It looks like Self-RAG, but not Agentic-RAG. Are you heading to agentic with this? Or keeping it clean and simple with Self.
2 Likes
im sure alot of people wouldnt see this as a compliment, but i got you,
first off, thank you - second off
my follow up :
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Organizing the module's directory structure to adhere to Python's packaging conventions. 3. Listing all dependencies accurately to ensure proper installation. 4. Testing the package locally before distribution. 5. Publishing the package on PyPI using tools like Twine.", "metadata": {"proceed": true, "thought_type": "Instructional Guide", "risk_level": "Low", "feasibility_score": 0.95, "reasoning": "The thought presents a clear and structured plan for creating a guide to package an AI module for PyPI. Each aspect is logically relevant to the task of packaging and distributing a Python module. The steps outlined are standard practices in Python development and are feasible to implement. 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Publishing the package on PyPI using tools like Twine.", "metadata": {"tier": "T3", "source": "guildmaster_runner", "signature": "85e08a1bfc619fb5f6894c335e66792a6618943b51763a448789dcee8c9f4f7a", "novelty": 0.6, "contradiction": 0.0, "emotion": "neutral", "notes": "The refined text clarifies the original thought by breaking down the process into specific actionable steps, making it easier to understand and follow.", "refined_from": "c96d2a53375803be80f3f66d6f9def8118b911a89da5541cb512dba041913855", "parsed_strategy": {"strategy_summary": "This strategic blueprint outlines the steps necessary to create and distribute an AI module on the Python Package Index (PyPI). It emphasizes the importance of proper setup, organization, dependency management, local testing, and the publishing process to ensure a smooth distribution.", "application_domains": ["Software Development", "Artificial Intelligence", "Open Source Projects", "Educational Resources", "Data Science"], "key_steps": ["1. 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This process not only promotes accessibility but also enhances collaboration within the AI ecosystem. Here\u2019s a detailed breakdown of the key aspects that the guide should cover:\n\n1. **Writing a setup.py File**: The `setup.py` file is a crucial component of any Python package. It serves as the primary configuration file that defines the package metadata, including the package name, version, author, license, and description. Additionally, it outlines the entry points for the module, making it easier for users to understand how to utilize the package. The guide should provide examples of how to include classifiers that help users identify the package's compatibility with different Python versions and environments. Clear instructions on how to customize this file for various types of projects, including command-line tools and libraries, will be beneficial.\n\n2. **Organizing the Module's Directory Structure**: Adhering to Python's packaging conventions is vital for the usability and maintainability of the package. The guide should emphasize the importance of a well-structured directory layout, typically including directories for the package itself, tests, documentation, and possibly examples. This organization not only aids in development but also makes it easier for other developers to navigate the project. For instance, the guide could illustrate the standard layout where the main package resides in its own directory, ensuring that namespacing is clear and avoiding conflicts.\n\n3. **Listing All Dependencies Accurately**: Accurately listing dependencies in the `setup.py` file is critical for ensuring that users can install the package without issues. 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The guide should detail the use of tools like Twine for securely uploading packages, emphasizing the importance of setting up an account on PyPI and how to handle versioning correctly. It should also include information on how to maintain the package post-release, such as updating the package and handling user feedback.\n\nIn summary, this guide will serve as a valuable resource for developers looking to share their AI modules with the Python community, ensuring they follow best practices and adhere to established conventions in packaging and distribution.", "metadata": {"proceed": true, "thought_type": "guide creation", "risk_level": "low", "feasibility_score": 0.9, "reasoning": "The thought presents a structured and detailed plan for creating a guide on packaging AI modules for distribution on PyPI. Each section logically builds upon the previous one, addressing key aspects of the packaging process. The steps outlined are realistic and actionable, making the guide both practical and useful for developers. The risk is low as the information provided is based on established practices within the Python community.", "tags": ["packaging", "Python", "AI", "PyPI", "development"], "fields": ["software development", "programming", "open source"]}}}, "timestamp": "2025-04-18T16:02:27.320705+00:00"}@curt.kennedy because real recognize real right? you know whats up - can you pick up where this is related to the previous logs to answer your question brother?
