sample_id stringlengths 21 196 | text stringlengths 105 936k | metadata dict | category stringclasses 6
values |
|---|---|---|---|
marimo-team/marimo:tests/_pyodide/test_pyodide_session.py | # Copyright 2026 Marimo. All rights reserved.
from __future__ import annotations
import asyncio
import json
from textwrap import dedent
from typing import TYPE_CHECKING
from unittest.mock import MagicMock, Mock
import msgspec
import pytest
from marimo._ast.app_config import _AppConfig
from marimo._config.config impo... | {
"repo_id": "marimo-team/marimo",
"file_path": "tests/_pyodide/test_pyodide_session.py",
"license": "Apache License 2.0",
"lines": 684,
"canary_id": -1,
"canary_value": "",
"pii_type": "",
"provider": "",
"regex_pattern": "",
"repetition": -1,
"template": ""
} | test |
marimo-team/marimo:tests/_pyodide/test_pyodide_streams.py | import asyncio
import json
from unittest.mock import Mock
import pytest
from marimo._pyodide.streams import (
PyodideStderr,
PyodideStdin,
PyodideStdout,
PyodideStream,
)
from marimo._types.ids import CellId_t
cell_id = CellId_t("test-cell-id")
@pytest.fixture
def pyodide_pipe() -> Mock:
return... | {
"repo_id": "marimo-team/marimo",
"file_path": "tests/_pyodide/test_pyodide_streams.py",
"license": "Apache License 2.0",
"lines": 155,
"canary_id": -1,
"canary_value": "",
"pii_type": "",
"provider": "",
"regex_pattern": "",
"repetition": -1,
"template": ""
} | test |
marimo-team/marimo:tests/_pyodide/test_restartable_task.py | import asyncio
import pytest
from marimo._pyodide.restartable_task import RestartableTask
async def test_restartable_task():
# Test basic start/stop
counter = 0
event = asyncio.Event()
async def increment_counter():
nonlocal counter
counter += 1
event.set() # Signal that we... | {
"repo_id": "marimo-team/marimo",
"file_path": "tests/_pyodide/test_restartable_task.py",
"license": "Apache License 2.0",
"lines": 204,
"canary_id": -1,
"canary_value": "",
"pii_type": "",
"provider": "",
"regex_pattern": "",
"repetition": -1,
"template": ""
} | test |
marimo-team/marimo:tests/_utils/test_inline_script_metadata.py | from __future__ import annotations
from typing import TYPE_CHECKING
import pytest
from marimo._utils.inline_script_metadata import (
PyProjectReader,
_pyproject_toml_to_requirements_txt,
has_marimo_in_script_metadata,
is_marimo_dependency,
script_metadata_hash_from_filename,
)
from marimo._utils.... | {
"repo_id": "marimo-team/marimo",
"file_path": "tests/_utils/test_inline_script_metadata.py",
"license": "Apache License 2.0",
"lines": 373,
"canary_id": -1,
"canary_value": "",
"pii_type": "",
"provider": "",
"regex_pattern": "",
"repetition": -1,
"template": ""
} | test |
marimo-team/marimo:marimo/_save/stores/rest.py | # Copyright 2026 Marimo. All rights reserved.
from __future__ import annotations
import urllib.error
import urllib.request
from typing import Optional
from marimo import _loggers
from marimo._save.stores.store import Store
from marimo._version import __version__
LOGGER = _loggers.marimo_logger()
class RestStore(St... | {
"repo_id": "marimo-team/marimo",
"file_path": "marimo/_save/stores/rest.py",
"license": "Apache License 2.0",
"lines": 87,
"canary_id": -1,
"canary_value": "",
"pii_type": "",
"provider": "",
"regex_pattern": "",
"repetition": -1,
"template": ""
} | function_complex |
marimo-team/marimo:tests/_output/formatters/test_ipython_update.py | from __future__ import annotations
from unittest.mock import MagicMock, patch
import pytest
from marimo._dependencies.dependencies import DependencyManager
from marimo._output.formatters.ipython_formatters import (
IPythonFormatter,
)
HAS_DEPS = DependencyManager.ipython.has()
@pytest.mark.skipif(not HAS_DEPS... | {
"repo_id": "marimo-team/marimo",
"file_path": "tests/_output/formatters/test_ipython_update.py",
"license": "Apache License 2.0",
"lines": 58,
"canary_id": -1,
"canary_value": "",
"pii_type": "",
"provider": "",
"regex_pattern": "",
"repetition": -1,
"template": ""
} | test |
marimo-team/marimo:marimo/_smoke_tests/issues/4746_altair_hstacks.py | import marimo
__generated_with = "0.15.5"
app = marimo.App(width="medium")
@app.cell
def _():
import altair as alt
import pandas as pd
import marimo as mo
from vega_datasets import data
source = data.cars()
plot_1 = mo.ui.altair_chart(
alt.Chart(source)
.mark_point()
... | {
"repo_id": "marimo-team/marimo",
"file_path": "marimo/_smoke_tests/issues/4746_altair_hstacks.py",
"license": "Apache License 2.0",
"lines": 42,
"canary_id": -1,
"canary_value": "",
"pii_type": "",
"provider": "",
"regex_pattern": "",
"repetition": -1,
"template": ""
} | function_simple |
mem0ai/mem0:examples/misc/strands_agent_aws_elasticache_neptune.py |
"""
GitHub Repository Research Agent with Persistent Memory
This example demonstrates how to build an AI agent with persistent memory using:
- Mem0 for memory orchestration and lifecycle management
- Amazon ElastiCache for Valkey for high-performance vector similarity search
- Amazon Neptune Analytics for graph-based... | {
"repo_id": "mem0ai/mem0",
"file_path": "examples/misc/strands_agent_aws_elasticache_neptune.py",
"license": "Apache License 2.0",
"lines": 314,
"canary_id": -1,
"canary_value": "",
"pii_type": "",
"provider": "",
"regex_pattern": "",
"repetition": -1,
"template": ""
} | function_complex |
mem0ai/mem0:mem0/configs/vector_stores/cassandra.py | from typing import Any, Dict, List, Optional
from pydantic import BaseModel, Field, model_validator
class CassandraConfig(BaseModel):
"""Configuration for Apache Cassandra vector database."""
contact_points: List[str] = Field(
...,
description="List of contact point addresses (e.g., ['127.0.... | {
"repo_id": "mem0ai/mem0",
"file_path": "mem0/configs/vector_stores/cassandra.py",
"license": "Apache License 2.0",
"lines": 62,
"canary_id": -1,
"canary_value": "",
"pii_type": "",
"provider": "",
"regex_pattern": "",
"repetition": -1,
"template": ""
} | function_simple |
mem0ai/mem0:mem0/vector_stores/cassandra.py | import json
import logging
import uuid
from typing import Any, Dict, List, Optional
import numpy as np
from pydantic import BaseModel
try:
from cassandra.cluster import Cluster
from cassandra.auth import PlainTextAuthProvider
except ImportError:
raise ImportError(
"Apache Cassandra vector store re... | {
"repo_id": "mem0ai/mem0",
"file_path": "mem0/vector_stores/cassandra.py",
"license": "Apache License 2.0",
"lines": 432,
"canary_id": -1,
"canary_value": "",
"pii_type": "",
"provider": "",
"regex_pattern": "",
"repetition": -1,
"template": ""
} | function_complex |
mem0ai/mem0:tests/vector_stores/test_cassandra.py | import json
import pytest
from unittest.mock import Mock, patch
from mem0.vector_stores.cassandra import CassandraDB, OutputData
@pytest.fixture
def mock_session():
"""Create a mock Cassandra session."""
session = Mock()
session.execute = Mock(return_value=Mock())
session.prepare = Mock(return_value=... | {
"repo_id": "mem0ai/mem0",
"file_path": "tests/vector_stores/test_cassandra.py",
"license": "Apache License 2.0",
"lines": 228,
"canary_id": -1,
"canary_value": "",
"pii_type": "",
"provider": "",
"regex_pattern": "",
"repetition": -1,
"template": ""
} | test |
mem0ai/mem0:mem0/embeddings/fastembed.py | from typing import Optional, Literal
from mem0.embeddings.base import EmbeddingBase
from mem0.configs.embeddings.base import BaseEmbedderConfig
try:
from fastembed import TextEmbedding
except ImportError:
raise ImportError("FastEmbed is not installed. Please install it using `pip install fastembed`")
class ... | {
"repo_id": "mem0ai/mem0",
"file_path": "mem0/embeddings/fastembed.py",
"license": "Apache License 2.0",
"lines": 24,
"canary_id": -1,
"canary_value": "",
"pii_type": "",
"provider": "",
"regex_pattern": "",
"repetition": -1,
"template": ""
} | function_simple |
mem0ai/mem0:tests/embeddings/test_fastembed_embeddings.py | from unittest.mock import Mock, patch
import pytest
import numpy as np
from mem0.configs.embeddings.base import BaseEmbedderConfig
try:
from mem0.embeddings.fastembed import FastEmbedEmbedding
except ImportError:
pytest.skip("fastembed not installed", allow_module_level=True)
@pytest.fixture
def mock_fast... | {
"repo_id": "mem0ai/mem0",
"file_path": "tests/embeddings/test_fastembed_embeddings.py",
"license": "Apache License 2.0",
"lines": 32,
"canary_id": -1,
"canary_value": "",
"pii_type": "",
"provider": "",
"regex_pattern": "",
"repetition": -1,
"template": ""
} | test |
mem0ai/mem0:mem0/configs/rerankers/base.py | from typing import Optional
from pydantic import BaseModel, Field
class BaseRerankerConfig(BaseModel):
"""
Base configuration for rerankers with only common parameters.
