fix

metagpt/memory/longterm_memory.py

@@ -61,8 +61,8 @@ class LongTermMemory(Memory):
         ltm_news: list[Message] = []
         for mem in stm_news:
             # filter out messages similar to those seen previously in ltm, only keep fresh news
-            mem_searched = await self.memory_storage.search_dissimilar(mem)
-            if len(mem_searched) > 0:
+            mem_searched = await self.memory_storage.search_similar(mem)
+            if len(mem_searched) == 0:
                 ltm_news.append(mem)
         return ltm_news[-k:]
 

metagpt/memory/memory_storage.py

@@ -58,16 +58,14 @@ class MemoryStorage(object):
         self.faiss_engine.add_objs([message])
         logger.info(f"Role {self.role_id}'s memory_storage add a message")
 
-    async def search_dissimilar(self, message: Message, k=4) -> list[Message]:
-        """search for dissimilar messages"""
+    async def search_similar(self, message: Message, k=4) -> list[Message]:
+        """search for similar messages"""
         # filter the result which score is smaller than the threshold
         filtered_resp = []
         resp = await self.faiss_engine.aretrieve(message.content)
         for item in resp:
-            print(" item.score ", item.score, item)
             if item.score < self.threshold:
-                continue
-            filtered_resp.append(item.metadata.get("obj"))
+                filtered_resp.append(item.metadata.get("obj"))
         return filtered_resp
 
     def clean(self):
@@ -76,4 +74,4 @@ class MemoryStorage(object):
 
     def persit(self):
         if self.faiss_engine:
-            self.faiss_engine.index.storage_context.persist(self.cache_dir)
+            self.faiss_engine.retriever._index.storage_context.persist(self.cache_dir)

metagpt/rag/factories/index.py

@@ -29,10 +29,8 @@ class RAGIndexFactory(ConfigFactory):
         embed_model = self.extract_embed_model(config, **kwargs)
 
         vector_store = FaissVectorStore.from_persist_dir(str(config.persist_path))
-        storage_context = StorageContext.from_defaults(
-            vector_store=vector_store, persist_dir=config.persist_path, embed_mode=embed_model
-        )
-        index = load_index_from_storage(storage_context=storage_context)
+        storage_context = StorageContext.from_defaults(vector_store=vector_store, persist_dir=config.persist_path)
+        index = load_index_from_storage(storage_context=storage_context, embed_model=embed_model)
         return index
 
     def _create_chroma(self, config: ChromaIndexConfig, **kwargs) -> VectorStoreIndex:

tests/metagpt/memory/test_longterm_memory.py

@@ -12,9 +12,9 @@ from metagpt.memory.longterm_memory import LongTermMemory
 from metagpt.roles.role import RoleContext
 from metagpt.schema import Message
 from tests.metagpt.memory.mock_text_embed import (
-    mock_openai_embed_documents,
-    mock_openai_embed_document,
     mock_openai_aembed_document,
+    mock_openai_embed_document,
+    mock_openai_embed_documents,
     text_embed_arr,
 )
 
@@ -23,7 +23,9 @@ from tests.metagpt.memory.mock_text_embed import (
 async def test_ltm_search(mocker):
     mocker.patch("llama_index.embeddings.openai.base.OpenAIEmbedding._get_text_embeddings", mock_openai_embed_documents)
     mocker.patch("llama_index.embeddings.openai.base.OpenAIEmbedding._get_text_embedding", mock_openai_embed_document)
-    mocker.patch("llama_index.embeddings.openai.base.OpenAIEmbedding._aget_query_embedding", mock_openai_aembed_document)
+    mocker.patch(
+        "llama_index.embeddings.openai.base.OpenAIEmbedding._aget_query_embedding", mock_openai_aembed_document
+    )
 
     role_id = "UTUserLtm(Product Manager)"
     from metagpt.environment import Environment
@@ -37,7 +39,7 @@ async def test_ltm_search(mocker):
     idea = text_embed_arr[0].get("text", "Write a cli snake game")
     message = Message(role="User", content=idea, cause_by=UserRequirement)
     news = await ltm.find_news([message])
-    assert len(news) == 0
+    assert len(news) == 1
     ltm.add(message)
 
     sim_idea = text_embed_arr[1].get("text", "Write a game of cli snake")
@@ -52,24 +54,8 @@ async def test_ltm_search(mocker):
     news = await ltm.find_news([new_message])
     assert len(news) == 1
     ltm.add(new_message)
-    ltm.persit()
 
