Initialize local AI platform project

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Brandon Wolfgang 2026-10-21 16:57:52 -05:00
commit ed9259d35e
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# Dependencies
node_modules/
# Build output
dist/
build/
coverage/
*.tsbuildinfo
# Environment variables and secrets
.env
.env.*
!.env.example
!.env.test.example
# Logs
logs/
*.log
npm-debug.log*
yarn-debug.log*
pnpm-debug.log*
# Test and tool caches
.nyc_output/
.eslintcache
.cache/
.parcel-cache/
# Local editor settings
.vscode/
.idea/
*.swp
*.swo
.DS_Store
# Local databases and generated data
data/
*.sqlite
*.sqlite3
*.db
# Temporary files
tmp/
temp/

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MIT License
Copyright (c) 2026 Brandon Wolfgang
Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:
The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.

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# Local AI Platform
A self-hosted AI application designed to demonstrate production-grade backend engineering, local LLM integration, retrieval-augmented generation (RAG), observability, security, and reliability.
The project emphasizes measurable behavior, reproducible deployments, automated testing, and documented architectural trade-offs.
## Project Goals
- Build and expose a well-defined API for local LLM inference.
- Integrate retrieval-augmented generation with source-grounded responses.
- Measure latency, throughput, errors, and retrieval quality.
- Implement structured logging, metrics, and distributed tracing.
- Apply authentication, authorization, input validation, and secure configuration.
- Test failure handling, retries, idempotency, and recovery.
- Automate testing and deployment.
- Document architectural decisions and operational procedures.
## Technology Stack
Planned technologies:
- **Runtime:** Node.js
- **Language:** TypeScript
- **API framework:** Fastify
- **Validation:** Zod
- **Local inference:** Ollama
- **Database and retrieval:** PostgreSQL with pgvector
- **Containers:** Docker and Docker Compose
- **Testing:** Automated unit, integration, and failure-injection tests
- **Observability:** OpenTelemetry and compatible monitoring tools
- **CI/CD:** Automated build, test, and deployment workflows
Technologies will be introduced incrementally as project requirements justify them.
## Current Status
**Status:** Initial development
The initial milestone is to establish a working API with health and readiness endpoints, then integrate local model inference and baseline performance measurements.
Features listed in the project goals are planned capabilities, not claims that they have already been implemented.
## Getting Started
### Prerequisites
- Node.js and npm
- Git
Additional dependencies, including Ollama and PostgreSQL, will be introduced as the project evolves.
### Installation
Clone the repository:
```bash
git clone <repository-url>
cd local-ai-platform
```
Install dependencies:
```bash
npm ci
```
### Development
The development server and available scripts will be documented here as they are implemented.
## Architecture
The initial architecture will consist of an HTTP API and a local model inference service.
Subsequent iterations will introduce retrieval, persistence, observability, security controls, and deployment automation.
Architecture diagrams and significant design decisions will be maintained alongside the code.
## Testing and Quality
The project will progressively introduce:
- Automated unit and integration tests
- API contract validation
- Performance benchmarks
- Retrieval and answer-quality evaluations
- Security regression tests
- Failure-recovery tests
Performance and quality claims will be backed by reproducible measurements.
## Security
- Never commit credentials, access tokens, private keys, or production data.
- Keep local configuration and secrets outside version control.
- Validate untrusted input and enforce authorization at the API boundary.
- Treat retrieved documents and model-generated output as untrusted.
- Do not expose the API publicly without appropriate authentication and security controls.
Report suspected vulnerabilities privately to the repository owner.
## Documentation
As the project develops, documentation will cover:
- Local setup and deployment
- Architecture decision records
- Performance and evaluation results
- Threat models and security controls
- Operational runbooks and recovery procedures
- Known limitations and future improvements
## License
[MIT License](LICENSE)

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{
"name": "local-ai-platform",
"version": "1.0.0",
"description": "",
"main": "index.js",
"scripts": {
"test": "echo \"Error: no test specified\" && exit 1",
"dev": "tsx watch src/server.ts",
"build": "tsc -p tsconfig.json",
"start": "node dist/server.js"
},
"keywords": [],
"author": "",
"license": "ISC",
"type": "module",
"dependencies": {
"fastify": "^5.12.7",
"zod": "^4.6.7"
},
"devDependencies": {
"@types/node": "^26.6.5",
"tsx": "^4.23.15",
"typescript": "^7.0.2"
}
}

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import Fastify from 'fastify';
const app = Fastify({
logger: true,
});
app.get('/health', async () => ({
status: 'ok',
}));
app.get('/ready', async () => ({
status: 'ready',
dependencies: {
ollama: 'not-integrated',
},
}));
const start = async () => {
try {
await app.listen({
host: '127.0.0.1',
port: 3000,
});
} catch (error) {
app.log.error(error);
process.exit(1);
}
};
void start();

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{
"compilerOptions": {
"target": "ES2022",
"module": "NodeNext",
"moduleResolution": "NodeNext",
"rootDir": "src",
"outDir": "dist",
"strict": true,
"esModuleInterop": true,
"skipLibCheck": true
},
"include": ["src/**/*.ts"]
}