Provider-specific configurations should be handled by separate config classes.
This class contains only the parameters that are comm... | {
"repo_id": "mem0ai/mem0",
"file_path": "mem0/configs/rerankers/base.py",
"license": "Apache License 2.0",
"lines": 13,
"canary_id": -1,
"canary_value": "",
"pii_type": "",
"provider": "",
"regex_pattern": "",
"repetition": -1,
"template": ""
} | documentation |
mem0ai/mem0:mem0/configs/rerankers/cohere.py | from typing import Optional
from pydantic import Field
from mem0.configs.rerankers.base import BaseRerankerConfig
class CohereRerankerConfig(BaseRerankerConfig):
"""
Configuration class for Cohere reranker-specific parameters.
Inherits from BaseRerankerConfig and adds Cohere-specific settings.
"""
... | {
"repo_id": "mem0ai/mem0",
"file_path": "mem0/configs/rerankers/cohere.py",
"license": "Apache License 2.0",
"lines": 11,
"canary_id": -1,
"canary_value": "",
"pii_type": "",
"provider": "",
"regex_pattern": "",
"repetition": -1,
"template": ""
} | function_simple |
mem0ai/mem0:mem0/configs/rerankers/config.py | from typing import Optional
from pydantic import BaseModel, Field
class RerankerConfig(BaseModel):
"""Configuration for rerankers."""
provider: str = Field(description="Reranker provider (e.g., 'cohere', 'sentence_transformer')", default="cohere")
config: Optional[dict] = Field(description="Provider-spe... | {
"repo_id": "mem0ai/mem0",
"file_path": "mem0/configs/rerankers/config.py",
"license": "Apache License 2.0",
"lines": 7,
"canary_id": -1,
"canary_value": "",
"pii_type": "",
"provider": "",
"regex_pattern": "",
"repetition": -1,
"template": ""
} | function_simple |
mem0ai/mem0:mem0/configs/rerankers/huggingface.py | from typing import Optional
from pydantic import Field
from mem0.configs.rerankers.base import BaseRerankerConfig
class HuggingFaceRerankerConfig(BaseRerankerConfig):
"""
Configuration class for HuggingFace reranker-specific parameters.
Inherits from BaseRerankerConfig and adds HuggingFace-specific setti... | {
"repo_id": "mem0ai/mem0",
"file_path": "mem0/configs/rerankers/huggingface.py",
"license": "Apache License 2.0",
"lines": 13,
"canary_id": -1,
"canary_value": "",
"pii_type": "",
"provider": "",
"regex_pattern": "",
"repetition": -1,
"template": ""
} | function_simple |
mem0ai/mem0:mem0/configs/rerankers/llm.py | from typing import Optional
from pydantic import Field
from mem0.configs.rerankers.base import BaseRerankerConfig
class LLMRerankerConfig(BaseRerankerConfig):
"""
Configuration for LLM-based reranker.
Attributes:
model (str): LLM model to use for reranking. Defaults to "gpt-4o-mini".
... | {
"repo_id": "mem0ai/mem0",
"file_path": "mem0/configs/rerankers/llm.py",
"license": "Apache License 2.0",
"lines": 43,
"canary_id": -1,
"canary_value": "",
"pii_type": "",
"provider": "",
"regex_pattern": "",
"repetition": -1,
"template": ""
} | function_simple |
mem0ai/mem0:mem0/configs/rerankers/sentence_transformer.py | from typing import Optional
from pydantic import Field
from mem0.configs.rerankers.base import BaseRerankerConfig
class SentenceTransformerRerankerConfig(BaseRerankerConfig):
"""
Configuration class for Sentence Transformer reranker-specific parameters.
Inherits from BaseRerankerConfig and adds Sentence ... | {
"repo_id": "mem0ai/mem0",
"file_path": "mem0/configs/rerankers/sentence_transformer.py",
"license": "Apache License 2.0",
"lines": 12,
"canary_id": -1,
"canary_value": "",
"pii_type": "",
"provider": "",
"regex_pattern": "",
"repetition": -1,
"template": ""
} | function_simple |
mem0ai/mem0:mem0/configs/rerankers/zero_entropy.py | from typing import Optional
from pydantic import Field
from mem0.configs.rerankers.base import BaseRerankerConfig
class ZeroEntropyRerankerConfig(BaseRerankerConfig):
"""
Configuration for Zero Entropy reranker.
Attributes:
model (str): Model to use for reranking. Defaults to "zerank-1".
... | {
"repo_id": "mem0ai/mem0",
"file_path": "mem0/configs/rerankers/zero_entropy.py",
"license": "Apache License 2.0",
"lines": 23,
"canary_id": -1,
"canary_value": "",
"pii_type": "",
"provider": "",
"regex_pattern": "",
"repetition": -1,
"template": ""
} | function_simple |
mem0ai/mem0:mem0/reranker/base.py | from abc import ABC, abstractmethod
from typing import List, Dict, Any
class BaseReranker(ABC):
"""Abstract base class for all rerankers."""
@abstractmethod
def rerank(self, query: str, documents: List[Dict[str, Any]], top_k: int = None) -> List[Dict[str, Any]]:
"""
Rerank documents ba... | {
"repo_id": "mem0ai/mem0",
"file_path": "mem0/reranker/base.py",
"license": "Apache License 2.0",
"lines": 16,
"canary_id": -1,
"canary_value": "",
"pii_type": "",
"provider": "",
"regex_pattern": "",
"repetition": -1,
"template": ""
} | documentation |
mem0ai/mem0:mem0/reranker/cohere_reranker.py | import os
from typing import List, Dict, Any
from mem0.reranker.base import BaseReranker
try:
import cohere
COHERE_AVAILABLE = True
except ImportError:
COHERE_AVAILABLE = False
class CohereReranker(BaseReranker):
"""Cohere-based reranker implementation."""
def __init__(self, config):
... | {
"repo_id": "mem0ai/mem0",
"file_path": "mem0/reranker/cohere_reranker.py",
"license": "Apache License 2.0",
"lines": 69,
"canary_id": -1,
"canary_value": "",
"pii_type": "",
"provider": "",
"regex_pattern": "",
"repetition": -1,
"template": ""
} | function_complex |
mem0ai/mem0:mem0/reranker/huggingface_reranker.py | from typing import List, Dict, Any, Union
import numpy as np
from mem0.reranker.base import BaseReranker
from mem0.configs.rerankers.base import BaseRerankerConfig
from mem0.configs.rerankers.huggingface import HuggingFaceRerankerConfig
try:
from transformers import AutoTokenizer, AutoModelForSequenceClassificati... | {
"repo_id": "mem0ai/mem0",
"file_path": "mem0/reranker/huggingface_reranker.py",
"license": "Apache License 2.0",
"lines": 120,
"canary_id": -1,
"canary_value": "",
"pii_type": "",
"provider": "",
"regex_pattern": "",
"repetition": -1,
"template": ""
} | function_complex |
mem0ai/mem0:mem0/reranker/llm_reranker.py | import re
from typing import List, Dict, Any, Union
from mem0.reranker.base import BaseReranker
from mem0.utils.factory import LlmFactory
from mem0.configs.rerankers.base import BaseRerankerConfig
from mem0.configs.rerankers.llm import LLMRerankerConfig
class LLMReranker(BaseReranker):
"""LLM-based reranker impl... | {
"repo_id": "mem0ai/mem0",
"file_path": "mem0/reranker/llm_reranker.py",
"license": "Apache License 2.0",
"lines": 112,
"canary_id": -1,
"canary_value": "",
"pii_type": "",
"provider": "",
"regex_pattern": "",
"repetition": -1,
"template": ""
} | function_complex |
mem0ai/mem0:mem0/reranker/sentence_transformer_reranker.py | from typing import List, Dict, Any, Union
import numpy as np
from mem0.reranker.base import BaseReranker
from mem0.configs.rerankers.base import BaseRerankerConfig
from mem0.configs.rerankers.sentence_transformer import SentenceTransformerRerankerConfig
try:
from sentence_transformers import SentenceTransformer
... | {
"repo_id": "mem0ai/mem0",
"file_path": "mem0/reranker/sentence_transformer_reranker.py",
"license": "Apache License 2.0",
"lines": 87,
"canary_id": -1,
"canary_value": "",
"pii_type": "",
"provider": "",
"regex_pattern": "",
"repetition": -1,
"template": ""
} | function_complex |
mem0ai/mem0:mem0/reranker/zero_entropy_reranker.py | import os
from typing import List, Dict, Any
from mem0.reranker.base import BaseReranker
try:
from zeroentropy import ZeroEntropy
ZERO_ENTROPY_AVAILABLE = True
except ImportError:
ZERO_ENTROPY_AVAILABLE = False
class ZeroEntropyReranker(BaseReranker):
"""Zero Entropy-based reranker implementation.""... | {
"repo_id": "mem0ai/mem0",
"file_path": "mem0/reranker/zero_entropy_reranker.py",
"license": "Apache License 2.0",
"lines": 77,
"canary_id": -1,
"canary_value": "",
"pii_type": "",
"provider": "",
"regex_pattern": "",
"repetition": -1,
"template": ""
} | function_complex |
mem0ai/mem0:mem0/utils/gcp_auth.py | import os
import json
from typing import Optional, Dict, Any
try:
from google.oauth2 import service_account
from google.auth import default
import google.auth.credentials
except ImportError:
raise ImportError("google-auth is required for GCP authentication. Install with: pip install google-auth")
cla... | {
"repo_id": "mem0ai/mem0",
"file_path": "mem0/utils/gcp_auth.py",
"license": "Apache License 2.0",
"lines": 140,
"canary_id": -1,
"canary_value": "",
"pii_type": "",
"provider": "",
"regex_pattern": "",
"repetition": -1,
"template": ""
} | function_complex |
mem0ai/mem0:tests/vector_stores/test_milvus.py | """
Unit tests for Milvus vector store implementation.
