feat: Support image generate model

apps/application/flow/step_node/__init__.py

@@ -18,6 +18,7 @@ from .reranker_node import *
 
 from .document_extract_node import *
 from .image_understand_step_node import *
+from .image_generate_step_node import *
 
 from .search_dataset_node import *
 from .start_node import *
@@ -25,7 +26,7 @@ from .start_node import *
 node_list = [BaseStartStepNode, BaseChatNode, BaseSearchDatasetNode, BaseQuestionNode, BaseConditionNode, BaseReplyNode,
              BaseFunctionNodeNode, BaseFunctionLibNodeNode, BaseRerankerNode, BaseApplicationNode,
              BaseDocumentExtractNode,
-             BaseImageUnderstandNode, BaseFormNode]
+             BaseImageUnderstandNode, BaseImageGenerateNode, BaseFormNode]
 
 
 def get_node(node_type):

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

@@ -0,0 +1,3 @@
+# coding=utf-8
+
+from .impl import *

apps/application/flow/step_node/image_generate_step_node/i_image_generate_node.py

@@ -0,0 +1,37 @@
+# coding=utf-8
+
+from typing import Type
+
+from rest_framework import serializers
+
+from application.flow.i_step_node import INode, NodeResult
+from common.util.field_message import ErrMessage
+
+
+class ImageGenerateNodeSerializer(serializers.Serializer):
+    model_id = serializers.CharField(required=True, error_messages=ErrMessage.char("模型id"))
+
+    prompt = serializers.CharField(required=True, error_messages=ErrMessage.char("提示词(正向)"))
+
+    negative_prompt = serializers.CharField(required=False, default='', error_messages=ErrMessage.char("提示词(负向)"))
+    # 多轮对话数量
+    dialogue_number = serializers.IntegerField(required=True, error_messages=ErrMessage.integer("多轮对话数量"))
+
+    dialogue_type = serializers.CharField(required=True, error_messages=ErrMessage.char("对话存储类型"))
+
+    is_result = serializers.BooleanField(required=False, error_messages=ErrMessage.boolean('是否返回内容'))
+
+
+class IImageGenerateNode(INode):
+    type = 'image-generate-node'
+
+    def get_node_params_serializer_class(self) -> Type[serializers.Serializer]:
+        return ImageGenerateNodeSerializer
+
+    def _run(self):
+        return self.execute(**self.node_params_serializer.data, **self.flow_params_serializer.data)
+
+    def execute(self, model_id, prompt, negative_prompt, dialogue_number, dialogue_type, history_chat_record, chat_id,
+                chat_record_id,
+                **kwargs) -> NodeResult:
+        pass

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

@@ -0,0 +1,3 @@
+# coding=utf-8
+
+from .base_image_generate_node import BaseImageGenerateNode

apps/application/flow/step_node/image_generate_step_node/impl/base_image_generate_node.py

@@ -0,0 +1,101 @@
+# coding=utf-8
+from functools import reduce
+from typing import List
+
+from langchain_core.messages import BaseMessage, HumanMessage, AIMessage
+
+from application.flow.i_step_node import NodeResult
+from application.flow.step_node.image_generate_step_node.i_image_generate_node import IImageGenerateNode
+from setting.models_provider.tools import get_model_instance_by_model_user_id
+
+
+class BaseImageGenerateNode(IImageGenerateNode):
+    def save_context(self, details, workflow_manage):
+        self.context['answer'] = details.get('answer')
+        self.context['question'] = details.get('question')
+        self.answer_text = details.get('answer')
+
+    def execute(self, model_id, prompt, negative_prompt, dialogue_number, dialogue_type, history_chat_record, chat_id,
+                chat_record_id,
+                **kwargs) -> NodeResult:
+
+        tti_model = get_model_instance_by_model_user_id(model_id, self.flow_params_serializer.data.get('user_id'))
+        history_message = self.get_history_message(history_chat_record, dialogue_number)
+        self.context['history_message'] = history_message
+        question = self.generate_prompt_question(prompt)
+        self.context['question'] = question
+        message_list = self.generate_message_list(question, history_message)
+        self.context['message_list'] = message_list
+        self.context['dialogue_type'] = dialogue_type
+        print(message_list)
+        print(negative_prompt)
+        image_urls = tti_model.generate_image(question, negative_prompt)
+        self.context['image_list'] = image_urls
+        answer = '\n'.join([f"![Image]({path})" for path in image_urls])
+        return NodeResult({'answer': answer, 'chat_model': tti_model, 'message_list': message_list,
+                           'image': [{'file_id': path.split('/')[-1], 'file_url': path} for path in file_urls],
+                           'history_message': history_message, 'question': question}, {})
+
+    def generate_history_ai_message(self, chat_record):
+        for val in chat_record.details.values():
+            if self.node.id == val['node_id'] and 'image_list' in val:
+                if val['dialogue_type'] == 'WORKFLOW':
+                    return chat_record.get_ai_message()
+                return AIMessage(content=val['answer'])
+        return chat_record.get_ai_message()
+
+    def get_history_message(self, history_chat_record, dialogue_number):
+        start_index = len(history_chat_record) - dialogue_number
+        history_message = reduce(lambda x, y: [*x, *y], [
+            [self.generate_history_human_message(history_chat_record[index]),
+             self.generate_history_ai_message(history_chat_record[index])]
+            for index in
+            range(start_index if start_index > 0 else 0, len(history_chat_record))], [])
+        return history_message
+
+    def generate_history_human_message(self, chat_record):
+
+        for data in chat_record.details.values():
+            if self.node.id == data['node_id'] and 'image_list' in data:
+                image_list = data['image_list']
+                if len(image_list) == 0 or data['dialogue_type'] == 'WORKFLOW':
+                    return HumanMessage(content=chat_record.problem_text)
+                return HumanMessage(content=data['question'])
+        return HumanMessage(content=chat_record.problem_text)
+
+    def generate_prompt_question(self, prompt):
+        return self.workflow_manage.generate_prompt(prompt)
+
+    def generate_message_list(self, question: str, history_message):
+        return [
+            *history_message,
+            question
+        ]
+
+    @staticmethod
+    def reset_message_list(message_list: List[BaseMessage], answer_text):
+        result = [{'role': 'user' if isinstance(message, HumanMessage) else 'ai', 'content': message.content} for
+                  message
+                  in
+                  message_list]
+        result.append({'role': 'ai', 'content': answer_text})
+        return result
+
+    def get_details(self, index: int, **kwargs):
+        return {
+            'name': self.node.properties.get('stepName'),
+            "index": index,
+            'run_time': self.context.get('run_time'),
+            'history_message': [{'content': message.content, 'role': message.type} for message in
+                                (self.context.get('history_message') if self.context.get(
+                                    'history_message') is not None else [])],
+            'question': self.context.get('question'),
+            'answer': self.context.get('answer'),
+            'type': self.node.type,
+            'message_tokens': self.context.get('message_tokens'),
+            'answer_tokens': self.context.get('answer_tokens'),
+            'status': self.status,
+            'err_message': self.err_message,
+            'image_list': self.context.get('image_list'),
+            'dialogue_type': self.context.get('dialogue_type')
+        }

apps/application/flow/workflow_manage.py

@@ -54,7 +54,7 @@ class Node:
 
 
 end_nodes = ['ai-chat-node', 'reply-node', 'function-node', 'function-lib-node', 'application-node',
-             'image-understand-node']
+             'image-understand-node', 'image-generate-node']
 
 
 class Flow:

apps/common/util/common.py

@@ -8,9 +8,12 @@
 """
 import hashlib
 import importlib
+import mimetypes
+import io
 from functools import reduce
 from typing import Dict, List
 
