# Management consultancies: form collection using Django

## Summary

A form collection blueprint for management consultancies built with Django on Ample. Domain schema: client_entities (name, industry, primary_contact_role): client organizations; engagements (client_entity_id, scope_title, phase, period_start, period_end): engagement periods and phases; workstreams (engagement_id, name, owner, status, due_at): tracked workstreams; deliverables (engagement_id, title, version, object_key, released_at): versioned deliverables shared with the client; uploads (id, owner_reference, object_key, content_type, size, uploaded_at): validated uploads linked to their owner. Public information: service offerings and case studies (anonymized), consultant profiles, engagement model. Kept out of scope until handling is reviewed: client strategy documents, financial models, interview notes. Client strategy material is confidential; authorization is modeled per engagement and no compliance claim is made. Technical basis verified on Django: content-type and size validation that rejects disallowed files, an object written to a private bucket and a row linking the record to the object key (reject=ok upload=ok linked=ok).

## Infrastructure 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.)
- S3-compatible object storage: verified (Buckets are S3-compatible with issued credentials; PutObject and GetObject are verified by canary. Other S3 operations are not verified.)

## Prerequisites

- A Django project (pip install into .ample/python from requirements.txt, then waitress serving project.wsgi from run.py reading PORT on the python-3.12 template)
- A PostgreSQL driver reading DATABASE_URL (auto-provisioned when omitted)
- Bucket credentials from `ample bucket create` passed as encrypted S3_* environment variables
- A review of which management consultancies data classes may be handled at all; this blueprint models public information only

## Steps

1. **Model the management consultancies domain.** Create the tables client_entities, engagements, workstreams, deliverables, uploads. Client organizations lives in client_entities; keep the sensitive classes (client strategy documents, financial models, interview notes) out of this schema.
2. **Workflow step 1.** Model document requests per engagement with due dates and status
3. **Workflow step 2.** Validate uploaded files (type, size) before storing them in the private bucket and linking them to the request
4. **Workflow step 3.** Authorize uploads by client entity
5. **Workflow step 4.** Deploy and verify rejection of disallowed files and a linked upload
6. **Deploy.** Run the synchronous deploy once and read the result. Re-running with no change is a no-op.
   
   ```
   ample deploy . --name <app-name> --public --start "python3 run.py" --env S3_ENDPOINT=... --env S3_REGION=... --env S3_BUCKET=... --env S3_ACCESS_KEY_ID=... --env S3_SECRET_ACCESS_KEY=...
   ```
7. **Verify.** Run the pattern self-test(s) from the example (/p/browser-file-uploads) and your own acceptance checks for the management consultancies workflow.
   
   ```
   ample logs <deployment_id> --kind build
   ```

## Tested examples

- **Django pattern fixture** (tests/deploy-canaries/django-patterns): Verified browser file uploads basis for this blueprint.

## Success checks

- app responds on its public URL (`/` on the live URL, expect ample canary django patterns)
- browser-file-uploads self-test from the example (`/p/browser-file-uploads` on the live URL, expect see the pattern fixture checks)

## Limitations

- The technical basis (browser file uploads on Django) was verified with the pattern fixture; the management consultancies schema and workflow are an original design for this blueprint and were not executed as a separate application.
- No health, financial, privacy or other compliance claim is made. Client strategy material is confidential; authorization is modeled per engagement and no compliance claim is made.
- Public content and synthetic examples only until actual data-handling requirements have been reviewed.
- Verified on the python-3.12 template at s-1vcpu-1gb; region, request-duration limits and other sizes are unknown or unverified.
- Managed PostgreSQL 16 only; extensions, connection limits and backup or restore procedures are not verified.
- PutObject and GetObject with path-style addressing are verified; other S3 operations and CDN cache rules are not.