promptr
AutoGPT
promptr | AutoGPT | |
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16 | 180 | |
883 | 161,878 | |
- | 1.0% | |
8.4 | 9.9 | |
2 months ago | 5 days ago | |
JavaScript | JavaScript | |
MIT License | MIT License |
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promptr
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Ask HN: What are some actual use cases of AI Agents?
I taught https://github.com/KillianLucas/open-interpreter how to use https://github.com/ferrislucas/promptr
Then I asked it to add a test suite to a rails side project. It created missing factories, corrected a broken test database configuration, and wrote tests for the classes and controllers that I asked it to.
I didn't have to get involved with mundane details. I did have to intervene here and there, but not much. The tests aren't the best in the world, but IMO they're adding value by at least covering the happy path. They're not as good as an experienced person would write.
I did spend a non-trivial amount of time fiddling with the prompts I used to teach OI about Promptr as well as the prompts I used to get it to successfully create the test suite.
The total cost was around $11 using GPT4 turbo.
I think in this case it was a fun experiment. I think in the future, this type of tooling will be ubiquitous.
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Ask HN: What apps have you created for your own use?
I made a CLI tool called Promptr that allows you to make changes to a codebase via plain English instructions:
https://github.com/ferrislucas/promptr
There’s a templating system (liquidjs) included which is useful if you have a library of prompts that you want to reference often.
You can think of it as a junior engineer that needs explicit instructions.
Here are a few example PR’s implemented by Promptr - see the commits for the prompt that was used to produce the code:
https://github.com/ferrislucas/promptr/pull/38
https://github.com/ferrislucas/promptr/pull/41
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Another Major Outage Across ChatGPT and API
https://github.com/ferrislucas/promptr
You just prompt it directly or with a file, and it applies the changes to your file system. There's also a templating system that allows you to reference other files from your prompt file if you want to have a shared prompt file that contains project conventions etc.
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ReactAgent: LLM Agent for React Coding
This is exactly the use that Promptr is intended for https://github.com/ferrislucas/promptr
* full disclosure: I’m the author of Promptr
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Ask HN: How do you use AI to get things done faster?
I’ve been experimenting with pairing a tool I wrote called Promptr [1] with another tool called Open Interpreter [2].
I start with a prompt that teaches Open Interpreter how to use Promptr, and then I discuss what I’m trying to accomplish. It’s certainly not perfect, but there’s definitely something good that happens when you can iterate using dialog with a robot that can modify your file system and execute commands locally.
[1] Promptr: https://github.com/ferrislucas/promptr
[2] Open Interpreter: https://github.com/KillianLucas/open-interpreter
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Coders Can Survive–and Thrive–In a ChatGPT World
I wrote a great tool for this: https://github.com/ferrislucas/promptr
It’s great for making changes to existing code because it automatically includes the relevant files for context.
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ChatGPT Changed How I Write Software
For those looking for specific examples of useful code being authored by AI, you can check out this tool:
https://github.com/ferrislucas/promptr
The README links to example PR’s comprised of commits written by GPT4. The prompts used to produce the code are noted in the commit messages.
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Ask HN: What's your favorite GPT powered tool?
Promptr is a coding assistant tool that allows you to ask GPT to produce or modify code, and the results will be automatically applied to your file system.
https://github.com/ferrislucas/promptr
From the README:
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Any recommended tools for accessing codebases?
I'm also interested in this problem. It can be theoretically solved by giving GPT long-term memory about a specific codebase through vector embedding generation (using OpenAI's embeddings API). The semantic embeddings can then be stored in a vector (or vector-supported) database such as Pinecone alongside metadata for querying. Some of the key considerations are how to compare vectors for similarity (there are many algorithms) and how to use metadata to better support your use case. The following resources can be helpful to further understand this technique: - https://platform.openai.com/docs/guides/embeddings - https://www.mlq.ai/fine-tuning-gpt-3-question-answer-bot/ - https://www.pinecone.io/learn/javascript-chatbot/ A couple of semi-related projects I've been looking into: - https://github.com/ferrislucas/promptr - https://github.com/pashpashpash/vault-ai
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5-Apr-2023
Promptr is a CLI tool for operating on your codebase using GPT. (https://github.com/ferrislucas/promptr)
AutoGPT
- Accessible AI for Everyone
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AGI has, in some sense, been achieved: Tell me why I am wrong
Define agency. Does AutoGPT or BabyAGI fit the definition?
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The Emergence of Autonomous Agents
This leap is evident in projects like BabyAGI and AutoGPT, showcasing how such agents can prioritize and execute tasks based on a pre-defined objective and the results of previous actions, such as sales prospecting or ordering pizza.
- An experimental open-source attempt to make GPT-4 autonomous
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[Long read] Deep dive into AutoGPT: A comprehensive and in-depth step-by-step guide to how it works
A system and a user message are constructed from the task given by the user in code and passed to the LLM as input.
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1000 Member Celebration and FAQ
A: How much do you know? If you can easily read code (in this example Python, but this will still benefit anyone who can read code), you should check out Auto-GPT. If you are looking to explore different options, check out this doc on AI Agents.
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Agents: An Open-source Framework for Autonomous Language Agents - AIWaves Inc 2023
Also I think most agents I have seen have implemented some form of long-short term memory. Why does it say autogpt doesnt support it? https://github.com/Significant-Gravitas/Auto-GPT/tree/master/autogpts/autogpt/autogpt/memory
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MetaGPT: The Next Evolution or Just More Hype?
In my newest experiment, I try out MetaGPT, which is supposed to be better than AutoGPT according to MetaGPT's paper.
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List of Awesome AI Agents like AutoGPT and BabyAGI / Many open-source Agents with code included!
In my opinion the most interesting Agents: Auto-GPT Github: https://github.com/Significant-Gravitas/Auto-GPT BabyAGI Github: https://github.com/yoheinakajima/babyagi Voyager Github: https://github.com/MineDojo/Voyager / Paper: https://arxiv.org/abs/2305.16291 I would also add: ChemCrow: Augmenting large-language models with chemistry tools Github: https://github.com/ur-whitelab/chemcrow-public/ Paper: https://arxiv.org/abs/2304.05376
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We've released Auto-GPT v0.4.5!
Check out the new Re-Arch README and ARCHITECTURE_NOTES.
What are some alternatives?
vault-ai - OP Vault ChatGPT: Give ChatGPT long-term memory using the OP Stack (OpenAI + Pinecone Vector Database). Upload your own custom knowledge base files (PDF, txt, epub, etc) using a simple React frontend.
langchain - ⚡ Building applications with LLMs through composability ⚡ [Moved to: https://github.com/langchain-ai/langchain]
lmql - A language for constraint-guided and efficient LLM programming.
gpt4all - gpt4all: run open-source LLMs anywhere
gish - GPT command line
llama.cpp - LLM inference in C/C++
plz-cli - Copilot for your terminal
Auto-Vicuna
ChatIDE - AI Coding Assistant in your IDE - ChatGPT (OpenAI) and Claude (Anthropic) in a VSCode extension.
JARVIS - JARVIS, a system to connect LLMs with ML community. Paper: https://arxiv.org/pdf/2303.17580.pdf
SuperAGI - <⚡️> SuperAGI - A dev-first open source autonomous AI agent framework. Enabling developers to build, manage & run useful autonomous agents quickly and reliably.