langchain-encrypted-redis-memory 1.0.2

Encrypted Redis chat message history for LangChain with AES-128 encryption via mores-encryption.

LangChain-Encrypted-Redis-Memory

A Secure, Encrypted Redis Chat Memory for LangChain Applications

LangChain-Encrypted-Redis-Memory extends RedisChatMessageHistory to provide AES-128 encryption for all stored messages. Built on top of mores-encryption, it ensures sensitive conversation data remains protected at rest.

Perfect for securing chat histories containing PII, medical data, financial information, or any sensitive conversation data in your LangChain applications.

LangChain-Encrypted-Redis-Memory removes the cryptographic complexity so you can focus on building — not configuring.

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Features

• AES-128 Encryption — Messages encrypted using Fernet (AES-128 CBC with PKCS7 padding)
• HMAC-SHA256 Integrity — Cryptographic verification of message integrity
• URL-safe Base64 Output — Encrypted data stored in URL-safe format
• Drop-in Replacement — Compatible with LangChain's chat memory interface
• TTL Support — Optional time-to-live for automatic message expiration
• Type Filtering — Supports human, AI, and system message types
• Zero-Config Encryption — Automatic key handling via mores-encryption

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Installation

pip install langchain-encrypted-redis-memory

Or install from source:

git clone https://github.com/HATAKEkakshi/langchain-encrypted-redis-memory.git
cd langchain-encrypted-redis-memory
pip install -e .

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Setup

Generate Encryption Key

Run this command in your terminal:

python -c "from cryptography.fernet import Fernet; print('ENCRYPTION_KEY=' + Fernet.generate_key().decode())"

Save to .env

Copy the output and save it in your .env file:

ENCRYPTION_KEY=your_generated_key_here

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Usage

1. Basic Usage

from langchain_encrypted_redis_memory import EncryptedRedisChatMessageHistory
from langchain_core.messages import HumanMessage, AIMessage

# Create encrypted history
history = EncryptedRedisChatMessageHistory(
    session_id="user-123",
    url="redis://localhost:6379"
)

# Add messages (automatically encrypted)
history.add_message(HumanMessage(content="Hello, how are you?"))
history.add_message(AIMessage(content="I'm doing great, thank you!"))

# Retrieve messages (automatically decrypted)
messages = history.messages
for msg in messages:
    print(f"{msg.type}: {msg.content}")

2. With TTL (Auto-expiry)

# Messages expire after 1 hour
history = EncryptedRedisChatMessageHistory(
    session_id="user-123",
    url="redis://localhost:6379",
    ttl=3600  # seconds
)

3. Reset Session History

# Clear history for a specific session
EncryptedRedisChatMessageHistory.reset_session_history(
    url="redis://localhost:6379",
    session_id="user-123"
)

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Why Use LangChain-Encrypted-Redis-Memory?

Because securing chat history shouldn't be painful.

Most developers store sensitive conversation data in Redis without encryption — exposing PII, medical records, and confidential information to potential breaches.

LangChain-Encrypted-Redis-Memory gives you:

• Automatic Encryption — Messages encrypted before storage
• Transparent Decryption — Seamless retrieval without extra code
• LangChain Compatible — Works with all LangChain memory patterns
• Production Ready — Built on proven cryptographic standards
• Minimal Code Changes — Drop-in replacement for RedisChatMessageHistory

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Configuration

Environment Variables

Variable	Description	Required	Default
ENCRYPTION_KEY	Base64-encoded 32-byte Fernet key	No (Auto-generated if missing)	N/A

Redis Connection URLs

# Local Redis
url="redis://localhost:6379"

# With password
url="redis://:password@localhost:6379"

# With database selection
url="redis://localhost:6379/1"

# TLS connection
url="rediss://localhost:6379"

Key Generation

Run these commands to generate secure values for your .env file:

Generate Encryption Key:

python -c "from cryptography.fernet import Fernet; print('ENCRYPTION_KEY=' + Fernet.generate_key().decode())"

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API Reference

EncryptedRedisChatMessageHistory

EncryptedRedisChatMessageHistory(
    session_id: str,
    url: str,
    ttl: Optional[int] = None,
    key_prefix: str = "message_store:"
)

Parameter	Type	Description
session_id	str	Unique identifier for the chat session
url	str	Redis connection URL
ttl	int	Optional TTL in seconds for message expiration
key_prefix	str	Prefix for Redis keys (default: message_store:)

Properties

Property	Type	Description
messages	List[BaseMessage]	List of decrypted messages

Methods

Method	Description
add_message(message)	Encrypt and store a message
clear()	Delete all messages for this session
reset_session_history(url, session_id)	Static method to clear a session

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Security Implementation Details

• Encryption: cryptography.fernet.Fernet (AES-128 CBC with PKCS7 padding, HMAC-SHA256 for integrity)
• Key Management: Automatic loading from ENCRYPTION_KEY environment variable
• Encoding: All outputs are URL-safe Base64 encoded strings
• Library: Built on mores-encryption for proven security

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Development

Setup

git clone https://github.com/HATAKEkakshi/langchain-encrypted-redis-memory.git
cd langchain-encrypted-redis-memory
python -m venv venv
source venv/bin/activate
pip install -e ".[dev]"

Running Tests

# Run all tests
pytest

# With verbose output
pytest -v

# With coverage
pytest --cov=langchain_encrypted_redis_memory

# Skip integration tests
pytest -m "not integration"

Code Quality

# Format code
black langchain_encrypted_redis_memory tests

# Lint
flake8 langchain_encrypted_redis_memory tests

# Type check
mypy langchain_encrypted_redis_memory

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Documentation & Source Code

• GitHub: https://github.com/HATAKEkakshi/langchain-encrypted-redis-memory
• PyPI: https://pypi.org/project/langchain-encrypted-redis-memory/
• mores-encryption: https://pypi.org/project/mores-encryption/

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License

MIT License — see LICENSE for details.

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Author

Hemant Kumar — GitHub

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Acknowledgments

• LangChain for the excellent LLM framework
• mores-encryption for encryption utilities
• cryptography for secure encryption primitives