Merge pull request #679 from SchrodingersCattt/dev-gmy

feat: enhance translation accuracy by vocabulary dict

Author: Rasic2

agents/matmaster_agent/core_agents/comp_agents/recommend_summary_agent/agent.py

@@ -58,7 +58,11 @@
 from agents.matmaster_agent.locales import i18n
 from agents.matmaster_agent.logger import PrefixFilter
 from agents.matmaster_agent.model import ToolCallInfoSchema
-from agents.matmaster_agent.prompt import GLOBAL_INSTRUCTION, GLOBAL_SCHEMA_INSTRUCTION
+from agents.matmaster_agent.prompt import (
+    GLOBAL_INSTRUCTION,
+    GLOBAL_SCHEMA_INSTRUCTION,
+    get_vocabulary_enforce_prompt,
+)
 from agents.matmaster_agent.state import RECOMMEND_PARAMS
 from agents.matmaster_agent.sub_agents.tools import ALL_TOOLS
 from agents.matmaster_agent.utils.event_utils import (
@@ -334,9 +338,11 @@ async def _run_events(self, ctx: InvocationContext) -> AsyncGenerator[Event, Non
 
         # TODO: needs a better way to handle customized summary prompt
         if ALL_TOOLS[current_step_tool_name].get('summary_prompt') is not None:
-            self.summary_agent.instruction = ALL_TOOLS[current_step_tool_name].get(
-                'summary_prompt'
+            custom_prompt = ALL_TOOLS[current_step_tool_name].get('summary_prompt')
+            self.summary_agent.instruction = (
+                f"{custom_prompt}\n\n{get_vocabulary_enforce_prompt()}"
             )
+
         if current_step['status'] != PlanStepStatusEnum.SUBMITTED:
             async for summary_event in self.summary_agent.run_async(ctx):
                 yield summary_event

agents/matmaster_agent/core_agents/comp_agents/recommend_summary_agent/subagent_summary_agent/prompt.py

@@ -1,4 +1,7 @@
-from agents.matmaster_agent.prompt import HUMAN_FRIENDLY_FORMAT_REQUIREMENT
+from agents.matmaster_agent.prompt import (
+    HUMAN_FRIENDLY_FORMAT_REQUIREMENT,
+    get_vocabulary_enforce_prompt,
+)
 
 
 def get_subagent_summary_prompt() -> str:
@@ -11,6 +14,7 @@ def get_subagent_summary_prompt() -> str:
 3. Providing expert commentary on the implications of the results
 4. Provide domain-specific considerations that contextualize the results (without actionable advices).
 
+{get_vocabulary_enforce_prompt()}
 
 # Format Requirements:
 {HUMAN_FRIENDLY_FORMAT_REQUIREMENT}

agents/matmaster_agent/prompt.py

@@ -143,6 +143,32 @@ def get_naming_rules_text():
    - Exception: If discussing a commercial product specifically sold under a trade name (e.g., "Sigma-Aldrich ZIF-8"), use the trade name but reference the scientific name in parentheses.
 """
 
+DOMAIN_SPECIFIC_VOCABULARY = {
+    'deep potential': '深度学习势函数',
+    'Deep Potential Molecular Dynamics': '深度学习势分子动力学',
+    'DPMD': '深度学习势分子动力学',
+    'DPA': 'DPA预训练原子间势函数',
+}
+
+
+def get_vocabulary_enforce_prompt() -> str:
+    mapping_list = '\n'.join(
+        [f'   - "{eng}" → "{chn}"' for eng, chn in DOMAIN_SPECIFIC_VOCABULARY.items()]
+    )
+
+    return f"""
+### DOMAIN-SPECIFIC VOCABULARY STANDARDS
+To ensure professional consistency, you strictly MUST adhere to the following terminology rules **based on your output language**:
+
+**Condition A: If you are responding in CHINESE (中文):**
+You MUST translate the following terms into their designated Chinese equivalents:
+{mapping_list}
+
+**Condition B: If you are responding in ENGLISH:**
+You MUST use the original English terms (e.g., "Deep Potential", "DPMD"). **DO NOT** use the Chinese translations in English sentences.
+"""
+
+
 STRUCTURE_BUILDING_SAVENAME = """
 Rules (MUST follow, no exceptions):
 1. ASCII letters/digits/underscores only; no spaces or symbols.