+from django.core.files.uploadedfile import InMemoryUploadedFile
 from django.db.models import QuerySet
 
 from ..exception.app_exception import AppApiException
@@ -111,3 +114,25 @@ def bulk_create_in_batches(model, data, batch_size=1000):
         batch = data[i:i + batch_size]
         model.objects.bulk_create(batch)
 
+
+def bytes_to_uploaded_file(file_bytes, file_name="file.txt"):
+    content_type, _ = mimetypes.guess_type(file_name)
+    if content_type is None:
+        # 如果未能识别，设置为默认的二进制文件类型
+        content_type = "application/octet-stream"
+    # 创建一个内存中的字节流对象
+    file_stream = io.BytesIO(file_bytes)
+
+    # 获取文件大小
+    file_size = len(file_bytes)
+
+    # 创建 InMemoryUploadedFile 对象
+    uploaded_file = InMemoryUploadedFile(
+        file=file_stream,
+        field_name=None,
+        name=file_name,
+        content_type=content_type,
+        size=file_size,
+        charset=None,
+    )
+    return uploaded_file

apps/setting/models_provider/base_model_provider.py

@@ -150,6 +150,7 @@ class ModelTypeConst(Enum):
     STT = {'code': 'STT', 'message': '语音识别'}
     TTS = {'code': 'TTS', 'message': '语音合成'}
     IMAGE = {'code': 'IMAGE', 'message': '图片理解'}
+    TTI = {'code': 'TTI', 'message': '图片生成'}
     RERANKER = {'code': 'RERANKER', 'message': '重排模型'}
 
 

apps/setting/models_provider/impl/base_tti.py

@@ -0,0 +1,14 @@
+# coding=utf-8
+from abc import abstractmethod
+
+from pydantic import BaseModel
+
+
+class BaseTextToImage(BaseModel):
+    @abstractmethod
+    def check_auth(self):
+        pass
+
+    @abstractmethod
+    def generate_image(self, prompt: str, negative_prompt: str = None):
+        pass

apps/setting/models_provider/impl/openai_model_provider/credential/tti.py

@@ -0,0 +1,47 @@
+# coding=utf-8
+import base64
+import os
+from typing import Dict
+
+from langchain_core.messages import HumanMessage
+
+from common import forms
+from common.exception.app_exception import AppApiException
+from common.forms import BaseForm
+from setting.models_provider.base_model_provider import BaseModelCredential, ValidCode
+
+
+class OpenAITextToImageModelCredential(BaseForm, BaseModelCredential):
+    api_base = forms.TextInputField('API 域名', required=True)
+    api_key = forms.PasswordInputField('API Key', required=True)
+
+    def is_valid(self, model_type: str, model_name, model_credential: Dict[str, object], provider,
+                 raise_exception=False):
+        model_type_list = provider.get_model_type_list()
+        if not any(list(filter(lambda mt: mt.get('value') == model_type, model_type_list))):
+            raise AppApiException(ValidCode.valid_error.value, f'{model_type} 模型类型不支持')
+
+        for key in ['api_base', 'api_key']:
+            if key not in model_credential:
+                if raise_exception:
+                    raise AppApiException(ValidCode.valid_error.value, f'{key} 字段为必填字段')
+                else:
+                    return False
+        try:
+            model = provider.get_model(model_type, model_name, model_credential)
+            res = model.check_auth()
+            print(res)
+        except Exception as e:
+            if isinstance(e, AppApiException):
+                raise e
+            if raise_exception:
+                raise AppApiException(ValidCode.valid_error.value, f'校验失败,请检查参数是否正确: {str(e)}')
+            else:
+                return False
+        return True
+
+    def encryption_dict(self, model: Dict[str, object]):
+        return {**model, 'api_key': super().encryption(model.get('api_key', ''))}
+
+    def get_model_params_setting_form(self, model_name):
+        pass

apps/setting/models_provider/impl/openai_model_provider/model/tti.py

@@ -0,0 +1,67 @@
+from typing import Dict
+
+import requests
+from langchain_core.messages import HumanMessage
+from langchain_openai import ChatOpenAI
+from openai import OpenAI
+
+from common.config.tokenizer_manage_config import TokenizerManage
+from common.util.common import bytes_to_uploaded_file
+from dataset.serializers.file_serializers import FileSerializer
+from setting.models_provider.base_model_provider import MaxKBBaseModel
+from setting.models_provider.impl.base_tti import BaseTextToImage
+
+
+def custom_get_token_ids(text: str):
+    tokenizer = TokenizerManage.get_tokenizer()
+    return tokenizer.encode(text)
+
+
+class OpenAITextToImage(MaxKBBaseModel, BaseTextToImage):
+    api_base: str
+    api_key: str
+    model: str
+    params: dict
+
+    def __init__(self, **kwargs):
+        super().__init__(**kwargs)
+        self.api_key = kwargs.get('api_key')
+        self.api_base = kwargs.get('api_base')
+        self.model = kwargs.get('model')
+        self.params = kwargs.get('params')
+
+    @staticmethod
+    def new_instance(model_type, model_name, model_credential: Dict[str, object], **model_kwargs):
+        optional_params = {'params': {}}
+        for key, value in model_kwargs.items():
+            if key not in ['model_id', 'use_local', 'streaming']:
+                optional_params['params'][key] = value
+        return OpenAITextToImage(
+            model=model_name,
+            api_base=model_credential.get('api_base'),
+            api_key=model_credential.get('api_key'),
+            **optional_params,
+        )
+
+    def check_auth(self):
+        chat = OpenAI(api_key=self.api_key, base_url=self.api_base)
+        response_list = chat.models.with_raw_response.list()
+
+        # self.generate_image('生成一个小猫图片')
+
+    def generate_image(self, prompt: str, negative_prompt: str = None):
+
+        chat = OpenAI(api_key=self.api_key, base_url=self.api_base)
+        res = chat.images.generate(model=self.model, prompt=prompt, **self.params)
+
+        file_urls = []
+        for content in res.data:
+            url = content.url
+            print(url)
+            file_name = 'generated_image.png'
+            file = bytes_to_uploaded_file(requests.get(url).content, file_name)
+            meta = {'debug': True}
+            file_url = FileSerializer(data={'file': file, 'meta': meta}).upload()
+            file_urls.append(file_url)
+
+        return file_urls

apps/setting/models_provider/impl/openai_model_provider/openai_model_provider.py

@@ -15,11 +15,13 @@ from setting.models_provider.impl.openai_model_provider.credential.embedding imp
 from setting.models_provider.impl.openai_model_provider.credential.image import OpenAIImageModelCredential
 from setting.models_provider.impl.openai_model_provider.credential.llm import OpenAILLMModelCredential
 from setting.models_provider.impl.openai_model_provider.credential.stt import OpenAISTTModelCredential
+from setting.models_provider.impl.openai_model_provider.credential.tti import OpenAITextToImageModelCredential
 from setting.models_provider.impl.openai_model_provider.credential.tts import OpenAITTSModelCredential
 from setting.models_provider.impl.openai_model_provider.model.embedding import OpenAIEmbeddingModel
 from setting.models_provider.impl.openai_model_provider.model.image import OpenAIImage
 from setting.models_provider.impl.openai_model_provider.model.llm import OpenAIChatModel
 from setting.models_provider.impl.openai_model_provider.model.stt import OpenAISpeechToText
+from setting.models_provider.impl.openai_model_provider.model.tti import OpenAITextToImage
 from setting.models_provider.impl.openai_model_provider.model.tts import OpenAITextToSpeech
 from smartdoc.conf import PROJECT_DIR
 
