resolve: conflict

api/config.py

@@ -79,7 +79,7 @@ class Config:
         self.CONSOLE_URL = get_env('CONSOLE_URL')
         self.API_URL = get_env('API_URL')
         self.APP_URL = get_env('APP_URL')
-        self.CURRENT_VERSION = "0.3.5"
+        self.CURRENT_VERSION = "0.3.6"
         self.COMMIT_SHA = get_env('COMMIT_SHA')
         self.EDITION = "SELF_HOSTED"
         self.DEPLOY_ENV = get_env('DEPLOY_ENV')

api/core/generator/llm_generator.py

@@ -2,7 +2,7 @@ import logging
 
 from langchain import PromptTemplate
 from langchain.chat_models.base import BaseChatModel
-from langchain.schema import HumanMessage, OutputParserException
+from langchain.schema import HumanMessage, OutputParserException, BaseMessage
 
 from core.constant import llm_constant
 from core.llm.llm_builder import LLMBuilder
@@ -23,10 +23,10 @@ class LLMGenerator:
     @classmethod
     def generate_conversation_name(cls, tenant_id: str, query, answer):
         prompt = CONVERSATION_TITLE_PROMPT
-        prompt = prompt.format(query=query, answer=answer)
+        prompt = prompt.format(query=query)
         llm: StreamableOpenAI = LLMBuilder.to_llm(
             tenant_id=tenant_id,
-            model_name=generate_base_model,
+            model_name='gpt-3.5-turbo',
             max_tokens=50
         )
 
@@ -40,11 +40,12 @@ class LLMGenerator:
     @classmethod
     def generate_conversation_summary(cls, tenant_id: str, messages):
         max_tokens = 200
+        model = 'gpt-3.5-turbo'
 
         prompt = CONVERSATION_SUMMARY_PROMPT
         prompt_with_empty_context = prompt.format(context='')
-        prompt_tokens = TokenCalculator.get_num_tokens(generate_base_model, prompt_with_empty_context)
-        rest_tokens = llm_constant.max_context_token_length[generate_base_model] - prompt_tokens - max_tokens
+        prompt_tokens = TokenCalculator.get_num_tokens(model, prompt_with_empty_context)
+        rest_tokens = llm_constant.max_context_token_length[model] - prompt_tokens - max_tokens
 
         context = ''
         for message in messages:
@@ -52,14 +53,14 @@ class LLMGenerator:
                 continue
 
             message_qa_text = "Human:" + message.query + "\nAI:" + message.answer + "\n"
-            if rest_tokens - TokenCalculator.get_num_tokens(generate_base_model, context + message_qa_text) > 0:
+            if rest_tokens - TokenCalculator.get_num_tokens(model, context + message_qa_text) > 0:
                 context += message_qa_text
 
         prompt = prompt.format(context=context)
 
         llm: StreamableOpenAI = LLMBuilder.to_llm(
             tenant_id=tenant_id,
-            model_name=generate_base_model,
+            model_name=model,
             max_tokens=max_tokens
         )
 
@@ -102,7 +103,7 @@ class LLMGenerator:
 
         llm: StreamableOpenAI = LLMBuilder.to_llm(
             tenant_id=tenant_id,
-            model_name=generate_base_model,
+            model_name='gpt-3.5-turbo',
             temperature=0,
             max_tokens=256
         )
@@ -114,6 +115,8 @@ class LLMGenerator:
 
         try:
             output = llm(query)
+            if isinstance(output, BaseMessage):
+                output = output.content
             questions = output_parser.parse(output)
         except Exception:
             logging.exception("Error generating suggested questions after answer")

api/core/indexing_runner.py

@@ -346,10 +346,10 @@ class IndexingRunner:
         return text_docs
 
     def filter_string(self, text):
-        text = text.replace('<|', '<')
-        text = text.replace('|>', '>')
-        pattern = re.compile('[\x00-\x08\x0B\x0C\x0E-\x1F\x7F\x80-\xFF]')
-        return pattern.sub('', text)
+        text = re.sub(r'<\|', '<', text)
+        text = re.sub(r'\|>', '>', text)
+        text = re.sub(r'[\x00-\x08\x0B\x0C\x0E-\x1F\x7F\x80-\xFF]', '', text)
+        return text
 
