page:recipes:knowledge base:flask:relational content

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

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