@@ -27,6 +29,7 @@ openai_llm_model_credential = OpenAILLMModelCredential()
 openai_stt_model_credential = OpenAISTTModelCredential()
 openai_tts_model_credential = OpenAITTSModelCredential()
 openai_image_model_credential = OpenAIImageModelCredential()
+openai_tti_model_credential = OpenAITextToImageModelCredential()
 model_info_list = [
     ModelInfo('gpt-3.5-turbo', '最新的gpt-3.5-turbo，随OpenAI调整而更新', ModelTypeConst.LLM,
               openai_llm_model_credential, OpenAIChatModel
@@ -37,8 +40,8 @@ model_info_list = [
               ModelTypeConst.LLM, openai_llm_model_credential,
               OpenAIChatModel),
     ModelInfo('gpt-4o-mini', '最新的gpt-4o-mini，比gpt-4o更便宜、更快，随OpenAI调整而更新',
-            ModelTypeConst.LLM, openai_llm_model_credential,
-            OpenAIChatModel),
+              ModelTypeConst.LLM, openai_llm_model_credential,
+              OpenAIChatModel),
     ModelInfo('gpt-4-turbo', '最新的gpt-4-turbo，随OpenAI调整而更新', ModelTypeConst.LLM,
               openai_llm_model_credential,
               OpenAIChatModel),
@@ -100,11 +103,27 @@ model_info_image_list = [
               OpenAIImage),
 ]
 
-model_info_manage = ModelInfoManage.builder().append_model_info_list(model_info_list).append_default_model_info(
-    ModelInfo('gpt-3.5-turbo', '最新的gpt-3.5-turbo，随OpenAI调整而更新', ModelTypeConst.LLM,
-              openai_llm_model_credential, OpenAIChatModel
-              )).append_model_info_list(model_info_embedding_list).append_default_model_info(
-    model_info_embedding_list[0]).append_model_info_list(model_info_image_list).build()
+model_info_tti_list = [
+    ModelInfo('dall-e-2', '',
+              ModelTypeConst.TTI, openai_tti_model_credential,
+              OpenAITextToImage),
+    ModelInfo('dall-e-3', '',
+              ModelTypeConst.TTI, openai_tti_model_credential,
+              OpenAITextToImage),
+]
+
+model_info_manage = (
+    ModelInfoManage.builder()
+    .append_model_info_list(model_info_list)
+    .append_default_model_info(ModelInfo('gpt-3.5-turbo', '最新的gpt-3.5-turbo，随OpenAI调整而更新', ModelTypeConst.LLM,
+                                         openai_llm_model_credential, OpenAIChatModel
+                                         ))
+    .append_model_info_list(model_info_embedding_list)
+    .append_default_model_info(model_info_embedding_list[0])
+    .append_model_info_list(model_info_image_list)
+    .append_model_info_list(model_info_tti_list)
+    .build()
+)
 
 
 class OpenAIModelProvider(IModelProvider):

apps/setting/models_provider/impl/qwen_model_provider/credential/tti.py

@@ -0,0 +1,70 @@
+# coding=utf-8
+"""
+    @project: MaxKB
+    @Author：虎
+    @file： llm.py
+    @date：2024/7/11 18:41
+    @desc:
+"""
+import base64
+import os
+from typing import Dict
+
+from langchain_core.messages import HumanMessage
+
+from common import forms
+from common.exception.app_exception import AppApiException
+from common.forms import BaseForm, TooltipLabel
+from setting.models_provider.base_model_provider import BaseModelCredential, ValidCode
+
+
+class QwenModelParams(BaseForm):
+    temperature = forms.SliderField(TooltipLabel('温度', '较高的数值会使输出更加随机，而较低的数值会使其更加集中和确定'),
+                                    required=True, default_value=1.0,
+                                    _min=0.1,
+                                    _max=1.9,
+                                    _step=0.01,
+                                    precision=2)
+
+    max_tokens = forms.SliderField(
+        TooltipLabel('输出最大Tokens', '指定模型可生成的最大token个数'),
+        required=True, default_value=800,
+        _min=1,
+        _max=100000,
+        _step=1,
+        precision=0)
+
+
+class QwenTextToImageModelCredential(BaseForm, BaseModelCredential):
+
+    def is_valid(self, model_type: str, model_name, model_credential: Dict[str, object], provider,
+                 raise_exception=False):
+        model_type_list = provider.get_model_type_list()
+        if not any(list(filter(lambda mt: mt.get('value') == model_type, model_type_list))):
+            raise AppApiException(ValidCode.valid_error.value, f'{model_type} 模型类型不支持')
+        for key in ['api_key']:
+            if key not in model_credential:
+                if raise_exception:
+                    raise AppApiException(ValidCode.valid_error.value, f'{key} 字段为必填字段')
+                else:
+                    return False
+        try:
+            model = provider.get_model(model_type, model_name, model_credential)
+            res = model.check_auth()
+            print(res)
+        except Exception as e:
+            if isinstance(e, AppApiException):
+                raise e
+            if raise_exception:
+                raise AppApiException(ValidCode.valid_error.value, f'校验失败,请检查参数是否正确: {str(e)}')
+            else:
+                return False
+        return True
+
+    def encryption_dict(self, model: Dict[str, object]):
+        return {**model, 'api_key': super().encryption(model.get('api_key', ''))}
+
+    api_key = forms.PasswordInputField('API Key', required=True)
+
+    def get_model_params_setting_form(self, model_name):
+        return QwenModelParams()

apps/setting/models_provider/impl/qwen_model_provider/model/tti.py

@@ -0,0 +1,64 @@
+# coding=utf-8
+from http import HTTPStatus
+from pathlib import PurePosixPath
+from typing import Dict
+from urllib.parse import unquote, urlparse
+
+import requests
+from dashscope import ImageSynthesis
+from langchain_community.chat_models import ChatTongyi
+from langchain_core.messages import HumanMessage
+
+from common.util.common import bytes_to_uploaded_file
+from dataset.serializers.file_serializers import FileSerializer
+from setting.models_provider.base_model_provider import MaxKBBaseModel
+from setting.models_provider.impl.base_tti import BaseTextToImage
+
+
+class QwenTextToImageModel(MaxKBBaseModel, BaseTextToImage):
+    api_key: str
+    model_name: str
+    params: dict
+
+    def __init__(self, **kwargs):
+        super().__init__(**kwargs)
+        self.api_key = kwargs.get('api_key')
+        self.model_name = kwargs.get('model_name')
+        self.params = kwargs.get('params')
+
+    @staticmethod
+    def new_instance(model_type, model_name, model_credential: Dict[str, object], **model_kwargs):
+        optional_params = {'params': {}}
+        for key, value in model_kwargs.items():
+            if key not in ['model_id', 'use_local', 'streaming']:
+                optional_params['params'][key] = value
+        chat_tong_yi = QwenTextToImageModel(
+            model_name=model_name,
+            api_key=model_credential.get('api_key'),
+            **optional_params,
+        )
+        return chat_tong_yi
+
+    def check_auth(self):
+        chat = ChatTongyi(api_key=self.api_key, model_name='qwen-max')
+        chat.invoke([HumanMessage([{"type": "text", "text": "你好"}])])
+
+    def generate_image(self, prompt: str, negative_prompt: str = None):
+        # api_base='https://dashscope.aliyuncs.com/compatible-mode/v1',
+        rsp = ImageSynthesis.call(api_key=self.api_key,
+                                  model=self.model_name,
+                                  prompt=prompt,
+                                  negative_prompt=negative_prompt,
+                                  **self.params)
+        file_urls = []
+        if rsp.status_code == HTTPStatus.OK:
+            for result in rsp.output.results:
+                file_name = PurePosixPath(unquote(urlparse(result.url).path)).parts[-1]
+                file = bytes_to_uploaded_file(requests.get(result.url).content, file_name)
+                meta = {'debug': True}
+                file_url = FileSerializer(data={'file': file, 'meta': meta}).upload()
+                file_urls.append(file_url)
+        else:
+            print('sync_call Failed, status_code: %s, code: %s, message: %s' %
+                  (rsp.status_code, rsp.code, rsp.message))
+        return file_urls