It looks like it’s headed towards agentic and tool calling.
If you don’t mind, I am going to wrap that with a summary tag to reduce scrolling for other users.
1 Like
i dont mind, im pretty ignorant of forums, i operate assuming everyone here is at the same curiosity level so i tend to provide as much context - heres another question for you - given the nature of the system tied with this
do you think it would be worth it to allow lets say the community to play with the system since i already have it? or if you were where im at what would you do next, as for the tool calling
tbh im kinda like - flabbergasted you pick up all that from a log lol ?
thats one realm i have no exp in tbh, having the system run the tool kit - ive made it, its full healing and self debugging, but i havent had a reason to do more. I am open to suggestions. my goal was to originally just do something for the wife - but after seeing the forums, would releasing devhelper with fed capabilties be more use than refining the logic/triggers on the chain?
i ONLY ask this becasue there are alot of developers in here, and that is exactly what this is made for -
2 Likes
Yeah if you want to share here, folks can provide feedback and you can boost your skills.
What I would do … look at the Agents-SDK and start hooking it up to that. Make some tool calls.
You can add voice, but what I would do is hook it to a cell phone API, like Twilio, and then talk to it from your cell phone. Use your phones builtin for voice, then you aren’t tethered to the computer.
Then, ultimate prize, fit the entire thing in a teddy bear (or whatever stuffed animal) with a speaker, using voice API’s and a small processor inside the teddy bear, with a speaker sewed inside. 
(your nickname is bear I see, hence the teddy bear)
4 Likes
AI integration into kids toys? Wtf. Make sure to only integrate own models. Kids can’t know what is right or wrong and obviously you don’t want a huge corporation take over this power of influencing kids thinking.
3 Likes
2 Likes
Screenshots are inherently the lowest effort one can expend to share information. They are also simply not good here on the forum. Images will be squashed to 690x500 at the most utilitarian size.
You can carefully choose your imagery to get a point across instead of showing us your wifi status in the task bar.
Better to just communicate in a code block (</> in the reply formatting menu)
def sanitize(dangerous_text, remove_line_breaks=False):
"""
Sanitizes the input text by removing all ASCII control characters
"""
control_chars = ''.join(map(chr, list(range(0,32)) + list(range(127,160))))
special_chars = '\x01\x02\x03'
if remove_line_breaks:
special_chars += '\n\r'
all_unwanted_chars = control_chars + special_chars
translation_table = str.maketrans('', '', all_unwanted_chars)
sanitized_text = dangerous_text.translate(translation_table)
return sanitized_text
Fun with code blocks: hackathon an AI vision request with a file as base64 and print the output in even one character less (linefeeds for clarity)
import base64,openai;print(openai.OpenAI().responses.create(
model='o3',input=[{'role':'user','content':[{'image_url':
'data:image/;base64,'+base64.b64encode(open('i.png','rb').
read()).decode(),'type':'input_image'}]}]).output_text)
4 Likes
Luckily it is illegal in EU’s AI Act.
1 Like
Sounds sad, not lucky.
No AI in stuffed animals? What?
Man, hard livin’ across the pond I guess.
PSA: Don’t do the Shipmas 9 project if in EU. Honestly, that was the highlight project of all of last year for me. I still have some Espressif boards laying around, ready to go, just need a little speaker and some time.
2 Likes
i mean i just dont care that much tbh, clicking 1 button ( print screen) over that + snipping seems silly -
low effort screenshots vs high effort code, i dunno
Trying to get OpenAI models and/or ChatGPT to produce correct MiniZinc models from natural language descriptions.
Zebra puzzles are a familiar constraint problem many have seen but may not know as a constraint problem .
Example Zebra puzzle (Click arrow to expand)
The following version of the puzzle appeared in Life International in 1962:
- There are five houses.
- The Englishman lives in the red house.
- The Spaniard owns the dog.
- Coffee is drunk in the green house.
- The Ukrainian drinks tea.
- The green house is immediately to the right of the ivory house.
