V3 Updated V3 core documents. Added data folder backup/restore before/after running destructive tests.

docs/schema_v3.md

@@ -1,6 +1,6 @@
 # Database Schema (Version 3)
 
-This document describes the relational schema for the transcription platform. It incorporates multi-image batch orchestration, page-level execution tracking, many-to-many author/recipient attribution, input prompt provenance capture, and raw API payload evidence for archival auditing.
+This document describes the relational schema for the transcription platform. It incorporates multi-image batch orchestration, page-level execution tracking, many-to-many author/recipient attribution, submission-time prompt snapshot capture, and raw API payload evidence for archival auditing.
 
 The schema uses generic JSON columns compatible with SQLite in local development and PostgreSQL native JSONB/UUID types in production.
 
@@ -54,6 +54,12 @@ JOB {
     INTEGER retry_count
     TEXT provider
     TEXT model
+    TEXT prompt_name
+    TEXT prompt_hash
+    TEXT system_prompt
+    TEXT user_prompt
+    FLOAT temperature
+    FLOAT top_p
     TIMESTAMPTZ date_created
     TIMESTAMPTZ date_updated
 }
@@ -79,12 +85,6 @@ JOB_SOURCE {
     UUID source_id FK
     VARCHAR status "pending | transcribed | failed"
     TEXT raw_transcription
-    TEXT prompt_name
-    TEXT prompt_hash
-    TEXT system_prompt
-    TEXT user_prompt
-    FLOAT temperature
-    FLOAT top_p
     JSONB ai_metadata
     JSONB raw_api_response
     TEXT error_detail
@@ -104,7 +104,7 @@ SOURCE ||--o{ JOB_SOURCE : "processed_in"
 ### Page-Level Execution & AI Outputs
 
 * **Execution Granularity:** Every single image execution attempt by an AI model produces a dedicated record in `job_source`.
-* **Page-Level Input Provenance:** Every `job_source` execution captures its exact hyperparameters (`temperature`, `top_p`), prompt identifier details (`prompt_name`, `prompt_hash`), and full prompt text strings (`system_prompt`, `user_prompt`) used for that specific page call.
+* **Submission Snapshot Provenance:** Every `job` captures the frozen prompt identifier details (`prompt_name`, `prompt_hash`), full prompt text strings (`system_prompt`, `user_prompt`), and hyperparameters (`temperature`, `top_p`) at submission time.
 * **Point-in-Time Output Auditability:** `job_source.raw_api_response` stores the complete, unedited provider REST response envelope for that specific image page call. `job_source.ai_metadata` stores spatial bounding boxes, normalized token usage, latency, and cost details for fast querying.
 * **Active Output Caching:** Upon successful completion of an image call, `source.raw_transcription` is updated with the latest output string from `job_source.raw_transcription` for fast UI rendering.