
             )
         except ProviderTokenNotInitError as ex:
             raise ProviderNotInitializeError(ex.description)

api/core/app/app_config/easy_ui_based_app/dataset/manager.py

@@ -62,7 +62,12 @@ class DatasetConfigManager:
             return None
 
         # dataset configs
-        dataset_configs = config.get('dataset_configs', {'retrieval_model': 'single'})
+        if 'dataset_configs' in config and config.get('dataset_configs'):
+            dataset_configs = config.get('dataset_configs')
+        else:
+            dataset_configs = {
+                'retrieval_model': 'multiple'
+            }
         query_variable = config.get('dataset_query_variable')
 
         if dataset_configs['retrieval_model'] == 'single':
@@ -83,9 +88,10 @@ class DatasetConfigManager:
                     retrieve_strategy=DatasetRetrieveConfigEntity.RetrieveStrategy.value_of(
                         dataset_configs['retrieval_model']
                     ),
-                    top_k=dataset_configs.get('top_k'),
+                    top_k=dataset_configs.get('top_k', 4),
                     score_threshold=dataset_configs.get('score_threshold'),
-                    reranking_model=dataset_configs.get('reranking_model')
+                    reranking_model=dataset_configs.get('reranking_model'),
+                    weights=dataset_configs.get('weights')
                 )
             )
 
@@ -114,12 +120,6 @@ class DatasetConfigManager:
         if not isinstance(config["dataset_configs"], dict):
             raise ValueError("dataset_configs must be of object type")
 
-        if config["dataset_configs"]['retrieval_model'] == 'multiple':
-            if not config["dataset_configs"]['reranking_model']:
-                raise ValueError("reranking_model has not been set")
-            if not isinstance(config["dataset_configs"]['reranking_model'], dict):
-                raise ValueError("reranking_model must be of object type")
-
         if not isinstance(config["dataset_configs"], dict):
             raise ValueError("dataset_configs must be of object type")
 

api/core/app/app_config/entities.py

@@ -159,7 +159,11 @@ class DatasetRetrieveConfigEntity(BaseModel):
     retrieve_strategy: RetrieveStrategy
     top_k: Optional[int] = None
     score_threshold: Optional[float] = None
+    rerank_mode: Optional[str] = 'reranking_model'
     reranking_model: Optional[dict] = None
+    weights: Optional[dict] = None
+
+
 
 
 class DatasetEntity(BaseModel):

api/core/app/segments/__init__.py

@@ -1,11 +1,12 @@
 from .segment_group import SegmentGroup
-from .segments import Segment
+from .segments import NoneSegment, Segment
 from .types import SegmentType
 from .variables import (
     ArrayVariable,
     FileVariable,
     FloatVariable,
     IntegerVariable,
+    NoneVariable,
     ObjectVariable,
     SecretVariable,
     StringVariable,
@@ -23,5 +24,7 @@ __all__ = [
     'Variable',
     'SegmentType',
     'SegmentGroup',
-    'Segment'
+    'Segment',
+    'NoneSegment',
+    'NoneVariable',
 ]

api/core/app/segments/factory.py

@@ -10,6 +10,7 @@ from .variables import (
     FileVariable,
     FloatVariable,
     IntegerVariable,
+    NoneVariable,
     ObjectVariable,
     SecretVariable,
     StringVariable,
@@ -39,6 +40,8 @@ def build_variable_from_mapping(m: Mapping[str, Any], /) -> Variable:
 
 
 def build_anonymous_variable(value: Any, /) -> Variable:
+    if value is None:
+        return NoneVariable(name='anonymous')
     if isinstance(value, str):
         return StringVariable(name='anonymous', value=value)
     if isinstance(value, int):

api/core/app/segments/segments.py

@@ -43,6 +43,23 @@ class Segment(BaseModel):
         return self.value
 
 
+class NoneSegment(Segment):
+    value_type: SegmentType = SegmentType.NONE
+    value: None = None
+
+    @property
+    def text(self) -> str:
+        return 'null'
+
+    @property
+    def log(self) -> str:
+        return 'null'
+
+    @property
+    def markdown(self) -> str:
+        return 'null'
+
+
 class StringSegment(Segment):
     value_type: SegmentType = SegmentType.STRING
     value: str

api/core/app/segments/types.py

@@ -2,16 +2,10 @@ from enum import Enum
 
 
 class SegmentType(str, Enum):
-    STRING = 'string'
+    NONE = 'none'
     NUMBER = 'number'
-    FILE = 'file'
-
+    STRING = 'string'
     SECRET = 'secret'
-
-    OBJECT = 'object'
-
     ARRAY = 'array'
-    ARRAY_STRING = 'array[string]'
-    ARRAY_NUMBER = 'array[number]'
-    ARRAY_OBJECT = 'array[object]'
-    ARRAY_FILE = 'array[file]'
+    OBJECT = 'object'
+    FILE = 'file'

api/core/app/segments/variables.py

@@ -6,7 +6,7 @@ from pydantic import Field
 from core.file.file_obj import FileVar
 from core.helper import encrypter
 
-from .segments import Segment, StringSegment
+from .segments import NoneSegment, Segment, StringSegment
 from .types import SegmentType
 
 
@@ -20,6 +20,7 @@ class Variable(Segment):
         description="Unique identity for variable. It's only used by environment variables now.",
     )
     name: str
+    description: str = Field(default='', description='Description of the variable.')
 
 
 class StringVariable(StringSegment, Variable):
@@ -81,3 +82,8 @@ class SecretVariable(StringVariable):
     @property
     def log(self) -> str:
         return encrypter.obfuscated_token(self.value)
+
+
+class NoneVariable(NoneSegment, Variable):
+    value_type: SegmentType = SegmentType.NONE
+    value: None = None

api/core/llm_generator/llm_generator.py

@@ -3,10 +3,13 @@ import logging
 import re
 from typing import Optional
 
-from core.llm_generator.output_parser.errors import OutputParserException
 from core.llm_generator.output_parser.rule_config_generator import RuleConfigGeneratorOutputParser
 from core.llm_generator.output_parser.suggested_questions_after_answer import SuggestedQuestionsAfterAnswerOutputParser
-from core.llm_generator.prompts import CONVERSATION_TITLE_PROMPT, GENERATOR_QA_PROMPT
+from core.llm_generator.prompts import (
+    CONVERSATION_TITLE_PROMPT,
+    GENERATOR_QA_PROMPT,
+    WORKFLOW_RULE_CONFIG_PROMPT_GENERATE_TEMPLATE,
+)
 from core.model_manager import ModelManager
 from core.model_runtime.entities.message_entities import SystemPromptMessage, UserPromptMessage
 from core.model_runtime.entities.model_entities import ModelType
@@ -115,55 +118,158 @@ class LLMGenerator:
         return questions
 
     @classmethod
-    def generate_rule_config(cls, tenant_id: str, audiences: str, hoping_to_solve: str) -> dict:
+    def generate_rule_config(cls, tenant_id: str, instruction: str, model_config: dict, no_variable: bool) -> dict:
         output_parser = RuleConfigGeneratorOutputParser()
 
+        error = ""
+        error_step = ""
+        rule_config = {
+            "prompt": "",
+            "variables": [],
+            "opening_statement": "",
+            "error": ""
+        }
+        model_parameters = {
+            "max_tokens": 512,
+            "temperature": 0.01
+        }
+
+        if no_variable:
+            prompt_template = PromptTemplateParser(
+                WORKFLOW_RULE_CONFIG_PROMPT_GENERATE_TEMPLATE
+            )
+
+            prompt_generate = prompt_template.format(
+                inputs={
+                    "TASK_DESCRIPTION": instruction,
+                },
+                remove_template_variables=False
+            )
+
+            prompt_messages = [UserPromptMessage(content=prompt_generate)]
+
+            model_manager = ModelManager()
+
+            model_instance = model_manager.get_default_model_instance(
+                tenant_id=tenant_id,
+                model_type=ModelType.LLM,
+            )
+
+            try:
+                response = model_instance.invoke_llm(
+                    prompt_messages=prompt_messages,
+                    model_parameters=model_parameters,
+                    stream=False
+                )
+
+                rule_config["prompt"] = response.message.content
+                
+            except InvokeError as e:
+                error = str(e)
+                error_step = "generate rule config"
+            except Exception as e:
+                logging.exception(e)
+                rule_config["error"] = str(e)
+
+            rule_config["error"] = f"Failed to {error_step}. Error: {error}" if error else ""
+
+            return rule_config
+
+        # get rule config prompt, parameter and statement
+        prompt_generate, parameter_generate, statement_generate = output_parser.get_format_instructions()
+
         prompt_template = PromptTemplateParser(
-            template=output_parser.get_format_instructions()
+            prompt_generate
         )
 
-        prompt = prompt_template.format(
+        parameter_template = PromptTemplateParser(
+            parameter_generate
+        )
+
+        statement_template = PromptTemplateParser(
+            statement_generate
+        )
+
+        # format the prompt_generate_prompt
+        prompt_generate_prompt = prompt_template.format(
             inputs={
-                "audiences": audiences,
-                "hoping_to_solve": hoping_to_solve,
-                "variable": "{{variable}}",
-                "lanA": "{{lanA}}",
-                "lanB": "{{lanB}}",
-                "topic": "{{topic}}"
+                "TASK_DESCRIPTION": instruction,
             },
             remove_template_variables=False
         )
+        prompt_messages = [UserPromptMessage(content=prompt_generate_prompt)]
 
+        # get model instance
         model_manager = ModelManager()
-        model_instance = model_manager.get_default_model_instance(
+        model_instance = model_manager.get_model_instance(
             tenant_id=tenant_id,
             model_type=ModelType.LLM,
+            provider=model_config.get("provider") if model_config else None,
+            model=model_config.get("name") if model_config else None,
         )
 
-        prompt_messages = [UserPromptMessage(content=prompt)]
-
         try:
-            response = model_instance.invoke_llm(
-                prompt_messages=prompt_messages,
-                model_parameters={
-                    "max_tokens": 512,
-                    "temperature": 0
-                },
-                stream=False
-            )
+            try:
+                # the first step to generate the task prompt
+                prompt_content = model_instance.invoke_llm(
+                    prompt_messages=prompt_messages,
+                    model_parameters=model_parameters,
+                    stream=False
+                )
+            except InvokeError as e:
+                error = str(e)
+                error_step = "generate prefix prompt"
+                rule_config["error"] = f"Failed to {error_step}. Error: {error}" if error else ""
+
+                return rule_config
+
+            rule_config["prompt"] = prompt_content.message.content
+
+            parameter_generate_prompt = parameter_template.format(
+                inputs={
+                    "INPUT_TEXT": prompt_content.message.content,
+                },
+                remove_template_variables=False
+            )
+            parameter_messages = [UserPromptMessage(content=parameter_generate_prompt)]
+
+            # the second step to generate the task_parameter and task_statement
+            statement_generate_prompt = statement_template.format(
+                inputs={
+                    "TASK_DESCRIPTION": instruction,
+                    "INPUT_TEXT": prompt_content.message.content,
+                },
+                remove_template_variables=False
+            )
+            statement_messages = [UserPromptMessage(content=statement_generate_prompt)]
+
+            try:
+                parameter_content = model_instance.invoke_llm(
+                    prompt_messages=parameter_messages,
+                    model_parameters=model_parameters,
+                    stream=False
+                )
+                rule_config["variables"] = re.findall(r'"\s*([^"]+)\s*"', parameter_content.message.content)
+            except InvokeError as e:
+                error = str(e)
+                error_step = "generate variables"
+
+            try:
+                statement_content = model_instance.invoke_llm(
+                    prompt_messages=statement_messages,
+                    model_parameters=model_parameters,
+                    stream=False
+                )
+                rule_config["opening_statement"] = statement_content.message.content
+            except InvokeError as e:
+                error = str(e)
+                error_step = "generate conversation opener"
 
-            rule_config = output_parser.parse(response.message.content)
-        except InvokeError as e:
-            raise e
-        except OutputParserException:
-            raise ValueError('Please give a valid input for intended audience or hoping to solve problems.')
         except Exception as e:
             logging.exception(e)
-            rule_config = {
-                "prompt": "",
-                "variables": [],
-                "opening_statement": ""
-            }
+            rule_config["error"] = str(e)
+
+        rule_config["error"] = f"Failed to {error_step}. Error: {error}" if error else ""
 
         return rule_config
 

api/core/llm_generator/output_parser/rule_config_generator.py

@@ -1,14 +1,18 @@
 from typing import Any
 
 from core.llm_generator.output_parser.errors import OutputParserException
-from core.llm_generator.prompts import RULE_CONFIG_GENERATE_TEMPLATE
+from core.llm_generator.prompts import (
+    RULE_CONFIG_PARAMETER_GENERATE_TEMPLATE,
+    RULE_CONFIG_PROMPT_GENERATE_TEMPLATE,
+    RULE_CONFIG_STATEMENT_GENERATE_TEMPLATE,
+)
 from libs.json_in_md_parser import parse_and_check_json_markdown
 
 
 class RuleConfigGeneratorOutputParser:
 
-    def get_format_instructions(self) -> str:
-        return RULE_CONFIG_GENERATE_TEMPLATE
+    def get_format_instructions(self) -> tuple[str, str, str]:
+        return RULE_CONFIG_PROMPT_GENERATE_TEMPLATE, RULE_CONFIG_PARAMETER_GENERATE_TEMPLATE, RULE_CONFIG_STATEMENT_GENERATE_TEMPLATE
 
     def parse(self, text: str) -> Any:
         try:

api/core/llm_generator/prompts.py

@@ -81,65 +81,73 @@ GENERATOR_QA_PROMPT = (
     '<QA Pairs>'
 )
 
-RULE_CONFIG_GENERATE_TEMPLATE = """Given MY INTENDED AUDIENCES and HOPING TO SOLVE using a language model, please select \
-the model prompt that best suits the input. 
-You will be provided with the prompt, variables, and an opening statement. 
-Only the content enclosed in double curly braces, such as {{variable}}, in the prompt can be considered as a variable; \
-otherwise, it cannot exist as a variable in the variables.
-If you believe revising the original input will result in a better response from the language model, you may \
-suggest revisions.
+WORKFLOW_RULE_CONFIG_PROMPT_GENERATE_TEMPLATE = """
+Here is a task description for which I would like you to create a high-quality prompt template for:
+<task_description>
+{{TASK_DESCRIPTION}}
+</task_description>
+Based on task description, please create a well-structured prompt template that another AI could use to consistently complete the task. The prompt template should include:
+- Do not inlcude <input> or <output> section and variables in the prompt, assume user will add them at their own will. 
+- Clear instructions for the AI that will be using this prompt, demarcated with <instructions> tags. The instructions should provide step-by-step directions on how to complete the task using the input variables. Also Specifies in the instructions that the output should not contain any xml tag. 
+- Relevant examples if needed to clarify the task further, demarcated with <example> tags. Do not include variables in the prompt. Give three pairs of input and output examples.   
+- Include other relevant sections demarcated with appropriate XML tags like <examples>, <instructions>.
+- Use the same language as task description. 
+- Output in ``` xml ``` and start with <instruction>
+Please generate the full prompt template with at least 300 words and output only the prompt template.
+"""
 
-<<PRINCIPLES OF GOOD PROMPT>>
-Integrate the intended audience in the prompt e.g. the audience is an expert in the field.
-Break down complex tasks into a sequence of simpler prompts in an interactive conversation.
-Implement example-driven prompting (Use few-shot prompting). 
-When formatting your prompt start with Instruction followed by either Example if relevant. \
-Subsequently present your content. Use one or more line breaks to separate instructions examples questions context and input data.
-Incorporate the following phrases: “Your task is” and “You MUST”.
-Incorporate the following phrases: “You will be penalized”.
-Use leading words like writing “think step by step”.
-Add to your prompt the following phrase “Ensure that your answer is unbiased and does not rely on stereotypes”.
-Assign a role to the large language models.
-Use Delimiters.
-To write an essay /text /paragraph /article or any type of text that should be detailed: “Write a detailed [essay/text/paragraph] for me on [topic] in detail by adding all the information necessary”.
-Clearly state the requirements that the model must follow in order to produce content in the form of the keywords regulations hint or instructions
+RULE_CONFIG_PROMPT_GENERATE_TEMPLATE = """
+Here is a task description for which I would like you to create a high-quality prompt template for:
+<task_description>
+{{TASK_DESCRIPTION}}
+</task_description>
+Based on task description, please create a well-structured prompt template that another AI could use to consistently complete the task. The prompt template should include:
+- Descriptive variable names surrounded by {{ }} (two curly brackets) to indicate where the actual values will be substituted in. Choose variable names that clearly indicate the type of value expected. Variable names have to be composed of number, english alphabets and underline and nothing else. 
+- Clear instructions for the AI that will be using this prompt, demarcated with <instructions> tags. The instructions should provide step-by-step directions on how to complete the task using the input variables. Also Specifies in the instructions that the output should not contain any xml tag. 
+- Relevant examples if needed to clarify the task further, demarcated with <example> tags. Do not use curly brackets any other than in <instruction> section. 
+- Any other relevant sections demarcated with appropriate XML tags like <input>, <output>, etc.
+- Use the same language as task description. 
+- Output in ``` xml ``` and start with <instruction>
+Please generate the full prompt template and output only the prompt template.
+"""
 
-<< FORMATTING >>
-Return a markdown code snippet with a JSON object formatted to look like, \
-no any other string out of markdown code snippet:
-```json
-{{{{
-    "prompt": string \\ generated prompt
-    "variables": list of string \\ variables
-    "opening_statement": string \\ an opening statement to guide users on how to ask questions with generated prompt \
-and fill in variables, with a welcome sentence, and keep TLDR.
-}}}}
-```
+RULE_CONFIG_PARAMETER_GENERATE_TEMPLATE = """
+I need to extract the following information from the input text. The <information to be extracted> tag specifies the 'type', 'description' and 'required' of the information to be extracted. 
+<information to be extracted>
+variables name bounded two double curly brackets. Variable name has to be composed of number, english alphabets and underline and nothing else. 
+</information to be extracted>
 
-<< EXAMPLES >>
-[EXAMPLE A]
-```json
-{
-  "prompt": "I need your help to translate the following {{Input_language}}paper paragraph into {{Target_language}}, in a style similar to a popular science magazine in {{Target_language}}. #### Rules Ensure accurate conveyance of the original text's facts and context during translation. Maintain the original paragraph format and retain technical terms and company abbreviations ",
-  "variables": ["Input_language", "Target_language"],
-  "opening_statement": " Hi. I am your translation assistant. I can help you with any translation and ensure accurate conveyance of information. "
-}
-```
+Step 1: Carefully read the input and understand the structure of the expected output.
+Step 2: Extract relevant parameters from the provided text based on the name and description of object. 
+Step 3: Structure the extracted parameters to JSON object as specified in <structure>.
+Step 4: Ensure that the list of variable_names is properly formatted and valid. The output should not contain any XML tags. Output an empty list if there is no valid variable name in input text. 
 
-[EXAMPLE B]
-```json
-{
-  "prompt": "Your task is to review the provided meeting notes and create a concise summary that captures the essential information, focusing on key takeaways and action items assigned to specific individuals or departments during the meeting. Use clear and professional language, and organize the summary in a logical manner using appropriate formatting such as headings, subheadings, and bullet points. Ensure that the summary is easy to understand and provides a comprehensive but succinct overview of the meeting's content, with a particular focus on clearly indicating who is responsible for each action item.",
-  "variables": ["meeting_notes"],
-  "opening_statement": "Hi! I'm your meeting notes summarizer AI. I can help you with any meeting notes and ensure accurate conveyance of information."
-}
-```
+### Structure
+Here is the structure of the expected output, I should always follow the output structure. 
+["variable_name_1", "variable_name_2"]
 
-<< MY INTENDED AUDIENCES >>
-{{audiences}}
+### Input Text
+Inside <text></text> XML tags, there is a text that I should extract parameters and convert to a JSON object.
+<text>
+{{INPUT_TEXT}}
+</text>
 
-<< HOPING TO SOLVE >>
-{{hoping_to_solve}}
+### Answer
+I should always output a valid list. Output nothing other than the list of variable_name. Output an empty list if there is no variable name in input text.
+"""
 
-<< OUTPUT >>
-"""
+RULE_CONFIG_STATEMENT_GENERATE_TEMPLATE = """
+<instruction>
+Step 1: Identify the purpose of the chatbot from the variable {{TASK_DESCRIPTION}} and infer chatbot's tone  (e.g., friendly, professional, etc.) to add personality traits. 
+Step 2: Create a coherent and engaging opening statement.
+Step 3: Ensure the output is welcoming and clearly explains what the chatbot is designed to do. Do not include any XML tags in the output.
+Please use the same language as the user's input language. If user uses chinese then generate opening statement in chinese,  if user uses english then generate opening statement in english. 
+Example Input: 
+Provide customer support for an e-commerce website
+Example Output: 
+Welcome! I'm here to assist you with any questions or issues you might have with your shopping experience. Whether you're looking for product information, need help with your order, or have any other inquiries, feel free to ask. I'm friendly, helpful, and ready to support you in any way I can.
+<Task>
+Here is the task description: {{INPUT_TEXT}}
+
+You just need to generate the output
+"""

api/core/model_runtime/docs/en_US/schema.md

@@ -86,6 +86,9 @@
 
 - `agent-thought` Agent reasoning, generally over 70B with thought chain capability.
 - `vision` Vision, i.e., image understanding.
+- `tool-call`
+- `multi-tool-call`
+- `stream-tool-call`
 
 ### FetchFrom
 

api/core/model_runtime/docs/zh_Hans/schema.md

@@ -87,6 +87,9 @@
 
 - `agent-thought` Agent 推理，一般超过 70B 有思维链能力。
 - `vision` 视觉，即：图像理解。
+- `tool-call` 工具调用
+- `multi-tool-call` 多工具调用
+- `stream-tool-call` 流式工具调用
 
 ### FetchFrom
 

api/core/model_runtime/model_providers/groq/llm/_position.yaml

@@ -0,0 +1,7 @@
+- llama-3.1-405b-reasoning
+- llama-3.1-70b-versatile
+- llama-3.1-8b-instant
+- llama3-70b-8192
+- llama3-8b-8192
+- mixtral-8x7b-32768
+- llama2-70b-4096

api/core/model_runtime/model_providers/groq/llm/llama-3.1-405b-reasoning.yaml

@@ -0,0 +1,25 @@
+model: llama-3.1-405b-reasoning
+label:
+  zh_Hans: Llama-3.1-405b-reasoning
+  en_US: Llama-3.1-405b-reasoning
+model_type: llm
+features:
+  - agent-thought
+model_properties:
+  mode: chat
+  context_size: 131072
+parameter_rules:
+  - name: temperature
+    use_template: temperature
+  - name: top_p
+    use_template: top_p
+  - name: max_tokens
+    use_template: max_tokens
+    default: 512
+    min: 1
+    max: 8192
+pricing:
+  input: '0.05'
+  output: '0.1'
+  unit: '0.000001'
+  currency: USD

api/core/model_runtime/model_providers/groq/llm/llama-3.1-70b-versatile.yaml

@@ -0,0 +1,25 @@
+model: llama-3.1-70b-versatile
+label:
+  zh_Hans: Llama-3.1-70b-versatile
+  en_US: Llama-3.1-70b-versatile
+model_type: llm
+features:
+  - agent-thought
+model_properties:
+  mode: chat
+  context_size: 131072
+parameter_rules:
+  - name: temperature
+    use_template: temperature
+  - name: top_p
+    use_template: top_p
+  - name: max_tokens
+    use_template: max_tokens
+    default: 512
+    min: 1
+    max: 8192
+pricing:
+  input: '0.05'
+  output: '0.1'
+  unit: '0.000001'
+  currency: USD

api/core/model_runtime/model_providers/groq/llm/llama-3.1-8b-instant.yaml

@@ -0,0 +1,25 @@
+model: llama-3.1-8b-instant
+label:
+  zh_Hans: Llama-3.1-8b-instant
+  en_US: Llama-3.1-8b-instant
+model_type: llm
+features:
+  - agent-thought
+model_properties:
+  mode: chat
+  context_size: 131072
+parameter_rules:
+  - name: temperature
+    use_template: temperature
+  - name: top_p
+    use_template: top_p
+  - name: max_tokens
+    use_template: max_tokens
+    default: 512
+    min: 1
+    max: 8192
+pricing:
+  input: '0.05'
+  output: '0.1'
+  unit: '0.000001'
+  currency: USD

api/core/model_runtime/model_providers/openrouter/llm/_position.yaml

@@ -12,6 +12,9 @@
 - google/gemini-pro
 - cohere/command-r-plus
 - cohere/command-r
+- meta-llama/llama-3.1-405b-instruct
+- meta-llama/llama-3.1-70b-instruct
+- meta-llama/llama-3.1-8b-instruct
 - meta-llama/llama-3-70b-instruct
 - meta-llama/llama-3-8b-instruct
 - mistralai/mixtral-8x22b-instruct

api/core/model_runtime/model_providers/openrouter/llm/llama-3.1-405b-instruct.yaml

@@ -0,0 +1,23 @@
+model: meta-llama/llama-3.1-405b-instruct
+label:
+  en_US: llama-3.1-405b-instruct
+model_type: llm
+model_properties:
+  mode: chat
+  context_size: 128000
+parameter_rules:
+  - name: temperature
+    use_template: temperature
+  - name: top_p
+    use_template: top_p
+  - name: max_tokens
+    use_template: max_tokens
+    required: true
+    default: 512
+    min: 1
+    max: 128000
+pricing:
+  input: "3"
+  output: "3"
+  unit: "0.000001"
+  currency: USD

api/core/model_runtime/model_providers/openrouter/llm/llama-3.1-70b-instruct.yaml