These tests verify:
1. Correct type handling for vector dimensions
2. Batch insert functionality
3. Filter creation for metadata queries
4. Update/upsert operations
"""
import pytest
from unittest.mock import MagicMock, patch
from mem0.vector_stores.milvus import... | {
"repo_id": "mem0ai/mem0",
"file_path": "tests/vector_stores/test_milvus.py",
"license": "Apache License 2.0",
"lines": 202,
"canary_id": -1,
"canary_value": "",
"pii_type": "",
"provider": "",
"regex_pattern": "",
"repetition": -1,
"template": ""
} | test |
mem0ai/mem0:mem0/configs/vector_stores/azure_mysql.py | from typing import Any, Dict, Optional
from pydantic import BaseModel, Field, model_validator
class AzureMySQLConfig(BaseModel):
"""Configuration for Azure MySQL vector database."""
host: str = Field(..., description="MySQL server host (e.g., myserver.mysql.database.azure.com)")
port: int = Field(3306, ... | {
"repo_id": "mem0ai/mem0",
"file_path": "mem0/configs/vector_stores/azure_mysql.py",
"license": "Apache License 2.0",
"lines": 68,
"canary_id": -1,
"canary_value": "",
"pii_type": "",
"provider": "",
"regex_pattern": "",
"repetition": -1,
"template": ""
} | function_complex |
mem0ai/mem0:mem0/vector_stores/azure_mysql.py | import json
import logging
from contextlib import contextmanager
from typing import Any, Dict, List, Optional
from pydantic import BaseModel
try:
import pymysql
from pymysql.cursors import DictCursor
from dbutils.pooled_db import PooledDB
except ImportError:
raise ImportError(
"Azure MySQL vec... | {
"repo_id": "mem0ai/mem0",
"file_path": "mem0/vector_stores/azure_mysql.py",
"license": "Apache License 2.0",
"lines": 404,
"canary_id": -1,
"canary_value": "",
"pii_type": "",
"provider": "",
"regex_pattern": "",
"repetition": -1,
"template": ""
} | function_complex |
mem0ai/mem0:tests/vector_stores/test_azure_mysql.py | import json
import pytest
from unittest.mock import Mock, patch
from mem0.vector_stores.azure_mysql import AzureMySQL, OutputData
@pytest.fixture
def mock_connection_pool():
"""Create a mock connection pool."""
pool = Mock()
conn = Mock()
cursor = Mock()
# Setup cursor mock
cursor.fetchall =... | {
"repo_id": "mem0ai/mem0",
"file_path": "tests/vector_stores/test_azure_mysql.py",
"license": "Apache License 2.0",
"lines": 208,
"canary_id": -1,
"canary_value": "",
"pii_type": "",
"provider": "",
"regex_pattern": "",
"repetition": -1,
"template": ""
} | test |
mem0ai/mem0:tests/memory/test_storage.py | import os
import sqlite3
import tempfile
import uuid
from datetime import datetime
import pytest
from mem0.memory.storage import SQLiteManager
class TestSQLiteManager:
"""Comprehensive test cases for SQLiteManager class."""
@pytest.fixture
def temp_db_path(self):
"""Create temporary database fi... | {
"repo_id": "mem0ai/mem0",
"file_path": "tests/memory/test_storage.py",
"license": "Apache License 2.0",
"lines": 242,
"canary_id": -1,
"canary_value": "",
"pii_type": "",
"provider": "",
"regex_pattern": "",
"repetition": -1,
"template": ""
} | test |
mem0ai/mem0:mem0/graphs/neptune/neptunedb.py | import logging
import uuid
from datetime import datetime
import pytz
from .base import NeptuneBase
try:
from langchain_aws import NeptuneGraph
except ImportError:
raise ImportError("langchain_aws is not installed. Please install it using 'make install_all'.")
logger = logging.getLogger(__name__)
class Memor... | {
"repo_id": "mem0ai/mem0",
"file_path": "mem0/graphs/neptune/neptunedb.py",
"license": "Apache License 2.0",
"lines": 453,
"canary_id": -1,
"canary_value": "",
"pii_type": "",
"provider": "",
"regex_pattern": "",
"repetition": -1,
"template": ""
} | documentation |
mem0ai/mem0:mem0/graphs/neptune/neptunegraph.py | import logging
from .base import NeptuneBase
try:
from langchain_aws import NeptuneAnalyticsGraph
from botocore.config import Config
except ImportError:
raise ImportError("langchain_aws is not installed. Please install it using 'make install_all'.")
logger = logging.getLogger(__name__)
class MemoryGrap... | {
"repo_id": "mem0ai/mem0",
"file_path": "mem0/graphs/neptune/neptunegraph.py",
"license": "Apache License 2.0",
"lines": 422,
"canary_id": -1,
"canary_value": "",
"pii_type": "",
"provider": "",
"regex_pattern": "",
"repetition": -1,
"template": ""
} | documentation |
mem0ai/mem0:tests/memory/test_neptune_analytics_memory.py | import unittest
from unittest.mock import MagicMock, patch
import pytest
from mem0.graphs.neptune.neptunegraph import MemoryGraph
from mem0.graphs.neptune.base import NeptuneBase
class TestNeptuneMemory(unittest.TestCase):
"""Test suite for the Neptune Memory implementation."""
def setUp(self):
"""Se... | {
"repo_id": "mem0ai/mem0",
"file_path": "tests/memory/test_neptune_analytics_memory.py",
"license": "Apache License 2.0",
"lines": 261,
"canary_id": -1,
"canary_value": "",
"pii_type": "",
"provider": "",
"regex_pattern": "",
"repetition": -1,
"template": ""
} | test |
mem0ai/mem0:mem0/exceptions.py | """Structured exception classes for Mem0 with error codes, suggestions, and debug information.
This module provides a comprehensive set of exception classes that replace the generic
APIError with specific, actionable exceptions. Each exception includes error codes,
user-friendly suggestions, and debug information to e... | {
"repo_id": "mem0ai/mem0",
"file_path": "mem0/exceptions.py",
"license": "Apache License 2.0",
"lines": 408,
"canary_id": -1,
"canary_value": "",
"pii_type": "",
"provider": "",
"regex_pattern": "",
"repetition": -1,
"template": ""
} | documentation |
mem0ai/mem0:mem0/configs/vector_stores/neptune.py | """
Configuration for Amazon Neptune Analytics vector store.
This module provides configuration settings for integrating with Amazon Neptune Analytics
as a vector store backend for Mem0's memory layer.
