SaaS Metrics
StartupHakk/OpenMonoAgent.ai
(BETA) AI shouldn't have a meter. Unlimited tokens. Forever. Your machine. Your agent. Use it from anywhere. Terminal-native coding agent powered by local LLMs — 100% open source, free forever, and installed with a single command. Proudly built on C#/.NET, because AI tooling should be infrastructure, not a subscription.
View Origin LinkProduct Positioning & Context
AI Executive Synthesis
Extending the 'local LLM, free forever, infrastructure-not-subscription' ethos to practical, real-world applications like smart home automation. The project aims to empower users to build complex AI systems on their own machines without recurring costs, positioning itself as foundational AI infrastructure for personal projects.
This issue reveals significant user demand for practical, accessible applications of local LLMs, specifically for autonomous home automation with audible interaction. The user's inability to implement this without clear guidance highlights a critical gap in developer experience for less knowledgeable users. The market implication is a strong desire for 'infrastructure-level' AI tools that provide clear, step-by-step implementation paths for complex, real-world use cases. Products that democratize advanced AI capabilities by simplifying deployment and integration for non-expert users will capture a substantial market segment. This reinforces the value proposition of open-source, locally-run AI as a foundation for personalized, cost-free automation, provided the learning curve is manageable. The 'submit button' issue also points to basic UX friction.
(BETA) AI shouldn't have a meter. Unlimited tokens. Forever. Your machine. Your agent. Use it from anywhere. Terminal-native coding agent powered by local LLMs — 100% open source, free forever, and installed with a single command. Proudly built on C#/.NET, because AI tooling should be infrastructure, not a subscription.
Related Ecosystem & Alternatives
Discover adjacent products, open-source repositories, and developer tools sharing similar technical architecture.
Deep-Dive FAQs
What is StartupHakk/OpenMonoAgent.ai?
StartupHakk/OpenMonoAgent.ai is analyzed by our AI as: Extending the 'local LLM, free forever, infrastructure-not-subscription' ethos to practical, real-world applications like smart home automation. The project aims to empower users to build complex AI systems on their own machines without recurring costs, positioning itself as foundational AI infrastructure for personal projects.. It focuses on This issue reveals significant user demand for practical, accessible applications of local LLMs, specifically for autonomous home automation with a...
Where did StartupHakk/OpenMonoAgent.ai originate?
Data for StartupHakk/OpenMonoAgent.ai was aggregated directly from the GitHub Open Source community ecosystem, representing raw developer and early-adopter sentiment.
When was StartupHakk/OpenMonoAgent.ai publicly launched?
The initial public indexing or launch date for StartupHakk/OpenMonoAgent.ai within our tracked developer communities was recorded on April 30, 2026.
How popular is StartupHakk/OpenMonoAgent.ai?
StartupHakk/OpenMonoAgent.ai has achieved measurable traction, logging over 946 traction score and facilitating 107 recorded discussions or engagements.
Are there active development issues for StartupHakk/OpenMonoAgent.ai?
Yes, we are currently tracking open architectural debates and bug reports for this project on GitHub. There are currently 5 active high-priority issues logged recently.
Are there open-source alternatives related to StartupHakk/OpenMonoAgent.ai?
Yes, the GitHub ecosystem contains correlated projects. For example, a repository named THU-MAIC/OpenMAIC shares highly similar architectural descriptions and topics.
How does the creator describe StartupHakk/OpenMonoAgent.ai?
The original author or development team describes the product as follows: "(BETA) AI shouldn't have a meter. Unlimited tokens. Forever. Your machine. Your agent. Use it from anywhere. Terminal-native coding agent powered by local LLMs — 100% open source, free forever, and..."
Active Developer Issues (GitHub)
Logged: May 10, 2026
Logged: May 7, 2026
Logged: May 7, 2026
Logged: May 7, 2026
Logged: May 6, 2026
Community Voice & Feedback
We now currently have other features in the roadmap because of which Fedora support would not be a priority at the moment.
I've opened a PR to add Fedora support - [#66 ](url).
It adds `dnf`/RPM branches to the install scripts alongside the existing apt path, #using dnf5-compatible syntax so it works on Fedora 41+. The Ubuntu path is untouched.
I've got it running end-to-end on Fedora 44 — full GPU install plus the agent running against a local llama-server (on a 12 GB card it auto-selects the Qwen3.5-9B model). Tested config:
- **OS:** Fedora Linux 44 · kernel 7.0.9-205.fc44 · dnf5
- **GPU:** NVIDIA GeForce RTX 3060 (12 GB)
- **CPU / RAM:** AMD Ryzen 7 5800X (16 threads) · 32 GB
- ASUS board · Wayland / KDE Plasma 6.6.5
**To try it before the PR merges:**
git clone https://github.com/TheAmericanMaker/OpenMonoAgent.ai/tree/feat/fedora-dnf-support
cd OpenMonoAgent.ai
run "./openmono setup"
Happy to help troubleshoot if anyone has an issue. Also happy to be a Fedora guinea pig for future releases.
-James
It adds `dnf`/RPM branches to the install scripts alongside the existing apt path, #using dnf5-compatible syntax so it works on Fedora 41+. The Ubuntu path is untouched.