@@ -0,0 +1,23 @@
+model: meta-llama/llama-3.1-70b-instruct
+label:
+  en_US: llama-3.1-70b-instruct
+model_type: llm
+model_properties:
+  mode: chat
+  context_size: 128000
+parameter_rules:
+  - name: temperature
+    use_template: temperature
+  - name: top_p
+    use_template: top_p
+  - name: max_tokens
+    use_template: max_tokens
+    required: true
+    default: 512
+    min: 1
+    max: 128000
+pricing:
+  input: "0.9"
+  output: "0.9"
+  unit: "0.000001"
+  currency: USD

api/core/model_runtime/model_providers/openrouter/llm/llama-3.1-8b-instruct.yaml

@@ -0,0 +1,23 @@
+model: meta-llama/llama-3.1-8b-instruct
+label:
+  en_US: llama-3.1-8b-instruct
+model_type: llm
+model_properties:
+  mode: chat
+  context_size: 128000
+parameter_rules:
+  - name: temperature
+    use_template: temperature
+  - name: top_p
+    use_template: top_p
+  - name: max_tokens
+    use_template: max_tokens
+    required: true
+    default: 512
+    min: 1
+    max: 128000
+pricing:
+  input: "0.2"
+  output: "0.2"
+  unit: "0.000001"
+  currency: USD

api/core/model_runtime/model_providers/tongyi/llm/llm.py

@@ -262,6 +262,10 @@ You should also complete the text started with ``` but not tell ``` directly.
         :param prompt_messages: prompt messages
         :return: llm response
         """
+        if response.status_code != 200 and response.status_code != HTTPStatus.OK:
+            raise ServiceUnavailableError(
+                response.message
+            )
         # transform assistant message to prompt message
         assistant_prompt_message = AssistantPromptMessage(
             content=response.output.choices[0].message.content,
@@ -421,7 +425,7 @@ You should also complete the text started with ``` but not tell ``` directly.
             raise ValueError(f"Got unknown type {message}")
 
         return message_text
-    
+
     def _convert_messages_to_prompt(self, messages: list[PromptMessage]) -> str:
         """
         Format a list of messages into a full prompt for the Anthropic model
@@ -496,6 +500,9 @@ You should also complete the text started with ``` but not tell ``` directly.
                 tongyi_messages.append({
                     'role': 'assistant',
                     'content': content if not rich_content else [{"text": content}],
+                    'tool_calls': [tool_call.model_dump() for tool_call in
+                                   prompt_message.tool_calls] if prompt_message.tool_calls else []
+
                 })
             elif isinstance(prompt_message, ToolPromptMessage):
                 tongyi_messages.append({

api/core/ops/utils.py

@@ -25,7 +25,6 @@ def measure_time():
         yield timing_info
     finally:
         timing_info['end'] = datetime.now()
-        print(f"Execution time: {timing_info['end'] - timing_info['start']}")
 
 
 def replace_text_with_content(data):

api/core/rag/data_post_processor/data_post_processor.py

@@ -5,15 +5,20 @@ from core.model_runtime.entities.model_entities import ModelType
 from core.model_runtime.errors.invoke import InvokeAuthorizationError
 from core.rag.data_post_processor.reorder import ReorderRunner
 from core.rag.models.document import Document
-from core.rag.rerank.rerank import RerankRunner
+from core.rag.rerank.constants.rerank_mode import RerankMode
+from core.rag.rerank.entity.weight import KeywordSetting, VectorSetting, Weights
+from core.rag.rerank.rerank_model import RerankModelRunner
+from core.rag.rerank.weight_rerank import WeightRerankRunner
 
 
 class DataPostProcessor:
     """Interface for data post-processing document.
     """
 
-    def __init__(self, tenant_id: str, reranking_model: dict, reorder_enabled: bool = False):
-        self.rerank_runner = self._get_rerank_runner(reranking_model, tenant_id)
+    def __init__(self, tenant_id: str, reranking_mode: str,
+                 reranking_model: Optional[dict] = None, weights: Optional[dict] = None,
+                 reorder_enabled: bool = False):
+        self.rerank_runner = self._get_rerank_runner(reranking_mode, tenant_id, reranking_model, weights)
         self.reorder_runner = self._get_reorder_runner(reorder_enabled)
 
     def invoke(self, query: str, documents: list[Document], score_threshold: Optional[float] = None,
@@ -26,19 +31,37 @@ class DataPostProcessor:
 
         return documents
 
-    def _get_rerank_runner(self, reranking_model: dict, tenant_id: str) -> Optional[RerankRunner]:
-        if reranking_model:
-            try:
-                model_manager = ModelManager()
-                rerank_model_instance = model_manager.get_model_instance(
-                    tenant_id=tenant_id,
-                    provider=reranking_model['reranking_provider_name'],
-                    model_type=ModelType.RERANK,
-                    model=reranking_model['reranking_model_name']
+    def _get_rerank_runner(self, reranking_mode: str, tenant_id: str, reranking_model: Optional[dict] = None,
+                           weights: Optional[dict] = None) -> Optional[RerankModelRunner | WeightRerankRunner]:
+        if reranking_mode == RerankMode.WEIGHTED_SCORE.value and weights:
+            return WeightRerankRunner(
+                tenant_id,
+                Weights(
+                    weight_type=weights['weight_type'],
+                    vector_setting=VectorSetting(
+                        vector_weight=weights['vector_setting']['vector_weight'],
+                        embedding_provider_name=weights['vector_setting']['embedding_provider_name'],
+                        embedding_model_name=weights['vector_setting']['embedding_model_name'],
+                    ),
+                    keyword_setting=KeywordSetting(
+                        keyword_weight=weights['keyword_setting']['keyword_weight'],
+                    )
                 )
-            except InvokeAuthorizationError:
-                return None
-            return RerankRunner(rerank_model_instance)
+            )
+        elif reranking_mode == RerankMode.RERANKING_MODEL.value:
+            if reranking_model:
+                try:
+                    model_manager = ModelManager()
+                    rerank_model_instance = model_manager.get_model_instance(
+                        tenant_id=tenant_id,
+                        provider=reranking_model['reranking_provider_name'],
+                        model_type=ModelType.RERANK,
+                        model=reranking_model['reranking_model_name']
+                    )
+                except InvokeAuthorizationError:
+                    return None
+                return RerankModelRunner(rerank_model_instance)
+            return None
         return None
 
     def _get_reorder_runner(self, reorder_enabled) -> Optional[ReorderRunner]:

api/core/rag/datasource/keyword/jieba/jieba_keyword_table_handler.py

@@ -1,4 +1,5 @@
 import re
+from typing import Optional
 
 import jieba
 from jieba.analyse import default_tfidf
@@ -11,7 +12,7 @@ class JiebaKeywordTableHandler:
     def __init__(self):
         default_tfidf.stop_words = STOPWORDS
 
-    def extract_keywords(self, text: str, max_keywords_per_chunk: int = 10) -> set[str]:
+    def extract_keywords(self, text: str, max_keywords_per_chunk: Optional[int] = 10) -> set[str]:
         """Extract keywords with JIEBA tfidf."""
         keywords = jieba.analyse.extract_tags(
             sentence=text,

api/core/rag/datasource/retrieval_service.py

@@ -6,6 +6,7 @@ from flask import Flask, current_app
 from core.rag.data_post_processor.data_post_processor import DataPostProcessor
 from core.rag.datasource.keyword.keyword_factory import Keyword
 from core.rag.datasource.vdb.vector_factory import Vector
+from core.rag.rerank.constants.rerank_mode import RerankMode
 from core.rag.retrieval.retrival_methods import RetrievalMethod
 from extensions.ext_database import db
 from models.dataset import Dataset
@@ -26,13 +27,19 @@ class RetrievalService:
 
     @classmethod
     def retrieve(cls, retrival_method: str, dataset_id: str, query: str,
-                 top_k: int, score_threshold: Optional[float] = .0, reranking_model: Optional[dict] = None):
+                 top_k: int, score_threshold: Optional[float] = .0,
+                 reranking_model: Optional[dict] = None, reranking_mode: Optional[str] = None,
+                 weights: Optional[dict] = None):
         dataset = db.session.query(Dataset).filter(
             Dataset.id == dataset_id
         ).first()
         if not dataset or dataset.available_document_count == 0 or dataset.available_segment_count == 0:
             return []
         all_documents = []
+        keyword_search_documents = []
+        embedding_search_documents = []
+        full_text_search_documents = []
+        hybrid_search_documents = []
         threads = []
         exceptions = []
         # retrieval_model source with keyword
@@ -87,7 +94,8 @@ class RetrievalService:
             raise Exception(exception_message)
 
         if retrival_method == RetrievalMethod.HYBRID_SEARCH.value:
-            data_post_processor = DataPostProcessor(str(dataset.tenant_id), reranking_model, False)
+            data_post_processor = DataPostProcessor(str(dataset.tenant_id), reranking_mode,
+                                                    reranking_model, weights, False)
             all_documents = data_post_processor.invoke(
                 query=query,
                 documents=all_documents,
@@ -143,7 +151,9 @@ class RetrievalService:
 
                 if documents:
                     if reranking_model and retrival_method == RetrievalMethod.SEMANTIC_SEARCH.value:
-                        data_post_processor = DataPostProcessor(str(dataset.tenant_id), reranking_model, False)
+                        data_post_processor = DataPostProcessor(str(dataset.tenant_id),
+                                                                RerankMode.RERANKING_MODEL.value,
+                                                                reranking_model, None, False)
                         all_documents.extend(data_post_processor.invoke(
                             query=query,
                             documents=documents,
@@ -175,7 +185,9 @@ class RetrievalService:
                 )
                 if documents:
                     if reranking_model and retrival_method == RetrievalMethod.FULL_TEXT_SEARCH.value:
-                        data_post_processor = DataPostProcessor(str(dataset.tenant_id), reranking_model, False)
+                        data_post_processor = DataPostProcessor(str(dataset.tenant_id),
+                                                                RerankMode.RERANKING_MODEL.value,
+                                                                reranking_model, None, False)
                         all_documents.extend(data_post_processor.invoke(
                             query=query,
                             documents=documents,

api/core/rag/datasource/vdb/qdrant/qdrant_vector.py

@@ -396,9 +396,11 @@ class QdrantVector(BaseVector):
         documents = []
         for result in results:
             if result:
-                documents.append(self._document_from_scored_point(
+                document = self._document_from_scored_point(
                     result, Field.CONTENT_KEY.value, Field.METADATA_KEY.value
-                ))
+                )
+                document.metadata['vector'] = result.vector
+                documents.append(document)
 
         return documents
 

api/core/rag/rerank/constants/rerank_mode.py

@@ -0,0 +1,8 @@
+from enum import Enum
+
+
+class RerankMode(Enum):
+
+    RERANKING_MODEL = 'reranking_model'
+    WEIGHTED_SCORE = 'weighted_score'
+

api/core/rag/rerank/entity/weight.py

@@ -0,0 +1,23 @@
+from pydantic import BaseModel
+
+
+class VectorSetting(BaseModel):
+    vector_weight: float
+
+    embedding_provider_name: str
+
+    embedding_model_name: str
+
+
+class KeywordSetting(BaseModel):
+    keyword_weight: float
+
+
+class Weights(BaseModel):
+    """Model for weighted rerank."""
+
+    weight_type: str
+
+    vector_setting: VectorSetting
+
+    keyword_setting: KeywordSetting

api/core/rag/rerank/rerank_model.py

@@ -4,7 +4,7 @@ from core.model_manager import ModelInstance
 from core.rag.models.document import Document
 
 
-class RerankRunner:
+class RerankModelRunner:
     def __init__(self, rerank_model_instance: ModelInstance) -> None:
         self.rerank_model_instance = rerank_model_instance
 

api/core/rag/rerank/weight_rerank.py

@@ -0,0 +1,178 @@
+import math
+from collections import Counter
+from typing import Optional
+
+import numpy as np
+
+from core.embedding.cached_embedding import CacheEmbedding
+from core.model_manager import ModelManager
+from core.model_runtime.entities.model_entities import ModelType
+from core.rag.datasource.keyword.jieba.jieba_keyword_table_handler import JiebaKeywordTableHandler
+from core.rag.models.document import Document
+from core.rag.rerank.entity.weight import VectorSetting, Weights
+
+
+class WeightRerankRunner:
+
+    def __init__(self, tenant_id: str, weights: Weights) -> None:
+        self.tenant_id = tenant_id
+        self.weights = weights
+
+    def run(self, query: str, documents: list[Document], score_threshold: Optional[float] = None,
+            top_n: Optional[int] = None, user: Optional[str] = None) -> list[Document]:
+        """
+        Run rerank model
+        :param query: search query
+        :param documents: documents for reranking
+        :param score_threshold: score threshold
+        :param top_n: top n
+        :param user: unique user id if needed
+
+        :return:
+        """
+        docs = []
+        doc_id = []
+        unique_documents = []
+        for document in documents:
+            if document.metadata['doc_id'] not in doc_id:
+                doc_id.append(document.metadata['doc_id'])
+                docs.append(document.page_content)
+                unique_documents.append(document)
+
+        documents = unique_documents
+
+        rerank_documents = []
+        query_scores = self._calculate_keyword_score(query, documents)
+
+        query_vector_scores = self._calculate_cosine(self.tenant_id, query, documents, self.weights.vector_setting)
+        for document, query_score, query_vector_score in zip(documents, query_scores, query_vector_scores):
+            # format document
+            score = self.weights.vector_setting.vector_weight * query_vector_score + \
+                    self.weights.keyword_setting.keyword_weight * query_score
+            if score_threshold and score < score_threshold:
+                continue
+            document.metadata['score'] = score
+            rerank_documents.append(document)
+        rerank_documents = sorted(rerank_documents, key=lambda x: x.metadata['score'], reverse=True)
+        return rerank_documents[:top_n] if top_n else rerank_documents
+
+    def _calculate_keyword_score(self, query: str, documents: list[Document]) -> list[float]:
+        """
+        Calculate BM25 scores
+        :param query: search query
+        :param documents: documents for reranking
+
+        :return:
+        """
+        keyword_table_handler = JiebaKeywordTableHandler()
+        query_keywords = keyword_table_handler.extract_keywords(query, None)
+        documents_keywords = []
+        for document in documents:
+            # get the document keywords
+            document_keywords = keyword_table_handler.extract_keywords(document.page_content, None)
+            document.metadata['keywords'] = document_keywords
+            documents_keywords.append(document_keywords)
+
+        # Counter query keywords(TF)
+        query_keyword_counts = Counter(query_keywords)
+
+        # total documents
+        total_documents = len(documents)
+
+        # calculate all documents' keywords IDF
+        all_keywords = set()
+        for document_keywords in documents_keywords:
+            all_keywords.update(document_keywords)
+
+        keyword_idf = {}
+        for keyword in all_keywords:
+            # calculate include query keywords' documents
+            doc_count_containing_keyword = sum(1 for doc_keywords in documents_keywords if keyword in doc_keywords)
+            # IDF
+            keyword_idf[keyword] = math.log((1 + total_documents) / (1 + doc_count_containing_keyword)) + 1
+
+        query_tfidf = {}
+
+        for keyword, count in query_keyword_counts.items():
+            tf = count
+            idf = keyword_idf.get(keyword, 0)
+            query_tfidf[keyword] = tf * idf
+
+        # calculate all documents' TF-IDF
+        documents_tfidf = []
+        for document_keywords in documents_keywords:
+            document_keyword_counts = Counter(document_keywords)
+            document_tfidf = {}
+            for keyword, count in document_keyword_counts.items():
+                tf = count
+                idf = keyword_idf.get(keyword, 0)
+                document_tfidf[keyword] = tf * idf
+            documents_tfidf.append(document_tfidf)
+
+        def cosine_similarity(vec1, vec2):
+            intersection = set(vec1.keys()) & set(vec2.keys())
+            numerator = sum(vec1[x] * vec2[x] for x in intersection)
+
+            sum1 = sum(vec1[x] ** 2 for x in vec1.keys())
+            sum2 = sum(vec2[x] ** 2 for x in vec2.keys())
+            denominator = math.sqrt(sum1) * math.sqrt(sum2)
+
+            if not denominator:
+                return 0.0
+            else:
+                return float(numerator) / denominator
+
+        similarities = []
+        for document_tfidf in documents_tfidf:
+            similarity = cosine_similarity(query_tfidf, document_tfidf)
+            similarities.append(similarity)
+
+        # for idx, similarity in enumerate(similarities):
+        #     print(f"Document {idx + 1} similarity: {similarity}")
+
+        return similarities
+
+    def _calculate_cosine(self, tenant_id: str, query: str, documents: list[Document],
+                          vector_setting: VectorSetting) -> list[float]:
+        """
+        Calculate Cosine scores
+        :param query: search query
+        :param documents: documents for reranking
+
+        :return:
+        """
+        query_vector_scores = []
+
+        model_manager = ModelManager()
+
+        embedding_model = model_manager.get_model_instance(
+            tenant_id=tenant_id,
+            provider=vector_setting.embedding_provider_name,
+            model_type=ModelType.TEXT_EMBEDDING,
+            model=vector_setting.embedding_model_name
+
+        )
+        cache_embedding = CacheEmbedding(embedding_model)
+        query_vector = cache_embedding.embed_query(query)
+        for document in documents:
+            # calculate cosine similarity
+            if 'score' in document.metadata:
+                query_vector_scores.append(document.metadata['score'])
+            else:
+                content_vector = document.metadata['vector']
+                # transform to NumPy
+                vec1 = np.array(query_vector)
+                vec2 = np.array(document.metadata['vector'])
+
+                # calculate dot product
+                dot_product = np.dot(vec1, vec2)
+
+                # calculate norm
+                norm_vec1 = np.linalg.norm(vec1)
+                norm_vec2 = np.linalg.norm(vec2)
+
+                # calculate cosine similarity
+                cosine_sim = dot_product / (norm_vec1 * norm_vec2)
+                query_vector_scores.append(cosine_sim)
+
+        return query_vector_scores

api/core/rag/retrieval/dataset_retrieval.py

@@ -1,4 +1,6 @@
+import math
 import threading
+from collections import Counter
 from typing import Optional, cast
 
 from flask import Flask, current_app
@@ -14,9 +16,10 @@ from core.model_runtime.entities.model_entities import ModelFeature, ModelType
 from core.model_runtime.model_providers.__base.large_language_model import LargeLanguageModel
 from core.ops.ops_trace_manager import TraceQueueManager, TraceTask, TraceTaskName
 from core.ops.utils import measure_time
+from core.rag.data_post_processor.data_post_processor import DataPostProcessor
+from core.rag.datasource.keyword.jieba.jieba_keyword_table_handler import JiebaKeywordTableHandler
 from core.rag.datasource.retrieval_service import RetrievalService
 from core.rag.models.document import Document
-from core.rag.rerank.rerank import RerankRunner
 from core.rag.retrieval.retrival_methods import RetrievalMethod
 from core.rag.retrieval.router.multi_dataset_function_call_router import FunctionCallMultiDatasetRouter
 from core.rag.retrieval.router.multi_dataset_react_route import ReactMultiDatasetRouter
@@ -132,8 +135,9 @@ class DatasetRetrieval:
                 app_id, tenant_id, user_id, user_from,
                 available_datasets, query, retrieve_config.top_k,
                 retrieve_config.score_threshold,
-                retrieve_config.reranking_model.get('reranking_provider_name'),
-                retrieve_config.reranking_model.get('reranking_model_name'),
+                retrieve_config.rerank_mode,
+                retrieve_config.reranking_model,
+                retrieve_config.weights,
                 message_id,
             )
 
@@ -272,7 +276,8 @@ class DatasetRetrieval:
                         retrival_method=retrival_method, dataset_id=dataset.id,
                         query=query,
                         top_k=top_k, score_threshold=score_threshold,
-                        reranking_model=reranking_model
+                        reranking_model=reranking_model,
+                        weights=retrieval_model_config.get('weights', None),
                     )
                 self._on_query(query, [dataset_id], app_id, user_from, user_id)
 
@@ -292,14 +297,18 @@ class DatasetRetrieval:
             query: str,
             top_k: int,
             score_threshold: float,
-            reranking_provider_name: str,
-            reranking_model_name: str,
+            reranking_mode: str,
+            reranking_model: Optional[dict] = None,
+            weights: Optional[dict] = None,
+            reranking_enable: bool = True,
             message_id: Optional[str] = None,
     ):
         threads = []
         all_documents = []
         dataset_ids = [dataset.id for dataset in available_datasets]
+        index_type = None
         for dataset in available_datasets:
+            index_type = dataset.indexing_technique
             retrieval_thread = threading.Thread(target=self._retriever, kwargs={
                 'flask_app': current_app._get_current_object(),
                 'dataset_id': dataset.id,
@@ -311,23 +320,24 @@ class DatasetRetrieval:
             retrieval_thread.start()
         for thread in threads:
             thread.join()
-        # do rerank for searched documents
-        model_manager = ModelManager()
-        rerank_model_instance = model_manager.get_model_instance(
-            tenant_id=tenant_id,
-            provider=reranking_provider_name,
-            model_type=ModelType.RERANK,
-            model=reranking_model_name
-        )
 
-        rerank_runner = RerankRunner(rerank_model_instance)
+        if reranking_enable:
+            # do rerank for searched documents
+            data_post_processor = DataPostProcessor(tenant_id, reranking_mode,
+                                                    reranking_model, weights, False)
 
-        with measure_time() as timer:
-            all_documents = rerank_runner.run(
-                query, all_documents,
-                score_threshold,
-                top_k
-            )
+            with measure_time() as timer:
+                all_documents = data_post_processor.invoke(
+                    query=query,
+                    documents=all_documents,
+                    score_threshold=score_threshold,
+                    top_n=top_k
+                )
+        else:
+            if index_type == "economy":
+                all_documents = self.calculate_keyword_score(query, all_documents, top_k)
+            elif index_type == "high_quality":
+                all_documents = self.calculate_vector_score(all_documents, top_k, score_threshold)
         self._on_query(query, dataset_ids, app_id, user_from, user_id)
 
         if all_documents:
@@ -420,7 +430,8 @@ class DatasetRetrieval:
                                                           score_threshold=retrieval_model['score_threshold']
                                                           if retrieval_model['score_threshold_enabled'] else None,
                                                           reranking_model=retrieval_model['reranking_model']
-                                                          if retrieval_model['reranking_enable'] else None
+                                                          if retrieval_model['reranking_enable'] else None,
+                                                          weights=retrieval_model.get('weights', None),
                                                           )
 
                     all_documents.extend(documents)
@@ -513,3 +524,94 @@ class DatasetRetrieval:
             tools.append(tool)
 
         return tools
+
+    def calculate_keyword_score(self, query: str, documents: list[Document], top_k: int) -> list[Document]:
+        """
+        Calculate keywords scores
+        :param query: search query
+        :param documents: documents for reranking
+
+        :return:
+        """
+        keyword_table_handler = JiebaKeywordTableHandler()
+        query_keywords = keyword_table_handler.extract_keywords(query, None)
+        documents_keywords = []
+        for document in documents:
+            # get the document keywords
+            document_keywords = keyword_table_handler.extract_keywords(document.page_content, None)
+            document.metadata['keywords'] = document_keywords
+            documents_keywords.append(document_keywords)
+
+        # Counter query keywords(TF)
+        query_keyword_counts = Counter(query_keywords)
+
+        # total documents
+        total_documents = len(documents)
+
+        # calculate all documents' keywords IDF
+        all_keywords = set()
+        for document_keywords in documents_keywords:
+            all_keywords.update(document_keywords)
+
+        keyword_idf = {}
+        for keyword in all_keywords:
+            # calculate include query keywords' documents
+            doc_count_containing_keyword = sum(1 for doc_keywords in documents_keywords if keyword in doc_keywords)
+            # IDF
+            keyword_idf[keyword] = math.log((1 + total_documents) / (1 + doc_count_containing_keyword)) + 1
+
+        query_tfidf = {}
+
+        for keyword, count in query_keyword_counts.items():
+            tf = count
+            idf = keyword_idf.get(keyword, 0)
+            query_tfidf[keyword] = tf * idf
+
+        # calculate all documents' TF-IDF
+        documents_tfidf = []
+        for document_keywords in documents_keywords:
+            document_keyword_counts = Counter(document_keywords)
+            document_tfidf = {}
+            for keyword, count in document_keyword_counts.items():
+                tf = count
+                idf = keyword_idf.get(keyword, 0)
+                document_tfidf[keyword] = tf * idf
+            documents_tfidf.append(document_tfidf)
+
+        def cosine_similarity(vec1, vec2):
+            intersection = set(vec1.keys()) & set(vec2.keys())
+            numerator = sum(vec1[x] * vec2[x] for x in intersection)
+
+            sum1 = sum(vec1[x] ** 2 for x in vec1.keys())
+            sum2 = sum(vec2[x] ** 2 for x in vec2.keys())
+            denominator = math.sqrt(sum1) * math.sqrt(sum2)
+
+            if not denominator:
+                return 0.0
+            else:
+                return float(numerator) / denominator
+
+        similarities = []
+        for document_tfidf in documents_tfidf:
+            similarity = cosine_similarity(query_tfidf, document_tfidf)
+            similarities.append(similarity)
+
+        for document, score in zip(documents, similarities):
+            # format document
+            document.metadata['score'] = score
+        documents = sorted(documents, key=lambda x: x.metadata['score'], reverse=True)
+        return documents[:top_k] if top_k else documents
+
+    def calculate_vector_score(self, all_documents: list[Document],
+                               top_k: int, score_threshold: float) -> list[Document]:
+        filter_documents = []
+        for document in all_documents:
+            if document.metadata['score'] >= score_threshold:
+                filter_documents.append(document)
+        if not filter_documents:
+            return []
+        filter_documents = sorted(filter_documents, key=lambda x: x.metadata['score'], reverse=True)
+        return filter_documents[:top_k] if top_k else filter_documents
+
+
+

api/core/tools/tool/dataset_retriever/dataset_multi_retriever_tool.py

@@ -7,7 +7,7 @@ from core.callback_handler.index_tool_callback_handler import DatasetIndexToolCa
 from core.model_manager import ModelManager
 from core.model_runtime.entities.model_entities import ModelType
 from core.rag.datasource.retrieval_service import RetrievalService
-from core.rag.rerank.rerank import RerankRunner
+from core.rag.rerank.rerank_model import RerankModelRunner
 from core.rag.retrieval.retrival_methods import RetrievalMethod
 from core.tools.tool.dataset_retriever.dataset_retriever_base_tool import DatasetRetrieverBaseTool
 from extensions.ext_database import db
@@ -72,7 +72,7 @@ class DatasetMultiRetrieverTool(DatasetRetrieverBaseTool):
             model=self.reranking_model_name
         )
 
