OmniRecall Beta: FAISS-Powered Memory Injection for Cloud LLM Chats

What OmniRecall Does
OmniRecall is a local mitmproxy bypass that intercepts traffic to cloud chat interfaces (tested on DeepSeek). It hacks into the proprietary SSE fragment stream and forces a long-term memory layer onto a system that was designed to be stateless.
Technical Mechanism
- Deep-Packet Parsing: Reconstructs the full assistant reply by tracking real-time patches
- Command Control: Detects [ADD], [UPDATE], [REMOVE], [CLEAR] from the AI's output
- Local Brain: Maintains memory.txt + FAISS index (sentence-transformers MiniLM-L6)
- Context Injection: Top recalled facts get force-fed into your next message as [RECALL: ...]
Current Status & Limitations
This is a beta/experimental release. The developer notes: "This is the closest I've gotten to the dream after weeks of debugging hell. It is buggy. It is experimental. [ADD] is mostly stable, but [SEARCH] is temperamental—if you want perfection, fix it yourself. I've hit my energy limit on this build."
Upstream UI changes will break it. The developer states: "If it breaks, that's on you now."
Requirements & Setup
Potato-PC Requirements:
- CPU only (faiss-cpu + all-MiniLM-L6-v2)
- No local LLM needed — augments the cloud models you already use
- Zero cost, zero API keys, 100% local data isolation
How to Deploy:
pip install mitmproxy faiss-cpu sentence-transformers numpyTrust the mitmproxy CA cert on your OS/browser (run mitmproxy once to generate it). Set system proxy to 127.0.0.1:8080. Then run:
mitmdump -s omnirecall.pyGo to chat.deepseek.com and start feeding it memories.
License Terms
The project uses an aggressively restrictive source-available license:
- No commercial use
- No private forks
- Mandatory public ALTERATIONS.md for any logic changes
- If you port to Claude/GPT-4o/whatever, keep it public per the license
The developer explains: "I've watched too many solo-dev projects get strip-mined, privatized, or turned into paid SaaS while the creator gets zero. This license isn't friendly—it's built to protect the work from exactly those people. If the terms scare you off, that's the point."
📖 Read the full source: r/LocalLLaMA
👀 See Also

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