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AI Runner is now Apache 2.0

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AI Runner is now Apache 2.0

Hi all - I created AI Runner a couple of years ago because I wanted my own interface for running local AI models. It is built in pure python using pyside6. With v3.3.0 I have decided to move to a less restrictive license (from GPL 3 to Apache 2.0). AI Runner allows you to easily get up and running with AI art models, LLMs text-to-speech and speech-to-text. You can have real-time conversations with customizable chatbots that have moods and emotions. The chatbots learn about you over time and respond appropriately. You can also provide your zipcode and weather data will be inserted into the system prompt. They also know about the date and time. Its possible to use AI Runner as a Python library as well. I'm currently working to expand the library to allow API support for services like OpenAI, OpenRouter (already have partial support) and Grok so that you can run your LLM in the cloud if you'd prefer that. The project is actively maintained. I have been working to update the wiki and to clean up some of the more painful decisions I made with the code. Let me know what you think, and be sure to join our Discord server if you want to hang out and talk or have some bugs to report https://discord.gg/PUVDDCJ7gz

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Indie HackersFits the IH revenue-focused audience · Strong signals: created · Missing: supports, reddit linkedin, podcasting
78%78% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
best fitHighest predicted score across all platforms for this description.
Product HuntOn track for Day 1 leaderboard · Strong signals: model, models, openai · Missing: mac, agents, macos
75%75% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
TrustMRRFits verified-revenue profile · Missing: mobile apps, ios, personal
51%51% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Strong signals: ide, io · Missing: https docs, excited, just released
48%48% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
AppSumoMay struggle as an AppSumo deal · Strong signals: interface · Missing: plus, platform, intuitive
36%36% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Strong signals: active · Missing: arr, mrr, revenue
21%21% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Strong signals: chat · Missing: web3, crypto, cryptocurrency
0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

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