♻️ Refactor: Partial constant extraction in the backend

Author: Bavichi

backend/consts/const.py

@@ -188,6 +188,10 @@
     "SYSTEM": "system"
 }
 
+# Knowledge summary max token limits
+KNOWLEDGE_SUMMARY_MAX_TOKENS_ZH = 300
+KNOWLEDGE_SUMMARY_MAX_TOKENS_EN = 120
+
 # Host Configuration Constants
 LOCALHOST_IP = "127.0.0.1"
 LOCALHOST_NAME = "localhost"

backend/services/elasticsearch_service.py

@@ -26,7 +26,7 @@
 from openai import OpenAI
 from openai.types.chat import ChatCompletionMessageParam
 
-from consts.const import ES_API_KEY, ES_HOST, LANGUAGE, MODEL_CONFIG_MAPPING
+from consts.const import ES_API_KEY, ES_HOST, LANGUAGE, MODEL_CONFIG_MAPPING, MESSAGE_ROLE, KNOWLEDGE_SUMMARY_MAX_TOKENS_ZH, KNOWLEDGE_SUMMARY_MAX_TOKENS_EN
 from database.attachment_db import delete_file
 from database.knowledge_db import (
     create_knowledge_record,
@@ -69,8 +69,8 @@ def generate_knowledge_summary_stream(keywords: str, language: str, tenant_id: s
 
     # Build messages
     messages: List[ChatCompletionMessageParam] = [
-        {"role": "system", "content": system_prompt},
-        {"role": "user", "content": user_prompt}
+        {"role": MESSAGE_ROLE["SYSTEM"], "content": system_prompt},
+        {"role": MESSAGE_ROLE["USER"], "content": user_prompt}
     ]
 
     # Get model configuration from tenant config manager
@@ -83,7 +83,7 @@ def generate_knowledge_summary_stream(keywords: str, language: str, tenant_id: s
 
     try:
         # Create stream chat completion request
-        max_tokens = 300 if language == LANGUAGE["ZH"] else 120
+        max_tokens = KNOWLEDGE_SUMMARY_MAX_TOKENS_ZH if language == LANGUAGE["ZH"] else KNOWLEDGE_SUMMARY_MAX_TOKENS_EN
         stream = client.chat.completions.create(
             model=get_model_name_from_config(model_config) if model_config.get(
                 "model_name") else "",  # use model name from config