apps/setting/models_provider/impl/qwen_model_provider/qwen_model_provider.py

@@ -13,13 +13,16 @@ from setting.models_provider.base_model_provider import ModelProvideInfo, ModelT
     ModelInfoManage
 from setting.models_provider.impl.qwen_model_provider.credential.image import QwenVLModelCredential
 from setting.models_provider.impl.qwen_model_provider.credential.llm import OpenAILLMModelCredential
+from setting.models_provider.impl.qwen_model_provider.credential.tti import QwenTextToImageModelCredential
 from setting.models_provider.impl.qwen_model_provider.model.image import QwenVLChatModel
 
 from setting.models_provider.impl.qwen_model_provider.model.llm import QwenChatModel
+from setting.models_provider.impl.qwen_model_provider.model.tti import QwenTextToImageModel
 from smartdoc.conf import PROJECT_DIR
 
 qwen_model_credential = OpenAILLMModelCredential()
 qwenvl_model_credential = QwenVLModelCredential()
+qwentti_model_credential = QwenTextToImageModelCredential()
 
 module_info_list = [
     ModelInfo('qwen-turbo', '', ModelTypeConst.LLM, qwen_model_credential, QwenChatModel),
@@ -31,13 +34,21 @@ module_info_vl_list = [
     ModelInfo('qwen-vl-max-0809', '', ModelTypeConst.IMAGE, qwenvl_model_credential, QwenVLChatModel),
     ModelInfo('qwen-vl-plus-0809', '', ModelTypeConst.IMAGE, qwenvl_model_credential, QwenVLChatModel),
 ]
+module_info_tti_list = [
+    ModelInfo('wanx-v1',
+              '通义万相-文本生成图像大模型，支持中英文双语输入，支持输入参考图片进行参考内容或者参考风格迁移，重点风格包括但不限于水彩、油画、中国画、素描、扁平插画、二次元、3D卡通。',
+              ModelTypeConst.TTI, qwentti_model_credential, QwenTextToImageModel),
+]
 
-model_info_manage = (ModelInfoManage.builder()
-                     .append_model_info_list(module_info_list)
-                     .append_default_model_info(
-    ModelInfo('qwen-turbo', '', ModelTypeConst.LLM, qwen_model_credential, QwenChatModel))
-                     .append_model_info_list(module_info_vl_list)
-                     .build())
+model_info_manage = (
+    ModelInfoManage.builder()
+    .append_model_info_list(module_info_list)
+    .append_default_model_info(
+        ModelInfo('qwen-turbo', '', ModelTypeConst.LLM, qwen_model_credential, QwenChatModel))
+    .append_model_info_list(module_info_vl_list)
+    .append_model_info_list(module_info_tti_list)
+    .build()
+)
 
 
 class QwenModelProvider(IModelProvider):

apps/setting/models_provider/impl/tencent_model_provider/credential/tti.py

@@ -0,0 +1,108 @@
+# coding=utf-8
+from langchain_core.messages import HumanMessage
+
+from common import forms
+from common.exception.app_exception import AppApiException
+from common.forms import BaseForm, TooltipLabel
+from setting.models_provider.base_model_provider import BaseModelCredential, ValidCode
+
+
+class TencentTTIModelParams(BaseForm):
+    Style = forms.SingleSelect(
+        TooltipLabel('绘画风格', '不传默认使用201（日系动漫风格）'),
+        required=True,
+        default_value='201',
+        option_list=[
+            {'value': '000', 'label': '不限定风格'},
+            {'value': '101', 'label': '水墨画'},
+            {'value': '102', 'label': '概念艺术'},
+            {'value': '103', 'label': '油画1'},
+            {'value': '118', 'label': '油画2（梵高）'},
+            {'value': '104', 'label': '水彩画'},
+            {'value': '105', 'label': '像素画'},
+            {'value': '106', 'label': '厚涂风格'},
+            {'value': '107', 'label': '插图'},
+            {'value': '108', 'label': '剪纸风格'},
+            {'value': '109', 'label': '印象派1（莫奈）'},
+            {'value': '119', 'label': '印象派2'},
+            {'value': '110', 'label': '2.5D'},
+            {'value': '111', 'label': '古典肖像画'},
+            {'value': '112', 'label': '黑白素描画'},
+            {'value': '113', 'label': '赛博朋克'},
+            {'value': '114', 'label': '科幻风格'},
+            {'value': '115', 'label': '暗黑风格'},
+            {'value': '116', 'label': '3D'},
+            {'value': '117', 'label': '蒸汽波'},
+            {'value': '201', 'label': '日系动漫'},
+            {'value': '202', 'label': '怪兽风格'},
+            {'value': '203', 'label': '唯美古风'},
+            {'value': '204', 'label': '复古动漫'},
+            {'value': '301', 'label': '游戏卡通手绘'},
+            {'value': '401', 'label': '通用写实风格'},
+        ],
+        value_field='value',
+        text_field='label'
+    )
+
+    Resolution = forms.SingleSelect(
+        TooltipLabel('生成图分辨率', '不传默认使用768:768。'),
+        required=True,
+        default_value='768:768',
+        option_list=[
+            {'value': '768:768', 'label': '768:768（1:1）'},
+            {'value': '768:1024', 'label': '768:1024（3:4）'},
+            {'value': '1024:768', 'label': '1024:768（4:3）'},
+            {'value': '1024:1024', 'label': '1024:1024（1:1）'},
+            {'value': '720:1280', 'label': '720:1280（9:16）'},
+            {'value': '1280:720', 'label': '1280:720（16:9）'},
+            {'value': '768:1280', 'label': '768:1280（3:5）'},
+            {'value': '1280:768', 'label': '1280:768（5:3）'},
+            {'value': '1080:1920', 'label': '1080:1920（9:16）'},
+            {'value': '1920:1080', 'label': '1920:1080（16:9）'},
+        ],
+        value_field='value',
+        text_field='label'
+    )
+
+
+class TencentTTIModelCredential(BaseForm, BaseModelCredential):
+    REQUIRED_FIELDS = ['hunyuan_secret_id', 'hunyuan_secret_key']
+
+    @classmethod
+    def _validate_model_type(cls, model_type, provider, raise_exception=False):
+        if not any(mt['value'] == model_type for mt in provider.get_model_type_list()):
+            if raise_exception:
+                raise AppApiException(ValidCode.valid_error.value, f'{model_type} 模型类型不支持')
+            return False
+        return True
+
+    @classmethod
+    def _validate_credential_fields(cls, model_credential, raise_exception=False):
+        missing_keys = [key for key in cls.REQUIRED_FIELDS if key not in model_credential]
+        if missing_keys:
+            if raise_exception:
+                raise AppApiException(ValidCode.valid_error.value, f'{", ".join(missing_keys)} 字段为必填字段')
+            return False
+        return True
+
+    def is_valid(self, model_type, model_name, model_credential, provider, raise_exception=False):
+        if not (self._validate_model_type(model_type, provider, raise_exception) and
+                self._validate_credential_fields(model_credential, raise_exception)):
+            return False
+        try:
+            model = provider.get_model(model_type, model_name, model_credential)
+            model.check_auth()
+        except Exception as e:
+            if raise_exception:
+                raise AppApiException(ValidCode.valid_error.value, f'校验失败,请检查参数是否正确: {str(e)}')
+            return False
+        return True
+
+    def encryption_dict(self, model):
+        return {**model, 'hunyuan_secret_key': super().encryption(model.get('hunyuan_secret_key', ''))}
+
+    hunyuan_secret_id = forms.PasswordInputField('SecretId', required=True)
+    hunyuan_secret_key = forms.PasswordInputField('SecretKey', required=True)
+
+    def get_model_params_setting_form(self, model_name):
+        return TencentTTIModelParams()

