message

agents/base_agent.py

@@ -19,16 +19,18 @@ class AgentMessage:
 class BaseAgent:
     """Agent 基类"""
     
-    def __init__(self, agent_id: str, llm_client):
+    def __init__(self, agent_id: str, llm_client, language: str = "Chinese"):
         """
         初始化 Agent
         
         Args:
             agent_id: Agent 标识符 (如 'ceo', 'cto')
             llm_client: LLM 客户端实例
+            language: 输出语言
         """
         self.agent_id = agent_id
         self.llm_client = llm_client
+        self.language = language
         
         profile = get_agent_profile(agent_id)
         if not profile:
@@ -38,7 +40,7 @@ class BaseAgent:
         self.emoji = profile["emoji"]
         self.perspective = profile["perspective"]
         self.focus_areas = profile["focus_areas"]
-        self.system_prompt = profile["system_prompt"]
+        self.system_prompt = f"{profile['system_prompt']}\n\nIMPORTANT: You MUST output your response in {self.language}."
         
         # 存储对话历史
         self.conversation_history = []

agents/research_agent.py

@@ -5,26 +5,28 @@ import config
 class ResearchAgent:
     """研究模式专用 Agent"""
     
-    def __init__(self, role: str, llm_client: LLMClient, name: str = None):
+    def __init__(self, role: str, llm_client: LLMClient, name: str = None, language: str = "Chinese"):
         self.role = role
         self.llm_client = llm_client
         self.role_config = config.RESEARCH_MODEL_ROLES.get(role, {})
         self.name = name if name else self.role_config.get("name", role.capitalize())
+        self.language = language
         
     @property
     def model_name(self) -> str:
         return self.llm_client.model
 
     def _get_system_prompt(self, context: str = "") -> str:
+        base_prompt = ""
         if self.role == "council_member":
-            return f"""You are {self.name}, a member of the Multi-Model Decision Council.
+            base_prompt = f"""You are {self.name}, a member of the Multi-Model Decision Council.
 Your goal is to participate in a round-table discussion to solve the user's problem.
 Be conversational, insightful, and constructive.
 Build upon others' ideas or respectfully disagree with valid reasoning.
 Context: {context}"""
 
         elif self.role == "expert_a":
-            return f"""You are Expert A, a Senior Analyst.
+            base_prompt = f"""You are Expert A, a Senior Analyst.
 You are participating in a round-table discussion.
 Your goal is to analyze the topic and propose solutions.
 Be conversational, direct, and responsive to other experts. 
@@ -32,21 +34,23 @@ Do not write a full final report; focus on the current discussion turn.
 Context: {context}"""
         
         elif self.role == "expert_b":
-            return f"""You are Expert B, a Critical Reviewer.
+            base_prompt = f"""You are Expert B, a Critical Reviewer.
 You are participating in a round-table discussion.
 Your goal is to critique Expert A's points and offer alternative perspectives.
 Be conversational and constructive. Challenge assumptions directly.
 Context: {context}"""
         
         elif self.role == "expert_c":
-            return f"""You are Expert C, a Senior Strategist and Visual Thinker.
+            base_prompt = f"""You are Expert C, a Senior Strategist and Visual Thinker.
 Your goal is to synthesize the final output. 
 Combine the structural strength of Expert A with the critical insights of Expert B.
 Produce a final, polished, comprehensive plan or report.
 CRITICAL: You MUST include a Mermaid.js diagram (using ```mermaid code block) to visualize the timeline, process, or architecture."""
         
         else:
-            return "You are a helpful assistant."
+            base_prompt = "You are a helpful assistant."
+            
+        return f"{base_prompt}\n\nIMPORTANT: You MUST output your response in {self.language}."
 
     def generate(self, prompt: str, context: str = "") -> Generator[str, None, None]:
         """Generate response stream"""

app.py

@@ -137,6 +137,14 @@ with st.sidebar:
         if not api_key:
             st.warning("请配置 API Key 以继续")
             
+    # Output Language Selection
+    output_language = st.sidebar.selectbox(
+        "🌐 输出语言",
+        options=config.SUPPORTED_LANGUAGES,
+        index=0,
+        help="所有 AI Agent 将使用此语言进行回复"
+    )
+            
     st.divider()
     
     # 模式选择
@@ -261,7 +269,8 @@ if mode == "Deep Research":
         config_obj = ResearchConfig(
             topic=research_topic,
             context=research_context,
-            experts=experts_config
+            experts=experts_config,
+            language=output_language
         )
         manager.create_agents(config_obj)
         
@@ -481,7 +490,8 @@ elif mode == "Debate Workshop":
                 context=context,
                 agent_ids=selected_agents,
                 max_rounds=max_rounds,
-                agent_clients=agent_clients
+                agent_clients=agent_clients,
+                language=output_language
             )
             debate_manager.setup_debate(debate_config)
             

config.py

@@ -93,6 +93,9 @@ AVAILABLE_MODELS = {
 MAX_DEBATE_ROUNDS = 3  # 最大辩论轮数
 MAX_AGENTS = 6  # 最大参与 Agent 数量
 
+# 支持的输出语言
+SUPPORTED_LANGUAGES = ["Chinese", "English", "Japanese", "Spanish", "French", "German"]
+
 # 研究模式模型角色配置
 RESEARCH_MODEL_ROLES = {
     "expert_a": {

orchestrator/debate_manager.py

@@ -18,6 +18,7 @@ class DebateConfig:
     agent_ids: List[str] = None
     max_rounds: int = 2
     agent_clients: dict = None # Map[agent_id, LLMClient]
+    language: str = "Chinese"
     
 
 @dataclass  
@@ -64,7 +65,7 @@ class DebateManager:
             if hasattr(debate_config, 'agent_clients') and debate_config.agent_clients and agent_id in debate_config.agent_clients:
                  client = debate_config.agent_clients[agent_id]
             
-            agent = BaseAgent(agent_id, client)
+            agent = BaseAgent(agent_id, client, language=debate_config.language)
             self.agents.append(agent)
     
     def run_debate_stream(

orchestrator/research_manager.py

@@ -10,6 +10,7 @@ class ResearchConfig:
     context: str = ""
     # Dynamic list of experts: [{"name": "Expert 1", "model": "gpt-4o", "role": "analyst"}, ...]
     experts: List[Dict[str, str]] = None 
+    language: str = "Chinese"
 
 class ResearchManager:
     """Manages the Multi-Model Council workflow"""
@@ -33,19 +34,12 @@ class ResearchManager:
         self.agents = []
         if config.experts:
             for idx, expert_conf in enumerate(config.experts):
-                # Assign role based on position or config
-                # First agents are discussion members, last one is Synthesizer usually, 
-                # but for equality we treat them all as members until the end.
-                # We'll assign a generic "member" role or specific if provided.
-                
                 role_type = "council_member"
-                # If it's the last one, maybe give them synthesizer duty? 
-                # For now, all are members, and we explicitly pick one for synthesis.
-                
                 agent = ResearchAgent(
                     role=role_type, 
                     llm_client=self._get_client(expert_conf["model"]),
-                    name=expert_conf.get("name", f"Expert {idx+1}")
+                    name=expert_conf.get("name", f"Expert {idx+1}"),
+                    language=config.language
                 )
                 self.agents.append(agent)