-        rerank_runner = RerankRunner(rerank_model_instance)
+        rerank_runner = RerankModelRunner(rerank_model_instance)
         all_documents = rerank_runner.run(query, all_documents, self.score_threshold, self.top_k)
 
         for hit_callback in self.hit_callbacks:
@@ -180,7 +180,8 @@ class DatasetMultiRetrieverTool(DatasetRetrieverBaseTool):
                                                           score_threshold=retrieval_model['score_threshold']
                                                           if retrieval_model['score_threshold_enabled'] else None,
                                                           reranking_model=retrieval_model['reranking_model']
-                                                          if retrieval_model['reranking_enable'] else None
+                                                          if retrieval_model['reranking_enable'] else None,
+                                                          weights=retrieval_model.get('weights', None),
                                                           )
 
                     all_documents.extend(documents)

api/core/tools/tool/dataset_retriever/dataset_retriever_tool.py

@@ -78,7 +78,8 @@ class DatasetRetrieverTool(DatasetRetrieverBaseTool):
                                                       score_threshold=retrieval_model['score_threshold']
                                                       if retrieval_model['score_threshold_enabled'] else None,
                                                       reranking_model=retrieval_model['reranking_model']
-                                                      if retrieval_model['reranking_enable'] else None
+                                                      if retrieval_model['reranking_enable'] else None,
+                                                      weights=retrieval_model.get('weights', None),
                                                       )
             else:
                 documents = []

api/core/workflow/nodes/knowledge_retrieval/entities.py

@@ -13,13 +13,41 @@ class RerankingModelConfig(BaseModel):
     model: str
 
 
+class VectorSetting(BaseModel):
+    """
+    Vector Setting.
+    """
+    vector_weight: float
+    embedding_provider_name: str
+    embedding_model_name: str
+
+
+class KeywordSetting(BaseModel):
+    """
+    Keyword Setting.
+    """
+    keyword_weight: float
+
+
+class WeightedScoreConfig(BaseModel):
+    """
+    Weighted score Config.
+    """
+    weight_type: str
+    vector_setting: VectorSetting
+    keyword_setting: KeywordSetting
+
+
 class MultipleRetrievalConfig(BaseModel):
     """
     Multiple Retrieval Config.
     """
     top_k: int
     score_threshold: Optional[float] = None
+    reranking_mode: str = 'reranking_model'
+    reranking_enable: bool = True
     reranking_model: RerankingModelConfig
+    weights: WeightedScoreConfig
 
 
 class ModelConfig(BaseModel):

api/core/workflow/nodes/knowledge_retrieval/knowledge_retrieval_node.py

@@ -137,13 +137,38 @@ class KnowledgeRetrievalNode(BaseNode):
                     planning_strategy=planning_strategy
                 )
         elif node_data.retrieval_mode == DatasetRetrieveConfigEntity.RetrieveStrategy.MULTIPLE.value:
+            if node_data.multiple_retrieval_config.reranking_mode == 'reranking_model':
+                reranking_model = {
+                    'reranking_provider_name': node_data.multiple_retrieval_config.reranking_model['provider'],
+                    'reranking_model_name': node_data.multiple_retrieval_config.reranking_model['name']
+                }
+                weights = None
+            elif node_data.multiple_retrieval_config.reranking_mode == 'weighted_score':
+                reranking_model = None
+                weights = {
+                    'weight_type': node_data.multiple_retrieval_config.weights.weight_type,
+                    'vector_setting': {
+                        "vector_weight": node_data.multiple_retrieval_config.weights.vector_setting.vector_weight,
+                        "embedding_provider_name": node_data.multiple_retrieval_config.weights.vector_setting.embedding_provider_name,
+                        "embedding_model_name": node_data.multiple_retrieval_config.weights.vector_setting.embedding_model_name,
+                    },
+                    'keyword_setting': {
+                        "keyword_weight": node_data.multiple_retrieval_config.weights.keyword_setting.keyword_weight
+                    }
+                }
+            else:
+                reranking_model = None
+                weights = None
             all_documents = dataset_retrieval.multiple_retrieve(self.app_id, self.tenant_id, self.user_id,
                                                                 self.user_from.value,
                                                                 available_datasets, query,
                                                                 node_data.multiple_retrieval_config.top_k,
                                                                 node_data.multiple_retrieval_config.score_threshold,
-                                                                node_data.multiple_retrieval_config.reranking_model.provider,
-                                                                node_data.multiple_retrieval_config.reranking_model.model)
+                                                                node_data.multiple_retrieval_config.reranking_mode,
+                                                                reranking_model,
+                                                                weights,
+                                                                node_data.multiple_retrieval_config.reranking_enable,
+                                                                )
 
         context_list = []
         if all_documents:

api/core/workflow/workflow_entry.py

@@ -31,15 +31,18 @@ logger = logging.getLogger(__name__)
 
 
 class WorkflowEntry:
-    def run_workflow(self, workflow: Workflow,
-                     user_id: str,
-                     user_from: UserFrom,
-                     invoke_from: InvokeFrom,
-                     user_inputs: Mapping[str, Any],
-                     system_inputs: Mapping[SystemVariable, Any],
-                     callbacks: Sequence[BaseWorkflowCallback],
-                     call_depth: int = 0,
-                     variable_pool: Optional[VariablePool] = None) -> None:
+    def run_workflow(
+            self,
+            *,
+            workflow: Workflow,
+            user_id: str,
+            user_from: UserFrom,
+            invoke_from: InvokeFrom,
+            user_inputs: Mapping[str, Any],
+            system_inputs: Mapping[SystemVariable, Any],
+            callbacks: Sequence[WorkflowCallback],
+            call_depth: int = 0
+    ) -> None:
         """
         :param workflow: Workflow instance
         :param user_id: user id
@@ -66,12 +69,11 @@ class WorkflowEntry:
             raise ValueError('edges in workflow graph must be a list')
 
         # init variable pool
-        if not variable_pool:
-            variable_pool = VariablePool(
-                system_variables=system_inputs,
-                user_inputs=user_inputs,
-                environment_variables=workflow.environment_variables,
-            )
+        variable_pool = VariablePool(
+            system_variables=system_inputs,
+            user_inputs=user_inputs,
+            environment_variables=workflow.environment_variables,
+        )
 
         workflow_call_max_depth = dify_config.WORKFLOW_CALL_MAX_DEPTH
         if call_depth > workflow_call_max_depth:

api/fields/dataset_fields.py

@@ -18,10 +18,28 @@ reranking_model_fields = {
     'reranking_model_name': fields.String
 }
 
+keyword_setting_fields = {
+    'keyword_weight': fields.Float
+}
+
+vector_setting_fields = {
+    'vector_weight': fields.Float,
+    'embedding_model_name': fields.String,
+    'embedding_provider_name': fields.String,
+}
+
+weighted_score_fields = {
+    'weight_type': fields.String,
+    'keyword_setting': fields.Nested(keyword_setting_fields),
+    'vector_setting': fields.Nested(vector_setting_fields),
+}
+
 dataset_retrieval_model_fields = {
     'search_method': fields.String,
     'reranking_enable': fields.Boolean,
+    'reranking_mode': fields.String,
     'reranking_model': fields.Nested(reranking_model_fields),
+    'weights': fields.Nested(weighted_score_fields, allow_null=True),
     'top_k': fields.Integer,
     'score_threshold_enabled': fields.Boolean,
     'score_threshold': fields.Float

api/migrations/versions/53bf8af60645_update_model.py

@@ -0,0 +1,41 @@
+"""update model
+
+Revision ID: 53bf8af60645
+Revises: 8e5588e6412e
+Create Date: 2024-07-24 08:06:55.291031
+
+"""
+import sqlalchemy as sa
+from alembic import op
+
+import models as models
+
+# revision identifiers, used by Alembic.
+revision = '53bf8af60645'
+down_revision = '8e5588e6412e'
+branch_labels = None
+depends_on = None
+
+
+def upgrade():
+    # ### commands auto generated by Alembic - please adjust! ###
+    with op.batch_alter_table('embeddings', schema=None) as batch_op:
+        batch_op.alter_column('provider_name',
+               existing_type=sa.VARCHAR(length=40),
+               type_=sa.String(length=255),
+               existing_nullable=False,
+               existing_server_default=sa.text("''::character varying"))
+
+    # ### end Alembic commands ###
+
+
+def downgrade():
+    # ### commands auto generated by Alembic - please adjust! ###
+    with op.batch_alter_table('embeddings', schema=None) as batch_op:
+        batch_op.alter_column('provider_name',
+               existing_type=sa.String(length=255),
+               type_=sa.VARCHAR(length=40),
+               existing_nullable=False,
+               existing_server_default=sa.text("''::character varying"))
+
+    # ### end Alembic commands ###

api/models/dataset.py

@@ -640,7 +640,7 @@ class Embedding(db.Model):
     hash = db.Column(db.String(64), nullable=False)
     embedding = db.Column(db.LargeBinary, nullable=False)
     created_at = db.Column(db.DateTime, nullable=False, server_default=db.text('CURRENT_TIMESTAMP(0)'))
-    provider_name = db.Column(db.String(40), nullable=False,
+    provider_name = db.Column(db.String(255), nullable=False,
                               server_default=db.text("''::character varying"))
 
     def set_embedding(self, embedding_data: list[float]):

api/models/model.py

@@ -328,7 +328,9 @@ class AppModelConfig(db.Model):
                 return {'retrieval_model': 'single'}
             else:
                 return dataset_configs
-        return {'retrieval_model': 'single'}
+        return {
+                'retrieval_model': 'multiple',
+            }
 
     @property
     def file_upload_dict(self) -> dict:

api/pyproject.toml

@@ -163,7 +163,8 @@ redis = { version = "~5.0.3", extras = ["hiredis"] }
 replicate = "~0.22.0"
 resend = "~0.7.0"
 safetensors = "~0.4.3"
-sentry-sdk = { version = "~2.8.0", extras = ["flask"] }
+scikit-learn = "^1.5.1"
+sentry-sdk = { version = "~1.44.1", extras = ["flask"] }
 sqlalchemy = "~2.0.29"
 tencentcloud-sdk-python-hunyuan = "~3.0.1158"
 tiktoken = "~0.7.0"
@@ -175,7 +176,7 @@ werkzeug = "~3.0.1"
 xinference-client = "0.9.4"
 yarl = "~1.9.4"
 zhipuai = "1.0.7"
-
+rank-bm25 = "~0.2.2"
 ############################################################
 # Tool dependencies required by tool implementations
 ############################################################
@@ -200,7 +201,7 @@ cloudscraper = "1.2.71"
 ############################################################
 
 [tool.poetry.group.vdb.dependencies]
-chromadb = "~0.5.1"
+chromadb = "0.5.1"
 oracledb = "~2.2.1"
 pgvecto-rs = "0.1.4"
 pgvector = "0.2.5"

api/services/app_service.py

@@ -287,8 +287,12 @@ class AppService:
         """
         db.session.delete(app)
         db.session.commit()
+
         # Trigger asynchronous deletion of app and related data
-        remove_app_and_related_data_task.delay(app.id)
+        remove_app_and_related_data_task.delay(
+            tenant_id=app.tenant_id,
+            app_id=app.id
+        )
 
     def get_app_meta(self, app_model: App) -> dict:
         """

api/services/hit_testing_service.py

@@ -38,14 +38,16 @@ class HitTestingService:
         if not retrieval_model:
             retrieval_model = dataset.retrieval_model if dataset.retrieval_model else default_retrieval_model
 
-        all_documents = RetrievalService.retrieve(retrival_method=retrieval_model['search_method'],
+        all_documents = RetrievalService.retrieve(retrival_method=retrieval_model.get('search_method', 'semantic_search'),
                                                   dataset_id=dataset.id,
                                                   query=cls.escape_query_for_search(query),
-                                                  top_k=retrieval_model['top_k'],
+                                                  top_k=retrieval_model.get('top_k', 2),
                                                   score_threshold=retrieval_model['score_threshold']
                                                   if retrieval_model['score_threshold_enabled'] else None,
                                                   reranking_model=retrieval_model['reranking_model']
-                                                  if retrieval_model['reranking_enable'] else None
+                                                  if retrieval_model['reranking_enable'] else None,
+                                                  reranking_mode=retrieval_model.get('reranking_mode', None),
+                                                  weights=retrieval_model.get('weights', None),
                                                   )
 
         end = time.perf_counter()

api/tasks/remove_app_and_related_data_task.py

@@ -3,7 +3,6 @@ import time
 
 import click
 from celery import shared_task
-from sqlalchemy import select
 from sqlalchemy.exc import SQLAlchemyError
 
 from extensions.ext_database import db
@@ -25,6 +24,7 @@ from models.model import (
     RecommendedApp,
     Site,
     TagBinding,
+    TraceAppConfig,
 )
 from models.tools import WorkflowToolProvider
 from models.web import PinnedConversation, SavedMessage
@@ -32,122 +32,287 @@ from models.workflow import Workflow, WorkflowAppLog, WorkflowNodeExecution, Wor
 
 
 @shared_task(queue='app_deletion', bind=True, max_retries=3)
-def remove_app_and_related_data_task(self, app_id: str):
-    logging.info(click.style(f'Start deleting app and related data: {app_id}', fg='green'))
+def remove_app_and_related_data_task(self, tenant_id: str, app_id: str):
+    logging.info(click.style(f'Start deleting app and related data: {tenant_id}:{app_id}', fg='green'))
     start_at = time.perf_counter()
     try:
-        # Use a transaction to ensure all deletions succeed or none do
-        with db.session.begin_nested():
-            # Delete related data
-            _delete_app_model_configs(app_id)
-            _delete_app_site(app_id)
-            _delete_app_api_tokens(app_id)
-            _delete_installed_apps(app_id)
-            _delete_recommended_apps(app_id)
-            _delete_app_annotation_data(app_id)
-            _delete_app_dataset_joins(app_id)
-            _delete_app_workflows(app_id)
-            _delete_app_conversations(app_id)
-            _delete_app_messages(app_id)
-            _delete_workflow_tool_providers(app_id)
-            _delete_app_tag_bindings(app_id)
-            _delete_end_users(app_id)
-
-        # If we reach here, the transaction was successful
-        db.session.commit()
+        # Delete related data
+        _delete_app_model_configs(tenant_id, app_id)
+        _delete_app_site(tenant_id, app_id)
+        _delete_app_api_tokens(tenant_id, app_id)
+        _delete_installed_apps(tenant_id, app_id)
+        _delete_recommended_apps(tenant_id, app_id)
+        _delete_app_annotation_data(tenant_id, app_id)
+        _delete_app_dataset_joins(tenant_id, app_id)
+        _delete_app_workflows(tenant_id, app_id)
+        _delete_app_workflow_runs(tenant_id, app_id)
+        _delete_app_workflow_node_executions(tenant_id, app_id)
+        _delete_app_workflow_app_logs(tenant_id, app_id)
+        _delete_app_conversations(tenant_id, app_id)
+        _delete_app_messages(tenant_id, app_id)
+        _delete_workflow_tool_providers(tenant_id, app_id)
+        _delete_app_tag_bindings(tenant_id, app_id)
+        _delete_end_users(tenant_id, app_id)
+        _delete_trace_app_configs(tenant_id, app_id)
 
         end_at = time.perf_counter()
         logging.info(click.style(f'App and related data deleted: {app_id} latency: {end_at - start_at}', fg='green'))
-
     except SQLAlchemyError as e:
-        db.session.rollback()
         logging.exception(
             click.style(f"Database error occurred while deleting app {app_id} and related data", fg='red'))
         raise self.retry(exc=e, countdown=60)  # Retry after 60 seconds
-
     except Exception as e:
         logging.exception(click.style(f"Error occurred while deleting app {app_id} and related data", fg='red'))
         raise self.retry(exc=e, countdown=60)  # Retry after 60 seconds
 
 
-def _delete_app_model_configs(app_id: str):
-    db.session.query(AppModelConfig).filter(AppModelConfig.app_id == app_id).delete()
+def _delete_app_model_configs(tenant_id: str, app_id: str):
+    def del_model_config(model_config_id: str):
+        db.session.query(AppModelConfig).filter(AppModelConfig.id == model_config_id).delete(synchronize_session=False)
+
+    _delete_records(
+        """select id from app_model_configs where app_id=:app_id limit 1000""",
+        {"app_id": app_id},
+        del_model_config,
+        "app model config"
+    )
 
 
-def _delete_app_site(app_id: str):
-    db.session.query(Site).filter(Site.app_id == app_id).delete()
+def _delete_app_site(tenant_id: str, app_id: str):
+    def del_site(site_id: str):
+        db.session.query(Site).filter(Site.id == site_id).delete(synchronize_session=False)
+
+    _delete_records(
+        """select id from sites where app_id=:app_id limit 1000""",
+        {"app_id": app_id},
+        del_site,
+        "site"
+    )
 
 
-def _delete_app_api_tokens(app_id: str):
-    db.session.query(ApiToken).filter(ApiToken.app_id == app_id).delete()
+def _delete_app_api_tokens(tenant_id: str, app_id: str):
+    def del_api_token(api_token_id: str):
+        db.session.query(ApiToken).filter(ApiToken.id == api_token_id).delete(synchronize_session=False)
+
+    _delete_records(
+        """select id from api_tokens where app_id=:app_id limit 1000""",
+        {"app_id": app_id},
+        del_api_token,
+        "api token"
+    )
 
 
-def _delete_installed_apps(app_id: str):
-    db.session.query(InstalledApp).filter(InstalledApp.app_id == app_id).delete()
+def _delete_installed_apps(tenant_id: str, app_id: str):
+    def del_installed_app(installed_app_id: str):
+        db.session.query(InstalledApp).filter(InstalledApp.id == installed_app_id).delete(synchronize_session=False)
+
+    _delete_records(
+        """select id from installed_apps where tenant_id=:tenant_id and app_id=:app_id limit 1000""",
+        {"tenant_id": tenant_id, "app_id": app_id},
+        del_installed_app,
+        "installed app"
+    )
 
 
-def _delete_recommended_apps(app_id: str):
-    db.session.query(RecommendedApp).filter(RecommendedApp.app_id == app_id).delete()
+def _delete_recommended_apps(tenant_id: str, app_id: str):
+    def del_recommended_app(recommended_app_id: str):
+        db.session.query(RecommendedApp).filter(RecommendedApp.id == recommended_app_id).delete(
+            synchronize_session=False)
+
+    _delete_records(
+        """select id from recommended_apps where app_id=:app_id limit 1000""",
+        {"app_id": app_id},
+        del_recommended_app,
+        "recommended app"
+    )
 
 
-def _delete_app_annotation_data(app_id: str):
-    db.session.query(AppAnnotationHitHistory).filter(AppAnnotationHitHistory.app_id == app_id).delete()
-    db.session.query(AppAnnotationSetting).filter(AppAnnotationSetting.app_id == app_id).delete()
+def _delete_app_annotation_data(tenant_id: str, app_id: str):
+    def del_annotation_hit_history(annotation_hit_history_id: str):
+        db.session.query(AppAnnotationHitHistory).filter(
+            AppAnnotationHitHistory.id == annotation_hit_history_id).delete(synchronize_session=False)
+
+    _delete_records(
+        """select id from app_annotation_hit_histories where app_id=:app_id limit 1000""",
+        {"app_id": app_id},
+        del_annotation_hit_history,
+        "annotation hit history"
+    )
+
+    def del_annotation_setting(annotation_setting_id: str):
+        db.session.query(AppAnnotationSetting).filter(AppAnnotationSetting.id == annotation_setting_id).delete(
+            synchronize_session=False)
+
+    _delete_records(
+        """select id from app_annotation_settings where app_id=:app_id limit 1000""",
+        {"app_id": app_id},
+        del_annotation_setting,
+        "annotation setting"
+    )
 
 
-def _delete_app_dataset_joins(app_id: str):
-    db.session.query(AppDatasetJoin).filter(AppDatasetJoin.app_id == app_id).delete()
+def _delete_app_dataset_joins(tenant_id: str, app_id: str):
+    def del_dataset_join(dataset_join_id: str):
+        db.session.query(AppDatasetJoin).filter(AppDatasetJoin.id == dataset_join_id).delete(synchronize_session=False)
+
+    _delete_records(
+        """select id from app_dataset_joins where app_id=:app_id limit 1000""",
+        {"app_id": app_id},
+        del_dataset_join,
+        "dataset join"
+    )
 
 
-def _delete_app_workflows(app_id: str):
-    db.session.query(WorkflowRun).filter(
-        WorkflowRun.workflow_id.in_(
-            db.session.query(Workflow.id).filter(Workflow.app_id == app_id)
-        )
-    ).delete(synchronize_session=False)
-    db.session.query(WorkflowNodeExecution).filter(
-        WorkflowNodeExecution.workflow_id.in_(
-            db.session.query(Workflow.id).filter(Workflow.app_id == app_id)
-        )
-    ).delete(synchronize_session=False)
-    db.session.query(WorkflowAppLog).filter(WorkflowAppLog.app_id == app_id).delete(synchronize_session=False)
-    db.session.query(Workflow).filter(Workflow.app_id == app_id).delete(synchronize_session=False)
+def _delete_app_workflows(tenant_id: str, app_id: str):
+    def del_workflow(workflow_id: str):
+        db.session.query(Workflow).filter(Workflow.id == workflow_id).delete(synchronize_session=False)
+
+    _delete_records(
+        """select id from workflows where tenant_id=:tenant_id and app_id=:app_id limit 1000""",
+        {"tenant_id": tenant_id, "app_id": app_id},
+        del_workflow,
+        "workflow"
+    )
 
 
-def _delete_app_conversations(app_id: str):
-    db.session.query(PinnedConversation).filter(
-        PinnedConversation.conversation_id.in_(
-            db.session.query(Conversation.id).filter(Conversation.app_id == app_id)
-        )
-    ).delete(synchronize_session=False)
-    db.session.query(Conversation).filter(Conversation.app_id == app_id).delete()
+def _delete_app_workflow_runs(tenant_id: str, app_id: str):
+    def del_workflow_run(workflow_run_id: str):
+        db.session.query(WorkflowRun).filter(WorkflowRun.id == workflow_run_id).delete(synchronize_session=False)
+
+    _delete_records(
+        """select id from workflow_runs where tenant_id=:tenant_id and app_id=:app_id limit 1000""",
+        {"tenant_id": tenant_id, "app_id": app_id},
+        del_workflow_run,
+        "workflow run"
+    )
 
 
-def _delete_app_messages(app_id: str):
-    message_ids = select(Message.id).filter(Message.app_id == app_id).scalar_subquery()
-    db.session.query(MessageFeedback).filter(MessageFeedback.message_id.in_(message_ids)).delete(
-        synchronize_session=False)
-    db.session.query(MessageAnnotation).filter(MessageAnnotation.message_id.in_(message_ids)).delete(
-        synchronize_session=False)
-    db.session.query(MessageChain).filter(MessageChain.message_id.in_(message_ids)).delete(synchronize_session=False)
-    db.session.query(MessageAgentThought).filter(MessageAgentThought.message_id.in_(message_ids)).delete(
-        synchronize_session=False)
-    db.session.query(MessageFile).filter(MessageFile.message_id.in_(message_ids)).delete(synchronize_session=False)
-    db.session.query(SavedMessage).filter(SavedMessage.message_id.in_(message_ids)).delete(synchronize_session=False)
-    db.session.query(Message).filter(Message.app_id == app_id).delete(synchronize_session=False)
+def _delete_app_workflow_node_executions(tenant_id: str, app_id: str):
+    def del_workflow_node_execution(workflow_node_execution_id: str):
+        db.session.query(WorkflowNodeExecution).filter(
+            WorkflowNodeExecution.id == workflow_node_execution_id).delete(synchronize_session=False)
+
+    _delete_records(
+        """select id from workflow_node_executions where tenant_id=:tenant_id and app_id=:app_id limit 1000""",
+        {"tenant_id": tenant_id, "app_id": app_id},
+        del_workflow_node_execution,
+        "workflow node execution"
+    )
 