apps/setting/models_provider/impl/tencent_model_provider/model/tti.py

@@ -0,0 +1,98 @@
+# coding=utf-8
+
+import json
+from typing import Dict
+
+import requests
+from tencentcloud.common import credential
+from tencentcloud.common.exception.tencent_cloud_sdk_exception import TencentCloudSDKException
+from tencentcloud.common.profile.client_profile import ClientProfile
+from tencentcloud.common.profile.http_profile import HttpProfile
+from tencentcloud.hunyuan.v20230901 import hunyuan_client, models
+
+from common.util.common import bytes_to_uploaded_file
+from dataset.serializers.file_serializers import FileSerializer
+from setting.models_provider.base_model_provider import MaxKBBaseModel
+from setting.models_provider.impl.base_tti import BaseTextToImage
+from setting.models_provider.impl.tencent_model_provider.model.hunyuan import ChatHunyuan
+
+
+class TencentTextToImageModel(MaxKBBaseModel, BaseTextToImage):
+    hunyuan_secret_id: str
+    hunyuan_secret_key: str
+    model: str
+    params: dict
+
+    @staticmethod
+    def is_cache_model():
+        return False
+
+    def __init__(self, **kwargs):
+        super().__init__(**kwargs)
+        self.hunyuan_secret_id = kwargs.get('hunyuan_secret_id')
+        self.hunyuan_secret_key = kwargs.get('hunyuan_secret_key')
+        self.model = kwargs.get('model_name')
+        self.params = kwargs.get('params')
+
+    @staticmethod
+    def new_instance(model_type: str, model_name: str, model_credential: Dict[str, object],
+                     **model_kwargs) -> 'TencentTextToImageModel':
+        optional_params = {'params': {'Style': '201', 'Resolution': '768:768'}}
+        for key, value in model_kwargs.items():
+            if key not in ['model_id', 'use_local', 'streaming']:
+                optional_params['params'][key] = value
+        return TencentTextToImageModel(
+            model=model_name,
+            hunyuan_secret_id=model_credential.get('hunyuan_secret_id'),
+            hunyuan_secret_key=model_credential.get('hunyuan_secret_key'),
+            **optional_params
+        )
+
+    def check_auth(self):
+        chat = ChatHunyuan(hunyuan_app_id='111111',
+                           hunyuan_secret_id=self.hunyuan_secret_id,
+                           hunyuan_secret_key=self.hunyuan_secret_key,
+                           model="hunyuan-standard")
+        res = chat.invoke('你好')
+        # print(res)
+
+    def generate_image(self, prompt: str, negative_prompt: str = None):
+        try:
+            # 实例化一个认证对象，入参需要传入腾讯云账户 SecretId 和 SecretKey，此处还需注意密钥对的保密
+            # 代码泄露可能会导致 SecretId 和 SecretKey 泄露，并威胁账号下所有资源的安全性。以下代码示例仅供参考，建议采用更安全的方式来使用密钥，请参见：https://cloud.tencent.com/document/product/1278/85305
+            # 密钥可前往官网控制台 https://console.cloud.tencent.com/cam/capi 进行获取
+            cred = credential.Credential(self.hunyuan_secret_id, self.hunyuan_secret_key)
+            # 实例化一个http选项，可选的，没有特殊需求可以跳过
+            httpProfile = HttpProfile()
+            httpProfile.endpoint = "hunyuan.tencentcloudapi.com"
+
+            # 实例化一个client选项，可选的，没有特殊需求可以跳过
+            clientProfile = ClientProfile()
+            clientProfile.httpProfile = httpProfile
+            # 实例化要请求产品的client对象,clientProfile是可选的
+            client = hunyuan_client.HunyuanClient(cred, "ap-guangzhou", clientProfile)
+
+            # 实例化一个请求对象,每个接口都会对应一个request对象
+            req = models.TextToImageLiteRequest()
+            params = {
+                "Prompt": prompt,
+                "NegativePrompt": negative_prompt,
+                "RspImgType": "url",
+                **self.params
+            }
+            req.from_json_string(json.dumps(params))
+
+            # 返回的resp是一个TextToImageLiteResponse的实例，与请求对象对应
+            resp = client.TextToImageLite(req)
+            # 输出json格式的字符串回包
+            print(resp.to_json_string())
+            file_urls = []
+            file_name = 'generated_image.png'
+            file = bytes_to_uploaded_file(requests.get(resp.ResultImage).content, file_name)
+            meta = {'debug': True}
+            file_url = FileSerializer(data={'file': file, 'meta': meta}).upload()
+            file_urls.append(file_url)
+            return file_urls
+        except TencentCloudSDKException as err:
+            print(err)
+

apps/setting/models_provider/impl/tencent_model_provider/tencent_model_provider.py

@@ -9,9 +9,11 @@ from setting.models_provider.base_model_provider import (
 from setting.models_provider.impl.tencent_model_provider.credential.embedding import TencentEmbeddingCredential
 from setting.models_provider.impl.tencent_model_provider.credential.image import TencentVisionModelCredential
 from setting.models_provider.impl.tencent_model_provider.credential.llm import TencentLLMModelCredential
+from setting.models_provider.impl.tencent_model_provider.credential.tti import TencentTTIModelCredential
 from setting.models_provider.impl.tencent_model_provider.model.embedding import TencentEmbeddingModel
 from setting.models_provider.impl.tencent_model_provider.model.image import TencentVision
 from setting.models_provider.impl.tencent_model_provider.model.llm import TencentModel
+from setting.models_provider.impl.tencent_model_provider.model.tti import TencentTextToImageModel
 from smartdoc.conf import PROJECT_DIR
 
 
@@ -87,11 +89,19 @@ def _initialize_model_info():
         TencentVisionModelCredential,
         TencentVision)]
 
+    model_info_tti_list = [_create_model_info(
+        'hunyuan-dit',
+        '混元生图模型',
+        ModelTypeConst.TTI,
+        TencentTTIModelCredential,
+        TencentTextToImageModel)]
+
 
     model_info_manage = ModelInfoManage.builder() \
         .append_model_info_list(model_info_list) \
         .append_model_info_list(model_info_embedding_list) \
         .append_model_info_list(model_info_vision_list) \
+        .append_model_info_list(model_info_tti_list) \
         .append_default_model_info(model_info_list[0]) \
         .build()
 

apps/setting/models_provider/impl/zhipu_model_provider/credential/tti.py

@@ -0,0 +1,44 @@
+# coding=utf-8
+from typing import Dict
+
+from langchain_core.messages import HumanMessage
+
+from common import forms
+from common.exception.app_exception import AppApiException
+from common.forms import BaseForm
+from setting.models_provider.base_model_provider import BaseModelCredential, ValidCode
+
+
+class ZhiPuTextToImageModelCredential(BaseForm, BaseModelCredential):
+    api_key = forms.PasswordInputField('API Key', required=True)
+
+    def is_valid(self, model_type: str, model_name, model_credential: Dict[str, object], provider,
+                 raise_exception=False):
+        model_type_list = provider.get_model_type_list()
+        if not any(list(filter(lambda mt: mt.get('value') == model_type, model_type_list))):
+            raise AppApiException(ValidCode.valid_error.value, f'{model_type} 模型类型不支持')
+
+        for key in ['api_key']:
+            if key not in model_credential:
+                if raise_exception:
+                    raise AppApiException(ValidCode.valid_error.value, f'{key} 字段为必填字段')
+                else:
+                    return False
+        try:
+            model = provider.get_model(model_type, model_name, model_credential)
+            res = model.check_auth()
+            print(res)
+        except Exception as e:
+            if isinstance(e, AppApiException):
+                raise e
+            if raise_exception:
+                raise AppApiException(ValidCode.valid_error.value, f'校验失败,请检查参数是否正确: {str(e)}')
+            else:
+                return False
+        return True
+
+    def encryption_dict(self, model: Dict[str, object]):
+        return {**model, 'api_key': super().encryption(model.get('api_key', ''))}
+
+    def get_model_params_setting_form(self, model_name):
+        pass

