## Host knowledge base with Flask: Postgres-backed content

### Summary
Deploy a knowledge base built with Flask on Ample using the relational records pattern. Compute runs the app in an isolated microVM behind a public HTTPS URL, a managed PostgreSQL 16 database is auto-provisioned and injected as DATABASE_URL, and a published bucket serves public assets from the CDN host. Verified on Flask: a workspace-scoped table, an explicit state machine (draft to review to published) that rejects invalid transitions, and a cross-workspace read that returns nothing (transitions=true isolation=true). Not separately tested: your record schema, states and access rules; treat the knowledge base-specific behavior as your application code.

### Framework and Workload
- **Framework**: Flask
- **Workload**: Knowledge base

### Resource Requirements
- **Compute**:  Verified, apps run in isolated x86_64 Firecracker microVMs that auto-pause when idle and wake on request; sizes are the priced VM sizes.
- **Postgres**: Verified, managed PostgreSQL 16 runs in its own microVM and is auto-provisioned when an app needs a database and no DATABASE_URL is supplied.
- **CDN**: Verified, the CDN host serves objects from published buckets.

### Execution Status
- **Release Status**: published
- **Support Status**: verified
- **Execution Status**: ready

### Prerequisites
1. A Flask project that builds and starts with the documented commands (pip install into .ample/python from requirements.txt, then waitress from app.py reading PORT on the python-3.12 template).
2. A PostgreSQL driver reading DATABASE_URL at runtime (auto-provisioned when omitted, or supplied with --env).
3. A bucket from `ample bucket create` with its credentials passed as encrypted S3_* environment variables.
4. An Ample account token with servers:write, databases:read, buckets:read.

### Tested Configuration
- **Template**: python-3.12
- **Runtime**: python
- **Size**: s-1vcpu-1gb
- **Install**: `python3 -m pip install --target .ample/python -r requirements.txt`
- **Start**: `PYTHONPATH=.ample/python:${PYTHONPATH:-} python3 app.py`

### Workflow Steps
1. **Build and start**: pip install into .ample/python from requirements.txt, then waitress from app.py reading PORT on the python-3.12 template.
2. **Implement the pattern on PostgreSQL**: Copy the approach into your schema; keep migrations idempotent and run them with --release-command.
3. **Wire object storage**: Create the bucket(s), then pass endpoint, region, bucket and keys as --env values.
4. **Deploy**: Run the synchronous deploy once and read the result.
5. **Verify**: Fetch the live URL and the pattern self-test route(s) from the example; then run your own checks.

### Examples
- **Flask pattern fixture**: Multi-pattern Flask app whose relational records module was checked live.

### Success Checks
1. App responds on its public URL.
2. Relational-records self-test.

### Limitations
- Verified on the python-3.12 template; other sizes and templates are not verified.
- The knowledge base behavior is application code and was not separately tested.
- Managed PostgreSQL 16 only; connection limits and backup procedures are not verified.

### Cost Estimate
- **Currency**: USD
- **Monthly Amount**: 10.0
- **Components**:
  - App server (s-1vcpu-1gb): $5.00
  - Managed PostgreSQL database (s-1vcpu-1gb): $5.00
- Note: Always-on monthly price of the tested sizes; apps and databases auto-pause when idle.

### Next Actions
- Browse the catalog index
- Search published recipes by intent, stack and constraints
- Prepare a side-effect-free deployment plan for an authorized project
- Read the existing agent authentication setup
- Browse Knowledge base
- Browse Flask
- Browse Relational records
- Browse Deploy web app

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**Note**: Ensure you handle all deployment according to the specifics outlined in the workflow steps.