"""
from pydantic import BaseModel, Field
class NeptuneAnalyticsConfig(BaseModel):
"""
Configuration class... | {
"repo_id": "mem0ai/mem0",
"file_path": "mem0/configs/vector_stores/neptune.py",
"license": "Apache License 2.0",
"lines": 20,
"canary_id": -1,
"canary_value": "",
"pii_type": "",
"provider": "",
"regex_pattern": "",
"repetition": -1,
"template": ""
} | documentation |
mem0ai/mem0:mem0/vector_stores/neptune_analytics.py | import logging
import time
import uuid
from typing import Dict, List, Optional
from pydantic import BaseModel
try:
from langchain_aws import NeptuneAnalyticsGraph
except ImportError:
raise ImportError("langchain_aws is not installed. Please install it using pip install langchain_aws")
from mem0.vector_stores... | {
"repo_id": "mem0ai/mem0",
"file_path": "mem0/vector_stores/neptune_analytics.py",
"license": "Apache License 2.0",
"lines": 372,
"canary_id": -1,
"canary_value": "",
"pii_type": "",
"provider": "",
"regex_pattern": "",
"repetition": -1,
"template": ""
} | documentation |
mem0ai/mem0:tests/vector_stores/test_neptune_analytics.py | import logging
import os
import sys
import pytest
from dotenv import load_dotenv
from mem0.utils.factory import VectorStoreFactory
load_dotenv()
# Configure logging
logging.getLogger("mem0.vector.neptune.main").setLevel(logging.INFO)
logging.getLogger("mem0.vector.neptune.base").setLevel(logging.INFO)
logger = logg... | {
"repo_id": "mem0ai/mem0",
"file_path": "tests/vector_stores/test_neptune_analytics.py",
"license": "Apache License 2.0",
"lines": 145,
"canary_id": -1,
"canary_value": "",
"pii_type": "",
"provider": "",
"regex_pattern": "",
"repetition": -1,
"template": ""
} | test |
mem0ai/mem0:mem0/configs/vector_stores/valkey.py | from pydantic import BaseModel
class ValkeyConfig(BaseModel):
"""Configuration for Valkey vector store."""
valkey_url: str
collection_name: str
embedding_model_dims: int
timezone: str = "UTC"
index_type: str = "hnsw" # Default to HNSW, can be 'hnsw' or 'flat'
# HNSW specific parameters w... | {
"repo_id": "mem0ai/mem0",
"file_path": "mem0/configs/vector_stores/valkey.py",
"license": "Apache License 2.0",
"lines": 12,
"canary_id": -1,
"canary_value": "",
"pii_type": "",
"provider": "",
"regex_pattern": "",
"repetition": -1,
"template": ""
} | function_simple |
mem0ai/mem0:mem0/vector_stores/valkey.py | import json
import logging
from datetime import datetime
from typing import Dict
import numpy as np
import pytz
import valkey
from pydantic import BaseModel
from valkey.exceptions import ResponseError
from mem0.memory.utils import extract_json
from mem0.vector_stores.base import VectorStoreBase
logger = logging.getL... | {
"repo_id": "mem0ai/mem0",
"file_path": "mem0/vector_stores/valkey.py",
"license": "Apache License 2.0",
"lines": 695,
"canary_id": -1,
"canary_value": "",
"pii_type": "",
"provider": "",
"regex_pattern": "",
"repetition": -1,
"template": ""
} | function_complex |
mem0ai/mem0:tests/vector_stores/test_valkey.py | import json
from datetime import datetime
from unittest.mock import MagicMock, patch
import numpy as np
import pytest
import pytz
from valkey.exceptions import ResponseError
from mem0.vector_stores.valkey import ValkeyDB
@pytest.fixture
def mock_valkey_client():
"""Create a mock Valkey client."""
with patch... | {
"repo_id": "mem0ai/mem0",
"file_path": "tests/vector_stores/test_valkey.py",
"license": "Apache License 2.0",
"lines": 665,
"canary_id": -1,
"canary_value": "",
"pii_type": "",
"provider": "",
"regex_pattern": "",
"repetition": -1,
"template": ""
} | test |
mem0ai/mem0:mem0/configs/vector_stores/s3_vectors.py | from typing import Any, Dict, Optional
from pydantic import BaseModel, ConfigDict, Field, model_validator
class S3VectorsConfig(BaseModel):
vector_bucket_name: str = Field(description="Name of the S3 Vector bucket")
collection_name: str = Field("mem0", description="Name of the vector index")
embedding_mo... | {
"repo_id": "mem0ai/mem0",
"file_path": "mem0/configs/vector_stores/s3_vectors.py",
"license": "Apache License 2.0",
"lines": 23,
"canary_id": -1,
"canary_value": "",
"pii_type": "",
"provider": "",
"regex_pattern": "",
"repetition": -1,
"template": ""
} | function_simple |
mem0ai/mem0:mem0/vector_stores/s3_vectors.py | import json
import logging
from typing import Dict, List, Optional
from pydantic import BaseModel
from mem0.vector_stores.base import VectorStoreBase
try:
import boto3
from botocore.exceptions import ClientError
except ImportError:
raise ImportError("The 'boto3' library is required. Please install it usi... | {
"repo_id": "mem0ai/mem0",
"file_path": "mem0/vector_stores/s3_vectors.py",
"license": "Apache License 2.0",
"lines": 151,
"canary_id": -1,
"canary_value": "",
"pii_type": "",
"provider": "",
"regex_pattern": "",
"repetition": -1,
"template": ""
} | function_complex |
mem0ai/mem0:tests/vector_stores/test_s3_vectors.py | from mem0.configs.vector_stores.s3_vectors import S3VectorsConfig
import pytest
from botocore.exceptions import ClientError
from mem0.memory.main import Memory
from mem0.vector_stores.s3_vectors import S3Vectors
BUCKET_NAME = "test-bucket"
INDEX_NAME = "test-index"
EMBEDDING_DIMS = 1536
REGION = "us-east-1"
@pytest... | {
"repo_id": "mem0ai/mem0",
"file_path": "tests/vector_stores/test_s3_vectors.py",
"license": "Apache License 2.0",
"lines": 182,
"canary_id": -1,
"canary_value": "",
"pii_type": "",
"provider": "",
"regex_pattern": "",
"repetition": -1,
"template": ""
} | test |
mem0ai/mem0:openmemory/api/app/routers/backup.py | from datetime import UTC, datetime
import io
import json
import gzip
import zipfile
from typing import Optional, List, Dict, Any
from uuid import UUID
from fastapi import APIRouter, Depends, HTTPException, UploadFile, File, Query, Form
from fastapi.responses import StreamingResponse
from pydantic import BaseModel
f... | {
"repo_id": "mem0ai/mem0",
"file_path": "openmemory/api/app/routers/backup.py",
"license": "Apache License 2.0",
"lines": 409,
"canary_id": -1,
"canary_value": "",
"pii_type": "",
"provider": "",
"regex_pattern": "",
"repetition": -1,
"template": ""
} | function_complex |
mem0ai/mem0:tests/llms/test_azure_openai_structured.py | from unittest import mock
from mem0.llms.azure_openai_structured import SCOPE, AzureOpenAIStructuredLLM
class DummyAzureKwargs:
def __init__(
self,
api_key=None,
azure_deployment="test-deployment",
azure_endpoint="https://test-endpoint.openai.azure.com",
api_version="2024-... | {
"repo_id": "mem0ai/mem0",
"file_path": "tests/llms/test_azure_openai_structured.py",
"license": "Apache License 2.0",
"lines": 87,
"canary_id": -1,
"canary_value": "",
"pii_type": "",
"provider": "",
"regex_pattern": "",
"repetition": -1,
"template": ""
} | test |
mem0ai/mem0:mem0/configs/llms/aws_bedrock.py | import os
from typing import Any, Dict, List, Optional
from mem0.configs.llms.base import BaseLlmConfig
class AWSBedrockConfig(BaseLlmConfig):
"""
Configuration class for AWS Bedrock LLM integration.
Supports all available Bedrock models with automatic provider detection.
"""
def __init__(
... | {
"repo_id": "mem0ai/mem0",
"file_path": "mem0/configs/llms/aws_bedrock.py",
"license": "Apache License 2.0",
"lines": 162,
"canary_id": -1,
"canary_value": "",
"pii_type": "",
"provider": "",
"regex_pattern": "",
"repetition": -1,
"template": ""
} | function_complex |
mem0ai/mem0:mem0/configs/vector_stores/databricks.py | from typing import Any, Dict, Optional
from pydantic import BaseModel, ConfigDict, Field, model_validator
from databricks.sdk.service.vectorsearch import EndpointType, VectorIndexType, PipelineType
class DatabricksConfig(BaseModel):
"""Configuration for Databricks Vector Search vector store."""