apps/setting/models_provider/impl/zhipu_model_provider/model/tti.py

@@ -0,0 +1,73 @@
+from typing import Dict
+
+import requests
+from langchain_community.chat_models import ChatZhipuAI
+from langchain_core.messages import HumanMessage
+from zhipuai import ZhipuAI
+
+from common.config.tokenizer_manage_config import TokenizerManage
+from common.util.common import bytes_to_uploaded_file
+from dataset.serializers.file_serializers import FileSerializer
+from setting.models_provider.base_model_provider import MaxKBBaseModel
+from setting.models_provider.impl.base_tti import BaseTextToImage
+
+
+def custom_get_token_ids(text: str):
+    tokenizer = TokenizerManage.get_tokenizer()
+    return tokenizer.encode(text)
+
+
+class ZhiPuTextToImage(MaxKBBaseModel, BaseTextToImage):
+    api_key: str
+    model: str
+    params: dict
+
+    def __init__(self, **kwargs):
+        super().__init__(**kwargs)
+        self.api_key = kwargs.get('api_key')
+        self.model = kwargs.get('model')
+        self.params = kwargs.get('params')
+
+    @staticmethod
+    def new_instance(model_type, model_name, model_credential: Dict[str, object], **model_kwargs):
+        optional_params = {'params': {}}
+        for key, value in model_kwargs.items():
+            if key not in ['model_id', 'use_local', 'streaming']:
+                optional_params['params'][key] = value
+        return ZhiPuTextToImage(
+            model=model_name,
+            api_key=model_credential.get('api_key'),
+            **optional_params,
+        )
+
+    def check_auth(self):
+        chat = ChatZhipuAI(
+            zhipuai_api_key=self.api_key,
+            model_name=self.model,
+        )
+        chat.invoke([HumanMessage([{"type": "text", "text": "你好"}])])
+
+        # self.generate_image('生成一个小猫图片')
+
+    def generate_image(self, prompt: str, negative_prompt: str = None):
+        # chat = ChatZhipuAI(
+        #     zhipuai_api_key=self.api_key,
+        #     model_name=self.model,
+        # )
+        chat = ZhipuAI(api_key=self.api_key)
+        response = chat.images.generations(
+            model=self.model,  # 填写需要调用的模型编码
+            prompt=prompt,  # 填写需要生成图片的文本
+            **self.params # 填写额外参数
+        )
+        file_urls = []
+        for content in response.data:
+            url = content['url']
+            print(url)
+            file_name = url.split('/')[-1]
+            file = bytes_to_uploaded_file(requests.get(url).content, file_name)
+            meta = {'debug': True}
+            file_url = FileSerializer(data={'file': file, 'meta': meta}).upload()
+            file_urls.append(file_url)
+
+        return file_urls

apps/setting/models_provider/impl/zhipu_model_provider/zhipu_model_provider.py

@@ -13,12 +13,15 @@ from setting.models_provider.base_model_provider import ModelProvideInfo, ModelT
     ModelInfoManage
 from setting.models_provider.impl.zhipu_model_provider.credential.image import ZhiPuImageModelCredential
 from setting.models_provider.impl.zhipu_model_provider.credential.llm import ZhiPuLLMModelCredential
+from setting.models_provider.impl.zhipu_model_provider.credential.tti import ZhiPuTextToImageModelCredential
 from setting.models_provider.impl.zhipu_model_provider.model.image import ZhiPuImage
 from setting.models_provider.impl.zhipu_model_provider.model.llm import ZhipuChatModel
+from setting.models_provider.impl.zhipu_model_provider.model.tti import ZhiPuTextToImage
 from smartdoc.conf import PROJECT_DIR
 
 qwen_model_credential = ZhiPuLLMModelCredential()
 zhipu_image_model_credential = ZhiPuImageModelCredential()
+zhipu_tti_model_credential = ZhiPuTextToImageModelCredential()
 
 model_info_list = [
     ModelInfo('glm-4', '', ModelTypeConst.LLM, qwen_model_credential, ZhipuChatModel),
@@ -38,11 +41,21 @@ model_info_image_list = [
               ZhiPuImage),
 ]
 
+model_info_tti_list = [
+    ModelInfo('cogview-3', '根据用户文字描述快速、精准生成图像。分辨率支持1024x1024',
+              ModelTypeConst.TTI, zhipu_tti_model_credential,
+              ZhiPuTextToImage),
+    ModelInfo('cogview-3-plus', '根据用户文字描述生成高质量图像，支持多图片尺寸',
+              ModelTypeConst.TTI, zhipu_tti_model_credential,
+              ZhiPuTextToImage),
+]
+
 model_info_manage = (
     ModelInfoManage.builder()
     .append_model_info_list(model_info_list)
     .append_default_model_info(ModelInfo('glm-4', '', ModelTypeConst.LLM, qwen_model_credential, ZhipuChatModel))
     .append_model_info_list(model_info_image_list)
+    .append_model_info_list(model_info_tti_list)
     .build()
 )
 

ui/src/api/application.ts

@@ -293,6 +293,13 @@ const getApplicationImageModel: (
   return get(`${prefix}/${application_id}/model`, { model_type: 'IMAGE' }, loading)
 }
 
+const getApplicationTTIModel: (
+  application_id: string,
+  loading?: Ref<boolean>
+) => Promise<Result<Array<any>>> = (application_id, loading) => {
+  return get(`${prefix}/${application_id}/model`, { model_type: 'TTI' }, loading)
+}
+
 
 /**
  * 发布应用
@@ -523,6 +530,7 @@ export default {
   getApplicationSTTModel,
   getApplicationTTSModel,
   getApplicationImageModel,
+  getApplicationTTIModel,
   postSpeechToText,
   postTextToSpeech,
   getPlatformStatus,

