perf(prompt_opt): improve prompt optimization and model output quality

api/app/services/prompt_optimizer_service.py

@@ -1,8 +1,10 @@
 import re
 import uuid
 
+import json_repair
 from langchain_core.prompts import ChatPromptTemplate
 from sqlalchemy.orm import Session
+from jinja2 import Template
 
 from app.core.error_codes import BizCode
 from app.core.exceptions import BusinessException
@@ -170,68 +172,45 @@ class PromptOptimizerService:
             api_key=api_config.api_key,
             base_url=api_config.api_base
         ), type=ModelType(model_config.type))
+        try:
+            with open('app/templates/prompt/prompt_optimizer_system.jinja2', 'r', encoding='utf-8') as f:
+                opt_system_prompt = f.read()
+            rendered_system_message = Template(opt_system_prompt).render()
+
+            with open('app/templates/prompt/prompt_optimizer_user.jinja2', 'r', encoding='utf-8') as f:
+                opt_user_prompt = f.read()
+        except FileNotFoundError:
+            raise BusinessException(message="System prompt template not found", code=BizCode.NOT_FOUND)
+
+        except Exception as e:
+            logger.error(f"Failed to load system prompt template: {e}")
+            raise BusinessException(message="Internal server error", code=BizCode.INTERNAL_ERROR)
+        rendered_user_message = Template(opt_user_prompt).render(
+            current_prompt=current_prompt,
+            user_require=user_require
+        )
 
         # build message
         messages = [
             # init system_prompt
             (
                 RoleType.SYSTEM.value,
-                "Your task is to optimize the original prompt provided by the user so that it can be directly used by AI tools,"
-                "and the variables that the user needs to insert must be wrapped in {{}}. "
-                "The optimized prompt should align with the optimization direction specified by the user (if any) and ensure clear logic, explicit instructions, and strong executability. "
-                "Please follow these rules when optimizing: "
-                '1. Ensure variables are wrapped in {{}}, e.g., optimize "Please enter your question" to "Please enter your {{question}}"'
-                "2. Instructions must be specific and operable, avoiding vague expressions"
-                "3. If the original prompt lacks key elements (such as output format requirements), supplement them completely "
-                "4. Keep the language concise and avoid redundancy "
-                "5. If the user does not specify an optimization direction, the default optimization is to make the prompt structurally clear and with explicit instructions"
-                "Please directly output the optimized prompt without additional explanations. The optimized prompt should be directly usable with correct variable positions."
+                rendered_system_message
             ),
+        ]
 
-            # base model limit
-            (RoleType.SYSTEM.value,
-             "Optimization Rules:\n"
-             "1. Fully adjust the prompt content according to the user's requirements.\n"
-             "When variables are required, use double curly braces {{variable_name}} as placeholders."
-             "Variable names must be derived from the user's requirements.\n"
-             "3. Keep the prompt logic clear and instructions explicit.\n"
-             "4. Ensure that the modified prompt can be directly used.\n\n")
-        ]
         messages.extend(session_history[:-1])  # last message is current message
-        user_message_template = ChatPromptTemplate.from_messages([
-            (RoleType.USER.value, "[original_prompt]\n{current_prompt}\n[user_require]\n{user_require}")
-        ])
-        formatted_user_message = user_message_template.format(current_prompt=current_prompt, user_require=user_require)
-        messages.extend([(RoleType.USER.value, formatted_user_message)])
+        messages.extend([(RoleType.USER.value, rendered_user_message)])
         logger.info(f"Prompt optimization message: {messages}")
-        optim_prompt = await llm.ainvoke(messages)
-        optim_desc = [
-            (
-                RoleType.SYSTEM.value,
-                "You are a prompt optimization assistant.\n"
-                "Compare the original prompt, the user's requirements, "
-                "and the optimized prompt.\n"
-                "Summarize the changes made during optimization.\n\n"
-                "Rules:\n"
-                "1. Output must be a single short sentence.\n"
-                "2. Be concise and factual.\n"
-                "3. Do not explain the prompts themselves.\n"
-                "4. Do not include any extra text."
-            ),
-            (
-                "[Original Prompt]\n"
-                f"{current_prompt}\n\n"
-                "[User Requirements]\n"
-                f"{user_require}\n\n"
-                "[Optimized Prompt]\n"
-                f"{optim_prompt.content}"
-            )
-        ]
-        optim_desc = await llm.ainvoke(optim_desc)
+        optim_resp = await llm.ainvoke(messages)
+        logger.info(optim_resp.content)
+        optim_result = json_repair.repair_json(optim_resp.content, return_objects=True)
+        prompt = optim_result.get("prompt")
+        desc = optim_result.get("desc")
 
         return OptimizePromptResult(
-            prompt=optim_prompt.content,
-            desc=optim_desc.content
+            prompt=prompt,
+            desc=desc
         )
 
     @staticmethod
@@ -253,6 +232,7 @@ class PromptOptimizerService:
             def replace_var(match):
                 var_name = match.group(1)
                 return variables.get(var_name, match.group(0))
+
             result = re.sub(pattern, replace_var, prompt)
             return result
         except Exception as e: