SuperAGI
GirlfriendGPT
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SuperAGI | GirlfriendGPT | |
---|---|---|
82 | 18 | |
14,442 | 2,540 | |
- | - | |
9.9 | 7.9 | |
18 days ago | about 1 month ago | |
Python | Python | |
MIT License | - |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
SuperAGI
- Introducing GPTs
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🐍🐍 23 issues to grow yourself as an exceptional open-source Python expert 🧑💻 🥇
Repo : https://github.com/TransformerOptimus/SuperAGI
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Introduction to Agent Summary – Improving Agent Output by Using LTS & STM
The recent introduction of the “Agent Summary” feature in SuperAGI version 0.0.10 has brought a drastic difference in agent performance – improving the quality of agent output. Agent Summary helps AI agents maintain a larger context about their goals while executing complex tasks that require longer conversations (iterations).
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🚀✨SuperAGI v0.0.10✨is now live on GitHub
Checkout the full release here: https://github.com/TransformerOptimus/SuperAGI/releases/tag/v0.0.10
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Top 20 Must Try AI Tools for Developers in 2023
10. SuperAGI
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We're bringing in Google 's PaLM2 🦬 Bison LLM API support into SuperAGI in our upcoming v0.0.8 release
Currently, PaLM2 Bison is live on the dev branch of SuperAGI GitHub for the community to try: https://github.com/TransformerOptimus/SuperAGI/tree/dev
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Why use SuperAGI
SuperAGI is made with developers in mind, therefore it takes into account their requirements and preferences when making autonomous AI agents. It has a number of advantages, including:
- In five years, there will be no programmers left, believes Stability AI CEO
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LLM Powered Autonomous Agents
I think for agents to truly find adoption in real world, agent trajectory fine tuning is critical component - how do you make an agent perform better to achieve particular objective with every subsequent run. Basically making the agents learn similar to how we learn when we
Also I think current LLMs might not fit well for agent use cases in mid to long term because the RL they go through is based on input-best output methods whereas the intelligence that you need in agents is more around how to build an algorithm to achieve an objective on the fly - this requires perhaps new type of large models ( Large Agent Models ? ) which are trained using RLfD ( Reinforcement Learning from demonstration )
Also I think one of the key missing piece is a highly configurable software middle ware between Intelligence ( LLMs ), Memory ( Vector Dbs ~LTMs, STMs ), Tools and workflows across every iteration. Current agent core loop to find next best action is too simplistic. For example if core self prompting loop or iteration of an agent can be configured for the use case in hand. Eg for BabyAGI, every iteration goes through workflow of Plan, Prioritize and Execute or in AutoGPT it finds the next best action based on LTM/STM, or GPTEngineer it is to write specs > write tests > write code. Now for dev infra monitoring agent this workflow might be totally different - it would look like consume logs from different tools like Grafana, Splunk, APMs > See if it doesnt have an anomaly > if it has an anomaly then take human input for feedback. Every use case in real world has it's own workflow and current construct of agent frameworks have this thing hard coded in base prompt. In SuperAGI( https://superagi.com) ( disclaimer : Im creator of it ), core iteration workflow of agent can be defined as part of agent provisioning.
Another missing piece is notion of Knowledge. Agents currently depend entirely upon knowledge of LLMs or search results to execute on tasks, but if a specialised knowledge set is plugged to an agent, it performs significantly better.
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Created a simple chrome dino game using SuperAGI's SuperCoder 😵 The dino changes color on every run :P (without writing a single line of code myself)
Build your own game here: https://github.com/TransformerOptimus/SuperAGI
GirlfriendGPT
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The gatekeepers trying to silence uncensored AI
While Poe from Quora is extempted from stripe restricted businesses, startups like GirlfriendGPT get bullied! The functionality of both AI chat engines is the same.
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Tutorials???
Geeesh I’m kinda new to this whole coding, making your own GPT type stuff lol and if you ask me so far so good I can definitely follow along and plug in codes and prompts just to make your basic chatbot lol. But! Now I’m trying to make the GirlfriendGpt & I’ve found the code/template on GitHub https://github.com/EniasCailliau/GirlfriendGPT only thing is I don’t know how to code it without watching someone on YouTube walk me through the steps. Is there anyone or anyway I can get this coded to create the AI girlfriend I want????
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🤖💟 An open-source AI tool to create a virtual partner right from your description
BTW, here is the service:)))
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Create your virtual partner with this open-source AI tool!
💻 Check GitHub to see the service. Would be glad to see your results! Maybe I’ll test it in the future, too:))
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(2/2) May 2023
Girlfriend GPT is a Python project to build your own AI girlfriend using ChatGPT4.0 (https://github.com/EniasCailliau/GirlfriendGPT)
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Thinking about creating an animated AI chatbot with Ryan Cohen where Apes pay $1 per minute to chat with their dad
Some guy has already made GirlfriendGPT, which allows you to define a personality, and it can also send you AI generated selfies. You could probably define an RC personality and host this things in the AWS free tier.
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Artificial intelligence could lead to extinction, experts warn
Here you go: https://github.com/EniasCailliau/GirlfriendGPT
- [P] GirlfriendGPT - build your own AI girlfriend
- [D] GirlfriendGPT - Your personal AI companion
What are some alternatives?
AutoGPT - AutoGPT is the vision of accessible AI for everyone, to use and to build on. Our mission is to provide the tools, so that you can focus on what matters.
SillyTavern - LLM Frontend for Power Users.
Auto-GPT - An experimental open-source attempt to make GPT-4 fully autonomous. [Moved to: https://github.com/Significant-Gravitas/AutoGPT]
tree-of-thoughts - Plug in and Play Implementation of Tree of Thoughts: Deliberate Problem Solving with Large Language Models that Elevates Model Reasoning by atleast 70%
autogen - A programming framework for agentic AI. Discord: https://aka.ms/autogen-dc. Roadmap: https://aka.ms/autogen-roadmap
gorilla - Gorilla: An API store for LLMs
Auto-GPT - An experimental open-source attempt to make GPT-4 fully autonomous. [Moved to: https://github.com/Significant-Gravitas/Auto-GPT]
ggml - Tensor library for machine learning
AgentGPT - 🤖 Assemble, configure, and deploy autonomous AI Agents in your browser.
gptqlora - GPTQLoRA: Efficient Finetuning of Quantized LLMs with GPTQ
AutoLearn-GPT - ChatGPT learns automatically.
DB-GPT - AI Native Data App Development framework with AWEL(Agentic Workflow Expression Language) and Agents