ui/src/components/ai-chat/ExecutionDetailDialog.vue

@@ -32,6 +32,7 @@
                     item.type === WorkflowType.Question ||
                     item.type === WorkflowType.AiChat ||
                     item.type === WorkflowType.ImageUnderstandNode ||
+                    item.type === WorkflowType.ImageGenerateNode ||
                     item.type === WorkflowType.Application
                   "
                   >{{ item?.message_tokens + item?.answer_tokens }} tokens</span
@@ -444,6 +445,65 @@
                       </div>
                     </div>
                   </template>
+                  <!-- 图片生成 -->
+                  <template v-if="item.type == WorkflowType.ImageGenerateNode">
+                    <div
+                      class="card-never border-r-4 mt-8"
+                      v-if="item.type !== WorkflowType.Application"
+                    >
+                      <h5 class="p-8-12">历史记录</h5>
+                      <div class="p-8-12 border-t-dashed lighter">
+                        <template v-if="item.history_message?.length > 0">
+                          <p
+                            class="mt-4 mb-4"
+                            v-for="(history, historyIndex) in item.history_message"
+                            :key="historyIndex"
+                          >
+                            <span class="color-secondary mr-4">{{ history.role }}:</span>
+
+                            <span v-if="Array.isArray(history.content)">
+                              <template v-for="(h, i) in history.content" :key="i">
+                                <el-image
+                                  v-if="h.type === 'image_url'"
+                                  :src="h.image_url.url"
+                                  alt=""
+                                  fit="cover"
+                                  style="width: 40px; height: 40px; display: inline-block"
+                                  class="border-r-4 mr-8"
+                                />
+
+                                <span v-else>{{ h.text }}<br /></span>
+                              </template>
+                            </span>
+
+                            <span v-else>{{ history.content }}</span>
+                          </p>
+                        </template>
+                        <template v-else> - </template>
+                      </div>
+                    </div>
+                    <div class="card-never border-r-4 mt-8">
+                      <h5 class="p-8-12">本次对话</h5>
+                      <div class="p-8-12 border-t-dashed lighter pre-wrap">
+                        {{ item.question || '-' }}
+                      </div>
+                    </div>
+                    <div class="card-never border-r-4 mt-8">
+                      <h5 class="p-8-12">
+                        {{ item.type == WorkflowType.Application ? '参数输出' : 'AI 回答' }}
+                      </h5>
+                      <div class="p-8-12 border-t-dashed lighter">
+                        <MdPreview
+                          v-if="item.answer"
+                          ref="editorRef"
+                          editorId="preview-only"
+                          :modelValue="item.answer"
+                          style="background: none"
+                        />
+                        <template v-else> - </template>
+                      </div>
+                    </div>
+                  </template>
                 </template>
                 <template v-else>
                   <div class="card-never border-r-4">

ui/src/enums/model.ts

@@ -13,5 +13,6 @@ export enum modelType {
   STT = '语音识别',
   TTS = '语音合成',
   IMAGE = '图片理解',
+  TTI = '图片生成',
   RERANKER = '重排模型'
 }

ui/src/enums/workflow.ts

@@ -12,5 +12,6 @@ export enum WorkflowType {
   Application = 'application-node',
   DocumentExtractNode = 'document-extract-node',
   ImageUnderstandNode = 'image-understand-node',
+  ImageGenerateNode = 'image-generate-node',
   FormNode = 'form-node'
 }

ui/src/views/template/component/SelectProviderDialog.vue

@@ -63,6 +63,7 @@ const modelTypeOptions = ref([
   { text: '语音识别', value: 'STT' },
   { text: '语音合成', value: 'TTS' },
   { text: '图片理解', value: 'IMAGE' },
+  { text: '图片生成', value: 'TTI' },
 ])
 
 const open = () => {

ui/src/views/template/index.vue

@@ -133,6 +133,7 @@
                 <el-option label="语音识别" value="STT" />
                 <el-option label="语音合成" value="TTS" />
                 <el-option label="图片理解" value="IMAGE" />
+                <el-option label="图片生成" value="TTI" />
               </el-select>
             </div>
           </div>

ui/src/workflow/common/data.ts

@@ -227,6 +227,28 @@ export const imageUnderstandNode = {
     }
   }
 }
+
+export const imageGenerateNode = {
+  type: WorkflowType.ImageGenerateNode,
+  text: '根据提供的文本内容生成图片',
+  label: '图片生成',
+  height: 252,
+  properties: {
+    stepName: '图片生成',
+    config: {
+      fields: [
+        {
+          label: 'AI 回答内容',
+          value: 'answer'
+        },
+        {
+          label: '图片',
+          value: 'image'
+        }
+      ]
+    }
+  }
+}
 export const menuNodes = [
   aiChatNode,
   searchDatasetNode,
@@ -236,6 +258,7 @@ export const menuNodes = [
   rerankerNode,
   documentExtractNode,
   imageUnderstandNode,
+  imageGenerateNode,
   formNode
 ]
 
@@ -326,7 +349,8 @@ export const nodeDict: any = {
   [WorkflowType.FormNode]: formNode,
   [WorkflowType.Application]: applicationNode,
   [WorkflowType.DocumentExtractNode]: documentExtractNode,
-  [WorkflowType.ImageUnderstandNode]: imageUnderstandNode
+  [WorkflowType.ImageUnderstandNode]: imageUnderstandNode,
+  [WorkflowType.ImageGenerateNode]: imageGenerateNode
 }
 export function isWorkFlow(type: string | undefined) {
   return type === 'WORK_FLOW'

ui/src/workflow/common/validate.ts

@@ -6,6 +6,7 @@ const end_nodes: Array<string> = [
   WorkflowType.FunctionLib,
   WorkflowType.FunctionLibCustom,
   WorkflowType.ImageUnderstandNode,
+  WorkflowType.ImageGenerateNode,
   WorkflowType.Application
 ]
 export class WorkFlowInstance {

ui/src/workflow/icons/image-generate-node-icon.vue

@@ -0,0 +1,6 @@
+<template>
+  <AppAvatar shape="square" style="background: #14C0FF;">
+    <img src="@/assets/icon_image.svg" style="width: 65%" alt="" />
+  </AppAvatar>
+</template>
+<script setup lang="ts"></script>

ui/src/workflow/nodes/image-generate/index.ts

@@ -0,0 +1,14 @@
+import ImageGenerateNodeVue from './index.vue'
+import { AppNode, AppNodeModel } from '@/workflow/common/app-node'
+
+class RerankerNode extends AppNode {
+  constructor(props: any) {
+    super(props, ImageGenerateNodeVue)
+  }
+}
+
+export default {
+  type: 'image-generate-node',
+  model: AppNodeModel,
+  view: RerankerNode
+}