workspace_u... | {
"repo_id": "mem0ai/mem0",
"file_path": "mem0/configs/vector_stores/databricks.py",
"license": "Apache License 2.0",
"lines": 51,
"canary_id": -1,
"canary_value": "",
"pii_type": "",
"provider": "",
"regex_pattern": "",
"repetition": -1,
"template": ""
} | function_simple |
mem0ai/mem0:mem0/vector_stores/databricks.py | import json
import logging
import uuid
from typing import Optional, List
from datetime import datetime, date
from databricks.sdk.service.catalog import ColumnInfo, ColumnTypeName, TableType, DataSourceFormat
from databricks.sdk.service.catalog import TableConstraint, PrimaryKeyConstraint
from databricks.sdk import Work... | {
"repo_id": "mem0ai/mem0",
"file_path": "mem0/vector_stores/databricks.py",
"license": "Apache License 2.0",
"lines": 683,
"canary_id": -1,
"canary_value": "",
"pii_type": "",
"provider": "",
"regex_pattern": "",
"repetition": -1,
"template": ""
} | function_complex |
mem0ai/mem0:tests/vector_stores/test_databricks.py | from types import SimpleNamespace
from unittest.mock import MagicMock, patch
from databricks.sdk.service.vectorsearch import VectorIndexType, QueryVectorIndexResponse, ResultManifest, ResultData, ColumnInfo
from mem0.vector_stores.databricks import Databricks
import pytest
# ---------------------- Fixtures ----------... | {
"repo_id": "mem0ai/mem0",
"file_path": "tests/vector_stores/test_databricks.py",
"license": "Apache License 2.0",
"lines": 281,
"canary_id": -1,
"canary_value": "",
"pii_type": "",
"provider": "",
"regex_pattern": "",
"repetition": -1,
"template": ""
} | test |
mem0ai/mem0:mem0/memory/kuzu_memory.py | import logging
from mem0.memory.utils import format_entities
try:
import kuzu
except ImportError:
raise ImportError("kuzu is not installed. Please install it using pip install kuzu")
try:
from rank_bm25 import BM25Okapi
except ImportError:
raise ImportError("rank_bm25 is not installed. Please install... | {
"repo_id": "mem0ai/mem0",
"file_path": "mem0/memory/kuzu_memory.py",
"license": "Apache License 2.0",
"lines": 621,
"canary_id": -1,
"canary_value": "",
"pii_type": "",
"provider": "",
"regex_pattern": "",
"repetition": -1,
"template": ""
} | function_complex |
mem0ai/mem0:tests/memory/test_kuzu.py | import numpy as np
import pytest
from unittest.mock import Mock, patch
from mem0.memory.kuzu_memory import MemoryGraph
class TestKuzu:
"""Test that Kuzu memory works correctly"""
# Create distinct embeddings that won't match with threshold=0.7
# Each embedding is mostly zeros with ones in different posit... | {
"repo_id": "mem0ai/mem0",
"file_path": "tests/memory/test_kuzu.py",
"license": "Apache License 2.0",
"lines": 173,
"canary_id": -1,
"canary_value": "",
"pii_type": "",
"provider": "",
"regex_pattern": "",
"repetition": -1,
"template": ""
} | test |
mem0ai/mem0:tests/memory/test_neo4j_cypher_syntax.py | import os
from unittest.mock import Mock, patch
class TestNeo4jCypherSyntaxFix:
"""Test that Neo4j Cypher syntax fixes work correctly"""
def test_get_all_generates_valid_cypher_with_agent_id(self):
"""Test that get_all method generates valid Cypher with agent_id"""
# Mock the langchain_ne... | {
"repo_id": "mem0ai/mem0",
"file_path": "tests/memory/test_neo4j_cypher_syntax.py",
"license": "Apache License 2.0",
"lines": 223,
"canary_id": -1,
"canary_value": "",
"pii_type": "",
"provider": "",
"regex_pattern": "",
"repetition": -1,
"template": ""
} | test |
mem0ai/mem0:mem0/configs/llms/anthropic.py | from typing import Optional
from mem0.configs.llms.base import BaseLlmConfig
class AnthropicConfig(BaseLlmConfig):
"""
Configuration class for Anthropic-specific parameters.
Inherits from BaseLlmConfig and adds Anthropic-specific settings.
"""
def __init__(
self,
# Base parameter... | {
"repo_id": "mem0ai/mem0",
"file_path": "mem0/configs/llms/anthropic.py",
"license": "Apache License 2.0",
"lines": 50,
"canary_id": -1,
"canary_value": "",
"pii_type": "",
"provider": "",
"regex_pattern": "",
"repetition": -1,
"template": ""
} | function_simple |
mem0ai/mem0:mem0/configs/llms/azure.py | from typing import Any, Dict, Optional
from mem0.configs.base import AzureConfig
from mem0.configs.llms.base import BaseLlmConfig
class AzureOpenAIConfig(BaseLlmConfig):
"""
Configuration class for Azure OpenAI-specific parameters.
Inherits from BaseLlmConfig and adds Azure OpenAI-specific settings.
... | {
"repo_id": "mem0ai/mem0",
"file_path": "mem0/configs/llms/azure.py",
"license": "Apache License 2.0",
"lines": 51,
"canary_id": -1,
"canary_value": "",
"pii_type": "",
"provider": "",
"regex_pattern": "",
"repetition": -1,
"template": ""
} | function_simple |
mem0ai/mem0:mem0/configs/llms/deepseek.py | from typing import Optional
from mem0.configs.llms.base import BaseLlmConfig
class DeepSeekConfig(BaseLlmConfig):
"""
Configuration class for DeepSeek-specific parameters.
Inherits from BaseLlmConfig and adds DeepSeek-specific settings.
"""
def __init__(
self,
# Base parameters
... | {
"repo_id": "mem0ai/mem0",
"file_path": "mem0/configs/llms/deepseek.py",
"license": "Apache License 2.0",
"lines": 50,
"canary_id": -1,
"canary_value": "",
"pii_type": "",
"provider": "",
"regex_pattern": "",
"repetition": -1,
"template": ""
} | function_simple |
mem0ai/mem0:mem0/configs/llms/lmstudio.py | from typing import Any, Dict, Optional
from mem0.configs.llms.base import BaseLlmConfig
class LMStudioConfig(BaseLlmConfig):
"""
Configuration class for LM Studio-specific parameters.
Inherits from BaseLlmConfig and adds LM Studio-specific settings.
"""
def __init__(
self,
# Base... | {
"repo_id": "mem0ai/mem0",
"file_path": "mem0/configs/llms/lmstudio.py",
"license": "Apache License 2.0",
"lines": 53,
"canary_id": -1,
"canary_value": "",
"pii_type": "",
"provider": "",
"regex_pattern": "",
"repetition": -1,
"template": ""
} | function_simple |
mem0ai/mem0:mem0/configs/llms/ollama.py | from typing import Optional
from mem0.configs.llms.base import BaseLlmConfig
class OllamaConfig(BaseLlmConfig):
"""
Configuration class for Ollama-specific parameters.
Inherits from BaseLlmConfig and adds Ollama-specific settings.
"""
def __init__(
self,
# Base parameters
... | {
"repo_id": "mem0ai/mem0",
"file_path": "mem0/configs/llms/ollama.py",
"license": "Apache License 2.0",
"lines": 50,
"canary_id": -1,
"canary_value": "",
"pii_type": "",
"provider": "",
"regex_pattern": "",
"repetition": -1,
"template": ""
} | function_simple |
mem0ai/mem0:mem0/configs/llms/openai.py | from typing import Any, Callable, List, Optional
from mem0.configs.llms.base import BaseLlmConfig
class OpenAIConfig(BaseLlmConfig):
"""
Configuration class for OpenAI and OpenRouter-specific parameters.
Inherits from BaseLlmConfig and adds OpenAI-specific settings.
"""
def __init__(
sel... | {
"repo_id": "mem0ai/mem0",
"file_path": "mem0/configs/llms/openai.py",
"license": "Apache License 2.0",
"lines": 72,
"canary_id": -1,
"canary_value": "",
"pii_type": "",
"provider": "",
"regex_pattern": "",
"repetition": -1,
"template": ""
} | function_simple |
mem0ai/mem0:mem0/configs/llms/vllm.py | from typing import Optional
from mem0.configs.llms.base import BaseLlmConfig
class VllmConfig(BaseLlmConfig):
"""
Configuration class for vLLM-specific parameters.
Inherits from BaseLlmConfig and adds vLLM-specific settings.
"""
def __init__(
self,
# Base parameters
model... | {
"repo_id": "mem0ai/mem0",
"file_path": "mem0/configs/llms/vllm.py",
"license": "Apache License 2.0",
"lines": 50,
"canary_id": -1,
"canary_value": "",
"pii_type": "",
"provider": "",
"regex_pattern": "",
"repetition": -1,
"template": ""
} | function_simple |
mem0ai/mem0:tests/vector_stores/test_pgvector.py | import importlib
import sys
import unittest
import uuid
from unittest.mock import MagicMock, patch
from mem0.vector_stores.pgvector import PGVector
class TestPGVector(unittest.TestCase):
def setUp(self):
"""Set up test fixtures."""
self.mock_conn = MagicMock()
self.mock_cursor = MagicMock... | {
"repo_id": "mem0ai/mem0",
"file_path": "tests/vector_stores/test_pgvector.py",
"license": "Apache License 2.0",
"lines": 1860,
"canary_id": -1,
"canary_value": "",
"pii_type": "",
"provider": "",
"regex_pattern": "",
"repetition": -1,
"template": ""
} | test |
mem0ai/mem0:examples/misc/personalized_search.py | """
Personalized Search Agent with Mem0 + Tavily
Uses LangChain agent pattern with Tavily tools for personalized search based on user memories stored in Mem0.
