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Synapse Layer — Python Basic Example

Python 3.9+ MIT License

Store and recall AI agent memories with semantic search in under 30 seconds.

What this does

This example connects to the Synapse Layer API, stores a memory with semantic content, and recalls it using a natural language query. It demonstrates the core store/recall loop that gives your AI agents persistent memory across sessions and tools.

Prerequisites

  • Python 3.9+
  • A Synapse Layer account and sk_connect_ token (get yours here)

Install

git clone https://github.com/SynapseLayer/synapse-layer-python-basic
cd synapse-layer-python-basic && pip install -r requirements.txt
cp .env.example .env  # edit with your token

Run

python3 main.py

Expected output

[store] Saving memory...
[store] Done.

[recall] Searching for user preferences...
  [0] content: The user prefers dark mode and communicates in Portuguese.
      tq_score: 0.716

[recall] 1 memories found.

Get your token

  1. Go to forge.synapselayer.org
  2. Sign up or log in
  3. Navigate to Dashboard → Connect
  4. Generate a new sk_connect_ token
  5. Paste it in your .env file