User/dyadav/fix telemetry issue (#2541)

Author: deshraj

mem0/client/main.py

@@ -5,14 +5,17 @@
 from typing import Any, Dict, List, Optional, Union
 
 import httpx
-import hashlib
 
+from mem0.memory.setup import get_user_id, setup_config
 from mem0.memory.telemetry import capture_client_event
 
 logger = logging.getLogger(__name__)
 
 warnings.filterwarnings("default", category=DeprecationWarning)
 
+# Setup user config
+setup_config()
+
 
 class APIError(Exception):
     """Exception raised for errors in the API."""
@@ -75,13 +78,11 @@ def __init__(
         self.host = host or "https://api.mem0.ai"
         self.org_id = org_id
         self.project_id = project_id
+        self.user_id = get_user_id()
 
         if not self.api_key:
             raise ValueError("Mem0 API Key not provided. Please provide an API Key.")
 
-        # Create MD5 hash of API key for user_id
-        self.user_id = hashlib.md5(self.api_key.encode()).hexdigest()
-
         self.client = httpx.Client(
             base_url=self.host,
             headers={"Authorization": f"Token {self.api_key}", "Mem0-User-ID": self.user_id},

mem0/configs/base.py

@@ -6,12 +6,9 @@
 from mem0.embeddings.configs import EmbedderConfig
 from mem0.graphs.configs import GraphStoreConfig
 from mem0.llms.configs import LlmConfig
+from mem0.memory.setup import mem0_dir
 from mem0.vector_stores.configs import VectorStoreConfig
 
-# Set up the directory path
-home_dir = os.path.expanduser("~")
-mem0_dir = os.environ.get("MEM0_DIR") or os.path.join(home_dir, ".mem0")
-
 
 class MemoryItem(BaseModel):
     id: str = Field(..., description="The unique identifier for the text data")

mem0/configs/vector_stores/azure_ai_search.py

@@ -7,7 +7,7 @@ class AzureAISearchConfig(BaseModel):
     collection_name: str = Field("mem0", description="Name of the collection")
     service_name: str = Field(None, description="Azure AI Search service name")
     api_key: str = Field(None, description="API key for the Azure AI Search service")
-    embedding_model_dims: int = Field(1536, description="Dimension of the embedding vector")
+    embedding_model_dims: int = Field(None, description="Dimension of the embedding vector")
     compression_type: Optional[str] = Field(
         None, description="Type of vector compression to use. Options: 'scalar', 'binary', or None"
     )

mem0/memory/main.py

@@ -3,7 +3,6 @@
 import hashlib
 import json
 import logging
-import os
 import uuid
 import warnings
 from datetime import datetime
@@ -19,7 +18,7 @@
     get_update_memory_messages,
 )
 from mem0.memory.base import MemoryBase
-from mem0.memory.setup import mem0_dir, setup_config
+from mem0.memory.setup import setup_config
 from mem0.memory.storage import SQLiteManager
 from mem0.memory.telemetry import capture_event
 from mem0.memory.utils import (
@@ -63,15 +62,6 @@ def __init__(self, config: MemoryConfig = MemoryConfig()):
             self.graph = MemoryGraph(self.config)
             self.enable_graph = True
 
-        self.config.vector_store.config.collection_name = "mem0_migrations"
-        if self.config.vector_store.provider in ["faiss", "qdrant"]:
-            provider_path = f"migrations_{self.config.vector_store.provider}"
-            self.config.vector_store.config.path = os.path.join(mem0_dir, provider_path)
-            os.makedirs(self.config.vector_store.config.path, exist_ok=True)
-
-        self._telemetry_vector_store = VectorStoreFactory.create(
-            self.config.vector_store.provider, self.config.vector_store.config
-        )
         capture_event("mem0.init", self)
 
     @classmethod

mem0/memory/setup.py

@@ -3,7 +3,6 @@
 import uuid
 
 # Set up the directory path
-VECTOR_ID = str(uuid.uuid4())
 home_dir = os.path.expanduser("~")
 mem0_dir = os.environ.get("MEM0_DIR") or os.path.join(home_dir, ".mem0")
 os.makedirs(mem0_dir, exist_ok=True)
@@ -30,29 +29,3 @@ def get_user_id():
             return user_id
     except Exception:
         return "anonymous_user"
-
-
-def get_or_create_user_id(vector_store):
-    """Store user_id in vector store and return it."""
-    user_id = get_user_id()
-
-    # Try to get existing user_id from vector store
-    try:
-        existing = vector_store.get(vector_id=VECTOR_ID)
-        if existing and hasattr(existing, "payload") and existing.payload and "user_id" in existing.payload:
-            return existing.payload["user_id"]
-    except:
-        pass
-
-    # If we get here, we need to insert the user_id
-    try:
-        dims = getattr(vector_store, "embedding_model_dims", 1)
-        vector_store.insert(
-            vectors=[[0.0] * dims],
-            payloads=[{"user_id": user_id, "type": "user_identity"}],
-            ids=[VECTOR_ID]
-        )
-    except:
-        pass
-
-    return user_id

mem0/memory/telemetry.py

@@ -6,7 +6,7 @@
 from posthog import Posthog
 
 import mem0
-from mem0.memory.setup import get_or_create_user_id
+from mem0.memory.setup import get_user_id, setup_config
 
 MEM0_TELEMETRY = os.environ.get("MEM0_TELEMETRY", "True")
 
@@ -21,11 +21,11 @@
 
 
 class AnonymousTelemetry:
-    def __init__(self, project_api_key, host, vector_store=None):
+    def __init__(self, project_api_key, host):
         self.posthog = Posthog(project_api_key=project_api_key, host=host)
-
-        self.user_id = get_or_create_user_id(vector_store)
-
+        # Call setup config to ensure that the user_id is generated
+        setup_config()
+        self.user_id = get_user_id()
         if not MEM0_TELEMETRY:
             self.posthog.disabled = True
 
@@ -50,12 +50,14 @@ def close(self):
         self.posthog.shutdown()
 
 
-def capture_event(event_name, memory_instance, additional_data=None):
-    global telemetry
+# Initialize AnonymousTelemetry
+telemetry = AnonymousTelemetry(
+    project_api_key="phc_hgJkUVJFYtmaJqrvf6CYN67TIQ8yhXAkWzUn9AMU4yX",
+    host="https://us.i.posthog.com",
+)
 
-    # For OSS, we use the telemetry vector store to store the user_id
-    telemetry = AnonymousTelemetry(project_api_key="phc_hgJkUVJFYtmaJqrvf6CYN67TIQ8yhXAkWzUn9AMU4yX", host="https://us.i.posthog.com", vector_store=memory_instance._telemetry_vector_store if hasattr(memory_instance, "_telemetry_vector_store") else None)
 
+def capture_event(event_name, memory_instance, additional_data=None):
     event_data = {
         "collection": memory_instance.collection_name,
         "vector_size": memory_instance.embedding_model.config.embedding_dims,

pyproject.toml

@@ -1,6 +1,6 @@
 [tool.poetry]
 name = "mem0ai"
-version = "0.1.89"
+version = "0.1.90"
 description = "Long-term memory for AI Agents"
 authors = ["Mem0 <[email protected]>"]
 exclude = [