Remove embeddings as argument in archival_memory.insert (#284)

memgpt/agent.py

@@ -800,8 +800,8 @@ def recall_memory_search_date(self, start_date, end_date, count=5, page=0):
             results_str = f"{results_pref} {json.dumps(results_formatted)}"
         return results_str
 
-    def archival_memory_insert(self, content, embedding=None):
-        self.persistence_manager.archival_memory.insert(content, embedding=None)
+    def archival_memory_insert(self, content):
+        self.persistence_manager.archival_memory.insert(content)
         return None
 
     def archival_memory_search(self, query, count=5, page=0):
@@ -1245,8 +1245,8 @@ async def recall_memory_search_date(self, start_date, end_date, count=5, page=0)
             results_str = f"{results_pref} {json.dumps(results_formatted)}"
         return results_str
 
-    async def archival_memory_insert(self, content, embedding=None):
-        await self.persistence_manager.archival_memory.a_insert(content, embedding=None)
+    async def archival_memory_insert(self, content):
+        await self.persistence_manager.archival_memory.a_insert(content)
         return None
 
     async def archival_memory_search(self, query, count=5, page=0):

memgpt/memory.py

@@ -231,9 +231,7 @@ def __repr__(self) -> str:
             memory_str = "\n".join([d["content"] for d in self._archive])
         return f"\n### ARCHIVAL MEMORY ###" + f"\n{memory_str}"
 
-    def insert(self, memory_string, embedding=None):
-        if embedding is not None:
-            raise ValueError("Basic text-based archival memory does not support embeddings")
+    def insert(self, memory_string):
         self._archive.append(
             {
                 # can eventually upgrade to adding semantic tags, etc
@@ -242,8 +240,8 @@ def insert(self, memory_string, embedding=None):
             }
         )
 
-    async def a_insert(self, memory_string, embedding=None):
-        return self.insert(memory_string, embedding)
+    async def a_insert(self, memory_string):
+        return self.insert(memory_string)
 
     def search(self, query_string, count=None, start=None):
         """Simple text-based search"""
@@ -293,14 +291,12 @@ def _insert(self, memory_string, embedding):
             }
         )
 
-    def insert(self, memory_string, embedding=None):
-        if embedding is None:
-            embedding = get_embedding_with_backoff(memory_string, model=self.embedding_model)
+    def insert(self, memory_string):
+        embedding = get_embedding_with_backoff(memory_string, model=self.embedding_model)
         return self._insert(memory_string, embedding)
 
-    async def a_insert(self, memory_string, embedding=None):
-        if embedding is None:
-            embedding = await async_get_embedding_with_backoff(memory_string, model=self.embedding_model)
+    async def a_insert(self, memory_string):
+        embedding = await async_get_embedding_with_backoff(memory_string, model=self.embedding_model)
         return self._insert(memory_string, embedding)
 
     def _search(self, query_embedding, query_string, count, start):
@@ -382,16 +378,14 @@ def _insert(self, memory_string, embedding):
         embedding = np.array([embedding]).astype("float32")
         self.index.add(embedding)
 
-    def insert(self, memory_string, embedding=None):
-        if embedding is None:
-            # Get the embedding
-            embedding = get_embedding_with_backoff(memory_string, model=self.embedding_model)
+    def insert(self, memory_string):
+        # Get the embedding
+        embedding = get_embedding_with_backoff(memory_string, model=self.embedding_model)
         return self._insert(memory_string, embedding)
 
-    async def a_insert(self, memory_string, embedding=None):
-        if embedding is None:
-            # Get the embedding
-            embedding = await async_get_embedding_with_backoff(memory_string, model=self.embedding_model)
+    async def a_insert(self, memory_string):
+        # Get the embedding
+        embedding = await async_get_embedding_with_backoff(memory_string, model=self.embedding_model)
         return self._insert(memory_string, embedding)
 
     def _search(self, query_embedding, query_string, count=None, start=None):
@@ -814,7 +808,7 @@ def search(self, query_string, count=None, start=None):
     async def a_search(self, query_string, count=None, start=None):
         return self.search(query_string, count, start)
 
-    async def a_insert(self, memory_string, embedding=None):
+    async def a_insert(self, memory_string):
         return self.insert(memory_string)
 
     def __repr__(self) -> str: