fix: patch error on memory overflow

memgpt/client/client.py

@@ -51,7 +51,7 @@
 # import pydantic response objects from memgpt.server.rest_api
 from memgpt.server.rest_api.tools.index import CreateToolRequest, ListToolsResponse
 from memgpt.server.server import SyncServer
-from memgpt.utils import get_human_text
+from memgpt.utils import get_human_text, get_persona_text
 
 
 def create_client(base_url: Optional[str] = None, token: Optional[str] = None):
@@ -259,7 +259,7 @@ def create_agent(
         embedding_config: Optional[EmbeddingConfig] = None,
         llm_config: Optional[LLMConfig] = None,
         # memory
-        memory: BaseMemory = ChatMemory(human=get_human_text(DEFAULT_HUMAN), persona=get_human_text(DEFAULT_PERSONA)),
+        memory: BaseMemory = ChatMemory(human=get_human_text(DEFAULT_HUMAN), persona=get_persona_text(DEFAULT_PERSONA)),
         # system prompt (can be templated)
         system_prompt: Optional[str] = None,
         # tools
@@ -729,7 +729,7 @@ def create_agent(
         embedding_config: Optional[EmbeddingConfig] = None,
         llm_config: Optional[LLMConfig] = None,
         # memory
-        memory: BaseMemory = ChatMemory(human=get_human_text(DEFAULT_HUMAN), persona=get_human_text(DEFAULT_PERSONA)),
+        memory: BaseMemory = ChatMemory(human=get_human_text(DEFAULT_HUMAN), persona=get_persona_text(DEFAULT_PERSONA)),
         # system prompt (can be templated)
         system_prompt: Optional[str] = None,
         # tools

memgpt/memory.py

@@ -1,5 +1,6 @@
 import datetime
 import uuid
+import warnings
 from abc import ABC, abstractmethod
 from typing import List, Optional, Tuple, Union
 
@@ -19,6 +20,7 @@
 )
 
 
+# always run validation
 class MemoryModule(BaseModel):
     """Base class for memory modules"""
 
@@ -31,10 +33,11 @@ def __setattr__(self, name, value):
         super().__setattr__(name, value)
         if name == "value":
             # run validation
-            self.__class__.validate(self.dict(exclude_unset=True))
+            self.__class__.validate(self.dict(exclude_unset=True))  # TODO: not sure what this does
 
-    @validator("value", always=True)
+    @validator("value", always=True, check_fields=False)
     def check_value_length(cls, v, values):
+        # TODO: this doesn't run all the time, should fix
         if v is not None:
             # Fetching the limit from the values dictionary
             limit = values.get("limit", 2000)  # Default to 2000 if limit is not yet set
@@ -48,10 +51,9 @@ def check_value_length(cls, v, values):
                 raise ValueError("Value must be either a string or a list of strings.")
 
             if length > limit:
-                error_msg = f"Edit failed: Exceeds {limit} character limit (requested {length})."
-                # TODO: add archival memory error?
-                raise ValueError(error_msg)
-        return v
+                raise ValueError(f"Value exceeds {limit} character limit (requested {length}).")
+
+            return v
 
     def __len__(self):
         return len(str(self))
@@ -93,6 +95,14 @@ def to_dict(self):
 class ChatMemory(BaseMemory):
 
     def __init__(self, persona: str, human: str, limit: int = 2000):
+        # TODO: clip if needed
+        if persona and len(persona) > limit:
+            warnings.warn(f"Persona exceeds {limit} character limit (requested {len(persona)}).")
+            persona = persona[:limit]
+
+        if human and len(human) > limit:
+            warnings.warn(f"Human exceeds {limit} character limit (requested {len(human)}).")
+            human = human[:limit]
         self.memory = {
             "persona": MemoryModule(name="persona", value=persona, limit=limit),
             "human": MemoryModule(name="human", value=human, limit=limit),