I've got it running end-to-end on Fedora 44 — full GPU install plus the agent running against a local llama-server (on a 12 GB card it auto-selects the Qwen3.5-9B model). Tested config:
- **OS:** Fedora Linux 44 · kernel 7.0.9-205.fc44 · dnf5
- **GPU:** NVIDIA GeForce RTX 3060 (12 GB)
- **CPU / RAM:** AMD Ryzen 7 5800X (16 threads) · 32 GB
- ASUS board · Wayland / KDE Plasma 6.6.5
**To try it before the PR merges:**
git clone https://github.com/TheAmericanMaker/OpenMonoAgent.ai/tree/feat/fedora-dnf-support
cd OpenMonoAgent.ai
run "./openmono setup"
Happy to help troubleshoot if anyone has an issue. Also happy to be a Fedora guinea pig for future releases.
-James
Confirming the scripts don't work on Fedora, and another user who'd love to try this project out; it seems to be exactly what I am looking for to run a local LLM and finally put the hardware I have to good work besides playing the occasion video game.
````
bash-5.3$ bash
````
bash-5.3$ bash
Second the huge utility of being able to highlight-copy text directly generated by the agent.
Ubuntu: 24.04.4 LTS (Noble Numbat)
Kernel: 6.17.0-23-generic
Kernel: 6.17.0-23-generic
@twcook - What version of ubuntu?
The original Issue was filed on a bare metal Ubuntu install. It still fails: [7/8] Building Docker images
ℹ Stopping any running containers...
ℹ Building llama-server image...
ℹ Building agent image...
✗ agent build failed
─── Last 30 log lines ───
23 | >>> RUN apt-get update && apt-get install -y --no-install-recommends \
24 | >>> git \
25 | >>> ripgrep \
26 | >>> curl \
27 | >>> jq \
28 | >>> tree \
29 | >>> python3 \
30 | >>> python3-pip \
31 | >>> && rm -rf /var/lib/apt/lists/*
32 |
--------------------
failed to solve: failed to compute cache key: failed to copy: httpReadSeeker: failed open: failed to do request: Get "https://mcr.microsoft.com/v2/dotnet/sdk/blobs/sha256:dcd84378ed84993ddac0c043e57d52784ffd0d79ae6ddce9f8e27d30bee9a037": read tcp [2603:6010:aa03:c6b:9b6c:5ef2:6292:b1de]:35238->[2603:1061:f:1...
ℹ Stopping any running containers...
ℹ Building llama-server image...
ℹ Building agent image...
✗ agent build failed
─── Last 30 log lines ───
23 | >>> RUN apt-get update && apt-get install -y --no-install-recommends \
24 | >>> git \
25 | >>> ripgrep \
26 | >>> curl \
27 | >>> jq \
28 | >>> tree \
29 | >>> python3 \
30 | >>> python3-pip \
31 | >>> && rm -rf /var/lib/apt/lists/*
32 |
--------------------
failed to solve: failed to compute cache key: failed to copy: httpReadSeeker: failed open: failed to do request: Get "https://mcr.microsoft.com/v2/dotnet/sdk/blobs/sha256:dcd84378ed84993ddac0c043e57d52784ffd0d79ae6ddce9f8e27d30bee9a037": read tcp [2603:6010:aa03:c6b:9b6c:5ef2:6292:b1de]:35238->[2603:1061:f:1...
dual-boot to Linux - you will thank me later. Windows is a terrible resource hog. Dual-boot to linux and you will truly get almost double the performance on the same hardware.
@rcraig12 - have you tried using it to reference files at a path? Remember that these are working in a docker / sandbox - so you have to reference inside the working directory. We can take a look as well.
We should do this, but I honestly haven't installed Fedora in almost a decade ... In theory ... it *should* work .... But IDK if any of the scripts are setup for it as we have done everything Debian so far ....
I believe we have this resolved - I think a MR is coming tomorrow to fix this.
We are working on improving it. Copy and Paste in the CLI is going to be tricky. We are working on a VC Code plugin - that should help a ton.
@pablo7913 @xerudro - pull down the latest. We have added dedicated support and it works great. The accuracy is a bit lower than a 24GB VRAM GPU, the CPUs we support that have 32GB VRAM. Pull down the latest.
Hello,
Previously, the system required 24GB VRAM minimum, which caused llama-server issues on 12GB and 16GB GPUs (like restart loops during model loading and health check failing).
**Exciting update!** We have now improved the install script with better hardware detection and handling. It no longer assumes a fixed setup and will now prompt you to choose the appropriate GPU mode/model tier when VRAM is detected, making installs more reliable across different systems.
We’ve also added dedicated support for 12GB–16GB GPUs (RTX 3060, 4060 Ti, 4080, etc.) with optimized models and loading strategies. While these won’t match 24GB+ GPU performance (3090/4090/5090 class), they’ve been tested and are now stable and usable with correct configuration.
Would love for you to try the latest version and share feedback!
Previously, the system required 24GB VRAM minimum, which caused llama-server issues on 12GB and 16GB GPUs (like restart loops during model loading and health check failing).
**Exciting update!** We have now improved the install script with better hardware detection and handling. It no longer assumes a fixed setup and will now prompt you to choose the appropriate GPU mode/model tier when VRAM is detected, making installs more reliable across different systems.
We’ve also added dedicated support for 12GB–16GB GPUs (RTX 3060, 4060 Ti, 4080, etc.) with optimized models and loading strategies. While these won’t match 24GB+ GPU performance (3090/4090/5090 class), they’ve been tested and are now stable and usable with correct configuration.
Would love for you to try the latest version and share feedback!
I have the exact same problem. Wanted to run `bash
Discovery Source
GitHub Open Source Aggregated via automated community intelligence tracking.
Tech Stack Dependencies
No direct open-source NPM package mentions detected in the product documentation.
Media Tractions & Mentions
No mainstream media stories specifically mentioning this product name have been intercepted yet.
Deep Research & Science
No direct peer-reviewed scientific literature matched with this product's architecture.