https://github.com/lamia-lang/lamia-cloud
Run Lamia scripts on GCP with one-shot --remote execution, Cloud Run Jobs scheduling, Cloud Triggers and Vertex AI integration for secure serverless automation. You don't need to start from scratch for you uses cases!
https://github.com/lamia-lang/lamia-cloud
ai-agent automation cloud-scheduler llm serverless vertex-ai workflow-automation
Last synced: about 11 hours ago
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Run Lamia scripts on GCP with one-shot --remote execution, Cloud Run Jobs scheduling, Cloud Triggers and Vertex AI integration for secure serverless automation. You don't need to start from scratch for you uses cases!
- Host: GitHub
- URL: https://github.com/lamia-lang/lamia-cloud
- Owner: lamia-lang
- License: mit
- Created: 2026-06-07T18:31:27.000Z (about 1 month ago)
- Default Branch: main
- Last Pushed: 2026-06-28T20:18:10.000Z (11 days ago)
- Last Synced: 2026-06-28T21:12:45.900Z (11 days ago)
- Topics: ai-agent, automation, cloud-scheduler, llm, serverless, vertex-ai, workflow-automation
- Language: Python
- Homepage: https://lamia-lang.github.io/lamia/
- Size: 71.3 KB
- Stars: 0
- Watchers: 0
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# lamia-cloud
Cloud execution backend for [Lamia](https://github.com/lamia-lang/lamia). Run `.lm` scripts once with `--remote`, deploy scheduled cloud jobs, and prepare for upcoming cloud trigger support. Currently supports GCP.
For common agent use cases, you usually do not need to build custom cloud-agent infrastructure from scratch before shipping with Lamia.
## Installation
```bash
pip install "lamia-lang[cloud]"
```
## Prerequisites
- GCP project with billing enabled
- Application Default Credentials: `gcloud auth application-default login`
All required GCP APIs (including Service Usage) are enabled automatically on first deploy.
## Quick Start
1. Add a `cloud` section to your project's `config.yaml`:
```yaml
cloud:
provider: gcp
project_id: my-gcp-project
location: us-central1 # optional, default: us-central1
```
2. Run a script once in the cloud with `--remote`:
```bash
lamia my_script.lm --remote
```
Use this one-shot run to validate cloud execution, permissions, and logs before adding a schedule.
3. Schedule your script with the `--remote` flag:
```bash
lamia schedule add my_script.lm --every day --remote
```
The `--remote` flag tells lamia to deploy and run the script in the cloud instead of locally.
## Managing Schedules
```bash
lamia schedule list # shows all jobs (local + cloud) with live status
lamia schedule add X --remote # deploy and schedule a new cloud job
lamia schedule remove # tears down cloud resources and removes the job
```
## How It Works
1. `lamia .lm --remote` packages your project and runs it as a Cloud Run Job (one-shot)
2. `lamia schedule add <script>.lm --remote` deploys the same cloud job with Cloud Scheduler
3. Cloud Scheduler triggers the job on your cron schedule
4. Logs are available in Cloud Logging
5. `lamia schedule list` fetches live execution status from the cloud
## LLM on Cloud — Vertex AI
Scripts that use LLM calls run through **Vertex AI** on cloud. This gives you:
- **No API keys** — authentication via IAM, no keys to store, rotate, or leak
- **Budget control** — Vertex AI quotas and billing alerts
- **Secure by default** — no API key transport or storage, traffic stays within GCP
### Supported Models
| Provider | Cloud routing |
|----------|--------------|
| **Anthropic** (Claude) | Runs natively on Vertex AI — same models, same quality |
| **Google** (Gemini) | Runs natively on Vertex AI |
| **OpenAI** (GPT, o-series) | Automatically mapped to Gemini by tier (strong/medium/light) with runtime selection of the best available current Gemini model |
Anthropic and Google models run as-is. OpenAI models are mapped because they're not available on Vertex AI — tier classification is stable while the selected Gemini model is discovered dynamically at runtime.
## Configuration Reference
| Field | Required | Default | Description |
|-------|----------|---------|-------------|
| `cloud.provider` | Yes | — | Cloud provider (currently `gcp`) |
| `cloud.project_id` | Yes | — | Your GCP project ID |
| `cloud.location` | No | `us-central1` | Region for Cloud Run deployment |
No environment variables are required.
## Troubleshooting
- If Vertex AI access is not enabled yet, lamia-cloud logs a project-specific URL and attempts to open it automatically in your browser:
`https://console.cloud.google.com/vertex-ai?project=<your-project-id>`
- After accepting terms, re-run the schedule/install command once.
## Development
```bash
git clone https://github.com/lamia-lang/lamia-cloud.git
cd lamia-cloud
pip install -e ".[dev]"
pytest
```
## Releasing
```bash
git tag v0.1.0
git push origin v0.1.0
```