"""
from dotenv import load_dotenv
from mem0 import MemoryClient
from langchain.agents import create_openai_tools_agent, AgentExecutor
from langchain_core.promp... | {
"repo_id": "mem0ai/mem0",
"file_path": "examples/misc/personalized_search.py",
"license": "Apache License 2.0",
"lines": 192,
"canary_id": -1,
"canary_value": "",
"pii_type": "",
"provider": "",
"regex_pattern": "",
"repetition": -1,
"template": ""
} | function_complex |
mem0ai/mem0:examples/multiagents/llamaindex_learning_system.py | """
Multi-Agent Personal Learning System: Mem0 + LlamaIndex AgentWorkflow Example
INSTALLATIONS:
!pip install llama-index-core llama-index-memory-mem0 openai
You need MEM0_API_KEY and OPENAI_API_KEY to run the example.
"""
import asyncio
import logging
from datetime import datetime
from dotenv import load_dotenv
#... | {
"repo_id": "mem0ai/mem0",
"file_path": "examples/multiagents/llamaindex_learning_system.py",
"license": "Apache License 2.0",
"lines": 165,
"canary_id": -1,
"canary_value": "",
"pii_type": "",
"provider": "",
"regex_pattern": "",
"repetition": -1,
"template": ""
} | function_complex |
mem0ai/mem0:examples/misc/multillm_memory.py | """
Multi-LLM Research Team with Shared Knowledge Base
Use Case: AI Research Team where each model has different strengths:
- GPT-4: Technical analysis and code review
- Claude: Writing and documentation
All models share a common knowledge base, building on each other's work.
Example: GPT-4 analyzes a tech stack → Cl... | {
"repo_id": "mem0ai/mem0",
"file_path": "examples/misc/multillm_memory.py",
"license": "Apache License 2.0",
"lines": 135,
"canary_id": -1,
"canary_value": "",
"pii_type": "",
"provider": "",
"regex_pattern": "",
"repetition": -1,
"template": ""
} | function_complex |
mem0ai/mem0:mem0/client/project.py | import logging
from abc import ABC, abstractmethod
from typing import Any, Dict, List, Optional
import httpx
from pydantic import BaseModel, ConfigDict, Field
from mem0.client.utils import api_error_handler
from mem0.memory.telemetry import capture_client_event
# Exception classes are referenced in docstrings only
l... | {
"repo_id": "mem0ai/mem0",
"file_path": "mem0/client/project.py",
"license": "Apache License 2.0",
"lines": 788,
"canary_id": -1,
"canary_value": "",
"pii_type": "",
"provider": "",
"regex_pattern": "",
"repetition": -1,
"template": ""
} | documentation |
mem0ai/mem0:mem0/client/utils.py | import json
import logging
import httpx
from mem0.exceptions import (
NetworkError,
create_exception_from_response,
)
logger = logging.getLogger(__name__)
class APIError(Exception):
"""Exception raised for errors in the API.
Deprecated: Use specific exception classes from mem0.exceptions instea... | {
"repo_id": "mem0ai/mem0",
"file_path": "mem0/client/utils.py",
"license": "Apache License 2.0",
"lines": 95,
"canary_id": -1,
"canary_value": "",
"pii_type": "",
"provider": "",
"regex_pattern": "",
"repetition": -1,
"template": ""
} | function_complex |
mem0ai/mem0:tests/test_memory_integration.py | from unittest.mock import MagicMock, patch
from mem0.memory.main import Memory
def test_memory_configuration_without_env_vars():
"""Test Memory configuration with mock config instead of environment variables"""
# Mock configuration without relying on environment variables
mock_config = {
"llm": ... | {
"repo_id": "mem0ai/mem0",
"file_path": "tests/test_memory_integration.py",
"license": "Apache License 2.0",
"lines": 152,
"canary_id": -1,
"canary_value": "",
"pii_type": "",
"provider": "",
"regex_pattern": "",
"repetition": -1,
"template": ""
} | test |
mem0ai/mem0:mem0/graphs/neptune/base.py | import logging
from abc import ABC, abstractmethod
from mem0.memory.utils import format_entities
try:
from rank_bm25 import BM25Okapi
except ImportError:
raise ImportError("rank_bm25 is not installed. Please install it using pip install rank-bm25")
from mem0.graphs.tools import (
DELETE_MEMORY_STRUCT_TOO... | {
"repo_id": "mem0ai/mem0",
"file_path": "mem0/graphs/neptune/base.py",
"license": "Apache License 2.0",
"lines": 424,
"canary_id": -1,
"canary_value": "",
"pii_type": "",
"provider": "",
"regex_pattern": "",
"repetition": -1,
"template": ""
} | function_complex |
mem0ai/mem0:tests/memory/test_neptune_memory.py | import unittest
from unittest.mock import MagicMock, patch
import pytest
from mem0.graphs.neptune.neptunedb import MemoryGraph
from mem0.graphs.neptune.base import NeptuneBase
class TestNeptuneMemory(unittest.TestCase):
"""Test suite for the Neptune Memory implementation."""
def setUp(self):
"""Set u... | {
"repo_id": "mem0ai/mem0",
"file_path": "tests/memory/test_neptune_memory.py",
"license": "Apache License 2.0",
"lines": 306,
"canary_id": -1,
"canary_value": "",
"pii_type": "",
"provider": "",
"regex_pattern": "",
"repetition": -1,
"template": ""
} | test |
mem0ai/mem0:examples/misc/test.py | from agents import Agent, Runner, enable_verbose_stdout_logging, function_tool
from dotenv import load_dotenv
from mem0 import MemoryClient
enable_verbose_stdout_logging()
load_dotenv()
# Initialize Mem0 client
mem0 = MemoryClient()
# Define memory tools for the agent
@function_tool
def search_memory(query: str, ... | {
"repo_id": "mem0ai/mem0",
"file_path": "examples/misc/test.py",
"license": "Apache License 2.0",
"lines": 65,
"canary_id": -1,
"canary_value": "",
"pii_type": "",
"provider": "",
"regex_pattern": "",
"repetition": -1,
"template": ""
} | function_simple |
mem0ai/mem0:examples/misc/vllm_example.py | """
Example of using vLLM with mem0 for high-performance memory operations.
SETUP INSTRUCTIONS:
1. Install vLLM:
pip install vllm
2. Start vLLM server (in a separate terminal):
vllm serve microsoft/DialoGPT-small --port 8000
Wait for the message: "Uvicorn running on http://0.0.0.0:8000"
(Small model: ~50... | {
"repo_id": "mem0ai/mem0",
"file_path": "examples/misc/vllm_example.py",
"license": "Apache License 2.0",
"lines": 115,
"canary_id": -1,
"canary_value": "",
"pii_type": "",
"provider": "",
"regex_pattern": "",
"repetition": -1,
"template": ""
} | function_complex |
mem0ai/mem0:tests/llms/test_vllm.py | from unittest.mock import MagicMock, Mock, patch
import pytest
from mem0 import AsyncMemory, Memory
from mem0.configs.llms.base import BaseLlmConfig
from mem0.llms.vllm import VllmLLM
@pytest.fixture
def mock_vllm_client():
with patch("mem0.llms.vllm.OpenAI") as mock_openai:
mock_client = Mock()
... | {
"repo_id": "mem0ai/mem0",
"file_path": "tests/llms/test_vllm.py",
"license": "Apache License 2.0",
"lines": 155,
"canary_id": -1,
"canary_value": "",
"pii_type": "",
"provider": "",
"regex_pattern": "",
"repetition": -1,
"template": ""
} | test |
mem0ai/mem0:mem0/configs/vector_stores/baidu.py | from typing import Any, Dict
from pydantic import BaseModel, ConfigDict, Field, model_validator
class BaiduDBConfig(BaseModel):
endpoint: str = Field("http://localhost:8287", description="Endpoint URL for Baidu VectorDB")
account: str = Field("root", description="Account for Baidu VectorDB")
api_key: str... | {
"repo_id": "mem0ai/mem0",
"file_path": "mem0/configs/vector_stores/baidu.py",
"license": "Apache License 2.0",
"lines": 22,
"canary_id": -1,
"canary_value": "",
"pii_type": "",
"provider": "",
"regex_pattern": "",
"repetition": -1,
"template": ""
} | function_simple |
mem0ai/mem0:tests/vector_stores/test_baidu.py | from unittest.mock import Mock, PropertyMock, patch
import pytest
from pymochow.exception import ServerError
from pymochow.model.enum import ServerErrCode, TableState
from pymochow.model.table import (
FloatVector,
Table,
VectorSearchConfig,
VectorTopkSearchRequest,
)
from mem0.vector_stores.baidu imp... | {
"repo_id": "mem0ai/mem0",
"file_path": "tests/vector_stores/test_baidu.py",
"license": "Apache License 2.0",
"lines": 174,
"canary_id": -1,
"canary_value": "",
"pii_type": "",
"provider": "",
"regex_pattern": "",
"repetition": -1,
"template": ""
} | test |
mem0ai/mem0:examples/misc/diet_assistant_voice_cartesia.py | """Simple Voice Agent with Memory: Personal Food Assistant.
