ComoRAG
Cognitive-Inspired Memory-Organized RAG for Stateful Long Narrative Reasoning
GraphCanon updated Sep 20, 2026 · GitHub synced Sep 20, 2026
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Decision brief
ComoRAG is a cognitive-inspired memory-organized RAG system designed for stateful long narrative reasoning, built for Python 3.10 or above, and supports CUDA 12.x for enhanced performance.
Good fit when
- Use ComoRAG when you need to handle long narrative reasoning tasks that require stateful memory and cognitive-inspired processing.
- Consider ComoRAG if your project involves complex narrative analysis and you have access to a GPU with CUDA 12.x for optimal performance.
Avoid when
- Avoid ComoRAG if your project does not require stateful long narrative reasoning or if you are working with short, simple narratives.
- Do not use ComoRAG if you are constrained to Python versions below 3.10 or do not have access to a GPU with CUDA 12.x support.
- Requirements:
- Python 3.10 or above is recommended.; CUDA 12.x is supported but optional.
Observed Sep 18, 2026 · Source: enrich:decision_facts
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Maintenance and security
Full trust report- Maintenance
- Dormant (385d since push)
- As of Sep 18, 2026
- Provenance
- Not a fork · Personal account
- As of Sep 18, 2026
- Security (OSV)
- 305 low (305 low)
- As of Sep 18, 2026
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Install
pip install ComoRAGSimilar tools
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Evidence and technical details
Sourced facts, taxonomy, compatibility claims, README excerpt, and machine-readable endpoints.
Overview
ComoRAG is a research project aimed at enhancing long narrative reasoning through a cognitive-inspired memory-organized RAG system.
Capability facts
- Languages
- python
Source: github.language · Sep 18, 2026
Categories
Compatibility
Sourced claims from the README excerpt - not unsourced marketing copy.
Source: README excerpt (regex_v1, Sep 18, 2026)
3. 🔑 **Environment variables**: Set your OpenAI API Key or local LLM/embedding paths as neededSource link
Source: README excerpt (regex_v1, Sep 18, 2026)
1. 🐍 **Python version**: Python 3.10 or above recommendedSource link
Tags
README
Installation & Environment 🛠️ 1. 🐍 Python version : Python 3.10 or above recommended 2. 📦 Install dependencies : 3. 🔑 Environment variables : Set your OpenAI API Key or local LLM/embedding paths as needed 4. ⚙️ GPU (optional but recommended) : CUDA 12.x supported by many depe...
For agents
This page has a .md twin and JSON over the API.