fix: align default model names with SDK defaults (#6704)

integrations/openclaw/cli/commands.ts

@@ -1449,7 +1449,7 @@ export function registerCliCommands(
             console.log("    openclaw mem0 config set auto_recall false");
           } else {
             console.log("    openclaw mem0 config set vector_provider qdrant");
-            console.log("    openclaw mem0 config set llm_model gpt-4o");
+            console.log("    openclaw mem0 config set llm_model gpt-5-mini");
             console.log("    openclaw mem0 config set embedder_provider openai");
           }
           console.log("");

mem0-ts/src/community/src/integrations/langchain/mem0.ts

@@ -141,7 +141,7 @@ export interface Mem0MemoryInput extends BaseChatMemoryInput {
  *
  * // Use with a chat model
  * const model = new ChatOpenAI({
- *   modelName: "gpt-3.5-turbo",
+ *   modelName: "gpt-5-mini",
  *   temperature: 0,
  * });
  *

mem0/configs/llms/base.py

@@ -31,7 +31,7 @@ class BaseLlmConfig(ABC):
         Initialize a base configuration class instance for the LLM.
 
         Args:
-            model: The model identifier to use (e.g., "gpt-4.1-nano-2025-04-14", "claude-3-5-sonnet-20240620")
+            model: The model identifier to use (e.g., "gpt-5-mini", "claude-3-5-sonnet-20240620")
                 Defaults to None (will be set by provider-specific configs)
             temperature: Controls the randomness of the model's output.
                 Higher values (closer to 1) make output more random, lower values make it more deterministic.

mem0/exceptions.py

@@ -353,7 +353,7 @@ class LLMError(MemoryError):
         raise LLMError(
             message="LLM operation failed",
             error_code="LLM_001",
-            details={"model": "gpt-4", "prompt_length": 500},
+            details={"model": "gpt-5-mini", "prompt_length": 500},
             suggestion="Please check your LLM configuration and API key"
         )
     """

server/.env.example

@@ -21,7 +21,7 @@ APP_DB_NAME=mem0_app
 
 # Default LLM and embedder models. Provider must be in BUNDLED_*_PROVIDERS
 # (see server/main.py). Override to pin a specific model without editing code.
-MEM0_DEFAULT_LLM_MODEL=gpt-4.1-nano-2025-04-14
+MEM0_DEFAULT_LLM_MODEL=gpt-5-mini
 MEM0_DEFAULT_EMBEDDER_MODEL=text-embedding-3-small
 
 # Anonymous telemetry. Sends a single onboarding event per install

server/main.py

@@ -19,7 +19,6 @@ from errors import (
 from fastapi import Depends, FastAPI, HTTPException, Query, Request
 from fastapi.middleware.cors import CORSMiddleware
 from fastapi.responses import JSONResponse, RedirectResponse
-from mem0.exceptions import ValidationError as Mem0ValidationError
 from models import RequestLog, User
 from pydantic import BaseModel, Field
 from rate_limit import limiter
@@ -39,6 +38,8 @@ from slowapi import _rate_limit_exceeded_handler
 from slowapi.errors import RateLimitExceeded
 from sqlalchemy import func, select
 
+from mem0.exceptions import ValidationError as Mem0ValidationError
+
 load_dotenv()
 
 install_request_id_logging()
@@ -113,7 +114,7 @@ POSTGRES_COLLECTION_NAME = os.environ.get("POSTGRES_COLLECTION_NAME", "memories"
 
 OPENAI_API_KEY = os.environ.get("OPENAI_API_KEY")
 HISTORY_DB_PATH = os.environ.get("HISTORY_DB_PATH", "/app/history/history.db")
-DEFAULT_LLM_MODEL = os.environ.get("MEM0_DEFAULT_LLM_MODEL", "gpt-4.1-nano-2025-04-14")
+DEFAULT_LLM_MODEL = os.environ.get("MEM0_DEFAULT_LLM_MODEL", "gpt-5-mini")
 DEFAULT_EMBEDDER_MODEL = os.environ.get("MEM0_DEFAULT_EMBEDDER_MODEL", "text-embedding-3-small")
 
 DEFAULT_CONFIG = {