A food assistant that remembers your dietary preferences and speaks recommendations
Powered by Agno + Cartesia + Mem0
export MEM0_API_KEY=your_mem0_api_key
export OPENAI_API_KEY=your_openai_api_key
export CARTESIA_API_KEY=your_cartesia_api_key
"""
from textw... | {
"repo_id": "mem0ai/mem0",
"file_path": "examples/misc/diet_assistant_voice_cartesia.py",
"license": "Apache License 2.0",
"lines": 103,
"canary_id": -1,
"canary_value": "",
"pii_type": "",
"provider": "",
"regex_pattern": "",
"repetition": -1,
"template": ""
} | function_complex |
mem0ai/mem0:mem0/configs/vector_stores/mongodb.py | from typing import Any, Dict, Optional
from pydantic import BaseModel, Field, model_validator
class MongoDBConfig(BaseModel):
"""Configuration for MongoDB vector database."""
db_name: str = Field("mem0_db", description="Name of the MongoDB database")
collection_name: str = Field("mem0", description="Nam... | {
"repo_id": "mem0ai/mem0",
"file_path": "mem0/configs/vector_stores/mongodb.py",
"license": "Apache License 2.0",
"lines": 20,
"canary_id": -1,
"canary_value": "",
"pii_type": "",
"provider": "",
"regex_pattern": "",
"repetition": -1,
"template": ""
} | function_simple |
mem0ai/mem0:mem0/vector_stores/mongodb.py | import logging
from importlib.metadata import version
from typing import Any, Dict, List, Optional
from pydantic import BaseModel
try:
from pymongo import MongoClient
from pymongo.driver_info import DriverInfo
from pymongo.errors import PyMongoError
from pymongo.operations import SearchIndexModel
exce... | {
"repo_id": "mem0ai/mem0",
"file_path": "mem0/vector_stores/mongodb.py",
"license": "Apache License 2.0",
"lines": 269,
"canary_id": -1,
"canary_value": "",
"pii_type": "",
"provider": "",
"regex_pattern": "",
"repetition": -1,
"template": ""
} | function_complex |
mem0ai/mem0:tests/vector_stores/test_mongodb.py | from unittest.mock import MagicMock, patch
import pytest
from mem0.vector_stores.mongodb import MongoDB
@pytest.fixture
@patch("mem0.vector_stores.mongodb.MongoClient")
def mongo_vector_fixture(mock_mongo_client):
mock_client = mock_mongo_client.return_value
mock_db = mock_client["test_db"]
mock_collect... | {
"repo_id": "mem0ai/mem0",
"file_path": "tests/vector_stores/test_mongodb.py",
"license": "Apache License 2.0",
"lines": 272,
"canary_id": -1,
"canary_value": "",
"pii_type": "",
"provider": "",
"regex_pattern": "",
"repetition": -1,
"template": ""
} | test |
mem0ai/mem0:openmemory/api/alembic/versions/afd00efbd06b_add_unique_user_id_constraints.py | """remove_global_unique_constraint_on_app_name_add_composite_unique
Revision ID: afd00efbd06b
Revises: add_config_table
Create Date: 2025-06-04 01:59:41.637440
"""
from typing import Sequence, Union
from alembic import op
# revision identifiers, used by Alembic.
revision: str = 'afd00efbd06b'
down_revision: Union[s... | {
"repo_id": "mem0ai/mem0",
"file_path": "openmemory/api/alembic/versions/afd00efbd06b_add_unique_user_id_constraints.py",
"license": "Apache License 2.0",
"lines": 26,
"canary_id": -1,
"canary_value": "",
"pii_type": "",
"provider": "",
"regex_pattern": "",
"repetition": -1,
"template": ""
} | function_simple |
mem0ai/mem0:mem0/llms/sarvam.py | import os
from typing import Dict, List, Optional
import requests
from mem0.configs.llms.base import BaseLlmConfig
from mem0.llms.base import LLMBase
class SarvamLLM(LLMBase):
def __init__(self, config: Optional[BaseLlmConfig] = None):
super().__init__(config)
# Set default model if not provide... | {
"repo_id": "mem0ai/mem0",
"file_path": "mem0/llms/sarvam.py",
"license": "Apache License 2.0",
"lines": 66,
"canary_id": -1,
"canary_value": "",
"pii_type": "",
"provider": "",
"regex_pattern": "",
"repetition": -1,
"template": ""
} | function_complex |
mem0ai/mem0:openmemory/api/alembic/versions/add_config_table.py | """add_config_table
Revision ID: add_config_table
Revises: 0b53c747049a
Create Date: 2023-06-01 10:00:00.000000
"""
import uuid
import sqlalchemy as sa
from alembic import op
# revision identifiers, used by Alembic.
revision = 'add_config_table'
down_revision = '0b53c747049a'
branch_labels = None
depends_on = None
... | {
"repo_id": "mem0ai/mem0",
"file_path": "openmemory/api/alembic/versions/add_config_table.py",
"license": "Apache License 2.0",
"lines": 31,
"canary_id": -1,
"canary_value": "",
"pii_type": "",
"provider": "",
"regex_pattern": "",
"repetition": -1,
"template": ""
} | function_simple |
mem0ai/mem0:openmemory/api/app/routers/config.py | from typing import Any, Dict, Optional
from app.database import get_db
from app.models import Config as ConfigModel
from app.utils.memory import reset_memory_client
from fastapi import APIRouter, Depends, HTTPException
from pydantic import BaseModel, Field
from sqlalchemy.orm import Session
router = APIRouter(prefix=... | {
"repo_id": "mem0ai/mem0",
"file_path": "openmemory/api/app/routers/config.py",
"license": "Apache License 2.0",
"lines": 235,
"canary_id": -1,
"canary_value": "",
"pii_type": "",
"provider": "",
"regex_pattern": "",
"repetition": -1,
"template": ""
} | function_complex |
mem0ai/mem0:examples/misc/healthcare_assistant_google_adk.py | import asyncio
import warnings
from google.adk.agents import Agent
from google.adk.runners import Runner
from google.adk.sessions import InMemorySessionService
from google.genai import types
from mem0 import MemoryClient
warnings.filterwarnings("ignore", category=DeprecationWarning)
# Initialize Mem0 client
mem0_c... | {
"repo_id": "mem0ai/mem0",
"file_path": "examples/misc/healthcare_assistant_google_adk.py",
"license": "Apache License 2.0",
"lines": 159,
"canary_id": -1,
"canary_value": "",
"pii_type": "",
"provider": "",
"regex_pattern": "",
"repetition": -1,
"template": ""
} | function_complex |
mem0ai/mem0:openmemory/api/alembic/env.py | import os
import sys
from logging.config import fileConfig
from alembic import context
from dotenv import load_dotenv
from sqlalchemy import engine_from_config, pool
# Add the parent directory to the Python path
sys.path.append(os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
# Load environment variables... | {
"repo_id": "mem0ai/mem0",
"file_path": "openmemory/api/alembic/env.py",
"license": "Apache License 2.0",
"lines": 66,
"canary_id": -1,
"canary_value": "",
"pii_type": "",
"provider": "",
"regex_pattern": "",
"repetition": -1,
"template": ""
} | function_simple |
mem0ai/mem0:openmemory/api/alembic/versions/0b53c747049a_initial_migration.py | """Initial migration
Revision ID: 0b53c747049a
Revises:
Create Date: 2025-04-19 00:59:56.244203
"""
from typing import Sequence, Union
import sqlalchemy as sa
from alembic import op
# revision identifiers, used by Alembic.
revision: str = '0b53c747049a'
down_revision: Union[str, None] = None
branch_labels: Union[s... | {
"repo_id": "mem0ai/mem0",
"file_path": "openmemory/api/alembic/versions/0b53c747049a_initial_migration.py",
"license": "Apache License 2.0",
"lines": 217,
"canary_id": -1,
"canary_value": "",
"pii_type": "",
"provider": "",
"regex_pattern": "",
"repetition": -1,
"template": ""
} | function_simple |
mem0ai/mem0:openmemory/api/app/database.py | import os
from dotenv import load_dotenv
from sqlalchemy import create_engine
from sqlalchemy.orm import declarative_base, sessionmaker
# load .env file (make sure you have DATABASE_URL set)
load_dotenv()
DATABASE_URL = os.getenv("DATABASE_URL", "sqlite:///./openmemory.db")
if not DATABASE_URL:
raise RuntimeErro... | {
"repo_id": "mem0ai/mem0",
"file_path": "openmemory/api/app/database.py",
"license": "Apache License 2.0",
"lines": 24,
"canary_id": -1,
"canary_value": "",
"pii_type": "",
"provider": "",
"regex_pattern": "",
"repetition": -1,
"template": ""
} | function_simple |
mem0ai/mem0:openmemory/api/app/mcp_server.py | """
MCP Server for OpenMemory with resilient memory client handling.