 
-def _delete_workflow_tool_providers(app_id: str):
-    db.session.query(WorkflowToolProvider).filter(
-        WorkflowToolProvider.app_id == app_id
-    ).delete(synchronize_session=False)
+def _delete_app_workflow_app_logs(tenant_id: str, app_id: str):
+    def del_workflow_app_log(workflow_app_log_id: str):
+        db.session.query(WorkflowAppLog).filter(WorkflowAppLog.id == workflow_app_log_id).delete(synchronize_session=False)
+
+    _delete_records(
+        """select id from workflow_app_logs where tenant_id=:tenant_id and app_id=:app_id limit 1000""",
+        {"tenant_id": tenant_id, "app_id": app_id},
+        del_workflow_app_log,
+        "workflow app log"
+    )
 
 
-def _delete_app_tag_bindings(app_id: str):
-    db.session.query(TagBinding).filter(
-        TagBinding.target_id == app_id
-    ).delete(synchronize_session=False)
+def _delete_app_conversations(tenant_id: str, app_id: str):
+    def del_conversation(conversation_id: str):
+        db.session.query(PinnedConversation).filter(PinnedConversation.conversation_id == conversation_id).delete(
+            synchronize_session=False)
+        db.session.query(Conversation).filter(Conversation.id == conversation_id).delete(synchronize_session=False)
+
+    _delete_records(
+        """select id from conversations where app_id=:app_id limit 1000""",
+        {"app_id": app_id},
+        del_conversation,
+        "conversation"
+    )
 
 
-def _delete_end_users(app_id: str):
-    db.session.query(EndUser).filter(EndUser.app_id == app_id).delete()
+def _delete_app_messages(tenant_id: str, app_id: str):
+    def del_message(message_id: str):
+        db.session.query(MessageFeedback).filter(MessageFeedback.message_id == message_id).delete(
+            synchronize_session=False)
+        db.session.query(MessageAnnotation).filter(MessageAnnotation.message_id == message_id).delete(
+            synchronize_session=False)
+        db.session.query(MessageChain).filter(MessageChain.message_id == message_id).delete(
+            synchronize_session=False)
+        db.session.query(MessageAgentThought).filter(MessageAgentThought.message_id == message_id).delete(
+            synchronize_session=False)
+        db.session.query(MessageFile).filter(MessageFile.message_id == message_id).delete(synchronize_session=False)
+        db.session.query(SavedMessage).filter(SavedMessage.message_id == message_id).delete(
+            synchronize_session=False)
+        db.session.query(Message).filter(Message.id == message_id).delete()
+
+    _delete_records(
+        """select id from messages where app_id=:app_id limit 1000""",
+        {"app_id": app_id},
+        del_message,
+        "message"
+    )
+
+
+def _delete_workflow_tool_providers(tenant_id: str, app_id: str):
+    def del_tool_provider(tool_provider_id: str):
+        db.session.query(WorkflowToolProvider).filter(WorkflowToolProvider.id == tool_provider_id).delete(
+            synchronize_session=False)
+
+    _delete_records(
+        """select id from tool_workflow_providers where tenant_id=:tenant_id and app_id=:app_id limit 1000""",
+        {"tenant_id": tenant_id, "app_id": app_id},
+        del_tool_provider,
+        "tool workflow provider"
+    )
+
+
+def _delete_app_tag_bindings(tenant_id: str, app_id: str):
+    def del_tag_binding(tag_binding_id: str):
+        db.session.query(TagBinding).filter(TagBinding.id == tag_binding_id).delete(synchronize_session=False)
+
+    _delete_records(
+        """select id from tag_bindings where tenant_id=:tenant_id and target_id=:app_id limit 1000""",
+        {"tenant_id": tenant_id, "app_id": app_id},
+        del_tag_binding,
+        "tag binding"
+    )
+
+
+def _delete_end_users(tenant_id: str, app_id: str):
+    def del_end_user(end_user_id: str):
+        db.session.query(EndUser).filter(EndUser.id == end_user_id).delete(synchronize_session=False)
+
+    _delete_records(
+        """select id from end_users where tenant_id=:tenant_id and app_id=:app_id limit 1000""",
+        {"tenant_id": tenant_id, "app_id": app_id},
+        del_end_user,
+        "end user"
+    )
+
+
+def _delete_trace_app_configs(tenant_id: str, app_id: str):
+    def del_trace_app_config(trace_app_config_id: str):
+        db.session.query(TraceAppConfig).filter(TraceAppConfig.id == trace_app_config_id).delete(
+            synchronize_session=False)
+
+    _delete_records(
+        """select id from trace_app_config where app_id=:app_id limit 1000""",
+        {"app_id": app_id},
+        del_trace_app_config,
+        "trace app config"
+    )
+
+
+def _delete_records(query_sql: str, params: dict, delete_func: callable, name: str) -> None:
+    while True:
+        with db.engine.begin() as conn:
+            rs = conn.execute(db.text(query_sql), params)
+            if rs.rowcount == 0:
+                break
+
+            for i in rs:
+                record_id = str(i.id)
+                try:
+                    delete_func(record_id)
+                    db.session.commit()
+                    logging.info(click.style(f"Deleted {name} {record_id}", fg='green'))
+                except Exception:
+                    logging.exception(f"Error occurred while deleting {name} {record_id}")
+                    continue
+            rs.close()

api/tests/unit_tests/app/test_variables.py

@@ -2,14 +2,16 @@ import pytest
 from pydantic import ValidationError
 
 from core.app.segments import (
+    ArrayVariable,
     FloatVariable,
     IntegerVariable,
+    NoneVariable,
+    ObjectVariable,
     SecretVariable,
     SegmentType,
     StringVariable,
     factory,
 )
-from core.app.segments.variables import ArrayVariable, ObjectVariable
 
 
 def test_string_variable():
@@ -134,3 +136,13 @@ def test_variable_to_object():
     assert var.to_object() == 3.14
     var = SecretVariable(name='secret', value='secret_value')
     assert var.to_object() == 'secret_value'
+
+
+def test_build_a_object_variable_with_none_value():
+    var = factory.build_anonymous_variable(
+        {
+            'key1': None,
+        }
+    )
+    assert isinstance(var, ObjectVariable)
+    assert isinstance(var.value['key1'], NoneVariable)

dev/pytest/pytest_vdb.sh

@@ -3,7 +3,6 @@ set -x
 
 pytest api/tests/integration_tests/vdb/chroma \
   api/tests/integration_tests/vdb/milvus \
-  api/tests/integration_tests/vdb/myscale \
   api/tests/integration_tests/vdb/pgvecto_rs \
   api/tests/integration_tests/vdb/pgvector \
   api/tests/integration_tests/vdb/qdrant \

docker-legacy/docker-compose.yaml

@@ -2,7 +2,7 @@ version: '3'
 services:
   # API service
   api:
-    image: langgenius/dify-api:0.6.14
+    image: langgenius/dify-api:0.6.15
     restart: always
     environment:
       # Startup mode, 'api' starts the API server.
@@ -224,7 +224,7 @@ services:
   # worker service
   # The Celery worker for processing the queue.
   worker:
-    image: langgenius/dify-api:0.6.14
+    image: langgenius/dify-api:0.6.15
     restart: always
     environment:
       CONSOLE_WEB_URL: ''
@@ -390,7 +390,7 @@ services:
 
   # Frontend web application.
   web:
-    image: langgenius/dify-web:0.6.14
+    image: langgenius/dify-web:0.6.15
     restart: always
     environment:
       # The base URL of console application api server, refers to the Console base URL of WEB service if console domain is

docker/docker-compose.middleware.yaml

@@ -48,7 +48,7 @@ services:
 
   # ssrf_proxy server
   # for more information, please refer to
-  # https://docs.dify.ai/getting-started/install-self-hosted/install-faq#id-16.-why-is-ssrf_proxy-needed
+  # https://docs.dify.ai/learn-more/faq/self-host-faq#id-18.-why-is-ssrf_proxy-needed
   ssrf_proxy:
     image: ubuntu/squid:latest
     restart: always

docker/docker-compose.yaml

@@ -179,7 +179,7 @@ x-shared-env: &shared-api-worker-env
 services:
   # API service
   api:
-    image: langgenius/dify-api:0.6.14
+    image: langgenius/dify-api:0.6.15
     restart: always
     environment:
       # Use the shared environment variables.
@@ -199,7 +199,7 @@ services:
   # worker service
   # The Celery worker for processing the queue.
   worker:
-    image: langgenius/dify-api:0.6.14
+    image: langgenius/dify-api:0.6.15
     restart: always
     environment:
       # Use the shared environment variables.
@@ -218,7 +218,7 @@ services:
 
   # Frontend web application.
   web:
-    image: langgenius/dify-web:0.6.14
+    image: langgenius/dify-web:0.6.15
     restart: always
     environment:
       CONSOLE_API_URL: ${CONSOLE_API_URL:-}

web/app/components/app-sidebar/app-info.tsx

@@ -434,7 +434,7 @@ const AppInfo = ({ expand }: IAppInfoProps) => {
         {showImportDSLModal && (
           <UpdateDSLModal
             onCancel={() => setShowImportDSLModal(false)}
-            onBackup={onExport}
+            onBackup={exportCheck}
           />
         )}
         {secretEnvList.length > 0 && (

web/app/components/app/configuration/config-prompt/advanced-prompt-input.tsx

@@ -43,6 +43,7 @@ type Props = {
   promptVariables: PromptVariable[]
   isContextMissing: boolean
   onHideContextMissingTip: () => void
+  noResize?: boolean
 }
 
 const AdvancedPromptInput: FC<Props> = ({
@@ -56,6 +57,7 @@ const AdvancedPromptInput: FC<Props> = ({
   promptVariables,
   isContextMissing,
   onHideContextMissingTip,
+  noResize,
 }) => {
   const { t } = useTranslation()
   const { eventEmitter } = useEventEmitterContextContext()
@@ -207,6 +209,7 @@ const AdvancedPromptInput: FC<Props> = ({
               <div className="h-[18px] leading-[18px] px-1 rounded-md bg-gray-100 text-xs text-gray-500">{value.length}</div>
             </div>
           )}
+          hideResize={noResize}
         >
           <PromptEditor
             className='min-h-[84px]'

web/app/components/app/configuration/config-prompt/index.tsx

@@ -19,6 +19,10 @@ export type IPromptProps = {
   promptTemplate: string
   promptVariables: PromptVariable[]
   readonly?: boolean
+  noTitle?: boolean
+  gradientBorder?: boolean
+  editorHeight?: number
+  noResize?: boolean
   onChange?: (prompt: string, promptVariables: PromptVariable[]) => void
 }
 
@@ -26,7 +30,11 @@ const Prompt: FC<IPromptProps> = ({
   mode,
   promptTemplate,
   promptVariables,
+  noTitle,
+  gradientBorder,
   readonly = false,
+  editorHeight,
+  noResize,
   onChange,
 }) => {
   const { t } = useTranslation()
@@ -99,6 +107,10 @@ const Prompt: FC<IPromptProps> = ({
         promptVariables={promptVariables}
         readonly={readonly}
         onChange={onChange}
+        noTitle={noTitle}
+        gradientBorder={gradientBorder}
+        editorHeight={editorHeight}
+        noResize={noResize}
       />
     )
   }
@@ -121,6 +133,7 @@ const Prompt: FC<IPromptProps> = ({
                 promptVariables={promptVariables}
                 isContextMissing={isContextMissing && !isHideContextMissTip}
                 onHideContextMissingTip={() => setIsHideContextMissTip(true)}
+                noResize={noResize}
               />
             ))
           )
@@ -136,6 +149,7 @@ const Prompt: FC<IPromptProps> = ({
               promptVariables={promptVariables}
               isContextMissing={isContextMissing && !isHideContextMissTip}
               onHideContextMissingTip={() => setIsHideContextMissTip(true)}
+              noResize={noResize}
             />
           )
         }

web/app/components/app/configuration/config-prompt/simple-prompt-input.tsx

@@ -14,6 +14,7 @@ import PromptEditorHeightResizeWrap from './prompt-editor-height-resize-wrap'
 import cn from '@/utils/classnames'
 import { type PromptVariable } from '@/models/debug'
 import Tooltip from '@/app/components/base/tooltip'
+import type { CompletionParams } from '@/types/app'
 import { AppType } from '@/types/app'
 import { getNewVar, getVars } from '@/utils/var'
 import AutomaticBtn from '@/app/components/app/configuration/config/automatic/automatic-btn'
@@ -28,6 +29,7 @@ import { useEventEmitterContextContext } from '@/context/event-emitter'
 import { ADD_EXTERNAL_DATA_TOOL } from '@/app/components/app/configuration/config-var'
 import { INSERT_VARIABLE_VALUE_BLOCK_COMMAND } from '@/app/components/base/prompt-editor/plugins/variable-block'
 import { PROMPT_EDITOR_UPDATE_VALUE_BY_EVENT_EMITTER } from '@/app/components/base/prompt-editor/plugins/update-block'
+import useBreakpoints, { MediaType } from '@/hooks/use-breakpoints'
 
 export type ISimplePromptInput = {
   mode: AppType
@@ -35,6 +37,10 @@ export type ISimplePromptInput = {
   promptVariables: PromptVariable[]
   readonly?: boolean
   onChange?: (promp: string, promptVariables: PromptVariable[]) => void
+  noTitle?: boolean
+  gradientBorder?: boolean
+  editorHeight?: number
+  noResize?: boolean
 }
 
 const Prompt: FC<ISimplePromptInput> = ({
@@ -43,11 +49,19 @@ const Prompt: FC<ISimplePromptInput> = ({
   promptVariables,
   readonly = false,
   onChange,
+  noTitle,
+  gradientBorder,
+  editorHeight: initEditorHeight,
+  noResize,
 }) => {
   const { t } = useTranslation()
+  const media = useBreakpoints()
+  const isMobile = media === MediaType.mobile
+
   const { eventEmitter } = useEventEmitterContextContext()
   const {
     modelConfig,
+    completionParams,
     dataSets,
     setModelConfig,
     setPrevPromptConfig,
@@ -116,6 +130,11 @@ const Prompt: FC<ISimplePromptInput> = ({
 
   const [showAutomatic, { setTrue: showAutomaticTrue, setFalse: showAutomaticFalse }] = useBoolean(false)
   const handleAutomaticRes = (res: AutomaticRes) => {
+    // put eventEmitter in first place to prevent overwrite the configs.prompt_variables.But another problem is that prompt won't hight the prompt_variables.
+    eventEmitter?.emit({
+      type: PROMPT_EDITOR_UPDATE_VALUE_BY_EVENT_EMITTER,
+      payload: res.prompt,
+    } as any)
     const newModelConfig = produce(modelConfig, (draft) => {
       draft.configs.prompt_template = res.prompt
       draft.configs.prompt_variables = res.variables.map(key => ({ key, name: key, type: 'string', required: true }))
@@ -125,41 +144,41 @@ const Prompt: FC<ISimplePromptInput> = ({
     if (mode !== AppType.completion)
       setIntroduction(res.opening_statement)
     showAutomaticFalse()
-    eventEmitter?.emit({
-      type: PROMPT_EDITOR_UPDATE_VALUE_BY_EVENT_EMITTER,
-      payload: res.prompt,
-    } as any)
   }
-  const minHeight = 228
+  const minHeight = initEditorHeight || 228
   const [editorHeight, setEditorHeight] = useState(minHeight)
 
   return (
-    <div className={cn(!readonly ? `${s.gradientBorder}` : 'bg-gray-50', ' relative shadow-md')}>
+    <div className={cn((!readonly || gradientBorder) ? `${s.gradientBorder}` : 'bg-gray-50', ' relative shadow-md')}>
       <div className='rounded-xl bg-[#EEF4FF]'>
-        <div className="flex justify-between items-center h-11 px-3">
-          <div className="flex items-center space-x-1">
-            <div className='h2'>{mode !== AppType.completion ? t('appDebug.chatSubTitle') : t('appDebug.completionSubTitle')}</div>
-            {!readonly && (
-              <Tooltip
-                htmlContent={<div className='w-[180px]'>
-                  {t('appDebug.promptTip')}
-                </div>}
-                selector='config-prompt-tooltip'>
-                <RiQuestionLine className='w-[14px] h-[14px] text-indigo-400' />
-              </Tooltip>
-            )}
+        {!noTitle && (
+          <div className="flex justify-between items-center h-11 pl-3 pr-6">
+            <div className="flex items-center space-x-1">
+              <div className='h2'>{mode !== AppType.completion ? t('appDebug.chatSubTitle') : t('appDebug.completionSubTitle')}</div>
+              {!readonly && (
+                <Tooltip
+                  htmlContent={<div className='w-[180px]'>
+                    {t('appDebug.promptTip')}
+                  </div>}
+                  selector='config-prompt-tooltip'>
+                  <RiQuestionLine className='w-[14px] h-[14px] text-indigo-400' />
+                </Tooltip>
+              )}
+            </div>
+            <div className='flex items-center'>
+              {!isAgent && !readonly && !isMobile && (
+                <AutomaticBtn onClick={showAutomaticTrue} />
+              )}
+            </div>
           </div>
-          <div className='flex items-center'>
-            {!isAgent && !readonly && (
-              <AutomaticBtn onClick={showAutomaticTrue} />
-            )}
-          </div>
-        </div>
+        )}
+
         <PromptEditorHeightResizeWrap
           className='px-4 pt-2 min-h-[228px] bg-white rounded-t-xl text-sm text-gray-700'
           height={editorHeight}
           minHeight={minHeight}
           onHeightChange={setEditorHeight}
+          hideResize={noResize}
           footer={(
             <div className='pl-4 pb-2 flex bg-white rounded-b-xl'>
               <div className="h-[18px] leading-[18px] px-1 rounded-md bg-gray-100 text-xs text-gray-500">{promptTemplate.length}</div>
@@ -216,6 +235,7 @@ const Prompt: FC<ISimplePromptInput> = ({
             onBlur={() => {
               handleChange(promptTemplate, getVars(promptTemplate))
             }}
+            editable={!readonly}
           />
         </PromptEditorHeightResizeWrap>
       </div>
@@ -232,6 +252,14 @@ const Prompt: FC<ISimplePromptInput> = ({
       {showAutomatic && (
         <GetAutomaticResModal
           mode={mode as AppType}
+          model={
+            {
+              provider: modelConfig.provider,
+              name: modelConfig.model_id,
+              mode: modelConfig.mode,
+              completion_params: completionParams as CompletionParams,
+            }
+          }
           isShow={showAutomatic}
           onClose={showAutomaticFalse}
           onFinished={handleAutomaticRes}

web/app/components/app/configuration/config/automatic/automatic-btn.tsx

@@ -2,29 +2,21 @@
 import type { FC } from 'react'
 import React from 'react'
 import { useTranslation } from 'react-i18next'
+import { Generator } from '@/app/components/base/icons/src/vender/other'
 
 export type IAutomaticBtnProps = {
   onClick: () => void
 }
-
-const leftIcon = (
-  <svg width="14" height="14" viewBox="0 0 14 14" fill="none" xmlns="http://www.w3.org/2000/svg">
-    <path d="M4.31346 0.905711C4.21464 0.708087 4.01266 0.583252 3.79171 0.583252C3.57076 0.583252 3.36877 0.708087 3.26996 0.905711L2.81236 1.82091C2.64757 2.15048 2.59736 2.24532 2.53635 2.32447C2.47515 2.40386 2.40398 2.47503 2.32459 2.53623C2.24544 2.59724 2.1506 2.64745 1.82103 2.81224L0.905833 3.26984C0.708209 3.36865 0.583374 3.57064 0.583374 3.79159C0.583374 4.01254 0.708209 4.21452 0.905833 4.31333L1.82103 4.77094C2.1506 4.93572 2.24544 4.98593 2.32459 5.04694C2.40398 5.10814 2.47515 5.17931 2.53635 5.2587C2.59736 5.33785 2.64758 5.43269 2.81236 5.76226L3.26996 6.67746C3.36877 6.87508 3.57076 6.99992 3.79171 6.99992C4.01266 6.99992 4.21465 6.87508 4.31346 6.67746L4.77106 5.76226C4.93584 5.43269 4.98605 5.33786 5.04707 5.2587C5.10826 5.17931 5.17943 5.10814 5.25883 5.04694C5.33798 4.98593 5.43282 4.93572 5.76238 4.77094L6.67758 4.31333C6.87521 4.21452 7.00004 4.01254 7.00004 3.79159C7.00004 3.57064 6.87521 3.36865 6.67758 3.26984L5.76238 2.81224C5.43282 2.64745 5.33798 2.59724 5.25883 2.53623C5.17943 2.47503 5.10826 2.40386 5.04707 2.32447C4.98605 2.24532 4.93584 2.15048 4.77106 1.82091L4.31346 0.905711Z" fill="#444CE7" />
-    <path d="M11.375 1.74992C11.375 1.42775 11.1139 1.16659 10.7917 1.16659C10.4695 1.16659 10.2084 1.42775 10.2084 1.74992V2.62492H9.33337C9.01121 2.62492 8.75004 2.88609 8.75004 3.20825C8.75004 3.53042 9.01121 3.79159 9.33337 3.79159H10.2084V4.66659C10.2084 4.98875 10.4695 5.24992 10.7917 5.24992C11.1139 5.24992 11.375 4.98875 11.375 4.66659V3.79159H12.25C12.5722 3.79159 12.8334 3.53042 12.8334 3.20825C12.8334 2.88609 12.5722 2.62492 12.25 2.62492H11.375V1.74992Z" fill="#444CE7" />
-    <path d="M3.79171 9.33325C3.79171 9.01109 3.53054 8.74992 3.20837 8.74992C2.88621 8.74992 2.62504 9.01109 2.62504 9.33325V10.2083H1.75004C1.42787 10.2083 1.16671 10.4694 1.16671 10.7916C1.16671 11.1138 1.42787 11.3749 1.75004 11.3749H2.62504V12.2499C2.62504 12.5721 2.88621 12.8333 3.20837 12.8333C3.53054 12.8333 3.79171 12.5721 3.79171 12.2499V11.3749H4.66671C4.98887 11.3749 5.25004 11.1138 5.25004 10.7916C5.25004 10.4694 4.98887 10.2083 4.66671 10.2083H3.79171V9.33325Z" fill="#444CE7" />
-    <path d="M10.4385 6.73904C10.3396 6.54142 10.1377 6.41659 9.91671 6.41659C9.69576 6.41659 9.49377 6.54142 9.39496 6.73904L8.84014 7.84869C8.67535 8.17826 8.62514 8.27309 8.56413 8.35225C8.50293 8.43164 8.43176 8.50281 8.35237 8.56401C8.27322 8.62502 8.17838 8.67523 7.84881 8.84001L6.73917 9.39484C6.54154 9.49365 6.41671 9.69564 6.41671 9.91659C6.41671 10.1375 6.54154 10.3395 6.73917 10.4383L7.84881 10.9932C8.17838 11.1579 8.27322 11.2082 8.35237 11.2692C8.43176 11.3304 8.50293 11.4015 8.56413 11.4809C8.62514 11.5601 8.67535 11.6549 8.84014 11.9845L9.39496 13.0941C9.49377 13.2918 9.69576 13.4166 9.91671 13.4166C10.1377 13.4166 10.3396 13.2918 10.4385 13.0941L10.9933 11.9845C11.1581 11.6549 11.2083 11.5601 11.2693 11.4809C11.3305 11.4015 11.4017 11.3304 11.481 11.2692C11.5602 11.2082 11.655 11.1579 11.9846 10.9932L13.0942 10.4383C13.2919 10.3395 13.4167 10.1375 13.4167 9.91659C13.4167 9.69564 13.2919 9.49365 13.0942 9.39484L11.9846 8.84001C11.655 8.67523 11.5602 8.62502 11.481 8.56401C11.4017 8.50281 11.3305 8.43164 11.2693 8.35225C11.2083 8.27309 11.1581 8.17826 10.9933 7.84869L10.4385 6.73904Z" fill="#444CE7" />
-  </svg>
-)
 const AutomaticBtn: FC<IAutomaticBtnProps> = ({
   onClick,
 }) => {
   const { t } = useTranslation()
 
   return (
-    <div className='flex px-3 space-x-2 items-center !h-8 cursor-pointer'
+    <div className='flex space-x-1 items-center !h-8 cursor-pointer'
       onClick={onClick}
     >
-      {leftIcon}
+      <Generator className='w-3.5 h-3.5 text-indigo-600' />
       <span className='text-xs font-semibold text-indigo-600'>{t('appDebug.operation.automatic')}</span>
     </div>
   )

web/app/components/app/configuration/config/automatic/get-automatic-res.tsx

@@ -1,70 +1,126 @@
 'use client'
 import type { FC } from 'react'
-import React from 'react'
+import React, { useCallback } from 'react'
 import { useTranslation } from 'react-i18next'
 import { useBoolean } from 'ahooks'
+import {
+  RiDatabase2Line,
+  RiFileExcel2Line,
+  RiGitCommitLine,
+  RiNewspaperLine,
+  RiPresentationLine,
+  RiRoadMapLine,
+  RiTerminalBoxLine,
+  RiTranslate,
+  RiUser2Line,
+} from '@remixicon/react'
+import cn from 'classnames'
+import s from './style.module.css'
 import Modal from '@/app/components/base/modal'
 import Button from '@/app/components/base/button'
 import Toast from '@/app/components/base/toast'
 import { generateRule } from '@/service/debug'
 import ConfigPrompt from '@/app/components/app/configuration/config-prompt'
+import type { Model } from '@/types/app'
 import { AppType } from '@/types/app'
 import ConfigVar from '@/app/components/app/configuration/config-var'
 import OpeningStatement from '@/app/components/app/configuration/features/chat-group/opening-statement'
 import GroupName from '@/app/components/app/configuration/base/group-name'
 import Loading from '@/app/components/base/loading'
 import Confirm from '@/app/components/base/confirm'
+
 // type
 import type { AutomaticRes } from '@/service/debug'
-import useBreakpoints, { MediaType } from '@/hooks/use-breakpoints'
-
-const noDataIcon = (
-  <svg width="56" height="56" viewBox="0 0 56 56" fill="none" xmlns="http://www.w3.org/2000/svg">
-    <path d="M10.4998 51.3333V39.6666M10.4998 16.3333V4.66663M4.6665 10.5H16.3332M4.6665 45.5H16.3332M30.3332 6.99996L26.2868 17.5206C25.6287 19.2315 25.2997 20.0869 24.7881 20.8065C24.3346 21.4442 23.7774 22.0014 23.1397 22.4549C22.4202 22.9665 21.5647 23.2955 19.8538 23.9535L9.33317 28L19.8539 32.0464C21.5647 32.7044 22.4202 33.0334 23.1397 33.5451C23.7774 33.9985 24.3346 34.5557 24.7881 35.1934C25.2997 35.913 25.6287 36.7684 26.2868 38.4793L30.3332 49L34.3796 38.4793C35.0376 36.7684 35.3666 35.913 35.8783 35.1934C36.3317 34.5557 36.8889 33.9985 37.5266 33.5451C38.2462 33.0334 39.1016 32.7044 40.8125 32.0464L51.3332 28L40.8125 23.9535C39.1016 23.2955 38.2462 22.9665 37.5266 22.4549C36.8889 22.0014 36.3317 21.4442 35.8783 20.8065C35.3666 20.0869 35.0376 19.2315 34.3796 17.5206L30.3332 6.99996Z" stroke="#EAECF0" strokeWidth="3" strokeLinecap="round" strokeLinejoin="round" />
-  </svg>
-)
+import { Generator } from '@/app/components/base/icons/src/vender/other'
 
 export type IGetAutomaticResProps = {
   mode: AppType
+  model: Model
   isShow: boolean
   onClose: () => void
   onFinished: (res: AutomaticRes) => void
+  isInLLMNode?: boolean
 }
 
