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license: apache-2.0
language:
- en
pipeline_tag: text-generation
tags:
- on-device
- local-llm
- coding-copilot
- ai-assistant
- code-generation
- pocketpal
- llm
- nlp
---
# AppBuilder — On-Device Coding Copilot & Local AI Assistant
AppBuilder is a lightweight, on-device **text-generation** LLM designed to run locally on your machine or mobile device — similar to [PocketPal AI](https://github.com/a-ghorbani/pocketpal-ai). It acts as a personal coding copilot and app-building assistant that works entirely offline, with no cloud dependency. Give it a natural language prompt and it returns structured code, project scaffolding, or step-by-step build instructions — all on-device.
> **Think PocketPal, but focused on building apps.** AppBuilder is optimized for developers who want a fast, private, always-available assistant that runs on CPU/GPU without sending data to external servers.
## Model Details
### Model Description
AppBuilder is a fine-tuned LLM for on-device assistant and coding copilot tasks. It understands developer intent from plain English and generates functional application code, API integrations, config files, and project structures across multiple frameworks — all locally.
- **Developed by:** codemeacoffee
- **Model type:** Text Generation / On-Device LLM / Coding Copilot
- **Language(s):** English
- **License:** Apache 2.0
- **Repository:** codemeacoffee/appbuilder
- **Inspired by:** PocketPal AI (local LLM assistant approach)
## Uses
### Direct Use
AppBuilder can be used directly as a local assistant to:
- Generate application boilerplate code from plain English descriptions
- Scaffold new projects (FastAPI, Next.js, Express, Flutter, etc.)
- Generate configuration files (Docker, CI/CD, .env, etc.)
- Answer developer questions and explain code — fully offline
- Act as a PocketPal-style chat assistant for coding tasks
### Downstream Use
Can be integrated or fine-tuned for:
- PocketPal AI / llama.cpp compatible on-device deployments
- IDE plugins and offline coding assistants
- Mobile AI apps (Android/iOS via NCNN, llama.cpp, MLC)
- Automated development pipelines and no-code platforms
### Out-of-Scope Use
- Generating malicious or harmful code
- Unauthorized system access or exploits
- Production-critical code without human review
## How to Get Started with the Model
### Option 1: Run locally via Transformers
```python
from transformers import pipeline
generator = pipeline("text-generation", model="codemeacoffee/appbuilder")
result = generator("Build a FastAPI endpoint that returns a list of users")
print(result[0]["generated_text"])
```
### Option 2: Run on-device via llama.cpp (PocketPal style)
```bash
# Convert to GGUF and run locally
./main -m appbuilder.gguf -p "Build a FastAPI endpoint that returns a list of users" -n 512
```
### Option 3: Load in PocketPal AI App
1. Export the model to GGUF format
2. Load into [PocketPal AI](https://github.com/a-ghorbani/pocketpal-ai) on Android/iOS
3. Chat with your local coding copilot — no internet required
## Training Details
### Training Data
Trained on a curated dataset of open-source code repositories, API documentation, developer forums, and application scaffolding patterns across popular frameworks.
### Training Procedure
- **Training regime:** Mixed precision (fp16)
- **Framework:** PyTorch / HuggingFace Transformers
- **Optimization target:** On-device inference speed + instruction following
## Evaluation
### Testing Data & Metrics
Evaluated on code generation benchmarks including HumanEval and custom application-building tasks measuring:
- Functional correctness
- Code quality and style
- Framework-specific accuracy
- On-device response latency
## Environmental Impact
- **Hardware used:** NVIDIA A100 GPUs (training) / CPU + mobile GPU (inference target)
- **Cloud Provider:** Google Cloud Platform
- **On-device target:** Runs on consumer hardware (4GB+ RAM, any modern CPU/GPU)
## Citation
```bibtex
@misc{appbuilder2026,
author = {codemeacoffee},
title = {AppBuilder: On-Device Coding Copilot and Local AI Assistant},
year = {2026},
publisher = {HuggingFace},
url = {https://huggingface.co/codemeacoffee/appbuilder}
}
```
## Model Card Contact
For questions or contributions, open an issue in the model repository or reach out via the HuggingFace community page. |