GirlfriendGPT
guidance
GirlfriendGPT | guidance | |
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18 | 89 | |
2,545 | 12,248 | |
- | - | |
7.9 | 9.5 | |
about 1 month ago | 9 months ago | |
Python | Jupyter Notebook | |
- | MIT License |
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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
guidance
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Guidance: A guidance language for controlling large language models
This IS Microsoft Guidance, they seem to have spun off a separate GitHub organization for it.
https://github.com/microsoft/guidance redirects to https://github.com/guidance-ai/guidance now.
- LangChain Agent Simulation – Multi-Player Dungeons and Dragons
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Llama: Add Grammar-Based Sampling
... and it sets the value of "armor" to "leather" so that you can use that value later in your code if you wish to. Guidance is pretty powerful, but I find the grammar hard to work with. I think the idea of being able to upload a bit of code or a context-free grammar to guide the model is super smart.
https://github.com/microsoft/guidance/blob/d2c5e3cbb730e337b...
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Introducing TypeChat from Microsoft
Here's one thing I don't get.
Why all the rigamarole of hoping you get a valid response, adding last-mile validators to detect invalid responses, trying to beg the model to pretty please give me the syntax I'm asking for...
...when you can guarantee a valid JSON syntax by only sampling tokens that are valid? Instead of greedily picking the highest-scoring token every time, you select the highest-scoring token that conforms to the requested format.
This is what Guidance does already, also from Microsoft: https://github.com/microsoft/guidance
But OpenAI apparently does not expose the full scores of all tokens, it only exposes the highest-scoring token. Which is so odd, because if you run models locally, using Guidance is trivial, and you can guarantee your json is correct every time. It's faster to generate, too!
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Accessing Llama 2 from the command-line with the LLM-replicate plugin
Perhaps something as simple as stating it was first built around OpenAI models and later expanded to local via plugins?
I've been meaning to ask you, have you seen/used MS Guidance[0] 'language' at all? I don't know if it's the right abstraction to interface as a plugin with what you've got in llm cli but there's a lot about Guidance that seems incredibly useful to local inference [token healing and acceleration especially].
[0]https://github.com/microsoft/guidance
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AutoChain, lightweight and testable alternative to LangChain
LangChain is just too much, personal solutions are great, until you need to compare metrics or methodologies of prompt generation. Then the onus is on these n-parties who are sharing their resources to ensure that all of them used the same templates, they were generated the same way, with the only diff being the models these prompts were run on.
So maybe a simpler library like Microsoft's Guidance (https://github.com/microsoft/guidance)? It does this really well.
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Structured Output from LLMs (Without Reprompting!)
I am unclear on the status of the project but here is the conversation that seem to be tracking it: https://github.com/microsoft/guidance/discussions/201
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/r/guidance is now a subreddit for Guidance, Microsoft's template language for controlling language models!
Let's have a subreddit about Guidance!
- Is there a UI that can limit LLM tokens to a preset list?
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Any suggestions for an open source model for parsing real estate listings?
You should look at guidance for an LLM to fill out a template. Define the output data structure and provide the real estate listing in the context (see the JSON template example here https://github.com/microsoft/guidance)
What are some alternatives?
SillyTavern - LLM Frontend for Power Users.
semantic-kernel - Integrate cutting-edge LLM technology quickly and easily into your apps
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%
lmql - A language for constraint-guided and efficient LLM programming.
gorilla - Gorilla: An API store for LLMs
langchain - ⚡ Building applications with LLMs through composability ⚡ [Moved to: https://github.com/langchain-ai/langchain]
ggml - Tensor library for machine learning
NeMo-Guardrails - NeMo Guardrails is an open-source toolkit for easily adding programmable guardrails to LLM-based conversational systems.
gptqlora - GPTQLoRA: Efficient Finetuning of Quantized LLMs with GPTQ
llama-cpp-python - Python bindings for llama.cpp
DB-GPT - AI Native Data App Development framework with AWEL(Agentic Workflow Expression Language) and Agents
langchainrb - Build LLM-powered applications in Ruby