-const genIcon = (
-  <svg width="16" height="16" viewBox="0 0 16 16" fill="none" xmlns="http://www.w3.org/2000/svg">
-    <path d="M3.6665 1.33332C3.6665 0.965133 3.36803 0.666656 2.99984 0.666656C2.63165 0.666656 2.33317 0.965133 2.33317 1.33332V2.33332H1.33317C0.964981 2.33332 0.666504 2.6318 0.666504 2.99999C0.666504 3.36818 0.964981 3.66666 1.33317 3.66666H2.33317V4.66666C2.33317 5.03485 2.63165 5.33332 2.99984 5.33332C3.36803 5.33332 3.6665 5.03485 3.6665 4.66666V3.66666H4.6665C5.03469 3.66666 5.33317 3.36818 5.33317 2.99999C5.33317 2.6318 5.03469 2.33332 4.6665 2.33332H3.6665V1.33332Z" fill="white" />
-    <path d="M3.6665 11.3333C3.6665 10.9651 3.36803 10.6667 2.99984 10.6667C2.63165 10.6667 2.33317 10.9651 2.33317 11.3333V12.3333H1.33317C0.964981 12.3333 0.666504 12.6318 0.666504 13C0.666504 13.3682 0.964981 13.6667 1.33317 13.6667H2.33317V14.6667C2.33317 15.0348 2.63165 15.3333 2.99984 15.3333C3.36803 15.3333 3.6665 15.0348 3.6665 14.6667V13.6667H4.6665C5.03469 13.6667 5.33317 13.3682 5.33317 13C5.33317 12.6318 5.03469 12.3333 4.6665 12.3333H3.6665V11.3333Z" fill="white" />
-    <path d="M9.28873 1.76067C9.18971 1.50321 8.94235 1.33332 8.6665 1.33332C8.39066 1.33332 8.1433 1.50321 8.04427 1.76067L6.88815 4.76658C6.68789 5.28727 6.62495 5.43732 6.53887 5.55838C6.4525 5.67986 6.34637 5.78599 6.2249 5.87236C6.10384 5.95844 5.95379 6.02137 5.43309 6.22164L2.42718 7.37776C2.16972 7.47678 1.99984 7.72414 1.99984 7.99999C1.99984 8.27584 2.16972 8.5232 2.42718 8.62222L5.43309 9.77834C5.95379 9.97861 6.10384 10.0415 6.2249 10.1276C6.34637 10.214 6.4525 10.3201 6.53887 10.4416C6.62495 10.5627 6.68789 10.7127 6.88816 11.2334L8.04427 14.2393C8.1433 14.4968 8.39066 14.6667 8.6665 14.6667C8.94235 14.6667 9.18971 14.4968 9.28873 14.2393L10.4449 11.2334C10.6451 10.7127 10.7081 10.5627 10.7941 10.4416C10.8805 10.3201 10.9866 10.214 11.1081 10.1276C11.2292 10.0415 11.3792 9.97861 11.8999 9.77834L14.9058 8.62222C15.1633 8.5232 15.3332 8.27584 15.3332 7.99999C15.3332 7.72414 15.1633 7.47678 14.9058 7.37776L11.8999 6.22164C11.3792 6.02137 11.2292 5.95844 11.1081 5.87236C10.9866 5.78599 10.8805 5.67986 10.7941 5.55838C10.7081 5.43732 10.6451 5.28727 10.4449 4.76658L9.28873 1.76067Z" fill="white" />
-  </svg>
-)
+const TryLabel: FC<{
+  Icon: any
+  text: string
+  onClick: () => void
+}> = ({ Icon, text, onClick }) => {
+  return (
+    <div
+      className='mt-2 mr-1 shrink-0 flex h-7 items-center px-2 bg-gray-100 rounded-lg cursor-pointer'
+      onClick={onClick}
+    >
+      <Icon className='w-4 h-4 text-gray-500'></Icon>
+      <div className='ml-1 text-xs font-medium text-gray-700'>{text}</div>
+    </div>
+  )
+}
 
 const GetAutomaticRes: FC<IGetAutomaticResProps> = ({
   mode,
+  model,
   isShow,
   onClose,
-  // appId,
+  isInLLMNode,
   onFinished,
 }) => {
   const { t } = useTranslation()
 
-  const media = useBreakpoints()
-  const isMobile = media === MediaType.mobile
+  const tryList = [
+    {
+      icon: RiTerminalBoxLine,
+      key: 'pythonDebugger',
+    },
+    {
+      icon: RiTranslate,
+      key: 'translation',
+    },
+    {
+      icon: RiPresentationLine,
+      key: 'meetingTakeaways',
+    },
+    {
+      icon: RiNewspaperLine,
+      key: 'writingsPolisher',
+    },
+    {
+      icon: RiUser2Line,
+      key: 'professionalAnalyst',
+    },
+    {
+      icon: RiFileExcel2Line,
+      key: 'excelFormulaExpert',
+    },
+    {
+      icon: RiRoadMapLine,
+      key: 'travelPlanning',
+    },
+    {
+      icon: RiDatabase2Line,
+      key: 'SQLSorcerer',
+    },
+    {
+      icon: RiGitCommitLine,
+      key: 'GitGud',
+    },
+  ]
 
-  const [audiences, setAudiences] = React.useState<string>('')
-  const [hopingToSolve, setHopingToSolve] = React.useState<string>('')
-  const isValid = () => {
-    if (audiences.trim() === '') {
-      Toast.notify({
-        type: 'error',
-        message: t('appDebug.automatic.audiencesRequired'),
-      })
-      return false
+  const [instruction, setInstruction] = React.useState<string>('')
+  const handleChooseTemplate = useCallback((key: string) => {
+    return () => {
+      const template = t(`appDebug.generate.template.${key}.instruction`)
+      setInstruction(template)
     }
-    if (hopingToSolve.trim() === '') {
+  }, [t])
+  const isValid = () => {
+    if (instruction.trim() === '') {
       Toast.notify({
         type: 'error',
-        message: t('appDebug.automatic.problemRequired'),
+        message: t('common.errorMsg.fieldRequired', {
+          field: t('appDebug.generate.instruction'),
+        }),
       })
       return false
     }
@@ -76,14 +132,17 @@ const GetAutomaticRes: FC<IGetAutomaticResProps> = ({
   const renderLoading = (
     <div className='w-0 grow flex flex-col items-center justify-center h-full space-y-3'>
       <Loading />
-      <div className='text-[13px] text-gray-400'>{t('appDebug.automatic.loading')}</div>
+      <div className='text-[13px] text-gray-400'>{t('appDebug.generate.loading')}</div>
     </div>
   )
 
   const renderNoData = (
     <div className='w-0 grow flex flex-col items-center px-8 justify-center h-full space-y-3'>
-      {noDataIcon}
-      <div className='text-[13px] text-gray-400'>{t('appDebug.automatic.noData')}</div>
+      <Generator className='w-14 h-14 text-gray-300' />
+      <div className='leading-5 text-center text-[13px] font-normal text-gray-400'>
+        <div>{t('appDebug.generate.noDataLine1')}</div>
+        <div>{t('appDebug.generate.noDataLine2')}</div>
+      </div>
     </div>
   )
 
@@ -94,11 +153,18 @@ const GetAutomaticRes: FC<IGetAutomaticResProps> = ({
       return
     setLoadingTrue()
     try {
-      const res = await generateRule({
-        audiences,
-        hoping_to_solve: hopingToSolve,
+      const { error, ...res } = await generateRule({
+        instruction,
+        model_config: model,
+        no_variable: !!isInLLMNode,
       })
       setRes(res)
+      if (error) {
+        Toast.notify({
+          type: 'error',
+          message: error,
+        })
+      }
     }
     finally {
       setLoadingFalse()
@@ -107,24 +173,7 @@ const GetAutomaticRes: FC<IGetAutomaticResProps> = ({
 
   const [showConfirmOverwrite, setShowConfirmOverwrite] = React.useState(false)
 
-  const isShowAutoPromptInput = () => {
-    if (isMobile) {
-      // hide prompt panel on mobile if it is loading or has had result
-      if (isLoading || res)
-        return false
-      return true
-    }
-
-    // always display prompt panel on desktop mode
-    return true
-  }
-
   const isShowAutoPromptResPlaceholder = () => {
-    if (isMobile) {
-      // hide placeholder panel on mobile
-      return false
-    }
-
     return !isLoading && !res
   }
 
@@ -132,75 +181,97 @@ const GetAutomaticRes: FC<IGetAutomaticResProps> = ({
     <Modal
       isShow={isShow}
       onClose={onClose}
-      className='!p-0 sm:min-w-[768px] xl:min-w-[1120px]'
+      className='!p-0 min-w-[1140px]'
       closable
     >
-      <div className='flex h-[680px] flex-wrap gap-y-4 overflow-y-auto'>
-        {isShowAutoPromptInput() && <div className='w-full sm:w-[360px] xl:w-[480px] shrink-0 px-8 py-6 h-full overflow-y-auto border-r border-gray-100'>
-          <div>
-            <div className='mb-1 text-xl font-semibold text-primary-600'>{t('appDebug.automatic.title')}</div>
-            <div className='text-[13px] font-normal text-gray-500'>{t('appDebug.automatic.description')}</div>
+      <div className='flex h-[680px] flex-wrap'>
+        <div className='w-[570px] shrink-0 p-6 h-full overflow-y-auto border-r border-gray-100'>
+          <div className='mb-8'>
+            <div className={`leading-[28px] text-lg font-bold ${s.textGradient}`}>{t('appDebug.generate.title')}</div>
+            <div className='mt-1 text-[13px] font-normal text-gray-500'>{t('appDebug.generate.description')}</div>
+          </div>
+          <div >
+            <div className='flex items-center'>
+              <div className='mr-3 shrink-0 leading-[18px] text-xs font-semibold text-gray-500 uppercase'>{t('appDebug.generate.tryIt')}</div>
+              <div className='grow h-px' style={{
+                background: 'linear-gradient(to right, rgba(243, 244, 246, 1), rgba(243, 244, 246, 0))',
+              }}></div>
+            </div>
+            <div className='flex flex-wrap'>
+              {tryList.map(item => (
+                <TryLabel
+                  key={item.key}
+                  Icon={item.icon}
+                  text={t(`appDebug.generate.template.${item.key}.name`)}
+                  onClick={handleChooseTemplate(item.key)}
+                />
+              ))}
+            </div>
           </div>
           {/* inputs */}
-          <div className='mt-2 space-y-5'>
-            <div className='space-y-2'>
-              <div className='text-[13px] font-medium text-gray-900'>{t('appDebug.automatic.intendedAudience')}</div>
-              <input className="w-full h-8 px-3 text-[13px] font-normal bg-gray-50 rounded-lg" placeholder={t('appDebug.automatic.intendedAudiencePlaceHolder') as string} value={audiences} onChange={e => setAudiences(e.target.value)} />
-            </div>
-            <div className='space-y-2'>
-              <div className='text-[13px] font-medium text-gray-900'>{t('appDebug.automatic.solveProblem')}</div>
-              <textarea className="w-full h-[200px] overflow-y-auto p-3 text-[13px] font-normal bg-gray-50 rounded-lg" placeholder={t('appDebug.automatic.solveProblemPlaceHolder') as string} value={hopingToSolve} onChange={e => setHopingToSolve(e.target.value)} />
+          <div className='mt-6'>
+            <div className='text-[0px]'>
+              <div className='mb-2 leading-5 text-sm font-medium text-gray-900'>{t('appDebug.generate.instruction')}</div>
+              <textarea className="w-full h-[200px] overflow-y-auto px-3 py-2 text-sm bg-gray-50 rounded-lg" placeholder={t('appDebug.generate.instructionPlaceHolder') as string} value={instruction} onChange={e => setInstruction(e.target.value)} />
             </div>
 
-            <div className='mt-6 flex justify-end'>
+            <div className='mt-5 flex justify-end'>
               <Button
-                className='flex space-x-2'
+                className='flex space-x-1'
                 variant='primary'
                 onClick={onGenerate}
                 disabled={isLoading}
               >
-                {genIcon}
-                <span className='text-xs font-semibold text-white uppercase'>{t('appDebug.automatic.generate')}</span>
+                <Generator className='w-4 h-4 text-white' />
+                <span className='text-xs font-semibold text-white'>{t('appDebug.generate.generate')}</span>
               </Button>
             </div>
           </div>
-        </div>}
+        </div>
 
         {(!isLoading && res) && (
-          <div className='w-0 grow px-8 pt-6 h-full overflow-y-auto'>
-            <div className='mb-4 text-lg font-medium text-gray-900'>{t('appDebug.automatic.resTitle')}</div>
+          <div className='w-0 grow p-6 pb-0 h-full'>
+            <div className='shrink-0 mb-3 leading-[160%] text-base font-semibold text-gray-800'>{t('appDebug.generate.resTitle')}</div>
+            <div className={cn('max-h-[555px] overflow-y-auto', !isInLLMNode && 'pb-2')}>
+              <ConfigPrompt
+                mode={mode}
+                promptTemplate={res?.prompt || ''}
+                promptVariables={[]}
+                readonly
+                noTitle={isInLLMNode}
+                gradientBorder
+                editorHeight={isInLLMNode ? 524 : 0}
+                noResize={isInLLMNode}
+              />
+              {!isInLLMNode && (
+                <>
+                  {(res?.variables?.length && res?.variables?.length > 0)
+                    ? (
+                      <ConfigVar
+                        promptVariables={res?.variables.map(key => ({ key, name: key, type: 'string', required: true })) || []}
+                        readonly
+                      />
+                    )
+                    : ''}
 
-            <ConfigPrompt
-              mode={mode}
-              promptTemplate={res?.prompt || ''}
-              promptVariables={[]}
-              readonly
-            />
+                  {(mode !== AppType.completion && res?.opening_statement) && (
+                    <div className='mt-7'>
+                      <GroupName name={t('appDebug.feature.groupChat.title')} />
+                      <OpeningStatement
+                        value={res?.opening_statement || ''}
+                        readonly
+                      />
+                    </div>
+                  )}
+                </>
+              )}
+            </div>
 
-            {(res?.variables?.length && res?.variables?.length > 0)
-              ? (
-                <ConfigVar
-                  promptVariables={res?.variables.map(key => ({ key, name: key, type: 'string', required: true })) || []}
-                  readonly
-                />
-              )
-              : ''}
-
-            {(mode !== AppType.completion && res?.opening_statement) && (
-              <div className='mt-7'>
-                <GroupName name={t('appDebug.feature.groupChat.title')} />
-                <OpeningStatement
-                  value={res?.opening_statement || ''}
-                  readonly
-                />
-              </div>
-            )}
-
-            <div className='sticky bottom-0 flex justify-end right-0 py-4 bg-white'>
+            <div className='flex justify-end py-4 bg-white'>
               <Button onClick={onClose}>{t('common.operation.cancel')}</Button>
               <Button variant='primary' className='ml-2' onClick={() => {
                 setShowConfirmOverwrite(true)
-              }}>{t('appDebug.automatic.apply')}</Button>
+              }}>{t('appDebug.generate.apply')}</Button>
             </div>
           </div>
         )}
@@ -208,8 +279,8 @@ const GetAutomaticRes: FC<IGetAutomaticResProps> = ({
         {isShowAutoPromptResPlaceholder() && renderNoData}
         {showConfirmOverwrite && (
           <Confirm
-            title={t('appDebug.automatic.overwriteTitle')}
-            content={t('appDebug.automatic.overwriteMessage')}
+            title={t('appDebug.generate.overwriteTitle')}
+            content={t('appDebug.generate.overwriteMessage')}
             isShow={showConfirmOverwrite}
             onClose={() => setShowConfirmOverwrite(false)}
             onConfirm={() => {

web/app/components/app/configuration/config/automatic/style.module.css

@@ -0,0 +1,7 @@
+.textGradient {
+  background: linear-gradient(92deg, #2250F2 -29.55%, #0EBCF3 75.22%);
+  -webkit-background-clip: text;
+  -webkit-text-fill-color: transparent;
+  background-clip: text;
+  text-fill-color: transparent;
+}

web/app/components/app/configuration/dataset-config/card-item/item.tsx

@@ -1,18 +1,20 @@
 'use client'
 import type { FC } from 'react'
 import React, { useState } from 'react'
-import { useTranslation } from 'react-i18next'
-import { RiDeleteBinLine } from '@remixicon/react'
+import {
+  RiDeleteBinLine,
+  RiEditLine,
+} from '@remixicon/react'
 import SettingsModal from '../settings-modal'
 import type { DataSet } from '@/models/datasets'
 import { DataSourceType } from '@/models/datasets'
-import { formatNumber } from '@/utils/format'
 import FileIcon from '@/app/components/base/file-icon'
-import { Settings01 } from '@/app/components/base/icons/src/vender/line/general'
 import { Folder } from '@/app/components/base/icons/src/vender/solid/files'
 import { Globe06 } from '@/app/components/base/icons/src/vender/solid/mapsAndTravel'
 import Drawer from '@/app/components/base/drawer'
 import useBreakpoints, { MediaType } from '@/hooks/use-breakpoints'
+import Badge from '@/app/components/base/badge'
+import { useKnowledge } from '@/hooks/use-knowledge'
 
 type ItemProps = {
   className?: string
@@ -27,12 +29,10 @@ const Item: FC<ItemProps> = ({
   onSave,
   onRemove,
 }) => {
-  const { t } = useTranslation()
-
   const media = useBreakpoints()
   const isMobile = media === MediaType.mobile
-
   const [showSettingsModal, setShowSettingsModal] = useState(false)
+  const { formatIndexingTechniqueAndMethod } = useKnowledge()
 
   const handleSave = (newDataset: DataSet) => {
     onSave(newDataset)
@@ -65,22 +65,17 @@ const Item: FC<ItemProps> = ({
       <div className='grow'>
         <div className='flex items-center h-[18px]'>
           <div className='grow text-[13px] font-medium text-gray-800 truncate' title={config.name}>{config.name}</div>
-          <div className='shrink-0 text-xs text-gray-500'>
-            {formatNumber(config.word_count)} {t('appDebug.feature.dataSet.words')} · {formatNumber(config.document_count)} {t('appDebug.feature.dataSet.textBlocks')}
-          </div>
+          <Badge
+            text={formatIndexingTechniqueAndMethod(config.indexing_technique, config.retrieval_model_dict?.search_method)}
+          />
         </div>
-        {/* {
-          config.description && (
-            <div className='text-xs text-gray-500'>{config.description}</div>
-          )
-        } */}
       </div>
       <div className='hidden rounded-lg group-hover:flex items-center justify-end absolute right-0 top-0 bottom-0 pr-2 w-[124px] bg-gradient-to-r from-white/50 to-white to-50%'>
         <div
           className='flex items-center justify-center mr-1 w-6 h-6 hover:bg-black/5 rounded-md cursor-pointer'
           onClick={() => setShowSettingsModal(true)}
         >
-          <Settings01 className='w-4 h-4 text-gray-500' />
+          <RiEditLine className='w-4 h-4 text-gray-500' />
         </div>
         <div
           className='group/action flex items-center justify-center w-6 h-6 hover:bg-[#FEE4E2] rounded-md cursor-pointer'

web/app/components/app/configuration/dataset-config/index.tsx

@@ -44,7 +44,8 @@ const DatasetConfig: FC = () => {
   const handleSave = (newDataset: DataSet) => {
     const index = dataSet.findIndex(item => item.id === newDataset.id)
 
-    setDataSet([...dataSet.slice(0, index), newDataset, ...dataSet.slice(index + 1)])
+    const newDatasets = [...dataSet.slice(0, index), newDataset, ...dataSet.slice(index + 1)]
+    setDataSet(newDatasets)
     formattingChangedDispatcher()
   }
 
@@ -74,7 +75,7 @@ const DatasetConfig: FC = () => {
       title={t('appDebug.feature.dataSet.title')}
       headerRight={
         <div className='flex items-center gap-1'>
-          {!isAgent && <ParamsConfig />}
+          {!isAgent && <ParamsConfig disabled={!hasData} selectedDatasets={dataSet} />}
           <OperationBtn type="add" onClick={showSelectDataSet} />
         </div>
       }

web/app/components/app/configuration/dataset-config/params-config/config-content.tsx

@@ -1,10 +1,12 @@
 'use client'
-import React from 'react'
+
+import { memo, useMemo } from 'react'
 import type { FC } from 'react'
 import { useTranslation } from 'react-i18next'
 import {
   RiQuestionLine,
 } from '@remixicon/react'
+import WeightedScore from './weighted-score'
 import TopKItem from '@/app/components/base/param-item/top-k-item'
 import ScoreThresholdItem from '@/app/components/base/param-item/score-threshold-item'
 import RadioCard from '@/app/components/base/radio-card/simple'
@@ -16,13 +18,20 @@ import {
 import type {
   DatasetConfigs,
 } from '@/models/debug'
-
 import ModelSelector from '@/app/components/header/account-setting/model-provider-page/model-selector'
 import { useModelListAndDefaultModelAndCurrentProviderAndModel } from '@/app/components/header/account-setting/model-provider-page/hooks'
 import type { ModelConfig } from '@/app/components/workflow/types'
 import ModelParameterModal from '@/app/components/header/account-setting/model-provider-page/model-parameter-modal'
 import TooltipPlus from '@/app/components/base/tooltip-plus'
 import { ModelTypeEnum } from '@/app/components/header/account-setting/model-provider-page/declarations'
+import type {
+  DataSet,
+  WeightedScoreEnum,
+} from '@/models/datasets'
+import { RerankingModeEnum } from '@/models/datasets'
+import cn from '@/utils/classnames'
+import { useSelectedDatasetsMode } from '@/app/components/workflow/nodes/knowledge-retrieval/hooks'
+import Switch from '@/app/components/base/switch'
 
 type Props = {
   datasetConfigs: DatasetConfigs
@@ -31,6 +40,7 @@ type Props = {
   singleRetrievalModelConfig?: ModelConfig
   onSingleRetrievalModelChange?: (config: ModelConfig) => void
   onSingleRetrievalModelParamsChange?: (config: ModelConfig) => void
+  selectedDatasets?: DataSet[]
 }
 
 const ConfigContent: FC<Props> = ({
@@ -40,8 +50,10 @@ const ConfigContent: FC<Props> = ({
   singleRetrievalModelConfig: singleRetrievalConfig = {} as ModelConfig,
   onSingleRetrievalModelChange = () => { },
   onSingleRetrievalModelParamsChange = () => { },
+  selectedDatasets = [],
 }) => {
   const { t } = useTranslation()
+  const selectedDatasetsMode = useSelectedDatasetsMode(selectedDatasets)
   const type = datasetConfigs.retrieval_model
   const setType = (value: RETRIEVE_TYPE) => {
     onChange({
@@ -54,7 +66,7 @@ const ConfigContent: FC<Props> = ({
     defaultModel: rerankDefaultModel,
   } = useModelListAndDefaultModelAndCurrentProviderAndModel(ModelTypeEnum.rerank)
   const rerankModel = (() => {
-    if (datasetConfigs.reranking_model) {
+    if (datasetConfigs.reranking_model?.reranking_provider_name) {
       return {
         provider_name: datasetConfigs.reranking_model.reranking_provider_name,
         model_name: datasetConfigs.reranking_model.reranking_model_name,
@@ -93,14 +105,73 @@ const ConfigContent: FC<Props> = ({
     })
   }
 
