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Long_term_memory Alternatives
Similar projects and alternatives to long_term_memory
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text-generation-webui
A Gradio web UI for Large Language Models. Supports transformers, GPTQ, AWQ, EXL2, llama.cpp (GGUF), Llama models.
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langchain
Discontinued ⚡ Building applications with LLMs through composability ⚡ [Moved to: https://github.com/langchain-ai/langchain] (by hwchase17)
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InfluxDB
Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.
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gpt-llama.cpp
A llama.cpp drop-in replacement for OpenAI's GPT endpoints, allowing GPT-powered apps to run off local llama.cpp models instead of OpenAI.
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StartUI-oobabooga-webui
WebUI StartGUI is a Python graphical user interface (GUI) written with PyQT5, that allows users to configure settings and start the oobabooga web user interface (WebUI). It provides a convenient way to adjust various parameters and launch the WebUI with the desired settings.
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SaaSHub
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TavernAI-extras
Discontinued Extensions API for SillyTavern [Moved to: https://github.com/Cohee1207/SillyTavern-extras]
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SaaSHub
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long_term_memory reviews and mentions
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Looking for the long-term memory extension.
what you're probably thinking of is this: https://github.com/wawawario2/long_term_memory
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Instruct Models not remembering previous responses?
I do believe there are some proposed solutions in order to retain memories such as LTM or Long Term Memory. I think there are some extensions for ooba's webui that implements that. see: https://github.com/wawawario2/long_term_memory
- Long-term memory (LTM) extension for oobabooga's Text Generation Web UI
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I just made an easy GUI for changing start Parameters
If I understand correctly, one of the extensions you have enabled as an option for the gui to be able to select is the long_term_memory extension. That extension enables people to store in their conversations with the model into a long-term memory upon the next chat. I didn't know if you had a method that interfaced with that so that you could enable the long-term memory read or not. Here is where it explains how long_term_memory works: https://github.com/wawawario2/long_term_memory
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Is there a way to feed in documents similar to the Llama Index?
I saw [this](https://github.com/wawawario2/long_term_memory) as a possible option, but now that I know about SuperBooga I am now not sure which would be better for my purposes.
- Suggestions for long term memories
- CarterAI's StableVicuna 13B with RHLF training. Now available quantised in GGML and GPTQ.
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Working on long term memories for the AI
I thought about Langchain, but it already does the functionality that we have built in which is.. just feed the context back to the model. What I am aiming to do.. is inject relevant memories with the combined text and mix it with the prompt. So the responses will be very fine tuned to the prompt itself based on the context/and memory! so when you say prompt something and it has a memory.. it will take the memory + prompt and the context of the conversation and give a very fine tuned response. https://github.com/wawawario2/long_term_memory
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Adding Long-Term Memory to Custom LLMs: Let's Tame Vicuna Together!
Is this going to function at all similarly to https://github.com/wawawario2/long_term_memory ?
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Advanced character documentation?
There is the long term memory extension that might assist with this. I found out about it though and haven't gotten it to load successfully yet.. https://github.com/wawawario2/long_term_memory
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Stats
wawawario2/long_term_memory is an open source project licensed under GNU Affero General Public License v3.0 which is an OSI approved license.
The primary programming language of long_term_memory is Python.
Popular Comparisons
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