result

minion/actions/lmp_action_node.py

@@ -36,7 +36,7 @@ async def execute(self, messages: Union[str, Message, List[Message]], response_f
 
         # 从 llm.config 获取配置
         api_params = {
-            "temperature": self.llm.config.temperature + random.random() * 0.01,
+            "temperature": self.llm.config.temperature + random.random() * 0.01, #add random to avoid prompt caching
             "model": self.llm.config.model,
         }
 

minion/main/ldb_worker.py

@@ -191,7 +191,7 @@ async def execute(self):
                 entry=self.input.entry_point,
                 model=self.model,
                 messages=messages,
-                dataset_type=self.input.dataset,
+                dataset_type=self.input.dataset, #todo: this dataset type is just for prompt
                 level="block"
             )
             self.input.metadata["messages"] = messages
@@ -226,7 +226,7 @@ async def execute(self):
                     failed_tests=self.input.metadata["ldb_format_test"] ,
                     num_comps=1,
                     temperature=self.brain.llm.config.temperature,
-                    dataset_type=self.input.dataset
+                    dataset_type=self.input.dataset #todo: this dataset type is just for prompt
                 )
 
                 self.answer = answer

minion/main/worker.py

@@ -622,7 +622,7 @@ async def choose_minion_and_run(self):
             return await self.execute_single()
 
     async def execute_ensemble(self):
-        if 'workers_config' not in self.input.execution_config:
+        if 'workers' not in self.input.execution_config:
             return await self.execute_single()
 
         # Get the result strategy
@@ -632,7 +632,7 @@ async def execute_ensemble(self):
 
         workers = []  # List to store actual worker instances
 
-        for worker_config in self.input.execution_config["workers_config"]:
+        for worker_config in self.input.execution_config["workers"]:
             minion_name = worker_config["name"]
             count = worker_config["count"]
             post_processing = worker_config.get("post_processing")
@@ -663,7 +663,7 @@ async def execute(self):
 
         if self.input.execution_state.current_minion:
             # Resume from previous state, assume pre_processing already been done
-            if hasattr(self.input, 'type') and self.input.type == "ensemble":
+            if hasattr(self.input, 'execution_config') and self.input.execution_config['type'] == "ensemble":
                 await self.execute_ensemble()
             else:
                 await self.execute_single()
@@ -768,7 +768,7 @@ async def get_minion_class_and_name(self):
         else:
             # 智能选择逻辑
             choose_template = Template(SMART_PROMPT_TEMPLATE)
-            filtered_registry = {key: value for key, value in MINION_REGISTRY.items()}
+            filtered_registry = {key: value for key, value in WORKER_MINIONS.items()}
             filled_template = choose_template.render(minions=filtered_registry, input=self.input)
 
             # 如果brain.llms中有route配置，则依次尝试每个LLM

requirements.txt

@@ -38,5 +38,6 @@ astor
 graphviz
 #vllm
 astroid
+pysnooper
 #ldb dependencies
 #llmdebugger