+  const handleWeightedScoreChange = (value: { type: WeightedScoreEnum; value: number[] }) => {
+    const configs = {
+      ...datasetConfigs,
+      weights: {
+        ...datasetConfigs.weights!,
+        weight_type: value.type,
+        vector_setting: {
+          ...datasetConfigs.weights!.vector_setting!,
+          vector_weight: value.value[0],
+        },
+        keyword_setting: {
+          keyword_weight: value.value[1],
+        },
+      },
+    }
+    onChange(configs)
+  }
+
+  const handleRerankModeChange = (mode: RerankingModeEnum) => {
+    onChange({
+      ...datasetConfigs,
+      reranking_mode: mode,
+    })
+  }
+
   const model = singleRetrievalConfig
 
+  const rerankingModeOptions = [
+    {
+      value: RerankingModeEnum.WeightedScore,
+      label: t('dataset.weightedScore.title'),
+      tips: t('dataset.weightedScore.description'),
+    },
+    {
+      value: RerankingModeEnum.RerankingModel,
+      label: t('common.modelProvider.rerankModel.key'),
+      tips: t('common.modelProvider.rerankModel.tip'),
+    },
+  ]
+
+  const showWeightedScore = selectedDatasetsMode.allHighQuality
+    && !selectedDatasetsMode.inconsistentEmbeddingModel
+
+  const showWeightedScorePanel = showWeightedScore && datasetConfigs.reranking_mode === RerankingModeEnum.WeightedScore && datasetConfigs.weights
+  const selectedRerankMode = datasetConfigs.reranking_mode || RerankingModeEnum.RerankingModel
+
+  const showRerankModel = useMemo(() => {
+    if (datasetConfigs.reranking_enable === false && selectedDatasetsMode.allEconomic)
+      return false
+
+    return true
+  }, [datasetConfigs.reranking_enable, selectedDatasetsMode.allEconomic])
+
   return (
     <div>
+      <div className='system-xl-semibold text-text-primary'>{t('dataset.retrievalSettings')}</div>
       <div className='mt-2 space-y-3'>
         <RadioCard
           icon={<NTo1Retrieval className='shrink-0 mr-3 w-9 h-9 rounded-lg' />}
-          title={t('appDebug.datasetConfig.retrieveOneWay.title')}
+          title={(
+            <div className='flex items-center'>
+              {t('appDebug.datasetConfig.retrieveOneWay.title')}
+              <TooltipPlus popupContent={<div className='w-[320px]'>{t('dataset.nTo1RetrievalLegacy')}</div>}>
+                <div className='ml-1 flex items-center px-[5px] h-[18px] rounded-[5px] border border-text-accent-secondary system-2xs-medium-uppercase text-text-accent-secondary'>legacy</div>
+              </TooltipPlus>
+            </div>
+          )}
           description={t('appDebug.datasetConfig.retrieveOneWay.description')}
           isChosen={type === RETRIEVE_TYPE.oneWay}
           onChosen={() => { setType(RETRIEVE_TYPE.oneWay) }}
@@ -115,43 +186,152 @@ const ConfigContent: FC<Props> = ({
       </div>
       {type === RETRIEVE_TYPE.multiWay && (
         <>
-          <div className='mt-6'>
-            <div className='leading-[32px] text-[13px] font-medium text-gray-900'>{t('common.modelProvider.rerankModel.key')}</div>
-            <div>
-              <ModelSelector
-                defaultModel={rerankModel && { provider: rerankModel?.provider_name, model: rerankModel?.model_name }}
-                onSelect={(v) => {
-                  onChange({
-                    ...datasetConfigs,
-                    reranking_model: {
-                      reranking_provider_name: v.provider,
-                      reranking_model_name: v.model,
-                    },
-                  })
-                }}
-                modelList={rerankModelList}
-              />
-            </div>
-          </div>
-          <div className='mt-4 space-y-4'>
-            <TopKItem
-              value={datasetConfigs.top_k}
-              onChange={handleParamChange}
-              enable={true}
-            />
-            <ScoreThresholdItem
-              value={datasetConfigs.score_threshold as number}
-              onChange={handleParamChange}
-              enable={datasetConfigs.score_threshold_enabled}
-              hasSwitch={true}
-              onSwitchChange={handleSwitch}
-            />
+          <div className='mb-2 mt-4 h-[1px] bg-divider-subtle'></div>
+          <div
+            className='flex items-center mb-2 h-6 system-md-semibold text-text-secondary'
+          >
+            {t('dataset.rerankSettings')}
           </div>
+          {
+            selectedDatasetsMode.inconsistentEmbeddingModel
+            && (
+              <div className='mt-4 system-xs-regular text-text-warning'>
+                {t('dataset.inconsistentEmbeddingModelTip')}
+              </div>
+            )
+          }
+          {
+            selectedDatasetsMode.mixtureHighQualityAndEconomic
+            && (
+              <div className='mt-4 system-xs-regular text-text-warning'>
+                {t('dataset.mixtureHighQualityAndEconomicTip')}
+              </div>
+            )
+          }
+          {
+            showWeightedScore && (
+              <div className='flex items-center justify-between'>
+                {
+                  rerankingModeOptions.map(option => (
+                    <div
+                      key={option.value}
+                      className={cn(
+                        'flex items-center justify-center w-[calc((100%-8px)/2)] h-8 rounded-lg border border-components-option-card-option-border bg-components-option-card-option-bg cursor-pointer system-sm-medium text-text-secondary',
+                        selectedRerankMode === option.value && 'border-[1.5px] border-components-option-card-option-selected-border bg-components-option-card-option-selected-bg text-text-primary',
+                      )}
+                      onClick={() => handleRerankModeChange(option.value)}
+                    >
+                      <div className='truncate'>{option.label}</div>
+                      <TooltipPlus
+                        popupContent={<div className='w-[200px]'>{option.tips}</div>}
+                        hideArrow
+                      >
+                        <RiQuestionLine className='ml-0.5 w-3.5 h-4.5 text-text-quaternary' />
+                      </TooltipPlus>
+                    </div>
+                  ))
+                }
+              </div>
+            )
+          }
+          {
+            !showWeightedScorePanel && (
+              <div className='mt-2'>
+                <div className='flex items-center'>
+                  {
+                    selectedDatasetsMode.allEconomic && (
+                      <Switch
+                        size='md'
+                        defaultValue={showRerankModel}
+                        onChange={(v) => {
+                          onChange({
+                            ...datasetConfigs,
+                            reranking_enable: v,
+                          })
+                        }}
+                      />
+                    )
+                  }
+                  <div className='ml-2 leading-[32px] text-[13px] font-medium text-gray-900'>{t('common.modelProvider.rerankModel.key')}</div>
+                  <TooltipPlus popupContent={<div className="w-[200px]">{t('common.modelProvider.rerankModel.tip')}</div>}>
+                    <RiQuestionLine className='ml-0.5 w-[14px] h-[14px] text-gray-400' />
+                  </TooltipPlus>
+                </div>
+                <div>
+                  <ModelSelector
+                    defaultModel={rerankModel && { provider: rerankModel?.provider_name, model: rerankModel?.model_name }}
+                    onSelect={(v) => {
+                      onChange({
+                        ...datasetConfigs,
+                        reranking_model: {
+                          reranking_provider_name: v.provider,
+                          reranking_model_name: v.model,
+                        },
+                      })
+                    }}
+                    modelList={rerankModelList}
+                  />
+                </div>
+              </div>
+            )
+          }
+          {
+            showWeightedScorePanel
+            && (
+              <div className='mt-2 space-y-4'>
+                <WeightedScore
+                  value={{
+                    type: datasetConfigs.weights!.weight_type,
+                    value: [
+                      datasetConfigs.weights!.vector_setting.vector_weight,
+                      datasetConfigs.weights!.keyword_setting.keyword_weight,
+                    ],
+                  }}
+                  onChange={handleWeightedScoreChange}
+                />
+                <TopKItem
+                  value={datasetConfigs.top_k}
+                  onChange={handleParamChange}
+                  enable={true}
+                />
+                <ScoreThresholdItem
+                  value={datasetConfigs.score_threshold as number}
+                  onChange={handleParamChange}
+                  enable={datasetConfigs.score_threshold_enabled}
+                  hasSwitch={true}
+                  onSwitchChange={handleSwitch}
+                />
+              </div>
+            )
+          }
+          {
+            !showWeightedScorePanel
+            && (
+              <div className='mt-4 space-y-4'>
+                <TopKItem
+                  value={datasetConfigs.top_k}
+                  onChange={handleParamChange}
+                  enable={true}
+                />
+                {
+                  showRerankModel && (
+                    <ScoreThresholdItem
+                      value={datasetConfigs.score_threshold as number}
+                      onChange={handleParamChange}
+                      enable={datasetConfigs.score_threshold_enabled}
+                      hasSwitch={true}
+                      onSwitchChange={handleSwitch}
+                    />
+                  )
+                }
+              </div>
+            )
+          }
         </>
       )}
 
       {isInWorkflow && type === RETRIEVE_TYPE.oneWay && (
-        <div className='mt-6'>
+        <div className='mt-4'>
           <div className='flex items-center space-x-0.5'>
             <div className='leading-[32px] text-[13px] font-medium text-gray-900'>{t('common.modelProvider.systemReasoningModel.key')}</div>
             <TooltipPlus
@@ -180,4 +360,4 @@ const ConfigContent: FC<Props> = ({
     </div >
   )
 }
-export default React.memo(ConfigContent)
+export default memo(ConfigContent)

web/app/components/app/configuration/dataset-config/params-config/index.tsx

@@ -1,29 +1,73 @@
 'use client'
-import type { FC } from 'react'
-import { memo, useState } from 'react'
+import { memo, useEffect, useState } from 'react'
 import { useTranslation } from 'react-i18next'
 import { useContext } from 'use-context-selector'
+import { RiEqualizer2Line } from '@remixicon/react'
 import ConfigContent from './config-content'
 import cn from '@/utils/classnames'
-import { Settings04 } from '@/app/components/base/icons/src/vender/line/general'
 import ConfigContext from '@/context/debug-configuration'
 import Modal from '@/app/components/base/modal'
 import Button from '@/app/components/base/button'
 import { RETRIEVE_TYPE } from '@/types/app'
 import Toast from '@/app/components/base/toast'
-import { DATASET_DEFAULT } from '@/config'
 import { useModelListAndDefaultModelAndCurrentProviderAndModel } from '@/app/components/header/account-setting/model-provider-page/hooks'
 import { ModelTypeEnum } from '@/app/components/header/account-setting/model-provider-page/declarations'
+import type { DataSet } from '@/models/datasets'
+import type { DatasetConfigs } from '@/models/debug'
+import {
+  getMultipleRetrievalConfig,
+  getSelectedDatasetsMode,
+} from '@/app/components/workflow/nodes/knowledge-retrieval/utils'
 
-const ParamsConfig: FC = () => {
+type ParamsConfigProps = {
+  disabled?: boolean
+  selectedDatasets: DataSet[]
+}
+const ParamsConfig = ({
+  disabled,
+  selectedDatasets,
+}: ParamsConfigProps) => {
   const { t } = useTranslation()
-  const [open, setOpen] = useState(false)
   const {
     datasetConfigs,
     setDatasetConfigs,
+    rerankSettingModalOpen,
+    setRerankSettingModalOpen,
   } = useContext(ConfigContext)
   const [tempDataSetConfigs, setTempDataSetConfigs] = useState(datasetConfigs)
 
+  useEffect(() => {
+    const {
+      allEconomic,
+    } = getSelectedDatasetsMode(selectedDatasets)
+    const { datasets, retrieval_model, score_threshold_enabled, ...restConfigs } = datasetConfigs
+    let rerankEnable = restConfigs.reranking_enable
+
+    if (allEconomic && !restConfigs.reranking_model?.reranking_provider_name && rerankEnable === undefined)
+      rerankEnable = false
+
+    setTempDataSetConfigs({
+      ...getMultipleRetrievalConfig({
+        top_k: restConfigs.top_k,
+        score_threshold: restConfigs.score_threshold,
+        reranking_model: restConfigs.reranking_model && {
+          provider: restConfigs.reranking_model.reranking_provider_name,
+          model: restConfigs.reranking_model.reranking_model_name,
+        },
+        reranking_mode: restConfigs.reranking_mode,
+        weights: restConfigs.weights,
+        reranking_enable: rerankEnable,
+      }, selectedDatasets),
+      reranking_model: restConfigs.reranking_model && {
+        reranking_provider_name: restConfigs.reranking_model.reranking_provider_name,
+        reranking_model_name: restConfigs.reranking_model.reranking_model_name,
+      },
+      retrieval_model,
+      score_threshold_enabled,
+      datasets,
+    })
+  }, [selectedDatasets, datasetConfigs])
+
   const {
     defaultModel: rerankDefaultModel,
     currentModel: isRerankDefaultModelVaild,
@@ -55,45 +99,68 @@ const ParamsConfig: FC = () => {
       } as any
     }
     setDatasetConfigs(config)
-    setOpen(false)
+    setRerankSettingModalOpen(false)
+  }
+
+  const handleSetTempDataSetConfigs = (newDatasetConfigs: DatasetConfigs) => {
+    const { datasets, retrieval_model, score_threshold_enabled, ...restConfigs } = newDatasetConfigs
+
+    const retrievalConfig = getMultipleRetrievalConfig({
+      top_k: restConfigs.top_k,
+      score_threshold: restConfigs.score_threshold,
+      reranking_model: restConfigs.reranking_model && {
+        provider: restConfigs.reranking_model.reranking_provider_name,
+        model: restConfigs.reranking_model.reranking_model_name,
+      },
+      reranking_mode: restConfigs.reranking_mode,
+      weights: restConfigs.weights,
+      reranking_enable: restConfigs.reranking_enable,
+    }, selectedDatasets)
+
+    setTempDataSetConfigs({
+      ...retrievalConfig,
+      reranking_model: restConfigs.reranking_model && {
+        reranking_provider_name: restConfigs.reranking_model.reranking_provider_name,
+        reranking_model_name: restConfigs.reranking_model.reranking_model_name,
+      },
+      retrieval_model,
+      score_threshold_enabled,
+      datasets,
+    })
   }
 
   return (
     <div>
-      <div
-        className={cn('flex items-center rounded-md h-7 px-3 space-x-1 text-gray-700 cursor-pointer hover:bg-gray-200', open && 'bg-gray-200')}
+      <Button
+        variant='ghost'
+        size='small'
+        className={cn('h-7', rerankSettingModalOpen && 'bg-components-button-ghost-bg-hover')}
         onClick={() => {
-          setTempDataSetConfigs({
-            ...datasetConfigs,
-            top_k: datasetConfigs.top_k || DATASET_DEFAULT.top_k,
-            score_threshold: datasetConfigs.score_threshold || DATASET_DEFAULT.score_threshold,
-          })
-          setOpen(true)
+          setRerankSettingModalOpen(true)
         }}
+        disabled={disabled}
       >
-        <Settings04 className="w-[14px] h-[14px]" />
-        <div className='text-xs font-medium'>
-          {t('appDebug.datasetConfig.params')}
-        </div>
-      </div>
+        <RiEqualizer2Line className='mr-1 w-3.5 h-3.5' />
+        {t('dataset.retrievalSettings')}
+      </Button>
       {
-        open && (
+        rerankSettingModalOpen && (
           <Modal
-            isShow={open}
+            isShow={rerankSettingModalOpen}
             onClose={() => {
-              setOpen(false)
+              setRerankSettingModalOpen(false)
             }}
             className='sm:min-w-[528px]'
-            title={t('appDebug.datasetConfig.settingTitle')}
           >
             <ConfigContent
               datasetConfigs={tempDataSetConfigs}
-              onChange={setTempDataSetConfigs}
+              onChange={handleSetTempDataSetConfigs}
+              selectedDatasets={selectedDatasets}
             />
 
             <div className='mt-6 flex justify-end'>
               <Button className='mr-2 flex-shrink-0' onClick={() => {
-                setOpen(false)
+                setRerankSettingModalOpen(false)
               }}>{t('common.operation.cancel')}</Button>
               <Button variant='primary' className='flex-shrink-0' onClick={handleSave} >{t('common.operation.save')}</Button>
             </div>

web/app/components/app/configuration/dataset-config/params-config/weighted-score.tsx

@@ -0,0 +1,112 @@
+import { memo, useCallback } from 'react'
+import { useTranslation } from 'react-i18next'
+import {
+  DEFAULT_WEIGHTED_SCORE,
+  WeightedScoreEnum,
+} from '@/models/datasets'
+import Slider from '@/app/components/base/slider'
+import cn from '@/utils/classnames'
+
+const formatNumber = (value: number) => {
+  if (value > 0 && value < 1)
+    return `0.${value * 10}`
+  else if (value === 1)
+    return '1.0'
+
+  return value
+}
+
+type Value = {
+  type: WeightedScoreEnum
+  value: number[]
+}
+
+type WeightedScoreProps = {
+  value: Value
+  onChange: (value: Value) => void
+}
+const WeightedScore = ({
+  value,
+  onChange = () => {},
+}: WeightedScoreProps) => {
+  const { t } = useTranslation()
+  const options = [
+    {
+      value: WeightedScoreEnum.SemanticFirst,
+      label: t('dataset.weightedScore.semanticFirst'),
+    },
+    {
+      value: WeightedScoreEnum.KeywordFirst,
+      label: t('dataset.weightedScore.keywordFirst'),
+    },
+    {
+      value: WeightedScoreEnum.Customized,
+      label: t('dataset.weightedScore.customized'),
+    },
+  ]
+
+  const disabled = value.type !== WeightedScoreEnum.Customized
+
+  const handleTypeChange = useCallback((type: WeightedScoreEnum) => {
+    const result = { ...value, type }
+
+    if (type === WeightedScoreEnum.SemanticFirst)
+      result.value = [DEFAULT_WEIGHTED_SCORE.semanticFirst.semantic, DEFAULT_WEIGHTED_SCORE.semanticFirst.keyword]
+
+    if (type === WeightedScoreEnum.KeywordFirst)
+      result.value = [DEFAULT_WEIGHTED_SCORE.keywordFirst.semantic, DEFAULT_WEIGHTED_SCORE.keywordFirst.keyword]
+
+    onChange(result)
+  }, [value, onChange])
+
+  return (
+    <div>
+      <div className='flex items-center mb-1 space-x-4'>
+        {
+          options.map(option => (
+            <div
+              key={option.value}
+              className='flex py-1.5 max-w-[calc((100%-32px)/3)] system-sm-regular text-text-secondary cursor-pointer'
+              onClick={() => handleTypeChange(option.value)}
+            >
+              <div
+                className={cn(
+                  'shrink-0 mr-2 w-4 h-4 bg-components-radio-bg border border-components-radio-border rounded-full shadow-xs',
+                  value.type === option.value && 'border-[5px] border-components-radio-border-checked',
+                )}
+              ></div>
+              <div className='truncate' title={option.label}>{option.label}</div>
+            </div>
+          ))
+        }
+      </div>
+      <div className='flex items-center px-3 h-9 space-x-3 rounded-lg border border-components-panel-border'>
+        <div className='shrink-0 flex items-center w-[90px] system-xs-semibold-uppercase text-util-colors-blue-blue-500'>
+          <div className='mr-1 truncate uppercase' title={t('dataset.weightedScore.semantic') || ''}>
+            {t('dataset.weightedScore.semantic')}
+          </div>
+          {formatNumber(value.value[0])}
+        </div>
+        <Slider
+          className={cn('grow h-0.5 bg-gradient-to-r from-[#53B1FD] to-[#2ED3B7]', disabled && 'cursor-not-allowed')}
+          max={1.0}
+          min={0}
+          step={0.1}
+          value={value.value[0]}
+          onChange={v => onChange({ type: value.type, value: [v, (10 - v * 10) / 10] })}
+          disabled={disabled}
+          thumbClassName={cn(disabled && '!cursor-not-allowed')}
+          trackClassName='!bg-transparent'
+        />
+        <div className='shrink-0 flex items-center justify-end w-[90px] system-xs-semibold-uppercase text-util-colors-cyan-cyan-500'>
+          {formatNumber(value.value[1])}
+          <div className='ml-1 truncate uppercase' title={t('dataset.weightedScore.keyword') || ''}>
+            {t('dataset.weightedScore.keyword')}
+          </div>
+        </div>
+      </div>
+    </div>
+  )
+}
+
+export default memo(WeightedScore)

web/app/components/app/configuration/dataset-config/select-dataset/index.tsx

@@ -13,7 +13,8 @@ import type { DataSet } from '@/models/datasets'
 import Button from '@/app/components/base/button'
 import { fetchDatasets } from '@/service/datasets'
 import Loading from '@/app/components/base/loading'
-import { formatNumber } from '@/utils/format'
+import Badge from '@/app/components/base/badge'
+import { useKnowledge } from '@/hooks/use-knowledge'
 
 export type ISelectDataSetProps = {
   isShow: boolean
@@ -38,6 +39,7 @@ const SelectDataSet: FC<ISelectDataSetProps> = ({
   const listRef = useRef<HTMLDivElement>(null)
   const [page, setPage, getPage] = useGetState(1)
   const [isNoMore, setIsNoMore] = useState(false)
+  const { formatIndexingTechniqueAndMethod } = useKnowledge()
 
   useInfiniteScroll(
     async () => {
@@ -45,7 +47,7 @@ const SelectDataSet: FC<ISelectDataSetProps> = ({
         const { data, has_more } = await fetchDatasets({ url: '/datasets', params: { page } })
         setPage(getPage() + 1)
         setIsNoMore(!has_more)
-        const newList = [...(datasets || []), ...data]
+        const newList = [...(datasets || []), ...data.filter(item => item.indexing_technique)]
         setDataSets(newList)
         setLoaded(true)
         if (!selected.find(item => !item.name))
@@ -136,14 +138,13 @@ const SelectDataSet: FC<ISelectDataSetProps> = ({
                     <span className='ml-1 shrink-0 px-1 border boder-gray-200 rounded-md text-gray-500 text-xs font-normal leading-[18px]'>{t('dataset.unavailable')}</span>
                   )}
                 </div>
-
-                <div className={cn('shrink-0 flex text-xs text-gray-500 overflow-hidden whitespace-nowrap', !item.embedding_available && 'opacity-50')}>
-                  <span className='max-w-[100px] overflow-hidden text-ellipsis whitespace-nowrap'>{formatNumber(item.word_count)}</span>
-                  {t('appDebug.feature.dataSet.words')}
-                  <span className='px-0.5'>·</span>
-                  <span className='max-w-[100px] min-w-[8px] overflow-hidden text-ellipsis whitespace-nowrap'>{formatNumber(item.document_count)} </span>
-                  {t('appDebug.feature.dataSet.textBlocks')}
-                </div>
+                {
+                  item.indexing_technique && (
+                    <Badge
+                      text={formatIndexingTechniqueAndMethod(item.indexing_technique, item.retrieval_model_dict?.search_method)}
+                    />
+                  )
+                }
               </div>
             ))}
           </div>

web/app/components/app/configuration/dataset-config/settings-modal/index.tsx

@@ -259,7 +259,7 @@ const SettingsModal: FC<SettingsModalProps> = ({
 
         {/* Retrieval Method Config */}
         <div className={rowClass}>
-          <div className={labelClass}>
+          <div className={cn(labelClass, 'w-auto min-w-[168px]')}>
             <div>
               <div>{t('datasetSettings.form.retrievalSetting.title')}</div>
               <div className='leading-[18px] text-xs font-normal text-gray-500'>
@@ -268,7 +268,7 @@ const SettingsModal: FC<SettingsModalProps> = ({
               </div>
             </div>
           </div>
-          <div className='w-[480px]'>
+          <div>
             {indexMethod === 'high_quality'
               ? (
                 <RetrievalMethodConfig

web/app/components/app/configuration/index.tsx

@@ -46,7 +46,7 @@ import { fetchDatasets } from '@/service/datasets'
 import { useProviderContext } from '@/context/provider-context'
 import { AgentStrategy, AppType, ModelModeType, RETRIEVE_TYPE, Resolution, TransferMethod } from '@/types/app'
 import { PromptMode } from '@/models/debug'
-import { ANNOTATION_DEFAULT, DEFAULT_AGENT_SETTING, DEFAULT_CHAT_PROMPT_CONFIG, DEFAULT_COMPLETION_PROMPT_CONFIG } from '@/config'
+import { ANNOTATION_DEFAULT, DATASET_DEFAULT, DEFAULT_AGENT_SETTING, DEFAULT_CHAT_PROMPT_CONFIG, DEFAULT_COMPLETION_PROMPT_CONFIG } from '@/config'
 import SelectDataSet from '@/app/components/app/configuration/dataset-config/select-dataset'
 import { useModalContext } from '@/context/modal-context'
 import useBreakpoints, { MediaType } from '@/hooks/use-breakpoints'
@@ -57,6 +57,10 @@ import { useTextGenerationCurrentProviderAndModelAndModelList } from '@/app/comp
 import { fetchCollectionList } from '@/service/tools'
 import { type Collection } from '@/app/components/tools/types'
 import { useStore as useAppStore } from '@/app/components/app/store'
+import {
+  getMultipleRetrievalConfig,
+  getSelectedDatasetsMode,
+} from '@/app/components/workflow/nodes/knowledge-retrieval/utils'
 
 type PublishConfig = {
   modelConfig: ModelConfig
@@ -174,14 +178,14 @@ const Configuration: FC = () => {
 
