Merge branch 'feat-memory-opt' into 'mgx_ops'

make memory_k configurable

See merge request pub/MetaGPT!392

config/config2.example.yaml

@@ -86,6 +86,9 @@ exp_pool:
 role_zero:
   enable_longterm_memory: false # Whether to use long-term memory. Default is `false`.
   longterm_memory_persist_path: .role_memory_data # The directory to save data.
+  memory_k: 200 # The capacity of short-term memory.
+  similarity_top_k: 5 # The number of long-term memories to retrieve.
+  use_llm_ranker: false # Whether to use LLM Reranker to get better result. Default is `false`.
 
 azure_tts_subscription_key: "YOUR_SUBSCRIPTION_KEY"
 azure_tts_region: "eastus"

metagpt/configs/role_zero_config.py

@@ -6,3 +6,6 @@ from metagpt.utils.yaml_model import YamlModel
 class RoleZeroConfig(YamlModel):
     enable_longterm_memory: bool = Field(default=False, description="Whether to use long-term memory.")
     longterm_memory_persist_path: str = Field(default=".role_memory_data", description="The directory to save data.")
+    memory_k: int = Field(default=200, description="The capacity of short-term memory.")
+    similarity_top_k: int = Field(default=5, description="The number of long-term memories to retrieve.")
+    use_llm_ranker: bool = Field(default=False, description="Whether to use LLM Reranker to get better result.")

metagpt/memory/role_zero_memory.py

@@ -31,6 +31,8 @@ class RoleZeroLongTermMemory(Memory):
     persist_path: str = Field(default=".role_memory_data", description="The directory to save data.")
     collection_name: str = Field(default="role_zero", description="The name of the collection, such as the role name.")
     memory_k: int = Field(default=200, description="The capacity of short-term memory.")
+    similarity_top_k: int = Field(default=5, description="The number of long-term memories to retrieve.")
+    use_llm_ranker: bool = Field(default=False, description="Whether to use LLM Reranker to get better result.")
 
     _rag_engine: Any = None
 
@@ -49,14 +51,18 @@ class RoleZeroLongTermMemory(Memory):
 
         try:
             from metagpt.rag.engines import SimpleEngine
-            from metagpt.rag.schema import ChromaRetrieverConfig
+            from metagpt.rag.schema import ChromaRetrieverConfig, LLMRankerConfig
         except ImportError:
             raise ImportError("To use the RoleZeroMemory, you need to install the rag module.")
 
         retriever_configs = [
-            ChromaRetrieverConfig(persist_path=self.persist_path, collection_name=self.collection_name)
+            ChromaRetrieverConfig(
+                persist_path=self.persist_path,
+                collection_name=self.collection_name,
+                similarity_top_k=self.similarity_top_k,
+            )
         ]
-        ranker_configs = []
+        ranker_configs = [LLMRankerConfig()] if self.use_llm_ranker else []
 
         rag_engine = SimpleEngine.from_objs(retriever_configs=retriever_configs, ranker_configs=ranker_configs)
 

metagpt/roles/di/role_zero.py

@@ -181,11 +181,14 @@ class RoleZero(Role):
         """
 
         if self.config.role_zero.enable_longterm_memory:
+            # Use config.role_zero to initialize long-term memory
             self.rc.memory = RoleZeroLongTermMemory(
                 **self.rc.memory.model_dump(),
                 persist_path=self.config.role_zero.longterm_memory_persist_path,
                 collection_name=self.name.replace(" ", ""),
-                memory_k=self.memory_k,
+                memory_k=self.config.role_zero.memory_k,
+                similarity_top_k=self.config.role_zero.similarity_top_k,
+                use_llm_ranker=self.config.role_zero.use_llm_ranker,
             )
             logger.info(f"Long-term memory set for role '{self.name}'")