     def _get_splitter(self, processing_rule: DatasetProcessRule) -> TextSplitter:
         """

api/core/prompt/prompts.py

 CONVERSATION_TITLE_PROMPT = (
-    "Human:{{query}}\n-----\n"
+    "Human:{query}\n-----\n"
     "Help me summarize the intent of what the human said and provide a title, the title should not exceed 20 words.\n"
     "If the human said is conducted in Chinese, you should return a Chinese title.\n" 
     "If the human said is conducted in English, you should return an English title.\n"
@@ -19,7 +19,7 @@ CONVERSATION_SUMMARY_PROMPT = (
 INTRODUCTION_GENERATE_PROMPT = (
     "I am designing a product for users to interact with an AI through dialogue. "
     "The Prompt given to the AI before the conversation is:\n\n"
-    "```\n{{prompt}}\n```\n\n"
+    "```\n{prompt}\n```\n\n"
     "Please generate a brief introduction of no more than 50 words that greets the user, based on this Prompt. "
     "Do not reveal the developer's motivation or deep logic behind the Prompt, "
     "but focus on building a relationship with the user:\n"
@@ -27,13 +27,13 @@ INTRODUCTION_GENERATE_PROMPT = (
 
 MORE_LIKE_THIS_GENERATE_PROMPT = (
     "-----\n"
-    "{{original_completion}}\n"
+    "{original_completion}\n"
     "-----\n\n"
     "Please use the above content as a sample for generating the result, "
     "and include key information points related to the original sample in the result. "
     "Try to rephrase this information in different ways and predict according to the rules below.\n\n"
     "-----\n"
-    "{{prompt}}\n"
+    "{prompt}\n"
 )
 
 SUGGESTED_QUESTIONS_AFTER_ANSWER_INSTRUCTION_PROMPT = (

docker/docker-compose.yaml

@@ -2,7 +2,7 @@ version: '3.1'
 services:
   # API service
   api:
-    image: langgenius/dify-api:0.3.5
+    image: langgenius/dify-api:0.3.6
     restart: always
     environment:
       # Startup mode, 'api' starts the API server.
@@ -110,7 +110,7 @@ services:
   # worker service
   # The Celery worker for processing the queue.
   worker:
-    image: langgenius/dify-api:0.3.5
+    image: langgenius/dify-api:0.3.6
     restart: always
     environment:
       # Startup mode, 'worker' starts the Celery worker for processing the queue.
@@ -156,7 +156,7 @@ services:
 
   # Frontend web application.
   web:
-    image: langgenius/dify-web:0.3.5
+    image: langgenius/dify-web:0.3.6
     restart: always
     environment:
       EDITION: SELF_HOSTED

web/app/components/app/overview/settings/index.tsx

@@ -83,17 +83,6 @@ const SettingsModal: FC<ISettingsModalProps> = ({
 
   return (
     <>
-      {showEmojiPicker && <EmojiPicker
-        onSelect={(icon, icon_background) => {
-          console.log(icon, icon_background)
-          setEmoji({ icon, icon_background })
-          setShowEmojiPicker(false)
-        }}
-        onClose={() => {
-          setEmoji({ icon: '🤖', icon_background: '#FFEAD5' })
-          setShowEmojiPicker(false)
-        }}
-      />}
       <Modal
         title={t(`${prefixSettings}.title`)}
         isShow={isShow}
@@ -161,6 +150,17 @@ const SettingsModal: FC<ISettingsModalProps> = ({
           <Button className='mr-2 flex-shrink-0' onClick={onHide}>{t('common.operation.cancel')}</Button>
           <Button type='primary' className='flex-shrink-0' onClick={onClickSave} loading={saveLoading}>{t('common.operation.save')}</Button>
         </div>
+        {showEmojiPicker && <EmojiPicker
+          onSelect={(icon, icon_background) => {
+            console.log(icon, icon_background)
+            setEmoji({ icon, icon_background })
+            setShowEmojiPicker(false)
+          }}
+          onClose={() => {
+            setEmoji({ icon: '🤖', icon_background: '#FFEAD5' })
+            setShowEmojiPicker(false)
+          }}
+        />}
       </Modal >
     </>
 

web/package.json

 {
   "name": "dify-web",
-  "version": "0.3.5",
+  "version": "0.3.6",
   "private": true,
   "scripts": {
     "dev": "next dev",