   }, [])
   const [datasetConfigs, setDatasetConfigs] = useState<DatasetConfigs>({
-    retrieval_model: RETRIEVE_TYPE.oneWay,
+    retrieval_model: RETRIEVE_TYPE.multiWay,
     reranking_model: {
       reranking_provider_name: '',
       reranking_model_name: '',
     },
-    top_k: 2,
+    top_k: DATASET_DEFAULT.top_k,
     score_threshold_enabled: false,
-    score_threshold: 0.7,
+    score_threshold: DATASET_DEFAULT.score_threshold,
     datasets: {
       datasets: [],
     },
@@ -202,6 +206,7 @@ const Configuration: FC = () => {
   const hasSetContextVar = !!contextVar
   const [isShowSelectDataSet, { setTrue: showSelectDataSet, setFalse: hideSelectDataSet }] = useBoolean(false)
   const selectedIds = dataSets.map(item => item.id)
+  const [rerankSettingModalOpen, setRerankSettingModalOpen] = useState(false)
   const handleSelect = (data: DataSet[]) => {
     if (isEqual(data.map(item => item.id), dataSets.map(item => item.id))) {
       hideSelectDataSet()
@@ -209,6 +214,7 @@ const Configuration: FC = () => {
     }
 
     formattingChangedDispatcher()
+    let newDatasets = data
     if (data.find(item => !item.name)) { // has not loaded selected dataset
       const newSelected = produce(data, (draft: any) => {
         data.forEach((item, index) => {
@@ -220,11 +226,45 @@ const Configuration: FC = () => {
         })
       })
       setDataSets(newSelected)
+      newDatasets = newSelected
     }
     else {
       setDataSets(data)
     }
     hideSelectDataSet()
+    const {
+      allEconomic,
+      mixtureHighQualityAndEconomic,
+      inconsistentEmbeddingModel,
+    } = getSelectedDatasetsMode(newDatasets)
+
+    if (allEconomic || mixtureHighQualityAndEconomic || inconsistentEmbeddingModel)
+      setRerankSettingModalOpen(true)
+
+    const { datasets, retrieval_model, score_threshold_enabled, ...restConfigs } = datasetConfigs
+
+    const retrievalConfig = getMultipleRetrievalConfig({
+      top_k: restConfigs.top_k,
+      score_threshold: restConfigs.score_threshold,
+      reranking_model: restConfigs.reranking_model && {
+        provider: restConfigs.reranking_model.reranking_provider_name,
+        model: restConfigs.reranking_model.reranking_model_name,
+      },
+      reranking_mode: restConfigs.reranking_mode,
+      weights: restConfigs.weights,
+      reranking_enable: restConfigs.reranking_enable,
+    }, newDatasets)
+
+    setDatasetConfigs({
+      ...retrievalConfig,
+      reranking_model: restConfigs.reranking_model && {
+        reranking_provider_name: restConfigs.reranking_model.reranking_provider_name,
+        reranking_model_name: restConfigs.reranking_model.reranking_model_name,
+      },
+      retrieval_model,
+      score_threshold_enabled,
+      datasets,
+    })
   }
 
   const [isShowHistoryModal, { setTrue: showHistoryModal, setFalse: hideHistoryModal }] = useBoolean(false)
@@ -509,7 +549,7 @@ const Configuration: FC = () => {
         syncToPublishedConfig(config)
         setPublishedConfig(config)
         setDatasetConfigs({
-          retrieval_model: RETRIEVE_TYPE.oneWay,
+          retrieval_model: RETRIEVE_TYPE.multiWay,
           ...modelConfig.dataset_configs,
         })
         setHasFetchedDetail(true)
@@ -744,6 +784,8 @@ const Configuration: FC = () => {
       isShowVisionConfig,
       visionConfig,
       setVisionConfig: handleSetVisionConfig,
+      rerankSettingModalOpen,
+      setRerankSettingModalOpen,
     }}
     >
       <>

web/app/components/base/action-button/index.css

@@ -0,0 +1,49 @@
+@tailwind components;
+
+@layer components {
+    .action-btn {
+        @apply inline-flex justify-center items-center cursor-pointer text-text-tertiary
+        hover:text-text-secondary 
+        hover:bg-state-base-hover 
+    }
+
+    .action-btn-disabled {
+        @apply cursor-not-allowed
+    }
+
+    .action-btn-xl {
+        @apply p-2 w-9 h-9 rounded-lg
+    }
+
+    .action-btn-l {
+        @apply p-1.5 w-[34px] h-[34px] rounded-lg
+    }
+
+    /* m is for the regular button */
+    .action-btn-m {
+        @apply p-0.5 w-6 h-6 rounded-lg
+    }
+
+    .action-btn-xs {
+        @apply p-0 w-5 h-5 rounded
+    }
+
+    .action-btn.action-btn-active {
+        @apply 
+        text-text-accent 
+        bg-state-accent-active
+        hover:bg-state-accent-active-alt
+    }
+
+    .action-btn.action-btn-disabled {
+        @apply
+        text-text-disabled
+    }
+
+    .action-btn.action-btn-destructive {
+        @apply
+        text-text-destructive
+        bg-state-destructive-hover
+    }
+
+}

web/app/components/base/action-button/index.tsx

@@ -0,0 +1,70 @@
+import type { CSSProperties } from 'react'
+import React from 'react'
+import { type VariantProps, cva } from 'class-variance-authority'
+import classNames from '@/utils/classnames'
+
+enum ActionButtonState {
+  Destructive = 'destructive',
+  Active = 'active',
+  Disabled = 'disabled',
+  Default = '',
+}
+
+const actionButtonVariants = cva(
+  'action-btn',
+  {
+    variants: {
+      size: {
+        xs: 'action-btn-xs',
+        m: 'action-btn-m',
+        l: 'action-btn-l',
+        xl: 'action-btn-xl',
+      },
+    },
+    defaultVariants: {
+      size: 'm',
+    },
+  },
+)
+
+export type ActionButtonProps = {
+  size?: 'xs' | 'm' | 'l' | 'xl'
+  state?: ActionButtonState
+  styleCss?: CSSProperties
+} & React.ButtonHTMLAttributes<HTMLButtonElement> & VariantProps<typeof actionButtonVariants>
+
+function getActionButtonState(state: ActionButtonState) {
+  switch (state) {
+    case ActionButtonState.Destructive:
+      return 'action-btn-destructive'
+    case ActionButtonState.Active:
+      return 'action-btn-active'
+    case ActionButtonState.Disabled:
+      return 'action-btn-disabled'
+    default:
+      return ''
+  }
+}
+
+const ActionButton = React.forwardRef<HTMLButtonElement, ActionButtonProps>(
+  ({ className, size, state = ActionButtonState.Default, styleCss, children, ...props }, ref) => {
+    return (
+      <button
+        type='button'
+        className={classNames(
+          actionButtonVariants({ className, size }),
+          getActionButtonState(state),
+        )}
+        ref={ref}
+        style={styleCss}
+        {...props}
+      >
+        {children}
+      </button>
+    )
+  },
+)
+ActionButton.displayName = 'ActionButton'
+
+export default ActionButton
+export { ActionButton, ActionButtonState, actionButtonVariants }

web/app/components/base/badge.tsx

@@ -0,0 +1,25 @@
+import { memo } from 'react'
+import cn from '@/utils/classnames'
+
+type BadgeProps = {
+  className?: string
+  text: string
+}
+
+const Badge = ({
+  className,
+  text,
+}: BadgeProps) => {
+  return (
+    <div
+      className={cn(
+        'inline-flex items-center px-[5px] h-5 rounded-[5px] border border-divider-deep system-2xs-medium-uppercase leading-3 text-text-tertiary',
+        className,
+      )}
+    >
+      {text}
+    </div>
+  )
+}
+
+export default memo(Badge)

web/app/components/base/button/index.css

@@ -2,46 +2,185 @@
 
 @layer components {
   .btn {
-    @apply inline-flex justify-center items-center border-[0.5px] font-medium cursor-pointer whitespace-nowrap shadow;
+    @apply inline-flex justify-center items-center cursor-pointer whitespace-nowrap;
   }
 
   .btn-disabled {
-    @apply opacity-60 cursor-not-allowed;
+    @apply cursor-not-allowed;
   }
 
   .btn-small {
-    @apply px-2 h-6 rounded-md text-xs
+    @apply px-2 h-6 rounded-md text-xs font-medium;
   }
 
   .btn-medium {
-    @apply px-3.5 h-8 rounded-lg text-[13px]
+    @apply px-3.5 h-8 rounded-lg text-[13px] leading-4 font-medium;
   }
 
   .btn-large {
-    @apply px-4 h-9 rounded-[10px] text-sm font-semibold
-  }
-
-  .btn-secondary {
-    @apply bg-white hover:bg-white/80 border-gray-200 hover:border-gray-300 text-gray-700;
-  }
-
-  .btn-secondary-accent {
-    @apply bg-white hover:bg-white/80 border-gray-200 hover:border-gray-300 text-primary-600;
+    @apply px-4 h-9 rounded-[10px] text-sm font-semibold;
   }
 
   .btn-primary {
-    @apply bg-primary-600 hover:bg-primary-700 text-white;
+    @apply 
+    shadow
+    bg-components-button-primary-bg
+    border-components-button-primary-border
+    hover:bg-components-button-primary-bg-hover
+    hover:border-components-button-primary-border-hover
+    text-components-button-primary-text;
+  }
+
+  .btn-primary.btn-destructive {
+    @apply 
+    bg-components-button-destructive-primary-bg
+    border-components-button-destructive-primary-border
+    hover:bg-components-button-destructive-primary-bg-hover
+    hover:border-components-button-destructive-primary-border-hover
+    text-components-button-destructive-primary-text;
+  }
+
+  .btn-primary.btn-disabled {
+    @apply 
+    shadow-none
+    bg-components-button-primary-bg-disabled
+    border-components-button-primary-border-disabled
+    text-components-button-primary-text-disabled;
+  }
+
+  .btn-primary.btn-destructive.btn-disabled {
+    @apply 
+    shadow-none
+    bg-components-button-destructive-primary-bg-disabled
+    border-components-button-destructive-primary-border-disabled
+    text-components-button-destructive-primary-text-disabled;
+  }
+
+  .btn-secondary {
+    @apply 
+    border-[0.5px]
+    shadow-xs
+    bg-components-button-secondary-bg 
+    border-components-button-secondary-border 
+    hover:bg-components-button-secondary-bg-hover 
+    hover:border-components-button-secondary-border-hover 
+    text-components-button-secondary-text;
+  }
+
+  .btn-secondary.btn-disabled {
+    @apply 
+    bg-components-button-secondary-bg-disabled 
+    border-components-button-secondary-border-disabled 
+    text-components-button-secondary-text-disabled;
+  }
+
+  .btn-secondary.btn-destructive {
+    @apply 
+    bg-components-button-destructive-secondary-bg 
+    border-components-button-destructive-secondary-border 
+    hover:bg-components-button-destructive-secondary-bg-hover 
+    hover:border-components-button-destructive-secondary-border-hover 
+    text-components-button-destructive-secondary-text;
+  }
+
+  .btn-secondary.btn-destructive.btn-disabled {
+    @apply 
+    bg-components-button-destructive-secondary-bg-disabled 
+    border-components-button-destructive-secondary-border-disabled 
+    text-components-button-destructive-secondary-text-disabled;
+  }
+
+  
+  .btn-secondary-accent {
+    @apply 
+    border-[0.5px]
+    shadow-xs
+    bg-components-button-secondary-bg 
+    border-components-button-secondary-border 
+    hover:bg-components-button-secondary-bg-hover 
+    hover:border-components-button-secondary-border-hover 
+    text-components-button-secondary-accent-text;
+  }
+
+  .btn-secondary-accent.btn-disabled {
+    @apply 
+    bg-components-button-secondary-bg-disabled 
+    border-components-button-secondary-border-disabled 
+    text-components-button-secondary-accent-text-disabled;
   }
 
   .btn-warning {
-    @apply bg-red-600 hover:bg-red-700 text-white;
+    @apply 
+    bg-components-button-destructive-primary-bg 
+    border-components-button-destructive-primary-border 
+    hover:bg-components-button-destructive-primary-bg-hover 
+    hover:border-components-button-destructive-primary-border-hover 
+    text-components-button-destructive-primary-text;
   }
 
-  .btn-ghost {
-    @apply bg-transparent hover:bg-gray-200 border-transparent shadow-none text-gray-700;
+  .btn-warning.btn-disabled {
+    @apply 
+    bg-components-button-destructive-primary-bg-disabled 
+    border-components-button-destructive-primary-border-disabled 
+    text-components-button-destructive-primary-text-disabled;
   }
 
   .btn-tertiary {
-    @apply bg-[#F2F4F7] hover:bg-[#E9EBF0] border-transparent shadow-none text-gray-700;
+    @apply 
+    bg-components-button-tertiary-bg 
+    hover:bg-components-button-tertiary-bg-hover 
+    text-components-button-tertiary-text;
+  }
+
+  .btn-tertiary.btn-disabled {
+    @apply 
+    bg-components-button-tertiary-bg-disabled 
+    text-components-button-tertiary-text-disabled;
+  }
+
+  .btn-tertiary.btn-destructive {
+    @apply 
+    bg-components-button-destructive-tertiary-bg 
+    hover:bg-components-button-destructive-tertiary-bg-hover 
+    text-components-button-destructive-tertiary-text;
+  }
+
+  .btn-tertiary.btn-destructive.btn-disabled {
+    @apply 
+    bg-components-button-destructive-tertiary-bg-disabled 
+    text-components-button-destructive-tertiary-text-disabled;
+  }
+
+  .btn-ghost {
+    @apply 
+    hover:bg-components-button-ghost-bg-hover 
+    text-components-button-ghost-text;
+  }
+
+  .btn-ghost.btn-disabled {
+    @apply 
+    text-components-button-ghost-text-disabled;
+  }
+
+  .btn-ghost.btn-destructive {
+    @apply 
+    hover:bg-components-button-destructive-ghost-bg-hover 
+    text-components-button-destructive-ghost-text;
+  }
+
+  .btn-ghost.btn-destructive.btn-disabled {
+    @apply 
+    text-components-button-destructive-ghost-text-disabled;
+  }
+
+  .btn-ghost-accent {
+    @apply 
+    hover:bg-state-accent-hover
+    text-components-button-secondary-accent-text;
+  }
+
+  .btn-ghost-accent.btn-disabled {
+    @apply 
+    text-components-button-secondary-accent-text-disabled;
   }
 }

web/app/components/base/button/index.tsx

@@ -14,6 +14,7 @@ const buttonVariants = cva(
         'secondary': 'btn-secondary',
         'secondary-accent': 'btn-secondary-accent',
         'ghost': 'btn-ghost',
+        'ghost-accent': 'btn-ghost-accent',
         'tertiary': 'btn-tertiary',
       },
       size: {
@@ -30,16 +31,20 @@ const buttonVariants = cva(
 )
 
 export type ButtonProps = {
+  destructive?: boolean
   loading?: boolean
   styleCss?: CSSProperties
 } & React.ButtonHTMLAttributes<HTMLButtonElement> & VariantProps<typeof buttonVariants>
 
 const Button = React.forwardRef<HTMLButtonElement, ButtonProps>(
-  ({ className, variant, size, loading, styleCss, children, ...props }, ref) => {
+  ({ className, variant, size, destructive, loading, styleCss, children, ...props }, ref) => {
     return (
       <button
         type='button'
-        className={classNames(buttonVariants({ variant, size, className }))}
+        className={classNames(
+          buttonVariants({ variant, size, className }),
+          destructive && 'btn-destructive',
+        )}
         ref={ref}
         style={styleCss}
         {...props}

web/app/components/base/chat/embedded-chatbot/chat-wrapper.tsx

@@ -111,7 +111,7 @@ const ChatWrapper = () => {
       )
     }
 
-    return <div className='mb-6' />
+    return null
   }, [currentConversationId, inputsForms, isMobile])
 
   return (

web/app/components/base/chat/embedded-chatbot/index.tsx

@@ -3,6 +3,8 @@ import {
   useState,
 } from 'react'
 import { useAsyncEffect } from 'ahooks'
+import { useTranslation } from 'react-i18next'
+import { RiLoopLeftLine } from '@remixicon/react'
 import {
   EmbeddedChatbotContext,
   useEmbeddedChatbotContext,
@@ -19,8 +21,10 @@ import LogoHeader from '@/app/components/base/logo/logo-embeded-chat-header'
 import Header from '@/app/components/base/chat/embedded-chatbot/header'
 import ConfigPanel from '@/app/components/base/chat/embedded-chatbot/config-panel'
 import ChatWrapper from '@/app/components/base/chat/embedded-chatbot/chat-wrapper'
+import Tooltip from '@/app/components/base/tooltip'
 
 const Chatbot = () => {
+  const { t } = useTranslation()
   const {
     isMobile,
     appInfoError,
@@ -80,7 +84,22 @@ const Chatbot = () => {
             <Loading type='app' />
           )}
           {chatReady && !appChatListDataLoading && (
-            <ChatWrapper />
+            <div className='relative h-full pt-8 mx-auto w-full max-w-[720px]'>
+              {!isMobile && (
+                <div className='absolute top-2.5 right-3 z-20'>
+                  <Tooltip
+                    selector={'embed-scene-restart-button'}
+                    htmlContent={t('share.chat.resetChat')}
+                    position='top'
+                  >
+                    <div className='p-1.5 bg-white border-[0.5px] border-gray-100 rounded-lg shadow-md cursor-pointer' onClick={handleNewConversation}>
+                      <RiLoopLeftLine className="h-4 w-4 text-gray-500"/>
+                    </div>
+                  </Tooltip>
+                </div>
+              )}
+              <ChatWrapper />
+            </div>
           )}
         </div>
       </div>

web/app/components/base/icons/assets/vender/other/generator.svg

@@ -0,0 +1,4 @@
+<svg width="14" height="14" viewBox="0 0 14 14" fill="none" xmlns="http://www.w3.org/2000/svg">
+<path opacity="0.5" d="M10.5402 2.95679L10.5402 2.95685C10.4455 3.05146 10.3424 3.13459 10.2314 3.2072C10.3429 3.27923 10.4468 3.36165 10.5422 3.45535L10.5402 2.95679ZM10.5402 2.95679C10.6348 2.86217 10.718 2.75907 10.7906 2.64807C10.8626 2.75955 10.945 2.86339 11.0387 2.95881L11.0388 2.95888C11.1304 3.05224 11.2302 3.13482 11.3377 3.20717C11.2297 3.27895 11.1292 3.36081 11.0367 3.45327L11.0366 3.45333C10.9442 3.5458 10.8623 3.64635 10.7905 3.75431M10.5402 2.95679L10.7905 3.75431M10.7905 3.75431C10.7182 3.64686 10.6356 3.54707 10.5422 3.45538L10.7905 3.75431Z" stroke="#155EEF" stroke-width="1.25"/>
+<path d="M6.99659 2.85105C6.96323 2.55641 6.71414 2.33368 6.41758 2.33337C6.12107 2.33307 5.87146 2.55529 5.83751 2.84987C5.67932 4.2213 5.27205 5.16213 4.6339 5.80028C3.99575 6.43841 3.05492 6.84569 1.68349 7.00389C1.3889 7.03784 1.16669 7.28745 1.16699 7.58396C1.1673 7.88052 1.39002 8.12961 1.68467 8.16297C3.03291 8.31569 3.99517 8.72292 4.64954 9.36546C5.30035 10.0045 5.71535 10.944 5.83593 12.3017C5.86271 12.6029 6.11523 12.8337 6.41763 12.8334C6.72009 12.833 6.97209 12.6016 6.99817 12.3003C7.11367 10.9656 7.52836 10.005 8.18344 9.34982C8.83858 8.69474 9.79922 8.28005 11.1339 8.16455C11.4352 8.13847 11.6666 7.88647 11.667 7.58402C11.6673 7.28162 11.4365 7.02909 11.1353 7.00232C9.77758 6.88174 8.83812 6.46676 8.19908 5.81592C7.55653 5.16155 7.14931 4.19929 6.99659 2.85105Z" fill="#155EEF"/>
+</svg>

web/app/components/base/icons/src/vender/other/Generator.json

@@ -0,0 +1,37 @@
+{
+	"icon": {
+		"type": "element",
+		"isRootNode": true,
+		"name": "svg",
+		"attributes": {
+			"width": "14",
+			"height": "14",
+			"viewBox": "0 0 14 14",
+			"fill": "none",
+			"xmlns": "http://www.w3.org/2000/svg"
+		},
+		"children": [
+			{
+				"type": "element",
+				"name": "path",
+				"attributes": {
+					"opacity": "0.5",
+					"d": "M10.5402 2.95679L10.5402 2.95685C10.4455 3.05146 10.3424 3.13459 10.2314 3.2072C10.3429 3.27923 10.4468 3.36165 10.5422 3.45535L10.5402 2.95679ZM10.5402 2.95679C10.6348 2.86217 10.718 2.75907 10.7906 2.64807C10.8626 2.75955 10.945 2.86339 11.0387 2.95881L11.0388 2.95888C11.1304 3.05224 11.2302 3.13482 11.3377 3.20717C11.2297 3.27895 11.1292 3.36081 11.0367 3.45327L11.0366 3.45333C10.9442 3.5458 10.8623 3.64635 10.7905 3.75431M10.5402 2.95679L10.7905 3.75431M10.7905 3.75431C10.7182 3.64686 10.6356 3.54707 10.5422 3.45538L10.7905 3.75431Z",
+					"stroke": "currentColor",
+					"stroke-width": "1.25"
+				},
+				"children": []
+			},
+			{
+				"type": "element",
+				"name": "path",
+				"attributes": {
+					"d": "M6.99659 2.85105C6.96323 2.55641 6.71414 2.33368 6.41758 2.33337C6.12107 2.33307 5.87146 2.55529 5.83751 2.84987C5.67932 4.2213 5.27205 5.16213 4.6339 5.80028C3.99575 6.43841 3.05492 6.84569 1.68349 7.00389C1.3889 7.03784 1.16669 7.28745 1.16699 7.58396C1.1673 7.88052 1.39002 8.12961 1.68467 8.16297C3.03291 8.31569 3.99517 8.72292 4.64954 9.36546C5.30035 10.0045 5.71535 10.944 5.83593 12.3017C5.86271 12.6029 6.11523 12.8337 6.41763 12.8334C6.72009 12.833 6.97209 12.6016 6.99817 12.3003C7.11367 10.9656 7.52836 10.005 8.18344 9.34982C8.83858 8.69474 9.79922 8.28005 11.1339 8.16455C11.4352 8.13847 11.6666 7.88647 11.667 7.58402C11.6673 7.28162 11.4365 7.02909 11.1353 7.00232C9.77758 6.88174 8.83812 6.46676 8.19908 5.81592C7.55653 5.16155 7.14931 4.19929 6.99659 2.85105Z",
+					"fill": "currentColor"
+				},
+				"children": []
+			}
+		]
+	},
+	"name": "Generator"
+}

web/app/components/base/icons/src/vender/other/Generator.tsx

@@ -0,0 +1,16 @@
+// GENERATE BY script
+// DON NOT EDIT IT MANUALLY
+
+import * as React from 'react'
+import data from './Generator.json'
+import IconBase from '@/app/components/base/icons/IconBase'
+import type { IconBaseProps, IconData } from '@/app/components/base/icons/IconBase'
+
+const Icon = React.forwardRef<React.MutableRefObject<SVGElement>, Omit<IconBaseProps, 'data'>>((
+  props,
+  ref,
+) => <IconBase {...props} ref={ref} data={data as IconData} />)
+
+Icon.displayName = 'Generator'
+
+export default Icon

web/app/components/base/icons/src/vender/other/index.ts

@@ -0,0 +1 @@
+export { default as Generator } from './Generator'

web/app/components/base/icons/src/vender/solid/general/QuestionTriangle.json

@@ -33,7 +33,7 @@
 						"attributes": {
 							"d": "M6.96353 1.5547C7.40657 0.890144 6.93018 0 6.13148 0H0V12L6.96353 1.5547Z",
 							"fill": "currentColor",
-							"fill-opacity": "0"
+							"fill-opacity": "0.5"
 						},
 						"children": []
 					}

web/app/components/base/radio-card/index.tsx

@@ -1,7 +1,6 @@
 'use client'
 import type { FC } from 'react'
 import React from 'react'
-import s from './style.module.css'
 import cn from '@/utils/classnames'
 
 type Props = {
@@ -29,7 +28,12 @@ const RadioCard: FC<Props> = ({
   chosenConfigWrapClassName,
 }) => {
   return (
-    <div className={cn(s.item, isChosen && s.active)}>
+    <div
+      className={cn(
+        'border border-components-option-card-option-border bg-components-option-card-option-bg rounded-xl hover:shadow-xs cursor-pointer',
+        isChosen && 'bg-components-option-card-option-selected-bg border-components-panel-border shadow-xs',
+      )}
+    >
       <div className='flex py-3 pl-3 pr-4' onClick={onChosen}>
         <div className={cn(iconBgClassName, 'mr-3 shrink-0 flex w-8 justify-center h-8 items-center rounded-lg')}>
           {icon}
@@ -40,12 +44,15 @@ const RadioCard: FC<Props> = ({
         </div>
         {!noRadio && (
           <div className='shrink-0 flex items-center h-8'>
-            <div className={s.radio}></div>
+            <div className={cn(
+              'w-4 h-4 border border-components-radio-border bg-components-radio-bg shadow-xs rounded-full',
+              isChosen && 'border-[5px] border-components-radio-border-checked',
+            )}></div>
           </div>
         )}
       </div>
       {((isChosen && chosenConfig) || noRadio) && (
-        <div className={cn(chosenConfigWrapClassName, 'pt-2 px-14 pb-6 border-t border-gray-200')}>
+        <div className={cn(chosenConfigWrapClassName, 'p-3 border-t border-gray-200')}>
           {chosenConfig}
         </div>
       )}

web/app/components/base/radio-card/simple/index.tsx

@@ -6,7 +6,7 @@ import cn from '@/utils/classnames'
 
 type Props = {
   className?: string
-  title: string
+  title: string | JSX.Element | null
   description: string
   isChosen: boolean
   onChosen: () => void

web/app/components/base/radio-card/style.module.css

@@ -1,25 +0,0 @@
-.item {
-  @apply relative rounded-xl border border-gray-100 cursor-pointer;
-  background-color: #fcfcfd;
-}
-
-.item.active {
-  border-width: 1.5px;
-  border-color: #528BFF;
-  box-shadow: 0px 1px 3px rgba(16, 24, 40, 0.1), 0px 1px 2px rgba(16, 24, 40, 0.06);
-}
-
-.item:hover {
-  background-color: #ffffff;
-  border-color: #B2CCFF;
-  box-shadow: 0px 12px 16px -4px rgba(16, 24, 40, 0.08), 0px 4px 6px -2px rgba(16, 24, 40, 0.03);
-}
-
-.radio {
-  @apply w-4 h-4 border-[2px] border-gray-200 rounded-full;
-}
-
-.item.active .radio {
-  border-width: 5px;
-  border-color: #155EEF;
-}

web/app/components/base/slider/index.tsx

@@ -4,6 +4,8 @@ import './style.css'
 
 type ISliderProps = {
   className?: string
+  thumbClassName?: string
+  trackClassName?: string
   value: number
   max?: number
   min?: number
@@ -12,16 +14,26 @@ type ISliderProps = {
   onChange: (value: number) => void
 }
 
