Memory-backed chat

This example demonstrates a practical memory stack:

• OpenAI GPT-5 is used as LLM.
• Mem0 stores and retrieves long-term memories extracted from the conversation.
• Qdrant is the vector database backend used by Mem0 for semantic retrieval.

The key takeaway is architectural: GPT-5 remains stateless between runs, while Mem0+Qdrant provides durable, searchable memory that can be injected back into the model’s context on each turn.

What you build

A CLI chat application that:

1. Retrieves relevant long-term memories from Mem0/Qdrant for each user message
2. Passes those memories to GPT-5 as part of the system instructions
3. Stores the latest interaction back into Mem0 so it can influence future sessions

Prerequisites

• Python 3.10+
• An OpenAI API key (exported as OPENAI_API_KEY env variable)
• A running Qdrant instance (e.g., using Docker)

Start Qdrant locally (Docker)

docker run -p 6333:6333 -p 6334:6334 qdrant/qdrant

Qdrant will listen on localhost:6333 by default.

If you already run Qdrant elsewhere, set:

• QDRANT_HOST
• QDRANT_PORT

Setup

python -m venv .venv

# macOS/Linux:
source .venv/bin/activate

# Windows Command Prompt:
.venv\Scripts\activate.bat

# Windows PowerShell:
.venv\Scripts\Activate.ps1

pip install -r requirements.txt

Create a .env file (optional):

OPENAI_API_KEY=your_key_here
MODEL=gpt-5
QDRANT_HOST=localhost
QDRANT_PORT=6333
MEM0_COLLECTION=mem0_demo

Run

python mem0_chat.py --user alice

Commands

Inside the chat:

• /help – show commands
• /memories – show a sample of stored memories for the user (best-effort)
• /forget – clear stored memories for the user (best-effort)
• /exit – quit

Suggested experiment

1. Tell the assistant a stable preference (e.g., "When I ask for recommendations, I prefer a short list with pros/cons.").
2. Exit the program and run it again.
3. Ask a related question ("Recommend books for my next trip.").
4. Observe that the assistant recalls and applies your preference, even though the in-session transcript is empty.
5. Run /memories to inspect what was stored.

Notes

• Mem0 performs extraction and conflict resolution when adding memories (default behavior).
• The script keeps a small in-session transcript (--window) for local coherence; cross-session continuity comes from Mem0+Qdrant.