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TeleAI-UAGI / telemem

TeleMem is a high-performance drop-in replacement for Mem0, featuring semantic deduplication, long-term dialogue memory, and multimodal video reasoning.

Why this job: topics: agent-memory, long-term-memory, memory

Picture from the TeleAI-UAGI/telemem README

What it does

  • Significantly improved memory accuracy. Achieved 86.33% accuracy on the ZH-4O Chinese multi-character long-dialogue benchmark, 19% higher than Mem0.
  • Doubled speed performance. Millisecond-level semantic retrieval enabled by efficient buffering and batch writing.
  • Greatly reduced token cost. Optimized token usage delivers the same performance with significantly lower LLM overhead.
  • Precise character memory preservation. Automatically builds independent memory profiles for each character, eliminating confusion.
  • Automated Video Processing Pipeline. From raw video → frame extraction → caption generation → vector database, fully automated

Get started

No single install command. Read the steps in the README (opens in new tab)

Maintenance
Active
Last commit 7 days ago
Stars
493
On GitHub
Licence
Apache-2.0
Allows business use
Downloads for
None listed
No release files
Latest version
v1.10.1
Released 17 days ago
Built with
Python
93% of the code

Is it looked after?

Contributors
4
Last 90 days
Issues
83% closed
1 still open
Pull requests
8 merged
0 waiting
Releases
13
13 in the last year

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More: languages, topics and project record

Languages

  • Python 93%
  • Go 4%
  • TypeScript 3%
  • Dockerfile <1%

Topics

  • agent
  • agent-memory
  • ai-agents
  • character-memory
  • conversational-ai
  • faiss
  • llm
  • long-term-memory
  • mcp
  • mem0
  • memory
  • model-context-protocol

Project record

  • JobAgent memory
  • StatusListed
  • Commits190
  • Forks36
  • Watching16
  • Stars in 28 days+1
  • CreatedDec 5, 2025
  • First seen by usNov 7, 2026
  • CheckedNov 7, 2026

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