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Inputs:
Outputs:
AI memory layer for smarter agents.
Most popular alternative: MemoryPlugin (7 saves)
Socials:
MemoriPy is an open-source AI memory layer designed to bring human-like memory and adaptability capabilities to AI systems. By providing AI agents with both short-term and long-term memory, it can transform repetitive, routine systems into platforms that are more aware of their context and are capable of acting as intelligent assistants.
MemoriPy enhances every interaction to help build smarter and more efficient AI systems by producing context-rich responses and therefore eliminating repetitive queries.
It improves accuracy by utilizing a unique concept that involves clustering and memory decay to refine responses and prioritize the most pertinent information.
MemoriPy is designed to work seamlessly with other platforms such as OpenAI and Ollama. It can be optimally used in diverse AI-driven projects. For instance, it can upgrade chatbots to remember past interactions and resolve queries faster, develop AI that evolves over time by adjusting to user preferences, construct autonomous systems that become smarter with each engagement, and enhance retail recommendations by recalling customer purchase history.
To sum up, MemoriPy is an effective AI tool that grants AI systems a memory feature, paving the way for AI that can adapt and evolve over time based on the learned and recalled information.
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December 30, 2024
Khazar Allahverdiyev
Initial release of MemoriPy.
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Comments
Emily Richardson
🙏 48 karma
Dec 30, 2024
Memoripy is a GAMECHANGER.
I see why it has so many stars on GitHub- we use it for all of our agents to ensure they are context aware! Great job 👏
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MemoriPy was manually vetted by our editorial team and was first featured on December 30th 2024.
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870,688643v1.6 released 24d agoFree + from $12/mo
Reducing manual efforts in first-pass during code-review process helps speed up the "final check" before merging PRs -
13,274108v2.1 released 2mo agoFree + from $45/mo
This is the first AI marketing tool I’ve used that actually helps me get things done, not just suggest generic ideas. The mix of AI-powered strategy and real experts executing the work makes it feel like having a high-performance marketing team without the overhead
Pros and Cons
Pros
Open-source
Human-like memory enhancement
Adaptive capabilities
Short-term and long-term memory
Transforms repetitive systems
Facilitates intelligent assistance
Produces context-rich responses
Eliminates repetitive queries
Utilizes concept clustering
Implements memory decay
Refinement of responses
Prioritizes most pertinent information
Compatibility with Ollama
Optimizes chatbots
Facilitates construction of autonomous systems
Enhances retail recommendations
Recalls customer purchase history
Efficiency improvement
Accuracy improvement
Supports learning and recall
Effortless integration
Cost efficiency
Optimizes LLM calls
Reduces token usage
Integrates past interaction recall
Facilitates building smarter systems
View 21 more pros
Cons
Lacks clear documentation
No mention of a UI
Possible memory management issues
Scalability concerns
May lack some integrations
Dependent on platform compatibility
No versioning information
Unclear error handling
Limited use cases
Potential slow response time
View 5 more cons
3 alternatives to MemoriPy for AI memory
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Cure AI amnesia: Remember everything you tell it.3857Released 1y agoFrom $12.5/yrI'm using MemoryPlugin since a year. It is brilliant how can it improve the work with LLM-s. With any LLM-s. Asad did a lot of improvement, he is open for discussion about enhancements. -
AI memory421Released 17d ago100% Free -
AI-powered memory coach for better recall.221Released 17d ago100% Free
Q&A
What is MemoriPy?
MemoriPy is an AI memory library that enhances agents with human-like short-term and long-term memory capabilities. It reduces hallucinations and improves contextual understanding by storing, clustering, and retrieving relevant information for more accurate and grounded responses.
What is the idea behind MemoriPy’s human-like memory feature?
The idea behind MemoriPy’s human-like memory feature is to emulate the brain's ability to store, cluster, and recall information contextually. It uses semantic embeddings for short-term relevance and persistent storage for long-term context, enabling AI to reason and respond with greater accuracy and depth.
How does MemoriPy provide both short-term and long-term memory?
MemoriPy provides short-term memory by storing recent context in in-memory structures and retrieving it efficiently using semantic embeddings and vector similarity (FAISS). Long-term memory relies on JSON-based and in-memory storage to persist and retrieve information, enabling contextual reasoning over extended periods.
What does it mean that MemoriPy can transform repetitive systems into context-aware platforms?
MemoriPy transforms repetitive systems into context-aware platforms by enabling AI to retain and retrieve relevant information from past interactions. This allows systems to adapt responses based on historical context, reducing redundancy and improving personalization and efficiency in decision-making.
How does MemoriPy work to eliminate repetitive queries?
MemoriPy eliminates repetitive queries by leveraging semantic memory and reasoning. It identifies and clusters previously encountered queries using embeddings, stores the relevant responses, and retrieves them when similar queries arise, ensuring efficient and context-aware responses without redundant processing.
What unique concept does MemoriPy use to enhance accuracy?
MemoriPy enhances accuracy by leveraging semantic clustering and context-aware retrieval from its memory layers. This approach ensures that the most relevant information is used in AI responses, improving contextual understanding and reducing errors.
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