makecindy
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cindy
Cindy is an open-source AI agent that runs locally on your machine, integrates multiple AI harnesses and models, and provides memory, skills, and automation to perform real work in your projects and apps.
MiniMem
MiniMem is a deliberately small, transparent baseline for conversational memory evaluation on LoCoMo-style question answering, using LLM fact extraction, embedding cosine similarity, direct top-k retrieval, and token-level F1.
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MIT
Last updated
2026-07-30
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FR-AI / ANALYSISWhy it is worth attention
It provides a minimal, understandable reference point in a field dominated by complex memory systems, and includes a curated survey of open-source memory research and a ready-to-run LoCoMo benchmark.
Who it is for
- Researchers evaluating conversational memory systems
- Developers seeking a simple baseline for LoCoMo-style QA
- Educators teaching LLM memory and retrieval pipelines
- Practitioners comparing lightweight memory pipelines before adopting richer systems
Use cases
- Baseline scoring on the bundled LoCoMo dataset
- Debugging and validating LLM fact extraction and retrieval behavior
- Educational demonstrations of a complete memory QA pipeline
- Lightweight evaluation of OpenAI-compatible chat models on memory tasks
Strengths
- Deliberately small pipeline with clearly separated construction, retrieval, answering, and evaluation stages
- Includes a bundled LoCoMo dataset and scripts to run full evaluation
- Quickstart makes only two LLM calls and prints progress before each API stage
- Open-source research index in references/README.md provides context and scope limitations
Considerations
- Excludes memory updating, clustering, keyword search, reranking, graph retrieval, and token-budget optimization
- Full LoCoMo evaluation requires 272 memory-construction calls and 1,540 answer calls, so API costs and rate limits must be considered
- Uses token-level F1 only and evaluates non-adversarial questions, not adversarial ones
README quick start
Quick start
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