-const Slider: React.FC<ISliderProps> = ({ className, max, min, step, value, disabled, onChange }) => {
+const Slider: React.FC<ISliderProps> = ({
+  className,
+  thumbClassName,
+  trackClassName,
+  max,
+  min,
+  step,
+  value,
+  disabled,
+  onChange,
+}) => {
   return <ReactSlider
     disabled={disabled}
     value={isNaN(value) ? 0 : value}
     min={min || 0}
     max={max || 100}
     step={step || 1}
-    className={cn(className, 'slider')}
-    thumbClassName="slider-thumb"
-    trackClassName="slider-track"
+    className={cn('slider', className)}
+    thumbClassName={cn('slider-thumb', thumbClassName)}
+    trackClassName={cn('slider-track', trackClassName)}
     onChange={onChange}
   />
 }

web/app/components/base/tooltip-plus/index.tsx

@@ -13,6 +13,7 @@ export type TooltipProps = {
   hideArrow?: boolean
   popupClassName?: string
   offset?: OffsetOptions
+  asChild?: boolean
 }
 
 const arrow = (
@@ -27,6 +28,7 @@ const Tooltip: FC<TooltipProps> = ({
   hideArrow,
   popupClassName,
   offset,
+  asChild,
 }) => {
   const [open, setOpen] = useState(false)
   const [isHoverPopup, {
@@ -79,6 +81,7 @@ const Tooltip: FC<TooltipProps> = ({
           }
         }}
         onMouseLeave={() => triggerMethod === 'hover' && handleLeave(true)}
+        asChild={asChild}
       >
         {children}
       </PortalToFollowElemTrigger>

web/app/components/datasets/common/check-rerank-model.ts

@@ -3,6 +3,7 @@ import type {
   DefaultModelResponse,
   Model,
 } from '@/app/components/header/account-setting/model-provider-page/declarations'
+import { RerankingModeEnum } from '@/models/datasets'
 
 export const isReRankModelSelected = ({
   rerankDefaultModel,
@@ -32,7 +33,7 @@ export const isReRankModelSelected = ({
 
   if (
     indexMethod === 'high_quality'
-    && (retrievalConfig.reranking_enable || retrievalConfig.search_method === RETRIEVE_METHOD.hybrid)
+    && (retrievalConfig.search_method === RETRIEVE_METHOD.hybrid && retrievalConfig.reranking_mode !== RerankingModeEnum.WeightedScore)
     && !rerankModelSelected
   )
     return false

web/app/components/datasets/common/retrieval-param-config/index.tsx

@@ -15,6 +15,11 @@ import type { RetrievalConfig } from '@/types/app'
 import ModelSelector from '@/app/components/header/account-setting/model-provider-page/model-selector'
 import { useModelListAndDefaultModel } from '@/app/components/header/account-setting/model-provider-page/hooks'
 import { ModelTypeEnum } from '@/app/components/header/account-setting/model-provider-page/declarations'
+import {
+  RerankingModeEnum,
+  WeightedScoreEnum,
+} from '@/models/datasets'
+import WeightedScore from '@/app/components/app/configuration/dataset-config/params-config/weighted-score'
 
 type Props = {
   type: RETRIEVE_METHOD
@@ -34,6 +39,7 @@ const RetrievalParamConfig: FC<Props> = ({
     defaultModel: rerankDefaultModel,
     modelList: rerankModelList,
   } = useModelListAndDefaultModel(ModelTypeEnum.rerank)
+  const isHybridSearch = type === RETRIEVE_METHOD.hybrid
 
   const rerankModel = (() => {
     if (value.reranking_model) {
@@ -50,9 +56,47 @@ const RetrievalParamConfig: FC<Props> = ({
     }
   })()
 
+  const handleChangeRerankMode = (v: RerankingModeEnum) => {
+    if (v === value.reranking_mode)
+      return
+
+    const result = {
+      ...value,
+      reranking_mode: v,
+    }
+
+    if (!result.weights && v === RerankingModeEnum.WeightedScore) {
+      result.weights = {
+        weight_type: WeightedScoreEnum.Customized,
+        vector_setting: {
+          vector_weight: 0.5,
+          embedding_provider_name: '',
+          embedding_model_name: '',
+        },
+        keyword_setting: {
+          keyword_weight: 0.5,
+        },
+      }
+    }
+    onChange(result)
+  }
+
+  const rerankingModeOptions = [
+    {
+      value: RerankingModeEnum.WeightedScore,
+      label: t('dataset.weightedScore.title'),
+      tips: t('dataset.weightedScore.description'),
+    },
+    {
+      value: RerankingModeEnum.RerankingModel,
+      label: t('common.modelProvider.rerankModel.key'),
+      tips: t('common.modelProvider.rerankModel.tip'),
+    },
+  ]
+
   return (
     <div>
-      {!isEconomical && (
+      {!isEconomical && !isHybridSearch && (
         <div>
           <div className='flex h-8 items-center text-[13px] font-medium text-gray-900 space-x-2'>
             {canToggleRerankModalEnable && (
@@ -75,10 +119,10 @@ const RetrievalParamConfig: FC<Props> = ({
             </div>
           </div>
           <ModelSelector
-            triggerClassName={`${!value.reranking_enable && type !== RETRIEVE_METHOD.hybrid && '!opacity-60 !cursor-not-allowed'}`}
+            triggerClassName={`${!value.reranking_enable && '!opacity-60 !cursor-not-allowed'}`}
             defaultModel={rerankModel && { provider: rerankModel.provider_name, model: rerankModel.model_name }}
             modelList={rerankModelList}
-            readonly={!value.reranking_enable && type !== RETRIEVE_METHOD.hybrid}
+            readonly={!value.reranking_enable}
             onSelect={(v) => {
               onChange({
                 ...value,
@@ -91,40 +135,152 @@ const RetrievalParamConfig: FC<Props> = ({
           />
         </div>
       )}
-
-      <div className={cn(!isEconomical && 'mt-4', 'flex space-between space-x-6')}>
-        <TopKItem
-          className='grow'
-          value={value.top_k}
-          onChange={(_key, v) => {
-            onChange({
-              ...value,
-              top_k: v,
-            })
-          }}
-          enable={true}
-        />
-        {(!isEconomical && !(value.search_method === RETRIEVE_METHOD.fullText && !value.reranking_enable)) && (
-          <ScoreThresholdItem
-            className='grow'
-            value={value.score_threshold}
-            onChange={(_key, v) => {
-              onChange({
-                ...value,
-                score_threshold: v,
-              })
-            }}
-            enable={value.score_threshold_enabled}
-            hasSwitch={true}
-            onSwitchChange={(_key, v) => {
-              onChange({
-                ...value,
-                score_threshold_enabled: v,
-              })
-            }}
-          />
-        )}
-      </div>
+      {
+        !isHybridSearch && (
+          <div className={cn(!isEconomical && 'mt-4', 'flex space-between space-x-6')}>
+            <TopKItem
+              className='grow'
+              value={value.top_k}
+              onChange={(_key, v) => {
+                onChange({
+                  ...value,
+                  top_k: v,
+                })
+              }}
+              enable={true}
+            />
+            {(!isEconomical && !(value.search_method === RETRIEVE_METHOD.fullText && !value.reranking_enable)) && (
+              <ScoreThresholdItem
+                className='grow'
+                value={value.score_threshold}
+                onChange={(_key, v) => {
+                  onChange({
+                    ...value,
+                    score_threshold: v,
+                  })
+                }}
+                enable={value.score_threshold_enabled}
+                hasSwitch={true}
+                onSwitchChange={(_key, v) => {
+                  onChange({
+                    ...value,
+                    score_threshold_enabled: v,
+                  })
+                }}
+              />
+            )}
+          </div>
+        )
+      }
+      {
+        isHybridSearch && (
+          <>
+            <div className='flex items-center justify-between'>
+              {
+                rerankingModeOptions.map(option => (
+                  <div
+                    key={option.value}
+                    className={cn(
+                      'flex items-center justify-center mb-4 w-[calc((100%-8px)/2)] h-8 rounded-lg border border-components-option-card-option-border bg-components-option-card-option-bg cursor-pointer system-sm-medium text-text-secondary',
+                      value.reranking_mode === RerankingModeEnum.WeightedScore && option.value === RerankingModeEnum.WeightedScore && 'border-[1.5px] border-components-option-card-option-selected-border bg-components-option-card-option-selected-bg text-text-primary',
+                      value.reranking_mode !== RerankingModeEnum.WeightedScore && option.value !== RerankingModeEnum.WeightedScore && 'border-[1.5px] border-components-option-card-option-selected-border bg-components-option-card-option-selected-bg text-text-primary',
+                    )}
+                    onClick={() => handleChangeRerankMode(option.value)}
+                  >
+                    <div className='truncate'>{option.label}</div>
+                    <Tooltip
+                      popupContent={<div className='w-[200px]'>{option.tips}</div>}
+                      hideArrow
+                    >
+                      <RiQuestionLine className='ml-0.5 w-3.5 h-4.5 text-text-quaternary' />
+                    </Tooltip>
+                  </div>
+                ))
+              }
+            </div>
+            {
+              value.reranking_mode === RerankingModeEnum.WeightedScore && (
+                <WeightedScore
+                  value={{
+                    type: value.weights!.weight_type,
+                    value: [
+                      value.weights!.vector_setting.vector_weight,
+                      value.weights!.keyword_setting.keyword_weight,
+                    ],
+                  }}
+                  onChange={(v) => {
+                    onChange({
+                      ...value,
+                      weights: {
+                        ...value.weights!,
+                        weight_type: v.type,
+                        vector_setting: {
+                          ...value.weights!.vector_setting,
+                          vector_weight: v.value[0],
+                        },
+                        keyword_setting: {
+                          ...value.weights!.keyword_setting,
+                          keyword_weight: v.value[1],
+                        },
+                      },
+                    })
+                  }}
+                />
+              )
+            }
+            {
+              value.reranking_mode !== RerankingModeEnum.WeightedScore && (
+                <ModelSelector
+                  triggerClassName={`${!value.reranking_enable && '!opacity-60 !cursor-not-allowed'}`}
+                  defaultModel={rerankModel && { provider: rerankModel.provider_name, model: rerankModel.model_name }}
+                  modelList={rerankModelList}
+                  readonly={!value.reranking_enable}
+                  onSelect={(v) => {
+                    onChange({
+                      ...value,
+                      reranking_model: {
+                        reranking_provider_name: v.provider,
+                        reranking_model_name: v.model,
+                      },
+                    })
+                  }}
+                />
+              )
+            }
+            <div className={cn(!isEconomical && 'mt-4', 'flex space-between space-x-6')}>
+              <TopKItem
+                className='grow'
+                value={value.top_k}
+                onChange={(_key, v) => {
+                  onChange({
+                    ...value,
+                    top_k: v,
+                  })
+                }}
+                enable={true}
+              />
+              <ScoreThresholdItem
+                className='grow'
+                value={value.score_threshold}
+                onChange={(_key, v) => {
+                  onChange({
+                    ...value,
+                    score_threshold: v,
+                  })
+                }}
+                enable={value.score_threshold_enabled}
+                hasSwitch={true}
+                onSwitchChange={(_key, v) => {
+                  onChange({
+                    ...value,
+                    score_threshold_enabled: v,
+                  })
+                }}
+              />
+            </div>
+          </>
+        )
+      }
     </div>
   )
 }

web/app/components/datasets/settings/form/index.tsx

@@ -113,6 +113,10 @@ const Form = () => {
       retrievalConfig,
       indexMethod,
     })
+    if (postRetrievalConfig.weights) {
+      postRetrievalConfig.weights.vector_setting.embedding_provider_name = currentDataset?.embedding_model_provider || ''
+      postRetrievalConfig.weights.vector_setting.embedding_model_name = currentDataset?.embedding_model || ''
+    }
     try {
       setLoading(true)
       const requestParams = {

web/app/components/header/account-about/index.tsx

@@ -45,7 +45,7 @@ export default function AccountAbout({
                 IS_CE_EDITION
                   ? <Link href={'https://github.com/langgenius/dify/blob/main/LICENSE'} target='_blank' rel='noopener noreferrer'>Open Source License</Link>
                   : <>
-                    <Link href='https://dify.ai/privacy' target='_blank' rel='noopener noreferrer'>Privacy Policy</Link>,
+                    <Link href='https://dify.ai/privacy' target='_blank' rel='noopener noreferrer'>Privacy Policy</Link>,<span> </span>
                     <Link href='https://dify.ai/terms' target='_blank' rel='noopener noreferrer'>Terms of Service</Link>
                   </>
               }

web/app/components/tools/add-tool-modal/category.tsx

@@ -22,7 +22,6 @@ const Icon = ({ svgString, active }: { svgString: string; active: boolean }) =>
       return null
     const parser = new DOMParser()
     const doc = parser.parseFromString(svg, 'image/svg+xml')
-    console.log(doc.documentElement)
     return doc.documentElement
   }
   useMount(() => {

web/app/components/workflow/index.tsx

@@ -248,6 +248,7 @@ const Workflow: FC<WorkflowProps> = memo(({
   } = useWorkflow()
   const { handleStartWorkflowRun } = useWorkflowStartRun()
   const {
+    exportCheck,
     handleExportDSL,
   } = useDSL()
 
@@ -334,7 +335,7 @@ const Workflow: FC<WorkflowProps> = memo(({
         showImportDSLModal && (
           <UpdateDSLModal
             onCancel={() => setShowImportDSLModal(false)}
-            onBackup={handleExportDSL}
+            onBackup={exportCheck}
             onImport={handlePaneContextmenuCancel}
           />
         )

web/app/components/workflow/nodes/_base/components/prompt/editor.tsx

@@ -9,6 +9,7 @@ import { useTranslation } from 'react-i18next'
 import { useBoolean } from 'ahooks'
 import { BlockEnum, EditionType } from '../../../../types'
 import type {
+  ModelConfig,
   Node,
   NodeOutPutVar,
   Variable,
@@ -16,6 +17,7 @@ import type {
 
 import Wrap from '../editor/wrap'
 import { CodeLanguage } from '../../../code/types'
+import PromptGeneratorBtn from '../../../llm/components/prompt-generator-btn'
 import cn from '@/utils/classnames'
 import ToggleExpandBtn from '@/app/components/workflow/nodes/_base/components/toggle-expand-btn'
 import useToggleExpend from '@/app/components/workflow/nodes/_base/hooks/use-toggle-expend'
@@ -28,6 +30,7 @@ import s from '@/app/components/app/configuration/config-prompt/style.module.css
 import { useEventEmitterContextContext } from '@/context/event-emitter'
 import { PROMPT_EDITOR_INSERT_QUICKLY } from '@/app/components/base/prompt-editor/plugins/update-block'
 import { Variable02 } from '@/app/components/base/icons/src/vender/solid/development'
+import ActionButton from '@/app/components/base/action-button'
 import TooltipPlus from '@/app/components/base/tooltip-plus'
 import CodeEditor from '@/app/components/workflow/nodes/_base/components/editor/code-editor/editor-support-vars'
 import Switch from '@/app/components/base/switch'
@@ -55,6 +58,9 @@ type Props = {
   }
   nodesOutputVars?: NodeOutPutVar[]
   availableNodes?: Node[]
+  isSupportPromptGenerator?: boolean
+  onGenerated?: (prompt: string) => void
+  modelConfig?: ModelConfig
   // for jinja
   isSupportJinja?: boolean
   editionType?: EditionType
@@ -80,11 +86,14 @@ const Editor: FC<Props> = ({
   hasSetBlockStatus,
   nodesOutputVars,
   availableNodes = [],
+  isSupportPromptGenerator,
   isSupportJinja,
   editionType,
   onEditionTypeChange,
   varList = [],
   handleAddVariable,
+  onGenerated,
+  modelConfig,
 }) => {
   const { t } = useTranslation()
   const { eventEmitter } = useEventEmitterContextContext()
@@ -120,13 +129,17 @@ const Editor: FC<Props> = ({
     <Wrap className={cn(className, wrapClassName)} style={wrapStyle} isInNode isExpand={isExpand}>
       <div ref={ref} className={cn(isFocus ? s.gradientBorder : 'bg-gray-100', isExpand && 'h-full', '!rounded-[9px] p-0.5')}>
         <div className={cn(isFocus ? 'bg-gray-50' : 'bg-gray-100', isExpand && 'h-full flex flex-col', 'rounded-lg')}>
-          <div className={cn(headerClassName, 'pt-1 pl-3 pr-2 flex justify-between h-6 items-center')}>
+          <div className={cn(headerClassName, 'pt-1 pl-3 pr-2 flex justify-between items-center')}>
             <div className='leading-4 text-xs font-semibold text-gray-700 uppercase'>{title}</div>
             <div className='flex items-center'>
               <div className='leading-[18px] text-xs font-medium text-gray-500'>{value?.length || 0}</div>
+              {isSupportPromptGenerator && (
+                <PromptGeneratorBtn className='ml-[5px]' onGenerated={onGenerated} modelConfig={modelConfig} />
+              )}
+
               <div className='w-px h-3 ml-2 mr-2 bg-gray-200'></div>
               {/* Operations */}
-              <div className='flex items-center space-x-2'>
+              <div className='flex items-center space-x-[2px]'>
                 {isSupportJinja && (
                   <TooltipPlus
                     popupContent={
@@ -153,19 +166,28 @@ const Editor: FC<Props> = ({
                 {!readOnly && (
                   <TooltipPlus
                     popupContent={`${t('workflow.common.insertVarTip')}`}
+                    asChild
                   >
-                    <Variable02 className='w-3.5 h-3.5 text-gray-500 cursor-pointer' onClick={handleInsertVariable} />
+                    <ActionButton onClick={handleInsertVariable}>
+                      <Variable02 className='w-4 h-4' />
+                    </ActionButton>
                   </TooltipPlus>
                 )}
                 {showRemove && (
-                  <RiDeleteBinLine className='w-3.5 h-3.5 text-gray-500 cursor-pointer' onClick={onRemove} />
+                  <ActionButton onClick={onRemove}>
+                    <RiDeleteBinLine className='w-4 h-4' />
+                  </ActionButton>
                 )}
                 {!isCopied
                   ? (
-                    <Clipboard className='w-3.5 h-3.5 text-gray-500 cursor-pointer' onClick={handleCopy} />
+                    <ActionButton onClick={handleCopy}>
+                      <Clipboard className='w-4 h-4' />
+                    </ActionButton>
                   )
                   : (
-                    <ClipboardCheck className='mx-1 w-3.5 h-3.5 text-gray-500' />
+                    <ActionButton>
+                      <ClipboardCheck className='w-4 h-4' />
+                    </ActionButton>
                   )
                 }
                 <ToggleExpandBtn isExpand={isExpand} onExpandChange={setIsExpand} />

web/app/components/workflow/nodes/_base/components/selector.tsx

@@ -63,7 +63,7 @@ const TypeSelector: FC<Props> = ({
           <div
             onClick={toggleShow}
             className={cn(showOption && 'bg-black/5', 'flex items-center h-5 pl-1 pr-0.5 rounded-md text-xs font-semibold text-gray-700 cursor-pointer hover:bg-black/5')}>
-            <div className={cn(triggerClassName, 'text-sm font-semibold', uppercase && 'uppercase', noValue && 'text-gray-400')}>{!noValue ? item?.label : placeholder}</div>
+            <div className={cn(triggerClassName, 'text-xs font-semibold', uppercase && 'uppercase', noValue && 'text-gray-400')}>{!noValue ? item?.label : placeholder}</div>
             {!readonly && <DropDownIcon className='w-3 h-3 ' />}
           </div>
         )}

web/app/components/workflow/nodes/_base/components/toggle-expand-btn.tsx

@@ -5,6 +5,7 @@ import {
   RiCollapseDiagonalLine,
   RiExpandDiagonalLine,
 } from '@remixicon/react'
+import ActionButton from '@/app/components/base/action-button'
 
 type Props = {
   isExpand: boolean
@@ -21,7 +22,9 @@ const ExpandBtn: FC<Props> = ({
 
   const Icon = isExpand ? RiCollapseDiagonalLine : RiExpandDiagonalLine
   return (
-    <Icon className='w-3.5 h-3.5 text-gray-500 cursor-pointer' onClick={handleToggle} />
+    <ActionButton onClick={handleToggle}>
+      <Icon className='w-4 h-4' />
+    </ActionButton>
   )
 }
 export default React.memo(ExpandBtn)

web/app/components/workflow/nodes/_base/components/variable/var-reference-picker.tsx

@@ -146,7 +146,10 @@ const VarReferencePicker: FC<Props> = ({
   const varName = useMemo(() => {
     if (hasValue) {
       const isSystem = isSystemVar(value as ValueSelector)
-      const varName = value.length >= 3 ? (value as ValueSelector).slice(-2).join('.') : value[value.length - 1]
+      let varName = ''
+      if (Array.isArray(value))
+        varName = value.length >= 3 ? (value as ValueSelector).slice(-2).join('.') : value[value.length - 1]
+
       return `${isSystem ? 'sys.' : ''}${varName}`
     }
     return ''

web/app/components/workflow/nodes/knowledge-retrieval/components/dataset-item.tsx

@@ -4,15 +4,17 @@ import React, { useCallback } from 'react'
 import { useBoolean } from 'ahooks'
 import {
   RiDeleteBinLine,
+  RiEditLine,
 } from '@remixicon/react'
 import type { DataSet } from '@/models/datasets'
 import { DataSourceType } from '@/models/datasets'
-import { Settings01 } from '@/app/components/base/icons/src/vender/line/general'
 import FileIcon from '@/app/components/base/file-icon'
 import { Folder } from '@/app/components/base/icons/src/vender/solid/files'
 import SettingsModal from '@/app/components/app/configuration/dataset-config/settings-modal'
 import Drawer from '@/app/components/base/drawer'
 import useBreakpoints, { MediaType } from '@/hooks/use-breakpoints'
+import Badge from '@/app/components/base/badge'
+import { useKnowledge } from '@/hooks/use-knowledge'
 
 type Props = {
   payload: DataSet
@@ -29,6 +31,7 @@ const DatasetItem: FC<Props> = ({
 }) => {
   const media = useBreakpoints()
   const isMobile = media === MediaType.mobile
+  const { formatIndexingTechniqueAndMethod } = useKnowledge()
 
   const [isShowSettingsModal, {
     setTrue: showSettingsModal,
@@ -62,7 +65,7 @@ const DatasetItem: FC<Props> = ({
             className='flex items-center justify-center w-6 h-6 hover:bg-black/5 rounded-md cursor-pointer'
             onClick={showSettingsModal}
           >
-            <Settings01 className='w-4 h-4 text-gray-500' />
+            <RiEditLine className='w-4 h-4 text-gray-500' />
           </div>
           <div
             className='flex items-center justify-center w-6 h-6 hover:bg-black/5 rounded-md cursor-pointer'
@@ -72,6 +75,10 @@ const DatasetItem: FC<Props> = ({
           </div>
         </div>
       )}
+      <Badge
+        className='group-hover/dataset-item:hidden shrink-0'
+        text={formatIndexingTechniqueAndMethod(payload.indexing_technique, payload.retrieval_model_dict?.search_method)}
+      />
 
       {isShowSettingsModal && (
         <Drawer isOpen={isShowSettingsModal} onClose={hideSettingsModal} footer={null} mask={isMobile} panelClassname='mt-16 mx-2 sm:mr-2 mb-3 !p-0 !max-w-[640px] rounded-xl'>