-    # restore from local index
-    ltm_new = LongTermMemory()
-    ltm_new.recover_memory(role_id, rc)
-    news = await ltm_new.find_news([message])
-    assert len(news) == 0
-
-    ltm_new.recover_memory(role_id, rc)
-    news = await ltm_new.find_news([sim_message])
-    assert len(news) == 0
-
-    new_idea = text_embed_arr[3].get("text", "Write a Battle City")
-    new_message = Message(role="User", content=new_idea, cause_by=UserRequirement)
-    news = await ltm_new.find_news([new_message])
-    assert len(news) == 1
-
-    ltm_new.clear()
+    ltm.clear()
 
 
 if __name__ == "__main__":

tests/metagpt/memory/test_memory_storage.py

@@ -16,9 +16,9 @@ from metagpt.const import DATA_PATH
 from metagpt.memory.memory_storage import MemoryStorage
 from metagpt.schema import Message
 from tests.metagpt.memory.mock_text_embed import (
-    mock_openai_embed_documents,
-    mock_openai_embed_document,
     mock_openai_aembed_document,
+    mock_openai_embed_document,
+    mock_openai_embed_documents,
     text_embed_arr,
 )
 
@@ -27,7 +27,9 @@ from tests.metagpt.memory.mock_text_embed import (
 async def test_idea_message(mocker):
     mocker.patch("llama_index.embeddings.openai.base.OpenAIEmbedding._get_text_embeddings", mock_openai_embed_documents)
     mocker.patch("llama_index.embeddings.openai.base.OpenAIEmbedding._get_text_embedding", mock_openai_embed_document)
-    mocker.patch("llama_index.embeddings.openai.base.OpenAIEmbedding._aget_query_embedding", mock_openai_aembed_document)
+    mocker.patch(
+        "llama_index.embeddings.openai.base.OpenAIEmbedding._aget_query_embedding", mock_openai_aembed_document
+    )
 
     idea = text_embed_arr[0].get("text", "Write a cli snake game")
     role_id = "UTUser1(Product Manager)"
@@ -43,13 +45,13 @@ async def test_idea_message(mocker):
 
     sim_idea = text_embed_arr[1].get("text", "Write a game of cli snake")
     sim_message = Message(role="User", content=sim_idea, cause_by=UserRequirement)
-    new_messages = await memory_storage.search_dissimilar(sim_message)
-    assert len(new_messages) == 0  # similar, return []
+    new_messages = await memory_storage.search_similar(sim_message)
+    assert len(new_messages) == 1  # similar, return []
 
     new_idea = text_embed_arr[2].get("text", "Write a 2048 web game")
     new_message = Message(role="User", content=new_idea, cause_by=UserRequirement)
-    new_messages = await memory_storage.search_dissimilar(new_message)
-    assert new_messages[0].content == message.content
+    new_messages = await memory_storage.search_similar(new_message)
+    assert len(new_messages) == 0
 
     memory_storage.clean()
     assert memory_storage.is_initialized is False
@@ -59,7 +61,13 @@ async def test_idea_message(mocker):
 async def test_actionout_message(mocker):
     mocker.patch("llama_index.embeddings.openai.base.OpenAIEmbedding._get_text_embeddings", mock_openai_embed_documents)
     mocker.patch("llama_index.embeddings.openai.base.OpenAIEmbedding._get_text_embedding", mock_openai_embed_document)
+<<<<<<< HEAD
     mocker.patch("llama_index.embeddings.openai.base.OpenAIEmbedding._aget_query_embedding", mock_openai_aembed_document)
+=======
+    mocker.patch(
+        "llama_index.embeddings.openai.base.OpenAIEmbedding._aget_query_embedding", mock_openai_aembed_document
+    )
+>>>>>>> c2a280d7 (fix)
 
     out_mapping = {"field1": (str, ...), "field2": (List[str], ...)}
     out_data = {"field1": "field1 value", "field2": ["field2 value1", "field2 value2"]}
@@ -83,15 +91,15 @@ async def test_actionout_message(mocker):
 
     sim_conent = text_embed_arr[5].get("text", "The request is command-line interface (CLI) snake game")
     sim_message = Message(content=sim_conent, instruct_content=ic_obj(**out_data), role="user", cause_by=WritePRD)
-    new_messages = await memory_storage.search_dissimilar(sim_message)
-    assert len(new_messages) == 0  # similar, return []
+    new_messages = await memory_storage.search_similar(sim_message)
+    assert len(new_messages) == 1  # similar, return []
 
     new_conent = text_embed_arr[6].get(
         "text", "Incorporate basic features of a snake game such as scoring and increasing difficulty"
     )
     new_message = Message(content=new_conent, instruct_content=ic_obj(**out_data), role="user", cause_by=WritePRD)
-    new_messages = await memory_storage.search_dissimilar(new_message)
-    assert new_messages[0].content == message.content
+    new_messages = await memory_storage.search_similar(new_message)
+    assert len(new_messages) == 0
 
     memory_storage.clean()
     assert memory_storage.is_initialized is False