This module implements an MCP (Model Context Protocol) server that provides
memory operations for OpenMemory. The memory client is initialized lazily
to prevent server crashes when external dependencies (like Ollama) are
unavailable. If the memory cl... | {
"repo_id": "mem0ai/mem0",
"file_path": "openmemory/api/app/mcp_server.py",
"license": "Apache License 2.0",
"lines": 415,
"canary_id": -1,
"canary_value": "",
"pii_type": "",
"provider": "",
"regex_pattern": "",
"repetition": -1,
"template": ""
} | function_complex |
mem0ai/mem0:openmemory/api/app/models.py | import datetime
import enum
import uuid
import sqlalchemy as sa
from app.database import Base
from app.utils.categorization import get_categories_for_memory
from sqlalchemy import (
JSON,
UUID,
Boolean,
Column,
DateTime,
Enum,
ForeignKey,
Index,
Integer,
String,
Table,
e... | {
"repo_id": "mem0ai/mem0",
"file_path": "openmemory/api/app/models.py",
"license": "Apache License 2.0",
"lines": 200,
"canary_id": -1,
"canary_value": "",
"pii_type": "",
"provider": "",
"regex_pattern": "",
"repetition": -1,
"template": ""
} | function_simple |
mem0ai/mem0:openmemory/api/app/routers/apps.py | from typing import Optional
from uuid import UUID
from app.database import get_db
from app.models import App, Memory, MemoryAccessLog, MemoryState
from fastapi import APIRouter, Depends, HTTPException, Query
from sqlalchemy import desc, func
from sqlalchemy.orm import Session, joinedload
router = APIRouter(prefix="/a... | {
"repo_id": "mem0ai/mem0",
"file_path": "openmemory/api/app/routers/apps.py",
"license": "Apache License 2.0",
"lines": 198,
"canary_id": -1,
"canary_value": "",
"pii_type": "",
"provider": "",
"regex_pattern": "",
"repetition": -1,
"template": ""
} | function_complex |
mem0ai/mem0:openmemory/api/app/routers/stats.py | from app.database import get_db
from app.models import App, Memory, MemoryState, User
from fastapi import APIRouter, Depends, HTTPException
from sqlalchemy.orm import Session
router = APIRouter(prefix="/api/v1/stats", tags=["stats"])
@router.get("/")
async def get_profile(
user_id: str,
db: Session = Depends(... | {
"repo_id": "mem0ai/mem0",
"file_path": "openmemory/api/app/routers/stats.py",
"license": "Apache License 2.0",
"lines": 23,
"canary_id": -1,
"canary_value": "",
"pii_type": "",
"provider": "",
"regex_pattern": "",
"repetition": -1,
"template": ""
} | function_simple |
mem0ai/mem0:openmemory/api/app/schemas.py | from datetime import datetime
from typing import List, Optional
from uuid import UUID
from pydantic import BaseModel, ConfigDict, Field, validator
class MemoryBase(BaseModel):
content: str
metadata_: Optional[dict] = Field(default_factory=dict)
class MemoryCreate(MemoryBase):
user_id: UUID
app_id: U... | {
"repo_id": "mem0ai/mem0",
"file_path": "openmemory/api/app/schemas.py",
"license": "Apache License 2.0",
"lines": 49,
"canary_id": -1,
"canary_value": "",
"pii_type": "",
"provider": "",
"regex_pattern": "",
"repetition": -1,
"template": ""
} | function_simple |
mem0ai/mem0:openmemory/api/app/utils/categorization.py | import logging
from typing import List
from app.utils.prompts import MEMORY_CATEGORIZATION_PROMPT
from dotenv import load_dotenv
from openai import OpenAI
from pydantic import BaseModel
from tenacity import retry, stop_after_attempt, wait_exponential
load_dotenv()
openai_client = OpenAI()
class MemoryCategories(Bas... | {
"repo_id": "mem0ai/mem0",
"file_path": "openmemory/api/app/utils/categorization.py",
"license": "Apache License 2.0",
"lines": 34,
"canary_id": -1,
"canary_value": "",
"pii_type": "",
"provider": "",
"regex_pattern": "",
"repetition": -1,
"template": ""
} | function_simple |
mem0ai/mem0:openmemory/api/app/utils/db.py | from typing import Tuple
from app.models import App, User
from sqlalchemy.orm import Session
def get_or_create_user(db: Session, user_id: str) -> User:
"""Get or create a user with the given user_id"""
user = db.query(User).filter(User.user_id == user_id).first()
if not user:
user = User(user_id=... | {
"repo_id": "mem0ai/mem0",
"file_path": "openmemory/api/app/utils/db.py",
"license": "Apache License 2.0",
"lines": 26,
"canary_id": -1,
"canary_value": "",
"pii_type": "",
"provider": "",
"regex_pattern": "",
"repetition": -1,
"template": ""
} | function_simple |
mem0ai/mem0:openmemory/api/app/utils/memory.py | """
Memory client utilities for OpenMemory.
This module provides functionality to initialize and manage the Mem0 memory client
with automatic configuration management and Docker environment support.
Docker Ollama Configuration:
When running inside a Docker container and using Ollama as the LLM or embedder provider,
t... | {
"repo_id": "mem0ai/mem0",
"file_path": "openmemory/api/app/utils/memory.py",
"license": "Apache License 2.0",
"lines": 330,
"canary_id": -1,
"canary_value": "",
"pii_type": "",
"provider": "",
"regex_pattern": "",
"repetition": -1,
"template": ""
} | function_complex |
mem0ai/mem0:openmemory/api/app/utils/permissions.py | from typing import Optional
from uuid import UUID
from app.models import App, Memory, MemoryState
from sqlalchemy.orm import Session
def check_memory_access_permissions(
db: Session,
memory: Memory,
app_id: Optional[UUID] = None
) -> bool:
"""
Check if the given app has permission to access a mem... | {
"repo_id": "mem0ai/mem0",
"file_path": "openmemory/api/app/utils/permissions.py",
"license": "Apache License 2.0",
"lines": 42,
"canary_id": -1,
"canary_value": "",
"pii_type": "",
"provider": "",
"regex_pattern": "",
"repetition": -1,
"template": ""
} | function_complex |
mem0ai/mem0:openmemory/api/app/utils/prompts.py | MEMORY_CATEGORIZATION_PROMPT = """Your task is to assign each piece of information (or “memory”) to one or more of the following categories. Feel free to use multiple categories per item when appropriate.
- Personal: family, friends, home, hobbies, lifestyle
- Relationships: social network, significant others, colleag... | {
"repo_id": "mem0ai/mem0",
"file_path": "openmemory/api/app/utils/prompts.py",
"license": "Apache License 2.0",
"lines": 26,
"canary_id": -1,
"canary_value": "",
"pii_type": "",
"provider": "",
"regex_pattern": "",
"repetition": -1,
"template": ""
} | documentation |
mem0ai/mem0:openmemory/api/main.py | import datetime
from uuid import uuid4
from app.config import DEFAULT_APP_ID, USER_ID
from app.database import Base, SessionLocal, engine
from app.mcp_server import setup_mcp_server
from app.models import App, User
from app.routers import apps_router, backup_router, config_router, memories_router, stats_router
from fa... | {
"repo_id": "mem0ai/mem0",
"file_path": "openmemory/api/main.py",
"license": "Apache License 2.0",
"lines": 75,
"canary_id": -1,
"canary_value": "",
"pii_type": "",
"provider": "",
"regex_pattern": "",
"repetition": -1,
"template": ""
} | function_simple |
mem0ai/mem0:mem0/embeddings/aws_bedrock.py | import json
import os
from typing import Literal, Optional
try:
import boto3
except ImportError:
raise ImportError("The 'boto3' library is required. Please install it using 'pip install boto3'.")
import numpy as np
from mem0.configs.embeddings.base import BaseEmbedderConfig
from mem0.embeddings.base import E... | {
"repo_id": "mem0ai/mem0",
"file_path": "mem0/embeddings/aws_bedrock.py",
"license": "Apache License 2.0",
"lines": 77,
"canary_id": -1,
"canary_value": "",
"pii_type": "",
"provider": "",
"regex_pattern": "",
"repetition": -1,
"template": ""
} | function_complex |
mem0ai/mem0:tests/memory/test_main.py | import logging
from unittest.mock import MagicMock
import pytest
from mem0.memory.main import AsyncMemory, Memory
def _setup_mocks(mocker):
"""Helper to setup common mocks for both sync and async fixtures"""
mock_embedder = mocker.MagicMock()
mock_embedder.return_value.embed.return_value = [0.1, 0.2, 0.... | {
"repo_id": "mem0ai/mem0",
"file_path": "tests/memory/test_main.py",
"license": "Apache License 2.0",
"lines": 102,
"canary_id": -1,
"canary_value": "",
"pii_type": "",
"provider": "",
"regex_pattern": "",
"repetition": -1,
"template": ""
} | test |
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