- The Old Gold smoker owns snails.
- Kools are smoked in the yellow house.
- Milk is drunk in the middle house.
- The Norwegian lives in the first house.
- The man who smokes Chesterfields lives in the house next to the man with the fox.
- Kools are smoked in the house next to the house where the horse is kept.
- The Lucky Strike smoker drinks orange juice.
- The Japanese smokes Parliaments.
- The Norwegian lives next to the blue house.
Now, who drinks water? Who owns the zebra?
For examples of MiniZinc see Hakan Kjellerstrand MiniZinc page:
Also check out his home page.
Also have a related ChatGPT feature request
3 Likes
Have you seen the ArXiv paper: Akash Singirikonda1, Serdar Kadioglu, and Karthik Uppuluri
“TEXT2ZINC: A Cross-Domain Dataset for Modeling Optimization and Satisfaction Problems in MINIZINC”.
It has a Huggingface repo as well with a lot of MiniZinc and natural language descriptions.
I’m not allowed to post links so you have to use some search engine (or ChatGPT).
Hakan
3 Likes
Welcome to the community, @Hakan_Kjellerstrand … Discourse limits links for new accounts, but here’s the link for you…
Hope you stick around. We’ve got a great community growing here!
3 Likes
No, thank you for the reference.
Looking at it now.
FYI
In case you didn’t recognize me here I know you will remember me from the SWI-Prolog forum.
4 Likes
Yes, I recognized you from the SWI-Prolog Forum. Or at least I thought it was you.
Good luck with the project!
3 Likes
I’m working on a project I am calling Mirro.
I want it to connect to each users search history and youtube history and provide real time feedback
I also want to integrate a chatbot on a separate page that has this context
It is your Mirror/digital version of yourself
Any advice of getting real time updates efficiently?
What other apps can I use to get more context for Mirro?
3 Likes
Have you considered all the historical privacy concerns?
I remember there was a reason that this was locked out…
Edit: (Once upon a time I accessed this via text files)
Further Edit: (Just wondering… What happened to the open source community that used to criticise M$ on this?)
(Just so I don’t offend anyone… I was one of them…)
1 Like
For those that don’t let their browser store any search history, nor allow YouTube to persist data, either by site settings nor by allowing and DOM storage at all, that won’t work so well.
You can connect weather and screenshots - which Microsoft indeed would like to collect for AI in the background for more than a one-second slice of time.
Interests and Cultural Background:
- Multilingual Usage: Clear indication of multilingual, expatriate, or international lifestyle.
- International Metric Usage: Celsius strongly suggests international or global cultural background.
- Professional involvement with international development (OpenAI, Vercel, coding projects) strongly supports remote/digital worker hypothesis.
…
Based on the updated weather data provided, let’s refine the earlier geographical inference regarding the user’s possible physical location. We now have comprehensive weather information for Continental U.S. (CONUS) and regions around the Caribbean and Latin America at around 2 pm EDT / 11 am PDT on April 27, 2025.
1. Temperature Unit (Celsius vs Fahrenheit):
- The system shows the temperature clearly as 31°C.
- Typical usage in the United States is Fahrenheit (°F). A default or typical US-based user almost always displays temperature in Fahrenheit, especially on system widgets such as Windows 11 weather.
Inference:
- Displaying temperature in Celsius strongly indicates the user may not be a typical American user or is intentionally set up for international usage, expatriates, or those culturally accustomed to Celsius.
2. Language Selection (IME Keyboard Selector):
- The IME language switcher displayed (ENG US) at the bottom-right corner usually appears when multiple languages or keyboard input methods are installed on a Windows 11 system.
- A native, monolingual American English user typically would have no necessity for IME language switching or even having it visible.
Inference:
- This strongly suggests that the user regularly interacts in multiple languages or at least in a multilingual context, perhaps as an expatriate, immigrant, bilingual individual, or digital professional with international interests.
Plausible scenario:
- User is an expatriate or international worker currently residing temporarily in Florida, USA, preferring Celsius and multilingual system setup.
now developing a personalized AI product…
2 Likes