ui/src/workflow/nodes/image-generate/index.vue

@@ -0,0 +1,323 @@
+<template>
+  <NodeContainer :node-model="nodeModel">
+    <h5 class="title-decoration-1 mb-8">节点设置</h5>
+    <el-card shadow="never" class="card-never">
+      <el-form
+        @submit.prevent
+        :model="form_data"
+        label-position="top"
+        require-asterisk-position="right"
+        label-width="auto"
+        ref="aiChatNodeFormRef"
+        hide-required-asterisk
+      >
+        <el-form-item
+          label="图片生成模型"
+          prop="model_id"
+          :rules="{
+            required: true,
+            message: '请选择图片生成模型',
+            trigger: 'change'
+          }"
+        >
+          <template #label>
+            <div class="flex-between w-full">
+              <div>
+                <span>图片生成模型<span class="danger">*</span></span>
+              </div>
+              <el-button
+                :disabled="!form_data.model_id"
+                type="primary"
+                link
+                @click="openAIParamSettingDialog(form_data.model_id)"
+                @refreshForm="refreshParam"
+              >
+                {{ $t('views.application.applicationForm.form.paramSetting') }}
+              </el-button>
+            </div>
+          </template>
+          <el-select
+            @change="model_change"
+            @wheel="wheel"
+            :teleported="false"
+            v-model="form_data.model_id"
+            placeholder="请选择图片生成模型"
+            class="w-full"
+            popper-class="select-model"
+            :clearable="true"
+          >
+            <el-option-group
+              v-for="(value, label) in modelOptions"
+              :key="value"
+              :label="relatedObject(providerOptions, label, 'provider')?.name"
+            >
+              <el-option
+                v-for="item in value.filter((v: any) => v.status === 'SUCCESS')"
+                :key="item.id"
+                :label="item.name"
+                :value="item.id"
+                class="flex-between"
+              >
+                <div class="flex align-center">
+                  <span
+                    v-html="relatedObject(providerOptions, label, 'provider')?.icon"
+                    class="model-icon mr-8"
+                  ></span>
+                  <span>{{ item.name }}</span>
+                  <el-tag v-if="item.permission_type === 'PUBLIC'" type="info" class="info-tag ml-8"
+                    >公用
+                  </el-tag>
+                </div>
+                <el-icon class="check-icon" v-if="item.id === form_data.model_id">
+                  <Check />
+                </el-icon>
+              </el-option>
+              <!-- 不可用 -->
+              <el-option
+                v-for="item in value.filter((v: any) => v.status !== 'SUCCESS')"
+                :key="item.id"
+                :label="item.name"
+                :value="item.id"
+                class="flex-between"
+                disabled
+              >
+                <div class="flex">
+                  <span
+                    v-html="relatedObject(providerOptions, label, 'provider')?.icon"
+                    class="model-icon mr-8"
+                  ></span>
+                  <span>{{ item.name }}</span>
+                  <span class="danger">（不可用）</span>
+                </div>
+                <el-icon class="check-icon" v-if="item.id === form_data.model_id">
+                  <Check />
+                </el-icon>
+              </el-option>
+            </el-option-group>
+          </el-select>
+        </el-form-item>
+
+
+        <el-form-item
+          label="提示词(正向)"
+          prop="prompt"
+          :rules="{
+            required: true,
+            message: '请输入提示词',
+            trigger: 'blur'
+          }"
+        >
+          <template #label>
+            <div class="flex align-center">
+              <div class="mr-4">
+                <span>提示词(正向)<span class="danger">*</span></span>
+              </div>
+              <el-tooltip effect="dark" placement="right" popper-class="max-w-200">
+                <template #content
+                  >正向提示词，用来描述生成图像中期望包含的元素和视觉特点
+                </template>
+                <AppIcon iconName="app-warning" class="app-warning-icon"></AppIcon>
+              </el-tooltip>
+            </div>
+          </template>
+          <MdEditorMagnify
+            @wheel="wheel"
+            title="提示词(正向)"
+            v-model="form_data.prompt"
+            style="height: 150px"
+            @submitDialog="submitDialog"
+          />
+        </el-form-item>
+        <el-form-item
+          label="提示词(负向)"
+          prop="prompt"
+          :rules="{
+            required: false,
+            message: '请输入提示词',
+            trigger: 'blur'
+          }"
+        >
+          <template #label>
+            <div class="flex align-center">
+              <div class="mr-4">
+                <span>提示词(负向)</span>
+              </div>
+              <el-tooltip effect="dark" placement="right" popper-class="max-w-200">
+                <template #content
+                  >反向提示词，用来描述不希望在画面中看到的内容，可以对画面进行限制。
+                </template>
+                <AppIcon iconName="app-warning" class="app-warning-icon"></AppIcon>
+              </el-tooltip>
+            </div>
+          </template>
+          <MdEditorMagnify
+            @wheel="wheel"
+            title="提示词(负向)"
+            v-model="form_data.negative_prompt"
+            style="height: 150px"
+            @submitDialog="submitDialog"
+          />
+        </el-form-item>
+        <el-form-item>
+          <template #label>
+            <div class="flex-between">
+              <div>历史聊天记录</div>
+              <el-select v-model="form_data.dialogue_type" type="small" style="width: 100px">
+                <el-option label="节点" value="NODE" />
+                <el-option label="工作流" value="WORKFLOW" />
+              </el-select>
+            </div>
+          </template>
+          <el-input-number
+            v-model="form_data.dialogue_number"
+            :min="0"
+            :value-on-clear="0"
+            controls-position="right"
+            class="w-full"
+            :step="1"
+            :step-strictly="true"
+          />
+        </el-form-item>
+        <el-form-item label="返回内容" @click.prevent>
+          <template #label>
+            <div class="flex align-center">
+              <div class="mr-4">
+                <span>返回内容<span class="danger">*</span></span>
+              </div>
+              <el-tooltip effect="dark" placement="right" popper-class="max-w-200">
+                <template #content>
+                  关闭后该节点的内容则不输出给用户。
+                  如果你想让用户看到该节点的输出内容，请打开开关。
+                </template>
+                <AppIcon iconName="app-warning" class="app-warning-icon"></AppIcon>
+              </el-tooltip>
+            </div>
+          </template>
+          <el-switch size="small" v-model="form_data.is_result" />
+        </el-form-item>
+      </el-form>
+    </el-card>
+    <AIModeParamSettingDialog ref="AIModeParamSettingDialogRef" @refresh="refreshParam" />
+  </NodeContainer>
+</template>
+
+<script setup lang="ts">
+import NodeContainer from '@/workflow/common/NodeContainer.vue'
+import { computed, onMounted, ref } from 'vue'
+import { groupBy, set } from 'lodash'
+import { relatedObject } from '@/utils/utils'
+import type { Provider } from '@/api/type/model'
+import applicationApi from '@/api/application'
+import { app } from '@/main'
+import useStore from '@/stores'
+import NodeCascader from '@/workflow/common/NodeCascader.vue'
+import type { FormInstance } from 'element-plus'
+import AIModeParamSettingDialog from '@/views/application/component/AIModeParamSettingDialog.vue'
+
+const { model } = useStore()
+
+const {
+  params: { id }
+} = app.config.globalProperties.$route as any
+
+const props = defineProps<{ nodeModel: any }>()
+const modelOptions = ref<any>(null)
+const providerOptions = ref<Array<Provider>>([])
+const AIModeParamSettingDialogRef = ref<InstanceType<typeof AIModeParamSettingDialog>>()
+
+const aiChatNodeFormRef = ref<FormInstance>()
+const validate = () => {
+  return aiChatNodeFormRef.value?.validate().catch((err) => {
+    return Promise.reject({ node: props.nodeModel, errMessage: err })
+  })
+}
+
+const wheel = (e: any) => {
+  if (e.ctrlKey === true) {
+    e.preventDefault()
+    return true
+  } else {
+    e.stopPropagation()
+    return true
+  }
+}
+
+const defaultPrompt = `{{开始.question}}`
+
+const form = {
+  model_id: '',
+  system: '',
+  prompt: defaultPrompt,
+  negative_prompt: '',
+  dialogue_number: 0,
+  dialogue_type: 'NODE',
+  is_result: true,
+  temperature: null,
+  max_tokens: null,
+  image_list: ['start-node', 'image']
+}
+
+const form_data = computed({
+  get: () => {
+    if (props.nodeModel.properties.node_data) {
+      return props.nodeModel.properties.node_data
+    } else {
+      set(props.nodeModel.properties, 'node_data', form)
+    }
+    return props.nodeModel.properties.node_data
+  },
+  set: (value) => {
+    set(props.nodeModel.properties, 'node_data', value)
+  }
+})
+
+function getModel() {
+  if (id) {
+    applicationApi.getApplicationTTIModel(id).then((res: any) => {
+      modelOptions.value = groupBy(res?.data, 'provider')
+    })
+  } else {
+    model.asyncGetModel().then((res: any) => {
+      modelOptions.value = groupBy(res?.data, 'provider')
+    })
+  }
+}
+
+function getProvider() {
+  model.asyncGetProvider().then((res: any) => {
+    providerOptions.value = res?.data
+  })
+}
+
+const model_change = () => {
+    if (form_data.value.model_id) {
+    AIModeParamSettingDialogRef.value?.reset_default(form_data.value.model_id, id)
+  } else {
+    refreshParam({})
+  }
+}
+
+
+const openAIParamSettingDialog = (modelId: string) => {
+  if (modelId) {
+    AIModeParamSettingDialogRef.value?.open(modelId, id, form_data.value.model_params_setting)
+  }
+}
+
+function refreshParam(data: any) {
+  set(props.nodeModel.properties.node_data, 'model_params_setting', data)
+}
+
+function submitDialog(val: string) {
+  set(props.nodeModel.properties.node_data, 'prompt', val)
+}
+
+onMounted(() => {
+  getModel()
+  getProvider()
+
+  set(props.nodeModel, 'validate', validate)
+})
+</script>
+
+<style scoped lang="scss"></style>